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Search Results (3,233)

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20 pages, 11405 KiB  
Article
Characterization of Three-Dimensional Strong Force Chain Properties of Mineral Aggregate Mixtures Based on the Discrete Element Method
by Yuan Gao, Guoqiang Liu and Nan Jiang
Buildings 2024, 14(10), 3289; https://doi.org/10.3390/buildings14103289 (registering DOI) - 17 Oct 2024
Abstract
The skeleton structure composed of mineral aggregates is the main body to bear and transfer external loading in asphalt mixtures. To investigate the loading transfer mechanism of the mineral aggregate skeleton, the uniaxial penetration test and Discrete Element Method (DEM) were conducted for [...] Read more.
The skeleton structure composed of mineral aggregates is the main body to bear and transfer external loading in asphalt mixtures. To investigate the loading transfer mechanism of the mineral aggregate skeleton, the uniaxial penetration test and Discrete Element Method (DEM) were conducted for the Mineral Aggregate Mixture (MAM) to analyze its mechanical behavior. The three-dimensional strong force chain (SFC) was identified and evaluated based on the proposed recognition criterion and evaluation indices. The results indicate that 4.75 mm should be the boundary to distinguish the coarse and fine aggregates. The skeleton composed of aggregates located on SFCs has better bearing and transferring loading capacity due to its SFC number, average length, and total length decreasing with an increase in the aggregate size. Compared to SMA-16 and OGFC-16, AC-16 exhibits a higher number and total length of its SFC, a smaller average length of its SFC, and a lower average strength of its SFC. Consequently, AC-16 has a lower bearing and transferring loading capacity than that of SMA-16 and OGFC-16. In addition, approximately 90% of SFCs can only transfer external loading downward through 3–5 aggregates. The average direction angle of the SFC formed by fine aggregates is significantly higher than those formed by coarse aggregates. This indicates that the load transfer range of MAM composed of fine aggregates is noticeably larger, leading to lower loading transfer efficiency. Full article
(This article belongs to the Special Issue Advances in Performance-Based Asphalt and Asphalt Mixtures)
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Figure 1
<p>Gradation curves of different MAM.</p>
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<p>Different DEM specimens of MAMs: (<b>a</b>) 9.50–13.2 mm; (<b>b</b>) 4.75–9.50 mm; (<b>c</b>) 2.36–4.75 mm (<b>d</b>) AC-16; (<b>e</b>) SMA-16; (<b>f</b>) OGFC-16.</p>
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<p>Schematic diagram of linear contact model.</p>
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<p>Different single-sized MAMs: (<b>a</b>) 19.0–26.5 mm; (<b>b</b>) 16.0–19.0 mm; (<b>c</b>) 13.2–16.0 mm (<b>d</b>) 9.50–13.2 mm; (<b>e</b>) 4.75–9.50 mm; (<b>f</b>) 2.36–4.75 mm.</p>
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<p>Experimental instruments: (<b>a</b>) test cylinder size diagram; (<b>b</b>) penetration head; (<b>c</b>) pavement strength tester, which can load the specimen at a constant speed of 1.25 mm/min.</p>
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<p>Penetration resistance curve of SMAMs: (<b>a</b>) coarse aggregates; (<b>b</b>) fine aggregates.</p>
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<p>Penetration resistance curve of DEM specimens: (<b>a</b>) SMAMs; (<b>b</b>) GMAMs.</p>
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<p>The virtual uniaxial penetration test program.</p>
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<p>Contact angle threshold.</p>
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<p>“Crescent-shaped” SFC.</p>
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<p>Force-extension γ diagram.</p>
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<p>Program of SFC recognition algorithm: (<b>a</b>) SFC recognition algorithm; (<b>b</b>) repeat SFC recognition algorithm.</p>
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<p>Mineral skeleton diagram of SMAM with 2.36–4.75 mm.</p>
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<p>The linearity of SFCs.</p>
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<p>The orientation angle of an SFC.</p>
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<p>Identified aggregates located on SFC of SMAMs: (<b>a</b>) 19.0–26.5 mm; (<b>b</b>) 16.0–19.0 mm; (<b>c</b>) 13.2–16.0 mm (<b>d</b>) 9.50–13.2 mm; (<b>e</b>) 4.75–9.50 mm; (<b>f</b>) 2.36–4.75 mm.</p>
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<p>SFC characteristics of SMAMs: (<b>a</b>) the number of SFCs; (<b>b</b>) the average length of the SFCs; (<b>c</b>) the total length of the SFCs; (<b>d</b>) the average particle number in an SFC; (<b>e</b>) particle number distribution; (<b>f</b>) the average linearity; (<b>g</b>) the average orientation angle; (<b>h</b>) the average strength.</p>
Full article ">Figure 17 Cont.
<p>SFC characteristics of SMAMs: (<b>a</b>) the number of SFCs; (<b>b</b>) the average length of the SFCs; (<b>c</b>) the total length of the SFCs; (<b>d</b>) the average particle number in an SFC; (<b>e</b>) particle number distribution; (<b>f</b>) the average linearity; (<b>g</b>) the average orientation angle; (<b>h</b>) the average strength.</p>
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<p>Identified aggregates located on SFCs of different GMAMs: (<b>a</b>) AC-16; (<b>b</b>) SMA-16; (<b>c</b>) OGFC-16.</p>
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<p>The length of the SFC of different GMAMs: (<b>a</b>) the average length of the SFC; (<b>b</b>) the total length of the SFC; (<b>c</b>) the length distribution of SFC.</p>
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<p>The number of particles in SFCs of different GMAMs: (<b>a</b>) average particle number in an SFC; (<b>b</b>) particle number distribution in SFCs.</p>
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<p>The linearity of SFCs of different GMAMs: (<b>a</b>) the average linearity of SFCs; (<b>b</b>) the linearity distribution of SFCs.</p>
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<p>The orientation angle of SFCs of different GMAMs: (<b>a</b>) the average orientation angle of SFCs; (<b>b</b>) the orientation angle distribution of SFCs.</p>
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<p>The strength of SFCs of different GMAMs: (<b>a</b>) the average strength of SFCs; (<b>b</b>) the strength distribution of SFCs.</p>
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19 pages, 6491 KiB  
Article
Identification and Location Method of Bitter Gourd Picking Point Based on Improved YOLOv5-Seg
by Sheng Jiang, Yechen Wei, Shilei Lyu, Hualin Yang, Ziyi Liu, Fangnan Xie, Jiangbo Ao, Jingye Lu and Zhen Li
Agronomy 2024, 14(10), 2403; https://doi.org/10.3390/agronomy14102403 (registering DOI) - 17 Oct 2024
Abstract
Aiming at the problems of small stems and irregular contours of bitter gourd, which lead to difficult and inaccurate location of picking points in the picking process of mechanical arms, this paper proposes an improved YOLOv5-seg instance segmentation algorithm with a coordinate attention [...] Read more.
Aiming at the problems of small stems and irregular contours of bitter gourd, which lead to difficult and inaccurate location of picking points in the picking process of mechanical arms, this paper proposes an improved YOLOv5-seg instance segmentation algorithm with a coordinate attention (CA) mechanism module, and combines it with a refinement algorithm to identify and locate the picking points of bitter gourd. Firstly, the improved algorithm model was used to identify and segment bitter gourd and melon stems. Secondly, the melon stem mask was extracted, and the thinning algorithm was used to refine the skeleton of the extracted melon stem mask image. Finally, a skeleton refinement graph of bitter gourd stem was traversed, and the midpoint of the largest connected region was selected as the picking point of bitter gourd. The experimental results show that the prediction precision (P), precision (R) and mean average precision (mAP) of the improved YOLOv5-seg model in object recognition were 98.04%, 97.79% and 98.15%, respectively. Compared with YOLOv5-seg, the P, R and mA values were increased by 2.91%, 4.30% and 1.39%, respectively. In terms of object segmentation, mask precision (P(M)) was 99.91%, mask recall (R(M)) 99.89%, and mask mean average precision (mAP(M)) 99.29%. Compared with YOLOv5-seg, the P(M), R(M), and mAP(M) values were increased by 6.22%, 7.81%, and 5.12%, respectively. After testing, the positioning error of the three-dimensional coordinate recognition of bitter gourd picking points was X-axis = 7.025 mm, Y-axis =5.6135 mm, and Z-axis = 11.535 mm, and the maximum allowable error of the cutting mechanism at the end of the picking manipulator was X-axis = 30 mm, Y-axis = 24.3 mm, and Z-axis = 50 mm. Therefore, this results of study meet the positioning accuracy requirements of the cutting mechanism at the end of the manipulator. The experimental data show that the research method in this paper has certain reference significance for the accurate identification and location of bitter gourd picking points. Full article
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<p>Partial sample of data set. (<b>a</b>) Original image; (<b>b</b>) random noise added; (<b>c</b>) random dimming; (<b>d</b>) random brightening.</p>
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<p>Partial sample of data set. (<b>a</b>) Original image; (<b>b</b>) random noise added; (<b>c</b>) random dimming; (<b>d</b>) random brightening.</p>
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<p>Data annotation example.</p>
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<p>CSPX structure diagram.</p>
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<p>Res unit structure diagram.</p>
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<p>Improving the YOLOv5-seg model.</p>
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<p>Flowchart of coordinate attention algorithm.</p>
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<p>Eight-field diagram.</p>
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<p>The extracted mask image of bitter gourd stem and its refinement image. (<b>a</b>) Original image of bitter gourd stem segmentation; (<b>b</b>) original picture of bitter gourd stem after thinning; (<b>c</b>) partial enlargement of bitter gourd stem; (<b>d</b>) local magnification of bitter gourd stem refinement.</p>
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<p>Two-dimensional picking point acquisition process. (<b>a</b>) Stem binary map, skeleton map and picking point location map (positioning success); (<b>b</b>) stem binary map, skeleton map and picking point location map (positioning failure).</p>
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<p>Spatial coordinate transform.</p>
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<p>Images taken by the depth camera at the same time. (<b>a</b>) Color map; (<b>b</b>) unaligned depth map; (<b>c</b>) aligned depth map.</p>
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<p>Images taken by the depth camera at the same time. (<b>a</b>) Color map; (<b>b</b>) unaligned depth map; (<b>c</b>) aligned depth map.</p>
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<p>Field deployment diagram of anchor point error test.</p>
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<p>Renderings of different models to identify bitter gourd and its stem. (<b>a</b>) Recognition effect of YOLACT model; (<b>b</b>) recognition effect of Mask R-CNN model; (<b>c</b>) recognition effect of YOLOv5-seg model; (<b>d</b>) recognition effect of YOLOv5-seg+ model.</p>
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<p>Renderings of different models to identify bitter gourd and its stem. (<b>a</b>) Recognition effect of YOLACT model; (<b>b</b>) recognition effect of Mask R-CNN model; (<b>c</b>) recognition effect of YOLOv5-seg model; (<b>d</b>) recognition effect of YOLOv5-seg+ model.</p>
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<p>Three-dimensional coordinate algorithm recognition interface.</p>
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20 pages, 14818 KiB  
Article
Control of Seepage Characteristics in Loose Sandstone Heap Leaching with Staged Particle Sieving-Out Method
by Quan Jiang, Mingtao Jia, Yihan Yang and Chuanfei Zhang
Minerals 2024, 14(10), 1039; https://doi.org/10.3390/min14101039 (registering DOI) - 17 Oct 2024
Abstract
This paper studies the influence of the staged particle sieving-out method on the seepage characteristics in loose sandstone heap leaching. The staged sieving out of ore sample particles was conducted according to particle size, and ground pressure was applied to them. Subsequently, parameters [...] Read more.
This paper studies the influence of the staged particle sieving-out method on the seepage characteristics in loose sandstone heap leaching. The staged sieving out of ore sample particles was conducted according to particle size, and ground pressure was applied to them. Subsequently, parameters such as the permeability, particle distribution, and pore distribution characteristics of the rock samples were obtained to investigate the influence of the staged particle sieving-out method on the seepage effect of loose sandstone heap leaching. The results indicate that sieving out particles smaller than 0.15 mm can significantly reduce the probability of hole blockage and increase the overall pore size, greatly enhancing permeability. Sieving out particles with sizes between 0.15 mm and 1.2 mm can result in the loss of skeleton particles, reducing the amount of flow channels and thereby decreasing permeability. Sieving out particles larger than 1.2 mm can reduce the overall particle size of rock samples, improve strength and pressure stability, and help maintain permeability. In the surface heap leaching of loose sandstone ore, by sieving out particles smaller than 0.15 mm during deep heap construction and sieving out particles larger than 1.2 mm during mid-level heap construction, and by using vat leaching for sieved-out particles, the seepage effect of the ore heap can be significantly optimized, and complete utilization of resources can be ensured. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
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Figure 1
<p>Typical surface heap leaching method and stress analysis of ore heap. (<b>a</b>) Typical structure of a heap leaching field; (<b>b</b>) Stress condition of shallow particles; (<b>c</b>) Stress condition of medium-deep particles; (<b>d</b>) Stress condition of deep particles.</p>
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<p>(<b>a</b>) Particle distribution and (<b>b</b>) pore distribution characteristic curves of the original samples.</p>
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<p>Sample preparation. (<b>a</b>) particle size distribution (<b>b</b>) finished samples.</p>
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<p>Samples after pressurization treatment.</p>
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<p>Depth–permeability relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Particle distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Pore distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Free particle distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Depth–free particle proportion relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Effective seepage pore distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Depth–effective seepage pore proportion relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Relationships of (<b>a</b>) free particle proportion–permeability and (<b>b</b>) effective seepage pore proportion–permeability.</p>
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<p>(<b>a</b>–<b>f</b>) Particle distribution difference curve of Group A−F; (<b>g</b>–<b>l</b>) cumulative particle distribution difference curve of Group A−F.</p>
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<p>(<b>a</b>–<b>f</b>) Pore distribution difference curve of Group A−F; (<b>g</b>–<b>l</b>) cumulative pore distribution difference curve of Group A−F.</p>
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<p>Depth–effective seepage pore proportion/total porosity relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Permeability of various rock samples at different depths.</p>
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<p>B3–A3 and F2–A2 (<b>a</b>) particle difference distribution curve, (<b>b</b>) cumulative particle difference curve, (<b>c</b>) pore difference distribution curve, (<b>d</b>) cumulative pore difference curve.</p>
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24 pages, 17346 KiB  
Article
Detection of Vertebrate Skeletons by Ground Penetrating Radars: An Example from the Ica Desert Fossil-Lagerstätte
by Antonio Schettino, Annalisa Ghezzi, Alberto Collareta, Pietro Paolo Pierantoni, Luca Tassi and Claudio Di Celma
Remote Sens. 2024, 16(20), 3858; https://doi.org/10.3390/rs16203858 (registering DOI) - 17 Oct 2024
Abstract
We present a technique for the detection of vertebrate skeletons buried at shallow depths through the use of a ground-penetrating radar (GPR). The technique is based on the acquisition of high-resolution data by medium-to-high frequency GPR antennas and the analysis of the radar [...] Read more.
We present a technique for the detection of vertebrate skeletons buried at shallow depths through the use of a ground-penetrating radar (GPR). The technique is based on the acquisition of high-resolution data by medium-to-high frequency GPR antennas and the analysis of the radar profiles by a new forward modelling method that is applied on a set of representative traces. This approach allows us to obtain synthetic traces that can be used to build detailed reflectivity diagrams that plot spikes with a distinct amplitude and polarity for each reflector in the ground. The method was tested in a controlled experiment performed at the top of Cerro Los Quesos, one of the most fossiliferous localities in the Ica Desert of Peru. We acquired GPR data at the location of a partially buried fossil skeleton of a large whale and analyzed the reflections associated with the bones using the new technique, determining the possible signature of vertebrae, ribs, the cranium (including the rostrum), and mandibles. Our results show that the technique is effective in the mapping of buried structures, particularly in the detection of tiny features, even below the classical (Ricker and Rayleigh) estimates of the vertical resolution of the antenna in civil engineering and forensic applications. Full article
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Figure 1
<p>Physiography of the study area. (<b>a</b>) Boundaries of the Pisco Basin (yellow line); CLQ = Cerro Los Quesos; NR = Nazca Ridge; (<b>b</b>) survey area at Cerro Los Quesos (purple line). The topography is slightly exaggerated.</p>
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<p>Trace analysis and modelling. In this example, the first 13 ns of a radar profile trace (dashed line) are modelled by the superposition of nine Ricker wavelets with either positive or negative polarity and different amplitudes. The arrival times of these wavelets mark the location of as many reflectors, some of which could not be detected by visual analysis.</p>
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<p>An example of the composition between 90°-phase Ricker wavelets with opposite polarities. The horizontal axis shows two-way travel times. <span class="html-italic">t<sub>c</sub></span> is the wavelet central time. (<b>a</b>) When the two wavelets are spaced by more than ~3 ns, their composition shows two distinct reflections. (<b>b</b>) If we increase the amount of overlap, a coalescent reflection forms, but we can still distinguish two positive peaks associated with the two component wavelets. (<b>c</b>) In the case of two strongly overlapped wavelets, a large amplitude peak forms, which could be erroneously interpreted as resulting from a single reflector separating two media characterized by a strong dielectric contrast. Instead, it results from wavelet interference.</p>
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<p>Top: Shift and reduction in the amplitude spectrum bandwidth with time due to dispersion. A quality factor <span class="html-italic">Q</span><sup>*</sup> = 20 is assumed. Both the peak and central frequencies are shifted to the left. Bottom: Corresponding dispersion of a 90°-phase Ricker wavelet in the time domain.</p>
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<p>Transient instrumental drift. The horizontal axis shows the elapsed time, while the vertical axis shows the observed peak amplitudes (in counts) after AGC gain, bandpass (200–600 MHz) filtering, and stacking (sliding window of width 7). The experiment shows that peaks below ~11 ns TWTT have an initial transient phase of ~600 s, characterized by instrumental drift, which is followed by a more stable phase of quasi-constant amplitude (red dashed lines).</p>
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<p>Mean trace and 1σ instrumental uncertainty. Left: Time-averaged trace &lt;<span class="html-italic">A</span>&gt; (black line) in the stable range between 600 and 1200 s. The dashed red and blue lines show the upper and lower 1σ intervals, respectively. This is the same dataset as that in <a href="#remotesensing-16-03858-f005" class="html-fig">Figure 5</a>. Right: Standard deviations of the mean trace amplitudes in the stable range between 600 and 1200 s (dots). The corresponding linear regression curve (black dashed line) is used in the forward modelling procedures as a depth-dependent estimate of the instrumental uncertainty.</p>
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<p>Large-scale structures and radar stratigraphy at the top of CLQ (Area P5), as observed by a 200 MHz antenna. (<b>a</b>) Geological structures identified on a representative radar profile. The dashed red line is a small-offset normal fault that causes downward slip and the anticlockwise rotation of the layers to the right of the fault plane. Inset <span class="html-italic">I</span> shows an interval characterized by numerous dolomite nodules. <span class="html-italic">T</span> is a representative trace that has been analyzed by forward modelling. <span class="html-italic">L</span><sub>1</sub> and <span class="html-italic">L</span><sub>2</sub> are thin low-velocity layers, while <span class="html-italic">H</span><sub>1</sub> and <span class="html-italic">H</span><sub>1</sub> are thin encapsulated high-velocity layers. Correlation with a key marker bed outcropping at area P4A indicates that the ~20 cm thick layer <span class="html-italic">P</span> around a depth of 400 cm is the Perro horizon described by [<a href="#B13-remotesensing-16-03858" class="html-bibr">13</a>]. <span class="html-italic">X</span> and <span class="html-italic">Y</span> are two reflectors that bound zones with a strong increase in velocity. α is a region of decreasing velocity between <span class="html-italic">H</span><sub>1</sub> and <span class="html-italic">H</span><sub>2</sub>, which can be observed in the radar profiles of area P4A (see below). (<b>b</b>) A model of trace <span class="html-italic">T</span> between zero and 170 ns. (<b>c</b>) A pseudo-reflectivity plot, showing wavelet arrivals, polarities, and scaled reflection amplitudes, and the associated geological interpretation. Green and reddish regions are encapsulated low- and high-velocity zones, respectively. Yellow regions are characterized by a general increase in velocity and can be interpreted as diatomaceous beds.</p>
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<p>Radar stratigraphy of Area P4A, as observed by a 400 MHz antenna. (<b>a</b>) Survey geometry at area P4A on a background DEM image. W is the outcropping part of the vertebral column, N is a surface bulge just above the dolomite nodule, P is the Perro key bed. (<b>b</b>) A radar profile (at <span class="html-italic">x</span> = 0) not affected by the presence of the buried skeleton. T is a representative trace (at <span class="html-italic">x</span> = 1 m). (<b>c</b>) A model of trace T (left) and the corresponding pseudo-reflectivity plot (right). The latter shows wavelet arrivals, polarities, and scaled reflection amplitudes. α is the decreasing velocity region of <a href="#remotesensing-16-03858-f007" class="html-fig">Figure 7</a>, while <span class="html-italic">H</span><sub>1</sub> and <span class="html-italic">H</span><sub>2</sub> are high-velocity beds. Correlation lines (black dashed lines) link the reflectivity peaks to wavelet centers, not to arrival times.</p>
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<p>Amplitude slices at site P4A. (<b>a</b>) Orthomosaic of area P4A after partial excavation and cleaning. The brown envelope around the skeleton is associated with the presence of iron oxides. The dolomite nodule above and around the whale skull is also evident. (<b>b</b>) Reflection amplitudes between 2.5 and 3.4 ns. Blue and red regions have low and high reflectivity, respectively. (<b>c</b>) Reflection amplitudes between 6.7 and 7.6 ns. (<b>d</b>) Reflection amplitudes between 9.5 and 10.5 ns.</p>
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<p>Identification of vertebrae and ribs on the radar profiles of the fossil whale at site P4A. The background image shows an orthomosaic of the whale after partial excavation and cleaning. Fe-Ox = Iron oxide layer; Mn-Ox = Manganese oxide layer; Ox = Iron and manganese oxide envelope around the whale skeleton; N = dolomite nodule; V = vertebral column. The modelling of traces T1 and T2 shows the signature of the vertebral column and some ribs. In these profiles, vertebrae and ribs are embedded in the layer α. Bones are detected as thin structures, bounded by strong reflectivity peaks of opposite polarity.</p>
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<p>Identification of the cranium and mandibles on the radar profiles of the fossil whale at site P4A. C = cranium; SP = supraorbital process; other symbols are the same as in <a href="#remotesensing-16-03858-f010" class="html-fig">Figure 10</a>.</p>
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<p>Identification of rostrum and mandible on the radar profiles of the fossil whale at site P4A. R-M = rostrum/mandible; other symbols are the same as <a href="#remotesensing-16-03858-f010" class="html-fig">Figure 10</a>.</p>
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<p>A reconstruction of the underground between depths of 0 and 130 cm along a cross-section at <span class="html-italic">x</span> = 3.5 m in Area P4A. This reconstruction shows the lateral extent of the high-velocity layers <span class="html-italic">H</span><sub>1</sub> and <span class="html-italic">H</span><sub>2</sub> and the geometry of the depression below the whale head. The small high-contrast brown, blue, and orange regions between <span class="html-italic">x</span> = 8.1 and 8.6 m represent the cranium and the underlying Mn and Fe oxides.</p>
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<p>Identification of dinosaur footprints on a radar profile (top) acquired at Dinosaur Ridge (CO) (data courtesy of L. Conyers). Yellow = sandstone; light green = mudstone. Orange and dark green areas are high- and low-velocity regions, respectively.</p>
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<p>Velocity analysis of area P4A. (<b>a</b>) Spline regression of the rms velocities obtained by hyperbola fitting (black line). Red dots are the observed rms velocities (by the migration procedure). The blue line shows the laterally homogeneous velocity profile, based on Dix’s equation. The numbers refer to layer numbering. (<b>b</b>) Reflectivity plot for area P4A, in terms of TWTT.</p>
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13 pages, 2934 KiB  
Article
Recovery and Restructuring of Fine and Coarse Soil Fractions as Earthen Construction Materials
by Mazhar Hussain, Ines Lamrous, Antony Provost, Nathalie Leblanc, Hafida Zmamou, Daniel Levacher and Abdoulaye Kane
Sustainability 2024, 16(20), 8952; https://doi.org/10.3390/su16208952 - 16 Oct 2024
Viewed by 313
Abstract
Excessive consumption of natural resources to meet the growing demands of building and infrastructure projects has put enormous stress on these resources. On the other hand, a significant quantity of soil is excavated for development activities across the globe and is usually treated [...] Read more.
Excessive consumption of natural resources to meet the growing demands of building and infrastructure projects has put enormous stress on these resources. On the other hand, a significant quantity of soil is excavated for development activities across the globe and is usually treated as waste material. This study explores the potential of excavated soils in the Brittany region of France for its reuse as earthen construction materials. Characterization of soil recovered from building sites was carried out to classify the soils and observe their suitability for earthen construction materials. These characteristics include mainly Atterberg limits, granulometry, organic matter and optimum moisture content. Soil samples were separated into fine and coarse particles through wet sieving. The percentage of fines (particles smaller than 0.063 mm) in studied soil samples range from 28% to 65%. The methylene blue value (MBV) for Lorient, Bruz and Polama soils is 1, 1.2 and 1.2 g/100 g, and French classification (Guide de terrassements des remblais et des couches de forme; GTR) of soil samples is A1, B5 and A1, respectively. The washing of soils with lower fine content helps to recover excellent-quality sand and gravel, which are a useful and precious resource. However, residual fine particles are a waste material. In this study, three soil formulations were used for manufacturing earth blocks. These formulations include raw soil, fines and restructured soil. In restructured soil, a fine fraction of soil smaller than 0.063 mm was mixed with 15% recycled sand. Restructuring of soil fine particles helps to improve soil matrix composition and suitability for earth bricks. Compressed-earth blocks of 4 × 4 × 16 cm were manufactured at a laboratory scale for flexural strength testing by using optimum molding moisture content and compaction through Proctor normal energy. Compressive strength tests were performed on cubic blocks of size 4 × 4 × 4 cm. Mechanical testing of bricks showed that bricks with raw soil had higher resistance with a maximum of 3.4 MPa for Lorient soil. Removal of coarse particles from soil decreased the strength of bricks considerably. Restructuring of fines with recycled sand improves their granular skeleton and increases the compressive strength and durability of bricks. Full article
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<p>Brittany soil samples: Lorient (<b>a</b>), Polama (<b>b</b>) and Bruz (<b>c</b>).</p>
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<p>Wet processing of excavated soils.</p>
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<p>Raw soil (<b>a</b>), mixing soil with water (<b>b</b>), wet sieving of soil (<b>c</b>) and fine particles of soil (<b>d</b>).</p>
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<p>Samples of prismatic earth blocks.</p>
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<p>Granulometry of recycled sand.</p>
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<p>Minerology of recycled sand.</p>
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<p>Flexural and compressive strength (MPa) of earth blocks. Note: S = raw soil; F = fine soil; RS = restructured soil; Fc = compressive strength; Ft = flexural strength.</p>
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26 pages, 6765 KiB  
Article
Performance Evaluation for the Expansion of Multi-Level Rail Transit Network in Xi’an Metropolitan Area: Empirical Analysis on Accessibility and Resilience
by Yulin Zhao, Linkun Li, Zhishuo Zhang and Daniel (Jian) Sun
Land 2024, 13(10), 1682; https://doi.org/10.3390/land13101682 - 15 Oct 2024
Viewed by 347
Abstract
As the main form of new urbanization, the coordinated development of cities in metropolitan areas requires reliable and efficient rail transit skeleton support. However, in the rapid development of metropolitan areas, the layout and analysis of multi-level rail transit systems have a certain [...] Read more.
As the main form of new urbanization, the coordinated development of cities in metropolitan areas requires reliable and efficient rail transit skeleton support. However, in the rapid development of metropolitan areas, the layout and analysis of multi-level rail transit systems have a certain lag. Taking the Xi’an metropolitan area as an example, this study analyzes the comprehensive accessibility and resilience of the multi-level rail transit network, and proposes an expansion plan accordingly. The traffic analysis zone (TAZ) is divided by towns and streets, and the relationship between points of interest (POIs) and the regional average level is analyzed using DEA. The improved weighted average travel time model is built with the analysis results as regional weights; a site selection model based on multiple construction influencing factors is proposed, and four expansion plans, namely, economic optimal, environmental optimal, transport optimal, and integrated optimal, are designed. The peak passenger flow scenario and the “failure–reparation” scenario during the entire operation period are designed to analyze the resilience of four plans, and the resilience is quantified by the elasticity curve of the maximum connected subgraph ratio (MCSR) changing over time. The research results show that the transport optimal plan has the best comprehensive accessibility and resilience, reducing travel costs in Houzhenzi Town, which has the worst accessibility, by 34%. The expansion model and evaluation method in this study can provide an empirical example for the development of other metropolitan areas and provide a reasonable benchmark and guidance for the development of multi-level rail transit networks in future urban areas. Full article
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<p>(<b>a</b>) Schematic diagram of the study area. (<b>b</b>) Schematic diagram of TAZ division.</p>
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<p>Overlapping results of TAZ buffer and three POIs; (<b>a</b>–<b>e</b>) represent the quantity of malls, companies, attractions, residence facilities, and transportation facilities within TAZ, respectively.</p>
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<p>Distribution of regional attractiveness.</p>
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<p>Weighted average travel time based on POIs.</p>
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<p>Kernel density analysis results of six types of POI; (<b>a</b>–<b>f</b>) represent malls, companies, transportation facilities, educational places, attractions, and residence facilities, respectively.</p>
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<p>POI combined heat value and preliminary candidate sites. (<b>a</b>) Visualization of Kriging interpolation of POI combined heat value, and (<b>b</b>) visualization of adding preliminary candidate sites and rail transit lines.</p>
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<p>POI combined heat value and preliminary candidate sites. (<b>a</b>) Visualization of Kriging interpolation of POI combined heat value, and (<b>b</b>) visualization of adding preliminary candidate sites and rail transit lines.</p>
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<p>Expansion plans: (<b>a</b>–<b>d</b>) are, respectively, economic optimal plan, environment optimal plan, transport optimal plan, and integrated optimal plan.</p>
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<p>Rail transit network resilience curve.</p>
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<p>Network topology of multi-level rail transit system in Xi’an metropolitan area.</p>
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<p>Passenger flow by route; (<b>a</b>–<b>d</b>) represent metro, four expansion plans, urban and intercity railways, and high-speed railway, respectively.</p>
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<p>Failure simulation in the morning rush hour scenario.</p>
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<p>MCSR curves from failure–reparation simulation for the four expansion plans.</p>
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18 pages, 3676 KiB  
Article
Thermo- and pH-Responsible Gels for Efficient Protein Adsorption and Desorption
by Izabela Poplewska, Beata Strachota, Adam Strachota, Grzegorz Poplewski and Dorota Antos
Molecules 2024, 29(20), 4858; https://doi.org/10.3390/molecules29204858 - 13 Oct 2024
Viewed by 597
Abstract
Protein adsorption behavior was examined on poly(N-isopropylacrylamide-co-sodium methacrylate)-based hydrogels at different temperatures: 5, 20, and 37 °C, and pH: 4.5, 7, and 9.2. The hydrogels, whose covalent skeleton contains pendant anionic units due to the presence of the sodium methacrylate co-monomer, [...] Read more.
Protein adsorption behavior was examined on poly(N-isopropylacrylamide-co-sodium methacrylate)-based hydrogels at different temperatures: 5, 20, and 37 °C, and pH: 4.5, 7, and 9.2. The hydrogels, whose covalent skeleton contains pendant anionic units due to the presence of the sodium methacrylate co-monomer, exhibited both thermo- and pH-sensitivity with different extents, which depended on the content of ionizable moieties and the cross-linker density. The hydrogel composition, temperature, and pH influenced the zeta potential of the hydrogels and their swelling properties. The proteins selected for the study, i.e., bovine serum albumin (BSA), ovalbumin (OVA), lysozyme (LYZ), and a monoclonal antibody (mAb2), differed in their aminoacidic composition and conformation, thus in isoelectric point, molecular weight, electrostatic charge, and hydrophobicity. Therefore, the response of their adsorption behavior to changes in the solution properties and the hydrogel composition was different. LYZ exhibited the strongest adsorption of all proteins with a maximum at pH 7 (189.5 mg ggel1); adsorption of BSA and OVA reached maximum at pH 4.5 (24.4 and 23.5 mg ggel1), whereas mAb2 was strongly adsorbed at 9.2 (21.7 mg ggel1). This indicated the possibility of using the hydrogels for pH-mediated separation of proteins differing in charge under mild conditions in a water-rich environment of both the liquid solution and the adsorbed phase. The adsorption affinity of all proteins increased with temperature, which was attributed to the synergistic effects of attractive electrostatic and hydrophobic interactions. That effect was particularly marked for mAb2, for which the temperature change from 5 to 37 °C caused a twentyfold increase in adsorption. In all cases, the proteins could be released from the hydrogel surface by a reduction in temperature, an increase in pH, or a combination of both. This allows for the elimination of the use of salt solution as a desorbing agent, whose presence renders the recycling of buffering solutions difficult. Full article
(This article belongs to the Special Issue Feature Papers in Applied Chemistry: 3rd Edition)
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<p>Structure of the tested polymer adsorbents (crosslinked PNIPAM-co-PolySMA), with highlighted monomeric units: NIPAM (the main monomer), responsible for LCST (T-induced switching between hydrophilic and hydrophobic state); SMA co-monomer responsible for swelling sensitivity to pH, which also means pH-dependent charge; BAA co-monomer incorporated as a crosslinker.</p>
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<p>Temperature and composition dependence of <span class="html-italic">Q</span> for PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Cartoon representation of interactions between a protein and hydrogel (<b>a</b>) at a lower pH, (<b>b</b>) at a higher pH, (<b>c</b>) at a higher temperature (T &gt; LCST), and (<b>d</b>) at a lower temperature.</p>
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<p>Illustration of the adsorption behavior of BSA on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Illustration of the adsorption behavior of BSA on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Illustration of the adsorption behavior of LYZ on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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<p>Illustration of the adsorption behavior of mAb2 on PNIPAM-co-PolySMA for different SMA and BAA content at pH 4.5 (<b>a</b>), 7 (<b>b</b>), and 9.2 (<b>c</b>).</p>
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19 pages, 12366 KiB  
Article
An Effective Yak Behavior Classification Model with Improved YOLO-Pose Network Using Yak Skeleton Key Points Images
by Yuxiang Yang, Yifan Deng, Jiazhou Li, Meiqi Liu, Yao Yao, Zhaoyuan Peng, Luhui Gu and Yingqi Peng
Agriculture 2024, 14(10), 1796; https://doi.org/10.3390/agriculture14101796 - 12 Oct 2024
Viewed by 420
Abstract
Yak behavior is a valuable indicator of their welfare and health. Information about important statuses, including fattening, reproductive health, and diseases, can be reflected and monitored through several indicative behavior patterns. In this study, an improved YOLOv7-pose model was developed to detect six [...] Read more.
Yak behavior is a valuable indicator of their welfare and health. Information about important statuses, including fattening, reproductive health, and diseases, can be reflected and monitored through several indicative behavior patterns. In this study, an improved YOLOv7-pose model was developed to detect six yak behavior patterns in real time using labeled yak key-point images. The model was trained using labeled key-point image data of six behavior patterns including walking, feeding, standing, lying, mounting, and eliminative behaviors collected from seventeen 18-month-old yaks for two weeks. There were another four YOLOv7-pose series models trained as comparison methods for yak behavior pattern detection. The improved YOLOv7-pose model achieved the best detection performance with precision, recall, mAP0.5, and mAP0.5:0.95 of 89.9%, 87.7%, 90.4%, and 76.7%, respectively. The limitation of this study is that the YOLOv7-pose model detected behaviors under complex conditions, such as scene variation, subtle leg postures, and different light conditions, with relatively lower precision, which impacts its detection performance. Future developments in yak behavior pattern detection will amplify the simple size of the dataset and will utilize data streams like optical and video streams for real-time yak monitoring. Additionally, the model will be deployed on edge computing devices for large-scale agricultural applications. Full article
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<p>Layout of the pen and camera setting position.</p>
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<p>Sample image of each behavior.</p>
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<p>Nineteen key points of yak.</p>
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<p>The structure of the SPPFCSPC module.</p>
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<p>The structure of the dynamic head block.</p>
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<p>The structure of the YOLOv7-w6-pose model.</p>
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<p>The structure of the YOLOv7-tiny-pose model.</p>
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<p>The structure of the improved YOLOv7-pose model.</p>
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<p>Confusion matrix of the detection accuracy of six behavior patterns of yak. The diagonal represents the detection accuracy for each behavior. The color is darker for higher accuracies.</p>
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<p>Detection performance comparison of the YOLOv7-pose and improved YOLOv7-pose models.</p>
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<p>The detection performance of the improved behavior monitoring model based on the YOLOv7-pose and improved YOLOv7-pose models.</p>
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10 pages, 918 KiB  
Article
Differential Resting-State Brain Characteristics of Skeleton Athletes and Non-Athletes: A Preliminary Resting-State fMRI Study
by Xinhong Jin, Shuying Chen, Yapeng Qi, Qichen Zhou, Jian Wang, Yingying Wang and Chenglin Zhou
Brain Sci. 2024, 14(10), 1016; https://doi.org/10.3390/brainsci14101016 - 12 Oct 2024
Viewed by 373
Abstract
(1) Background: This study investigates the resting-state brain characteristics of skeleton athletes compared to healthy age-matched non-athletes, using resting-state fMRI to investigate long-term skeleton-training-related changes in the brain. (2) Methods: Eleven skeleton athletes and twenty-three matched novices with no prior experience with skeleton [...] Read more.
(1) Background: This study investigates the resting-state brain characteristics of skeleton athletes compared to healthy age-matched non-athletes, using resting-state fMRI to investigate long-term skeleton-training-related changes in the brain. (2) Methods: Eleven skeleton athletes and twenty-three matched novices with no prior experience with skeleton were recruited. Amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity analyses were explored to investigate resting-state functional magnetic resonance imaging (rs-fMRI) data, aiming to elucidate differences in resting-state brain function between the two groups. (3) Results: Compared to the control group, skeleton athletes exhibited significantly higher ALFF in the left fusiform, left inferior temporal gyrus, right inferior frontal gyrus, left middle temporal gyrus, left and right insula, left Rolandic operculum, left inferior frontal gyrus, and left superior temporal gyrus. Skeleton athletes exhibit stronger functional connectivity in brain regions associated with cognitive and motor control (superior frontal gyrus, insula), as well as those related to reward learning (putamen), visual processing (precuneus), spatial cognition (inferior parietal), and emotional processing (amygdala), during resting-state brain function. (4) Conclusions: The study contributes to understanding how motor training history shapes skeleton athletes’ brains, which have distinct neural characteristics compared to the control population, indicating potential adaptations in brain function related to their specialized training and expertise in the sport. Full article
(This article belongs to the Section Neurotechnology and Neuroimaging)
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<p>Inter-group comparison results of mALFF values. The color bar represents the <span class="html-italic">t</span>-values (<span class="html-italic">t</span> = 3.40). Warm colors indicate positive values (skeleton group minus control group), while cold colors represent negative values (skeleton group minus control group). Hemisphere designation: left (L) or right (R). Clusters with <span class="html-italic">p</span> &lt; 0.05 and a spatial extent of <span class="html-italic">k</span> &gt; 50 voxels were deemed statistically significant.</p>
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<p>The inter-group comparison results of functional connectivity values. The functional connectivity results depicted in (<b>a</b>) are based on the seed region of interest located in the superior frontal gyrus. (<b>b</b>) displays the results utilizing the insula as the seed region of interest. The color bar indicates the <span class="html-italic">t</span>-values (<span class="html-italic">t</span> = 3.40). Warm colors indicate positive differences (skeleton group greater than control group), while cold colors represent negative differences (skeleton group less than control group) in either the left (L) or right (R) hemisphere. Clusters with <span class="html-italic">p</span> &lt; 0.05 and a spatial extent <span class="html-italic">k</span> &gt; 50 voxels were considered statistically significant.</p>
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18 pages, 9827 KiB  
Article
Hysteresis Model of RC Column Considering Cumulative Damage Effect under Variable Axial Load
by Jie Shen, Bo Chen and Guangjun Sun
Buildings 2024, 14(10), 3219; https://doi.org/10.3390/buildings14103219 - 10 Oct 2024
Viewed by 395
Abstract
The axial force will be altered as a result of the overturning influence exerted by both horizontal and vertical seismic events, as well as the secondary effects induced by gravitational loads. The variation of the axial force will greatly affect the seismic performance [...] Read more.
The axial force will be altered as a result of the overturning influence exerted by both horizontal and vertical seismic events, as well as the secondary effects induced by gravitational loads. The variation of the axial force will greatly affect the seismic performance of reinforced concrete (RC) columns, thus warranting close attention. This paper proposes a hysteresis model of RC columns considering the cumulative damage effect under the action of variable axial force. First, three groups of cyclic loading tests were performed across three distinct groups. Subsequently, numerical analysis models were constructed, employing fiber-based finite element methods. Furthermore, according to the test and finite element simulation results, the existing damage value was modified to describe the degradation of the stiffness and load-bearing capacity. Next, through a regression analysis, the skeleton curve was established. Finally, the hysteresis behavior under the influence of variable axial load was ascertained. The results, when compared with the experimental data, show that the proposed hysteresis model can accurately describe the seismic performance of RC columns under the influence of variable axial force. Full article
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<p>Details of specimens.</p>
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<p>Test device.</p>
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<p>Schematic of the test loading device.</p>
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<p>Fiber element models of RC circular columns.</p>
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<p>Comparison of test hysteresis curve and finite element simulation.</p>
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<p>Comparison of damage values.</p>
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<p>Cracks appeared when the horizontal displacement reached 10 mm.</p>
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<p>Comparison of the damage values.</p>
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<p>Relationship between stiffness degradation coefficient and damage values.</p>
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<p>Degeneration of the load-bearing capacity when changing the skeleton curve.</p>
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<p>Calculation method for load-bearing capacity degradation.</p>
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<p>The range of changes in the ratio.</p>
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<p>Relationship between load-bearing capacity degradation coefficient and damage value.</p>
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<p>Dimensionless skeleton curves.</p>
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<p>Concrete crush.</p>
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<p>Simplified skeleton curve model.</p>
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<p>Fitting of characteristic points.</p>
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<p>Fitting of characteristic points.</p>
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<p>Relationship between peak displacement and shear-span ratio.</p>
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<p>Proposed hysteretic model.</p>
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<p>Comparison of testing and calculation of skeleton curve.</p>
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<p>Comparison of testing and calculation of hysteretic curves.</p>
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10 pages, 3626 KiB  
Article
Turn-On Fluorescence Probe for Cancer-Related γ-Glutamyltranspeptidase Detection
by Muhammad Saleem, Muhammad Hanif, Samuel Bonne, Muhammad Zeeshan, Salahuddin Khan, Muhammad Rafiq, Tehreem Tahir, Changrui Lu and Rujie Cai
Molecules 2024, 29(19), 4776; https://doi.org/10.3390/molecules29194776 - 9 Oct 2024
Viewed by 559
Abstract
The design and development of fluorescent materials for detecting cancer-related enzymes are crucial for cancer diagnosis and treatment. Herein, we present a substituted rhodamine derivative for the chromogenic and fluorogenic detection of the cancer-relevant enzyme γ-glutamyltranspeptidase (GGT). Initially, the probe is non-chromic [...] Read more.
The design and development of fluorescent materials for detecting cancer-related enzymes are crucial for cancer diagnosis and treatment. Herein, we present a substituted rhodamine derivative for the chromogenic and fluorogenic detection of the cancer-relevant enzyme γ-glutamyltranspeptidase (GGT). Initially, the probe is non-chromic and non-emissive due to its spirolactam form, which hinders extensive electronic delocalization over broader pathway. However, selective enzymatic cleavage of the side-coupled group triggers spirolactam ring opening, resulting in electronic flow across the rhodamine skeleton, and reduces the band gap for low-energy electronic transitions. This transformation turns the reaction mixture from colorless to intense pink, with prominent UV and fluorescence bands. The sensor’s selectivity was tested against various human enzymes, including urease, alkaline phosphatase, acetylcholinesterase, tyrosinase, and cyclooxygenase, and showed no response. Absorption and fluorescence titration analyses of the probe upon incremental addition of GGT into the probe solution revealed a consistent increase in both absorption and emission spectra, along with intensified pink coloration. The cellular toxicity of the receptor was evaluated using the MTT assay, and bioimaging analysis was performed on BHK-21 cells, which produced bright red fluorescence, demonstrating the probe’s excellent cell penetration and digestion capabilities for intracellular analytical detection. Molecular docking results supported the fact that probe-4 made stable interactions with the GGT active site residues. Full article
(This article belongs to the Special Issue Research Progress of Fluorescent Probes)
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<p>(<b>a</b>) UV and (<b>b</b>) fluorescence spectra of probe alone and after reaction with <span class="html-italic">γ</span>-glutamyltranspeptidase, urease, alkaline phosphatase, acetylcholinesterase, tyrosinase, and cyclooxygenase; inset represents chromogenic change in probe solution upon reaction with enzyme.</p>
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<p>(<b>a</b>) UV and (<b>b</b>) fluorescence titration of probe upon incremental induction of GGT (10–100 µL from 0.05 U/mL enzyme solutions) into probe solution (30 µM).</p>
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<p>pH tolerance of probe and probe–GGT solution.</p>
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<p>(<b>a</b>) UV and (<b>b</b>) fluorescence analysis of probe–GGT mixture in varieties of pure organic and mixed aqueous–organic solvent systems.</p>
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<p>(<b>a</b>) Docked complex of GGT (PDB: 4ZBK) and probe-4 with minimum binding energy (kcal/mol); (<b>b</b>) 3D representation of key interacting groups between GGT and probe-4 with distances in Angstrom; (<b>c</b>) 2D representation of key interacting groups between GGT and probe-4.</p>
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<p>Results of bioimaging analysis upon incubation of BHK-21 cells with probe and GGT; (<b>a</b>) bright field images; (<b>b</b>) fluorescence; and (<b>c</b>) merged images; scale bar: 50 µM.</p>
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<p>Cell viability at various incubation times following treatment with probe at concentrations of 0 and 5 µM.</p>
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<p>Sensing mechanism of probe toward GGT.</p>
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<p>Synthesis of probe-4: (i) Phosphorous oxychloride, dichloromethane, reflux for 2 h; (ii) Liq. NH<sub>3</sub>, dichloromethane, stirring overnight; (iii) BOC-L-glutamic acid-1-ter-butylester, HATU, DIPEA, dichloromethane, stirring for 4 h followed by overnight stirring with TFA.</p>
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30 pages, 15361 KiB  
Review
Medicinally Significant Enantiopure Compounds from Garcinia Acid Isolated from Garcinia gummi-gutta
by Simimole Haleema, Chithra Gopinath, Zabeera Kallingathodi, Grace Thomas and Prasad L. Polavarapu
Symmetry 2024, 16(10), 1331; https://doi.org/10.3390/sym16101331 - 9 Oct 2024
Viewed by 530
Abstract
Garcinia gummi-gutta, commonly known as Garcinia cambogia (syn.), is a popular traditional herbal medicine known for its role in treating obesity, and has been incorporated into several nutraceuticals globally for this purpose. The fruit rind is also used as a food preservative [...] Read more.
Garcinia gummi-gutta, commonly known as Garcinia cambogia (syn.), is a popular traditional herbal medicine known for its role in treating obesity, and has been incorporated into several nutraceuticals globally for this purpose. The fruit rind is also used as a food preservative and a condiment because of its high content of hydroxycitric acid, which imparts a sharp, sour flavour. This review highlights the major bioactive compounds present in the tree Garcinia gummi-gutta, with particular emphasis on (2S, 3S)-tetrahydro-3-hydroxy-5-oxo-2,3-furan dicarboxylic acid, commonly referred to as garcinia acid. This acid can be isolated in large amounts through a simple procedure. Additionally, it explores the synthetic transformations of garcinia acid into biologically potent and functionally useful enantiopure compounds, a relatively under-documented area in the literature. This acid, with its six-carbon skeleton, a γ-butyrolactone moiety, and two chiral centres bearing chemically amenable functional groups, offers a versatile framework as a chiron for the construction of diverse molecules of both natural and synthetic origin. The synthesis of chiral 3-substituted and 3,4-disubstituted pyrrolidine-2,5-diones, analogues of the Quararibea metabolite—a chiral enolic-γ-lactone; the concave bislactone skeletons of fungal metabolites (+)-avenaciolide and (−)-canadensolide; the structural skeletons of the furo[2,3-b]furanol part of the anti-HIV drug Darunavir; (−)-tetrahydropyrrolo[2,1-a]isoquinolinones, an analogue of (−)-crispine A; (−)-hexahydroindolizino[8,7-b]indolones, an analogue of the naturally occurring (−)-harmicine; and furo[2,3-b]pyrroles are presented here. Full article
(This article belongs to the Special Issue Chemistry: Symmetry/Asymmetry—Feature Papers and Reviews)
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<p>Optical isomers of HCA.</p>
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<p>The lactonisation of (−)-HCA.</p>
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<p>Important chiral hydroxy acids.</p>
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<p>Naturally occurring compounds having bislactone moiety.</p>
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<p>Naturally occurring Quararibea metabolite chiral enolic-γ-lactones.</p>
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<p>Plausible mechanism for the formation of <b>91a–b</b> [<a href="#B36-symmetry-16-01331" class="html-bibr">36</a>].</p>
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<p>Plausible mechanism for the formation of <b>93a–b</b> [<a href="#B36-symmetry-16-01331" class="html-bibr">36</a>].</p>
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<p>Natural product associated with furopyrrole structure.</p>
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<p>Synthesis of chiral bislactone <b>81</b>, an analogue of (−)-candensolide [<a href="#B35-symmetry-16-01331" class="html-bibr">35</a>].</p>
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<p>Synthesis of chiral bislactone <b>85</b>, an analogue of (+)-avenaciolide [<a href="#B35-symmetry-16-01331" class="html-bibr">35</a>].</p>
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<p>A plausible mechanism for the formation of <b>86</b>.</p>
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<p>Conversion of diol <b>86</b> to iminosugar intermediate <b>88</b>.</p>
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<p>Synthesis of chiral enolic-γ-lactones [<a href="#B36-symmetry-16-01331" class="html-bibr">36</a>].</p>
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<p>Synthesis of 3,4-disubstituted pyrrolidine-2,5-diones from bicyclic anhydride <b>82</b> [<a href="#B53-symmetry-16-01331" class="html-bibr">53</a>].</p>
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<p>Synthesis of 3-substituted pyrrolidine-2,5-diones from ester derivatives of <b>1</b> [<a href="#B53-symmetry-16-01331" class="html-bibr">53</a>].</p>
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<p><span class="html-italic">N</span>-acyliminium cyclization involving unsymmetrical pyrrolidine-2,5-dione [<a href="#B53-symmetry-16-01331" class="html-bibr">53</a>].</p>
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<p>Synthesis of tetrahydropyrrolo[2,1-<span class="html-italic">a</span>]isoquinones and furo[2,3-<span class="html-italic">b</span>]pyrroles [<a href="#B53-symmetry-16-01331" class="html-bibr">53</a>].</p>
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<p>Synthesis of hexahydroindolizino[8,7-<span class="html-italic">b</span>]indolone and furo[2,3-<span class="html-italic">b</span>]pyrroles [<a href="#B53-symmetry-16-01331" class="html-bibr">53</a>].</p>
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<p>List of furopyrroles synthesized from <b>1</b> [<a href="#B52-symmetry-16-01331" class="html-bibr">52</a>].</p>
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<p>Synthesis of pyrroloisoquinolinone <b>39</b> from bicyclic anhydride <b>82</b> [<a href="#B53-symmetry-16-01331" class="html-bibr">53</a>].</p>
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<p>Proposed mechanism for stereospecific deoxygenation [<a href="#B53-symmetry-16-01331" class="html-bibr">53</a>].</p>
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<p>Synthesis of furo[2,3-<span class="html-italic">b</span>]furanol <b>43</b> [<a href="#B87-symmetry-16-01331" class="html-bibr">87</a>].</p>
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22 pages, 14276 KiB  
Review
Superscan Pattern on Bone Scintigraphy: A Comprehensive Review
by Emran Askari, Sara Shakeri, Hessamoddin Roustaei, Maryam Fotouhi, Ramin Sadeghi, Sara Harsini and Reza Vali
Diagnostics 2024, 14(19), 2229; https://doi.org/10.3390/diagnostics14192229 - 6 Oct 2024
Viewed by 771
Abstract
Background/Objectives: The superscan pattern is a characteristic finding on bone scintigraphy, associated with a variety of metabolic bone diseases, malignancies, and other conditions. This pattern is characterized by a diffuse and intense uptake of radiotracer throughout the entire skeleton. Despite being a relatively [...] Read more.
Background/Objectives: The superscan pattern is a characteristic finding on bone scintigraphy, associated with a variety of metabolic bone diseases, malignancies, and other conditions. This pattern is characterized by a diffuse and intense uptake of radiotracer throughout the entire skeleton. Despite being a relatively rare finding, the superscan pattern can have significant clinical implications. Methods: This comprehensive review summarizes the available literature on the superscan pattern, focusing on its pathophysiology, clinical significance, and differential diagnoses. Relevant studies and case reports were analyzed to outline the diagnostic challenges associated with the interpretation of bone scintigraphy featuring the superscan pattern. Results: The literature highlights the clinical significance of the superscan pattern in various metabolic and oncologic conditions. Misinterpretation of this pattern can lead to diagnostic challenges, especially in distinguishing it from other pathologic conditions. Differential diagnosis remains crucial in the accurate interpretation and subsequent management of patients with this finding. Conclusions: This review provides a comprehensive overview of the superscan pattern on bone scintigraphy, aiming to assist clinicians in recognizing and managing this rare yet clinically important finding. Full article
(This article belongs to the Special Issue Recent Advances in Bone and Joint Imaging—2nd Edition)
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Figure 1
<p>Typical cases of superscan pattern are shown in patients with metastatic breast cancer (<b>A</b>) and metastatic castration-resistant prostate cancer (<b>B</b>). The latter was confirmed through whole-body <sup>99m</sup>Tc-HYNIC-PSMA SPECT/CT imaging (<b>C</b>). In some cases, bone scintigraphy, PSMA imaging, and post-treatment scans using <sup>177</sup>Lu-PSMA-617 show nearly identical visual appearances.</p>
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<p>Atypical case of metastatic superscan in an 83-year-old man with metastatic prostate cancer being referred for evaluation of his response to treatment. He had been experiencing gradual pain in his lower extremities over the past 3 months, despite a decline in his PSA levels from 15 to 6.2 ng/mL. A bone scan showed increased activity in the proximal humeri, proximal and distal femora, and proximal tibiae, with activity smearing to the mid-shaft of the femur and tibia on both sides. Given his history of de novo high-volume metastatic disease and generalized bone pain, an SPECT/CT correlation was acquired. The scan revealed diffuse marrow involvement throughout the axial and appendicular skeleton (superscan equivalent). Interestingly, bilateral renal uptake (arrows) was primarily located at the site of nephrolithiasis, indicating obstructive uropathy (arrowheads).</p>
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<p>Atypical case of metastatic superscan in a 67-year-old man with biochemical persistence following radical prostatectomy (Gleason score 4 + 5 and initial PSA = 64 ng/mL). The patient was referred for <sup>99m</sup>Tc-HYNIC-PSMA SPECT/CT and repeat bone scan due to highly elevated PSA levels, 3 months post-prostatectomy (PSA = 42 ng/mL). The initial bone scan was reported as negative (<b>A</b>), but a retrospective review revealed subtle, suspicious foci in the left lowest rib and right sacroiliac region. Subsequently, the recent bone scan (<b>B</b>) suggested a superscan, although the visualization of the kidneys was uncertain (black arrow). A few days later, PSMA imaging (<b>C</b>) was performed, unveiling widespread skeletal metastases (<b>D</b>) and indicating a poorly functioning right kidney and obstructive uropathy (black arrows in (<b>B</b>,<b>C</b>); white arrowhead in (<b>E</b>)). Notably, the right kidney showed more prominent abnormalities. It is important to note that non-visualization of the kidneys is not a prerequisite for a superscan and should be considered in prostate cancer patients with a long-standing history of benign prostatic hyperplasia, where kidney uptake may be preserved despite extensive bone metastases. This specific type of superscan is sometimes referred to as a sub-superscan or forme-frustré of a superscan.</p>
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<p>Atypical case of metastatic superscan in a 52-year-old woman with a history of breast cancer, prior radiation therapy, and recent paraplegia. In the recent bone scan, the patient exhibits multiple non-homogeneous foci of increased tracer uptake throughout the axial skeleton, accompanied by the absence of kidney visualization—a pattern consistent with a metastatic superscan (<b>A</b>). Additionally, a photopenic area is observed in the lower thoracic spine (arrow). Fused SPCET and CT images provide further insights, revealing a compression fracture in the T9 and T10 vertebrae, which coincides with the region previously treated with radiotherapy (<b>B</b>). This compression fracture exerts a compressive effect on the spinal cord.</p>
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<p>(<b>A</b>–<b>D</b> and <b>E</b>) Two representative cases of high-grade lymphoma are presented with extensive involvement leading to suppressed cardiac and brain metabolic activity (FDG superscan). In the first case (<b>A</b>–<b>D</b>), diffuse bone marrow involvement is noted along with peritoneal lymphomatosis. The second case (<b>E</b>) illustrates diffuse bone marrow, splenic, and nodal involvement. (<b>F</b>) A case with refractory neuroblastoma with diffuse marrow involvement having intense somatostatin receptor avidity. The patient received two doses of <sup>177</sup>Lu-DOTATATE, given his history of mIBG-negative disease and tumoral recurrence following bone marrow transplant. However, disease progression was inevitable.</p>
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<p>Comparison of metabolic and metastatic superscan (for more details, see also <a href="#sec7dot3-diagnostics-14-02229" class="html-sec">Section 7.3</a>).</p>
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<p>This is a typical case of metabolic superscan (<b>A</b>) in a patient with a history of renal transplantation. The transplant kidney is visible in the pelvic fossa (dashed, (<b>B</b>)) while the native kidneys appear atrophic (asterisks, (<b>C</b>)). The scan shows a focal zone of MDP uptake in the left pubic ramus, compatible with fracture (arrows, (<b>A</b>,<b>D</b>)) and multiple lytic areas (curved arrows in (<b>E</b>–<b>H</b>)) localized to the left femoral head, left acetabular roof, and multiple ribs. Additionally, a periosteal reaction is noted in the left proximal femur (dashed rectangle, (<b>F</b>)). Many of these abnormalities are not easily discernible in the whole-body bone scan. Subsequent correlative imaging using the dual tracer protocol was employed (<b>I</b>,<b>J</b>), revealing a focus of retained activity on the right side due to a thyroid nodule (blue triangle, (<b>I</b>) and arrow, (<b>K</b>)) and enlarged parathyroid glands bilaterally (red triangle, (<b>I</b>) and arrowheads in (<b>K</b>,<b>L</b>)). The final diagnosis was secondary parathyroid hyperplasia and renal osteodystrophy.</p>
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<p>Atypical case of metabolic superscan in a patient with a history of generalized bone pain and recent swelling of the right distal humerus and proximal radius (<b>A</b>). Upon examination, the bone scan reveals bone expansion and a focal rib uptake consistent with a fracture (<b>B</b>). Parathyroid scintigraphy uncovers a sizable <sup>99m</sup>Tc-sestamibi-avid lesion on the left side, suggestive of parathyroid adenoma/carcinoma, which is later confirmed to be parathyroid carcinoma (<b>C</b>). Correlative CT images exhibit lytic-destructive lesions with bone expansion in the right radius, indicating a probable brown tumor (<b>D</b>). Visualization of the kidneys in the bone scan may imply a rapidly progressive nature of the disease and good functioning kidneys in a previously healthy middle-aged woman.</p>
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<p>Double superscan, also known as super-superscan. A case of a prostate cancer patient with coexistent metastatic superscan and secondary hyperparathyroidism (PTH = 294 pg/mL, calcium = 7.6 mg/dL, Phosphorus = 2.6 mg/dL, and Creatinine = 1 mg/dL). Note the mandibular uptake (arrow) and absence of kidneys in the first post-treatment scan of <sup>177</sup>Lu-PSMA-617 (<b>A</b>). Also, note the visualization of the kidneys in the pre-treatment <sup>68</sup>Ga-PSMA-11 scan ((<b>B</b>), arrowhead). The underlying mechanism for discordant kidney uptake in the <sup>177</sup>Lu-PSMA-617 and <sup>68</sup>Ga-PSMA-11 is unknown. Another case of an elderly patient with a history of prostate cancer presents with progressive anemia and generalized weakness. A recent bone scan reveals atypical findings compared to the typical metastatic superscan observed in prostate cancer. Notable features include a prominent mandible and significant appendicular uptake (<b>C</b>). Upon examining fused images, widespread bone sclerosis is evident (<b>D</b>–<b>F</b>). The differential diagnoses considered are myelofibrosis/myelosclerosis or hyperparathyroidism superimposed on a metastatic superscan.</p>
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15 pages, 3086 KiB  
Article
Local Shear Stress and Dyslipidemia Interfere with Actin Cyto-Skeleton and Lysosomal Organization Contributing to Vascular Fragility
by Natalia F. Do Couto, Augusto M. Lima, Luisa Rezende, Rodrigo Fraga-Silva, Weslley Fernandes-Braga, Lucas A. B. Michelin, Thiago Castro-Gomes, Nikolaos Stergiopulos and Luciana O. Andrade
J. Vasc. Dis. 2024, 3(4), 360-374; https://doi.org/10.3390/jvd3040028 - 5 Oct 2024
Viewed by 538
Abstract
Shear stress is one of the major hemodynamic forces acting on the endothelium. However, it is not well known how endothelial cells (EC) respond mechanically to these stimuli in vivo. Here we investigated whether changes in biomechanics properties and shear stress could increase [...] Read more.
Shear stress is one of the major hemodynamic forces acting on the endothelium. However, it is not well known how endothelial cells (EC) respond mechanically to these stimuli in vivo. Here we investigated whether changes in biomechanics properties and shear stress could increase cell susceptibility to injury, contributing to vascular fragility. We surgically implanted a shear stress modifier device on the carotid artery of ApoE-knockout mice (ApoE−/−), which, due to its shape, causes a gradual stenosis in the vessel, resulting in distinct shear stress patterns. Our data show actin fibers accumulation in areas with higher lipid deposition in ApoE−/−, indicating that dyslipidemia might interfere with EC actin cytoskeleton organization. We also showed that both shear stress and dyslipidemia were important for EC susceptibility to injury. Furthermore, lysosomal distribution, an important organelle for plasma membrane repair, was altered in ApoE−/−, which could compromise EC’s ability to repair from damage. Therefore, dyslipidemia and variations in shear stress patterns not only affect cellular mechanics by compromising the actin cytoskeleton organization, but also enhance cell susceptibility to injury and alter vesicle trafficking in vascular cells. This may likely contribute to vascular fragility and thus to the initial steps of atherosclerosis development. Full article
(This article belongs to the Section Cardiovascular Diseases)
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<p>Timeline of plaque formation in ApoE<sup>−/−</sup> mice. (<b>a</b>) Shear stress modifier device (cast). Device developed by Cheng et al. [<a href="#B3-jvd-03-00028" class="html-bibr">3</a>]; the cast consists of 2 longitudinal halves of a cylinder with a cone-shaped lumen with a gradual decline in the inner diameter (from 500 μm to 250 μm). (<b>b</b>) Experimental principle: the shape of the device causes gradual stenosis in the vessel, resulting in increased shear stress (HSS) in the vessel segment inside the device, a decrease in blood flow, a consequent low shear stress (LSS) region upstream, and a vortex in the downstream region (oscillatory shear stress, OSS). The left carotid artery of each animal was divided into three regions and used as an internal control. (<b>c</b>,<b>d</b>) Oil Red O staining of left and right carotids (LC and RC, respectively) of (<b>c</b>) WT mice (n = 4) and (<b>d</b>) ApoE<sup>−/−</sup> mice 1 and 5 weeks post-cast implantation (wpci) (n = 4). Scale bar, 100 µm (<b>e</b>). Plaque size in the left carotid artery of ApoE<sup>−/−</sup> and WT mice 1–5 wpci (n = 4). (<b>f</b>) Plaque size in the right carotid artery of ApoE<sup>−/−</sup> and WT mice 1–5 wpci. Asterisks indicate statistically significant differences in relation to their respective WT control (<span class="html-italic">p</span> &lt; 0.05 using two-way ANOVA).</p>
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<p>Effects of dyslipidemia and shear stress on flow-induced injury in carotid arteries. (<b>a</b>) Representative merged images of Propidium Iodide (PI; red) staining of the left carotid artery (LC) of WT and ApoE<sup>−/−</sup> mice. The cell nuclei were stained with DAPI (blue) and endothelial cells with CD31 (green). Scale bar, 100 µm. Insets show magnification images of the boxed regions. (<b>b</b>) PI fluorescence intensity in LC endothelium (WT, n = 11; ApoE<sup>−/−</sup>, n = 11; * <span class="html-italic">p</span> &lt; 0.05 using the Wilcoxon test). (<b>c</b>) Representative merged images of PI staining in the three distinct regions of the right carotid artery (RC; LSS, HSS, and OSS) of WT and ApoE<sup>−/−</sup> mice (PI, red; DAPI, blue). Insets show magnification images of the boxed regions. (<b>d</b>) PI fluorescence intensity in the endothelium (WT, n = 9; ApoE<sup>−/−</sup>, n = 11) in the three distinct regions of the RC (* <span class="html-italic">p</span> &lt; 0.05 using the Wilcoxon test). (<b>e</b>) PI fluorescence intensity in the endothelium of ApoE<sup>−/−</sup> mice in the three distinct regions of the RC versus their contralateral control LC (n = 11, * <span class="html-italic">p</span> &lt; 0.05 using the Wilcoxon test).</p>
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<p>Actin cytoskeleton organization in the vascular wall of ApoE<sup>−/−</sup> and WT mice. Representative merged images of Phalloidin-Atto 565 staining (red) in the different regions of (<b>a</b>) left carotid artery (LC) and (<b>b</b>) right carotid artery (RC) of WT and ApoE<sup>−/−</sup> mice. The cell nuclei were stained with DAPI (blue). Merged images are shown. Scale bar, 10 µm. Arrowheads: elastic fibers are evidenced by its autofluorescence. Dash arrows indicate filament-like structures. Insets show magnification images of the boxed regions. Images were captured in the Zeiss Axio Imager.Z2 (ApoTome.2 structured illumination system) fluorescence microscope using the 63× objective. (<b>c</b>) Phalloidin-Atto 565 fluorescence intensity in the endothelium of WT and ApoE<sup>−/−</sup> mice in the 3 distinct regions of the RC (LSS, HSS and OSS). (<b>d</b>) Phalloidin-Atto 565 fluorescence intensity in the endothelium of ApoE<sup>−/−</sup> mice in the 3 distinct regions of the RC versus their contralateral control LC (n = 5; * <span class="html-italic">p</span> &lt; 0.05 using the Wilcoxon test).</p>
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<p>Effects of dyslipidemia on LAMP−2 distribution of ApoE<sup>−/−</sup> and WT carotid arteries. (<b>a</b>) Representative images of LAMP−2 staining of the left carotid artery (LC) of WT and ApoE<sup>−/−</sup> mice. Scale bar, 100 µm. Insets show magnification images of the boxed regions. (<b>b</b>) LAMP−2 fluorescence intensity in LC endothelium (WT, n = 11; ApoE<sup>−/−</sup>, n = 11; * <span class="html-italic">p</span> &lt; 0.05 using the Wilcoxon test). (<b>c</b>) Representative images of LAMP−2 staining in the 3 distinct regions of the right carotid artery (RC; LSS, HSS, and OSS) of WT and ApoE<sup>−/−</sup> mice. Scale bar, 100 µm. Insets show magnification images of the boxed regions. (<b>d</b>,<b>e</b>) LAMP−2 fluorescence intensity in the (<b>d</b>) endothelium (WT, n = 9; ApoE<sup>−/−</sup>, n = 11) and (<b>e</b>) vascular wall of WT and ApoE<sup>−/−</sup> mice in the 3 distinct regions of the RC (WT, n = 13; ApoE<sup>−/−</sup>, n = 13, * <span class="html-italic">p</span> &lt; 0.05 using the Wilcoxon test).</p>
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19 pages, 2277 KiB  
Article
Vessel Geometry Estimation for Patients with Peripheral Artery Disease
by Hassan Saeed and Andrzej Skalski
Sensors 2024, 24(19), 6441; https://doi.org/10.3390/s24196441 - 4 Oct 2024
Viewed by 487
Abstract
The estimation of vessels’ centerlines is a critical step in assessing the geometry of the vessel, the topological representation of the vessel tree, and vascular network visualization. In this research, we present a novel method for obtaining geometric parameters from peripheral arteries in [...] Read more.
The estimation of vessels’ centerlines is a critical step in assessing the geometry of the vessel, the topological representation of the vessel tree, and vascular network visualization. In this research, we present a novel method for obtaining geometric parameters from peripheral arteries in 3D medical binary volumes. Our approach focuses on centerline extraction, which yields smooth and robust results. The procedure starts with a segmented 3D binary volume, from which a distance map is generated using the Euclidean distance transform. Subsequently, a skeleton is extracted, and seed points and endpoints are identified. A search methodology is used to derive the best path on the skeletonized 3D binary array while tracking from the goal points to the seed point. We use the distance transform to calculate the distance between voxels and the nearest vessel surface, while also addressing bifurcations when vessels divide into multiple branches. The proposed method was evaluated on 22 real cases and 10 synthetically generated vessels. We compared our method to different state-of-the-art approaches and demonstrated its better performance. The proposed method achieved an average error of 1.382 mm with real patient data and 0.571 mm with synthetic data, both of which are lower than the errors obtained by other state-of-the-art methodologies. This extraction of the centerline facilitates the estimation of multiple geometric parameters of vessels, including radius, curvature, and length. Full article
(This article belongs to the Collection Biomedical Imaging and Sensing)
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<p>Peripheral artery structure and analysis. (<b>a</b>) Three-dimensional binary mask and extracted skeleton. (<b>b</b>) Centerpoints extracted in binary mask. (<b>c</b>) User-extracted seed and goal points. (<b>d</b>) Traversed skeleton via BFS alogrithm. (<b>e</b>) Spurious branches from skeletonization. (<b>f</b>) Spheres formed around the centerpoint.</p>
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<p>Employing BFS on a binary mask, generating a depth map, and then extracting an optimal path from the goal (encircled in red) to the seed point (encircled in blue). (<b>a</b>) Binary mask. (<b>b</b>) Depth map. (<b>c</b>) Path from goal to seed.</p>
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<p>Side-by-side comparison of skeletonization (<b>left</b>) and best-path result on skeleton (<b>right</b>).</p>
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<p>Vessel length measurement and six sub-arrays forming cube around centerpoint visualization. (<b>a</b>) Best path from seed to goal shown on the skeleton. (<b>b</b>) Cube centered around the seed point, illustrating the spatial region of interest.</p>
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<p>Algorithm update step to address bifurcation and follow best path. (<b>a</b>) Max distance point detected off best path. (<b>b</b>) Algorithm checking for best-path intersection. (<b>c</b>) Algorithm following updated direction.</p>
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<p>Examples of VMR dataset and synthetic data. (<b>a</b>) Exemplary cases of real patient data. (<b>b</b>) Exemplary cases of synthetic data.</p>
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<p>Side-by-side comparison of skeletonization (<b>left</b>) and proposed algorithm result (<b>right</b>).</p>
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<p>Side-by-side comparison of the VMTK centerline model <b>(left</b>)—the magnified view shows small vessel centerlines missed. Proposed algorithm (<b>center</b>)—capturing accurate and complete centerlines and the VMTK network model (<b>right</b>) with off-center centerlines that extend beyond the model’s boundary.</p>
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<p>The image illustrates various data points from the VMR database with poorly annotated points that are misaligned and not centered on the vessel.</p>
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<p>Side-by-side comparison of the VMTK centerline model (<b>left</b>)—the encircled area shows missed vessel centerlines, and the zoomed-in area reveals centerlines not passing through centerpoints at bifurcations; the proposed algorithm (<b>center</b>); and the VMTK network Model (<b>right</b>)—the zoomed-in part shows centerlines not passing through centerpoints at bifurcations—on synthetic data.</p>
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<p>Dependence of centerline extraction on segmentation quality: Accurate segmentation yields reliable results; inaccurate segmentation yields unreliable results. (<b>a</b>) Poor segmentation causing incorrect vessel connections, with encircled vessels improperly joined. (<b>b</b>) False positive skeleton branch due to erroneous vessel connection, emphasizing the segmentation’s impact on accuracy.</p>
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