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Volume 13
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Appl. Sci., Volume 13, Issue 20 (October-2 2023) – 492 articles

Cover Story (view full-size image): The aerospace industry is one of the leading figures in the development and improvement of techniques for the design of new products. One of the most promising developments of recent decades is the exploitation of digital models that make it possible to evaluate design solutions and simulate the behavior of individual systems as well as their interactions. The goal is to be able to predict and analyze all aspects of an aircraft much in advance of its industrialization in order to heavily reduce the time as well as costs of product development and to guarantee the flexibility to test a multitude of solutions. The main issue in this context is the complexity of creating models that are capable of accurately sizing and simulating multiple interacting systems, thus considering the constraints imposed by the need for their mutual compatibility. View this paper
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19 pages, 454 KiB  
Article
Social Network Sentiment Analysis Using Hybrid Deep Learning Models
by Noemí Merayo, Jesús Vegas, César Llamas and Patricia Fernández
Appl. Sci. 2023, 13(20), 11608; https://doi.org/10.3390/app132011608 - 23 Oct 2023
Cited by 4 | Viewed by 2185
Abstract
The exponential growth in information on the Internet, particularly within social networks, highlights the importance of sentiment and opinion analysis. The intrinsic characteristics of the Spanish language coupled with the short length and lack of context of messages on social media pose a [...] Read more.
The exponential growth in information on the Internet, particularly within social networks, highlights the importance of sentiment and opinion analysis. The intrinsic characteristics of the Spanish language coupled with the short length and lack of context of messages on social media pose a challenge for sentiment analysis in social networks. In this study, we present a hybrid deep learning model combining convolutional and long short-term memory layers to detect polarity levels in Twitter for the Spanish language. Our model significantly improved the accuracy of existing approaches by up to 20%, achieving accuracies of around 76% for three polarities (positive, negative, neutral) and 91% for two polarities (positive, negative). Full article
(This article belongs to the Special Issue New Techniques of Machine Learning and Deep Learning in Text Classification)
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<p>Block diagram of our proposed hybrid model showing the different layers.</p> Full article ">Figure 2
<p>Final composition of the hybrid deep learning network model: (<b>a</b>) embedding layer, (<b>b</b>) one-dimensional convolutional layer (Conv1D), (<b>c</b>) MaxPooling layer, (<b>d</b>) LSTM layer, and (<b>e</b>) dense layer.</p> Full article ">Figure 3
<p>Confusion matrix of our hybrid model for the 3 considered classes (P, NONE, N), showing the number of cases assigned to each input class. The x-axis represents the real values, and the y-axis represents the classification or predicted values.</p> Full article ">
17 pages, 4631 KiB  
Article
Experimental Study on the Influence of Different Dam Body on the Sediment Interception and Discharge Capacity of the Cascade Permeable Dams
by Jian Liu, Hongwei Zhou, Longyang Pan, Junyi Cai, Niannian Li and Mingyang Wang
Appl. Sci. 2023, 13(20), 11607; https://doi.org/10.3390/app132011607 - 23 Oct 2023
Viewed by 1036
Abstract
Sediment deposition is an ecological and environmental problem faced by most water bodies. In view of the poor structural stability and unrepeatable use of existing permeable structures, this paper proposes a cascade permeable dam, which consists of four dam bodies. As the composition [...] Read more.
Sediment deposition is an ecological and environmental problem faced by most water bodies. In view of the poor structural stability and unrepeatable use of existing permeable structures, this paper proposes a cascade permeable dam, which consists of four dam bodies. As the composition of the dam material is the key to sediment interception and discharge capacity, this study sets up two groups of dam material particle sizes for experiments. The results show that the sediment interception performance of the cascade permeable dam is good. When the dam material with a small particle size is selected, the percentage of intercepted sediment mass inside the four dam bodies is 75–89%. The interception sediment rate is much greater than that of the dam material with a large particle size, which tends to decline one by one along the flow direction. The discharge capacity of the dam gradually decreases with time, and there is an obvious decrease in the permeability coefficient of 1# dam. The results of this study provide programmatic support for reducing sediment entering shallow lakes and rivers, which can further optimize the structure design of permeable dams. Full article
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<p>Study Area—the Xinglong Lake in Luxi River (The red dot represents the location of cascade permeable dam).</p> Full article ">Figure 2
<p>Schematic diagram of the experimental setup: (<b>a</b>) Side view; (<b>b</b>) Top view; (<b>c</b>) Layout of the cascade permeable dam; (<b>d</b>) Sediment interception in pre-dam.The triangle in (<b>a</b>) marks the water sampling position in the experiments.</p> Full article ">Figure 3
<p>Percentage distribution of intercepted sediment mass by a permeable dam along the flow direction.</p> Full article ">Figure 4
<p>Variation curve of the relative water in front of each dam.</p> Full article ">Figure 5
<p>Curves of the water level difference of the dams along the flow direction.</p> Full article ">Figure 6
<p>Variation curve of the permeable coefficient of 1–3# dam body.</p> Full article ">Figure 7
<p>Turbidity variation curve at different locations in the main flume and at the outlet for small particle size (the black line is the fitted curve for the total turbidity removal rate).</p> Full article ">Figure 8
<p>Turbidity variation curve at different locations in the main flume and at the outlet for large particle size (the black line is the fitted curve for the total turbidity removal rate).</p> Full article ">Figure 9
<p>Distribution of the intercepted sediment mass along the flow direction: (<b>a</b>) 1# Dam; (<b>b</b>) 2# Dam; (<b>c</b>) 3# Dam; (<b>d</b>) 4# Dam.</p> Full article ">Figure 10
<p>Sediment interception rate along the flow direction: (<b>a</b>) Q = 300 L/H; (<b>b</b>) Q = 500 L/H; (<b>c</b>) Q = 700 L/H.</p> Full article ">
23 pages, 969 KiB  
Article
Bayesian Optimal Experimental Design for Race Tracking in Resin Transfer Moulding
by Nicholas Wright, Piaras Kelly, Oliver Maclaren, Ruanui Nicholson and Suresh Advani
Appl. Sci. 2023, 13(20), 11606; https://doi.org/10.3390/app132011606 - 23 Oct 2023
Viewed by 894
Abstract
A Bayesian inference formulation is applied to the Resin Transfer Moulding process to estimate bulk permeability and race-tracking effects using measured values of pressure at discrete sensor locations throughout a preform. The algorithm quantifies uncertainty in both the permeability and race-tracking effects, which [...] Read more.
A Bayesian inference formulation is applied to the Resin Transfer Moulding process to estimate bulk permeability and race-tracking effects using measured values of pressure at discrete sensor locations throughout a preform. The algorithm quantifies uncertainty in both the permeability and race-tracking effects, which decreases when more sensors are used or the preform geometry is less complex. We show that this approach becomes less reliable with a smaller resin exit vent. Numerical experiments show that the formulation can accurately predict race-tracking effects with few measurements. A Bayesian A-optimality formulation is used to develop a method for producing optimal sensor locations that reduce the uncertainty in the permeability and race-tracking estimates the most. This method is applied to two numerical examples which show that optimal designs reduce uncertainty by up to an order of magnitude compared to a random design. Full article
(This article belongs to the Section Mechanical Engineering)
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<p>Control volumes (blue) offset from the triangular finite elements (black) for a basic mesh (a more complex mesh is used in the numerical simulations).</p> Full article ">Figure 2
<p>Domain for Model 1, representing a rectangular part with a square block at the centre. Race-tracking regions are indicated in blue and are numbered.</p> Full article ">Figure 3
<p>Domain for Model 2, representing a rectangular part with two square blocks. Each race-tracking region is labelled in blue and numbered.</p> Full article ">Figure 4
<p>Marginal prior (red) and posterior (blue) distributions for Model 1 with 2 sensors. Truth is shown with a black dashed line. Note that these distributions are presented on separate <span class="html-italic">y</span>-axes, for ease of comparison.</p> Full article ">Figure 5
<p>Marginal prior (red) and posterior (blue) distributions for Model 1 with 10 sensors. Truth is shown with a black dashed line. Note that these distributions are presented on separate <span class="html-italic">y</span>-axes, for ease of comparison.</p> Full article ">Figure 6
<p>Marginal prior (red) and posterior (blue) distributions for Model 2 with 10 sensors. Truth is shown with a black dashed line. Note that these distributions are associated with separate y-axes, for ease of comparison. For presentation, <math display="inline"><semantics> <msub> <mi>α</mi> <mn>10</mn> </msub> </semantics></math> is also omitted.</p> Full article ">Figure 7
<p>The positions within the domain of the optimal sensor locations, as determined by the greedy algorithm for Model 1. Sensors are indicated in red and numbered in the order they appear in the greedy algorithm—i.e., the optimal locations of four sensors are locations 1, 2, 3, and 4. All candidate locations are shown in grey.</p> Full article ">Figure 8
<p>(<b>Top:</b>) Sum of the trace of the posterior covariance over all simulations versus the number of sensors used. The optimal solution is shown in red, and random solutions are shown in blue. (<b>Bottom:</b>) Individual variances of each posterior parameter (log scale), for the optimal design.</p> Full article ">Figure 9
<p>MAP estimate (solid line) and 99% confidence intervals (shaded region) for each parameter versus the number of sensors used, in the optimal locations. The true value of each parameter is indicated with a dashed line.</p> Full article ">Figure 10
<p>An example of pressure measurements over time from a sensor located at (0.45 m, 0.175 m) in Model 1 (blue). This simulation uses a small 5 mm vent.</p> Full article ">Figure 11
<p>The true posteriors visualised for a one-parameter formulation.</p> Full article ">Figure A1
<p>Numbered optimal sensor locations, as determined by the greedy algorithm. Sensors are numbered in the order they appear in the greedy algorithm—i.e., the optimal locations of 4 sensors are locations 1, 2, 3, and 4. All candidate locations are shown in grey.</p> Full article ">Figure A2
<p>Sum of the covariance trace over all simulations versus the number of sensors used. The optimal solution is in red, and random solutions are in blue.</p> Full article ">Figure A3
<p>Average covariance trace in the training set vs. the test set, when an increasing number of training samples are considered.</p> Full article ">
21 pages, 1140 KiB  
Article
The Dose-Dependent Role of Sage, Clove, and Pine Essential Oils in Modulating Ruminal Fermentation and Biohydrogenation of Polyunsaturated Fatty Acids: A Promising Strategy to Reduce Methane Emissions and Enhance the Nutritional Profile of Ruminant Products
by Mostafa Bokharaeian, Taghi Ghoorchi, Abdolhakim Toghdory and Iman Janghorban Esfahani
Appl. Sci. 2023, 13(20), 11605; https://doi.org/10.3390/app132011605 - 23 Oct 2023
Cited by 3 | Viewed by 1120
Abstract
The livestock industry significantly contributes to greenhouse gas emissions, with ruminant animals, including cows, sheep, and goats, being responsible for a substantial share of these emissions due to methane production. Reducing methane emissions from ruminants is crucial for mitigating the environmental impact of [...] Read more.
The livestock industry significantly contributes to greenhouse gas emissions, with ruminant animals, including cows, sheep, and goats, being responsible for a substantial share of these emissions due to methane production. Reducing methane emissions from ruminants is crucial for mitigating the environmental impact of livestock production. Additionally, there has been a growing interest in improving the nutritional quality of ruminant products through modifying their profile of fatty acids. The current study aimed to investigate the potential of sage (SAG), pine (PIN), and clove (CLO) essential oils as natural additives for modulating in vitro ruminal fermentation characteristics and biohydrogenation of polyunsaturated fatty acids (PUFA). Within the current experiment, three dose levels (300, 600, and 900 mg/L) of essential oils were evaluated using rumen inoculum from three mature Dalagh ewes (58 ± 2.84 kg body weight). The results revealed that the essential oils had a significant impact on gas production, methane and carbon dioxide production, ruminal fermentation parameters, and ruminal biohydrogenation of dietary PUFAs. The essential oil treatments resulted in reduced gas production compared with the control group. Methane production was significantly reduced by all doses of the essential oils, with the highest dose of CLO resulting in the lowest methane production. In addition, the essential oils affected ruminal fermentation parameters, including pH, ammonia concentration, and production of total volatile fatty acids. Promising modifications in ruminal biohydrogenation of PUFAs and the profile of fatty acids were also observed in the current study. These findings suggest that SAG, Pin, and CLO hold promise in mitigating methane emissions and improve the nutritional value of ruminant products. Further investigation is required to evaluate their effectiveness in practical feeding strategies for livestock. Full article
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<p>The effects of SAG, PIN, and CLO at inclusion levels of 0 (CON), 300, 600, and 900 mg/L on the in vitro cumulative gas production over 120 h. CON, SAG, PIN, and CLO represent control, sage essential oil, pine essential oil, and clove essential oil, respectively. In addition, 300, 600, and 900 represent corresponding dose levels in mg/L of each essential oils in the in vitro rumen culture.</p> Full article ">Figure 2
<p>Regression analysis for the effects of various dose levels (0, 300, 600, and 900 mg/L) of SAG, PIN, and CLO on methane (CH<sub>4</sub>) and carbon dioxide (CO<sub>2</sub>) production (mL) in vitro.</p> Full article ">
17 pages, 7675 KiB  
Article
Carbon Dioxide Fluxes and Influencing Factors in the Momoge Salt Marsh Ecosystem, Jilin Province, China
by Qiongfang Ma, Chaofan Zhang, Ling Chen, Mingyuan Yao, Fan Yang, Hong Yan and Wei Li
Appl. Sci. 2023, 13(20), 11604; https://doi.org/10.3390/app132011604 - 23 Oct 2023
Viewed by 900
Abstract
This study observed the characteristics and influencing factors of the carbon fluxes of the Momoge salt marsh ecosystem over four years, which behaves as a CO2 sink. The daily, seasonal, and interannual variations in CO2 fluxes in the Momoge salt marshes [...] Read more.
This study observed the characteristics and influencing factors of the carbon fluxes of the Momoge salt marsh ecosystem over four years, which behaves as a CO2 sink. The daily, seasonal, and interannual variations in CO2 fluxes in the Momoge salt marshes were observed using the eddy covariance method and were compared with various environmental factors. An overall daily “U”-shaped distribution was observed, with uptake during the day (negative values) and release at night (positive values). Annually, the carbon fluxes in the study area roughly exhibited a “V” shape. The carbon fluxes during the non-growing season predominantly showed positive values, indicating the release of CO2 into the atmosphere. Photosynthetically active radiation was the primary influencing factor affecting the hourly and daytime variations in net ecosystem exchange (NEE) during the growing season, while temperature was the main factor influencing nighttime NEE dynamics. The air temperature, soil temperature, photosynthetically active radiation, precipitation, and water level all had significant impacts on the daily net CO2 exchange. At the monthly scale, larger values of soil temperature, air temperature, photosynthetically active radiation, and aboveground biomass corresponded to a stronger carbon absorption capacity of the ecosystem. Overall, temperature remains the primary factor for carbon fluxes in the Momoge wetlands. Full article
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<p>Study area’s location.</p> Full article ">Figure 2
<p>Eddy correlation system and vegetation in monitoring area.</p> Full article ">Figure 3
<p>Daily dynamics of net ecosystem carbon exchange in different months (2015).</p> Full article ">Figure 4
<p>Daily dynamics of net ecosystem carbon exchange in different months (2016).</p> Full article ">Figure 5
<p>Daily dynamics of net ecosystem carbon exchange in different months (2017).</p> Full article ">Figure 6
<p>Daily dynamics of net ecosystem carbon exchange in different months (2021).</p> Full article ">Figure 7
<p>Total daily cumulative values of net ecosystem carbon exchange (NEE).</p> Full article ">Figure 8
<p>Total daily cumulative values of ecosystem respiration (RE).</p> Full article ">Figure 9
<p>Total daily cumulative values of the ecosystem’s total gross primary productivity (GPP).</p> Full article ">Figure 10
<p>Seasonal dynamics of monthly mean net ecosystem carbon exchange (NEE) in the Momoge salt marsh. Different lowercase letters indicate significant difference (<span class="html-italic">p</span> &lt; 0.05) among different years in the same month, ns indicates no significant difference.</p> Full article ">Figure 11
<p>Response of daytime net ecosystem carbon exchange (NEE) to photosynthetically active radiation (PAR).</p> Full article ">Figure 12
<p>Relationship between nighttime net ecosystem exchange (NEE) and temperature of soil (Tsoil) at depth of 5 cm. *** represents a significance level of <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 13
<p>Relationship between nighttime net ecosystem exchange (NEE) and air temperature (Tair). *** represents a significance level of <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 14
<p>Net ecosystem exchange (NEE) correlations with environmental and biological factors at the monthly scale for 2015–2017 and 2021. (<b>a</b>) Air temperature (Tair), (<b>b</b>) soil water content at depth of 5 cm (Tsoil), (<b>c</b>) photosynthetically active radiation (PAR), (<b>d</b>) rainfall (PPT), (<b>e</b>) water level (WL), and (<b>f</b>) aboveground biomass (AGB). The error line represents the standard deviation of the means.</p> Full article ">
18 pages, 4832 KiB  
Article
A Study on Analyses of the Production Data of Feed Crops and Vulnerability to Climate Impacts According to Climate Change in Republic of Korea
by MoonSun Shin, Seonmin Hwang, Junghwan Kim, Byungcheol Kim and Jeong-Sung Jung
Appl. Sci. 2023, 13(20), 11603; https://doi.org/10.3390/app132011603 - 23 Oct 2023
Viewed by 1400
Abstract
According to the climate change scenario, climate change in the Korean Peninsula is expected to worsen due to extreme temperatures, with effects such as rising average temperatures, heat waves, and droughts. In Republic of Korea, which relies on foreign countries for the supply [...] Read more.
According to the climate change scenario, climate change in the Korean Peninsula is expected to worsen due to extreme temperatures, with effects such as rising average temperatures, heat waves, and droughts. In Republic of Korea, which relies on foreign countries for the supply of forage crops, a decrease in the productivity of forage crops is expected to cause increased damage to the domestic livestock industry. In this paper, to solve the issue of climate vulnerability for forage crops, we performed a study to predict the productivity of forage crops in relation to climate change. We surveyed and compiled not only forage crop production data from various regions, but also experimental cultivation production data over several years from reports of the Korea Institute of Animal Science and Technology. Then, we crawled related climate data from the Korea Meteorological Administration. Therefore, we were able to construct a basic database for forage crop production data and related climate data. Using the database, a production prediction model was implemented, applying a multivariate regression analysis and deep learning regression. The key factors were determined as a result of analyzing the changes in forage crop production due to climate change. Using the prediction model, it could be possible to forecast the shifting locations of suitable cultivation areas. As a result of our study, we were able to construct electromagnetic climate maps for forage crops in Republic of Korea. It can be used to present region-specific agricultural insights and guidelines for cultivation technology for forage crops against climate change. Full article
(This article belongs to the Special Issue Recent Advances in Precision Farming and Digital Agriculture)
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<p>Climate change on the Korean Peninsula (RCP 8.5).</p> Full article ">Figure 2
<p>A framework of the research methodology process.</p> Full article ">Figure 3
<p>Preprocessed dataset of IRG.</p> Full article ">Figure 4
<p>Preprocessed dataset of forage grass.</p> Full article ">Figure 5
<p>Graphs of correlation analysis results with IRG dataset.</p> Full article ">Figure 6
<p>Graphs of correlation analysis results with the forage grass dataset.</p> Full article ">Figure 7
<p>Electromagnetic climate map of suitable cultivation areas for IRG.</p> Full article ">Figure 8
<p>Electromagnetic climate map of suitable cultivation areas for forage grass.</p> Full article ">Figure 9
<p>Electromagnetic climate map applying the predictive model of forage crop productivity in Republic of Korea (2022).</p> Full article ">
19 pages, 5688 KiB  
Article
Parametric Design and Shape Sensing of Geared Back Frame Shell Structure for Floating Cylindrical Reflector Antenna off the Coast
by Mengmei Mei, He Huang, Yugang Li and Zhe Zheng
Appl. Sci. 2023, 13(20), 11602; https://doi.org/10.3390/app132011602 - 23 Oct 2023
Cited by 1 | Viewed by 992
Abstract
At present, numerous reflector antennas have been constructed worldwide on land. However, there are few applications of reflector antennas directly set off the coast. To expand the application region of reflector antennas, a floating cylindrical reflector antenna (FCRA) driven by the moving mass [...] Read more.
At present, numerous reflector antennas have been constructed worldwide on land. However, there are few applications of reflector antennas directly set off the coast. To expand the application region of reflector antennas, a floating cylindrical reflector antenna (FCRA) driven by the moving mass was developed to implement the elevation angle adjustment. Firstly, the structure design is introduced in detail. The design parameters are stated and analyzed to obtain the kinematic relationship while considering the water surface constraint. Then, the effects of each variable on the rotation capacity and structural stability are discussed. Further, the feasibility of the elevation angle adjustment process is demonstrated by using a prototype model test and software simulation. Finally, the deformation analyses and shape sensing of the back frame are carried out on the basis of the inverse finite element method (iFEM). We concluded that this new structure is feasible and expected to sit off the coast. In addition, the iFEM algorithm with sub-region reconstruction was proved to be suitable for the shape sensing of the over-constrained FCRA during the angle adjustment process via several quasi-static sampling moments. Full article
(This article belongs to the Topic Recent Advances in Structural Health Monitoring, 2nd Volume)
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<p>Structure design of FCRA. (<b>a</b>) Vertical view, (<b>b</b>) Axonometric view, (<b>c</b>) Axonometric view without semi-cylindrical shell.</p> Full article ">Figure 2
<p>Parameter definitions (upright state of FCRA).</p> Full article ">Figure 3
<p>Moving mass motion and structural rotation. (<b>a</b>) Stage 1, mass moving relative to the track, (<b>b</b>) Stage 2, structure rotation.</p> Full article ">Figure 4
<p>Left view before and after heeling.</p> Full article ">Figure 5
<p>Parameter analyses. (<b>a</b>) Curves of <span class="html-italic">a</span> − <span class="html-italic">β</span><sub>min</sub> and <span class="html-italic">a</span> − <span class="html-italic">S</span>, (<b>b</b>) Curves of <span class="html-italic">b</span> − <span class="html-italic">β</span><sub>min</sub> and <span class="html-italic">b</span> − <span class="html-italic">S</span>, (<b>c</b>) Curves of <span class="html-italic">c</span> − <span class="html-italic">β</span><sub>min</sub> and <span class="html-italic">c</span> − <span class="html-italic">S</span>, (<b>d</b>) Curves of <span class="html-italic">n</span> − <span class="html-italic">β</span><sub>min</sub> and <span class="html-italic">n</span> − <span class="html-italic">S</span>, (<b>e</b>) Curves of <span class="html-italic">a</span><sub>1</sub> − <span class="html-italic">β</span><sub>min</sub> and <span class="html-italic">a</span><sub>1</sub> − <span class="html-italic">S</span>, (<b>f</b>) Curves of <span class="html-italic">b</span><sub>1</sub> − <span class="html-italic">β</span><sub>min</sub> and <span class="html-italic">b</span><sub>1</sub> − <span class="html-italic">S</span>.</p> Full article ">Figure 6
<p>Prototype model.</p> Full article ">Figure 7
<p>Analysis model. (<b>a</b>) Model in axonometric view, (<b>b</b>) Model without shell.</p> Full article ">Figure 8
<p>Rotation process of test. (<b>a</b>) <span class="html-italic">γ</span> = 0°, <span class="html-italic">β</span> = 90°, (<b>b</b>) <span class="html-italic">γ</span> = 12.5°, <span class="html-italic">β</span> = 80°, (<b>c</b>) <span class="html-italic">γ</span> = 20°, <span class="html-italic">β</span> = 75°, (<b>d</b>) <span class="html-italic">γ</span> = 32.5°, <span class="html-italic">β</span> = 65°.</p> Full article ">Figure 9
<p>Rotation process of simulation. (<b>a</b>) <span class="html-italic">γ</span> = 0°, <span class="html-italic">β</span> = 90°, (<b>b</b>) γ = 12.5°, β = 80.13°, (<b>c</b>) <span class="html-italic">γ</span> = 20°, <span class="html-italic">β</span> = 74.21°, (<b>d</b>) <span class="html-italic">γ</span> = 32.5°, <span class="html-italic">β</span> = 64.18°.</p> Full article ">Figure 10
<p>The four-node quadrilateral shell element (iQS4). (<b>a</b>) Element local coordinates, (<b>b</b>) Isoparametric coordinates.</p> Full article ">Figure 11
<p>Discrete surface strain measurement.</p> Full article ">Figure 12
<p>Finite element model of back frame.</p> Full article ">Figure 13
<p>The FEM contours of total displacement in four rotation states. (<b>a</b>) <span class="html-italic">β</span> = 90°, <span class="html-italic">φ</span> = 0°, (<b>b</b>) <span class="html-italic">β</span> = 80°, <span class="html-italic">φ</span>= 10°, (<b>c</b>) <span class="html-italic">β</span> = 75°, <span class="html-italic">φ</span> = 15°, (<b>d</b>) <span class="html-italic">β</span> = 65°, <span class="html-italic">φ</span> = 25°.</p> Full article ">Figure 14
<p>The iFEM contours of total displacement for fine mesh in four rotation states. (<b>a</b>) <span class="html-italic">β</span> = 90°, <span class="html-italic">φ</span> = 0°, (<b>b</b>) <span class="html-italic">β</span> = 80°, <span class="html-italic">φ</span> = 10°, (<b>c</b>) <span class="html-italic">β</span> = 75°, <span class="html-italic">φ</span> = 15°, (<b>d</b>) <span class="html-italic">β</span> = 65°, <span class="html-italic">φ</span> = 25°.</p> Full article ">Figure 15
<p>The iFEM contour of total displacement for coarse mesh at <span class="html-italic">β</span> = 90°, <span class="html-italic">φ</span> = 0°.</p> Full article ">
3 pages, 166 KiB  
Editorial
Special Issue on New Trends in Nonlinear Optics in Nanostructures and Plasmonics
by Gennady M. Mikheev
Appl. Sci. 2023, 13(20), 11601; https://doi.org/10.3390/app132011601 - 23 Oct 2023
Viewed by 900
Abstract
Nonlinear optics, which emerged in the early 60s of the 20th century, immediately after the invention of powerful lasers, had a significant influence on the formation of modern photonics [...] Full article
(This article belongs to the Special Issue New Trends on Nonlinear Optics in Nanostructures and Plasmonics)
25 pages, 5175 KiB  
Article
Adaptive Smoothing for Visual Improvement of Image Quality via the p(x)-Laplacian Operator Effects of the p(x)-Laplacian Smoothing Operator on Digital Image Restoration: Contribution to an Adaptive Control Criterion
by Jean-Luc Henry, Jimmy Nagau, Jean Velin and Issa-Paul Moussa
Appl. Sci. 2023, 13(20), 11600; https://doi.org/10.3390/app132011600 - 23 Oct 2023
Cited by 1 | Viewed by 957
Abstract
This article concerns the improvement of digital image quality using mathematical tools such as nonlinear partial differential operators. In this paper, to perform smoothing on digital images, we propose to use the p(x)-Laplacian operator. Its smoothing power plays a main role in the [...] Read more.
This article concerns the improvement of digital image quality using mathematical tools such as nonlinear partial differential operators. In this paper, to perform smoothing on digital images, we propose to use the p(x)-Laplacian operator. Its smoothing power plays a main role in the restoration process. This enables us to dynamically process certain areas of an image. We used a mathematical model of image regularisation that is described by a nonlinear diffusion Equation (this diffusion is modelled by the p(x)-Laplacian operator). We implemented the continuous model in order to observe the steps of the regularisation process to understand the effects of the different parameters of the model on an image. This will enable parameters to be used and adapted in order to provide a proposed solution. Full article
(This article belongs to the Special Issue Image Processing in Biomedical Engineering—Latest Advances and Prospects)
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<p>Comparison between a degraded and a non-degraded image. Above: BMP, 2160 × 3840, 23.7 MB; below: an image which has been compressed, 2160 × 3840, 4.8 MB.</p> Full article ">Figure 2
<p>Effects of parameters <span class="html-italic">p</span> and <math display="inline"><semantics> <mi>λ</mi> </semantics></math> on the Lena image. From left to right, parameter <span class="html-italic">p</span> increases to values <math display="inline"><semantics> <mrow> <mo>{</mo> <mn>0.01</mn> <mo>;</mo> <mn>1.00</mn> <mo>;</mo> <mn>2.00</mn> <mo>}</mo> </mrow> </semantics></math>. From top to bottom, the lambda increases by taking values <math display="inline"><semantics> <mrow> <mo>{</mo> <mn>0.01</mn> <mo>;</mo> <mn>0.10</mn> <mo>;</mo> <mn>1.00</mn> <mo>}</mo> </mrow> </semantics></math>.</p> Full article ">Figure 3
<p>Illustration of the interval <math display="inline"><semantics> <msub> <mi>I</mi> <mrow> <mn>1.5</mn> </mrow> </msub> </semantics></math> effects. The (<b>first line</b>) shows the original images, the (<b>second line</b>) shows the result of the edge and noise detection, and the last line shows the result of the proposed classification. More specifically, the pixels that have a gradient value in the interval are shown in red and the pixels with a value outside of this interval are shown in green.</p> Full article ">Figure 4
<p>Illustration of the adaptive model effects on the Lena image.</p> Full article ">Figure 5
<p>Illustration the effects of the adaptive model. From top to bottom, the original images, the result of applying the Sobel filter, then the result of applying the adaptive algorithm, and finally the result of applying the Sobel filter. The application of the proposed adaptive method reduces the number of noise and contour points for the Lena image from 21,571 pixels to 19,552 pixels (a reduction of 9.35%) and for the Tiger image from 15,600 to 14,374 (a reduction of 7.86%).</p> Full article ">Figure 6
<p>Illustration of the images contained in the Berkeley database.</p> Full article ">Figure 7
<p>Illustration of the images contained in the USC-SIPI databases.</p> Full article ">Figure 8
<p>Illustration of the images contained in the KODAK database.</p> Full article ">Figure 9
<p>Illustrations of the results obtained by testing 100 images extracted from the Berkeley database with an alteration (a degraded aspect due to, for instance, bad capture or compression) with a ratio of almost 50%. From top to bottom (<b>a</b>–<b>d</b>), we note the two best results and the two worst results obtained using the PSNR and DSSIM parameters. From left to right, the original degraded image followed by the result of the application of the Sobel filter, then the result of the application of the adaptive algorithm on the degraded image, and finally, the result of the Sobel filter. In all cases, there is a decreasing number of pixels with a high gradient.</p> Full article ">Figure 10
<p>Illustration of the effects of the use of static <math display="inline"><semantics> <mi>λ</mi> </semantics></math> and dynamic <math display="inline"><semantics> <mi>λ</mi> </semantics></math> on the Lena image. (<b>Left side</b>) <math display="inline"><semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mn>1.0</mn> </mrow> </semantics></math>; (<b>Right side</b>) <math display="inline"><semantics> <mi>λ</mi> </semantics></math> is dynamic.</p> Full article ">Figure 11
<p>Results on the evolution of the PSNR according to the quality of compression.</p> Full article ">Figure 12
<p>Results on the evolution of the DSSIM according to the quality of the compression.</p> Full article ">
26 pages, 9978 KiB  
Article
Study on the Nonlinear Permeability Mechanism and Pore Structure Characteristics of Deep Confined Aquifers
by Shilong Peng, Zhijun Li, Yuhao Xu and Guangyong Cao
Appl. Sci. 2023, 13(20), 11599; https://doi.org/10.3390/app132011599 - 23 Oct 2023
Viewed by 860
Abstract
The study of deep soil mechanics is the basis of deep shaft construction. Exploring the nonlinear permeability mechanism of deep confined aquifers in depth is the prerequisite and foundation for carrying out calculations of the hydrophobic consolidation settlement of thick alluviums and preventing [...] Read more.
The study of deep soil mechanics is the basis of deep shaft construction. Exploring the nonlinear permeability mechanism of deep confined aquifers in depth is the prerequisite and foundation for carrying out calculations of the hydrophobic consolidation settlement of thick alluviums and preventing and controlling deep-well-damage disasters. Against the background of shaft damage caused by hydrophobic consolidation settlement of the bottom aquifer of thick alluviums, a joint HPLTC-HPPNP (high-pressure long-term consolidation and high-pore-pressure nonlinear permeability) test was carried out on the bottom aquifer of thick alluviums based on the ETAS test system. This paper studied the evolution law of the permeability coefficient (kv) of bottom aquifers under different heads of confined water, confining pressures (σr), permeability hydraulic gradients (i) and loading–unloading methods. The internal pore structure characteristics of clayey sand were obtained by using low-field nuclear magnetic resonance (NMR) technology to explore the clayey sand’s nonlinear permeability micro-mechanism. The research results showed that the bottom aquifer seepage volume (ΔQi) under high stress is affected by the head pressure difference and pore water dissipation, and kv decreases with an increasing σr according to the power function relationship. The influence of the hydraulic gradient (i) on kv is significantly influenced by σr. When σr  < 4 MPa, kv decreased with an increasing i, and when σr  > 4 MPa, kv increased with an increasing i first, then decreased, before then tending to be stable. Under different stress states, the T2 spectrum of clayey sand showed a bispectrum peak type, and the adsorbed water content decreased linearly with an increasing σr, while the capillary water decreased according to the power function. The content of capillary water in the permeable pores plays a key role in the permeability of clayey sand, and it has a power function relationship with σr. The research results of this paper provide a good experimental method for the study of deep soil permeability characteristics and parameter determination, provide a theoretical basis for deep alluvial hydrophobic consolidation and settlement, and further make up for the shortcomings of existing deep soil mechanics in permeability characteristics. Full article
(This article belongs to the Special Issue Recent Advances in Tunneling and Underground Space Technology)
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<p>Location map of the coal mine and geological histogram of the sampling points.</p> Full article ">Figure 2
<p>Clayey sand sample.</p> Full article ">Figure 3
<p>Environmental triaxial automated system (ETAS).</p> Full article ">Figure 4
<p>Installation of the permeation test sample.</p> Full article ">Figure 5
<p>Schematic diagram of the permeability test of clayey sand with low-confined water bearing.</p> Full article ">Figure 6
<p>Schematic diagram of the permeability test of clayey sand with high-confined water bearing.</p> Full article ">Figure 7
<p>Time history curves of low-confined water seepage discharge.</p> Full article ">Figure 7 Cont.
<p>Time history curves of low-confined water seepage discharge.</p> Full article ">Figure 8
<p>Time history curves of high-confined water seepage discharge.</p> Full article ">Figure 8 Cont.
<p>Time history curves of high-confined water seepage discharge.</p> Full article ">Figure 9
<p>Curves of the low-confined water permeability coefficient with time under different <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mi>r</mi> </msub> </mrow> </semantics></math> values.</p> Full article ">Figure 10
<p>Curves of the high-confined water permeability coefficient with time under different <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mi>r</mi> </msub> </mrow> </semantics></math> values.</p> Full article ">Figure 11
<p>Fitted curves of the <math display="inline"><semantics> <mrow> <msub> <mi>k</mi> <mi>v</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mi>r</mi> </msub> </mrow> </semantics></math> .</p> Full article ">Figure 12
<p>Relationship curves between the permeability coefficient and <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mi>r</mi> </msub> </mrow> </semantics></math> in the loading–unloading process.</p> Full article ">Figure 13
<p>Relationship between the permeability coefficient and hydraulic gradient of clayey sand.</p> Full article ">Figure 13 Cont.
<p>Relationship between the permeability coefficient and hydraulic gradient of clayey sand.</p> Full article ">Figure 14
<p>Low-temperature and high-pressure nuclear magnetic resonance test platform.</p> Full article ">Figure 15
<p>Distribution of the ‘<span class="html-italic">T</span><sub>2</sub>’ spectrum of clayey sand under different stress conditions.</p> Full article ">Figure 16
<p>Fitting curve of the capillary water and adsorbed water content with the <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mi>r</mi> </msub> </mrow> </semantics></math> in clayey sand.</p> Full article ">Figure 17
<p>Permeability mechanism of clayey sand.</p> Full article ">
18 pages, 10018 KiB  
Communication
Integral Analysis of a Vehicle and Electric Power Steering Logic for Improving Steering Feel Performance
by Seunghoon Woo, Chanwoo Heo, Man-Ok Jeong and Jun-Mo Lee
Appl. Sci. 2023, 13(20), 11598; https://doi.org/10.3390/app132011598 - 23 Oct 2023
Cited by 1 | Viewed by 3081
Abstract
This research aims to investigate steering feel by analyzing a steering system and an electric power steering logic. First, steering feel is defined based on previous research, and methods for evaluating it are discussed. Second, a sensitivity analysis is conducted by modeling our [...] Read more.
This research aims to investigate steering feel by analyzing a steering system and an electric power steering logic. First, steering feel is defined based on previous research, and methods for evaluating it are discussed. Second, a sensitivity analysis is conducted by modeling our developed vehicle and that of a competitor known for its excellent steering feel via a multi-body simulation. We then propose a straightforward method to determine the parameters associated with steering feel to achieve the desired steering characteristics. Last, by modifying the electric power steering control system, we achieve a steering feel in our vehicle that matches the desired steering characteristics. Full article
(This article belongs to the Special Issue Advances in Vehicle Dynamics and Road Safety: Technologies, Simulations and Applications)
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<p>(<b>a</b>) Steering feel performance indices in steering wheel angle and torque graph; (<b>b</b>) steering feel performance indices in lateral acceleration and steering wheel torque graph.</p> Full article ">Figure 2
<p>Steering response performance factors (Farrer [<a href="#B15-applsci-13-11598" class="html-bibr">15</a>], 1993).</p> Full article ">Figure 3
<p>Steering feeling test methods (ISO 13674-1, 2).</p> Full article ">Figure 4
<p>Free-body diagram: from the steering wheel to the pinion.</p> Full article ">Figure 5
<p>Free-body diagram: from the pinion to the tie rod.</p> Full article ">Figure 6
<p>Free-body diagram: from the tie rod to the tire.</p> Full article ">Figure 7
<p>Reverse engineering of control logic through implementing the same input and output.</p> Full article ">Figure 8
<p>Steering system model and microsection elastic deformation characteristics friction model.</p> Full article ">Figure 9
<p>Model for vehicle and control system integration characteristics.</p> Full article ">Figure 10
<p>Reliability of steering evaluation at weave test.</p> Full article ">Figure 11
<p>Reliability of steering evaluation at transition test.</p> Full article ">Figure 12
<p>Competitor vehicle modeling by reserve engineering and reliability result.</p> Full article ">Figure 13
<p>(<b>a</b>) Comparison of weave test; (<b>b</b>) comparison of transition test.</p> Full article ">Figure 14
<p>(<b>a</b>) Steering torque route twist; (<b>b</b>) decreasing stability under high-frequency assist.</p> Full article ">Figure 15
<p>Damping gain setting concept with respect to angular velocity.</p> Full article ">Figure 16
<p>(<b>a</b>) Improvement in initial response; (<b>b</b>) improvement in steering returnability.</p> Full article ">Figure 17
<p>Steering performance at various steering angular velocities.</p> Full article ">Figure 18
<p>Comparison of steering returnability during high-speed maneuver.</p> Full article ">Figure 19
<p>Effect analysis of vehicle characteristic factors.</p> Full article ">Figure 20
<p>Effect analysis of factors compared between two vehicles.</p> Full article ">Figure 21
<p>(<b>a</b>) Sinusoidal sensitivity according to tire characteristics; (<b>b</b>) sinusoidal torque build-up according to tire characteristics.</p> Full article ">Figure 22
<p>Transition characteristic according to tire characteristics.</p> Full article ">Figure 23
<p>Realizing the sinusoidal characteristic of the competitor vehicle via logic tuning.</p> Full article ">
17 pages, 2287 KiB  
Article
Research on the Comprehensive Evaluation Method of Driving Behavior of Mining Truck Drivers in an Open-Pit Mine
by Zhao Zhang, Ruixin Zhang and Jiandong Sun
Appl. Sci. 2023, 13(20), 11597; https://doi.org/10.3390/app132011597 - 23 Oct 2023
Cited by 2 | Viewed by 1123
Abstract
Trucking is an important production link in most open-pit mines, and its transportation cost accounts for more than 50% of the total production cost of open-pit mines. The quality of the driver’s driving behavior plays a crucial role in the fine control of [...] Read more.
Trucking is an important production link in most open-pit mines, and its transportation cost accounts for more than 50% of the total production cost of open-pit mines. The quality of the driver’s driving behavior plays a crucial role in the fine control of the production cost of transportation. Different from the previous evaluation studies of drivers’ driving behavior in open-pit mines, which mainly took safety driving behavior index as a factor variable, this paper puts forward a comprehensive evaluation method of driving behavior of mining truck drivers, which takes both safety driving and transportation cost as factor variables. Taking the mining truck as the research object, firstly, a scientific and reasonable data collection scheme is established, and the data information characterizing the transport state of the mining truck is obtained through data collection and analysis. Secondly, the RKNN algorithm of time series prediction and the wavelet analysis method are used to achieve noise reduction and missing processing of the original data so as to obtain accurate sample data. Then, taking the principal component analysis method as the entry point, through constructing the principal component analysis theory model, the key index system representing safe driving behavior and transportation cost is established to realize the comprehensive evaluation of the driving behavior of mining truck drivers, and the evaluation system of “standard driving”, “prudent driving” and “aggressive driving” of mining truck drivers is formulated. The results show that after noise reduction, the accuracy of mining car operation data can be improved by 7~12%, and the transportation cost can be reduced by about 5% after the driver’s operation behavior is standardized. Full article
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<p>Schematic diagram of the production cost ratio of an open-pit mine. (<b>a</b>) Open-pit mine production links. (<b>b</b>) Open-pit mine transportation link.</p> Full article ">Figure 2
<p>A schematic diagram of the whole process of mining truck transportation.</p> Full article ">Figure 3
<p>Schematic diagram of the data acquisition scheme.</p> Full article ">Figure 4
<p>Part data before and after noise reduction of running speed and position of truck No. 1. (<b>a</b>) Partial running speed data of truck No. 1. (<b>b</b>) Partial operation location data of truck No. 1.</p> Full article ">Figure 5
<p>Part data before and after noise reduction of running speed and position of truck No. 2. (<b>a</b>). Partial running speed data of truck No. 2. (<b>b</b>). Partial operation location data of truck No. 2.</p> Full article ">
20 pages, 10043 KiB  
Article
Calibration of Model Parameters for Soda Saline Soil-Subsoiling Component Interaction Based on DEM
by Min Liu, Jingli Wang, Weizhi Feng, Haiyang Jing, Yang Wang, Yingjie Guo and Tianyue Xu
Appl. Sci. 2023, 13(20), 11596; https://doi.org/10.3390/app132011596 - 23 Oct 2023
Cited by 2 | Viewed by 915
Abstract
To apply the discrete element method (DEM) to simulate the interaction process between soda saline–alkali soil and subsoiling component in Northeast China, establishing the soda saline–alkali soil particle model and selecting more accurate simulation parameters are important. In this paper, we studied the [...] Read more.
To apply the discrete element method (DEM) to simulate the interaction process between soda saline–alkali soil and subsoiling component in Northeast China, establishing the soda saline–alkali soil particle model and selecting more accurate simulation parameters are important. In this paper, we studied the soda saline–alkali soil of the Songnen Plain in China. First, we studied the geometric shape of soda saline–alkali soil particles and proposed a modeling method for single soil particles based on the multisphere combination method. Considering the cohesion of soda saline–alkali soil particles, the Hertz–Mindlin with JKR (JKR) model was used as the contact model between soil particles. Then, the calibration method was used to obtain simulation parameters of soils that are difficult to obtain experimentally. We conducted soil angle of repose (AoR) tests, the Plackett–Burman (PB) tests, and steepest ascent (SA) tests in turn to perform a sensitivity analysis for microscopic contact parameters and select the parameters that have a significant effect on the response value (static AoR), i.e., soil surface energy, soil–soil static friction coefficient, and soil–soil rolling friction coefficient. Then, the optimal combination of simulation parameters was obtained via the Box–Behnken (BB) tests, using ANOVA to optimize the multiple regression equation. Finally, the optimal parameter combination was verified by the AoR test and the direct shear (DS) test. The results showed that the parameters had good adaptability for the AoR test. However, the simulation results of the DS test were significantly different from the experimental values. Therefore, the contact model needs to be further modified by adding Bonding bonds between soil particles based on the JKR model and further correcting for Rayleigh time step, shear modulus, and surface energy. By comparing the simulation and the experimental results, it was found that the simulation results obtained from both the DS test and AoR test had relatively small errors relative to physical tests, the two trends are the same, and the values are similar. This verified the feasibility and effectiveness of the soda saline–alkali soil particle modeling method and parameter selection proposed in this paper. Full article
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<p>Administrative map of Daan City.</p> Full article ">Figure 2
<p>Saline landform pictures.</p> Full article ">Figure 3
<p>Three different shapes of soil particles.</p> Full article ">Figure 4
<p>Simulation model of three different shapes of soil particles.</p> Full article ">Figure 5
<p>Soil AoR test.</p> Full article ">Figure 6
<p>Simulation screenshot of the soil AoR test.</p> Full article ">Figure 7
<p>DS physical test.</p> Full article ">Figure 8
<p>Particle size of soda saline–alkali soil under different tillage layers.</p> Full article ">Figure 9
<p>pH value of soda saline–alkali soil under different tillage layers.</p> Full article ">Figure 10
<p>Moisture content of soda saline–alkali soil under different plow layers.</p> Full article ">Figure 11
<p>Density of soda saline–alkali soil under different plow layers.</p> Full article ">Figure 12
<p>Variation of soda saline–alkali soil firmness under different tillage depths.</p> Full article ">Figure 13
<p>Relationship curve between the actual value and predicted value of soil AOR.</p> Full article ">Figure 14
<p>Comparison of simulation static AoR test and physical static AoR test results.</p> Full article ">Figure 15
<p>Screenshot of the DS test simulation.</p> Full article ">Figure 16
<p>Comparison of simulation results and physical results.</p> Full article ">Figure 17
<p>Simulation screenshot of DS test after correction.</p> Full article ">Figure 18
<p>Comparison of simulation results and physical results after correction.</p> Full article ">Figure 19
<p>Comparison of static AoR between simulation test and physical test after correction.</p> Full article ">
15 pages, 5894 KiB  
Article
Optimal Control Strategy for Floating Offshore Wind Turbines Based on Grey Wolf Optimizer
by Seydali Ferahtia, Azeddine Houari, Mohamed Machmoum, Mourad Ait-Ahmed and Abdelhakim Saim
Appl. Sci. 2023, 13(20), 11595; https://doi.org/10.3390/app132011595 - 23 Oct 2023
Viewed by 1417
Abstract
Due to the present trend in the wind industry to operate in deep seas, floating offshore wind turbines (FOWTs) are an area of study that is expanding. FOWT platforms cause increased structural movement, which can reduce the turbine’s power production and increase structural [...] Read more.
Due to the present trend in the wind industry to operate in deep seas, floating offshore wind turbines (FOWTs) are an area of study that is expanding. FOWT platforms cause increased structural movement, which can reduce the turbine’s power production and increase structural stress. New FOWT control strategies are now required as a result. The gain-scheduled proportional-integral (GSPI) controller, one of the most used control strategies, modifies the pitch angle of the blades in the above-rated zone. However, this method necessitates considerable mathematical approximations to calculate the control advantages. This study offers an improved GSPI controller (OGSPI) that uses the grey wolf optimizer (GWO) optimization method to reduce platform motion while preserving rated power output. The GWO chooses the controller’s ideal settings. The optimization objective function incorporates decreasing the platform pitch movements, and the resulting value is used to update the solutions. The effectiveness of the GWO in locating the best solutions has been evaluated using new optimization methods. These algorithms include the COOT optimization algorithm, the sine cosine algorithm (SCA), the African vultures optimization algorithm (AVOA), the Harris hawks optimization (HHO), and the whale optimization algorithm (WOA). The final findings show that, compared to those caused by the conventional GSPI, the suggested OGSPI may successfully minimize platform motion by 50.48%. Full article
(This article belongs to the Special Issue Artificial Intelligence Applications in Smart Energy Systems)
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<p>Different floating platforms for FOWTs.</p> Full article ">Figure 2
<p>Typical wind turbine power evolution versus wind speed.</p> Full article ">Figure 3
<p>Evolution of an optimization process using the GWO.</p> Full article ">Figure 4
<p>Matlab/Simulink with OpenFast co-simulation platform.</p> Full article ">Figure 5
<p>Wave elevations as a function of the time.</p> Full article ">Figure 6
<p>Average fitness evolution.</p> Full article ">Figure 7
<p>The resulting pitch angle of the OGSPI and the GSPI as a function of the wave elevation.</p> Full article ">Figure 8
<p>The generated power using the OGSPI and the GSPI.</p> Full article ">Figure 9
<p>The platform inclinations using: (<b>right</b>)—GSPI; (<b>left</b>)—OGSPI.</p> Full article ">Figure 10
<p>The platform motions using: blue—GSPI; red—OGSPI.</p> Full article ">
20 pages, 4902 KiB  
Article
Performance Analysis of Interval Type-2 Fuzzy X¯ and R Control Charts
by Túlio S. Almeida, Amanda dos Santos Mendes, Paloma M. S. Rocha Rizol and Marcela A. G. Machado
Appl. Sci. 2023, 13(20), 11594; https://doi.org/10.3390/app132011594 - 23 Oct 2023
Cited by 1 | Viewed by 1029
Abstract
Statistical process control (SPC) is one of the most powerful techniques for improving quality, as it is able to detect special causes of problems in processes, products and services with a remarkable degree of accuracy. Among SPC tools, X¯ and R control [...] Read more.
Statistical process control (SPC) is one of the most powerful techniques for improving quality, as it is able to detect special causes of problems in processes, products and services with a remarkable degree of accuracy. Among SPC tools, X¯ and R control charts are widely employed in process monitoring. However, scenarios involving vague, imprecise and even subjective data require a type-2 fuzzy set approach. Thus, X¯ and R control charts should be coupled with interval type-2 triangular fuzzy numbers (IT2TFN) in order to add further information to traditional control charts. This paper proposes a performance analysis of IT2TFN and X¯ and R control charts by means of average run length (ARL), standard deviation of the run length (SDRL) and RL percentile. Computer simulations were carried out considering 10,000 runs to obtain ARL, SDRL and the 5th, 25th, 50th, 75th and 95th RL percentiles. Simulation results reveal that the proposed control charts increased fault detection capability (speed of response) and slightly reduced the number of false alarms in processes under control. Moreover, it was observed that, in addition to superior performance, IT2TFN X¯-R control charts proved to be more robust and flexible when compared to traditional control charts. Full article
(This article belongs to the Section Applied Industrial Technologies)
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<p>Interval type-2 triangular fuzzy number (3, 8, 12, 15, 18) in a three-dimensional space.</p> Full article ">Figure 2
<p>Interval type-2 triangular fuzzy number and the membership functions. Adapted from [<a href="#B12-applsci-13-11594" class="html-bibr">12</a>].</p> Full article ">Figure 3
<p>Interval type-2 triangular fuzzy number and the footprint of uncertainty and <math display="inline"><semantics> <mrow> <mi mathvariant="normal">H</mi> <mfenced> <mrow> <msup> <mrow> <mover> <mi mathvariant="normal">A</mi> <mo stretchy="false">˜</mo> </mover> </mrow> <mi mathvariant="normal">L</mi> </msup> </mrow> </mfenced> </mrow> </semantics></math>. Adapted from [<a href="#B12-applsci-13-11594" class="html-bibr">12</a>].</p> Full article ">Figure 4
<p>Steps of a fuzzification process for IT2TFN.</p> Full article ">Figure 5
<p>Defuzzification method. Adapted from [<a href="#B25-applsci-13-11594" class="html-bibr">25</a>].</p> Full article ">Figure 6
<p>IT2TFN <math display="inline"><semantics> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">X</mi> <mo>¯</mo> </mover> </mrow> </semantics></math> control chart example. The type-2 fuzzy mean <math display="inline"><semantics> <mrow> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">x</mi> <mo>¯</mo> </mover> </mrow> <mo>=</mo> <mfenced> <mrow> <msubsup> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">x</mi> <mo>¯</mo> </mover> </mrow> <mn>1</mn> <mi mathvariant="normal">U</mi> </msubsup> <mo>,</mo> <msubsup> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">x</mi> <mo>¯</mo> </mover> </mrow> <mn>1</mn> <mi mathvariant="normal">L</mi> </msubsup> <mo>,</mo> <msubsup> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">x</mi> <mo>¯</mo> </mover> </mrow> <mn>2</mn> <mi mathvariant="normal">U</mi> </msubsup> <mo>,</mo> <msubsup> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">x</mi> <mo>¯</mo> </mover> </mrow> <mn>3</mn> <mn>3</mn> </msubsup> <mo>,</mo> <msubsup> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">x</mi> <mo>¯</mo> </mover> </mrow> <mn>3</mn> <mi mathvariant="normal">U</mi> </msubsup> </mrow> </mfenced> </mrow> </semantics></math> is transformed into mean <math display="inline"><semantics> <mrow> <mo> </mo> <mover> <mi mathvariant="normal">X</mi> <mo>¯</mo> </mover> </mrow> </semantics></math>D<sub>TriT</sub>. The red lines correspond to the upper and lower control limits, respectively, while the dashed green line is the center line.</p> Full article ">Figure 7
<p>IT2TFN R control chart example. The type-2 fuzzy mean <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>=</mo> <mfenced> <mrow> <msubsup> <mi>R</mi> <mn>1</mn> <mi>U</mi> </msubsup> <mo>,</mo> <msubsup> <mi>R</mi> <mn>1</mn> <mi>L</mi> </msubsup> <mo>,</mo> <msubsup> <mi>R</mi> <mn>2</mn> <mi>U</mi> </msubsup> <mo>,</mo> <msubsup> <mi>R</mi> <mn>3</mn> <mn>3</mn> </msubsup> <mo>,</mo> <msubsup> <mi>R</mi> <mn>3</mn> <mi>U</mi> </msubsup> </mrow> </mfenced> </mrow> </semantics></math> is transformed into range RD<sub>TriT</sub>. The red lines correspond to the upper and lower control limits, respectively, while the dashed green line is the center line.</p> Full article ">Figure 8
<p>Simulation algorithm for calculating the ARL, SDRL and RL percentile parameters for the IT2TFN <math display="inline"><semantics> <mover accent="true"> <mi>X</mi> <mo>¯</mo> </mover> </semantics></math> and <span class="html-italic">R</span> control charts.</p> Full article ">Figure 9
<p>Average run length, highlighting the scenario in which the process is in control (δ = 0.0 and λ = 1.0).</p> Full article ">Figure 10
<p>Standard deviation of the run length, highlighting the scenario in which the process is in control (<span class="html-italic">δ</span> = 0.0 and <span class="html-italic">λ</span> = 1.0).</p> Full article ">Figure 11
<p>Run length for the 50th percentile, highlighting the scenario in which the process is in control (δ = 0.0 and λ = 1.0).</p> Full article ">Figure 12
<p>IT2TFN <math display="inline"><semantics> <mover accent="true"> <mi>X</mi> <mo>¯</mo> </mover> </semantics></math> control chart for illustrative example.</p> Full article ">Figure 13
<p>IT2TFN R control chart for illustrative example.</p> Full article ">
21 pages, 19414 KiB  
Article
Investigation on the Microstructural Diversity of a Three-Dimensional Porous Hydroxyapatite/Wollastonite Skeleton via Biomineralization in Simulated Body Fluids
by Bin Jiang, Xin Li, Bozhi Yang, Shujie Yang, Xinyi Chen, Junhong Chen, Minghao Fang, Zhaohui Huang, Xin Min and Xiaozhi Hu
Appl. Sci. 2023, 13(20), 11593; https://doi.org/10.3390/app132011593 - 23 Oct 2023
Cited by 1 | Viewed by 1063
Abstract
The occurrence of fractures has emerged as one of the most prevalent injuries in the human body. In bone reconstruction surgery, after the implantation of porous hydroxyapatite materials, there is an initial infiltration of body fluids into the porous implant, followed by biomineralization-mediated [...] Read more.
The occurrence of fractures has emerged as one of the most prevalent injuries in the human body. In bone reconstruction surgery, after the implantation of porous hydroxyapatite materials, there is an initial infiltration of body fluids into the porous implant, followed by biomineralization-mediated apatite crystal formation and the subsequent ingrowth of bone cells. Despite extensive research efforts in this field, previous investigations have primarily focused on the formation of apatite crystals on exposed surfaces, with limited literature available regarding the formation of apatite crystals within the internal microstructures of bone implants. Herein, we demonstrate the occurrence of dynamic biomineralization within a three-dimensional porous hydroxyapatite/wollastonite (HA/WS) skeleton, leading to the abundant formation of nano-sized apatite crystals across diverse internal environments. Our findings reveal that these apatite nanocrystals demonstrate distinct rates of nucleation, packing densities, and crystal forms in comparison to those formed on the surface. Therefore, the objective of this study was to elucidate the temporal evolution of biomineralization processes by investigating the microstructures of nanocrystals on the internal surfaces of HA/WS three-dimensional porous materials at distinct stages of biomineralization and subsequently explore the biological activity exhibited by HA/WS when combined with cell investigation into apatite crystal biomineralization mechanisms at the nanoscale, aiming to comprehend natural bone formation processes and develop efficacious biomimetic implants for tissue engineering applications. The simultaneous examination of bone cell attachment and its interaction with ongoing internal nanocrystal formation will provide valuable insights for designing optimal scaffolds conducive to bone cell growth, which is imperative in tissue engineering endeavors. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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<p>Schematic process for the preparation of a three-dimensional porous HA/WS skeleton and immersion in 1.5 × SBF solution.</p> Full article ">Figure 2
<p>Microstructure of a nanocrystal. (<b>a</b>) Tilted landscape and near-surface cross-section view of the porous HA/WS skeleton. Red and blue insets stand for two different nanocrystal structures. (<b>b</b>) Three typical internal environments inside HA/WS skeleton: (<b>i</b>) fully filled by SBFs, (<b>ii</b>) half-full, (<b>iii</b>) wall-only (SBF is diffused through and attached only to the cavity wall).</p> Full article ">Figure 3
<p>The complex microstructure of the three-dimensional porous HA/WS skeleton. (<b>a</b>) Completely closed and half-closed holes. (<b>b</b>) Enlarged view of the mid-section in (<b>a</b>), showing different interior sail-like nano-platelet clusters. (<b>c</b>) Enlarged view of (<b>b</b>), showing a small entry has been sealed by the nano-platelet crystal formations. (<b>d</b>) Enlarged view of an enclosed cavity at the bottom-right in (<b>a</b>).</p> Full article ">Figure 4
<p>A crystal-clear view of the surface at nano-scale. (<b>a</b>) An HA/WS grain apex on the uneven skeleton surface. (<b>b</b>) The interface between HA/WS and apatite nanocrystals. (<b>c</b>) Enlarged view of (<b>b</b>). The extension of the interface in (<b>b</b>), showing a perfect interface at the nano-scale.</p> Full article ">Figure 5
<p>Nanocrystals close to the interface inside the scaffold. (<b>a</b>) Apatite nano-crystals formed on the HA. (<b>b</b>) Top view of sail-like nano-platelet clusters.</p> Full article ">Figure 6
<p>A microscopic view of the V-bottom interior of HA/WS skeleton. (<b>a</b>) Micrographs of the interior environment of the half-full cavity. (<b>b</b>) Enlarged view of the flat surface and the V-bottom section, showing seaweed-like nanocrystals. (<b>c</b>) Further enlarged view at the V-bottom.</p> Full article ">Figure 7
<p>Diverse types of apatite nanocrystals. (<b>a</b>) The cavity wall is covered mostly by the impermeable glass phase of wollastonite. (<b>b</b>) Miniature caves with different SBF contact conditions. (<b>c</b>) Thin wall between two fully filled cavities.</p> Full article ">Figure 8
<p>Morphology of the 90HA/10WS scaffolds obtained via micro-CT analysis. (<b>a</b>) Front view; (<b>b</b>) top view; (<b>c</b>) side view; and (<b>d</b>) inside cutting-surface view.</p> Full article ">Figure 9
<p>(<b>a</b>) Microstructure of three-dimensional porous HA/WS skeleton before immersion; (<b>b</b>,<b>c</b>) microstructure of three-dimensional porous HA/WS skeleton after 21-days immersion.</p> Full article ">Figure 10
<p>Microstructure of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 1 day. (<b>a</b>–<b>c</b>) SEM images of HA/WS skeleton after immersed in simulated body fluids for 1 day at different magnifications.</p> Full article ">Figure 11
<p>Microstructure of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 3 days. (<b>a</b>–<b>c</b>) SEM images of HA/WS skeleton after immersed in simulated body fluids for 3 days at different magnifications.</p> Full article ">Figure 12
<p>Microstructure of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 7 days. (<b>a</b>–<b>c</b>) SEM images of HA/WS skeleton after immersed in simulated body fluids for 7 days at different magnifications.</p> Full article ">Figure 13
<p>Microstructure of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 14 days. (<b>a</b>–<b>c</b>) SEM images of HA/WS skeleton after immersed in simulated body fluids for 14 days at different magnifications.</p> Full article ">Figure 14
<p>Microstructure of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 21 days. (<b>a</b>–<b>c</b>) SEM images of HA/WS skeleton after immersed in simulated body fluids for 21 days at different magnifications.</p> Full article ">Figure 15
<p>Surface morphology and elemental analysis of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 21 days.</p> Full article ">Figure 16
<p>Surface element analysis results of three-dimensional porous HA/WS skeleton immersed in simulated body fluids for 21 days.</p> Full article ">Figure 17
<p>Optical images of adhesion status of osteoclast cell adhesion on HA/WS skeleton (top view) after 3 days of seeding; (<b>a</b>,<b>b</b>) non-SBF-immersed porous HA/WS skeleton; (<b>c</b>) SBF-immersed porous HA/WS skeleton.</p> Full article ">Figure 18
<p>The SEM images of HA/WS three-dimensional porous osteoclasts cultured without SBF immersion. (<b>a</b>–<b>c</b>) SEM images of osteoclasts on HA/WS at different magnifications.</p> Full article ">Figure 19
<p>SEM images showing more details of osteoclast cell antenna adhesion on apatite nanocrystals of porous three-dimensional HA/WS skeleton. (<b>a</b>–<b>c</b>) Different views of cells attached tightly on walls and holes inside, at different magnifications, after 3 days of seeding.</p> Full article ">
20 pages, 3758 KiB  
Article
Threat Detection Model for WLAN of Simulated Data Using Deep Convolutional Neural Network
by Omar I. Dallal Bashi, Shymaa Mohammed Jameel, Yasir Mahmood Al Kubaisi, Husamuldeen K. Hameed and Ahmad H. Sabry
Appl. Sci. 2023, 13(20), 11592; https://doi.org/10.3390/app132011592 - 23 Oct 2023
Cited by 2 | Viewed by 1476
Abstract
Security identification solutions against WLAN network attacks according to straightforward digital detectors, such as SSID, IP addresses, and MAC addresses, are not efficient in identifying such hacking or router impersonation. These detectors can be simply mocked. Therefore, a further protected key uses new [...] Read more.
Security identification solutions against WLAN network attacks according to straightforward digital detectors, such as SSID, IP addresses, and MAC addresses, are not efficient in identifying such hacking or router impersonation. These detectors can be simply mocked. Therefore, a further protected key uses new information by combining these simple digital identifiers with an RF signature of the radio link. In this work, a design of a convolutional neural network (CNN) based on fingerprinting radio frequency (RF) is developed with computer-generated data. The developed CNN is trained with beacon frames of a wireless local area network (WLAN) that is simulated as a result of identified and unidentified router nodes of fingerprinting RF. The proposed CNN is able to detect router impersonators by comparing the data pair of the MAC address and RF signature of the received signal from the known and unknown routers. ADAM optimizer, which is the extended version of stochastic gradient descent, has been used with a developed deep learning convolutional neural network containing three fully connected and two convolutional layers. According to the training progress graphic, the network converges to around 100% accuracy within the first epoch, which indicates that the developed architecture was efficient in detecting router impersonations. Full article
(This article belongs to the Special Issue New Challenges in Security, Privacy and Trust for Mobile Systems and Networks)
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<p>The diagram of the first scenario of three known routers.</p> Full article ">Figure 2
<p>A user is linked to a mobile hot spot and a router, where the observer decodes the MAC address and collects beacon frames after training.</p> Full article ">Figure 3
<p>The effect of a router intrusion is that an impersonator router (evil twin) tries to transmit beacon frames by replicating the MAC address of a known router.</p> Full article ">Figure 4
<p>Beacon frames production for the WLAN.</p> Full article ">Figure 5
<p>SDR-based Data collection.</p> Full article ">Figure 6
<p>A general MAC frame diagram.</p> Full article ">Figure 7
<p>Flow work stages of generating MAC beacon frames.</p> Full article ">Figure 8
<p>Generating Data Frames for Training and Applying Channel Impairments.</p> Full article ">Figure 9
<p>Creating Input Matrices with Real-Values.</p> Full article ">Figure 10
<p>Generating the data frames for routers.</p> Full article ">Figure 11
<p>The training progress shows the accuracy and loss along with the iterations.</p> Full article ">Figure 12
<p>Plotting the confusion matrix for test data and a sample of the analytical results.</p> Full article ">Figure 13
<p>Scenario 2 (<b>a</b>) the training progress, (<b>b</b>) the confusion matrix for the tested data, and (<b>c</b>) router intrusion detections.</p> Full article ">Figure 14
<p>Accuracy versus number of devices for the developed architecture.</p> Full article ">
27 pages, 1122 KiB  
Article
Evaluation of Preferences for a Thermal-Camera-Based Abnormal Situation Detection Service via the Integrated Fuzzy AHP/TOPSIS Model
by Woochul Choi, Bongjoo Jang, Intaek Jung, Hongki Sung and Younmi Jang
Appl. Sci. 2023, 13(20), 11591; https://doi.org/10.3390/app132011591 - 23 Oct 2023
Cited by 1 | Viewed by 1379
Abstract
Research related to thermal cameras, which are major control measures, is increasing to overcome the limitations of closed-circuit television (CCTV) images. Thermal cameras have the advantage of easily detecting objects at night and of being able to identify initial signs of dangerous situations [...] Read more.
Research related to thermal cameras, which are major control measures, is increasing to overcome the limitations of closed-circuit television (CCTV) images. Thermal cameras have the advantage of easily detecting objects at night and of being able to identify initial signs of dangerous situations owing to changes in temperature. However, research on thermal cameras from a comprehensive perspective for practical urban control is insufficient. Accordingly, this study presents a thermal camera-based abnormal-situation detection service that can supplement/replace CCTV image analysis and evaluate service preferences. We suggested an integrated Fuzzy AHP/TOPSIS model, which induces a more reasonable selection to support the decision-making of the demand for introducing thermography cameras. We found that developers highly evaluated services that can identify early signs of dangerous situations by detecting temperature changes in heat, which is the core principle of thermography cameras (e.g., pre-fire phenomenon), while local governments highly evaluated control services related to citizen safety (e.g., pedestrian detection at night). Clearly, while selecting an effective service model, the opinions of experts with a high understanding of the technology itself and operators who actually manage ser-vices should be appropriately reflected. This study contributes to the literature and provides the basic foundation for the development of services utilizing thermography cameras by presenting a thermography camera-based abnormal situation detection service and selection methods and joint decision-making engagement between developers and operators. Full article
(This article belongs to the Section Civil Engineering)
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<p>Triangular fuzzy number M.</p> Full article ">Figure 2
<p>Hierarchy structure.</p> Full article ">
32 pages, 30270 KiB  
Article
Analytic Investigation of Hooked Stirrups on Seismic Behavior of Reinforced Concrete 3D Frame Buildings
by Ibrahim Baran Karasin
Appl. Sci. 2023, 13(20), 11590; https://doi.org/10.3390/app132011590 - 23 Oct 2023
Cited by 1 | Viewed by 1915
Abstract
Ensuring the safety and stability of buildings during earthquakes is of utmost importance. This can be achieved by assessing the seismic performance of reinforced concrete structures with consideration of design details. This study focused on the seismic behavior of reinforced concrete buildings by [...] Read more.
Ensuring the safety and stability of buildings during earthquakes is of utmost importance. This can be achieved by assessing the seismic performance of reinforced concrete structures with consideration of design details. This study focused on the seismic behavior of reinforced concrete buildings by comparing the effects of two different types of stirrups, namely those with a 135° angled end-hook shape and straight hooks, with variation of concrete strength. Pushover analysis of a sample building was performed to determine the effect of hook shape on stirrup reinforcement with a constant volumetric ratio for various concrete strength classes. The results of the analysis indicated significant differences in concrete strength and seismic behavior between the two stirrup configurations. The hooked stirrups demonstrated superior energy dissipation capability and ductility, which led to better seismic performance compared to unhooked stirrups across varying levels of concrete strength. To extend the investigation, the study compared the Mander et al., Kent–Scott–Park, and Kappos–Konstantinidis concrete models with different concrete classes (C50-C25-C20-C16-C10). The findings emphasized the importance of stirrup configuration in the design of earthquake-resistant structures. The study concluded that RC structural performance with the 135-degree hooked concrete members exhibited much better behavior of the 90-degree members for the various concrete strength. In this way, it has been revealed the arrangement and detailing of reinforcement in the construction beams and columns improves the governing effect on seismic structural performance. Full article
(This article belongs to the Special Issue Advanced Structural Analysis for Earthquake-Resistant Design of Buildings)
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<p>Sample of hooked (<b>a</b>) and unhooked (<b>b</b>) stirrups [<a href="#B1-applsci-13-11590" class="html-bibr">1</a>].</p> Full article ">Figure 2
<p>Heavily damaged and collapsed elements due to lack of stirrups and 90° hooked configuration.</p> Full article ">Figure 3
<p>Heavily damaged column elements due to 90° hooked stirrups.</p> Full article ">Figure 4
<p>Heavily damaged column element and bond-slip due to 90° hooked stirrups.</p> Full article ">Figure 5
<p>Flowchart of the static pushover analysis.</p> Full article ">Figure 6
<p>Mander concrete model [<a href="#B36-applsci-13-11590" class="html-bibr">36</a>].</p> Full article ">Figure 7
<p>Concrete model according to Konstantinidis et al. [<a href="#B42-applsci-13-11590" class="html-bibr">42</a>,<a href="#B43-applsci-13-11590" class="html-bibr">43</a>].</p> Full article ">Figure 8
<p>Concrete model according to the Kent–Scott–Park model [<a href="#B34-applsci-13-11590" class="html-bibr">34</a>,<a href="#B35-applsci-13-11590" class="html-bibr">35</a>].</p> Full article ">Figure 9
<p>Menegotto-Pinto steel model.</p> Full article ">Figure 10
<p>Fiber modeling and cross-section details [<a href="#B63-applsci-13-11590" class="html-bibr">63</a>,<a href="#B64-applsci-13-11590" class="html-bibr">64</a>].</p> Full article ">Figure 11
<p>Blueprint of the sample building.</p> Full article ">Figure 12
<p>Pushover curves of different concrete models for C10 grade in the X-direction.</p> Full article ">Figure 13
<p>Kent–Scott–Park in the X-direction. (<b>a</b>) 90° (C10, LF: 4.4727), (<b>b</b>) 135° (C10, LF: 4.7347).</p> Full article ">Figure 14
<p>Mander et al. in the X-direction. (<b>a</b>) 90° (C10, LF: 4.7476), (<b>b</b>) 135° (C10, LF: 4.8998).</p> Full article ">Figure 15
<p>Kappos–Konstantinidis in the X-direction. (<b>a</b>) 90° (C10, LF: 3.4156), (<b>b</b>) 135° (C10, LF: 4.6383).</p> Full article ">Figure 16
<p>Pushover curves of different concrete models for C16 grade in the X-direction.</p> Full article ">Figure 17
<p>Kent–Scott–Park in the X-direction. (<b>a</b>) 90° (C16, LF: 5.3244), (<b>b</b>) 135° (C16, LF: 5.4109).</p> Full article ">Figure 18
<p>Mander et al. in the X-direction. (<b>a</b>) 90° (C16, LF: 5.6951), (<b>b</b>) 135° (C16, LF: 5.6245).</p> Full article ">Figure 19
<p>Kappos–Konstantinidis in the X-direction. (<b>a</b>) 90° (C16, LF: 4.1404), (<b>b</b>) 135° (C16, LF: 5.6497).</p> Full article ">Figure 20
<p>Pushover curves of different concrete models for C20 grade in the X-direction.</p> Full article ">Figure 21
<p>Kent–Scott–Park in the X-direction. (<b>a</b>) 90° (C20, LF: 5.0944), (<b>b</b>) 135° (C20, LF: 5.4478).</p> Full article ">Figure 22
<p>Mander et al. in the X-direction. (<b>a</b>) 90° (C20, LF: 6.067), (<b>b</b>) 135° (C20, LF: 6.21).</p> Full article ">Figure 23
<p>Kappos–Konstantinidis in the X-direction. (<b>a</b>) 90° (C20, LF: 4.5997), (<b>b</b>) 135° (C20, LF: 5.9781).</p> Full article ">Figure 24
<p>Pushover curves of different concrete models for C25 grade in the X-direction.</p> Full article ">Figure 25
<p>Kent–Scott–Park in the X-direction. (<b>a</b>) 90° (C25, LF: 6.1932), (<b>b</b>) 135° (C25, LF: 6.3438).</p> Full article ">Figure 26
<p>Mander et al. in the X-direction. (<b>a</b>) 90° (C25, LF: 6.5467), (<b>b</b>) 135° (C25, LF: 6.6342).</p> Full article ">Figure 27
<p>Kappos–Konstantinidis in the X-direction. (<b>a</b>) 90° (C25, LF: 5.2844), (<b>b</b>) 135° (C25, LF: 6.4215).</p> Full article ">Figure 28
<p>Pushover curves of different concrete models for C50 grade in the X-direction.</p> Full article ">Figure 29
<p>Kent–Scott–Park in the X-direction. (<b>a</b>) 90° (C50, LF: 6.9757), (<b>b</b>) 135° (C50, LF: 6.9841).</p> Full article ">Figure 30
<p>Mander et al. in the X-direction. (<b>a</b>) 90° (C50, LF: 7.1151), (<b>b</b>) 135° (C50, LF: 7.2813).</p> Full article ">Figure 31
<p>Kappos–Konstantinidis in the X-direction. (<b>a</b>) 90° (C50, LF: 6.8999), (<b>b</b>) 135° (C50, LF: 7.0672).</p> Full article ">Figure 32
<p>Pushover curves of different concrete models for C10 grade in the Y-direction.</p> Full article ">Figure 33
<p>Kent–Scott–Park in the Y-direction. (<b>a</b>) 90° (C10, LF: 3.3656), (<b>b</b>) 135° (C10, LF: 4.1138).</p> Full article ">Figure 34
<p>Mander et al. in the Y-direction. (<b>a</b>) 90° (C10, LF: 3.1594), (<b>b</b>) 135° (C10, LF: 3.9511).</p> Full article ">Figure 35
<p>Kappos–Konstantinidis in the Y-direction. (<b>a</b>) 90° (C10, LF: 2.5392), (<b>b</b>) 135° (C10, LF: 3.6938).</p> Full article ">Figure 36
<p>Pushover curves of different concrete models for C16 grade in the Y-direction.</p> Full article ">Figure 37
<p>Kent–Scott–Park in the Y-direction. (<b>a</b>) 90° (C16, LF: 4.037), (<b>b</b>) 135° (C16, LF: 4.4135).</p> Full article ">Figure 38
<p>Mander et al. in the Y-direction. (<b>a</b>) 90° (C16, LF: 4.5053), (<b>b</b>) 135° (C16, LF: 4.6645).</p> Full article ">Figure 39
<p>Kappos–Konstantinidis in the Y-direction. (<b>a</b>) 90° (C16, LF: 3.2018), (<b>b</b>) 135° (C16, LF: 4.4671).</p> Full article ">Figure 40
<p>Pushover curves of different concrete models for C20 grade in the Y-direction.</p> Full article ">Figure 41
<p>Kent–Scott–Park in the Y-direction. (<b>a</b>) 90° (C20, LF: 4.0301), (<b>b</b>) 135° (C20, LF: 4.5364).</p> Full article ">Figure 42
<p>Mander et al. in the Y-direction. (<b>a</b>) 90° (C20, LF: 4.7954), (<b>b</b>) 135° (C20, LF: 4.9073).</p> Full article ">Figure 43
<p>Kappos–Konstantinidis in the Y-direction. (<b>a</b>) 90° (C20, LF: 3.7479), (<b>b</b>) 135° (C20, LF: 4.8492).</p> Full article ">Figure 44
<p>Pushover curves of different concrete models for C25 grade in the Y-direction.</p> Full article ">Figure 45
<p>Kent–Scott–Park in the Y-direction. (<b>a</b>) 90° (C25, LF: 4.8781), (<b>b</b>) 135° (C25, LF: 4.8227).</p> Full article ">Figure 46
<p>Mander et al. in the Y-direction. (<b>a</b>) 90° (C25, LF: 5.1352), (<b>b</b>) 135° (C25, LF: 5.17).</p> Full article ">Figure 47
<p>Kappos–Konstantinidis in the Y-direction. (<b>a</b>) 90° (C25, LF: 4.3378), (<b>b</b>) 135° (C25, LF: 5.0707).</p> Full article ">Figure 48
<p>Pushover curves of different concrete models for C50 grade in the Y-direction.</p> Full article ">Figure 49
<p>Kent–Scott–Park in the Y-direction. (<b>a</b>) 90° (C50, LF: 5.3634), (<b>b</b>) 135° (C50, LF: 5.3948).</p> Full article ">Figure 50
<p>Mander et al. in the Y-direction. (<b>a</b>) 90° (C50, LF: 5.4869), (<b>b</b>) 135° (C50, LF: 5.4993).</p> Full article ">Figure 51
<p>Kappos–Konstantinidis in the Y-direction. (<b>a</b>) 90° (C50, LF: 5.2569), (<b>b</b>) 135° (C50, LF: 5.2843).</p> Full article ">
15 pages, 3991 KiB  
Article
Experimental–Simulation Analysis of a Radiation Tolerant Erbium-Doped Fiber Amplifier for Space Applications
by Alberto Facchini, Adriana Morana, Luciano Mescia, Cosimo Campanella, Md Mizan Kabir Shuvo, Thierry Robin, Emmanuel Marin, Youcef Ouerdane, Aziz Boukenter and Sylvain Girard
Appl. Sci. 2023, 13(20), 11589; https://doi.org/10.3390/app132011589 - 23 Oct 2023
Viewed by 1944
Abstract
Research on optical amplifiers has highlighted how ionizing radiation negatively impacts the performance of erbium-doped fiber amplifiers (EDFAs), through the degradation of their gain. The amplitudes and kinetics of this degradation are mainly explained by the radiation-induced attenuation (RIA) phenomenon at the pump [...] Read more.
Research on optical amplifiers has highlighted how ionizing radiation negatively impacts the performance of erbium-doped fiber amplifiers (EDFAs), through the degradation of their gain. The amplitudes and kinetics of this degradation are mainly explained by the radiation-induced attenuation (RIA) phenomenon at the pump and signal wavelengths. In this work, the gain degradation of a radiation tolerant EDFA (exploiting a cerium-co-doped active optical fiber) induced by ionizing radiation up to 3 kGy (SiO2), at two dose rates, 0.28 Gy/s and 0.093 Gy/s, is studied through an experimental/simulation approach. Using a home-made simulation code based on the rate and power propagation equations and including the RIA effects, the radiation-dependent performance of EDFAs were estimated. The variations in the spectroscopic parameters caused by irradiation were also characterized, but our results show that they give rise to EDFA gain degradation of about 1%. To overcome the issue of overestimating the RIA during the radiation tests on the sole active rare-earth-doped fiber, a new RIA experimental setup is introduced allowing us to better consider the photobleaching mechanisms related to the pumping at 980 nm. A good agreement between experimental and simulated gain degradation dose dependences was obtained for two different irradiation conditions, thus also validating the simulation code for harsh environments applications. Full article
(This article belongs to the Section Aerospace Science and Engineering)
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<p>Schematic of the erbium energy levels system used in the model, adapted from [<a href="#B35-applsci-13-11589" class="html-bibr">35</a>]. The green arrows correspond to the energetic transitions involving <sup>4</sup>I<sub>15/2</sub>, <sup>4</sup>I<sub>13/2</sub> and <sup>4</sup>I<sub>9/2</sub> energy levels. The dotted arrows indicate non-radiative decays, and the dashed arrows correspond to the ion–ion energy transfer mechanisms.</p> Full article ">Figure 2
<p>Experimental setup of the RIA measurement used in this work.</p> Full article ">Figure 3
<p>Experimental setup of the gain degradation measurement used in this work.</p> Full article ">Figure 4
<p><sup>4</sup>I<sub>13/2</sub> energy level lifetime as a function of the dose.</p> Full article ">Figure 5
<p>(<b>a</b>) Spectral attenuation and (<b>b</b>) Er<sup>3+</sup> absorption and emission cross sections of two samples: one pristine (red curves) and one irradiated at 3 kGy (blue curves).</p> Full article ">Figure 6
<p>Spectral RIA obtained at 3 kGy TID for the four different case studies.</p> Full article ">Figure 7
<p>Dose dependence of the (<b>a</b>) 980 nm RIA (<b>b</b>) 1550 nm RIA for various 980 nm pumping conditions.</p> Full article ">Figure 8
<p>Gain degradation as a function of the dose, for two dose rates: 0.28 Gy/s (blue dots) and 0.0093 Gy/s (red dots), at 25 °C.</p> Full article ">Figure 9
<p>Evolution of measured–simulated gain degradation as the dose varies, for two dose rates: (<b>a</b>) 0.28 Gy/s; (<b>b</b>) 0.093 Gy/s.</p> Full article ">
19 pages, 6089 KiB  
Article
Semi-Analytical Prediction of Ground Surface Heave Induced by Shield Tunneling Considering Three-Dimensional Space Effect
by Jianfeng Qi, Guohua Zhang, Yuyong Jiao, Luyi Shen, Fei Zheng, Junpeng Zou and Peng Zhang
Appl. Sci. 2023, 13(20), 11588; https://doi.org/10.3390/app132011588 - 23 Oct 2023
Viewed by 836
Abstract
The ground surface deformation induced by shield tunnels passing through enclosure structures of existing tunnels is a particular underground construction scenario that has been encountered in Wuhan Metro Line 12 engineering cases in China. Timely ground deformation prediction is important to keep shield [...] Read more.
The ground surface deformation induced by shield tunnels passing through enclosure structures of existing tunnels is a particular underground construction scenario that has been encountered in Wuhan Metro Line 12 engineering cases in China. Timely ground deformation prediction is important to keep shield tunneling safe. However, the classic ground deformation theory is difficult to accurately predict for this ground deformation. This paper develops a semi-analytical method to predict ground heave considering the space effect in this engineering condition. Based on the improved ground deformation theory, a novel deformation prediction method for the ground and enclosure structure is derived and combined with Kirchhoff plate theory. Comparing with field deformation measurements, the maximum difference between the measured and calculated deformation is 14.6%, which demonstrates that the proposed method can be used to predict the ground heave induced by shield tunnels passing through the enclosure structure of existing tunnels. The parameters of the underground diaphragm wall used in Wuhan Metro Line 12 are further studied in detail. The results show that the ground heaves have a positive correlation with the embedded ratio of the diaphragm wall, but a negative correlation with its elastic modulus and thickness. However, the thickness and embedded ratio have a limited effect on ground heaves. This study provides a technical reference for optimizing the setting of enclosure structures in order to protect existing buildings. Full article
(This article belongs to the Section Civil Engineering)
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<p>Location of Metro Line 12 in Wuhan city, China.</p> Full article ">Figure 2
<p>Space relationship of Metro Line 4 and Line 12.</p> Full article ">Figure 3
<p>Calculation model of ground heave induced by diaphragm wall deformation.</p> Full article ">Figure 4
<p>The simplified calculation model of the tunnel for Metro Line 12 passing through the diaphragm wall.</p> Full article ">Figure 5
<p>(<b>a</b>) Calculation model of transverse deformation curve; (<b>b</b>) calculation model of longitudinal deformation curve.</p> Full article ">Figure 6
<p>Flowchart of the ground heave calculation.</p> Full article ">Figure 7
<p>Layout of field monitoring points. Red circle represents deformation monitoring point, and red triangle represents diaphragm wall top deformation and horizontal displacement monitoring points.</p> Full article ">Figure 8
<p>(<b>a</b>) Installation instruction of deformation monitoring points; (<b>b</b>) installation instruction of diaphragm wall top monitoring points.</p> Full article ">Figure 9
<p>The monitoring results of ground heave of DB1–DB5. Day 38 is when Line 12 passed through the underground diaphragm wall.</p> Full article ">Figure 10
<p>The monitoring results of wall top vertical deformation of CX1–CX4.</p> Full article ">Figure 11
<p>The monitoring results of wall top horizontal deformation of ZL1–ZL2.</p> Full article ">Figure 12
<p>Calculated deformation of underground diaphragm wall acting of additional thrust P.</p> Full article ">Figure 13
<p>Deformation of the diaphragm wall and ground. The solid line is ground heave calculated by the proposed method; dashed line is horizontal deformation of diaphragm wall, solid square is measured deformation and open square is measure horizontal deformation of the diaphragm wall.</p> Full article ">Figure 14
<p>3D ground heave distribution of the proposed method.</p> Full article ">Figure 15
<p>The effects of thickness of diaphragm wall b on ground heave.</p> Full article ">Figure 16
<p>The effects of elasticity modulus E of diaphragm wall on ground heave.</p> Full article ">Figure 17
<p>The effects of embedded ratio re of diaphragm wall on ground heave.</p> Full article ">Figure A1
<p>Calculated model of the diaphragm wall with additional trust.</p> Full article ">
21 pages, 7890 KiB  
Article
Effects of Micro-Scale Environmental Factors on the Quantity of Questing Black-Legged Ticks in Suburban New York
by Chong Di, Brian Sulkow, Weigang Qiu and Shipeng Sun
Appl. Sci. 2023, 13(20), 11587; https://doi.org/10.3390/app132011587 - 23 Oct 2023
Cited by 1 | Viewed by 1239
Abstract
The questing behaviors of blacklegged ticks (Ixodes scapularis) are largely regulated by environmental factors such as temperature, humidity, and vegetation. While this relationship is relatively clear at the macro- and meso-spatial scales, it is inadequately examined at the micro scale. Our [...] Read more.
The questing behaviors of blacklegged ticks (Ixodes scapularis) are largely regulated by environmental factors such as temperature, humidity, and vegetation. While this relationship is relatively clear at the macro- and meso-spatial scales, it is inadequately examined at the micro scale. Our field work in the New York City suburbs during 2017–2018 revealed significant local variations in the quantity of questing blacklegged ticks. The purpose of this study is to identify and test the environmental factors that impact the number of questing blacklegged ticks at the micro-spatial scale. In addition to the number of ticks, surface temperature, and relative humidity data collected in the field, geospatial technologies were leveraged to extract micro-scale spatial and environmental measures, including vegetation index, land cover, elevation, and ecotone, from high-resolution digital imagery and LiDAR data. Regression models were then built to identify the key factors that influence the spatiotemporal patterns of questing blacklegged ticks. The results largely align with the existing research but display characteristics of complexity such as multicollinearity, nonlinearity, and thresholds in relation to temperature, humidity, and vegetation composition at the micro scale, whereas mixed hardwood and dwarf shrubs tend to have higher numbers of questing ticks. Full article
(This article belongs to the Section Ecology Science and Engineering)
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<p>Study area and sampling sites: (<b>A</b>) Rockefeller Park Preserve, RPP; (<b>B</b>) Caumsett State Park, CSP; (<b>C</b>) Connetquot River State Park, CRSP; (<b>D</b>) Fire Island National Seashore, FINS. All four parks are near New York City and in suburban areas. The black dots are the locations of the 5 m by 5 m sampling sites where questing blacklegged ticks were collected.</p> Full article ">Figure 2
<p>Landscapes of the Four New York City Suburban Parks. The parks represent the typical landscapes in suburban New York with various levels of fragmentation, diverse land-cover types, and different vegetation compositions.</p> Full article ">Figure 3
<p>Ecotone Inside Sampling Site. An ecotone is the boundary between different vegetation land-cover types. The length of ecotone is one indicator of the diversity, fragmentation, and heterogeneity of the land-cover types.</p> Full article ">Figure 4
<p>Statistics of Questing Black-legged Tick. The number of questing black-legged ticks varies significantly across time and between the four parks. Overall, temperature has a positive correlation with the questing tick numbers. Parks with more vegetation land cover also have higher numbers.</p> Full article ">Figure 5
<p>Total Number of Questing Blacklegged Ticks and Temperature in Each Sampling Site. Blue and red lines are fitted total number of questing ticks using linear and generalized additive models, respectively. Shaded areas are their standard error bounds. The relationship between the number of questing ticks and temperature is nonlinear and varies across parks. The number peaks at approximately 20 °C. Black-legged ticks still quest under 0 °C.</p> Full article ">Figure 6
<p>Total Number of Questing Blacklegged Ticks and Relative Humidity in Each Sampling Site. Blue and red lines are fitted total number of questing ticks using linear and generalized additive models, respectively. Shaded areas are their standard error bounds. In the natural environment, the influence of relative humidity on the questing activity of black-legged ticks is complex. Extreme low or high relative humidity seems to negatively affect the number of questing ticks.</p> Full article ">Figure 7
<p>Linearity and nonlinearity revealed through the generalized additive model (GAM). The Y axes are transformed by the negative binomial function. GAM favors a linear relationship between temperature and the transformed number of questing ticks. By contrast, the relative humidity has a complex nonlinear relationship.</p> Full article ">Figure 7 Cont.
<p>Linearity and nonlinearity revealed through the generalized additive model (GAM). The Y axes are transformed by the negative binomial function. GAM favors a linear relationship between temperature and the transformed number of questing ticks. By contrast, the relative humidity has a complex nonlinear relationship.</p> Full article ">Figure 8
<p>Landscape of hardwood forest (CSP, <b>left</b>) and seashore (FINS, <b>right</b>). The two parks have drastically different land-cover types in the sampling sites. CSP has large areas covered by hardwood trees, whereas FINS is mainly covered by short shrubs in a very dry condition.</p> Full article ">
17 pages, 1135 KiB  
Review
Applications of Natural Language Processing Tools in Orthopaedic Surgery: A Scoping Review
by Francesca Sasanelli, Khang Duy Ricky Le, Samuel Boon Ping Tay, Phong Tran and Johan W. Verjans
Appl. Sci. 2023, 13(20), 11586; https://doi.org/10.3390/app132011586 - 23 Oct 2023
Cited by 2 | Viewed by 1786
Abstract
The advent of many popular commercial forms of natural language processing tools has changed the way we can utilise digital technologies to tackle problems with big data. The objective of this review is to evaluate the current research and landscape of natural language [...] Read more.
The advent of many popular commercial forms of natural language processing tools has changed the way we can utilise digital technologies to tackle problems with big data. The objective of this review is to evaluate the current research and landscape of natural language processing tools and explore their potential use and impact in the field of orthopaedic surgery. In doing so, this review aims to answer the research question of how NLP tools can be utilised to streamline processes within orthopedic surgery. To do this, a scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Arksey and O’Malley framework for scoping reviews, as well as a computer-assisted literature search on the Medline, Embase and Google Scholar databases. Papers that evaluated the use of natural language processing tools in the field of orthopaedic surgery were included. Our literature search identified 24 studies that were eligible for inclusion. Our scoping review captured articles that highlighted multiple uses of NLP tools in orthopaedics. In particular, one study reported on the use of NLP for intraoperative monitoring, six for detection of adverse events, five for establishing orthopaedic diagnoses, two for assessing the patient experience, two as an informative resource for patients, one for predicting readmission, one for triaging, five for auditing and one for billing and coding. All studies assessed these various uses of NLP through its tremendous computational ability in extracting structured and unstructured text from the medical record, including operative notes, pathology and imaging reports, and progress notes, for use in orthopaedic surgery. Our review demonstrates that natural language processing tools are becoming increasingly studied for use and integration within various processes of orthopaedic surgery. These AI tools offer tremendous promise in improving efficiency, auditing and streamlining tasks through their immense computational ability and versatility. Despite this, further research to optimise and adapt these tools within the clinical environment, as well as the development of evidence-based policies, guidelines and frameworks are required before their wider integration within orthopaedics can be considered. Full article
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<p>Search strategy and workflow in accordance with PRISMA guidelines.</p> Full article ">Figure 2
<p>Overview of applications of natural language processing tools of included studies.</p> Full article ">Figure 3
<p>Publication year of included studies.</p> Full article ">Figure 4
<p>Country of publication of included studies.</p> Full article ">
16 pages, 3439 KiB  
Article
Piplartine Synthetic Analogs: In Silico Analysis and Antiparasitic Study against Trypanosoma cruzi
by Rayanne H. N. Silva, Emanuel P. Magalhães, Rebeca C. Gomes, Yunierkis Perez-Castillo, Alice M. C. Martins and Damião P. de Sousa
Appl. Sci. 2023, 13(20), 11585; https://doi.org/10.3390/app132011585 - 23 Oct 2023
Viewed by 1091
Abstract
Neglected tropical diseases (NTDs) cause thousands of deaths each year. Among these diseases, we find Chagas disease, whose etiologic agent is Trypanosoma cruzi. Piplartine is an alkamide present in various species of the genus Piper that possess trypanocidal activity. In this study, the [...] Read more.
Neglected tropical diseases (NTDs) cause thousands of deaths each year. Among these diseases, we find Chagas disease, whose etiologic agent is Trypanosoma cruzi. Piplartine is an alkamide present in various species of the genus Piper that possess trypanocidal activity. In this study, the antiparasitic potential of a collection of 23 synthetic analogs of piplartine against Trypanosoma cruzi was evaluated in vitro. The compounds were prepared via amidation and esterification reactions using 3,4,5-trimethoxybenzoic acid as starting material. The products were structurally characterized using 1H and 13C nuclear magnetic resonance, infrared spectroscopy, and high-resolution mass spectrometry. Of the twenty-three compounds tested in the cytotoxic activity assays, five presented good activity in the trypomastigote, epimastigote, and amastigote forms of T. cruzi, showing IC50 values ranging from 2.21 to 35.30 µM, 4.06 to 34.30 µM, and 1.72 to 5.72 µM, respectively. N-iso-butyl-3,4,5-trimethoxybenzamide (17) presented potent trypanocidal activity with an IC50 = 2.21 µM and selectively caused apoptosis (SI = 298.6). Molecular modeling experiments suggested the inhibitions of the histone deacetylase (HDAC) enzyme as the main trypanocidal mechanism of action of compound 17 in T. cruzi. Full article
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<p>Chemical structure of piplartine.</p> Full article ">Figure 2
<p>Scatter plots of cells from the cell death study. (<b>A</b>) Control group; (<b>B</b>) group treated with compound <b>16</b>; (<b>C</b>) group treated with compound <b>17</b>; (<b>D</b>) group treated with compound <b>18</b>; (<b>E</b>) group treated with compound <b>20</b>; (<b>F</b>) group treated with compound <b>15</b>.</p> Full article ">Figure 3
<p>Relative fluorescence intensity box plot (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>,<b>I</b>) and histogram graphs (<b>B</b>,<b>D,F</b>,<b>H</b>,<b>I</b>) of Rho123 dye in epimastigote forms treated with compounds <b>15</b> (<b>A</b>,<b>B</b>), <b>16</b> (<b>C</b>,<b>D</b>), <b>17</b> (<b>E</b>,<b>F</b>), <b>18</b> (<b>G</b>,<b>H</b>) and <b>20</b> (<b>I</b>,<b>J</b>). The black, dark blue, and light blue lines represent the fluorescence of the control groups, the highest, and the lowest compound concentrations, respectively. * <span class="html-italic">p</span> &lt; 0.05 vs. control group.</p> Full article ">Figure 4
<p>Free energies of binding of compound <b>17</b> to its potential molecular targets.</p> Full article ">Figure 5
<p>Predicted binding conformation of compound <b>17</b> to HDAC. The represented ligand conformation is the centroid of the most populated cluster obtained after clustering the ligand conformations in the 100 MD snapshots used for MM-PBSA calculations. The compound is represented as orange balls and sticks. Only residues interacting with the ligand in at least 50% of the analyzed MD snapshots are labeled and included in the interactions diagram. The figure was produced with UCSF Chimera [<a href="#B19-applsci-13-11585" class="html-bibr">19</a>] and LigPlot+ [<a href="#B20-applsci-13-11585" class="html-bibr">20</a>].</p> Full article ">Scheme 1
<p>Synthesis of <b>1</b>–<b>23</b>. Reaction conditions: (<b>a</b>) ROH, H<sub>2</sub>SO<sub>4</sub>, reflux; (<b>b</b>) halide, Et<sub>3</sub>N, acetone, 60 °C, reflux; (<b>c</b>) ROH, THF, TPP, DEAD, 0 °C to r.t; (<b>d</b>) RNH<sub>2</sub> or pyrrolidine, DMF, PyBOP, Et<sub>3</sub>N, CH<sub>2</sub>Cl<sub>2</sub>, 0 °C to r.t. Yield variation: 29.8 to 99.6%.</p> Full article ">
18 pages, 3807 KiB  
Article
Designing a User-Centered Inspection Device’s Handle for the Aircraft Manufacturing Industry
by Ana Colim, Débora Pereira, Pedro Lima, André Cardoso, Rui Almeida, Duarte Fernandes, Sacha Mould and Pedro Arezes
Appl. Sci. 2023, 13(20), 11584; https://doi.org/10.3390/app132011584 - 23 Oct 2023
Cited by 2 | Viewed by 1020
Abstract
In aircraft manufacturing settings, workers are frequently exposed to biomechanical risk factors, mainly in the later stages of the production processes, including inspection tasks. To support the development of a novel inspection device appropriate for the end-users and their tasks, this study presents [...] Read more.
In aircraft manufacturing settings, workers are frequently exposed to biomechanical risk factors, mainly in the later stages of the production processes, including inspection tasks. To support the development of a novel inspection device appropriate for the end-users and their tasks, this study presents a user-centered approach for the device’s handle. Three different handles were proposed, and the current study aims to find out which handle can offer (1) the best ergonomic conditions and (2) the best stability in holding the device in hand during an inspection task. To this end, 23 volunteers participated in the experimental assessment, which comprised qualitative and quantitative data. A questionnaire was used for subjective comfort assessment. Partial times to execute the task studied, stability metrics of the device during its handling, and kinematic and electromyographic data of the upper limb recruited were measured and analyzed to compare the three handles. Outstanding results include the higher comfort perceived by the participants working with the selected handle for the final design, as well as the reduction in muscle effort. Globally, the results obtained demonstrated that the handle user-centered design potentiates good efficiency and usability of the novel device. Full article
(This article belongs to the Special Issue Intelligent, Sustainable and Resilient Personalized Product-Service Systems towards Industry 5.0)
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<p>Device prototype and handles 1, 2, and 3 (from left to right).</p> Full article ">Figure 2
<p>Experimental setup.</p> Full article ">Figure 3
<p>Summary of the ergonomic assessment.</p> Full article ">Figure 4
<p>One participant with the EMG sensors and IMU trackers attached.</p> Full article ">Figure 5
<p>Median scores for the descriptors related to functionality, physical interaction, and adverse body effects.</p> Full article ">Figure 6
<p>Median scores for the descriptors related to the handle characteristics, quality, and aesthetics.</p> Full article ">Figure 7
<p>Median scores for the expected comfort at first sight and overall comfort after the use of each handle.</p> Full article ">Figure 8
<p>Distribution of the task execution times (in seconds) while using the handles. The crosses represent the mean time; the middle line represents the median time; dots represent outliers.</p> Full article ">Figure 9
<p>Web diagram with the average values of the stability metrics: mean acceleration (3D Acc mean), mean velocity (3D Vel mean), oscillations of the acceleration (3D Acc oscill), oscillations of the velocity (3D Vel oscill), oscillations of the position (3D Pos oscill), and traveled distance. The values are presented in an adapted scale only for visualization purposes: 3D Acc mean is in m/s2 multiplied by a factor of 10, 3D Vel mean is in m/s multiplied by 100, and so on, as in the diagram labels.</p> Full article ">Figure 10
<p>Distributions of the participants’ joint angles (in degrees) while using the handles. The crosses represent the mean time; the middle line represents the median time; dots represent outliers.</p> Full article ">Figure 11
<p>Web diagram of the MVC (%) for the muscles: <span class="html-italic">Deltoideus anterior</span> (DA); <span class="html-italic">Extensor carpi ulnaris</span> (ECU); and <span class="html-italic">Flexor carpi radialis</span> (FCR) muscles.</p> Full article ">Figure 12
<p>Drawing of the proposed final design for the device.</p> Full article ">
20 pages, 594 KiB  
Article
Improving Automated Machine-Learning Systems through Green AI
by Dagoberto Castellanos-Nieves and Luis García-Forte
Appl. Sci. 2023, 13(20), 11583; https://doi.org/10.3390/app132011583 - 23 Oct 2023
Cited by 4 | Viewed by 1971
Abstract
Automated machine learning (AutoML), which aims to facilitate the design and optimization of machine-learning models with reduced human effort and expertise, is a research field with significant potential to drive the development of artificial intelligence in science and industry. However, AutoML also poses [...] Read more.
Automated machine learning (AutoML), which aims to facilitate the design and optimization of machine-learning models with reduced human effort and expertise, is a research field with significant potential to drive the development of artificial intelligence in science and industry. However, AutoML also poses challenges due to its resource and energy consumption and environmental impact, aspects that have often been overlooked. This paper predominantly centers on the sustainability implications arising from computational processes within the realm of AutoML. Within this study, a proof of concept has been conducted using the widely adopted Scikit-learn library. Energy efficiency metrics have been employed to fine-tune hyperparameters in both Bayesian and random search strategies, with the goal of enhancing the environmental footprint. These findings suggest that AutoML can be rendered more sustainable by thoughtfully considering the energy efficiency of computational processes. The obtained results from the experimentation are promising and align with the framework of Green AI, a paradigm aiming to enhance the ecological footprint of the entire AutoML process. The most suitable proposal for the studied problem, guided by the proposed metrics, has been identified, with potential generalizability to other analogous problems. Full article
(This article belongs to the Special Issue Recent Advances in Automated Machine Learning)
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<p>Illustrates the AutoML lifecycle, encompassing data generation and storage, algorithm and configuration selection, model training and evaluation, and model implementation. Notably, it features a feedback loop that cycles back to the selection of algorithms and configurations after the model training and evaluation stage.</p> Full article ">Figure 2
<p>The illustration shows a workflow of the proposed methodology. It includes the input dataset, the selection of ML algorithms, the search and optimization of hyperparameters with sustainability metrics, the evaluation of the models, and the final model, which is slightly greener AI.</p> Full article ">Figure 3
<p>This class diagram shows the main classes and relationships within a sustainable-focused AutoML system, including the AutoML classifier, data processing pipelines, and a variety of machine-learning algorithms.</p> Full article ">Figure 4
<p>The figure shows the results of the calculation of the means, medians, standard deviations, and interquartile ranges (IQR) for both samples. It also shows the result of the Mann–Whitney U statistical test, which determined if there are significant differences between the samples.</p> Full article ">
17 pages, 2499 KiB  
Article
Theoretical Study of Large Uncoupling Coefficient Loading for Surface Blasting
by Mengxiang Wang, Haibo Wang, Qi Zong, Feng Xiong, Qian Kang, Chun Zhu and Yuanyuan Pan
Appl. Sci. 2023, 13(20), 11582; https://doi.org/10.3390/app132011582 - 23 Oct 2023
Cited by 2 | Viewed by 935
Abstract
Smooth surface blasting control technology is aimed at blasting the rock body until it is left with a smooth surface and to protect it from damage; the current air spaced axial uncoupled charge and air spaced radial uncoupled continuous charge are effective charging [...] Read more.
Smooth surface blasting control technology is aimed at blasting the rock body until it is left with a smooth surface and to protect it from damage; the current air spaced axial uncoupled charge and air spaced radial uncoupled continuous charge are effective charging structures for smooth surface blasting. Reserved air spacing can effectively reduce the blast wave and the peak pressure of the explosive gas, improving the quasi-static pressure of the explosive gas under the action of rock surface blasting with fracture seam quality. In order to ensure the effect of surface blasting, small-diameter light surface holes are more often used; with the development of drilling machinery, the use of large-diameter light blast holes with an oversized uncoupled coefficient of loading structure effectively improves the efficiency of the construction and at the same time achieves better blasting results. However, according to the bursting assumption of obtaining the theory of light surface blasting in the application of large uncoupling coefficient loading, light surface blasting has certain limitations. In this regard, the bursting theory explores the air spacing uncoupling charge in line with the multi-faceted exponential expansion of the critical uncoupling coefficient and is in accordance with the following: the requirements of light surface blasting and the field loading structure; the derivation of the quasi-static pressure on the wall of the gunhole under the action of large uncoupling, uncoupling coefficient, and the parameters of the spacing between the gunholes; the establishment of the axial uncoupling coefficient and the radial uncoupling coefficient-equivalent relationship between the uncoupling coefficient and the theoretical relationship between the selection of the spacing between the holes; the uncoupling coefficient and the selection of the theoretical relationship between the spacing between the holes. This study reveals the mechanism by which different parameters of surface blasting can achieve good results in engineering practices. A slope in Guizhou is an example of sample calculations and the application of two different charging structures applied to field loading, which have achieved good surface blasting results. Full article
(This article belongs to the Topic Complex Rock Mechanics Problems and Solutions)
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<p>Cross-sectional view of equivalent uncoupled charge in the blast hole.</p> Full article ">Figure 2
<p>Cross-sectional view of an equivalent blast hole for a radially and axially uncoupled charge.</p> Full article ">Figure 3
<p>Relationship between the pressure increase factor <span class="html-italic">N</span> and air shock wave <span class="html-italic">P</span><sub>λ</sub>.</p> Full article ">Figure 4
<p>Tensile stress concentration coefficient curve (Gao et al. [<a href="#B35-applsci-13-11582" class="html-bibr">35</a>]).</p> Full article ">Figure 5
<p>Rock compression and splitting test. (<b>a</b>) Uniaxial compression test damage pattern (<b>b</b>) Splitting test damage pattern.</p> Full article ">Figure 6
<p>Structure diagram of smooth-face hole charge. (<b>a</b>) Radial uncoupling factor 2.0. (<b>b</b>) Radial uncoupling factor 2.8.</p> Full article ">Figure 7
<p>Blasting effect diagram.</p> Full article ">
18 pages, 5174 KiB  
Article
Time-Varying Topology Formation Reconfiguration Control of the Multi-Agent System Based on the Improved Hungarian Algorithm
by Yingxue Zhang, Meng Chen, Jinbao Chen, Chuanzhi Chen, Hongzhi Yu, Yunxiao Zhang and Xiaokang Deng
Appl. Sci. 2023, 13(20), 11581; https://doi.org/10.3390/app132011581 - 23 Oct 2023
Cited by 1 | Viewed by 1035
Abstract
Distributed time-varying formation technology for multi-agent systems is recently become a research hotspot in formation control field. However, the formation reconfiguration control technology for agents that randomly appeared to fail during maneuvers is rarely studied. In this paper, the topological relations between intelligence [...] Read more.
Distributed time-varying formation technology for multi-agent systems is recently become a research hotspot in formation control field. However, the formation reconfiguration control technology for agents that randomly appeared to fail during maneuvers is rarely studied. In this paper, the topological relations between intelligence are designed by graph theory to simplify the cooperative interaction between multi-agent systems. Moreover, this paper constructs the time-varying configuration of the target formation based on the rigidity graph theory and leader–follower strategy. Drawing on the establishment of the expert experience database in a collaborative process, we innovatively propose the establishment of a graphic library to help the multi-agent system quickly form an affine transformation as soon as it is disabled. Secondly, the improved Hungarian algorithm is adopted to allocate the target point when the first failure occurs. This algorithm incorporates a gradient weighting factor from the auction algorithm to improve the speed of system reconfiguration with minimum path cost. On this basis, a distributed multi-agent control law based on consistency theory is established, and the system’s stability can be guaranteed via Lyapunov functions. Finally, the simulation results demonstrate the feasibility and effectiveness of the proposed formation reconfiguration control algorithm in a collaborative environment. Full article
(This article belongs to the Special Issue Robotics in Life Science Automation)
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<p>Affine transformation types of a nominal configuration [<a href="#B19-applsci-13-11581" class="html-bibr">19</a>].</p> Full article ">Figure 2
<p>Reconstructed formations in the graphics library.</p> Full article ">Figure 3
<p>Flow chart of time-varying formation based on improved Hungarian algorithm.</p> Full article ">Figure 4
<p>Target allocation in static case. (<b>a</b>) The seventh agent in the sequence fails, leaving six agents. (<b>b</b>) A random fourth agent fails, leaving six agents. (<b>c</b>) The sixth agent in the sequence fails, leaving five agents. (<b>d</b>) A random fifth agent fails, leaving five agents.</p> Full article ">Figure 4 Cont.
<p>Target allocation in static case. (<b>a</b>) The seventh agent in the sequence fails, leaving six agents. (<b>b</b>) A random fourth agent fails, leaving six agents. (<b>c</b>) The sixth agent in the sequence fails, leaving five agents. (<b>d</b>) A random fifth agent fails, leaving five agents.</p> Full article ">Figure 5
<p>Comparison of path curves of the two strategies.</p> Full article ">Figure 6
<p>Comparison of tracking errors of two strategies.</p> Full article ">Figure 7
<p>Time-varying formation topology path diagram.</p> Full article ">Figure 8
<p>Comparison of time-varying topological formation tracking errors.</p> Full article ">
16 pages, 27576 KiB  
Article
Inspired by Earthworms and Leeches: The Effects of Cylindrical Pit Arrays on the Performance of Piston-Cylinder Liner Friction Pairs
by Tianyu Gao, Hao Chen, Danna Tang and Yumo Wang
Appl. Sci. 2023, 13(20), 11580; https://doi.org/10.3390/app132011580 - 23 Oct 2023
Cited by 3 | Viewed by 1108
Abstract
To improve the friction and wear performance of the piston-cylinder liner friction pair, inspired by earthworms and leeches, 27 kinds of pistons with cylindrical pit arrays are designed and processed. Through a friction test, four superior textured pistons are optimized, and wear, life [...] Read more.
To improve the friction and wear performance of the piston-cylinder liner friction pair, inspired by earthworms and leeches, 27 kinds of pistons with cylindrical pit arrays are designed and processed. Through a friction test, four superior textured pistons are optimized, and wear, life and thermal imaging tests are performed. Finite element analysis of the friction pair model is performed, and the friction and wear mechanisms are discussed. The results show that the pistons with cylindrical pit arrays have excellent friction and wear performance, less heat generation by friction, longer lives and less scratches on the cylinder liner. The temperature of the optimized textured pistons was reduced by around 5–10 °C. The wear amount of some textured pistons was reduced by over 50%, resulting in an improvement in their lifespan of at least 30% or more. The results of the finite element analysis indicate that the textured piston exhibited reduced deformation and favorable stress–strain distribution and satisfied the required contact pressure. Full article
(This article belongs to the Section Surface Sciences and Technology)
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<p>Back holes of earthworms.</p> Full article ">Figure 2
<p>SEM images of a leech’s surface.</p> Full article ">Figure 3
<p>Piston design: (<b>a</b>) cylindrical pit array and (<b>b</b>) cylindrical pit parameters.</p> Full article ">Figure 4
<p>The (<b>a</b>) fabrication and (<b>b</b>) labeling of textured pistons.</p> Full article ">Figure 5
<p>Friction force test bench.</p> Full article ">Figure 6
<p>BW-250 mud pump test equipment.</p> Full article ">Figure 7
<p>Pump body: (<b>a</b>) cylinder liner and (<b>b</b>) piston.</p> Full article ">Figure 8
<p>Thermal imaging chart: (<b>a</b>) friction pair and (<b>b</b>) temperature measurement area.</p> Full article ">Figure 9
<p>Modeling of textured pistons.</p> Full article ">Figure 10
<p>Quarter model.</p> Full article ">Figure 11
<p>Mesh refinement.</p> Full article ">Figure 12
<p>Boundary conditions.</p> Full article ">Figure 13
<p>Time–temperature curve.</p> Full article ">Figure 14
<p>Deformation of standard and textured pistons.</p> Full article ">Figure 15
<p>Equivalent stress of standard and textured pistons.</p> Full article ">Figure 16
<p>Contact pressure of standard and textured pistons.</p> Full article ">Figure 17
<p>Piston and cylinder liner after test: (<b>a</b>) standard piston and (<b>b</b>) piston 4.</p> Full article ">
17 pages, 5846 KiB  
Article
Experimental Study on Permeability Evolution of Sandstone during Triaxial Compression Damage
by Lide Wei, Zhinan Lin, Haifeng Long and Qiongyao Ye
Appl. Sci. 2023, 13(20), 11579; https://doi.org/10.3390/app132011579 - 23 Oct 2023
Viewed by 994
Abstract
In order to investigate the mechanical properties and permeability characteristics of sandstone during damage evolution under hydromechanical condition, a series of coupled hydro-mechanical triaxial tests on sandstone specimens were conducted based on the Rock Top 50HT full-stress multi-field coupling triaxial test system. Variations [...] Read more.
In order to investigate the mechanical properties and permeability characteristics of sandstone during damage evolution under hydromechanical condition, a series of coupled hydro-mechanical triaxial tests on sandstone specimens were conducted based on the Rock Top 50HT full-stress multi-field coupling triaxial test system. Variations in permeability as a function of confining pressure, seepage pressure gradient, and volumetric strain during damage evolution were obtained. The results show that: (1) When the confining pressure is constant and the specimen is gradually changed from a dry to a saturated state, the failure mode of sandstone changes from shear failure to single-slope shear failure. (2) There are four distinctive stages in the permeability evolution of sandstone: gradual decrease, steady development, gradual increase, and rapid growth. These stages correspond to the complete stress–strain curve under the respective working conditions. (3) Employing the Weibull distribution formula, this study investigates the evolution of fracture damage under varying working conditions and determines the permeability evolution relationships associated with damage variables. This exploration reveals an intrinsic link between permeability and damage variables. These findings enhance our understanding of the interplay between stress, deformation, permeability, and damage evolution in seepage-stress coupled sandstone. The results contribute valuable insights to the field of rock mechanics and hold implications for diverse geotechnical and engineering applications. Full article
(This article belongs to the Special Issue Rock Mechanics: Current Challenges and Novel Technologies)
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<p>The sandstone samples.</p> Full article ">Figure 2
<p>Electron microscope scanning image of white sandstone samples: (<b>a</b>) 1000 times; (<b>b</b>) 3000 times.</p> Full article ">Figure 3
<p>Rock Top 50HT full-stress multi-field coupling triaxial test system.</p> Full article ">Figure 4
<p>Stress–strain curves of sandstone during the whole process of deformation.</p> Full article ">Figure 4 Cont.
<p>Stress–strain curves of sandstone during the whole process of deformation.</p> Full article ">Figure 5
<p>Failure modes of drying specimens under different confining pressures.</p> Full article ">Figure 6
<p>Failure modes of saturation specimens under different confining pressures.</p> Full article ">Figure 7
<p>Failure modes of specimens under different confining pressures (seepage pressure of 2 MPa).</p> Full article ">Figure 8
<p>Failure modes of specimens under different seepage pressures (confining pressure of 15 MPa).</p> Full article ">Figure 9
<p>The strength characteristics of sandstone under different conditions.</p> Full article ">Figure 10
<p>Typical relationship curve between permeability and axial stress–strain.</p> Full article ">Figure 11
<p>Relationship between sandstone permeability and axial stress–strain under different working conditions.</p> Full article ">Figure 12
<p>Permeability–axial stress–volumetric strain relationship curves for sandstone under different conditions.</p> Full article ">Figure 13
<p>The relationship between permeability and volumetric strain in different stages (confining pressure of 15 MPa).</p> Full article ">Figure 14
<p>Relationship between permeability and the damage variable under different conditions.</p> Full article ">
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