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Appl. Sci., Volume 7, Issue 12 (December 2017) – 127 articles

Cover Story (view full-size image): The Bloch Surface Wave (BSW) is an evanescent electromagnetic mode found on the surface of a Distributed Bragg Reflector multilayer. This surface mode can be used for channeling the emission of fluorescent material. As one intriguing example, when a MoS2 monolayer is deposited on top of a photonic crystal, its emission is channeled into the BSW. The MoS2 radiation can efficiently spread long distances, in the plane of the device, thanks to the high group velocity in evanescent mode. Such a finding paves the way for an on-chip propagation control and manipulation of transition metal dichalcogenide emissions. View this paper
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2540 KiB  
Article
A Bibliometric Study to Assess Bioprinting Evolution
by Adrien Naveau, Rawen Smirani, Sylvain Catros, Hugo De Oliveira, Jean-Christophe Fricain and Raphael Devillard
Appl. Sci. 2017, 7(12), 1331; https://doi.org/10.3390/app7121331 - 20 Dec 2017
Cited by 22 | Viewed by 6969
Abstract
Bioprinting as a tissue engineering tool is one of the most promising technologies for overcoming organ shortage. However, the spread of populist articles among on this technology could potentially lead public opinion to idealize its readiness. This bibliometric study aimed to trace the [...] Read more.
Bioprinting as a tissue engineering tool is one of the most promising technologies for overcoming organ shortage. However, the spread of populist articles among on this technology could potentially lead public opinion to idealize its readiness. This bibliometric study aimed to trace the evolution of bioprinting literature over the past decade (i.e., 2000 to 2015) using the SCI-expanded database of Web of Science® (WoS, Thomson Reuters). The articles were analyzed by combining various bibliometric tools, such as science mapping and topic analysis, and a Technology Readiness Scale was adapted to assess the evolution of this emerging field. The number of analyzed publications was low (231), but the literature grew exceptionally fast. The “Engineering, Biomedical” was still the most represented WoS category. Some of the recent fronts were “hydrogels” and “stem cells”, while “in vitro” remained one of the most used keywords. The number of countries and journals involved in bioprinting literature grew substantially in one decade, also supporting the idea of an increasing community. Neither the United States’ leadership in bioprinting productivity nor the role of universities in publications were challenged. “Biofabrication” and “Biomaterials” journals were still the leaders of the bioprinting field. Bioprinting is a young but promising technology. Full article
(This article belongs to the Special Issue Biofabrication: From Additive Bio-Manufacturing to Bioprinting)
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Graphical abstract

Graphical abstract
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<p>Trends of publication productivity in the scientific literature involving “3D printing” and “bioprinting” from 2000 to 2015 (articles and reviews published in English). Overall: scientific literature.</p>
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<p>The science mapping of Web of ScienceTM (WoS) categories for assessing bioprinting evolution in time slices, (<b>a</b>): 2006–2010; (<b>b</b>): 2011–2015. The WoS categories were grouped into “macro-disciplines”: Matter Sciences (yellow), Engineering (blue), Biology (green), and Medicine (red). The size of each node is proportionate to its degree and the thickness of the links represents the tie strength.</p>
Full article ">Figure 3
<p>Temporal evolution of keyword co-occurrence networks between 2006 and 2016 with a time interval of 5 years, (<b>a</b>): 2006–2010; (<b>b</b>): 2011–2015. The size of each node is proportionate to its degree and the thickness of the links represents the tie strength.</p>
Full article ">Figure 4
<p>Distribution of bioprinting original articles according to the bioprinting technology readiness level (BTRL). The 2006–2015 bioprinting articles were analyzed and distributed into 4 groups: 1 (in vitro, BTRL 1–4), 2 (animal-in vivo, BTRL 5), 3 (human-clinical grade, BTRL 6–8) and 4 (industrial, BTRL 9). There has never been any paper in group 4.</p>
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<p>Temporal evolution of the involved organizations. Citation analysis of the organizations between 2006 and 2016 with a time interval of 5 years, (<b>a</b>): 2006–2010; (<b>b</b>): 2011–2015. The size of each node is proportionate to its degree and the thickness of the links represents the tie strength.</p>
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<p>Temporal evolution of the publishing journals. Co-citation analysis of the citations sources between 2006 and 2016 with a time interval of 5 years, (<b>a</b>): 2006–2010; (<b>b</b>): 2011–2015. The size of each node is proportionate to its degree and the thickness of the links represents the tie strength.</p>
Full article ">Figure 6 Cont.
<p>Temporal evolution of the publishing journals. Co-citation analysis of the citations sources between 2006 and 2016 with a time interval of 5 years, (<b>a</b>): 2006–2010; (<b>b</b>): 2011–2015. The size of each node is proportionate to its degree and the thickness of the links represents the tie strength.</p>
Full article ">
3812 KiB  
Article
Production and Characterization of Glass-Ceramic Materials for Potential Use in Dental Applications: Thermal and Mechanical Properties, Microstructure, and In Vitro Bioactivity
by Francesco Baino and Enrica Verné
Appl. Sci. 2017, 7(12), 1330; https://doi.org/10.3390/app7121330 - 20 Dec 2017
Cited by 32 | Viewed by 5544
Abstract
Multicomponent silicate glasses and their corresponding glass-ceramic derivatives were prepared and tested for potential applications in dentistry. The glasses were produced via a melting-quenching process, ground and sieved to obtain fine-grained powders that were pressed in the form of small cylinders and thermally [...] Read more.
Multicomponent silicate glasses and their corresponding glass-ceramic derivatives were prepared and tested for potential applications in dentistry. The glasses were produced via a melting-quenching process, ground and sieved to obtain fine-grained powders that were pressed in the form of small cylinders and thermally treated to obtain sintered glass-ceramic samples. X-ray diffraction investigations were carried out on the materials before and after sintering to detect the presence of crystalline phases. Thermal analyses, mechanical characterizations (assessment of bending strength, Young’s modulus, Vickers hardness, fracture toughness), and in vitro bioactivity tests in simulated body fluid were performed. On the basis of the acquired results, different potential applications in the dental field were discussed for the proposed glass-ceramics. The use of such materials can be suggested for either restorative dentistry or dental implantology, mainly depending on their peculiar bioactive and mechanical properties. At the end of the work, the feasibility of a novel full-ceramic bilayered implant was explored and discussed. This implant, comprising a highly bioactive layer expected to promote osteointegration and another one mimicking the features of tooth enamel, can have an interesting potential for whole tooth substitution. Full article
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Figure 1

Figure 1
<p>Preparation of the bilayered glass-derived samples for potential use in dental implantology: casting of (<b>a</b>) CEL2 powders; and (<b>b</b>) SCNA powders in the mould; (<b>c</b>) 1-D pressing; and (<b>d</b>) extraction from the mould.</p>
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<p>XRD patterns of the as-poured materials: (<b>a</b>) CEL2; (<b>b</b>) FaGC; and (<b>c</b>) SCNA.</p>
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<p>XRD patterns of the sintered materials: (<b>a</b>) TT-CEL2; (<b>b</b>) TT-FaGC; and (<b>c</b>) TT-SCNA.</p>
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<p>In vitro bioactivity tests carried out on TT-CEL2 samples: (<b>a,b</b>) sample surface after soaking for seven days in simulated body fluid (SBF) and (<b>c</b>) corresponding energy dispersive spectroscopy (EDS) pattern.</p>
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<p>XRD pattern of TT-CEL2 after soaking for seven days in SBF.</p>
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<p>In vitro bioactivity tests carried out on TT-FaGC samples: (<b>a</b>) sample surface after soaking for seven days in SBF and (<b>b</b>) corresponding EDS pattern.</p>
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<p>Bilayered glass-ceramic implant: interface between TT-CEL2 and TT-SCNA layers.</p>
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<p>Cross-sections of a bilayered implant after soaking for seven days in SBF: (<b>a</b>) TT-SCNA region and (<b>b</b>) TT-CEL2 region.</p>
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<p>Cross-sections of a bilayered implant after soaking for one month in SBF at different magnifications: (<b>a</b>,<b>c</b>) TT-SCNA region and (<b>b</b>,<b>d</b>) TT-CEL2 region.</p>
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1375 KiB  
Article
Populating the Mix Space: Parametric Methods for Generating Multitrack Audio Mixtures
by Alex Wilson and Bruno M. Fazenda
Appl. Sci. 2017, 7(12), 1329; https://doi.org/10.3390/app7121329 - 20 Dec 2017
Cited by 4 | Viewed by 5695
Abstract
The creation of multitrack mixes by audio engineers is a time-consuming activity and creating high-quality mixes requires a great deal of knowledge and experience. Previous studies on the perception of music mixes have been limited by the relatively small number of human-made mixes [...] Read more.
The creation of multitrack mixes by audio engineers is a time-consuming activity and creating high-quality mixes requires a great deal of knowledge and experience. Previous studies on the perception of music mixes have been limited by the relatively small number of human-made mixes analysed. This paper describes a novel “mix-space”, a parameter space which contains all possible mixes using a finite set of tools, as well as methods for the parametric generation of artificial mixes in this space. Mixes that use track gain, panning and equalisation are considered. This allows statistical methods to be used in the study of music mixing practice, such as Monte Carlo simulations or population-based optimisation methods. Two applications are described: an investigation into the robustness and accuracy of tempo-estimation algorithms and an experiment to estimate distributions of spectral centroid values within sets of mixes. The potential for further work is also described. Full article
(This article belongs to the Special Issue Sound and Music Computing)
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Figure 1

Figure 1
<p>Points <span class="html-italic">p</span>, <math display="inline"> <semantics> <msup> <mi>p</mi> <mo>′</mo> </msup> </semantics> </math> and <span class="html-italic">r</span>, in 2-track gain space. Note that the audio output at points <span class="html-italic">p</span> and <math display="inline"> <semantics> <msup> <mi>p</mi> <mo>′</mo> </msup> </semantics> </math> is the same ‘mix’.</p>
Full article ">Figure 2
<p>Graphical representation of three mixes in mix-space. While shown for three tracks, this is generalisable to any number of tracks <span class="html-italic">n</span>, using hyperspherical coordinates. (a) Mix at a point in 3-track gain space. Note that the audio output at points <span class="html-italic">p</span> and <math display="inline"> <semantics> <msup> <mi>p</mi> <mo>′</mo> </msup> </semantics> </math> is the same ‘mix’, despite the vectors having different lengths in this space; (<b>b</b>) For a 3-track mixture, while the cube (<math display="inline"> <semantics> <msup> <mi mathvariant="double-struck">R</mi> <mn>3</mn> </msup> </semantics> </math>) represents all outputs of a summing mixer, the surface of the sphere (<math display="inline"> <semantics> <msup> <mi mathvariant="double-struck">S</mi> <mn>2</mn> </msup> </semantics> </math>) represents all possible mixes.</p>
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<p>Schematic representation of a four-track mixing task, with track gains <math display="inline"> <semantics> <mrow> <msub> <mi>g</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>g</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>g</mi> <mn>3</mn> </msub> <mo>,</mo> <msub> <mi>g</mi> <mn>4</mn> </msub> </mrow> </semantics> </math>, and the semantic description of the three <math display="inline"> <semantics> <mi>ϕ</mi> </semantics> </math> terms, when adjusted from 0 to <math display="inline"> <semantics> <mrow> <mi>π</mi> <mo>/</mo> <mn>2</mn> </mrow> </semantics> </math>. Figure taken from [<a href="#B7-applsci-07-01329" class="html-bibr">7</a>].</p>
Full article ">Figure 4
<p>A time-varying mix can be considered as a path in the mix-space. Here, a random time-varying mix is generated by means of a random walk. (<b>a</b>) Random walk in mix-space; Brownian motion, halted after 30 s; (<b>b</b>) Random walk from <a href="#applsci-07-01329-f004" class="html-fig">Figure 4</a>a converted to gain-space; (<b>c</b>) Time series of gain values for each of the three tracks.</p>
Full article ">Figure 5
<p>Three sets of mixes, drawn from the mix-space. This shows the effect of varying the concentration parameter <math display="inline"> <semantics> <mi>κ</mi> </semantics> </math>, that a larger value results in less diversity.</p>
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<p>Boxplots of track gains for two generated datasets of mixes, drawn from separate distributions. (<b>a</b>) <math display="inline"> <semantics> <mrow> <mi>μ</mi> <mo>=</mo> </mrow> </semantics> </math> Equation (<a href="#FD7-applsci-07-01329" class="html-disp-formula">7</a>), <math display="inline"> <semantics> <mrow> <mi>κ</mi> <mo>=</mo> <mn>200</mn> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <mi>μ</mi> <mo>=</mo> </mrow> </semantics> </math> Equation (<a href="#FD8-applsci-07-01329" class="html-disp-formula">8</a>), <math display="inline"> <semantics> <mrow> <mi>κ</mi> <mo>=</mo> <mn>200</mn> </mrow> </semantics> </math>.</p>
Full article ">Figure 7
<p>Panning of two tracks, represented as a 1-sphere. The panning mix is determined by the angle <math display="inline"> <semantics> <mi>θ</mi> </semantics> </math> with <math display="inline"> <semantics> <msub> <mi>r</mi> <mi>pan</mi> </msub> </semantics> </math> acting as a scaling variable, adjusting the overall width of the mix. For example, <math display="inline"> <semantics> <msup> <mi>C</mi> <mo>′</mo> </msup> </semantics> </math> is a wider version of <span class="html-italic">C</span>.</p>
Full article ">Figure 8
<p>Panning method 1—separate vMF distributions for <math display="inline"> <semantics> <msub> <mi>gain</mi> <mi>L</mi> </msub> </semantics> </math> and <math display="inline"> <semantics> <msub> <mi>gain</mi> <mi>R</mi> </msub> </semantics> </math>, both using Equation (<a href="#FD7-applsci-07-01329" class="html-disp-formula">7</a>). (<b>a</b>) Boxplot of track gains for left channel, using Equation (<a href="#FD7-applsci-07-01329" class="html-disp-formula">7</a>); (<b>b</b>) Boxplot of track gains for right channel, using Equation (<a href="#FD7-applsci-07-01329" class="html-disp-formula">7</a>); (<b>c</b>) Boxplot of pan positions for each track; (<b>d</b>) Probability density of pan positions for each track.</p>
Full article ">Figure 9
<p>Panning method 1b—separate vMF distributions for left and right channels but using unique <math display="inline"> <semantics> <mi>μ</mi> </semantics> </math> vectors, shown in Equations (<a href="#FD10-applsci-07-01329" class="html-disp-formula">10</a>) and (<a href="#FD11-applsci-07-01329" class="html-disp-formula">11</a>). (<b>a</b>) Boxplot of track gains for left channel, using Equation (<a href="#FD10-applsci-07-01329" class="html-disp-formula">10</a>); (<b>b</b>) Boxplot of track gains for right channel, using Equation (<a href="#FD11-applsci-07-01329" class="html-disp-formula">11</a>); (<b>c</b>) Boxplot of pan positions for each track. Where <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>P</mi> <mo>|</mo> <mo>&gt;</mo> <mn>1</mn> </mrow> </semantics> </math>, this is caused by negative track gains; (<b>d</b>) Probability density of pan positions for each track.</p>
Full article ">Figure 10
<p>Panning method 2—generating vMF distributions in panning space. As expected, increasing <math display="inline"> <semantics> <mi>κ</mi> </semantics> </math> (concentration parameter) results in a narrower range of pan positions for each track, around the target vector Equation (<a href="#FD13-applsci-07-01329" class="html-disp-formula">13</a>).</p>
Full article ">Figure 11
<p>Two random mixes generated using panning method 2, shown as squares and circles. Each mix has a different gain vector (based on Equation (<a href="#FD7-applsci-07-01329" class="html-disp-formula">7</a>) and different pan vector (based on Equation (<a href="#FD13-applsci-07-01329" class="html-disp-formula">13</a>).</p>
Full article ">Figure 12
<p>Five randomly-chosen examples of 3-band equalisation, chosen from the tone-space. As <math display="inline"> <semantics> <mrow> <msub> <mi>ψ</mi> <mn>2</mn> </msub> <mo>→</mo> <mn>0</mn> </mrow> </semantics> </math>, the gain of the high band decreases. As <math display="inline"> <semantics> <mrow> <msub> <mi>ψ</mi> <mn>1</mn> </msub> <mo>→</mo> <mn>0</mn> </mrow> </semantics> </math>, the gain of the low band increases at the expense of the other two bands; their balance is determined by <math display="inline"> <semantics> <msub> <mi>ψ</mi> <mn>2</mn> </msub> </semantics> </math>.</p>
Full article ">Figure 13
<p>Estimated tempo for three songs, 500 mixes each using Equation (<a href="#FD7-applsci-07-01329" class="html-disp-formula">7</a>). In each histogram, the data is split into 100 bins. Overall, performance is better for the metre-based method, as it demonstrates greater accuracy and improved robustness to changes in the mix. (<b>a</b>) “Burning Bridges”—The correct tempo is ≈100 bpm; (<b>b</b>) “I’m Alright”—The correct tempo is ≈96 bpm; (<b>c</b>) “What I Want”—The correct tempo is ≈99 bpm.</p>
Full article ">Figure 14
<p>Estimated tempo for three songs, 500 mixes each using Equation (<a href="#FD8-applsci-07-01329" class="html-disp-formula">8</a>). In each histogram, the data is split into 100 bins. Overall, performance is better for the metre-based method, as it demonstrates greater accuracy and improved robustness to changes in the mix; (<b>a</b>) “Burning Bridges”—The correct tempo is ≈100 bpm; (<b>b</b>) “I’m Alright”—The correct tempo is ≈96 bpm; (<b>c</b>) “What I Want”—The correct tempo is ≈99 bpm.</p>
Full article ">Figure 14 Cont.
<p>Estimated tempo for three songs, 500 mixes each using Equation (<a href="#FD8-applsci-07-01329" class="html-disp-formula">8</a>). In each histogram, the data is split into 100 bins. Overall, performance is better for the metre-based method, as it demonstrates greater accuracy and improved robustness to changes in the mix; (<b>a</b>) “Burning Bridges”—The correct tempo is ≈100 bpm; (<b>b</b>) “I’m Alright”—The correct tempo is ≈96 bpm; (<b>c</b>) “What I Want”—The correct tempo is ≈99 bpm.</p>
Full article ">Figure 15
<p>Probability distribution of spectral centroid as a function of mix-space parameters; (<b>a</b>) “Burning Bridges”; (<b>b</b>) “I’m Alright”; (<b>c</b>) “What I Want”.</p>
Full article ">
11615 KiB  
Article
Virtual Analog Models of the Lockhart and Serge Wavefolders
by Fabián Esqueda, Henri Pöntynen, Julian D. Parker and Stefan Bilbao
Appl. Sci. 2017, 7(12), 1328; https://doi.org/10.3390/app7121328 - 20 Dec 2017
Cited by 22 | Viewed by 9632
Abstract
Wavefolders are a particular class of nonlinear waveshaping circuits, and a staple of the “West Coast” tradition of analog sound synthesis. In this paper, we present analyses of two popular wavefolding circuits—the Lockhart and Serge wavefolders—and show that they achieve a very similar [...] Read more.
Wavefolders are a particular class of nonlinear waveshaping circuits, and a staple of the “West Coast” tradition of analog sound synthesis. In this paper, we present analyses of two popular wavefolding circuits—the Lockhart and Serge wavefolders—and show that they achieve a very similar audio effect. We digitally model the input–output relationship of both circuits using the Lambert-W function, and examine their time- and frequency-domain behavior. To ameliorate the issue of aliasing distortion introduced by the nonlinear nature of wavefolding, we propose the use of the first-order antiderivative method. This method allows us to implement the proposed digital models in real-time without having to resort to high oversampling factors. The practical synthesis usage of both circuits is discussed by considering the case of multiple wavefolder stages arranged in series. Full article
(This article belongs to the Special Issue Sound and Music Computing)
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Figure 1

Figure 1
<p>(<b>a</b>) Simplified schematic of the Lockhart wavefolder circuit (adapted from [<a href="#B53-applsci-07-01328" class="html-bibr">53</a>]); and (<b>b</b>) its Ebers–Moll large-signal equivalent model.</p>
Full article ">Figure 2
<p>Transfer function of the Lockhart wavefolder simulated using: (<b>a</b>) SPICE (Simulation Program with Integrated Circuit Emphasis); and (<b>b</b>) the proposed virtual analog (VA) model. Different colors indicate different values of <math display="inline"> <semantics> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> </semantics> </math>.</p>
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<p>Absolute value of the difference between a SPICE simulation of the Lockhart wavefolder and its proposed VA model.</p>
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<p>Time-domain view of the proposed Lockhart wavefolder model plotted against its SPICE simulation for a 500-Hz sinusoidal input (peak amplitude 1 V) with load resistance: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> k<math display="inline"> <semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics> </math>; and (<b>b</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics> </math> k<math display="inline"> <semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics> </math>.</p>
Full article ">Figure 5
<p>Schematic of a single folding cell in the middle section of the Serge Wave Multipliers (VCM). Figure adapted from [<a href="#B63-applsci-07-01328" class="html-bibr">63</a>].</p>
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<p>Equivalent view of the diode saturator at the non-inverting input of the op-amp in <a href="#applsci-07-01328-f005" class="html-fig">Figure 5</a>.</p>
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<p>(<b>a</b>) Transfer function of a single wavefolding stage in the Serge middle VCM measured using SPICE and the proposed model; and (<b>b</b>) the absolute difference between these two curves.</p>
Full article ">Figure 8
<p>Time-domain view of the Serge wavefolder model plotted against its SPICE simulation for a 500-Hz sinusoidal input with peak amplitude if 1 V.</p>
Full article ">Figure 9
<p>Transfer functions for the proposed Serge and Lockhart (<math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> <mo>=</mo> <mn>7.5</mn> </mrow> </semantics> </math> k<math display="inline"> <semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics> </math>) wavefolder models.</p>
Full article ">Figure 10
<p>Averaged processing times required to compute <math display="inline"> <semantics> <mrow> <mi>W</mi> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> </semantics> </math> using Halley’s method and Fritsch’s iteration.</p>
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<p>Spectrogram of the Lockhart wavefolder under 150-Hz sinusoidal input for values of <math display="inline"> <semantics> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> </semantics> </math> between 1 and 50 k<math display="inline"> <semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics> </math>.</p>
Full article ">Figure 12
<p>Spectogram for a linear sweep from 20 Hz to 5 kHz processed using: (<b>a</b>) the proposed Lockhart wavefolder model (<math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics> </math> k<math display="inline"> <semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics> </math>); and (<b>b</b>) the proposed Serge wavefolder model. A sample rate <math display="inline"> <semantics> <mrow> <msub> <mi>F</mi> <mi mathvariant="normal">s</mi> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics> </math> MHz was used to simulate analog behavior.</p>
Full article ">Figure 13
<p>Spectrogram for a 1 V linear sweep from 20 Hz–5 kHz processed with the proposed Lockhart wavefolder (<math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics> </math> k<math display="inline"> <semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics> </math>) model: (<b>a</b>) at audio rate; (<b>b</b>) using two times oversampling; (<b>c</b>) with antialiasing at audio rate; and (<b>d</b>) with antialiasing and oversampling by two.</p>
Full article ">Figure 14
<p>Spectrogram for a 1 V linear sweep from 20 Hz–5 kHz processed with the proposed Serge wavefolder model: (<b>a</b>) at audio rate; (<b>b</b>) using two times oversampling; (<b>c</b>) with antialiasing at audio rate; and (<b>d</b>) with antialiasing and oversampling by two.</p>
Full article ">Figure 15
<p>Measured A-weighted noise-to-mask ratios (ANMRs) for a range of sinusoidal waveforms processed: (<b>a</b>) using the Lockhart wavefolder model (<math display="inline"> <semantics> <mrow> <msub> <mi>R</mi> <mi mathvariant="normal">L</mi> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics> </math> k<math display="inline"> <semantics> <mi mathvariant="sans-serif">Ω</mi> </semantics> </math>) under six different sampling rates; and (<b>b</b>) using the Serge wavefolder model under two different sampling rates, with and without the proposed antialiasing method. Values below the −10 dB threshold indicate lack of perceivable aliasing.</p>
Full article ">Figure 16
<p>Block diagram representation of the Serge middle VCM. Blocks labeled “SWF” indicate the Serge wavefolder model.</p>
Full article ">Figure 17
<p>(<b>a</b>) Transfer function of the proposed Serge middle VCM; and (<b>b</b>) its output when driven by a 100-Hz sinewave for <math display="inline"> <semantics> <mrow> <msub> <mi>G</mi> <mi mathvariant="normal">S</mi> </msub> <mo>=</mo> <mn>6</mn> </mrow> </semantics> </math> and zero dc offset.</p>
Full article ">Figure 18
<p>Spectrogram of: (<b>a</b>) a 150-Hz sinewave with peak amplitude 1 V processed by the proposed Serge middle VCM with varying gain <math display="inline"> <semantics> <msub> <mi>G</mi> <mi mathvariant="normal">S</mi> </msub> </semantics> </math> from 0–6; and (<b>b</b>) a 200-Hz sinewave processed with varying gain <math display="inline"> <semantics> <msub> <mi>G</mi> <mi mathvariant="normal">S</mi> </msub> </semantics> </math> from 0–3 and dc offset from 0–3 V.</p>
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<p>Block diagram for the proposed VA cascaded Lockhart wavefolder topology. Blocks labeled “LWF” and “LPF” indicate the Lockart wavefolder model and lowpass filtering, respectively.</p>
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<p>(<b>a</b>) Transfer function of the proposed cascaded Lockhart wavefolder structure measured after the post-gain block; and (<b>b</b>) its output when driven by a 100-Hz sinusoidal input for <math display="inline"> <semantics> <mrow> <msub> <mi>G</mi> <mi mathvariant="normal">L</mi> </msub> <mo>=</mo> <mn>10</mn> </mrow> </semantics> </math> and zero dc offset.</p>
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<p>Spectrogram of: (<b>a</b>) a 150-Hz sinewave with peak amplitude 1 V processed by the proposed cascaded Lockhart topology with varying gain <math display="inline"> <semantics> <msub> <mi>G</mi> <mi mathvariant="normal">L</mi> </msub> </semantics> </math> from 0 to15; and (<b>b</b>) a 200-Hz sinewave processed with varying gain <math display="inline"> <semantics> <msub> <mi>G</mi> <mi mathvariant="normal">S</mi> </msub> </semantics> </math> from 0 to 0 and dc offset from 0 to 5 V.</p>
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1624 KiB  
Article
Day-Ahead Dispatch Model of Electro-Thermal Integrated Energy System with Power to Gas Function
by Deyou Yang, Yufei Xi and Guowei Cai
Appl. Sci. 2017, 7(12), 1326; https://doi.org/10.3390/app7121326 - 20 Dec 2017
Cited by 15 | Viewed by 4753
Abstract
The application of power to gas (P2G) provides a new way to absorb intermittent renewable energy generation, which improves the efficiency of renewable energy utilization and provides the necessary flexibility for operating the integrated energy system. The electro-thermal integrated energy system with P2G [...] Read more.
The application of power to gas (P2G) provides a new way to absorb intermittent renewable energy generation, which improves the efficiency of renewable energy utilization and provides the necessary flexibility for operating the integrated energy system. The electro-thermal integrated energy system with P2G is a new form of using energy efficiently. In this paper, we first introduce the technology and application of P2G. On the basis of considering the characteristics of P2G facilities, power systems, natural gas systems and heating systems, an optimal dispatching model of electro-thermal multi-energy system with P2G facilities is proposed. Particle swarm optimization is used to solve the optimal scheduling model. The simulation results are discussed for the six-bus and six-node integration system and show that when the volume fraction of hydrogen does not exceed 20% in the gas network, for the same operating mode, an integrated energy grid with P2G function will save about 20 tons of standard coal per day and the abandoned wind rate can be regarded as 0. Full article
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Figure 1

Figure 1
<p>Diagrams of (<b>a</b>) alkaline electrolyzer, (<b>b</b>) Proton exchange membrane electrolyzer and (<b>c</b>) Solid oxide electrolyzer.</p>
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<p>The architecture diagram of combined power-heat system with power to gas (P2G) function.</p>
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<p>Flowing of solving day-ahead dispatch model with particle swarm optimization (PSO).</p>
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<p>Configuration of the six-bus and six-node integration system.</p>
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<p>Daily profile for wind power, electric and thermal loads.</p>
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<p>Profiles of Mode 1 with P2G: (<b>a</b>) power generation and (<b>b</b>) thermal generation.</p>
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<p>Profiles of Mode 2 with P2G: (<b>a</b>) power generation and (<b>b</b>) thermal generation.</p>
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<p>Standard coal consumption of two modes.</p>
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16070 KiB  
Article
An Accurate Perception Method for Low Contrast Bright Field Microscopy in Heterogeneous Microenvironments
by Keshav Rajasekaran, Ekta Samani, Manasa Bollavaram, John Stewart and Ashis G. Banerjee
Appl. Sci. 2017, 7(12), 1327; https://doi.org/10.3390/app7121327 - 19 Dec 2017
Cited by 5 | Viewed by 4831
Abstract
Automated optical tweezers-based robotic manipulation of microscale objects requires real-time visual perception for estimating the states, i.e., positions and orientations, of the objects. Such visual perception is particularly challenging in heterogeneous environments comprising mixtures of biological and colloidal objects, such as cells and [...] Read more.
Automated optical tweezers-based robotic manipulation of microscale objects requires real-time visual perception for estimating the states, i.e., positions and orientations, of the objects. Such visual perception is particularly challenging in heterogeneous environments comprising mixtures of biological and colloidal objects, such as cells and microspheres, when the popular imaging modality of low contrast bright field microscopy is used. In this paper, we present an accurate method to address this challenge. Our method combines many well-established image processing techniques such as blob detection, histogram equalization, erosion, and dilation with a convolutional neural network in a novel manner. We demonstrate the effectiveness of our processing pipeline in perceiving objects of both regular and irregular shapes in heterogeneous microenvironments of varying compositions. The neural network, in particular, helps in distinguishing the individual microspheres present in dense clusters. Full article
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Graphical abstract

Graphical abstract
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<p>Holographic optical tweezers system.</p>
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<p>Example images of cells and microspheres in different fluid media: (<b>a</b>) amoeba cell and silica beads in water, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mi>j</mi> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) human endothelial cells and silica beads in water, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mi>j</mi> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) human endothelial cells and silica beads in Matrigel, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mi>j</mi> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>d</b>) clustered silica beads in polymerizing Matrigel, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mi>j</mi> <mrow> <mi>c</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Smudge free image of amoeba cell and silica beads in water.</p>
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<p>Histogram equalized bright field images of beads and cells: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>h</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>h</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>h</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Processed bright field images with beads identified: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>b</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>b</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>b</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Architecture of the convolutional neural network used for perceiving the individual beads in clusters.</p>
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<p>Processed bright field images with beads hidden: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>b</mi> <mi>h</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>b</mi> <mi>h</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>b</mi> <mi>h</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Processed bright field images with edges detected: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>e</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>e</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>e</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Dilated bright field images: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>d</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>d</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>d</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Result of floodfill algorithm applied to the dilated bright field images shown in <a href="#applsci-07-01327-f009" class="html-fig">Figure 9</a>: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Result of the addition of dilated image and bitwise NOT on the floodfilled bright field images shown in <a href="#applsci-07-01327-f010" class="html-fig">Figure 10</a>: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> <mi>d</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> <mi>d</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> <mi>d</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Eroded bright field images: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>e</mi> <mi>r</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>e</mi> <mi>r</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>e</mi> <mi>r</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Result of applying floodfill algorithm on the eroded bright field images shown in <a href="#applsci-07-01327-f012" class="html-fig">Figure 12</a>: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> <mi>e</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> <mi>e</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>f</mi> <mi>e</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Silhouettes of the objects on image boundaries obtained by subtracting <a href="#applsci-07-01327-f013" class="html-fig">Figure 13</a> from the eroded bright field images shown in <a href="#applsci-07-01327-f012" class="html-fig">Figure 12</a>: (<b>a</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>s</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>s</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>s</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Fully processed bright field images: (<b>a</b>) amoeba cells and silica beads in water, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>c</mi> </mrow> <mrow> <mi>i</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>b</b>) human endothelial cells and silica beads in water, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>c</mi> </mrow> <mrow> <mi>s</mi> <mi>w</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>c</b>) human endothelial cells and silica beads in Matrigel, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>c</mi> </mrow> <mrow> <mi>s</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>; (<b>d</b>) clustered silica beads in polymerizing Matrigel, <math display="inline"> <semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mi>j</mi> <mi>c</mi> </mrow> <mrow> <mi>c</mi> <mi>m</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </semantics> </math>.</p>
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<p>Microscale object perception method flowchart. CLAHE: contrast limited adaptive histogram equalization.</p>
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<p>Examples of positive training samples for the convolutional neural network.</p>
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<p>Examples of negative training samples for the convolutional neural network.</p>
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<p>Processed images of densely clustered silica beads in Matrigel: (<b>a</b>) single cluster with one bead sightly separated from the rest; (<b>b</b>) multiple clusters; (<b>c</b>) single cluster with all the beads tightly aggregated.</p>
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<p>Processed images of amoeba cells and silica beads in water using various perception methods: (<b>a</b>) Maximally stable extremal regions (MSER) with circularity parameter; (<b>b</b>) Speeded up robust features (SURF); (<b>c</b>) Canny edge detector with Otsu’s thresholding; (<b>d</b>) MSER.</p>
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<p>Processed images of human endothelial cells and silica beads in water using various perception methods: (<b>a</b>) MSER with circularity parameter; (<b>b</b>) SURF; (<b>c</b>) Canny edge detector with Otsu’s thresholding; (<b>d</b>) MSER.</p>
Full article ">Figure 22
<p>Processed images of human endothelial cells and silica beads in Matrigel using various perception methods: (<b>a</b>) MSER with circularity parameter; (<b>b</b>) SURF; (<b>c</b>) Canny edge detector with Otsu’s thresholding; (<b>d</b>) MSER.</p>
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<p>Performance comparison of different perception methods for dicty cells and silica beads in water.</p>
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<p>Performance comparison of different perception methods for human endothelial cells and silica beads in water.</p>
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<p>Performance comparison of different perception methods for human endothelial cells and silica beads in Matrigel.</p>
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<p>Performance comparison of different perception methods for clustered beads in Matrigel.</p>
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2043 KiB  
Article
Fog over Virtualized IoT: New Opportunity for Context-Aware Networked Applications and a Case Study
by Paola G. V. Naranjo, Zahra Pooranian, Shahaboddin Shamshirband, Jemal H. Abawajy and Mauro Conti
Appl. Sci. 2017, 7(12), 1325; https://doi.org/10.3390/app7121325 - 19 Dec 2017
Cited by 28 | Viewed by 5574
Abstract
In this paper, we discuss the most significant application opportunities and outline the challenges in real-time and energy-efficient management of the distributed resources available in mobile devices and at the Internet-to-Data Center. We also present an energy-efficient adaptive scheduler for Vehicular Fog Computing [...] Read more.
In this paper, we discuss the most significant application opportunities and outline the challenges in real-time and energy-efficient management of the distributed resources available in mobile devices and at the Internet-to-Data Center. We also present an energy-efficient adaptive scheduler for Vehicular Fog Computing (VFC) that operates at the edge of a vehicular network, connected to the served Vehicular Clients (VCs) through an Infrastructure-to-Vehicular (I2V) over multiple Foglets (Fls). The scheduler optimizes the energy by leveraging the heterogeneity of Fls, where the Fl provider shapes the system workload by maximizing the task admission rate over data transfer and computation. The presented scheduling algorithm demonstrates that the resulting adaptive scheduler allows scalable and distributed implementation. Full article
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<p>The overall VFC architecture. CDC: Cloud-Data-Center with the main areas; FN: Fog-Node; RSU: Road-Side-Unit; Fl: Foglet; FDC: Fog-Data-Center.</p>
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<p>Trace sample of I/O arrival data from an enterprise cluster in WorldCup98 Workload [1:1000] [<a href="#B26-applsci-07-01325" class="html-bibr">26</a>]. The corresponding average arrival rate and PMR (Peak Mean Rate) are 1.56 and 19.65, respectively.</p>
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<p>FDC structure in the StreamVehicularFog scenario.</p>
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<p>Energy saving of SVF (dashed plot) and energy consumption of SVF (continuous plot) for the Fast Ethernet LAN for <math display="inline"> <semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics> </math>.</p>
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<p>Fast/Giga Ethernet LANs on the energy consumption of SVF for <math display="inline"> <semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>1000</mn> </mrow> </semantics> </math>.</p>
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<p>(<b>a</b>) Behavior time in relation to the number of turned ON VMs and physical servers, and (<b>b</b>) the average total energy in <math display="inline"> <semantics> <mrow> <mi>T</mi> <mo>=</mo> <mn>1000</mn> </mrow> </semantics> </math>, respectively.</p>
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4759 KiB  
Article
Bandwidth Widening of Piezoelectric Cantilever Beam Arrays by Mass-Tip Tuning for Low-Frequency Vibration Energy Harvesting
by Eduard Dechant, Feodor Fedulov, Leonid Y. Fetisov and Mikhail Shamonin
Appl. Sci. 2017, 7(12), 1324; https://doi.org/10.3390/app7121324 - 19 Dec 2017
Cited by 50 | Viewed by 8047
Abstract
Wireless sensor networks usually rely on internal permanent or rechargeable batteries as a power supply, causing high maintenance efforts. An alternative solution is to supply the entire system by harvesting the ambient energy, for example, by transducing ambient vibrations into electric energy by [...] Read more.
Wireless sensor networks usually rely on internal permanent or rechargeable batteries as a power supply, causing high maintenance efforts. An alternative solution is to supply the entire system by harvesting the ambient energy, for example, by transducing ambient vibrations into electric energy by virtue of the piezoelectric effect. The purpose of this paper is to present a simple engineering approach for the bandwidth optimization of vibration energy harvesting systems comprising multiple piezoelectric cantilevers (PECs). The frequency tuning of a particular cantilever is achieved by changing the tip mass. It is shown that the bandwidth enhancement by mass tuning is limited and requires several PECs with close resonance frequencies. At a fixed frequency detuning between subsequent PECs, the achievable bandwidth shows a saturation behavior as a function of the number of cantilevers used. Since the resonance frequency of each PEC is different, the output voltages at a particular excitation frequency have different amplitudes and phases. A simple power-transfer circuit where several PECs with an individual full wave bridge rectifier are connected in parallel allows one to extract the electrical power close to the theoretical maximum excluding the diode losses. The experiments performed on two- and three-PEC arrays show reasonable agreement with simulations and demonstrate that this power-transfer circuit additionally influences the frequency dependence of the harvested electrical power. Full article
(This article belongs to the Special Issue Piezoelectric Energy Harvesting: Materials, Devices and Application)
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<p>The lumped parameter model of a single piezoelectric cantilever (PEC) drawn in LTspice.</p>
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<p>Simulation (sim) of the conventional (con) and adjusted (adj) lumped element model compared to the measurements (meas).</p>
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<p>Mechanical set up with a PEC array.</p>
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<p>Simulated resonance curves of piezoelectric cantilever beam arrays.</p>
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<p>(<b>a</b>) Simulated dependence of the bandwidth on the frequency detuning Δ<span class="html-italic">f</span>; (<b>b</b>) Dependence of the power at the half-power frequencies on the frequency detuning Δ<span class="html-italic">f</span>.</p>
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<p>Simulated bandwidth of the array with large detuning ∆<span class="html-italic">f</span> = 2.4 Hz.</p>
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<p>Simulation of a cantilever beam array with 12 cantilevers and ∆<span class="html-italic">f</span> = 1.5 Hz.</p>
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<p>Simulation of bandwidth dependence on the number of cantilevers for ∆<span class="html-italic">f</span> = 1.5 Hz. The lines connecting theoretical points serve as a guide for the eye.</p>
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<p>(<b>a</b>) Simulated dependence of the number of cantilevers on the frequency detuning ∆<span class="html-italic">f</span>; (<b>b</b>) Dependence of the maximum bandwidth on the frequency detuning ∆<span class="html-italic">f</span>. The lines connecting theoretical points serve as a guide for the eye.</p>
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<p>(<b>a</b>) Simulated dependence of the number of cantilevers on the frequency detuning ∆<span class="html-italic">f</span>; (<b>b</b>) Dependence of the maximum bandwidth on the frequency detuning ∆<span class="html-italic">f</span>. The lines connecting theoretical points serve as a guide for the eye.</p>
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<p>Power of parallel and series connection compared with the optimum power (designated as “PEC 1 + PEC 2”). FB: full bridge.</p>
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<p>Two piezoelectric cantilevers (denoted as PZ1, PZ2) with the individual full wave bridge rectifiers connected parallel to the resistance <span class="html-italic">R</span><sub>L</sub>.</p>
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<p>Dependence of the normalized electrical power on the load resistance.</p>
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<p>Comparison of the frequency dependency of the bandwidth (<b>a</b>,<b>c</b>) and the guaranteed electrical power (<b>b</b>,<b>d</b>) between simulation and measurement for arrays with two (<b>a</b>,<b>b</b>) and three (<b>c</b>,<b>d</b>) PECs.</p>
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<p>Comparison of the simulated and measured power with dependence upon frequency for the parallel connection of two PECs with individual rectifiers and ∆<span class="html-italic">f</span> = 1.5 Hz (<b>left</b>) or ∆<span class="html-italic">f</span> = 2 Hz (<b>right</b>).</p>
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<p>Comparison of the simulated and measured power with dependence upon frequency for the parallel connection of three PECs with individual rectifiers and ∆<span class="html-italic">f</span> = 1.5 Hz (<b>left</b>) or ∆<span class="html-italic">f</span> = 2 Hz (<b>right</b>).</p>
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2961 KiB  
Article
Evaluating the High Frequency Behavior of the Modified Grounding Scheme in Wind Farms
by Seyede Fatemeh Hajeforosh, Zahra Pooranian, Ali Shabani and Mauro Conti
Appl. Sci. 2017, 7(12), 1323; https://doi.org/10.3390/app7121323 - 19 Dec 2017
Cited by 16 | Viewed by 6210
Abstract
Wind generators are exposed to numerous destructive forces such as lightning and are therefore vulnerable to these phenomena. To evaluate the transient behavior of a wind power plant during direct and indirect strikes, modeling of all relevant components is required. Among the protective [...] Read more.
Wind generators are exposed to numerous destructive forces such as lightning and are therefore vulnerable to these phenomena. To evaluate the transient behavior of a wind power plant during direct and indirect strikes, modeling of all relevant components is required. Among the protective and control components of wind turbines, the grounding system is the most important element for protection against lightning strikes. This paper examines the impact of nonlinear soil ionization behavior and frequency dependency on a wind turbine in order to model a sufficient protection scheme to reduce overvoltage and make the system tolerable against transitions. The high frequency models of other equipment such as transformers, horizontal conductors, vertical rods, surge arresters and underground cables must also be taken into account to design the grounding system. Our Proposed Modified Grounding Scheme (PMGS) is to reduce the maximum transient overvoltages. We simulate the model in a restructured version of the Electromagnetic Transient Program (EMTP-RV) software to examine the effectiveness of the system. We then apply the simulated results to pair of turbines that are interconnected with a frequency-dependent cable. We carry out the simulation for direct and indirect lightning strikes. The results indicate that the MGS can lead to considerably more than a 50% reduction in transient voltages for lightning and thus leads to more reliable networks. Full article
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<p>Proposed Modified Grounding Scheme (PMGS).</p>
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<p>EMTP-RV circuit of the simulated single wind turbine with PMGS.</p>
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<p>Impact of PMGS on transient overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>Comparison of different types of grounding schemes.</p>
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<p>Circuit of the simulated wind turbine with a surge arrester.</p>
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<p>Impact of high frequency SA on transient overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>Circuit of the simulated wind turbine with dependent cable.</p>
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<p>Impact of frequency-dependent cable on transient overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>Impact of increased horizontal conductor on transient overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>Impact of increased vertical conductor on transient overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>EMTP-RV Circuit of the comprehensive wind turbine model with PMGS.</p>
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<p>Impact of comprehensive wind turbine model with PMGS on transient overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>Impact of direct strike on in-service wind turbine overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>Impact of direct strike on out-of-service wind turbine overvoltages. (<b>a</b>) LV side of the main transformer; (<b>b</b>) HV side of the main transformer from node to ground; (<b>c</b>) control circuits.</p>
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<p>EMTP-RV circuit of the pair of turbines. (<b>a</b>) Interconnected PMGS; (<b>b</b>) separated PMGS.</p>
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<p>Impact of indirect lightning on overvoltages. (<b>a</b>) LV side of the first tower; (<b>b</b>) HV side of the first tower; (<b>c</b>) control circuit of the first tower; (<b>d</b>) LV side of the second tower; (<b>e</b>) HV side of the second tower; (<b>f</b>) control circuit of the second tower.</p>
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<p>Impact of indirect lightning on overvoltages. (<b>a</b>) LV side of the first tower; (<b>b</b>) HV side of the first tower; (<b>c</b>) control circuit of the first tower; (<b>d</b>) LV side of the second tower; (<b>e</b>) HV side of the second tower; (<b>f</b>) control circuit of the second tower.</p>
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<p>Impact of direct lightning on overvoltages. (<b>a</b>) LV side of the first tower; (<b>b</b>) HV side of the first tower; (<b>c</b>) control circuit of the first tower; (<b>d</b>) LV side of the second tower; (<b>e</b>) HV side of the second tower; (<b>f</b>) control circuit of the second tower.</p>
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2502 KiB  
Article
Current-Fluctuation Mechanism of Field Emitters Using Metallic Single-Walled Carbon Nanotubes with High Crystallinity
by Norihiro Shimoi and Kazuyuki Tohji
Appl. Sci. 2017, 7(12), 1322; https://doi.org/10.3390/app7121322 - 19 Dec 2017
Cited by 3 | Viewed by 4532
Abstract
Field emitters can be used as a cathode electrode in a cathodoluminescence device, and single-walled carbon nanotubes (SWCNTs) that are synthesized by arc discharge are expected to exhibit good field emission (FE) properties. However, a cathodoluminescence device that uses field emitters radiates rays [...] Read more.
Field emitters can be used as a cathode electrode in a cathodoluminescence device, and single-walled carbon nanotubes (SWCNTs) that are synthesized by arc discharge are expected to exhibit good field emission (FE) properties. However, a cathodoluminescence device that uses field emitters radiates rays whose intensity considerably fluctuates at a low frequency, and the radiant fluctuation is caused by FE current fluctuation. To solve this problem, is very important to obtain a stable output for field emitters in a cathodoluminescence device. The authors consider that the electron-emission fluctuation is caused by Fowler–Nordheim electron tunneling and that the electrons in the Fowler–Nordheim regime pass through an inelastic potential barrier. We attempted to develop a theoretical model to analyze the power spectrum of the FE current fluctuation using metallic SWCNTs as field emitters, owing to their electrical conductivity by determining their FE properties. Field emitters that use metallic SWCNTs with high crystallinity were successfully developed to achieve a fluctuating FE current from field emitters at a low frequency by employing inelastic electron tunneling. This paper is the first report of the successful development of an inelastic-electron-tunneling model with a Wentzel–Kramers–Brillouin approximation for metallic SWCNTs based on the evaluation of FE properties. Full article
(This article belongs to the Special Issue Field Emission from Graphene and other Nanostructures)
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<p>Tin-doped indium oxide (ITO) film images after field emission (FE) activation. (<b>a</b>) Schematic diagram of the scratched area and single-walled carbon nanotubes (SWCNTs) protruding from the ITO film; (<b>b</b>) Scanning electron microscope (SEM) overview after scratching the ITO film, including metallic SWCNTs to activate FE; and, (<b>c</b>) Enlarged SEM view of the metallic SWCNTs protruding from the ITO film; (<b>d</b>) Transmission electron microscope (TEM) overview of bundles of metallic highly crystalline SWCNTs that were used in the ITO film (<b>b</b>,<b>c</b>).</p>
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<p>Schematic diagram of the FE measurement system with a diode structure.</p>
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<p>Primitive model of the FE using an SWCNT emitter based on Fowler–Nordheim tunneling.</p>
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<p>Current density–electric-field characteristics of metallic SWCNTs. The inset shows the planar lighting.</p>
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<p>Distributions of (<b>a</b>) FE current fluctuation and (<b>b</b>) spectrum of the FE current fluctuation obtained by the Fourier transform method.</p>
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<p>Distributions of (<b>a</b>) FE current fluctuation and (<b>b</b>) spectrum of the FE current fluctuation obtained by the Fourier transform method.</p>
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<p>Dependence of power spectrum by simulation on the applied voltage. <span class="html-italic">E</span><sub>0</sub> indicates the original field supplied between the cathode and anode electrodes.</p>
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25421 KiB  
Article
Playing for a Virtual Audience: The Impact of a Social Factor on Gestures, Sounds and Expressive Intents
by Simon Schaerlaeken, Didier Grandjean and Donald Glowinski
Appl. Sci. 2017, 7(12), 1321; https://doi.org/10.3390/app7121321 - 19 Dec 2017
Cited by 8 | Viewed by 5643
Abstract
Can we measure the impact of the presence of an audience on musicians’ performances? By exploring both acoustic and motion features for performances in Immersive Virtual Environments (IVEs), this study highlights the impact of the presence of a virtual audience on both the [...] Read more.
Can we measure the impact of the presence of an audience on musicians’ performances? By exploring both acoustic and motion features for performances in Immersive Virtual Environments (IVEs), this study highlights the impact of the presence of a virtual audience on both the performance and the perception of authenticity and emotional intensity by listeners. Gestures and sounds produced were impacted differently when musicians performed at different expressive intents. The social factor made features converge towards values related to a habitual way of playing regardless of the expressive intent. This could be due to musicians’ habits to perform in a certain way in front of a crowd. On the listeners’ side, when comparing different expressive conditions, only one congruent condition (projected expressive intent in front of an audience) boosted the participants’ ratings for both authenticity and emotional intensity. At different values for kinetic energy and metrical centroid, stimuli recorded with an audience showed a different distribution of ratings, challenging the ecological validity of artificially created expressive intents. Finally, this study highlights the use of IVEs as a research tool and a training assistant for musicians who are eager to learn how to cope with their anxiety in front of an audience. Full article
(This article belongs to the Special Issue Sound and Music Computing)
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<p>Motion and acoustic features computed: (<b>A</b>) Chronograph of the motion capture data for one excerpt played in front of an audience while exaggerating expressive intent. (<b>B</b>) Kinetic energy associated with movements of all the markers for the excerpt depicted in (<b>A</b>). (<b>C</b>) 3D view of the motion capture and the line associated with the pelvis and shoulder. (<b>D</b>) Transversal view of the motion capture data and the angle computed between the line from the pelvis and shoulders. (<b>E</b>) Computation of Body Twist Index. The angle between the aforementioned lines is computed over the duration of the excerpt. The Body Twist Index consists of the average of all values comprised in the top quantile (above the quantile 75 value). (<b>F</b>) Sound profile of the performance of the Scherzo of L. van Beethoven’s Symphony No.9 in D minor, op.125. (<b>G</b>) Corresponding autocorrelogram with tracking of the metrical structure. (<b>H</b>) Corresponding metrical centroid curve (Copyright Grandjean, D. et al., 2013 [<a href="#B73-applsci-07-01321" class="html-bibr">73</a>]).</p>
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<p>Impact of the interaction of the expressiveness and the presence of an audience on body features (deadpan: DP, projected: PROJ, and exaggerated: EXAG): (<b>A</b>) Kinetic energy (red); (<b>B</b>) Body Twist Index (green); and (<b>C</b>) Metrical centroid (blue). (* <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.05</mn> </mrow> </semantics> </math>, ** <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.01</mn> </mrow> </semantics> </math>, *** <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.001</mn> </mrow> </semantics> </math>).</p>
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<p>Interaction of the expressiveness and the presence of an audience on: (<b>A</b>) the perceived emotional intensity; and (<b>B</b>) the perceived authenticity (deadpan: DP, projected: PROJ, and exaggerated: EXAG) (** <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.01</mn> </mrow> </semantics> </math>, *** <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.001</mn> </mrow> </semantics> </math>).</p>
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<p>Impact of the interaction of the computed features: (<b>A</b>,<b>C</b>) kinetic energy (red); and (<b>B</b>,<b>D</b>) metrical centroid (blue); and the presence of an audience on: (<b>A</b>,<b>B</b>) the perceived emotional intensity; and (<b>C</b>,<b>D</b>) the perceived authenticity (deadpan: DP, projected: PROJ, and exaggerated: EXAG) (<math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.01</mn> </mrow> </semantics> </math>, * <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.05</mn> </mrow> </semantics> </math>, ** <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.01</mn> </mrow> </semantics> </math>, *** <math display="inline"> <semantics> <mrow> <mi>p</mi> <mo>&lt;</mo> <mn>0.001</mn> </mrow> </semantics> </math>).</p>
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<p>Interactive Virtual Environment: (<b>A</b>) Example views of both social conditions (left, empty; right, audience); (<b>B</b>) details of a disengaged audience (deadpan: DP, projected: PROJ, and exaggerated: EXAG).</p>
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<p>Impact of the expressiveness on (<b>A</b>) the perceived emotional intensity; (<b>B</b>) the perceived authenticity (deadpan: DP, projected: PROJ, and exaggerated: EXAG).</p>
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<p>Impact of the interaction between the Geneva emotional scale and the expressiveness (deadpan: DP, projected: PROJ, and exaggerated: EXAG).</p>
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3246 KiB  
Review
Wavefront Shaping and Its Application to Enhance Photoacoustic Imaging
by Zhipeng Yu, Huanhao Li and Puxiang Lai
Appl. Sci. 2017, 7(12), 1320; https://doi.org/10.3390/app7121320 - 19 Dec 2017
Cited by 39 | Viewed by 7301
Abstract
Since its introduction to the field in mid-1990s, photoacoustic imaging has become a fast-developing biomedical imaging modality with many promising potentials. By converting absorbed diffused light energy into not-so-diffused ultrasonic waves, the reconstruction of the ultrasonic waves from the targeted area in photoacoustic [...] Read more.
Since its introduction to the field in mid-1990s, photoacoustic imaging has become a fast-developing biomedical imaging modality with many promising potentials. By converting absorbed diffused light energy into not-so-diffused ultrasonic waves, the reconstruction of the ultrasonic waves from the targeted area in photoacoustic imaging leads to a high-contrast sensing of optical absorption with ultrasonic resolution in deep tissue, overcoming the optical diffusion limit from the signal detection perspective. The generation of photoacoustic signals, however, is still throttled by the attenuation of photon flux due to the strong diffusion effect of light in tissue. Recently, optical wavefront shaping has demonstrated that multiply scattered light could be manipulated so as to refocus inside a complex medium, opening up new hope to tackle the fundamental limitation. In this paper, the principle and recent development of photoacoustic imaging and optical wavefront shaping are briefly introduced. Then we describe how photoacoustic signals can be used as a guide star for in-tissue optical focusing, and how such focusing can be exploited for further enhancing photoacoustic imaging in terms of sensitivity and penetration depth. Finally, the existing challenges and further directions towards in vivo applications are discussed. Full article
(This article belongs to the Special Issue Biomedical Photoacoustic and Thermoacoustic Imaging)
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<p>(<b>a</b>) A typical optical speckle pattern behind a ground glass diffuser without a shaped incident wavefront; (<b>b</b>) Optical pattern of the region with an optimized incident wavefront compensation by using wavefront shaping. A lot of energy of the multiply-scattered light is focused to a spot that is 1000 times brighter than other speckle grains. The size of the optical focus is determined by the sensitivity area of the feedback signal (Figure reproduced from [<a href="#B42-applsci-07-01320" class="html-bibr">42</a>]).</p>
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<p>Left: experimental schematic of the first photoacoustically guided optical focusing system. DM, deformable mirror; UT, ultrasound transducer. Right: optical spot behind the scattering layer (<b>a</b>) before and (<b>b</b>) after being guided to the ultrasonic focal spot (marked by the arrows) via wavefront shaping; (<b>c</b>) a photo of graphite particle (marked by wide arrow) after being shifted to 10 μm from the optical beam; and (<b>d</b>) the refocused optical beam centered at the graphite particle after wavefront shaping. The narrow arrows mark the locations of the center of ultrasonic focus. The diameter of the ultrasound focus is 90 μm (Figure from ref. [<a href="#B25-applsci-07-01320" class="html-bibr">25</a>]).</p>
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<p>(<b>a</b>) Schematic of the two-stage PAWS experimental set-up. λ/2: half-wave plate; PBS: polarizing beam splitter; SLM: LCoS-type spatial light modulator; PAWS, photoacoustically-guided wavefront shaping. (<b>b</b>) a representative demonstration for optimization procedure with two stages: linear PAWS focuses light into the acoustic resolution (within the acoustic focal region denoted by blue dashed line); nonlinear PAWS focuses light down to optical resolution (observed as a single-speckle grain); (<b>c</b>) the observation upon speckle pattern behind the diffuser without phase modulation (a randomized phase pattern uploaded on the SLM); and (<b>d</b>) the optical focus down to optical resolution observed behind the diffuser with phase modulation by nonlinear PAWS (Figure from [<a href="#B48-applsci-07-01320" class="html-bibr">48</a>]).</p>
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<p>Left: schematic of the experiment. Right: (<b>a</b>) the initial optical speckle pattern; (<b>b</b>) focusing light onto one focus by measuring the TM with 256 controlled units on the SLM; (<b>c</b>) the norm of the focusing operator: each line represents the desired output focusing signal on CCD camera; and (<b>d</b>) an example of focusing light onto multiple foci (Figure reproduced from ref. [<a href="#B21-applsci-07-01320" class="html-bibr">21</a>]).</p>
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<p>(<b>a</b>) The phase of each SLM input mode (in Hadamard basis [<a href="#B84-applsci-07-01320" class="html-bibr">84</a>]) is scanned from 0 to 2π in 16 steps; the corresponding photoacoustic trace is measured for each phase step; (<b>b</b>) the peak-to-peak amplitude of each PA signal window closely follows a cosine modulation as a function of the phase of an input mode; the photoacoustic transmission-matrix elements are retrieved directly from these cosine modulation phases <span class="html-italic">θij</span> and amplitudes <span class="html-italic">β<sub>ij</sub></span> for all input–output mode pairs <span class="html-italic">j</span>, <span class="html-italic">i</span>. The matrix is converted to the SLM-pixel input basis by a basis transformation (Figure from [<a href="#B22-applsci-07-01320" class="html-bibr">22</a>]).</p>
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<p>Three-dimensional photoacoustic imaging of two capillary samples: (<b>a</b>–<b>c</b>) represent the imaging optimized by PAWS; (<b>d</b>–<b>f</b>) represent the imaging without PAWS by displaying a flat phase pattern on SLM; (<b>a</b>,<b>d</b>) three-dimensional scan with a 2% intensity threshold regarding the maximum intensity; (<b>b</b>,<b>e</b>) two-dimensional scan; and (<b>c</b>,<b>f</b>) 1D scan of the capillary tubes at <span class="html-italic">x</span> = 0.02 mm (Figure from [<a href="#B28-applsci-07-01320" class="html-bibr">28</a>]).</p>
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<p>Super-resolution photoacoustic imaging. Scale bar: 100 μm. (<b>a</b>) Photoacoustic image of a black alpaca hair (25 μm diameter) and (<b>b</b>) PA signal intensity profile along the dashed line in (<b>a</b>), showing a diameter of 30 μm defined by the full width of half maximum (FWHM). (<b>c</b>) Direct microscopic image of multiple hairs. (<b>d</b>) Experimental one-dimensional (1D) scan images with direct optical microscopic, and with uniform, random, and optimized phase compensations, repsctively. (<b>e</b>–<b>g</b>) Sweat bee wing images with uniform, random speckle, as well as optimized wavefront illuminations, respectively. (<b>h</b>) Direction microscopic image of the bee wing serves as the gold standard for comparison. (Figure from [<a href="#B26-applsci-07-01320" class="html-bibr">26</a>]).</p>
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<p>(<b>a</b>) Experimental setup for PAWS (transmission matrix measurement approach); (<b>b</b>) reference photograph of the absorbing leaf skeleton embedded in a transparent agarose gel block; (<b>c</b>) a standard photoacoustic image obtained by averaging different speckle illuminations and its envelope (<b>d</b>); and (<b>e</b>) enhanced photoacoustic imaging with PAWS optimization.</p>
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5364 KiB  
Article
Estimation of Tendon Force Distribution in Prestressed Concrete Girders Using Smart Strand
by Keunhee Cho, Sung Tae Kim, Jeong-Rae Cho and Young-Hwan Park
Appl. Sci. 2017, 7(12), 1319; https://doi.org/10.3390/app7121319 - 19 Dec 2017
Cited by 7 | Viewed by 12959
Abstract
The recently developed smart strand offers the possibility of measuring the prestress force of the tendon from jacking and all along its service life. In the present study, a method estimating the force distribution in all the tendons of a prestressed concrete (PSC) [...] Read more.
The recently developed smart strand offers the possibility of measuring the prestress force of the tendon from jacking and all along its service life. In the present study, a method estimating the force distribution in all the tendons of a prestressed concrete (PSC) girder installed with one smart strand is proposed. The force distribution in the prestressed tendons is formulated by the friction and the anchorage slip, and is obtained through an optimization process with respect to the compatibility conditions and equilibrium of the forces in the section of the PSC girder. The validation of the proposed method through a numerical example and experiment shows that it can be used to estimate the force developed in the tendon. Full article
(This article belongs to the Section Mechanical Engineering)
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<p>Shape and composition of conventional and smart strands: (<b>a</b>) Conventional strand; (<b>b</b>) Smart strand.</p>
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<p>Prestressed concrete (PSC) girder with multiple tendons.</p>
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<p>Coordinate system in the girder.</p>
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<p>Example PSC girder for the verification of the proposed method (unit: m).</p>
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<p>Comparison of tendon prestress force distributions per analysis case: (<b>a</b>) Case A; (<b>b</b>) Case B.</p>
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<p>Comparison of tendon prestress force distributions per analysis case: (<b>a</b>) Case A; (<b>b</b>) Case B.</p>
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<p>Comparison of prestress force distribution in cases where the strain measured by the smart strand shows definite fluctuation: (<b>a</b>) Variation #1: the smallest error; (<b>b</b>) Variation #7: the median error; (<b>c</b>) Variation #10: the largest error.</p>
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<p>Shape of specimen and jacking process.</p>
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<p>Strains measured by smart strands at each jacking stage: (<b>a</b>) Jacking of Tendon #1; (<b>b</b>) Setting of Tendon #1; (<b>c</b>) Jacking of Tendon #2; (<b>d</b>) Setting of Tendon #2; (<b>e</b>) Jacking of Tendon #3; (<b>f</b>) Setting of Tendon #3.</p>
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<p>Comparison between experiment and optimization per jacking stage (gray lines represent 95% confidence interval): (<b>a</b>) Tendon #1: Jacking of Tendon #1; (<b>b</b>) Tendon #1: Setting of Tendon #3; (<b>c</b>) Tendon #2: Jacking of Tendon #2; (<b>d</b>) Tendon #2: Setting of Tendon #3; (<b>e</b>) Tendon #3: Jacking of Tendon #3; (<b>f</b>) Tendon #3: Setting of Tendon #3.</p>
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<p>Comparison between experiment and optimization per jacking stage (gray lines represent 95% confidence interval): (<b>a</b>) Tendon #1: Jacking of Tendon #1; (<b>b</b>) Tendon #1: Setting of Tendon #3; (<b>c</b>) Tendon #2: Jacking of Tendon #2; (<b>d</b>) Tendon #2: Setting of Tendon #3; (<b>e</b>) Tendon #3: Jacking of Tendon #3; (<b>f</b>) Tendon #3: Setting of Tendon #3.</p>
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1524 KiB  
Article
Mobile Music, Sensors, Physical Modeling, and Digital Fabrication: Articulating the Augmented Mobile Instrument
by Romain Michon, Julius Orion Smith, Matthew Wright, Chris Chafe, John Granzow and Ge Wang
Appl. Sci. 2017, 7(12), 1311; https://doi.org/10.3390/app7121311 - 19 Dec 2017
Cited by 15 | Viewed by 6987
Abstract
Two concepts are presented, extended, and unified in this paper: mobile device augmentation towards musical instruments design and the concept of hybrid instruments. The first consists of using mobile devices at the heart of novel musical instruments. Smartphones and tablets are augmented with [...] Read more.
Two concepts are presented, extended, and unified in this paper: mobile device augmentation towards musical instruments design and the concept of hybrid instruments. The first consists of using mobile devices at the heart of novel musical instruments. Smartphones and tablets are augmented with passive and active elements that can take part in the production of sound (e.g., resonators, exciter, etc.), add new affordances to the device, or change its global aesthetics and shape. Hybrid instruments combine physical/acoustical and “physically informed” virtual/digital elements. Recent progress in physical modeling of musical instruments and digital fabrication is exploited to treat instrument parts in a multidimensional way, allowing any physical element to be substituted with a virtual one and vice versa (as long as it is physically possible). A wide range of tools to design mobile hybrid instruments is introduced and evaluated. Aesthetic and design considerations when making such instruments are also presented through a series of examples. Full article
(This article belongs to the Special Issue Sound and Music Computing)
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<p>Overview of <tt>faust2smartkeyb</tt>.</p>
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<p>Simple <span class="html-small-caps">SmartKeyboard</span> interface.</p>
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<p><span class="html-small-caps">SmartKeyboard</span> pitch rounding “pseudo code” algorithm.</p>
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<p>iPhone 5 augmented with a horn used as passive amplifier on its built-in speaker (instrument by Erin Meadows).</p>
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<p>Mouthpiece for mobile device built-in mic (<b>on the left</b>) and frequency-based blow sensor for mobile device built-in microphone (<b>on the right</b>).</p>
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<p>Hand resonator (<b>on the left</b>) and mouth resonator (<b>on the right</b>) for mobile device built-in speaker.</p>
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<p>Mobile-device-based top creating a “Leslie” effect when spun.</p>
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<p>Rolling mobile phone with phasing effect by Revital Hollander (<b>on the left</b>) and mobile device mounted on a bike wheel by Patricia Robinson (<b>on the right</b>).</p>
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<p>Thumb-held mobile-device-based musical instrument (<b>on the left</b>) and smart-phone augmented to be held as a wind instrument (<b>on the right</b>).</p>
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<p><span class="html-italic">Bouncy-Phone</span> by Casey Kim, <span class="html-italic">Something Else</span> by Edmond Howser, and <span class="html-italic">Mobile Hang</span> by Marit Brademann (from left to right).</p>
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<p>Bidirectional connection between virtual and physical elements of a hybrid instrument.</p>
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<p>“Typical” acoustically driven mobile hybrid instrument model.</p>
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<p>Bidirectional construction in <span class="html-small-caps">Faust</span> using the tilde diagram composition operation.</p>
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<p>Bidirectional construction in <span class="html-small-caps">Faust</span> using the <tt>chain</tt> primitive.</p>
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<p><tt>lTermination(A,B)</tt> and <tt>rTermination(B,C)</tt> in the <span class="html-small-caps">Faust</span> Physical Modeling Library.</p>
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6605 KiB  
Article
Multi-Fidelity Multi-Objective Efficient Global Optimization Applied to Airfoil Design Problems
by Atthaphon Ariyarit and Masahiro Kanazaki
Appl. Sci. 2017, 7(12), 1318; https://doi.org/10.3390/app7121318 - 18 Dec 2017
Cited by 25 | Viewed by 7939
Abstract
In this study, efficient global optimization (EGO) with a multi-fidelity hybrid surrogate model for multi-objective optimization is proposed to solve multi-objective real-world design problems. In the proposed approach, a design exploration is carried out assisted by surrogate models, which are constructed by adding [...] Read more.
In this study, efficient global optimization (EGO) with a multi-fidelity hybrid surrogate model for multi-objective optimization is proposed to solve multi-objective real-world design problems. In the proposed approach, a design exploration is carried out assisted by surrogate models, which are constructed by adding a local deviation estimated by the kriging method and a global model approximated by a radial basis function. An expected hypervolume improvement is then computed on the basis of the model uncertainty to determine additional samples that could improve the model accuracy. In the investigation, the proposed approach is applied to two-objective and three-objective optimization test functions. Then, it is applied to aerodynamic airfoil design optimization with two objective functions, namely minimization of aerodynamic drag and maximization of airfoil thickness at the trailing edge. Finally, the proposed method is applied to aerodynamic airfoil design optimization with three objective functions, namely minimization of aerodynamic drag at cruising speed, maximization of airfoil thickness at the trialing edge and maximization of lift at low speed assuming a landing attitude. XFOILis used to investigate the low-fidelity aerodynamic force, and a Reynolds-averaged Navier–Stokes simulation is applied for high-fidelity aerodynamics in conjunction with a high-cost approach. For comparison, multi-objective optimization is carried out using a kriging model only with a high-fidelity solver (single fidelity). The design results indicate that the non-dominated solutions of the proposed method achieve greater data diversity than the optimal solutions of the kriging method. Moreover, the proposed method gives a smaller error than the kriging method. Full article
(This article belongs to the Special Issue Soft Computing Techniques in Structural Engineering and Materials)
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<p>Schematic illustration of single-fidelity and multi-fidelity surrogate models.</p>
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<p>Flowchart of efficient global optimization: (<b>a</b>) single-fidelity efficient global optimization (EGO); (<b>b</b>) multi-fidelity EGO.</p>
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<p>Schematic illustration of hypervolume improvement and hypervolume: (<b>a</b>) hypervolume improvement; (<b>b</b>) hypervolume.</p>
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<p>Initial sampling data and additional sampling data of two-objective test problem: (<b>a</b>) multi-fidelity approach; (<b>b</b>) single-fidelity approach.</p>
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<p>Hypervolume comparison of multi-fidelity approach and single-fidelity approach of two-objective test problem.</p>
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<p>Cross-validation results of the two-objective test problem: (<b>a</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>1</mn> </msub> </semantics> </math>; (<b>b</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>2</mn> </msub> </semantics> </math>.</p>
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<p>Initial sampling data and additional sampling data of three-objective test problem: (<b>a</b>) multi-fidelity approach; (<b>b</b>) single-fidelity approach.</p>
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<p>Hypervolume comparison of the multi-fidelity approach and the single-fidelity approach of three-objective test problem.</p>
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<p>Cross-validation results of the three-objective test problem: (<b>a</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>1</mn> </msub> </semantics> </math>; (<b>b</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>2</mn> </msub> </semantics> </math>; (<b>c</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>3</mn> </msub> </semantics> </math>.</p>
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<p>Cross-validation results of the three-objective test problem: (<b>a</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>1</mn> </msub> </semantics> </math>; (<b>b</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>2</mn> </msub> </semantics> </math>; (<b>c</b>) result of <math display="inline"> <semantics> <msub> <mi>f</mi> <mn>3</mn> </msub> </semantics> </math>.</p>
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<p>Computation structured grid: (<b>a</b>) full length; (<b>b</b>) grid around the airfoil.</p>
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<p>Initial sampling data and additional sampling data of two-objective airfoil shape optimization problem: (<b>a</b>) multi-fidelity approach; (<b>b</b>) single-fidelity approach.</p>
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<p>Hypervolume comparison of multi-fidelity approach and single-fidelity approach of two-objective airfoil shape optimization problem.</p>
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<p>Cross-validation of two-objective airfoil shape optimization problem of <math display="inline"> <semantics> <msub> <mi>C</mi> <mi mathvariant="normal">d</mi> </msub> </semantics> </math>.</p>
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<p>Comparison of design geometries of two-objective airfoil shape optimization problem: (<b>a</b>) multi-fidelity approach; (<b>b</b>) single-fidelity approach.</p>
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<p>Initial sampling data and additional sampling data of three-objective airfoil shape optimization problem: (<b>a</b>) multi-fidelity approach; (<b>b</b>) single-fidelity approach.</p>
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<p>Hypervolume comparison of multi-fidelity approach and single-fidelity approach.</p>
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<p>Cross-validation results of three-objective airfoil shape optimization problem: (<b>a</b>) results of <math display="inline"> <semantics> <msub> <mi>C</mi> <mi mathvariant="normal">d</mi> </msub> </semantics> </math>; (<b>b</b>) results of <math display="inline"> <semantics> <msub> <mi>C</mi> <mi mathvariant="normal">l</mi> </msub> </semantics> </math>.</p>
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<p>Comparison of design geometries of three-objective airfoil shape optimization problem: (<b>a</b>) multi-fidelity approach; (<b>b</b>) single-fidelity approach.</p>
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4219 KiB  
Review
Inorganic Salt Hydrate for Thermal Energy Storage
by Ning Xie, Zhaowen Huang, Zigeng Luo, Xuenong Gao, Yutang Fang and Zhengguo Zhang
Appl. Sci. 2017, 7(12), 1317; https://doi.org/10.3390/app7121317 - 18 Dec 2017
Cited by 128 | Viewed by 14063
Abstract
Using phase change materials (PCMs) for thermal energy storage has always been a hot topic within the research community due to their excellent performance on energy conservation such as energy efficiency in buildings, solar domestic hot water systems, textile industry, biomedical and food [...] Read more.
Using phase change materials (PCMs) for thermal energy storage has always been a hot topic within the research community due to their excellent performance on energy conservation such as energy efficiency in buildings, solar domestic hot water systems, textile industry, biomedical and food agroindustry. Several literatures have reported phase change materials concerning various aspects. Among these materials, salt hydrates are worthy of exploring due to their high-energy storage density, rational price, multiple sources and relatively good thermal conductivity. This paper reviews the present state of salt hydrates PCMs targeting classification, properties, defects, possible solutions as well as their idiographic features which are suitable for applications. In addition, new trends of future research are also indicated. Full article
(This article belongs to the Section Energy Science and Technology)
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<p>(<b>a</b>) Optical microscope images and (<b>b</b>) SEM (Scanning Electron Microscope) image of the PLA (polytrimethylene carbonate) microcapsules in vacuum. Reproduced with permission from [<a href="#B57-applsci-07-01317" class="html-bibr">57</a>], <b>IDEALS, copyright 2015</b>.</p>
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<p>(<b>a</b>) Optical microscope images and (<b>b</b>) SEM (Scanning Electron Microscope) image of the PLA (polytrimethylene carbonate) microcapsules in vacuum. Reproduced with permission from [<a href="#B57-applsci-07-01317" class="html-bibr">57</a>], <b>IDEALS, copyright 2015</b>.</p>
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<p>(<b>a</b>) Optical microscope images and (<b>b</b>) SEM image of microcapsules synthesized in a microfluidic device. Reproduced with permission from [<a href="#B57-applsci-07-01317" class="html-bibr">57</a>], <b>IDEALS, copyright 2015</b>.</p>
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<p>(<b>a</b>) Optical microscope images and (<b>b</b>) SEM image of microcapsules synthesized in a microfluidic device. Reproduced with permission from [<a href="#B57-applsci-07-01317" class="html-bibr">57</a>], <b>IDEALS, copyright 2015</b>.</p>
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<p>(<b>a</b>) Solar thermal collectors (<b>b</b>) Hot-water tanks with PCM modules. Reproduced with permission from [<a href="#B74-applsci-07-01317" class="html-bibr">74</a>]. Elsevier: Solar Energy Materials and Solar Cells, copyright 2006.</p>
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<p>(<b>a</b>) The schematic of a full-scale experimental room with PCM; (<b>b</b>) Temperature comparison of ordinary wall room and PCM room. Reproduced with permission from [<a href="#B80-applsci-07-01317" class="html-bibr">80</a>]. Elsevier: Energy Procedia, copyright 2017.</p>
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<p>(<b>a</b>) The schematic of a full-scale experimental room with PCM; (<b>b</b>) Temperature comparison of ordinary wall room and PCM room. Reproduced with permission from [<a href="#B80-applsci-07-01317" class="html-bibr">80</a>]. Elsevier: Energy Procedia, copyright 2017.</p>
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<p>Photographs of the panels without (<b>left</b>) and with the CaCl<sub>2</sub>·6H<sub>2</sub>O /EG composite PCM (<b>right</b>). Reproduced with permission from [<a href="#B82-applsci-07-01317" class="html-bibr">82</a>]. Elsevier, Applied Energy, copyright 2017.</p>
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<p>(<b>a</b>) Chilled water tank for air conditioning; (<b>b</b>) Ice storage tank for air conditioning (<b>c</b>) PCM storage tank for air conditioning. Reproduced with permission from [<a href="#B90-applsci-07-01317" class="html-bibr">90</a>]. Springer: Energy Solutions to Combat Global Warming, copyright 2016.</p>
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6041 KiB  
Review
Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase
by Cristian Mejia and Yuya Kajikawa
Appl. Sci. 2017, 7(12), 1316; https://doi.org/10.3390/app7121316 - 18 Dec 2017
Cited by 42 | Viewed by 6914
Abstract
As robotics becomes ubiquitous, there is increasing interest in understanding how to develop robots that better respond to social needs, as well as how robotics impacts society. This is evidenced by the growing rate of publications on social robotics. In this article, we [...] Read more.
As robotics becomes ubiquitous, there is increasing interest in understanding how to develop robots that better respond to social needs, as well as how robotics impacts society. This is evidenced by the growing rate of publications on social robotics. In this article, we analyze the citation network of academic articles on social robotics to understand its structure, reveal research trends and expose its knowledgebase. We found eight major clusters, namely robots as social partners, human factors and ergonomics on human robot interaction, robotics for children’s development, swarm robotics, emotion detection, assessment of robotic surgery, robots for the elderly and telepresence and human robot interaction in rescue robots. In addition, despite its social focus, social science literature as a source of knowledge is barely present. Research trends point to studies on applications, rather than to specific technologies or morphologies, and in particular, towards robots as partners, for child development and assistance for the elderly. Full article
(This article belongs to the Special Issue Social Robotics)
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<p>Data collection and methodology described in this article. (<b>a</b>) Data retrieval; (<b>b</b>) A citation network is created based on the references of the articles; (<b>c</b>) The largest connected component is extracted; (<b>d</b>) Clusters are obtained from the network.</p>
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<p>Yearly trends of publications on robotics and social robotics.</p>
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<p>Trends in publications of social robotics. (<b>a</b>) By number of articles; (<b>b</b>) proportion in relation to all-robotics research.</p>
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<p>Citation networks of (<b>a</b>) robotics research and (<b>b</b>) social robotics research.</p>
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<p>Yearly trends in publishing per cluster. Clusters 1–4: robots as social partners, human factors and ergonomics in human robot interaction, robotics for child development and swarm robotics.</p>
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<p>Yearly trends in publishing per cluster. Clusters 5–8: emotion detection, assessment of robotic surgery, robots for the elderly and telepresence and human-robot interaction in rescue robots.</p>
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<p>Visualization of seven sub-clusters of human-robot interaction (HRI).</p>
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<p>Heatmap analysis based on the cosine similarity of cluster contents. The intensity of red varies according to the similarity score, being 1 a perfect content match between the pair of clusters.</p>
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4083 KiB  
Article
Plasmon Modulation Spectroscopy of Noble Metals to Reveal the Distribution of the Fermi Surface Electrons in the Conduction Band
by Kentaro Takagi, Selvakumar V. Nair, Jumpei Saito, Keisuke Seto, Ryosuke Watanabe, Takayoshi Kobayashi and Eiji Tokunaga
Appl. Sci. 2017, 7(12), 1315; https://doi.org/10.3390/app7121315 - 18 Dec 2017
Cited by 6 | Viewed by 5676
Abstract
To directly access the dynamics of electron distribution near the Fermi-surface after plasmon excitation, pump-probe spectroscopy was performed by pumping plasmons on noble-metal films and probing the interband transition. Spectral change in the interband transitions is sensitive to the electron distribution near the [...] Read more.
To directly access the dynamics of electron distribution near the Fermi-surface after plasmon excitation, pump-probe spectroscopy was performed by pumping plasmons on noble-metal films and probing the interband transition. Spectral change in the interband transitions is sensitive to the electron distribution near the Fermi-surface, because it involves the d valence-band to the conduction band transitions and should reflect the k-space distribution dynamics of electrons. For the continuous-wave pump and probe experiment, the plasmon modulation spectra are found to differ from both the current modulation and temperature difference spectra, possibly reflecting signatures of the plasmon wave function. For the femtosecond-pulse pump and probe experiment, the transient spectra agree well with the known spectra upon the excitation of the respective electrons resulting from plasmon relaxation, probably because the lifetime of plasmons is shorter than the pulse duration. Full article
(This article belongs to the Special Issue Laser Interaction with Plasmonic Nanostructures)
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<p>Change in the electronic distribution expected after plasmon excitation (dashed lines: Fermi distribution function).</p>
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<p>Experimental setup for the continuous wave (CW) plasmon modulation experiment.</p>
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<p>Experimental setup for femtosecond pump-probe spectroscopy of plasmons.</p>
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<p>Reflection spectra of Ag with a film thickness of about 50 nm in the Kretschmann arrangement for p- and s-polarized light at an incident angle of &gt;45°. The dip around 430 nm is due to the surface plasmon resonance appearing only in the reflection spectra for p-polarized light. The dip near 310 nm in the reflection spectra for both p- and s-polarized light is due to the interband transition.</p>
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<p>Plasmon modulation spectrum ΔR/R, which was taken around the interband transition edge from the air side of the prism, while the plasmon resonance dip around 410 nm was excited by a 408-nm laser.</p>
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<p>Change in (<b>a</b>) the current modulation spectra and (<b>b</b>) the normalized current modulation spectra with the increase in the current.</p>
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<p>Temperature difference spectra normalized by the reflection spectrum at room temperature. The temperature is increased from room temperature in steps of +10 K.</p>
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<p>Comparison between plasmon modulation (red, (<b>b</b>)), current modulation (at 1.56 A, blue, (<b>c</b>)), temperature difference spectra (at ΔT = +50 K, thin black line), and the second derivative of the reflectance (green, (<b>a</b>)) calculated from the reflectance in <a href="#applsci-07-01315-f006" class="html-fig">Figure 6</a>a.</p>
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<p>The calculated change in reflectivity for a 50 nm-thick Ag film on a quartz substrate for p-polarized light incident from the air side at an angle of incidence of 55 degrees. Results for (i) a thermal distribution with electron temperature change <math display="inline"> <semantics> <mrow> <mo>Δ</mo> <msub> <mi>T</mi> <mi>e</mi> </msub> <mo>=</mo> <mn>0.16</mn> <mtext> </mtext> </mrow> </semantics> </math>K (red line labelled thermal) and (ii) a rigid shift of the Fermi sphere (blue line labelled drift) with the same energy content as (i) are shown.</p>
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<p>Experimental ΔR/R spectra after excitation of plasmons in the Au film.</p>
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<p>Calculated ΔR/R spectra after excitation of respective particles. (Reproduced with permission from Figure 12b in [<a href="#B14-applsci-07-01315" class="html-bibr">14</a>]).</p>
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Article
Investigation into the Fire Hazards of Lithium-Ion Batteries under Overcharging
by Dongxu Ouyang, Jiahao Liu, Mingyi Chen and Jian Wang
Appl. Sci. 2017, 7(12), 1314; https://doi.org/10.3390/app7121314 - 18 Dec 2017
Cited by 66 | Viewed by 12142
Abstract
Numerous lithium-ion battery (LIB) fires and explosions have raised serious concerns about the safety issued associated with LIBs; some of these incidents were mainly caused by overcharging of LIBs. Therefore, to have a better understanding of the fire hazards caused by LIB overcharging, [...] Read more.
Numerous lithium-ion battery (LIB) fires and explosions have raised serious concerns about the safety issued associated with LIBs; some of these incidents were mainly caused by overcharging of LIBs. Therefore, to have a better understanding of the fire hazards caused by LIB overcharging, two widely used commercial LIBs, nickel manganese cobalt oxide (NMC) and lithium iron phosphate (LFP), with different cut-off voltages (4.2 V, 4.5 V, 4.8 V and 5.0 V), were tested in this work. Some parameters including the surface temperature, the flame temperature, voltage, and radiative heat flux were measured and analyzed. The results indicate that the initial discharging voltage increases with the growth of charge cut-off voltage. Moreover, the higher the cut-off voltage, the longer the discharging time to reach 2.5 V. An overcharged LIB will undergo a more violent combustion process and has lower stability than a normal one, and the increasing cut-off voltage aggravates the severity. In addition, it is also revealed that the NMC fails earlier than the LFP under the same condition. The temperatures for safety vent cracking, ignition, and thermal runaway of LIBs exhibit similar values for the same condition, which demonstrates that the LIB will fail at a certain temperature. Finally, the peak heat flux, total radiative heat flux, and total radiative heat will rise with the increase in voltage. Full article
(This article belongs to the Special Issue Advanced Materials for Rechargeable Lithium Batteries)
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<p>The physical diagrams of batteries.</p>
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<p>(<b>a</b>) Schematic of experimental setup; (<b>b</b>) the thermocouples setup around the battery (TC1 was used to detect the battery surface temperature; TC2, 3, 4, 5 were used to detect the flame temperature).</p>
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<p>(<b>a</b>) Schematic of experimental setup; (<b>b</b>) the thermocouples setup around the battery (TC1 was used to detect the battery surface temperature; TC2, 3, 4, 5 were used to detect the flame temperature).</p>
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<p>Discharging curves of LIBs subjected to different cut-off voltage at 2 C rate.</p>
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<p>The surface temperature curves of LIBs during charging and discharging at 2 °C rate.</p>
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<p>Burning process of LIBs in tests: (<b>a</b>) 4.2 V NMC; (<b>b</b>) 5.0 V NMC; (<b>c</b>) 4.2 V LFP; (<b>d</b>) 5.0 V LFP.</p>
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<p>Burning process of LIBs in tests: (<b>a</b>) 4.2 V NMC; (<b>b</b>) 5.0 V NMC; (<b>c</b>) 4.2 V LFP; (<b>d</b>) 5.0 V LFP.</p>
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<p>Photographs of batteries before and after burning.</p>
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<p>The typical curves of LIB surface temperature during tests: (<b>a</b>) NMC; (<b>b</b>) LFP.</p>
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<p>The typical curves of LIB temperature rise rate vs. surface temperature during tests: (<b>a</b>) NMC; (<b>b</b>) LFP.</p>
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<p>Some critical temperatures of LIB in tests.</p>
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<p>The typical curves of LIB flame temperature during tests: (<b>a</b>) NMC (4.2 V); (<b>b</b>) NMC (4.5 V); (<b>c</b>) NMC (4.8 V); (<b>d</b>) NMC (5.0 V); (<b>e</b>) LFP (4.2 V); (<b>f</b>) LFP (4.5 V); (<b>g</b>) LFP (4.8 V); (<b>h</b>) LFP (5.0 V).</p>
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<p>The typical curves of LIB flame temperature during tests: (<b>a</b>) NMC (4.2 V); (<b>b</b>) NMC (4.5 V); (<b>c</b>) NMC (4.8 V); (<b>d</b>) NMC (5.0 V); (<b>e</b>) LFP (4.2 V); (<b>f</b>) LFP (4.5 V); (<b>g</b>) LFP (4.8 V); (<b>h</b>) LFP (5.0 V).</p>
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<p>The typical curves of LIB flame temperature during tests: (<b>a</b>) NMC (4.2 V); (<b>b</b>) NMC (4.5 V); (<b>c</b>) NMC (4.8 V); (<b>d</b>) NMC (5.0 V); (<b>e</b>) LFP (4.2 V); (<b>f</b>) LFP (4.5 V); (<b>g</b>) LFP (4.8 V); (<b>h</b>) LFP (5.0 V).</p>
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<p>The typical curves of LIB flame temperature during tests: (<b>a</b>) NMC (4.2 V); (<b>b</b>) NMC (4.5 V); (<b>c</b>) NMC (4.8 V); (<b>d</b>) NMC (5.0 V); (<b>e</b>) LFP (4.2 V); (<b>f</b>) LFP (4.5 V); (<b>g</b>) LFP (4.8 V); (<b>h</b>) LFP (5.0 V).</p>
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<p>Heat flux curves of LIBs during tests: (<b>a</b>) NMC; (<b>b</b>) LFP.</p>
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<p>Heat flux curves of LIBs during tests: (<b>a</b>) NMC; (<b>b</b>) LFP.</p>
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<p>The schematic of yjr electrochemical model.</p>
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<p>The schematic of s battery catching fire.</p>
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2125 KiB  
Article
A Neural Parametric Singing Synthesizer Modeling Timbre and Expression from Natural Songs
by Merlijn Blaauw and Jordi Bonada
Appl. Sci. 2017, 7(12), 1313; https://doi.org/10.3390/app7121313 - 18 Dec 2017
Cited by 75 | Viewed by 19327
Abstract
We recently presented a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of pitch and timbre. This allows conveniently modifying [...] Read more.
We recently presented a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of pitch and timbre. This allows conveniently modifying pitch to match any target melody, facilitates training on more modest dataset sizes, and significantly reduces training and generation times. Nonetheless, compared to modeling waveform directly, ways of effectively handling higher-dimensional outputs, multiple feature streams and regularization become more important with our approach. In this work, we extend our proposed system to include additional components for predicting F0 and phonetic timings from a musical score with lyrics. These expression-related features are learned together with timbrical features from a single set of natural songs. We compare our method to existing statistical parametric, concatenative, and neural network-based approaches using quantitative metrics as well as listening tests. Full article
(This article belongs to the Special Issue Sound and Music Computing)
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<p>Diagram depicting an overview of the system with its different components. Here, V/UV is the predicted voice/unvoiced decision, and the Fill UV block fills unvoiced isegments by interpolation.</p>
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<p>Overview of the modified WaveNet network architecture. In this case, the network depicted predicts harmonic spectral envelope features (top-right and bottom), given control inputs (mid-right).</p>
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<p>Example distributions of the constrained mixture density output. All subplots use location <math display="inline"> <semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics> </math> and scale <math display="inline"> <semantics> <mrow> <mi>ω</mi> <mo>=</mo> <mrow> <mn>6</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </mrow> </semantics> </math>, but varying skewness <math display="inline"> <semantics> <mi>α</mi> </semantics> </math> and shape <math display="inline"> <semantics> <mi>β</mi> </semantics> </math>. The plots show the resulting mixture distributions (solid) and the four underlying Gaussian components (dashed).</p>
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<p>Diagram depicting the cascaded multistream architecture for training and generation phases. The “<math display="inline"> <semantics> <msup> <mi>z</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </semantics> </math>” blocks represent unit delays. The upward inputs represent control inputs, shared between all streams. Autoregressive connections in generation phase are not shown.</p>
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<p>Comparing the average modulation spectrum of harmonic Mel-Generalized Coefficient (MGC) features. In the plotted excerpt, the relation between pitch and timbre during vibratos can be observed.</p>
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<p>Comparing the average modulation spectrum of log F0 contours predicted by various systems and natural singing.</p>
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<p>Results of the preference test for systems trained on pseudo singing. The Sinsy-HMM and Sinsy-DNN systems were excluded from this comparison, as the only available models are trained on natural singing.</p>
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8634 KiB  
Article
Effect of Aggregate Mineralogy and Concrete Microstructure on Thermal Expansion and Strength Properties of Concrete
by Jinwoo An, S. Sonny Kim, Boo Hyun Nam and Stephan A. Durham
Appl. Sci. 2017, 7(12), 1307; https://doi.org/10.3390/app7121307 - 18 Dec 2017
Cited by 42 | Viewed by 10055
Abstract
Aggregate type and mineralogy are critical factors that influence the engineering properties of concrete. Temperature variations result in internal volume changes could potentially cause a network of micro-cracks leading to a reduction in the concrete’s compressive strength. The study specifically studied the effect [...] Read more.
Aggregate type and mineralogy are critical factors that influence the engineering properties of concrete. Temperature variations result in internal volume changes could potentially cause a network of micro-cracks leading to a reduction in the concrete’s compressive strength. The study specifically studied the effect of the type and mineralogy of fine and coarse aggregates in the normal strength concrete properties. As performance measures, the coefficient of thermal expansion (CTE) and compressive strength were tested with concrete specimens containing different types of fine aggregates (manufactured and natural sands) and coarse aggregates (dolomite and granite). Petrographic examinations were then performed to determine the mineralogical characteristics of the aggregate and to examine the aggregate and concrete microstructure. The test results indicate the concrete CTE increases with the silicon (Si) volume content in the aggregate. For the concrete specimens with higher CTE, the micro-crack density in the interfacial transition zone (ITZ) tended to be higher. The width of ITZ in one of the concrete specimens with a high CTE displayed the widest core ITZ (approx. 11 µm) while the concrete specimens with a low CTE showed the narrowest core ITZ (approx. 3.5 µm). This was attributed to early-age thermal cracking. Specimens with higher CTE are more susceptible to thermal stress. Full article
(This article belongs to the Section Materials Science and Engineering)
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<p>Gradation curves and ASTM C33 grading requirements for fine aggregates.</p>
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<p>Gradation curves for coarse aggregates and ASTM C33 grading requirements for number 57 aggregate.</p>
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<p>Test setup for the determination of the coefficient of thermal expansion (CTE) of the cylindrical concrete specimens.</p>
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<p>Effect of low volume of coarse aggregate and high volume of fine aggregate on concrete CTE.</p>
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<p>Effect of high volume of coarse aggregate and low volume of fine aggregate on concrete CTE.</p>
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<p>The results of the compressive strength and the modulus of the elasticity.</p>
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<p>SEM images of fine aggregates (note: 1 KX = 1000 X).</p>
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<p>SEM images of dolomite and granite with magnification (note: 1 KX = 1000 X).</p>
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<p>SEM images of dolomite and granite with magnification (note: 1 KX = 1000 X).</p>
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<p>Mineral assemblage of igneous rock and chemical compositional analysis results.</p>
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<p>Backscatter SEM images showing microstructure (micro-pores and micro-cracks).</p>
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<p>Line scanning analyses (SEM and energy dispersive X-ray (EDX)) of ITZ regions for dolomite concrete mixtures.</p>
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<p>Line scanning analyses (SEM and energy dispersive X-ray (EDX)) of ITZ regions for dolomite concrete mixtures.</p>
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<p>Line scanning analyses (SEM and EDX) of interfacial transition zone (ITZ) regions for granite concrete mixtures.</p>
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467 KiB  
Article
Compensation for Group Velocity of Polychromatic Wave Measurement in Dispersive Medium
by Seung Jin Chang and Seung-Il Moon
Appl. Sci. 2017, 7(12), 1306; https://doi.org/10.3390/app7121306 - 18 Dec 2017
Cited by 2 | Viewed by 3879
Abstract
The estimation of instantaneous frequency (IF) method is introduced to compensate for the group velocity of electromagnetic wave in dispersive medium. The location of the reflected signal can be obtained by using the time-frequency cross correlation (TFCC), following which it is used to [...] Read more.
The estimation of instantaneous frequency (IF) method is introduced to compensate for the group velocity of electromagnetic wave in dispersive medium. The location of the reflected signal can be obtained by using the time-frequency cross correlation (TFCC), following which it is used to extract the transmitted signal from the total signal acquired. The signal propagated in the dispersive medium is attenuated and distorted by the attenuation characteristics, which depend on the frequency of the medium. By using the IF curve calculated for the transmitted signal, the changed center frequency and time terms can be obtained. The obtained terms are used to compensate for the group velocity error induced by signal distortion and attenuation. Through experiments and simulation, the accuracy of the proposed method is 2% higher than that of the conventional method when the signal propagates over a long distance. Full article
(This article belongs to the Special Issue Ultrasonic Guided Waves)
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<p>Illustration of compensation method based on IF curves.</p>
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<p>Experimental setup.</p>
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<p>The results of acquired signals: 40 m lossy cable, 80 m lossy cable, lossless cable (<b>a</b>) total signal; (<b>b</b>) reflected signal.</p>
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<p>The results of (<b>a</b>) acquired signals, (<b>b</b>) TFCC graph.</p>
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<p>(<b>a</b>) Estimation of instantaneous phase, (<b>b</b>) frequency band of transmitted signal.</p>
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603 KiB  
Article
Cognitive Routing in Software-Defined Underwater Acoustic Networks
by Huma Ghafoor and Insoo Koo
Appl. Sci. 2017, 7(12), 1312; https://doi.org/10.3390/app7121312 - 17 Dec 2017
Cited by 17 | Viewed by 5171
Abstract
There are two different types of primary users (natural acoustic and artificial acoustic), and there is a long propagation delay for acoustic links in underwater cognitive acoustic networks (UCANs). Thus, the selection of a stable route is one of the key design factors [...] Read more.
There are two different types of primary users (natural acoustic and artificial acoustic), and there is a long propagation delay for acoustic links in underwater cognitive acoustic networks (UCANs). Thus, the selection of a stable route is one of the key design factors for improving overall network stability, thereby reducing end-to-end delay. Software-defined networking (SDN) is a novel approach that improves network intelligence. To this end, we propose a novel SDN-based routing protocol for UCANs in order to find a stable route between source and destination. A main controller is placed in a surface buoy that is responsible for the global view of the network, whereas local controllers are placed in different autonomous underwater vehicles (AUVs) that are responsible for a localized view of the network. The AUVs have fixed trajectories, and sensor nodes within transmission range of the AUVs serve as gateways to relay the gathered information to the controllers. This is an SDN-based underwater communications scheme whereby two nodes can only communicate when they have a consensus about a common idle channel. To evaluate our proposed scheme, we perform extensive simulations and improve network performance in terms of end-to-end delay, delivery ratio, and overhead. Full article
(This article belongs to the Special Issue Underwater Acoustics, Communications and Information Processing)
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<p>Cognitive acoustic software-defined underwater network (CA-SDUN). SDN: software-defined networking; PU: primary user.</p>
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<p>A flowchart representing the CA-SDUN protocol. MC: main controller.</p>
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<p>Performance comparison between CA-SDUN, Cog-AA-RP, and Cog-DVRP for average delay as a function of the number of sensor nodes with different numbers of channels, <span class="html-italic">M</span>. (<b>a</b>) average delay when <span class="html-italic">M</span> = 1; (<b>b</b>) average delay when <span class="html-italic">M</span> = 3; and (<b>c</b>) average delay when <span class="html-italic">M</span> = 5. CA-SDUN: cognitive acoustic software-defined underwater network; Cog-AA-RP: cognitive AUV-aided routing method integrated path planning; Cog-DVRP: cognitive diagonal and vertical routing protocol; AUV: autonomous underwater vehicle.</p>
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<p>Performance comparison between CA-SDUN, Cog-AA-RP, and Cog-DVRP for the packet delivery ratio as a function of the number of sensor nodes with different numbers of channels, <span class="html-italic">M</span>. (<b>a</b>) packet delivery ratio when <span class="html-italic">M</span> = 1; (<b>b</b>) packet delivery ratio when <span class="html-italic">M</span> = 3; and (<b>c</b>) packet delivery ratio when <span class="html-italic">M</span> = 5. CA-SDUN: cognitive acoustic software-defined underwater network; Cog-AA-RP: cognitive AUV-aided routing method integrated path planning; Cog-DVRP: cognitive diagonal and vertical routing protocol; AUV: autonomous underwater vehicle.</p>
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<p>Performance comparison between CA-SDUN, Cog-AA-RP, and Cog-DVRP for overhead ratio as a function of the number of sensor nodes with different numbers of channels, <span class="html-italic">M</span>. (<b>a</b>) overhead ratio when <span class="html-italic">M</span> = 1; (<b>b</b>) overhead ratio when <span class="html-italic">M</span> = 3; and (<b>c</b>) overhead ratio when <span class="html-italic">M</span> = 5. CA-SDUN: cognitive acoustic software-defined underwater network; Cog-AA-RP: cognitive AUV-aided routing method integrated path planning; Cog-DVRP: cognitive diagonal and vertical routing protocol; AUV: autonomous underwater vehicle.</p>
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<p>Data rate as a function of different frequencies. CA-SDUN: cognitive acoustic software-defined underwater network.</p>
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<p>Bit error rate as a function of signal-to-noise-ratio (SNR). CA-SDUN: cognitive acoustic software-defined underwater network.</p>
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4151 KiB  
Article
Laterally Loaded Single Pile Response Considering the Influence of Suction and Non-Linear Behaviour of Reinforced Concrete Sections
by Stefano Stacul, Nunziante Squeglia and Francesco Morelli
Appl. Sci. 2017, 7(12), 1310; https://doi.org/10.3390/app7121310 - 17 Dec 2017
Cited by 18 | Viewed by 5771
Abstract
A hybrid BEM-p-y curves approach was developed for the single pile analysis with free/fixed head restraint conditions. The method considers the soil non-linear behaviour by means of p-y curves in series to a multi-layered elastic half-space. The non-linearity of reinforced concrete pile sections, [...] Read more.
A hybrid BEM-p-y curves approach was developed for the single pile analysis with free/fixed head restraint conditions. The method considers the soil non-linear behaviour by means of p-y curves in series to a multi-layered elastic half-space. The non-linearity of reinforced concrete pile sections, also considering the influence of tension-stiffening, has been considered. The model reproduces the influence of suction by increasing the stress state and hence the stiffness of shallow soil-layers. Suction is modeled using the Modified-Kovacs model. The hybrid BEM-py curves method was validated by comparing results from data of 22 load tests on single piles. In addition, a detailed comparison is presented between measured and computed data on a large-diameter reinforced concrete bored single pile. Full article
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<p>Pile—discretization.</p>
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<p>Pile flexibility matrix using the elastic beam theory (auxiliary restraint approach).</p>
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<p>Scheme for the flexibility matrix of a pile modeled as a beam with variable flexural rigidity (see Equation (3)).</p>
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<p>Mindlin solution scheme.</p>
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<p>Hybrid BEM-p-y method.</p>
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<p>Flow chart of the proposed solution procedure.</p>
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<p>Adaptive step-size control.</p>
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<p>Comparison of measured and computed horizontal loads at the same displacement level: <span class="html-italic">y</span>/<span class="html-italic">D</span> = 0.5–1.5%; <span class="html-italic">y</span>/<span class="html-italic">D</span> = 2–3%; <span class="html-italic">y</span>/<span class="html-italic">D</span> = 5–6%; <span class="html-italic">y</span>/<span class="html-italic">D</span> = 9–10%.</p>
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<p>Computed “average moment-curvature” relationship for B7 pile section.</p>
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<p>Comparison of measured and computed (Huang et al. [<a href="#B43-applsci-07-01310" class="html-bibr">43</a>] and proposed method) Lateral Load vs. Head Deflection curve.</p>
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<p>Pile deflections versus depth for B7 single pile under various load levels: Computed data obtained considering suction.</p>
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<p>Pile deflections versus depth for B7 single pile under various load levels: Computed data obtained without considering suction.</p>
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<p>Computed bending moments of B7 single pile at various load levels (results obtained considering suction).</p>
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4098 KiB  
Article
Fast Object Detection in Light Field Imaging by Integrating Deep Learning with Defocusing
by Mingjun Ren, Runxing Liu, Haibo Hong, Jieji Ren and Gaobo Xiao
Appl. Sci. 2017, 7(12), 1309; https://doi.org/10.3390/app7121309 - 17 Dec 2017
Cited by 14 | Viewed by 5940
Abstract
Although four-dimensional (4D) light field imaging has many advantages over traditional two-dimensional (2D) imaging, its high computation cost often hinders the application of this technique in many fields, such as object detection and tracking. This paper presents a hybrid method to accelerate the [...] Read more.
Although four-dimensional (4D) light field imaging has many advantages over traditional two-dimensional (2D) imaging, its high computation cost often hinders the application of this technique in many fields, such as object detection and tracking. This paper presents a hybrid method to accelerate the object detection in light field imaging by integrating the deep learning with the depth estimation algorithm. The method takes full advantage of computation imaging of the light field to generate an all-in-focus image, a series of focal stacks, and multi-view images at the same time, and convolutional neural network and defocusing are consequently used to perform initial detection of the objects in three-dimensional (3D) space. The estimated depths of the detected objects are further optimized based on multi-baseline super-resolution stereo matching while efficiency is maintained, as well by compressing the searching space of the disparity. Experimental studies are conducted to demonstrate the effectiveness of the proposed method. Full article
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<p>Framework of the proposed method.</p>
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<p>Two-plane parametrization of light field. (<b>a</b>) Two-plane parametrization; (<b>b</b>) two-dimensional (2D) Cartesian ray-space diagram.</p>
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<p>The principle of digital refocusing based on two-plane parametrization of light field. (<b>a</b>) Refocusing denoted by two-plane parametrization; (<b>b</b>) Representing the four-dimensional (4D) light field by 2D (<span class="html-italic">u</span>, <span class="html-italic">s</span>); (<b>c</b>) Sampling of radiance before refocusing which focus on <span class="html-italic">ST</span> plane; and, (<b>d</b>) Sampling of radiance after refocusing which focus on <span class="html-italic">S</span>′<span class="html-italic">T</span>′ plane.</p>
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<p>The Architecture of the convolutional neural network.</p>
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<p>An illustration of depth estimation based on the defocus response of the focal stacks.</p>
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<p>Result of Mona synthetic 4D light. (<b>a</b>) The input 4D light field. (<b>b</b>) Identified objects in all focus image. (<b>c</b>) Focal stacks of object regions. (<b>d</b>) Depth estimation by defocus analysis of the down sampled focal stacks. (<b>e</b>) Depth estimation of objects by stereo matching.</p>
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<p>Application of the proposed method in real scene. (<b>a</b>) Light field data collected by Lytro Illum. (<b>b</b>) The decoded light field data. (<b>c</b>) Identified objects on all-in-focus image. (<b>d</b>) Focal stacks of object regions. (<b>e</b>) Depth estimation by defocus response. (<b>f</b>) Depth estimation per pixel by multi-baseline stereo matching.</p>
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3375 KiB  
Article
Wearable Plasma Pads for Biomedical Applications
by Junggil Kim, Kyong-Hoon Choi, Yunjung Kim, Bong Joo Park and Guangsup Cho
Appl. Sci. 2017, 7(12), 1308; https://doi.org/10.3390/app7121308 - 17 Dec 2017
Cited by 26 | Viewed by 7914
Abstract
A plasma pad that can be attached to human skin was developed for aesthetic and dermatological treatment. A polyimide film was used for the dielectric layer of the flexible pad, and high-voltage and ground electrodes were placed on the film surface. Medical gauze [...] Read more.
A plasma pad that can be attached to human skin was developed for aesthetic and dermatological treatment. A polyimide film was used for the dielectric layer of the flexible pad, and high-voltage and ground electrodes were placed on the film surface. Medical gauze covered the ground electrodes and was placed facing the skin to act as a spacer; thus, the plasma floated between the gauze and ground electrodes. In vitro and in vivo biocompatibility tests of the pad showed no cytotoxicity to normal cells and no irritation of mouse skin. Antibacterial activity was shown against Staphylococcus aureus and clinical isolates of methicillin-resistant S. aureus. Furthermore, skin wound healing with increased hair growth resulting from increased exogenous nitric oxide and capillary tube formation induced by the plasma pad was also confirmed in vivo. The present study suggests that this flexible and wearable plasma pad can be used for biomedical applications such as treatment of wounds and bacterial infections. Full article
(This article belongs to the Special Issue Smart Environment and Healthcare)
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<p>Schematic illustration of the wearable plasma pad kit and photographs of the thin-film plasma pad discharge.</p>
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<p>(<b>a</b>) Schematic illustration of the plasma pad and photographs of the thin-film plasma pad discharge; (<b>b</b>) Optical emission spectroscopy of plasma pad discharge; (<b>c</b>) Variation of temperature measured inside the pad attached to the skin with β = 100% and β = 50% during 1 h operation; (<b>d</b>) Ozone concentration according to the duty ratio at the distances of d = 10 cm and d = 20 cm over the plasma surface.</p>
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<p>(<b>a</b>) Schematic of the plasma pad attached to a glass plate and (<b>b</b>) a photograph of plasma pad discharge under a glass plate.</p>
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<p>In vitro and in vivo biocompatibility of the plasma pad. (<b>a</b>) Quantitative analysis of in vitro cytotoxicity of the plasma pad on GFP-transfected human keratinocytes (HaCaT cells) and mouse fibroblasts (L-929 cells). (<span class="html-italic">n</span> = 4, * <span class="html-italic">P</span> &lt; 0.05 compared to control); (<b>b</b>) Images of plasma-treated GFP-transfected HaCaT cells and L-929 cells. The images are magnified from those inserted in each picture taken with a 4× optical lens. Scale bars are 100 μm; (<b>c</b>) Schematic illustration for evaluating the in vivo skin irritation test using the plasma pad; (<b>d</b>) Photographs and histological images of mouse skin at day 2 post-plasma treatment for 10 min. Scale bars represent 200 μm.</p>
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<p>Exogenous nitric oxide (<math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>NO</mi> </mrow> <mn>2</mn> <mo>−</mo> </msubsup> </mrow> </semantics> </math>) and in vitro capillary tube formation with plasma treatment. (<b>a</b>) Quantitative analysis of <math display="inline"> <semantics> <mrow> <msubsup> <mrow> <mi>NO</mi> </mrow> <mn>2</mn> <mo>−</mo> </msubsup> </mrow> </semantics> </math> generated by a plasma pad (<span class="html-italic">n</span> = 4, * <span class="html-italic">P</span> &lt; 0.005, ** <span class="html-italic">P</span> &lt; 0.0005 compared to control); (<b>b</b>) Images of capillary tube formation by HDMVECs with plasma treatment and quantitative analysis of capillary tube length (<span class="html-italic">n</span> = 5, * <span class="html-italic">P</span> &lt; 0.005, ** <span class="html-italic">P</span> &lt; 0.0005 compared to control). Scale bars are 100 μm.</p>
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<p>In vivo wound healing effects of plasma pads in the full-thickness excisional wound splinting model. (<b>a</b>) Quantification of the wound closure rate following wounding. (<span class="html-italic">n</span> = 8, * <span class="html-italic">P</span> &lt; 0.05 compared to control); (<b>b</b>) Representative stereomicroscopic images of full-thickness wound sites and wound contraction at Days 0 and 21. Scale bars are 2 mm; (<b>c</b>) Histological images of hematoxylin and eosin (H&amp;E) staining of negative control and plasma-treated skin. Scale bars are 500 μm; (<b>d</b>) Quantitative hair follicle assessment in repaired wound sites. Total and hair follicles at each stage (anagen, catagen, and telogen) were determined after H&amp;E staining (<span class="html-italic">n</span> = 8, * <span class="html-italic">P</span> &lt; 0.05 compared to control).</p>
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<p>Antibacterial activity of the plasma pad. Viable bacterial cells were counted after 24 h post-plasma treatment. Differences of <span class="html-italic">P</span> &lt; 0.05 were considered statistically significant (<span class="html-italic">n</span> = 3, <span class="html-italic">* P</span> &lt; 0.05, <span class="html-italic">** P</span> &lt; 0.005 compared to the control).</p>
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3935 KiB  
Article
Intensification of Organophosphorus Hydrolase Synthesis by Using Substances with Gas-Transport Function
by Olga Senko, Nikolay Stepanov, Andrey Tyutyunov, Sergey Sterlin, Vitaly Grinberg, Tatiana Makhlis and Elena Efremenko
Appl. Sci. 2017, 7(12), 1305; https://doi.org/10.3390/app7121305 - 17 Dec 2017
Cited by 3 | Viewed by 3806
Abstract
We have performed studies and comparative analysis of the biosynthesis characteristics of intracellular recombinant enzyme, such as hexahistidine-containing organophosphorus hydrolase (His6-OPH) in Escherichia coli SG13009[pREP4] cells when various perfluorocarbon compounds (PFC) were introduced into the medium for cell cultivation. The PFC [...] Read more.
We have performed studies and comparative analysis of the biosynthesis characteristics of intracellular recombinant enzyme, such as hexahistidine-containing organophosphorus hydrolase (His6-OPH) in Escherichia coli SG13009[pREP4] cells when various perfluorocarbon compounds (PFC) were introduced into the medium for cell cultivation. The PFC were found to facilitate the biosynthesis of His6-OPH: increased levels of the total OPH-activity (up to 37%) were measured upon introduction of 1,1,1,2,2,3,3,4,4,5,5,6,6,6-tetradecafluorohexane (PFH) and 4,7,10,13,16,19,22,25,28,31-decaoxaperfluoro-5,8,11,14,17,18,21,24,27,30-decamethyl tetratriacontane (Polyether II) into culture medium. We have demonstrated the possibility of effective and multiple (at least five-fold) use of PFH for biosynthesis of intracellular recombinant protein His6-OPH, which catalyzes the hydrolysis of organophosphorus pesticides (OP), is widely used in agriculture and can be applied as new antidote for OP-detoxification in vivo. The multiple use of PFH was achieved through recycling of this substance: sediment of Escherichia coli SG13009[pREP4] cell biomass was collected at the end of each culture growing step and disintegrated with ultrasound, and obtained residue containing almost all of the initially introduced PFC was then added to the medium at the start of the following culture growing step. Full article
(This article belongs to the Section Chemical and Molecular Sciences)
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<p>The accumulated biomass of <span class="html-italic">E. coli</span> SG13009[pREP4] cells (<b>a</b>) and His<sub>6</sub>-OPH-activity in the cells (<b>b</b>) vs. initial concentration of the additive (●—PFH, ▲—polyether I, ▲—PFD, ♦—polyether II) Control sample (without PFC additives) is marked by dashed line.</p>
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<p>General scheme of the recycling process of perfluorohexane (PFH) present in the disintegrated biomass.</p>
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<p>Accumulation of the total His<sub>6</sub>-OPH activity in the course of multiple batch re-use of PFH (white bars–control, black bars—cells cultivated in the medium containing 0.5% (<span class="html-italic">v</span>/<span class="html-italic">v</span>) of PFH).</p>
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<p>The electrophoregram conducted under non-denaturing (<b>a</b>) (1—without PFH addition, 2—with PFH addition) and denaturing (<b>b</b>) conditions (1–3 without PFH addition, 4–6 with PFH addition, the 1,4—total protein fractions; 2,5—insoluble protein fractions, 3,6—soluble fraction), reflecting the impact of the presence of PFH in the culture medium on the biosynthesis of OPH. M—markers of molecular weight.</p>
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8529 KiB  
Article
An NHPP Software Reliability Model with S-Shaped Growth Curve Subject to Random Operating Environments and Optimal Release Time
by Kwang Yoon Song, In Hong Chang and Hoang Pham
Appl. Sci. 2017, 7(12), 1304; https://doi.org/10.3390/app7121304 - 16 Dec 2017
Cited by 30 | Viewed by 5586
Abstract
The failure of a computer system because of a software failure can lead to tremendous losses to society; therefore, software reliability is a critical issue in software development. As software has become more prevalent, software reliability has also become a major concern in [...] Read more.
The failure of a computer system because of a software failure can lead to tremendous losses to society; therefore, software reliability is a critical issue in software development. As software has become more prevalent, software reliability has also become a major concern in software development. We need to predict the fluctuations in software reliability and reduce the cost of software testing: therefore, a software development process that considers the release time, cost, reliability, and risk is indispensable. We thus need to develop a model to accurately predict the defects in new software products. In this paper, we propose a new non-homogeneous Poisson process (NHPP) software reliability model, with S-shaped growth curve for use during the software development process, and relate it to a fault detection rate function when considering random operating environments. An explicit mean value function solution for the proposed model is presented. Examples are provided to illustrate the goodness-of-fit of the proposed model, along with several existing NHPP models that are based on two sets of failure data collected from software applications. The results show that the proposed model fits the data more closely than other existing NHPP models to a significant extent. Finally, we propose a model to determine optimal release policies, in which the total software system cost is minimized depending on the given environment. Full article
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<p>System cost model infrastructure.</p>
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<p>Mean value function of the ten models for DS1.</p>
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<p>Mean value function of the ten models for DS2.</p>
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<p>Mean value function of the ten models for DS3.</p>
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<p>95% confidence limits of the newly proposed model for DS1.</p>
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<p>95% confidence limits of the newly proposed model for DS2.</p>
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<p>95% confidence limits of the newly proposed model for DS3.</p>
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<p>Relative error of the ten models for DS1.</p>
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<p>Relative error of the ten models for DS2.</p>
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<p>Relative error of the ten models for DS3.</p>
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<p>Expected total cost for the baseline case.</p>
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<p>Expected total cost subject to the warranty period for the 1st condition.</p>
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<p>Expected total cost subject to the warranty period for the 2nd condition.</p>
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<p>Expected total cost subject to the warranty period for the 3rd condition.</p>
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<p>Expected total cost according to cost coefficient C<sub>2</sub> for the 2nd condition.</p>
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<p>Expected total cost according to cost coefficient C<sub>4</sub> for the 1st condition.</p>
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<p>Expected total cost according to cost coefficient C<sub>4</sub> for the 2nd condition.</p>
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<p>Expected total cost according to cost coefficient C<sub>4</sub> for the 3rd condition.</p>
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2068 KiB  
Article
The Use of Heat-Resistant Concrete Made with Ceramic Sanitary Ware Waste for a Thermal Energy Storage
by Paweł Ogrodnik, Bartosz Zegardło and Maciej Szeląg
Appl. Sci. 2017, 7(12), 1303; https://doi.org/10.3390/app7121303 - 16 Dec 2017
Cited by 29 | Viewed by 6356
Abstract
The paper presents the results obtained in the course of a study on the concrete made of aggregate obtained from wastes of sanitary ceramics. Previous examinations proved high in strength and durability of concrete of this type, and it showed a resistance to [...] Read more.
The paper presents the results obtained in the course of a study on the concrete made of aggregate obtained from wastes of sanitary ceramics. Previous examinations proved high in strength and durability of concrete of this type, and it showed a resistance to high temperatures. The material was classified as a fireproof concrete. While searching for the optimal applications of such concrete, a series of examinations and analyses on its thermal energy storage (TES) properties were performed. This paper describes the two-stage experiment on the thermal behavior of the concrete made with sanitary ceramic wastes during cooling processes in comparison to different building materials subjected to the same thermal conditions. On the basis of the thermal, infrared analysis, and suitable calculations, the thermal power and the ability of the composite to store thermal energy was estimated. Finally, it was stated that the concrete made of sanitary ceramic waste aggregate and alumina cement can be recommended as a heat-accumulating material, and in combination with high durability can be used, e.g., for the construction of fireplace bodies. Full article
(This article belongs to the Section Materials Science and Engineering)
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<p>The samples used for testing: (<b>a</b>) in a laboratory dryer; and (<b>b</b>) on the temperature measurement stand.</p>
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<p>The furnace used in the study: (<b>a</b>) scheme; and (<b>b</b>) real image.</p>
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<p>Thermal images of materials tested after 3 min of cooling.</p>
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<p>A temperature drop of the materials during cooling on the first stage of the experiment; S: steel; AC: aerated concrete; SLB: sand-lime brick; CB: ceramic brick; FB: fireclay brick; CGA-PC: concrete with gravel aggregate and Portland cement; CGA-AC: concrete with gravel aggregate and alumina cement; CCA-PC: concrete with ceramic aggregate and Portland cement; CCA-AC: concrete with ceramic aggregate and alumina cement; G: granite.</p>
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<p>The relation of the temperature drop as a function of the cooling time during the second stage of the experiment; designations are the same as for <a href="#applsci-07-01303-f004" class="html-fig">Figure 4</a>.</p>
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<p>Comparison of the materials’ thermal power between the results obtained in the course of the first and the second stages of the experiment.</p>
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<p>Surface of CCA-AC (<b>left</b>) and CGA-AC (<b>right</b>) samples after heating at 400 °C.</p>
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28566 KiB  
Article
Printing Speed and Quality Enhancement by Controlling the Surface Energy of Cliché in Reverse Offset Printing
by Young Tae Cho, Yeonho Jeong, Youn Jae Kim, Sin Kwon, Seung-Hyun Lee, Kwang Young Kim, Dongwoo Kang and Taik-Min Lee
Appl. Sci. 2017, 7(12), 1302; https://doi.org/10.3390/app7121302 - 15 Dec 2017
Cited by 13 | Viewed by 6961
Abstract
Printed electronics is one of the emerging technologies owing to its low cost and productivity. Recently, many researchers tried to adapt printing technology to the fabrication of fine electronic patterns on flexible substrates, including the gate line of thin film transistors. In this [...] Read more.
Printed electronics is one of the emerging technologies owing to its low cost and productivity. Recently, many researchers tried to adapt printing technology to the fabrication of fine electronic patterns on flexible substrates, including the gate line of thin film transistors. In this study, we fabricated a flexible cliché using the nanoimprint process and used it in reverse offset printing. Then, we analyzed the effect of the surface energy of the imprinted cliché on process parameters, such as printing speed and rolling direction. We showed that the productivity of the process and quality of printed pattern can be considerably enhanced by controlling the surface energy of the cliché. When a flexible cliché is manufactured using a resin with a surface energy considerably different from that of the blanket, the ink can be detached easily and fine patterns can be engraved successfully regardless of the pattern shape. Full article
(This article belongs to the Special Issue Thin-Film Transistor)
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<p>Silicon master mold with a line and space pattern for the UV-NIL process to fabricate the cliché.</p>
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<p>Fabricated flexible cliché using UV-curable resin by the NIL process.</p>
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<p>The schematic explanation of reverse offset printing process.</p>
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<p>Reverse offset printing equipment used in this experiment.</p>
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<p>Results for printed pattern with 2-μm line width in reverse offset printing: (<b>a</b>) 1 mm/s, (<b>b</b>) 10 mm/s, and (<b>c</b>) 20 mm/s printing speed using PUA1 (surface energy: 21.5 mN/m); (<b>d</b>) 1 mm/s, (<b>e</b>) 10 mm/s, and (<b>f</b>) 20 mm/s printing speed using PUA4 (surface energy: 30.5 mN/m); and (<b>g</b>) 1 mm/s, (<b>h</b>) 10 mm/s, and (<b>i</b>) 20 mm/s printing speed using PUA5 (surface energy: 79.1 mN/m).</p>
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<p>Results for the printed pattern with a 2-μm line width in reverse offset printing using PUA5 resin as the cliché material with the highest surface energy (79.1 mN/m) at printing speeds ranging from 25 mm/s to 50 mm/s.</p>
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<p>Maximum allowable printing speed according to the surface energy difference between the blanket and the flexible cliché.</p>
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<p>Angle dependency of printed pattern using cliché fabricated from different resins.</p>
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