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18 pages, 1089 KiB  
Article
Establishment of Betalain-Producing Cell Line and Optimization of Pigment Production in Cell Suspension Cultures of Celosia argentea var. plumosa
by Thapagorn Sang A Roon, Poramaporn Klanrit, Poramate Klanrit, Pornthap Thanonkeo, Jirawan Apiraksakorn, Sudarat Thanonkeo and Preekamol Klanrit
Plants 2024, 13(22), 3225; https://doi.org/10.3390/plants13223225 (registering DOI) - 16 Nov 2024
Viewed by 215
Abstract
The prevalence of synthetic colorants in commercial products has raised concerns regarding potential risks, including allergic reactions and carcinogenesis, associated with their use or consumption. Natural plant extracts have gained attention as potential alternatives. This research focuses on callus induction and the establishment [...] Read more.
The prevalence of synthetic colorants in commercial products has raised concerns regarding potential risks, including allergic reactions and carcinogenesis, associated with their use or consumption. Natural plant extracts have gained attention as potential alternatives. This research focuses on callus induction and the establishment of cell suspension cultures from Celosia argentea var. plumosa. Friable callus was successfully induced using hypocotyl explants cultured on semi-solid Murashige and Skoog (MS) medium supplemented with 1 mg/L 2,4-dichlorophenoxyacetic acid (2,4-D) and 0.1 mg/L 6-benzylaminopurine (BAP). The friable callus cell line was used to establish a suspension culture. The effects of sucrose, BAP, and tyrosine concentrations on betalain production were investigated using response surface methodology (RSM) based on central composite design (CCD). Optimal conditions (43.88 g/L sucrose, 0.15 mg/L tyrosine, and 0.77 mg/L BAP) yielded 43.87 mg/L total betalain content after 21 days, representing a threefold increase compared to the control. BAP had a significant positive impact on betalain production, and increasing BAP and sucrose concentrations generally led to higher betalain production. However, tyrosine was not a significant factor for betalain production in cell suspension cultures. Additionally, antioxidant assays showed that suspension-cultured cells (SCCs) under optimized conditions exhibited free radical scavenging activity comparable to that observed in C. argentea var. plumosa flower extract. This study indicates the potential for further research on betalain production using C. argentea var. plumosa cell cultures, which may have commercial applications. Full article
(This article belongs to the Section Plant Development and Morphogenesis)
28 pages, 12916 KiB  
Article
Road Landscape Design: Harmonious Relationship Between Ecology and Aesthetics
by Mingqian Si, Yan Mu and Youting Han
Forests 2024, 15(11), 2008; https://doi.org/10.3390/f15112008 - 14 Nov 2024
Viewed by 255
Abstract
In view of global climate and environmental challenges, exploring sustainable urban vegetation management and development is crucial. This study aims to investigate the design strategies of urban road green space plants under the guidance of the dual theories of carbon sequestration and cooling [...] Read more.
In view of global climate and environmental challenges, exploring sustainable urban vegetation management and development is crucial. This study aims to investigate the design strategies of urban road green space plants under the guidance of the dual theories of carbon sequestration and cooling eco-efficiency and aesthetics. In this study, Yangling, a representative small- and medium-sized city, was selected as the study area, and road green space plants were identified as the research objects. The assimilation method was employed to ascertain the carbon sequestration and oxygen release, as well as the cooling and humidification capacities of the plants. The aesthetic quality of the plants was evaluated using the Scenic Beauty Estimation and Landscape Character Assessment. Finally, we propose design strategies for landscapes with higher aesthetic and carbon sequestration and cooling benefits. The results demonstrate a clear nonlinear positive correlation. The carbon sequestration and cooling benefits of plants and the aesthetic quality, with correlation coefficients of 0.864 and 0.922, respectively. Across the same sample points, the rankings of standardized values for carbon sequestration, cooling benefits, and aesthetic quality vary minimally. This indicates that eco-efficient plants with harmonious colors and elegant forms can boost the aesthetic appeal and ecological function in road green spaces. Furthermore, the Sophora japonica Linn., Ligustrum lucidum Ait., Koelreuteria paniculata Laxm., Prunus serrulata Lindl., Prunus cerasifera Ehrhar f., Ligustrum sinense Lour., Photinia × fraseri Dress, Ligustrum × vicaryi Rehder, Sabina chinensis (L.) Ant. cv. Kaizuca, and Ophiopogon japonicus (L. f.) Ker Gawl. are proved to be ecologically dominant plants. They can be employed as the principal selected species for plant design. This study summarizes applicable design strategies for three types of green spaces: avenue greenbelts, traffic separation zones, and roadside greenbelts. The nonlinear regression model developed here provides a reference for scientifically assessing and optimizing urban planting designs. Full article
(This article belongs to the Section Urban Forestry)
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<p>Graphical abstract.</p>
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<p>Location of Yangling Demonstration Zone, Xianyang, Shaanxi, China.</p>
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<p>Road green space plant application frequency.</p>
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<p>Road network analysis and sample distribution in the study area.</p>
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<p>Photographs for SBE. “G” is the Grass sample points, “S” is the Shrub sample points, “TS” is the Tree/Shrub sample points, “TG” is the Tree/Grass sample points, “SG” is the Shrub/Grass sample points, “TSG” is the Tree/Shrub/Grass sample points, “Z” is the Traffic separation green zone, “R” is the Roadside greenbelt, and “A” is the Avenue greenbelt. See <a href="#app1-forests-15-02008" class="html-app">Appendix A</a> for details.</p>
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<p>In the road green space plant application frequency table, “P” is the application frequency, and “%” on A represents the percentage of the number of plants in the interval to the total number of plants.</p>
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<p>Cluster analysis of plant’s carbon sequestration and cooling value.</p>
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<p>Trend chart of sample points feature score, and “Range” is the score interval.</p>
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<p>Correlation between SBE and landscape characteristic value.</p>
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<p>Scatter plot between W<sub>C</sub>-SBI and T-SBI.</p>
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<p>The linear regression model of the SBI–ecological relationship. The simulation process is shown in <a href="#app6-forests-15-02008" class="html-app">Appendix F</a>.</p>
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<p>Standardized value ranking of SBI, W<sub>C</sub>, and T.</p>
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<p>Evaluation of population structure analysis.</p>
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<p>Scatter plot of correlation coefficient.</p>
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15 pages, 7931 KiB  
Article
Color Models in the Process of 3D Digitization of an Artwork for Presentation in a VR Environment of an Art Gallery
by Irena Drofova and Milan Adamek
Electronics 2024, 13(22), 4431; https://doi.org/10.3390/electronics13224431 - 12 Nov 2024
Viewed by 448
Abstract
This study deals with the color reproduction of a work of art to digitize it into a 3D realistic model. The experiment aims to digitize a work of art for application in a virtual reality environment concerning faithful color reproduction. Photogrammetry and scanning [...] Read more.
This study deals with the color reproduction of a work of art to digitize it into a 3D realistic model. The experiment aims to digitize a work of art for application in a virtual reality environment concerning faithful color reproduction. Photogrammetry and scanning with a LiDAR sensor are used to compare the methods and work with colors during the reconstruction of the 3D model. An innovative tablet with a camera and LiDAR sensor is used for both methods. At the same time, current findings from the field of color vision and colorimetry are applied to 3D reconstruction. The experiment focuses on working with the RGB and L*a*b* color models and, simultaneously, on the sRGB, CIE XYZ, and Rec.2020(HDR) color spaces for transforming colors into a virtual environment. For this purpose, the color is defined in the Hex Color Value format. This experiment is a starting point for further research on color reproduction in the digital environment. This study represents a partial contribution to the much-discussed area of forgeries of works of art in current trends in forensics and forgery. Full article
(This article belongs to the Section Electronic Multimedia)
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<p>Digitization of an art object: (<b>a</b>) 2D digitized object and detail marked in red; (<b>b</b>) matrix of partial details the yellow range of the image; and (<b>c</b>) visualization of the detail of the structure and color of a partial part of the object.</p>
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<p>The basic principle of the Structure from Motion (SfM) method [<a href="#B37-electronics-13-04431" class="html-bibr">37</a>].</p>
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<p>Creation of a 3D model using the SfM photogrammetry method: (<b>a</b>) Digitized object; (<b>b</b>) position of 24 photos from which the basic cloud of points is created; (<b>c</b>) Dense Cloud generation; (<b>d</b>) the resulting 3D texture model of the artwork.</p>
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<p>Creating a 3D model using a LiDAR sensor: (<b>a</b>) digitized object; (<b>b</b>) 3D model generated by Scaniverse; (<b>c</b>) 3D texture model imported into Agisoft 3D SW; and (<b>d</b>) generated point cloud from the textured 3D model.</p>
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<p>Generated Dense Cloud: (<b>a</b>) 3D SfM photogrammetry method and (<b>b</b>) LiDAR sensor.</p>
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<p>Colorimetry: (<b>a</b>) RGB color model and (<b>b</b>) sRGB color space (gamut).</p>
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<p>SfM—Points Segmentation #758605: (<b>a</b>) Dense Cloud 3D model using SfM photogrammetry; (<b>b</b>) segmentation points by color G#758605; (<b>c</b>) body #758605 in Dense Cloud.</p>
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<p>LiDAR—Segmentation of points #758605: (<b>a</b>) 3D model using LiDAR sensor; (<b>b</b>) Segmentation of points by color G#758605; (<b>c</b>) detail of the points generated in Dense Cloud.</p>
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<p>CIE XYZ 1931 standardized color space: (<b>a</b>) Basic ColorChecker standardized color gamut; (<b>b</b>) position of individual standardized colors in the CIE 1931 chromatic diagram; (<b>c</b>) color model L*a*b*; (<b>d</b>) CIE 1931 chromaticity diagram with Rec.2020 gamuts; sRGB and L*a*b.</p>
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<p>Visual comparison of reproduction quality in the process of 3D modeling and color segmentation: 3D models using the SfM photogrammetry method and 3D models using the LiDAR sensor.</p>
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<p>Visualization of a realistic 3D reconstruction of the artwork: (<b>a</b>) 3D Dense Cloud model; (<b>b</b>) 3D texture model by the SfM method; (<b>c</b>) 3D texture model by LiDAR sensor.</p>
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21 pages, 20361 KiB  
Article
The Seismic Surface Rupture Zone in the Western Segment of the Northern Margin Fault of the Hami Basin and Its Causal Interpretation, Eastern Tianshan
by Hao Sun, Daoyang Yuan, Ruihuan Su, Shuwu Li, Youlin Wang, Yameng Wen and Yanwen Chen
Remote Sens. 2024, 16(22), 4200; https://doi.org/10.3390/rs16224200 - 11 Nov 2024
Viewed by 392
Abstract
The Eastern Tianshan region, influenced by the far-field effect of northward compression and expansion of the Qinghai-Xizang block, features highly developed Late Quaternary active faults that exhibit significant neotectonic activity. Historically, the Barkol-Yiwu Basin, located to the north of the Eastern Tianshan, experienced [...] Read more.
The Eastern Tianshan region, influenced by the far-field effect of northward compression and expansion of the Qinghai-Xizang block, features highly developed Late Quaternary active faults that exhibit significant neotectonic activity. Historically, the Barkol-Yiwu Basin, located to the north of the Eastern Tianshan, experienced two major earthquakes in 1842 and 1914, each with a magnitude of M71/2. In contrast, the Hami Basin on the southern margin of the Eastern Tianshan has no historical records of any major earthquakes, and its seismic potential, mechanisms, and future earthquake hazards remain unclear. Based on satellite image interpretation and field surveys, this study identified a relatively recent and well-preserved seismic surface rupture zone with good continuity in the Liushugou area of the western segment of the Northern Margin Fault of the Hami Basin (HMNF), which is the seismogenic structure responsible for the rupture. The surface rupture zone originates at Kekejin in the east, extends intermittently westward through Daipuseke Bulake and Liushugou, and terminates at Wuzun Bulake, with a total length of approximately 21 km. The rupture zone traverses the youngest geomorphic surface units, such as river beds or floodplains and first-order terraces (platforms), and is characterized by a series of single or multiple reverse fault scarps. The morphology of fault scarps is clear, presenting a light soil color with heights ranging from 0.15 m to 2.13 m and an average displacement of 0.56 m, suggesting that this surface rupture zone likely represents the most recent seismic event. Comparison with historical earthquake records in the Eastern Tianshan region suggests that the rupture zone may have been formed simultaneously with the Xiongkuer rupture zone by the 1842 M71/2 earthquake along the boundary faults on both sides of the Barkol Mountains, exhibiting a flower-like structural pattern. Alternatively, it might represent a separate, unrecorded seismic event occurring shortly after the 1842 earthquake. The estimated magnitude of the associated earthquake is about 6.6~6.9. Given that surface-rupturing earthquakes have already occurred in the western segment, the study indicates that the Erdaogou–Nanshankou section of the HMNF has surpassed the average recurrence interval for major earthquakes, indicating a potential future earthquake hazard. Full article
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<p>Seismotectonic map of Eastern Tianshan: (<b>a</b>) the location of Eastern Tianshan; (<b>b</b>) primary active faults and earthquakes in Eastern Tianshan; (<b>c</b>) the distribution features of HMNF. TNF: The Northern Margin Fault of Turpan Basin; J-LF: Jianquanzi–Luobaoquan Fault; ZFF: Zhifang Fault; BSF: The Southern Margin Fault of Barkol Basin; BNF: The Northern Margin Fault of Barkol Basin; HMNF: The Northern Margin Fault of Hami Basin; K-YSF: The Southern Margin Fault of Kuisu-Yiwu Basin; KCF: The Central Fault of Karlik Mountains; WZXF: Weizixia Fault; XMYF: Xiamaya Fault; YWSF: The Southern Margin Fault of Yiwu Basin; GTSFS: Gobi–Tianshan Sinistral Strike-Slip Faults. The base map is based on 30 m DEM of USGS [<a href="#B19-remotesensing-16-04200" class="html-bibr">19</a>]. The fault data are modified from studies [<a href="#B9-remotesensing-16-04200" class="html-bibr">9</a>,<a href="#B11-remotesensing-16-04200" class="html-bibr">11</a>,<a href="#B13-remotesensing-16-04200" class="html-bibr">13</a>,<a href="#B20-remotesensing-16-04200" class="html-bibr">20</a>]. The earthquake dates are from the China Earthquake Catalogue (1831BC-1969AD) [<a href="#B21-remotesensing-16-04200" class="html-bibr">21</a>] and the National Earthquake Date Centre [<a href="#B22-remotesensing-16-04200" class="html-bibr">22</a>].</p>
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<p>Features of active tectonics, seismic rupture zone, and landform in Liushugou segment: (<b>a</b>) original geomorphic features showed by the Hillshade of DEM; (<b>b</b>) geomorphic surface in Liushugou; (<b>c</b>) the profile of P1.</p>
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<p>SFM photography schematic of UAV (UAV-DJ Phantom 4 Pro V2.0, GCP-Ground Control Point).</p>
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<p>The distribution characteristics of the Liushugou rupture zone and UAV aerial photography areas (displayed in Google Earth satellite imagery; the light gray-white thin stripes inside the yellow solid line box are the seismic surface rupture zones): (<b>A</b>) The distribution of the seismic surface rupture zone and its spatial relationship with the Xiongkuer Rupture Zone and the epicentral area around Barkol County of 1842 M7<sup>1</sup>/<sub>2</sub> earthquake; (<b>a</b>–<b>e</b>) The entire distribution of the seismic surface rupture zone; (<b>a</b>–<b>d</b>) The most obvious and typical phenomenon of the Liushugou rupture zone; (<b>a</b>,<b>c</b>–<b>e</b>) The UAV aerial survey areas.</p>
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<p>Features of seismic rupture zone in Kekejin segment: (<b>a</b>) the distribution of the surface rupture zone in the Kekejin segment; (<b>b</b>) the UAV aerial survey area and the original geomorphic features showed by the Hillshade of DEM; (<b>c</b>) geomorphic surface and distribution of the rupture zone; (<b>d</b>–<b>f</b>) typical photos of seismic rupture scarp (the red arrows indicate the seismic rupture scarp).</p>
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<p>Features of seismic rupture zone in Daipuseke Bulake segment: (<b>a</b>) original geomorphic features showed by the Hillshade of DEM; (<b>b</b>) geomorphic surfaces and the distribution of the rupture zone; (<b>c</b>–<b>f</b>) typical photos of seismic rupture scarp (the red arrows indicate the seismic rupture scarp).</p>
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<p>Distribution and features of seismic rupture zone in Liushugou segment: (<b>a</b>) geomorphic surfaces and the distribution of the rupture zone; (<b>b</b>) the profile of P0, showing Fan2 fold deformation and seismic rupture scarps on it; (<b>c</b>) the profile of the maximum offset.</p>
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<p>Typical photos of the seismic rupture zone in the Liushugou segment (the red arrows indicate the seismic rupture scarp): (<b>a</b>) the maximum vertical offset of the seismic rupture scarp; (<b>b</b>) the seismic rupture scarp west of the maximum vertical offset point; (<b>c</b>,<b>d</b>) the seismic rupture scarp on the fold; (<b>e</b>) the seismic rupture sca rp on Fan2; (<b>f</b>) the seismic rupture scarp on the Terrace1 of a gully on the west of Liushugou.</p>
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<p>Distribution features and typical photos of seismic rupture zone in Wuzun Bulake segment: (<b>a</b>) original geomorphic features showed by the Hillshade of DEM; (<b>b</b>) geomorphic surfaces and the distribution of the rupture zone; (<b>c</b>,<b>d</b>,<b>f</b>) the seismic rupture scarps in alluvial flat (the white dashed line represents the topography, the red dashed line indicates the fault, and the red arrow indicates the seismic rupture scarp); (<b>e</b>) the fault profile on the east sidewall of the gully (The red arrows indicate the motion of the reverse fault).</p>
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<p>Coseismic vertical offset distribution map of Liushugou rupture zone.</p>
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<p>Characteristics of seismic rupture zone and its surrounding geomorphic surfaces: (<b>a</b>,<b>b</b>) the features of the dirt roads; (<b>c</b>,<b>d</b>) features of the scarp of the seismic rupture zone on the forelimb of Liushugou Fan2 fold; (<b>e</b>) features of the older scarp in Liushugou.</p>
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<p>Isoseismal lines of 1842 and 1914 historical earthquakes near Barkol (modified from Gu et al. [<a href="#B21-remotesensing-16-04200" class="html-bibr">21</a>]): (<b>a</b>) the location index map of the study area.; (<b>b</b>) the distribution of isoseismal lines of two major historical earthquakes and the main active faults in the Eastern Tianshan.</p>
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<p>Comparison of the features between the Xiongkur and the Liushugou seismic rupture zone (the red arrows indicate the seismic rupture scarp): (<b>a</b>–<b>c</b>) the features of the Xiongkuer seismic rupture zone (Wu, 2016 [<a href="#B9-remotesensing-16-04200" class="html-bibr">9</a>]); (<b>d</b>–<b>f</b>) the features of the Liushugou seismic rupture zone.</p>
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<p>Formation model of Liushugou seismic rupture zone (Wu, 2016 [<a href="#B9-remotesensing-16-04200" class="html-bibr">9</a>]).</p>
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12 pages, 625 KiB  
Article
On the Thermomechanics of Hadrons and Their Mass Spectrum
by Leonardo Chiatti
Particles 2024, 7(4), 955-966; https://doi.org/10.3390/particles7040058 - 11 Nov 2024
Viewed by 216
Abstract
A little-known thermomechanical relation between entropy and action, originally discovered by Boltzmann in the classical domain, was later reconsidered by de Broglie in relation to the wave–particle duality in the free propagation of single particles. In this paper, we present a version adapted [...] Read more.
A little-known thermomechanical relation between entropy and action, originally discovered by Boltzmann in the classical domain, was later reconsidered by de Broglie in relation to the wave–particle duality in the free propagation of single particles. In this paper, we present a version adapted to the phenomenological description of the hadronization process. The substantial difference with respect to the original de Broglie scheme is represented by the universality of the temperature at which the process occurs; this, in fact, coincides with the Hagedorn temperature. The main results are as follows: (1) a clear connection between the universality of the temperature and the existence of a confinement radius of the color forces; (2) a lower bound on the hadronic mass, represented by the universal temperature, in agreement with experimental data; and (3) a scale invariance, which allows the reproduction of the well-known hadronic mass spectrum solution of the statistical bootstrap model. The approach therefore presents a heuristic interest connected to the study of the strong interaction. Full article
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<p>The smoothed mass spectrum of hadronic states as a function of mass. Experimental data: <span class="html-italic">green line</span> with the 1411 states known in 1967; <span class="html-italic">red line</span> with the 4627 states of mid-1990s. The <span class="html-italic">blue line</span> represents the exponential fit with Equation (12) yielding <span class="html-italic">T</span><sub>H</sub> = 158 MeV. Adapted from Rafelski and Ericson ([<a href="#B24-particles-07-00058" class="html-bibr">24</a>], Ch. 6, Figure 6.2).</p>
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<p>Visual representation, using three-dimensional spheres, of the fission of a hadron into two hadrons, with the creation of a pair of opposite colored charges. All the spheres are tangent to ordinary space. For clarity, the relativistic contraction of the radii of the spheres is not shown.The additional coordinate, perpendicular to spacetime, is only an aid in visualizing the intrinsic curvature of the positional constraint on strong charges and has no physical relevance in itself.</p>
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21 pages, 28562 KiB  
Article
Deep-Learning-Based Approach in Cancer-Region Assessment from HER2-SISH Breast Histopathology Whole Slide Images
by Zaka Ur Rehman, Mohammad Faizal Ahmad Fauzi, Wan Siti Halimatul Munirah Wan Ahmad, Fazly Salleh Abas, Phaik-Leng Cheah, Seow-Fan Chiew and Lai-Meng Looi
Cancers 2024, 16(22), 3794; https://doi.org/10.3390/cancers16223794 - 11 Nov 2024
Viewed by 467
Abstract
Fluorescence in situ hybridization (FISH) is widely regarded as the gold standard for evaluating human epidermal growth factor receptor 2 (HER2) status in breast cancer; however, it poses challenges such as the need for specialized training and issues related to signal degradation from [...] Read more.
Fluorescence in situ hybridization (FISH) is widely regarded as the gold standard for evaluating human epidermal growth factor receptor 2 (HER2) status in breast cancer; however, it poses challenges such as the need for specialized training and issues related to signal degradation from dye quenching. Silver-enhanced in situ hybridization (SISH) serves as an automated alternative, employing permanent staining suitable for bright-field microscopy. Determining HER2 status involves distinguishing between “Amplified” and “Non-Amplified” regions by assessing HER2 and centromere 17 (CEN17) signals in SISH-stained slides. This study is the first to leverage deep learning for classifying Normal, Amplified, and Non-Amplified regions within HER2-SISH whole slide images (WSIs), which are notably more complex to analyze compared to hematoxylin and eosin (H&E)-stained slides. Our proposed approach consists of a two-stage process: first, we evaluate deep-learning models on annotated image regions, and then we apply the most effective model to WSIs for regional identification and localization. Subsequently, pseudo-color maps representing each class are overlaid, and the WSIs are reconstructed with these mapped regions. Using a private dataset of HER2-SISH breast cancer slides digitized at 40× magnification, we achieved a patch-level classification accuracy of 99.9% and a generalization accuracy of 78.8% by applying transfer learning with a Vision Transformer (ViT) model. The robustness of the model was further evaluated through k-fold cross-validation, yielding an average performance accuracy of 98%, with metrics reported alongside 95% confidence intervals to ensure statistical reliability. This method shows significant promise for clinical applications, particularly in assessing HER2 expression status in HER2-SISH histopathology images. It provides an automated solution that can aid pathologists in efficiently identifying HER2-amplified regions, thus enhancing diagnostic outcomes for breast cancer treatment. Full article
(This article belongs to the Special Issue Feature Papers in Section "Cancer Biomarkers" in 2023–2024)
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<p>A Whole Slide Image (WSI) depicting tissue regions (<b>left</b>) and a magnified selected region (<b>right</b>) for detailed analysis of tissue anatomy, with Amplified and Normal regions marked by a pathologist for diagnostic purposes.</p>
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<p>Proposed framework for patch-based image classification and identification of respective class samples from the whole slide image (WSI) using the trained model.</p>
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<p>Procedural diagram illustrating the automated selection of tissue regions and image patching from whole slide images (WSIs), with expert-level annotation.</p>
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<p>Annotated regions in the images have irregular shapes. A segmentation process standardizes their shape to <math display="inline"><semantics> <mrow> <mn>512</mn> <mo>×</mo> <mn>512</mn> <mo>×</mo> <mn>3</mn> </mrow> </semantics></math> pixels by sliding a window from the top-left corner horizontally and vertically to cover the entire region of interest. Portions outside the window are discarded.</p>
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<p>Examples of HER2-SISH patch samples categorized into their respective classes: (<b>a</b>) Normal, (<b>b</b>) Amplified, and (<b>c</b>) Non-Amplified.</p>
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<p>Overview of the DenseNet121 architecture.</p>
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<p>Overview of the VGG16 architecture.</p>
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<p>Overview of the MobileNetV2 architecture.</p>
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<p>Overview of the Vision Transformer (ViT) architecture: The model divides input images into patches and treats each patch as a token for processing.</p>
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<p>Confusion matrices illustrating the classification performance of the fine-tuned models: (<b>a</b>) MobileNetV2, (<b>b</b>) VGG16, (<b>c</b>) Vision Transformer (ViT), and (<b>d</b>) DenseNet121.</p>
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<p>Examples of HER2-SISH patch samples with their respective model-predicted classifications.</p>
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<p>Visualization of classification results on WSIs with pseudo-color class maps. The figure illustrates the ViT model’s performance at the WSI patch level, with corresponding outputs shown on the right of each WSI.</p>
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<p>Confusion matrix illustrating the Vision Transformer (ViT) model’s performance on unseen test data, highlighting its generalization capabilities.</p>
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<p>Comparison of Cohen’s Kappa and AUC-ROC values for each model.</p>
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<p>Comparison of performance metrics across models for accuracy, Cohen’s Kappa, and MCC.</p>
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20 pages, 6129 KiB  
Article
Optimized YOLOv5 Architecture for Superior Kidney Stone Detection in CT Scans
by Khasanov Asliddin Abdimurotovich and Young-Im Cho
Electronics 2024, 13(22), 4418; https://doi.org/10.3390/electronics13224418 - 11 Nov 2024
Viewed by 460
Abstract
The early and accurate detection of kidney stones is crucial for effective treatment and improved patient outcomes. This paper proposes a novel modification of the YOLOv5 model, specifically tailored for detecting kidney stones in CT images. Our approach integrates the squeeze-and-excitation (SE) block [...] Read more.
The early and accurate detection of kidney stones is crucial for effective treatment and improved patient outcomes. This paper proposes a novel modification of the YOLOv5 model, specifically tailored for detecting kidney stones in CT images. Our approach integrates the squeeze-and-excitation (SE) block within the C3 block of the YOLOv5m architecture, thereby enhancing the ability of the model to recalibrate channel-wise dependencies and capture intricate feature relationships. This modification leads to significant improvements in the detection accuracy and reliability. Extensive experiments were conducted to evaluate the performance of the proposed model against standard YOLOv5 variants (nano-sized, small, and medium-sized). The results demonstrate that our model achieves superior performance metrics, including higher precision, recall, and mean average precision (mAP), while maintaining a balanced inference speed and model size suitable for real-time applications. The proposed methodology incorporates advanced noise reduction and data augmentation techniques to ensure the preservation of critical features and enhance the robustness of the training dataset. Additionally, a novel color-coding scheme for bounding boxes improves the clarity and differentiation of the detected stones, facilitating better analysis and understanding of the detection results. Our comprehensive evaluation using essential metrics, such as precision, recall, mAP, and intersection over union (IoU), underscores the efficacy of the proposed model for detecting kidney stones. The modified YOLOv5 model offers a robust, accurate, and efficient solution for medical imaging applications and represents a significant advancement in computer-aided diagnosis and kidney stone detection. Full article
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<p>Architecture of YOLOv5 with a C3 block.</p>
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<p>Bottleneck blocks, each consisting of two convolutional layers with a residual connection, contribute to parameter reduction while preserving the representational capacity of the model. (<b>a</b>) C3 block with three convolutions. (<b>b</b>) SE block. (<b>c</b>) Bottleneck of the C3 block.</p>
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<p>Comparative analysis of different YOLOv5 model variants (nano-sized, small, and medium) along with the proposed modified YOLOv5 model for the detection of kidney stones in CT images.</p>
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<p>Different coloring approaches for boundary boxes of detected objects.</p>
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15 pages, 19310 KiB  
Article
Kavokta Deposit, Middle Vitim Mountain Country, Russia: Composition and Genesis of Dolomite Type Nephrite
by Evgeniy V. Kislov
Geosciences 2024, 14(11), 303; https://doi.org/10.3390/geosciences14110303 - 10 Nov 2024
Viewed by 443
Abstract
The Kavokta deposit of the dolomite type nephrite is located in the Middle Vitim mountain country, Russia (Russian Federation). The deposit area is composed of granite of the Late Paleozoic Vitimkan complex. The granite contains complex shape blocks of Lower Proterozoic rocks. They [...] Read more.
The Kavokta deposit of the dolomite type nephrite is located in the Middle Vitim mountain country, Russia (Russian Federation). The deposit area is composed of granite of the Late Paleozoic Vitimkan complex. The granite contains complex shape blocks of Lower Proterozoic rocks. They are represented by metasandstone, crystalline schist, amphibolite, and dolomite marble. The calcite–tremolite and epidote–tremolite skarns were formed on the contact of dolomite and amphibolite. Calcite–tremolite skarn contains nephrite bodies. The mineral composition of 16 core samples obtained during the geological exploration conducted by JSC “Transbaikal Mining Enterprise” within Vein 1 of Prozrachny site has been studied in thin sections using a petrographic microscope, and in polished sections using a scanning electron microscope, with an energy-dispersive microanalysis system. Twenty-five minerals have been identified. They have been attributed to relict, metasomatic associations of the pre-nephrite and nephrite stages and hydrothermal and secondary associations. The intensity of the nephrite’s green color is explained by the Fe admixture in tremolite, and the black color is explained by its transition to actinolite in the areas of contact with epidote–tremolite skarn after amphibolite. In the formation and alteration of nephrite, dolomite is replaced by diopside, diopside by tremolite, prismatic tremolite by tangled fibrous tremolite, and tremolite by chlorite. Granite provides heat for metasomatism. Participation of amphibolite in the nephrite formation determines the variety of nephrite colors. The role of metamorphism is reduced to tectonic fragmentation facilitating fluid penetration; stress provides a tangled fibrous cryptocrystalline texture. Full article
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<p>Scheme of the geological structure of Prozrachny site, Kavokta deposit based on the materials of JSC “Transbaikal Mining Enterprise”.</p>
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<p>Scheme of the geological structure of Prozrachny site, Kavokta deposit based on the materials of JSC “Transbaikal Mining Enterprise”.</p>
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<p>Geological plan of Vein 1, Prozrachny site based on the materials of JSC “Transbaikal Mining Enterprise”. The numbers of the samples used in this work are marked. They correspond to the numbers in the text and captions to the figures.</p>
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<p>Variety of nephrite colors, sample 464501.</p>
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<p>Green to black nephrite, sample 916202.</p>
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<p>Various-sized radial tremolite aggregates, crossed nicols, samples 464901 (<b>a</b>) and 550101 (<b>b</b>).</p>
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<p>Mineral composition of nephrite. The images were taken using a LEO-1430VP scanning electron microscope: (<b>a</b>)—tremolite bundles, 917001; (<b>b</b>)—parallel-fibrous tremolite aggregate with different Fe content, 519703; (<b>c</b>)—light and dark tremolite strips of the same composition, 465401; (<b>d</b>)—secondary calcite cuts tremolite and interlayering of phlogopite, calcite, and tremolite, 519703; (<b>e</b>)—tremolite with 0 wt.% Fe with aggregate of tremolite with 1.13 wt.% FeO, phlogopite, calcite, chlorite, 519703/1; (<b>f</b>)—chromium magnetite, actinolite grains and veinlets, dolomite at tremolite, 916202; (<b>g</b>)—meionite at tremolite, 464901; (<b>h</b>)—titanite grains at tremolite, 916202; (<b>i</b>)—zircon grain at tremolite, 917001; (<b>j</b>)—corroded diopside grain at tremolite, 517601; (<b>k</b>)—forsterite aggregate with grains of dolomite, tremolite, apatite, 464501; (<b>l</b>)—epidote aggregate—in the center the epidote-Ce, along the periphery of epidote at tremolite, 516701; (<b>m</b>)—large segregation of calcite with inclusions of tremolite and fluorapatite at tremolite, 917001; (<b>n</b>)—apatite crystal with an elongated inclusion of calcite at tremolite, 917001; (<b>o</b>)—fluorapatite aggregate, 464501; (<b>p</b>)—elongated grains of galena and sphalerite at tremolite, serpentine is along a crack, 464501; (<b>q</b>)—pyrite grain with galena inclusions, 464501; (<b>r</b>)—pyrite at tremolite, 915902; (<b>s</b>)—molybdenite plate-like grains at fluorphlogopite, 915902; (<b>t</b>)—intergrowths of molybdenite and galena at tremolite, 916001; (<b>u</b>)—gypsum and barite intergrowth, 917001; (<b>v</b>)—fluorite aggregate at tremolite, 465401; (<b>w</b>)—interlayers of prehnite, fluorite, and chlorite at tremolite, 465401; (<b>x</b>)—tremolite with phlogopite cut by romaneshite? 464401. Act—actinolite, Ap—apatite, Brt—barite, Cal—calcite, Chl—chlorite, Cr-Mag—Cr-rich magnetite, Di—diopside, Dol—dolomite, Ep—epidote, Fl—fluorite, Fo—forsterite, Gn—galena, Gp—gypsum, Mei—meionite, Mn—Mn minerals, Mol—molybdenite, Phl—phlogopite, Prh—prehnite, Py—pyrite, Sp—sphalerite, Srp—serpentine, Tr—tremolite, Ttn—titanite, Zrn—zircon.</p>
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16 pages, 6426 KiB  
Article
Unveiling Illumination Variations During a Lunar Eclipse: Multi-Wavelength Spaceborne Observations of the January 21, 2019 Event
by Min Shu, Tianyi Xu, Wei Cai, Shibo Wen, Hengyue Jiao and Yunzhao Wu
Remote Sens. 2024, 16(22), 4181; https://doi.org/10.3390/rs16224181 - 9 Nov 2024
Viewed by 355
Abstract
Space-based observations of the total lunar eclipse on 21 January 2019 were conducted using the geostationary Earth-orbiting satellite Gaofen-4 (GF-4). This study represents a pioneering effort to address the observational gap in full-disk lunar eclipse photometry from space. With its high resolution and [...] Read more.
Space-based observations of the total lunar eclipse on 21 January 2019 were conducted using the geostationary Earth-orbiting satellite Gaofen-4 (GF-4). This study represents a pioneering effort to address the observational gap in full-disk lunar eclipse photometry from space. With its high resolution and ability to capture the entire lunar disk, GF-4 enabled both quantitative and qualitative analyses of the variations in lunar brightness, as well as spectra and color changes, across two spatial dimensions, from the whole lunar disk to resolved regions. Our results indicate that before the totality phase of the lunar eclipse, the irradiance of the Moon diminishes to below approximately 0.19% of that of the uneclipsed Moon. Additionally, we observed an increase in lunar brightness at the initial entry into the penumbra. This phenomenon is attributed to the opposition effect, providing scientific evidence for this unexpected behavior. To investigate detailed spectral variations, specific calibration sites, including the Chang’E-3 landing site, MS-2 in Mare Serenitatis, and the Apollo 16 highlands, were analyzed. Notably, the red-to-blue ratio dropped below 1 near the umbra, contradicting the common perception that the Moon appears red during lunar eclipses. The red/blue ratio images reveal that as the Moon enters Earth’s umbra, it does not simply turn red; instead, a blue-banded ring appears at the boundary due to ozone absorption and the lunar surface composition. These findings significantly enhance our understanding of atmospheric effects on lunar eclipses and provide crucial reference information for the future modeling of lunar eclipse radiation, promoting the integration of remote sensing science with astronomy. Full article
(This article belongs to the Special Issue Laser and Optical Remote Sensing for Planetary Exploration)
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<p>The effects of removing bad pixels and bad columns for GF-4 B2. (<b>a</b>) Before bad pixels removal; (<b>b</b>) After bad pixels removal; (<b>c</b>) before bad columns removal; (<b>d</b>) after bad columns removal.</p>
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<p>GF-4 B4 image mosaic (<b>Top</b>) and true color image mosaic (red: B4; green: B3; and blue: B2) (<b>Bottom</b>) before and after flat-field correction ((<b>Left</b>): before; (<b>Right</b>): after). The non-uniformity problems between the two stripe areas are significantly resolved.</p>
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<p>An overview of lunar radiation images obtained with a 30 ms exposure time during the lunar eclipse on 21 January 2019, presented in true color (red: B4; green: B3; and blue: B2). A 2% linear stretch was applied to these images for display enhancement to improve visibility.</p>
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<p>Disk-integrated irradiance at the standard distances during the lunar eclipse on 21 January 2019, measured by GF-4 across spectral bands B2–B5. Six sets of double-dotted lines depict each stage of the eclipse, denoted as P1–P4.</p>
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<p>Three sites in GF-4 color mosaic images captured at 02:30 UTC. (1) CE-3, (2) MS-2, and (3) Apollo-16 highlands. Due to the influence of observational geometry and fact that Site (3) is located in highlands, the brightness observed at site (3) is significantly higher than that of other sites. Consequently, a 2% linear stretch was specifically applied to Site (3) to enhance image contrast.</p>
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<p>The radiance spectra variation of CE-3 (<b>Top</b>), MS-2 (<b>Middle</b>) and Apollo 16 highlands (<b>Bottom</b>).</p>
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<p>Ratio of eclipsed irradiance to uneclipsed irradiance at corresponding phase angles over time, utilizing the lunar photometric model for GF-4 B2.</p>
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<p>Ratio images (654 nm/491 nm) from GF-4 data captured at 03:30 UTC, 03:40 UTC, 03:50 UTC, and 04:10 UTC on 21 January 2019.</p>
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13 pages, 7732 KiB  
Article
Formation Mechanism of Crystal Spots in Jian Kiln Oil-Spot Glaze Revealed by Simulation Experiments
by Caishui Jiang, Junming Wu, Jianer Zhou, Ting Luo, Qifu Bao and Kun Liu
Appl. Sci. 2024, 14(22), 10210; https://doi.org/10.3390/app142210210 - 7 Nov 2024
Viewed by 360
Abstract
The crystalline morphology and glaze color of Jian Kiln oil-spot glaze porcelain exhibit artistic beauty, making it one of the typical representatives of iron-based crystallized black porcelain from the Song Dynasty in China. This study sampled a series of specimens from key temperature [...] Read more.
The crystalline morphology and glaze color of Jian Kiln oil-spot glaze porcelain exhibit artistic beauty, making it one of the typical representatives of iron-based crystallized black porcelain from the Song Dynasty in China. This study sampled a series of specimens from key temperature points during simulation experiments, employing rapid air quenching to preserve the high-temperature state, capturing the formation process of oil-spot glaze crystals in Jian kiln ceramics. Key samples were subjected to microscopic structure and phase analysis using scanning electron microscopy (SEM), laser Raman spectroscopy (LRS), and X-ray photoelectron spectroscopy (XPS), revealing the formation mechanism of oil-spot glaze crystals in Jian kiln ceramics. The results indicate that the bubbles generated from the decomposition of iron oxide at high temperatures facilitate the migration and enrichment of iron-rich particles towards the glaze surface, laying a crucial material foundation for the subsequent crystallization process. The high-temperature reducing atmosphere accelerates the decomposition reaction of iron oxide, altering the concentration of Fe2+ in the glaze, the viscosity of the melt, and the surface tension, all of which are critical conditions that promote the formation of oil-spot glaze crystals. During the cooling phase, Fe3O4 nanocrystals oxidize into ε-Fe2O3 crystals, with external iron sources migrating inward to support ε-Fe2O3 crystal growth. This process gradually leads to the formation of micrometer-scale, leaf-shaped ε-Fe2O3 crystals that fully occupy the crystalline spots. The coloration of crystalline spots is closely tied to the size of the crystals. Thus, by adjusting the cooling regime, it is possible to create iron-based crystallization glazes with innovative color effects. Furthermore, this study offers significant insights for understanding the crystallization mechanisms of other ancient Chinese high-temperature iron-based crystallization glazes. Full article
(This article belongs to the Special Issue Archaeological Analysis and Characterization of Ceramics Materials)
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<p>Firing curve and photographs of samples RC-1 to RC-9 taken at different temperature points from the kiln.</p>
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<p>Optical images of samples RC-1 to RC-9.</p>
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<p>(<b>a</b>) Micromorphology of the crystalline spot region on the glaze surface of sample RC-2; (<b>b</b>) Raman spectrum of the crystalline spot region; (<b>c</b>) micromorphology of the cross-section of the glaze layer in sample RC-2; (<b>d</b>) enlarged morphology of the rectangular region in the glaze layer from Figure (<b>c</b>).</p>
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<p>(<b>a</b>) shows the microstructure of the glaze surface of sample RC-4; (<b>b</b>) presents the Raman spectrum of the glaze surface of sample RC-3; (<b>c</b>) illustrates the microstructure of the glaze surface of sample RC-4; (<b>d</b>) displays the Raman spectrum of the glaze surface of sample RC-4.</p>
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<p>(<b>a</b>) shows the microstructure of the crystalline spot region on the glaze surface of sample RC-5; (<b>b</b>) illustrates the magnified microstructure of the rectangular area in (<b>a</b>); (<b>c</b>) presents the Raman spectrum of the crystalline spot region of sample RC-5.</p>
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<p>(<b>a</b>) shows the fitted peak spectrum of the Fe 2p orbital for sample RC-4 glaze; (<b>b</b>) displays the fitted peak spectrum for sample RC-5 glaze.</p>
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<p>(<b>a</b>) shows an optical photograph of the glaze surface of sample RC-7; (<b>b</b>) SEM image of region A in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>c</b>) SEM image of region B in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>d</b>) SEM image of region C in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>e</b>) Mapping image of region C in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>f</b>) RC-7-A, RC-7-B, RC-7-C are the Raman spectra of the A, B, and C regions of sample RC-7, respectively.</p>
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<p>(<b>a</b>) shows an optical photograph of the glaze surface of sample RC-7; (<b>b</b>) SEM image of region A in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>c</b>) SEM image of region B in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>d</b>) SEM image of region C in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>e</b>) Mapping image of region C in <a href="#applsci-14-10210-f007" class="html-fig">Figure 7</a>a; (<b>f</b>) RC-7-A, RC-7-B, RC-7-C are the Raman spectra of the A, B, and C regions of sample RC-7, respectively.</p>
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<p>Schematic diagram of the formation process of oil-spot glaze crystal spots in Jian kiln.</p>
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21 pages, 6346 KiB  
Article
Novel Steganographic Method Based on Hermitian Positive Definite Matrix and Weighted Moore–Penrose Inverses
by Selver Pepić, Muzafer Saračević, Aybeyan Selim, Darjan Karabašević, Marija Mojsilović, Amor Hasić and Pavle Brzaković
Appl. Sci. 2024, 14(22), 10174; https://doi.org/10.3390/app142210174 - 6 Nov 2024
Viewed by 381
Abstract
In this paper, we describe the concept of a new data-hiding technique for steganography in RGB images where a secret message is embedded in the blue layer of specific bytes. For increasing security, bytes are chosen randomly using a random square Hermitian positive [...] Read more.
In this paper, we describe the concept of a new data-hiding technique for steganography in RGB images where a secret message is embedded in the blue layer of specific bytes. For increasing security, bytes are chosen randomly using a random square Hermitian positive definite matrix, which is a stego-key. The proposed solution represents a very strong key since the number of variants of positive definite matrices of order 8 is huge. Implementing the proposed steganographic method consists of splitting a color image into its R, G, and B channels and implementing two segments, which take place in several phases. The first segment refers to embedding a secret message in the carrier (image or text) based on the unique absolute elements values of the Hermitian positive definite matrix. The second segment refers to extracting a hidden message based on a stego-key generated based on the Hermitian positive definite matrix elements. The objective of the data-hiding technique using a Hermitian positive definite matrix is to embed confidential or sensitive data within cover media (such as images, audio, or video) securely and imperceptibly; by doing so, the hidden data remain confidential and tamper-resistant while the cover media’s visual or auditory quality is maintained. Full article
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<p>Universal scenario for data embedding.</p>
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<p>Carrier image.</p>
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<p>R, G, and B channels of carrier.</p>
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<p>Base64 of the B channel.</p>
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<p>Binary of the B channel.</p>
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<p>Binary of the B channel with an embedded secret message.</p>
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<p>Base64 of the B channel with an embedded secret message.</p>
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<p>B channel with an embedded secret message.</p>
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<p>Original image with an embedded secret message.</p>
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<p>General scenario for data extraction.</p>
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<p>Histogram of the original B channel of the image.</p>
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<p>Histogram of the B channel of stego-image with a secret massage.</p>
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<p>The result of comparing histograms of the original and stego-images.</p>
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<p>Input parameters in the process of embedding data.</p>
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<p>Comparison of entropy (original vs. stego-image).</p>
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<p>Distribution of bits in the stego-image.</p>
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<p>Uniform distribution on R, G, and B channels in the stego-image.</p>
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<p>Detection percentage for 12 test cases for 5 types of attacks (series 1, 2, ...5).</p>
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11 pages, 3095 KiB  
Article
Electrodeposition of Sn-Ru Alloys by Using Direct, Pulsed, and Pulsed Reverse Current for Decorative Applications
by Margherita Verrucchi, Giulio Mazzoli, Andrea Comparini, Roberta Emanuele, Marco Bonechi, Ivan Del Pace, Walter Giurlani, Claudio Fontanesi, Remigiusz Kowalik and Massimo Innocenti
Materials 2024, 17(21), 5326; https://doi.org/10.3390/ma17215326 - 31 Oct 2024
Viewed by 424
Abstract
Pulsed current has proven to be a promising alternative to direct current in electrochemical deposition, offering numerous advantages regarding deposit quality and properties. Concerning the electrodeposition of metal alloys, the role of pulsed current techniques may vary depending on the specific metals involved. [...] Read more.
Pulsed current has proven to be a promising alternative to direct current in electrochemical deposition, offering numerous advantages regarding deposit quality and properties. Concerning the electrodeposition of metal alloys, the role of pulsed current techniques may vary depending on the specific metals involved. We studied an innovative tin–ruthenium electroplating bath used as an anti-corrosive layer for decorative applications. The bath represents a more environmentally and economically viable alternative to nickel and palladium formulations. The samples obtained using both direct and pulsed currents were analyzed using various techniques to observe any differences in thickness, color, composition, and morphology of the deposits depending on the pulsed current waveform used for deposition. Full article
(This article belongs to the Special Issue Corrosion and Corrosion Inhibition of Materials)
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<p>Cyclic voltammetries of the two metal components, 50 °C, 10 mV/s. Matrix: SC 30 g/L, ST 120 g/L, KOH 1 g/L; pH: 13.5. (<b>a</b>) Matrix with Sn 8 g/L, pH: 13.5. From −0.5 V to −1.4; −1.5; −1.8 V to −0.5 V. (<b>b</b>) Matrix with Ru 250 mg/L, pH: 9. From 0 V to −1.3; −1.4; −1.5 V to 1.1 V to 0 V. The Sn(IV) and Ru(III) oxidation peaks are at −1 V and +1 V, respectively.</p>
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<p>Chronopotentiometries of the electroplating bath containing all the components (black line) and all the components except Ru (blue line) or Sn (red line), J: 1 A/dm<sup>2</sup>, 50 °C, 30 s.</p>
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<p>Composition (<b>a</b>) and thickness (<b>b</b>) of samples measured by both XRF and EDS techniques. DC samples were indicated with pulsed time = 0 ms; for PRC samples, the pulsed times correspond to the t<sub>C</sub> times (2, 5, 10 ms). XRF data are expressed as the mean (and standard deviation) of three successive measurements made on the same point.</p>
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<p>Colorimetric differences (<math display="inline"><semantics> <mrow> <mo>Δ</mo> <mi>E</mi> </mrow> </semantics></math> <math display="inline"><semantics> <mrow> <mo>=</mo> <mo>√</mo> <mo>(</mo> <msub> <mrow> <mi>L</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>−</mo> <msub> <mrow> <mi>L</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <msup> <mrow> <mo>)</mo> </mrow> <mrow> <mn>2</mn> </mrow> </msup> <mo>+</mo> <mo>(</mo> <msub> <mrow> <mi>a</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>−</mo> <msub> <mrow> <mi>a</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <msup> <mrow> <mo>)</mo> </mrow> <mrow> <mn>2</mn> </mrow> </msup> <mo>+</mo> <mo>(</mo> <msub> <mrow> <mi>b</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>−</mo> <msub> <mrow> <mi>b</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <msup> <mrow> <mo>)</mo> </mrow> <mrow> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>). The values were calculated and compared for the PC samples to the two corresponding DC samples (0.5 A/dm<sup>2</sup>: light grey and 1 A/dm<sup>2</sup>: grey). For the PRC samples (dark grey), the values were calculated with respect to the 1 A/dm<sup>2</sup> DC sample. DC (blue) refers to the color difference between the two samples at 1 and 0.5 A/dm<sup>2</sup>.</p>
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<p>XRF thickness maps of the Sn-Ru deposit. (<b>a</b>) DC sample 1 A/dm<sup>2</sup>, (<b>b</b>) PC 2 ms, (<b>c</b>) PC 5 ms, (<b>d</b>) PC 10 ms, (<b>e</b>) PRC 2 ms, (<b>f</b>) PRC 5 ms, (<b>g</b>) PRC 10 ms. Data were acquired on the four corners (0.5 cm away from the edges) and in the center of the samples.</p>
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<p>XRD patterns of Sn-Ru deposits obtained by using direct (DC), pulsed (PC with t = 2 ms), and pulsed reverse (PRC with t<sub>C</sub> = 2 ms) current. Substrate: brass/Cu/bronze/Au; 2<math display="inline"><semantics> <mrow> <mi>θ</mi> </mrow> </semantics></math>: 35–60°, increment: 0.03°, 1 s/step, grazing angle geometry. The attributions were made with the PDF-5+ 2024 database. Black: Sn (asterisk) and SnO<sub>x</sub> (circle) reflections, light blue: Ru<sub>3</sub>Sn<sub>7</sub> alloy (asterisk) and Ru<sub>2</sub>Sn<sub>3</sub> alloy (circle), violet: Ru reflections (asterisk).</p>
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20 pages, 2702 KiB  
Review
Lost in the Dark: Current Evidence and Knowledge Gaps About Microplastic Pollution in Natural Caves
by Manuela Piccardo and Stanislao Bevilacqua
Environments 2024, 11(11), 238; https://doi.org/10.3390/environments11110238 - 29 Oct 2024
Viewed by 561
Abstract
In this study, a systematic review of the scientific literature was carried out to summarize the emerging evidence on microplastic pollution in natural caves. After the screening of 655 papers on the topic from a combined search on the Web of Knowledge and [...] Read more.
In this study, a systematic review of the scientific literature was carried out to summarize the emerging evidence on microplastic pollution in natural caves. After the screening of 655 papers on the topic from a combined search on the Web of Knowledge and the Scopus databases, we found only 14 studies reporting quantitative data on microplastics from a total of 27 natural caves. Most of the assessments focused on water and sediment, with very limited investigations concerning the cave biota. Overall, the most common types of particles found in caves were small (<1 mm) fibers (~70–90% of items), transparent or light-colored, mostly made of polyethylene and polyethylene terephthalate. Anthropogenic cellulosic materials, however, represented a non-negligible portion of particles (i.e., ~20–30%). Microplastic concentrations in caves varied between 0.017 and 911 items/L for water and 7.9 and 4777 items/kg for sediment, thus falling within the levels of microplastic pollution found in other terrestrial, freshwater, and marine environments. Levels of microplastic pollution appear largely variable among caves, stressing the need to extend the geographic and environmental ranges of the assessments, which are currently concentrated on Italian caves on land, with very few case studies from other regions of the world and from marine caves. Despite their putative isolation, natural caves have a high vulnerability to microplastic contamination, requiring much more research effort to understand the potential risk that plastics pose to these fragile ecosystems. Full article
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<p>PRISMA 2020 flow diagram adopted for the systematic review presented [<a href="#B22-environments-11-00238" class="html-bibr">22</a>].</p>
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<p>Identikit of the most representative micro-particles detected in water samples collected in natural caves according to the (<b>a</b>) type, (<b>b</b>) polymer (anthropogenic cellulose = natural cellulose with the presence of chemicals such as dyes, PE = polyethylene, PP = polypropylene, PET = polyethylene terephthalate, PVC = polyvinyl chloride, polyester), (<b>c</b>) color, and (<b>d</b>) class of size. na = not available. Graphs created with Infogram (<a href="https://infogram.com/" target="_blank">https://infogram.com/</a>, accessed on 20 October 2024).</p>
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<p>Identikit of the most representative micro-particles detected in sediment samples collected in natural caves according to the (<b>a</b>) type, (<b>b</b>) polymer (anthropogenic cellulose, PE = polyethylene, PP = polypropylene, PET = polyethylene terephthalate, copolymer), (<b>c</b>) color, and (<b>d</b>) class of size. na = not available. Graphs created with Infogram (<a href="https://infogram.com/" target="_blank">https://infogram.com/</a>, accessed on 20 October 2024).</p>
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<p>Maximum levels of micro-particle/plastic pollution in (<b>a</b>) sediment and (<b>b</b>) water collected worldwide in cave systems. For the correct interpretation of the reference ID, refer to <a href="#environments-11-00238-t001" class="html-table">Table 1</a>.</p>
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<p>Geographical distribution of studies performed on microplastics in cave systems. A special focus on the Italian and Slovenian Karst regions (the most studied areas). Data are shown as percentage of contamination with respect to the maximum (for sediments: Balestra et al. 2024b [<a href="#B32-environments-11-00238" class="html-bibr">32</a>], reference ID = 10; for waters: Sforzi et al. 2024 [<a href="#B24-environments-11-00238" class="html-bibr">24</a>], reference ID = 2). The graphs have been placed inside boxes of different colors, corresponding to the different sub-regions. Numbers in the global map and in bar plots refer to paper ID in <a href="#environments-11-00238-t001" class="html-table">Table 1</a>.</p>
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<p>Ranges (min–max) of particle concentrations in water and sediment from marine (including brackish and estuarine systems), lake (including lakes, ponds, and reservoirs), riverine (including canal, streams, and rivers), soil (water: groundwater including aquifer and wells; sediment: agricultural, urban, and rural soil), and cave environmental compartments. Numbers in brackets indicate the approximate average concentration. For each environmental matrix in each compartment, the most common type of particles, polymers, and colors are also shown (for types of particles and colors, two symbols indicate an almost equal contribution). Data are from the following sources—marines: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B50-environments-11-00238" class="html-bibr">50</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B52-environments-11-00238" class="html-bibr">52</a>,<a href="#B53-environments-11-00238" class="html-bibr">53</a>,<a href="#B54-environments-11-00238" class="html-bibr">54</a>,<a href="#B55-environments-11-00238" class="html-bibr">55</a>,<a href="#B56-environments-11-00238" class="html-bibr">56</a>,<a href="#B57-environments-11-00238" class="html-bibr">57</a>,<a href="#B58-environments-11-00238" class="html-bibr">58</a>]; lakes: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B59-environments-11-00238" class="html-bibr">59</a>,<a href="#B60-environments-11-00238" class="html-bibr">60</a>,<a href="#B61-environments-11-00238" class="html-bibr">61</a>]; rivers: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B58-environments-11-00238" class="html-bibr">58</a>,<a href="#B60-environments-11-00238" class="html-bibr">60</a>,<a href="#B61-environments-11-00238" class="html-bibr">61</a>,<a href="#B62-environments-11-00238" class="html-bibr">62</a>,<a href="#B63-environments-11-00238" class="html-bibr">63</a>,<a href="#B64-environments-11-00238" class="html-bibr">64</a>]; soil: [<a href="#B48-environments-11-00238" class="html-bibr">48</a>,<a href="#B49-environments-11-00238" class="html-bibr">49</a>,<a href="#B51-environments-11-00238" class="html-bibr">51</a>,<a href="#B65-environments-11-00238" class="html-bibr">65</a>,<a href="#B66-environments-11-00238" class="html-bibr">66</a>,<a href="#B67-environments-11-00238" class="html-bibr">67</a>,<a href="#B68-environments-11-00238" class="html-bibr">68</a>]; caves: this study.</p>
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24 pages, 8204 KiB  
Article
A Comprehensive Method for Example-Based Color Transfer with Holistic–Local Balancing and Unit-Wise Riemannian Information Gradient Acceleration
by Zeyu Wang, Jialun Zhou, Song Wang and Ning Wang
Entropy 2024, 26(11), 918; https://doi.org/10.3390/e26110918 - 29 Oct 2024
Viewed by 460
Abstract
Color transfer, an essential technique in image editing, has recently received significant attention. However, achieving a balance between holistic color style transfer and local detail refinement remains a challenging task. This paper proposes an innovative color transfer method, named BHL, which stands for [...] Read more.
Color transfer, an essential technique in image editing, has recently received significant attention. However, achieving a balance between holistic color style transfer and local detail refinement remains a challenging task. This paper proposes an innovative color transfer method, named BHL, which stands for Balanced consideration of both Holistic transformation and Local refinement. The BHL method employs a statistical framework to address the challenge of achieving a balance between holistic color transfer and the preservation of fine details during the color transfer process. Holistic color transformation is achieved using optimal transport theory within the generalized Gaussian modeling framework. The local refinement module adjusts color and texture details on a per-pixel basis using a Gaussian Mixture Model (GMM). To address the high computational complexity inherent in complex statistical modeling, a parameter estimation method called the unit-wise Riemannian information gradient (uRIG) method is introduced. The uRIG method significantly reduces the computational burden through the second-order acceleration effect of the Fisher information metric. Comprehensive experiments demonstrate that the BHL method outperforms state-of-the-art techniques in both visual quality and objective evaluation criteria, even under stringent time constraints. Remarkably, the BHL method processes high-resolution images in an average of 4.874 s, achieving the fastest processing time compared to the baselines. The BHL method represents a significant advancement in the field of color transfer, offering a balanced approach that combines holistic transformation and local refinement while maintaining efficiency and high visual quality. Full article
(This article belongs to the Topic Color Image Processing: Models and Methods (CIP: MM))
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<p>Overview of the BHL method.</p>
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<p>Source image: purple flower; Example image: tomato.</p>
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<p>Source image: blue flower; Example image: mountain.</p>
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<p>Source image: clusters; Example image: parrot.</p>
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<p>Source image: pink flower; Example image: sunflower.</p>
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<p>Source image: bouquet; Example image: seaside.</p>
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<p>Comparison of details with zoomed-in images.</p>
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<p>Comparison of uRIG with SGD, AIG, and Adam.</p>
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13 pages, 4617 KiB  
Communication
Assessing Wear Characteristics of Sprayable, Diacetylene-Containing Sensor Formulations
by Priyanka Shiveshwarkar, Anthony David Nelson, My Thi Nguyen and Justyn Jaworski
Sensors 2024, 24(21), 6925; https://doi.org/10.3390/s24216925 - 29 Oct 2024
Viewed by 358
Abstract
This work extends recent developments in diacetylene-based, sprayable sensors by identification and assessment of formulations which facilitate their use for wearable sensing. Diacetylene-based spray-on sensors have the potential to be a widely deployed sensing technology, as they require no power and can be [...] Read more.
This work extends recent developments in diacetylene-based, sprayable sensors by identification and assessment of formulations which facilitate their use for wearable sensing. Diacetylene-based spray-on sensors have the potential to be a widely deployed sensing technology, as they require no power and can be applied as thin coatings onto surfaces to provide a colorimetric response to target exposure. In responding to radiation, liquid-phase targets, or gas-phase targets specifically determined by the formulation of the sprayable sensor used, this technology is amenable to wearable sensors for measuring exposure to different environmental risks. Here, we provide the means to improve wear resistance, reduce false-positive signals due to wetting, and enhance color fastness for coatings of sprayable, diacetylene-based sensor formulations on cotton fabric. These sensor formulations possess polymethyl methacrylate (PMMA), which enhances the coating stability to only 8% color loss due to wear compared to 18–25% without PMMA, while maintaining the inherent ability of diacetylene-component formulations to detect radiation as well as gas or liquid phase analytes. This represents a significant step toward the use of diacetylene-based sensing formulations for wearable sensing. In the future, the form of spray-on sensor materials demonstrated here may find use in wearable sensing applications for detection of cumulative exposure to UV radiation, hydrogen peroxide vapors, or solvent exposure. We expect trends toward applications toward other wearable sensors for environmental monitoring given the well-known customizability in target response of diacetylene-containing monomers by modifying their headgroup chemistry. Full article
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Figure 1
<p>Overview of our study in utilizing PMMA to enhance the wear resistance of PCDA-based, spray-on sensor coatings with assessment after implementing a crockmeter for providing controlled abrasion of coated fabrics.</p>
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<p>The effect of PMMA concentration and UV polymerization on the amount of coating lost due to crocking was examined. PCDA solutions of 20 mg/mL containing different concentrations of PMMA, and different extents of UV irradiation, were subjected to 10 rounds of dry crocking. Relative change in the % darkness of the coating was calculated by the difference between the (100-L*) values before and after 10 cycles of dry crocking. This difference was then divided by the (100-L*) value before crocking, and the percentage value was obtained.</p>
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<p>Color fastness (transfer of PCDA from the coatings to the crock meter squares) was examined as a function of PMMA concentration within the spray formulations. The darkness of the transferred color (100−L*) values for each crock meter square are reported, which represent the amount of PCDA coating transferred onto the crock meter square used for rubbing the substrate in each case.</p>
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<p>Retention of function of the diacetylene coating to generate a polymerization response upon exposure to H<sub>2</sub>O<sub>2</sub> vapor was examined. Diacetylene solutions containing different concentrations of PMMA were coated on separate cotton substrates and subjected to 10 rounds of crocking. The crocked and uncrocked samples were exposed to H<sub>2</sub>O<sub>2</sub> vapor at different concentrations. The color change was measured by calculating the CIELAB color space distance using the a* and b* values of the substrate before and after exposure to H<sub>2</sub>O<sub>2</sub> vapor.</p>
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<p>Retention of function of the diacetylene coating to undergo a color change upon exposure to solvent was examined, specifically using 100% ethanol. PCDA formulations with different concentrations of PMMA were coated onto cotton fabric, exposed to UV for polymerization, and subjected to 10 rounds of dry crocking. The samples were then exposed to ethanol, revealing an observable color change. The color change was calculated by applying the CIEDE2000 color-difference formula for ΔE* which uses the L*, a*, and b* values measured for the substrate before and after exposure to 100% ethanol to determine the solvent responsiveness (solvatochromism).</p>
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<p>Upon wetting and drying of the polydiacetylene coated cotton strips, a color change was observed to have taken place from blue to purple/pink, depending on the concentration of the polydiacetylene solution in the specific region in the gradient. To investigate this further, decreasing concentration of PCDA were spray-coated onto the cotton fabric strips, and it was observed that at lower concentrations, the color change was more apparent. Upon addition of 17 mg/mL PMMA to this formulation, no change in color was observed, thus retaining its use as a colorimetric sensor for detection of stimuli.</p>
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<p>Optical microscopy images of cotton fabric without spray-on sensor coating (<b>left</b>), with spray coating formulation of 20 mg/mL PCDA (<b>middle</b>), or with spray coating formulation of 20 mg/mL PCDA containing 17 mg/mL PMMA (<b>right</b>). Coatings were UV polymerized for 10 s. (Scale bars indicate 0.2 mm.)</p>
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