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Appl. Sci., Volume 14, Issue 2 (January-2 2024) – 480 articles

Cover Story (view full-size image): This paper presents a new concept of a modular system for the production and storage of energy in a bicycle at any speed above 9 km/h. A User-Centered Design methodology was applied to establish the design premises, and then each component of the modular system was selected, developed, and refined separately, carrying out all component integration (hub dynamo, USB charger, batteries, and solar panel) by means of a simple extension cable. Then, simulations were made with different software tools to create a design candidate. A new design of an integrated modular energy production–storage system was obtained, aiming to cover the needs of long-distance bikers and daily bike commuters. The system entails a modular integration solution that is not only cost-effective but also highly efficient. Its ergonomic design allows users to effortlessly replace batteries as and when needed. View this paper
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15 pages, 3345 KiB  
Article
Exploring the Potential Protective Effect of Probiotics in Obesity-Induced Colorectal Cancer: What Insights Can In Vitro Models Provide?
by Rejane Viana, Ana C. Rocha, André P. Sousa, Diogo Ferreira, Rúben Fernandes, Cátia Almeida, Patrick J. Pais, Pilar Baylina and Ana Cláudia Pereira
Appl. Sci. 2024, 14(2), 951; https://doi.org/10.3390/app14020951 - 22 Jan 2024
Viewed by 1833
Abstract
Colorectal cancer (CRC) is the third most common cancer diagnosed today and the third leading cause of death among cancer types. CRC is one of the gastrointestinal tumors with obesity as the main extrinsic risk factor, since, according to authors, the meta-inflammation sustained [...] Read more.
Colorectal cancer (CRC) is the third most common cancer diagnosed today and the third leading cause of death among cancer types. CRC is one of the gastrointestinal tumors with obesity as the main extrinsic risk factor, since, according to authors, the meta-inflammation sustained by the excess adipose tissue can provide abundant circulating lipids, as well as hormones and metabolites crucial to tumor development and aggressiveness. The gut microbiota can protect the colon from meta-inflammation and endocrine changes caused by obesity. The present study aimed to investigate the antitumor activity of a commercial probiotic in intestinal tumor cells under two adiposity conditions. Experimental assays were performed on the Caco2 cell line (colon adenocarcinoma) supplemented with differentiated adipocyte’s secretomes of the 3T3-L1 cell line (mouse pre-adipocytes) in two adiposity conditions: (i) differentiation without the use of Pioglitazone (noPGZ) and (ii) differentiation using Pioglitazone (PGZ). The Caco2 cells were first exposed to both secretomes for 24 h and evaluated and subsequently exposed to probiotic extract followed by secretome and evaluated. The effects of these treatments were evaluated using cytotoxicity assays by MTT, cell migration by injury, and antioxidant activity by glutathione assay. The use of secretomes showed a statistically significant increase in cell viability in Caco2 cells, either in noPGZ (p < 0.01) or PGZ (p < 0.05), and the probiotic was not able to reduce this effect. In the injury assay, secretome increased cell migration by more than 199% in both adiposity conditions (p < 0.001 in noPGZ and p < 0.01 in PGZ). In the probiotic treatment, there was a reduction in cell migration compared to the control in adiposity conditions. The antioxidant response of Caco2 cells was increased in both adiposity conditions previously exposed to the probiotic supernatant. This pilot work brings to light some findings that may answer why the modulation of the intestinal microbiota using probiotics is an alternative strategy leading to improvements in the condition and stage of the colon tumor. Additional studies are needed to clarify the role of Pioglitazone in this type of tumor and the metabolites of obesity that are attenuated by the use of probiotics. Full article
(This article belongs to the Section Biomedical Engineering)
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<p>Summary of the study.</p>
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<p>Summary of supernatant acquisition. To obtain the bacterial supernatant resuspended in minimum essential medium (MEM) for cell culture, it was first necessary to place the cocktail bacteria in a culture medium suitable for bacterial strains to grow in, the Tryptic Soy Broth (TSB), for 48 h at 39 °C. Subsequently, the content was vortexed, and 2 mL was collected to be resuspended in MEM. After this period, the content was centrifuged at 4000 rpm for 10 min to separate the bacterial part of the extract containing products released by the bacteria. The supernatant was filtered in a sterile filter of 0.2 µm and consecutively stored in an arc of −80 °C to be used in future tests.</p>
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<p>Sanger sequencing image for the Lac1 gene (specific and conserved areas) in (<b>a</b>) Forward direction (5′–3′) and (<b>b</b>) Reverse direction (3′–5′).</p>
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<p>Results of cell viability assays by MTT in Caco2 supplemented with red indicating the 3T3-L1 differentiation secretome exclusively and blue indicating probiotic supernatant followed by 3T3-L1 differentiation secretome. CN: negative control; noPGZ: without Pioglitazone; PGZ: with Pioglitazone; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Cell line migration Caco2: (<b>a</b>) graphic representation and (<b>b</b>) photographic representation. The results express the migration rate in Caco2 cells after a mechanical tear, followed by the addition of the treatments in question, where the red is a graphic and photographic representation in which Caco2 was supplemented exclusively with the adiposity secretome produced in the differentiation of adipocytes 3T3-L1, and the blue is a graphical and photographic representation in which Caco2 was first supplemented with supernatant of bacteria from the probiotic cocktail resuspended in MEM, followed by secretome of the differentiation of adipocytes 3T3L1 under conditions without Pioglitazone (noPGZ) and with Pioglitazone (PGZ). **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Results of stress oxidative assay in cellular Caco2 supplemented with supernatant of probiotics followed by 3T3-L1 differentiation secretome. CN: negative control; noPGZ: without Pioglitazone; PGZ: with Pioglitazone. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Results of gene expression of interleukins by RT-qPCR in Caco2 cells supplemented with supernatant of probiotic cocktail bacteria, followed by secretome of differentiation of 3T3L1 adipocytes under different conditions. CN: negative control; noPGZ: without Pioglitazone; PGZ: with Pioglitazone. Interleukins IL-1b and IL-10 were evaluated.</p>
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12 pages, 6937 KiB  
Article
The Impact of Fine-Layering of Tailings Dam on the Variation Pattern of Infiltration Lines
by Wenze Geng, Zhifei Song, Cheng He, Hongtao Wang and Xinyi Dong
Appl. Sci. 2024, 14(2), 950; https://doi.org/10.3390/app14020950 - 22 Jan 2024
Cited by 1 | Viewed by 1233
Abstract
The type of soil and its compactness significantly influence its permeability coefficient, which in turn affects the drainage difficulty of soil pore water and the distribution of the infiltration line. However, current tailings dam models typically consider only a single soil layer instead [...] Read more.
The type of soil and its compactness significantly influence its permeability coefficient, which in turn affects the drainage difficulty of soil pore water and the distribution of the infiltration line. However, current tailings dam models typically consider only a single soil layer instead of taking into account the differences in soil types and compactness, resulting in a deviation between simulated results and actual conditions. To address this issue, this study proposes three models with a gradually increasing degree of layering refinement based on soil type and compactness. These models aim to simulate the variations in the infiltration line under three different strategies: constant head, rainfall, and drainage. The simulation results indicate that the average increase in the infiltration line of the three schemes after rainfall is 46.2%, 65.88%, 83.52%, respectively; the fitting percentages for each scheme of infiltration line after 720 days of drainage and the constant head stage are 72.38%, 88.27%, and 93.61%, respectively. It can be seen that the higher the refinement level of the layered model, the more sensitive it is to changes in the infiltration line. Furthermore, as the refinement level of the layered model increases, the simulation effect on the changes in the infiltration line improves, and the simulated results become more consistent with the actual situation. This finding provides a strategy and possibility for the study of the tailings dam’s infiltration lines, safety, and stability. Full article
(This article belongs to the Special Issue Predictive Modeling in Mining and Geotechnical Engineering)
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<p>Scheme 1 stratification model.</p>
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<p>Scheme 2 stratification model.</p>
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<p>Scheme 3 stratification model.</p>
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<p>Distribution of measurement lines A–E.</p>
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<p>Distribution of the infiltration line in scheme 1 during the constant head strategy.</p>
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<p>Distribution of the infiltration line in scheme 2 during the constant head strategy.</p>
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<p>Distribution of the infiltration line in scheme 3 during the constant head strategy.</p>
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<p>Distribution of the infiltration line in scheme 1 during the rainfall strategy.</p>
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<p>Distribution of the infiltration line in scheme 2 during the rainfall strategy.</p>
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<p>Distribution of the infiltration line in scheme 3 during the rainfall strategy.</p>
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<p>The heights of the infiltration lines after 9 days of rainfall. Notes: The percentage increase in the figure represents the percentage increase of the infiltration line height at the same location between the rainfall strategy and the constant head strategy.</p>
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<p>Distribution of the infiltration line in scheme 1 during the drainage strategy.</p>
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<p>Distribution of the infiltration line in scheme 2 during the drainage strategy.</p>
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<p>Distribution of the infiltration line in scheme 3 during the drainage strategy.</p>
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<p>The heights of the infiltration lines after 720 days of drainage. Notes: The goodness of fit in this figure refers to the percent similarity between the infiltration line height after 720 days of drainage and the infiltration line height during the constant head stage.</p>
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21 pages, 5458 KiB  
Article
Unraveling a Histopathological Needle-in-Haystack Problem: Exploring the Challenges of Detecting Tumor Budding in Colorectal Carcinoma Histology
by Daniel Rusche, Nils Englert, Marlen Runz, Svetlana Hetjens, Cord Langner, Timo Gaiser and Cleo-Aron Weis
Appl. Sci. 2024, 14(2), 949; https://doi.org/10.3390/app14020949 - 22 Jan 2024
Viewed by 1321
Abstract
Background: In this study focusing on colorectal carcinoma (CRC), we address the imperative task of predicting post-surgery treatment needs by identifying crucial tumor features within whole slide images of solid tumors, analogous to locating a needle in a histological haystack. We evaluate [...] Read more.
Background: In this study focusing on colorectal carcinoma (CRC), we address the imperative task of predicting post-surgery treatment needs by identifying crucial tumor features within whole slide images of solid tumors, analogous to locating a needle in a histological haystack. We evaluate two approaches to address this challenge using a small CRC dataset. Methods: First, we explore a conventional tile-level training approach, testing various data augmentation methods to mitigate the memorization effect in a noisy label setting. Second, we examine a multi-instance learning (MIL) approach at the case level, adapting data augmentation techniques to prevent over-fitting in the limited data set context. Results: The tile-level approach proves ineffective due to the limited number of informative image tiles per case. Conversely, the MIL approach demonstrates success for the small dataset when coupled with post-feature vector creation data augmentation techniques. In this setting, the MIL model accurately predicts nodal status corresponding to expert-based budding scores for these cases. Conclusions: This study incorporates data augmentation techniques into a MIL approach, highlighting the effectiveness of the MIL method in detecting predictive factors such as tumor budding, despite the constraints of a limited dataset size. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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<p><b>Region definition and distribution of informative tiles per case</b>. (<b>A</b>) Sketch of WSI with annotated tumor region and border region. Based on a trained U-NET model the whole slide images are segmented into non-tumor (grey) and tumor (blue) tissue. The latter is subdivided based on the tumor content in each tile into tumor central (dashed line in magenta) and tumor border (dashed line in red). The tiles per region (exemplarily shown red dashed boxes) are then saved. For a graphic workflow of the tile preparations see <a href="#app1-applsci-14-00949" class="html-app">Figure S3</a>. (<b>B</b>) Boxplot for the frequency of meaningful instances per case. The MIL approach approach gives a class probability per instance or image tile. Per WSI, there are only a few instances with high class-probabilities. These few instances are the meaningful ones per case. The frequency of these meaningful instances per case is variable. The instances highly informative for nodal negativity are termed “low”, while those with significant relevance to nodal positivity are termed “high”. WSI: whole slide image; MIL: multi-instance learning.</p>
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<p><b>L-space analysis.</b> Based on a PCA analysis of MIL results, for each instance a feature vector is plotted in 2D. (<b>A</b>) Instances from the entire data set, comprising the training and validation set, are plotted. The nodal status (nodal negative (N−) or positive (N+)) is used as a label. The silhouette score, as a clustering metric, is 0.008, which indicates a high overlap of the clusters based on the case labels. (<b>B</b>) Instances from the training set (<b>B1</b>) and the validation set (<b>B2</b>) are plotted. The label used involves the information gained concerning the nodal status. The MIL model produces a pseudo-probability per instance for the nodal status, which ranges between 0 and 1. For this plot, this range is stretched between −1 (low probability for nodal positivity and vice versa, therefore highly predictive for nodal negativity; here called “low”) and +1 (high probability for nodal positivity; here called “high”). For (<b>B1</b>) the silhouette score is 0.008 and respectively for (<b>B2</b>) −0.082. PCA: principal component analysis; MIL: multi-instance learning.</p>
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<p><b>Clustermap analysis of the bag feature vectors produced by the MIL model.</b> Prior to the final fully connected layer for the decision the MIL model produces a feature vector per bag based on all input instances. (<b>A</b>) The feature vector per bag is clustered against the nodal status. On the left the true status of a bag is shown with nodal negative as blue bar and nodal positive as red bar. The feature vector of one bag is split along the x-axis and different bags along the y-axis. The instances of a feature vector are depicted with color-coding representing the N+ probability (black bars equal zero). (<b>B1</b>) For the entire dataset, comprising the training and validation set, a PCA of the bag feature vectors are plotted in the latent space. The nodal status (nodal negative (0) or positive (1)) is used as a label. (<b>B2</b>) Comparable to <a href="#applsci-14-00949-f002" class="html-fig">Figure 2</a>(B2) the pseudo-probability is shown in the L-space. Here, we compute the probability not for an instance but for whole bags for the entire dataset. Probability range is stretched between −1 (low probability for nodal positivity and vice versa, therefore highly predictive for nodal negativity; here called “low”) and +1 (high probability for nodal positivity; here called “high”). MIL: multi-instance learning; PCA: principal component analysis.</p>
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<p><b>Confusion matrix for MIL model with exemplary tiles.</b> The validation set (defined as 0.25 of the entire data set) comprises 31 cases or rather bags with 27 nodal negative cases (N−) and 14 nodal positive cases (N+). A total of 18 cases are correctly predicted by the MIL model as N−; and 14 cases are predicted as N+. 9 cases are false positive and 0 cases are false-negative. In summary, for the validation data set an accuracy of 0.756 and an F1-score of 0.737 is achieved. Based on the pseudo-probabilities of the network an AUC of 0.870 can be achieved. From each evaluated case, the 10 most informative tiles or the tiles with the highest significance for the respective decision are selected. AUC: area under the receiver operator characteristics curve.</p>
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13 pages, 2686 KiB  
Article
Sports Video Classification Method Based on Improved Deep Learning
by Tianhao Gao, Meng Zhang, Yifan Zhu, Youjian Zhang, Xiangsheng Pang, Jing Ying and Wenming Liu
Appl. Sci. 2024, 14(2), 948; https://doi.org/10.3390/app14020948 - 22 Jan 2024
Cited by 5 | Viewed by 2532
Abstract
Classifying sports videos is complex due to their dynamic nature. Traditional methods, like optical flow and the Histogram of Oriented Gradient (HOG), are limited by their need for expertise and lack of universality. Deep learning, particularly Convolutional Neural Networks (CNNs), offers more effective [...] Read more.
Classifying sports videos is complex due to their dynamic nature. Traditional methods, like optical flow and the Histogram of Oriented Gradient (HOG), are limited by their need for expertise and lack of universality. Deep learning, particularly Convolutional Neural Networks (CNNs), offers more effective feature recognition in sports videos, but standard CNNs struggle with fast-paced or low-resolution sports videos. Our novel neural network model addresses these challenges. It begins by selecting important frames from sports footage and applying a fuzzy noise reduction algorithm to enhance video quality. The model then uses a bifurcated neural network to extract detailed features, leading to a densely connected neural network with a specific activation function for categorizing videos. We tested our model on a High-Definition Sports Video Dataset covering over 20 sports and a low-resolution dataset. Our model outperformed established classifiers like DenseNet, VggNet, Inception v3, and ResNet-50. It achieved high precision (0.9718), accuracy (0.9804), F-score (0.9761), and recall (0.9723) on the high-resolution dataset, and significantly better precision (0.8725) on the low-resolution dataset. Correspondingly, the highest values on the matrix of four traditional models are: precision (0.9690), accuracy (0.9781), F-score (0.9670), recall (0.9681) on the high-resolution dataset, and precision (0.8627) on the low-resolution dataset. This demonstrates our model’s superior performance in sports video classification under various conditions, including rapid motion and low resolution. It marks a significant step forward in sports data analytics and content categorization. Full article
(This article belongs to the Collection Computer Science in Sport)
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<p>Image frames from a partial video dataset.</p>
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<p>Images from self-collected sports video dataset (contains artifacts and low resolution).</p>
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<p>Fine−grained feature extraction architecture.</p>
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<p>Two−branch Neural network model architecture for sports video classification.</p>
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<p>Example of classification results of proposed algorithm.</p>
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<p>Accuracy and loss curves of classification on the high-resolution dataset.</p>
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<p>Accuracy and loss curves of classification on the low-resolution dataset.</p>
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<p>Confusion Matrix under the Validation Set of the low-resolution dataset.</p>
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16 pages, 3179 KiB  
Article
Underwater Vehicle Path Planning Based on Bidirectional Path and Cached Random Tree Star Algorithm
by Jinxiong Gao, Xu Geng, Yonghui Zhang and Jingbo Wang
Appl. Sci. 2024, 14(2), 947; https://doi.org/10.3390/app14020947 - 22 Jan 2024
Viewed by 1403
Abstract
Underwater autonomous path planning is a critical component of intelligent underwater vehicle system design, especially for maritime conservation and monitoring missions. Effective path planning for these robots necessitates considering various constraints related to robot kinematics, optimization objectives, and other pertinent factors. Sample-based strategies [...] Read more.
Underwater autonomous path planning is a critical component of intelligent underwater vehicle system design, especially for maritime conservation and monitoring missions. Effective path planning for these robots necessitates considering various constraints related to robot kinematics, optimization objectives, and other pertinent factors. Sample-based strategies have successfully tackled this problem, particularly the rapidly exploring random tree star (RRT*) algorithm. However, conventional path-searching algorithms may face challenges in the marine environment due to unique terrain undulations, sparse and unpredictable obstacles, and inconsistent results across multiple planning iterations. To address these issues, we propose a new approach specifically tailored to the distinct features of the marine environment for navigation path planning of underwater vehicles, named bidirectional cached rapidly exploring random tree star (BCRRT*). By incorporating bidirectional path planning and caching algorithms on top of the RRT*, the search process can be expedited, and an efficient path connection can be achieved. When encountering new obstacles, ineffective portions of the cached path can be efficiently modified and severed, thus minimizing the computational workload while enhancing the algorithm’s adaptability. A certain number of simulation experiments were conducted, demonstrating that our proposed method outperformed cutting-edge techniques like the RRT* in several critical metrics such as the density of path nodes, planning time, and dynamic adaptability. Full article
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<p>Schematic diagram of optimal kinodynamic motion planning using incremental sampling-based methods (RRT*) [<a href="#B30-applsci-14-00947" class="html-bibr">30</a>]. The meaning of <math display="inline"><semantics> <msub> <mi>X</mi> <mrow> <mi>i</mi> <mi>n</mi> <mi>i</mi> <mi>t</mi> </mrow> </msub> </semantics></math> is initial position. The meaning of <math display="inline"><semantics> <msub> <mi>X</mi> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> </semantics></math> is the point closest to the initial position. The meaning of <math display="inline"><semantics> <msub> <mi>X</mi> <mrow> <mi>n</mi> <mi>e</mi> <mi>a</mi> <mi>r</mi> </mrow> </msub> </semantics></math> is the point adjacent to the initial position. The meaning of <math display="inline"><semantics> <msub> <mi>X</mi> <mrow> <mi>n</mi> <mi>e</mi> <mi>w</mi> </mrow> </msub> </semantics></math> is the new location node explored according to the algorithm. The meaning of <math display="inline"><semantics> <msub> <mi>X</mi> <mrow> <mi>r</mi> <mi>a</mi> <mi>n</mi> <mi>d</mi> </mrow> </msub> </semantics></math> is that there is a probability of the most new node.</p>
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<p>Schematic diagram of two-way extended RRT* algorithm. <math display="inline"><semantics> <msub> <mi>T</mi> <mi>i</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>T</mi> <mi>g</mi> </msub> </semantics></math> mean two random trees. <math display="inline"><semantics> <msub> <mi>q</mi> <mi>i</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>q</mi> <mi>g</mi> </msub> </semantics></math> represent the node of random sampling expansion.</p>
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<p>Schematic diagram of two-way extended RRT* algorithm. <math display="inline"><semantics> <msub> <mi>T</mi> <mi>i</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>T</mi> <mi>g</mi> </msub> </semantics></math> mean two random trees. <math display="inline"><semantics> <msub> <mi>q</mi> <mi>i</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>q</mi> <mi>g</mi> </msub> </semantics></math> represent the node of random sampling expansion. The bolded boxes highlight points of divergence between the methodology proposed in this paper and other existing approaches.</p>
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<p>Experimental results of RRT* algorithm. The three-dimensional space depicted in the figure represents a synthetically simulated underwater environment. The variably sized reddish-brown spheres in the illustration simulate underwater obstacles. The thin red lines and green dots within the figure denote the exploration and planning processes. The thicker reddish-brown lines in the figure represent the ultimately planned optimal path.</p>
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<p>Two-way extended RTT* algorithm effect diagram. The three-dimensional space depicted in the figure represents a synthetically simulated underwater environment. The variably sized reddish-brown spheres in the illustration simulate underwater obstacles. The thin red lines and green dots within the figure denote the exploration and planning processes. The thicker reddish-brown lines in the figure represent the ultimately planned optimal path.</p>
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<p>Two-way expansion and path cache optimization RTT* algorithm effect diagram. The three-dimensional space depicted in the figure represents a synthetically simulated underwater environment. The variably sized reddish-brown spheres in the illustration simulate underwater obstacles. The thin red lines and green dots within the figure denote the exploration and planning processes. The thicker reddish-brown lines in the figure represent the ultimately planned optimal path.</p>
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<p>Position change curve. Three curves represent the trajectory from the starting point to the endpoint in the three-dimensional coordinates of X, Y, and Z.</p>
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<p>The number of nodes in path planning before and after changes in obstacles. The figure depicts 100 iterations of repeated experiments with randomly changing obstacles. The orange curve represents the number of nodes in path planning before obstacles undergo changes, while the blue curve represents the number of nodes in path planning after obstacle modifications.</p>
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<p>Minimum path length and number of iterations planned by different algorithms.</p>
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13 pages, 1931 KiB  
Article
Pilot Study on the Biomechanical Quantification of Effective Offensive Range and Ball Speed Enhancement of the Diving Header in Soccer: Insights for Skill Advancement and Application Strategy
by Gongbing Shan, Yufeng Liu, Tom Gorges, Xiang Zhang and Kerstin Witte
Appl. Sci. 2024, 14(2), 946; https://doi.org/10.3390/app14020946 - 22 Jan 2024
Cited by 3 | Viewed by 1865
Abstract
This pioneering study presents an in-depth biomechanical examinations of soccer’s diving header, aiming to quantify its impact on ball speed enhancement (BSE) and effective offensive range (EOR). Despite the diving header’s widespread acclaim and historical significance, there remains a dearth of scientific scrutiny [...] Read more.
This pioneering study presents an in-depth biomechanical examinations of soccer’s diving header, aiming to quantify its impact on ball speed enhancement (BSE) and effective offensive range (EOR). Despite the diving header’s widespread acclaim and historical significance, there remains a dearth of scientific scrutiny into its biomechanical intricacies. Employing an innovative research design featuring a static hanging ball at varied offensive distances and heights, this study replicates diverse header scenarios. The results of 3D motion quantification have shown that a physically excellent player (identified through the maximal standing long jump test) could reach an EOR around 2.64 times his body height. Furthermore, this study unveils that proficient players could attain BSE surpassing 9 m/s, signifying the diving header’s heightened efficacy compared to traditional heading techniques, which could only result in 4.5 m/s. Correlation analyses unveil noteworthy relationships, highlighting the pivotal role of head speed at impact and the influence of minimizing speed drop and temporal disparities for amplified effectiveness. Considerations for optimizing diving header execution are introduced, emphasizing the necessity for targeted training programs. Despite acknowledged limitations inherent to its pilot nature, this exploration furnishes foundational knowledge to guide subsequent research and practical applications, providing valuable insights into soccer training and skill development through a biomechanical lens. Full article
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<p>Breathtaking diving headers in elite soccer. (<b>left</b>): Keith Houchen’s diving header in 1987 England FA Cup final (the figure is generated by using the public video from YouTube [<a href="#B10-applsci-14-00946" class="html-bibr">10</a>]), (<b>right</b>): Robin van Persie’s diving header in the 2014 FIFA World Cup Brazil (the figure is generated by using the public video from FIFA [<a href="#B11-applsci-14-00946" class="html-bibr">11</a>]).</p>
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<p>Definition of offensive range. The biomechanical model animation is generated from 3D data obtained in the current study.</p>
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<p>Test condition selections based on the physical strength assessment: left—short–high ball, right—long–low ball.</p>
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<p>An exemplary video frame (<b>left</b>) and 3D capture data (<b>right</b>) of a diving header. The ball position is indicated by the three yellow markers, and the trajectory of the head is illustrated by the four blue lines tracking the four head markers.</p>
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<p>Exemplary representation of speed changes over time for the head and ball during a diving header.</p>
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15 pages, 2190 KiB  
Article
Adhesion Testing Device for 3D Printed Objects on Diverse Printing Bed Materials: Design and Evaluation
by Jakub Kaščak, Marek Kočiško, Adrián Vodilka, Jozef Török and Tomáš Coranič
Appl. Sci. 2024, 14(2), 945; https://doi.org/10.3390/app14020945 - 22 Jan 2024
Cited by 4 | Viewed by 1384
Abstract
The persistent challenge of adhesion in Fused Filament Fabrication (FFF) technology is deeply rooted in the mechanical and chemical properties of utilized materials, necessitating the exploration of potential resolutions. This involves adjustments targeting the interplay of printing parameters, the mechanical fortification of print [...] Read more.
The persistent challenge of adhesion in Fused Filament Fabrication (FFF) technology is deeply rooted in the mechanical and chemical properties of utilized materials, necessitating the exploration of potential resolutions. This involves adjustments targeting the interplay of printing parameters, the mechanical fortification of print beds, and the integration of more adhesive materials, resonating across user levels, from enthusiasts to complex industrial configurations. An in-depth investigation is outlined in this paper, detailing the plan for a systematically designed device. Engineered for FFF device installation, the device facilitates the detachment of printed models, while precisely recording the detachment process, capturing the maximum force, and its progression over time. The primary objective is fabricating a comprehensive measurement apparatus, created for adhesion assessment. The device is adaptable across diverse FFF machines and print bed typologies, conforming to pre-defined conditions, with key features including compactness, facile manipulability, and capacity for recurrent measurements. This pursuit involves evaluating adhesion levels in prints made from diverse materials on varying print bed compositions, aiming to establish a comprehensive database. This repository facilitates judicious material and bed type selection, emphasizing maximal compatibility. Emphasis is placed on operating within a thermally stable context, a pivotal prerequisite for consistent and reproducible results. Full article
(This article belongs to the Topic Advances in Non-Destructive Testing Methods, 2nd Edition)
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<p>An illustration of existing Cartesian-type FFF device constructions.</p>
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<p>The Emsyst EMS20-5KN sensor with the converter EMS650.</p>
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<p>Graphical representation of generally known properties of PLA and PETG materials.</p>
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<p>The construction of the prototype designed for adhesive testing.</p>
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<p>Comparison of maximum forces when detaching the bed with PI and borosilicate coatings.</p>
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<p>Comparison of maximum forces when detaching the bed with and without a PEI coating.</p>
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<p>Comparison of maximum forces when detaching the bed with PEI and PI coatings.</p>
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<p>Example of the most common deficiencies of the test model.</p>
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19 pages, 4012 KiB  
Article
Implementation of Quality Tools in Mechanical Engineering Piece Production
by Štefan Markulik, Marek Šolc and Milan Fiľo
Appl. Sci. 2024, 14(2), 944; https://doi.org/10.3390/app14020944 - 22 Jan 2024
Cited by 1 | Viewed by 1829
Abstract
The world is undergoing dynamic changes. For businesses, it brings positives, but also negatives. The positive is the global market for business. The downside of the global market is the increasing competitive pressure. Large enterprises with serial production who are setting production for [...] Read more.
The world is undergoing dynamic changes. For businesses, it brings positives, but also negatives. The positive is the global market for business. The downside of the global market is the increasing competitive pressure. Large enterprises with serial production who are setting production for a longer period ahead are not so noticeable. Small companies are the most vulnerable. There are various tools or overall approaches to business management that allow them to increase work efficiency or production productivity or eliminate waste. In recent years, one can see an increase in the popularity of Lean or Six Sigma. Their contribution to businesses cannot be disputed. Most of the tools and approaches to support business management are oriented or based on the conditions of serial production. Small businesses with piece production are at a disadvantage here. It was this fact that motivated us to focus on piece production and to find space for the implementation of supporting tools that could be helpful. Our research has shown that there are tools that can be applied in the conditions of piece production. The application of the identified tools proved that the results achieved in reducing production times or increasing productivity are unmistakable. Full article
(This article belongs to the Special Issue Mechanical and Biomedical Engineering in Paradigm)
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<p>Basic tools of Lean.</p>
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<p>Storage of fixtures and molds in the company before the application of 5S.</p>
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<p>Storage of fixtures and molds in the company after the application of 5S.</p>
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<p>Analyze the problem.</p>
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<p>Product movement during production.</p>
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<p>Sample of the Production plan.</p>
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<p>Layout design.</p>
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<p>Floor plan of the workplace.</p>
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<p>Machine card.</p>
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<p>Visual work instructions for packaging.</p>
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<p>Shelf with components at the assembly workplace.</p>
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23 pages, 9822 KiB  
Article
Wire and Cable Quality Traceability System Based on Industrial Internet of Things and Blockchain
by Jintao Zhao, Wenlei Sun, Cheng Lu, Xuedong Zhang, Lixin Wang and Dajiang Wang
Appl. Sci. 2024, 14(2), 943; https://doi.org/10.3390/app14020943 - 22 Jan 2024
Cited by 1 | Viewed by 1468
Abstract
Wire and cable are important industrial products involving the national economy and people’s livelihood, which are hailed as the “blood vessel” and “nerve” of the national economy, providing the basic guarantee for the normal operation of modern economy and society. The data traceability [...] Read more.
Wire and cable are important industrial products involving the national economy and people’s livelihood, which are hailed as the “blood vessel” and “nerve” of the national economy, providing the basic guarantee for the normal operation of modern economy and society. The data traceability of their production and circulation process is a key factor in ensuring their quality and safety management. We aim to solve the problems of unsafe data transmission, weak quality control, and information islands in the process of wire and cable quality traceability in order to improve the production management efficiency of wire and cable manufacturing enterprises and to reduce the cost of consumer quality traceability of wire and cable products. We analyzed the technical characteristics and advantages of Industrial Internet of Things (IIoT) identity resolution and the blockchain. Key technologies are introduced, a traceability method that integrates the two is proposed, and a quality traceability framework based on the IIoT identity resolution system and blockchain technology is constructed. By analyzing the quality information composition of the wire and cable supply chain, a new quality traceability model based on the wire and cable supply chain is established. Finally, through the verification of the developed quality traceability system, the quality traceability function and quality information of each production link of wire and cable are successfully realized. This paper fills a gap in the field of cable product quality traceability using the combination of IIoT and blockchain technology. According to this model, it also has some potential for the traceability of other industrial products. Full article
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<p>Handle identification code coding rules.</p>
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<p>Handle system resolution architecture.</p>
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<p>Basic block structure.</p>
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<p>Smart contract.</p>
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<p>Middleware for blockchain and IIoT architecture model diagram.</p>
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<p>Identity data storage scheme based on blockchain technology.</p>
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<p>Identify data resolution smart contract process.</p>
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<p>Technical framework for the integration of identity resolution and blockchain.</p>
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<p>Wire and cable core quality traceability data model.</p>
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<p>Flowchart of cable quality traceability for the integration of identity resolution and blockchain.</p>
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<p>Cable quality traceability model for the integration of identity resolution and blockchain.</p>
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<p>Identity Resolution System Monitoring Diagram.</p>
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<p>Blockchain operation monitoring diagram.</p>
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<p>Product management information diagram.</p>
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<p>Warning diagram of the tampering prevention system.</p>
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<p>Traceability of quality information in the manufacturing stage of photoelectric composite cable.</p>
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<p>Information tracing in the stage of photoelectric composite cable acquisition and storage.</p>
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<p>Main cable product market access requirements.</p>
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<p>Consumer Complaints and Claims window.</p>
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<p>System query and resolution processing capacity gradient change curve.</p>
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<p>System transaction performance test curve.</p>
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17 pages, 8233 KiB  
Article
On the Local and String Stability Analysis of Traffic Collision Risk
by Tianyu Dong, Jiazu Zhou, Junfan Zhuo, Bo Li and Feng Zhu
Appl. Sci. 2024, 14(2), 942; https://doi.org/10.3390/app14020942 - 22 Jan 2024
Cited by 1 | Viewed by 1120
Abstract
Conventional traffic stability studies primarily concentrate on the evolution of disturbances in vehicle motion but seldom consider how collision risk changes spatially and temporally. This study bridges the gap by extending the principles of traffic stability analysis to the field of traffic safety, [...] Read more.
Conventional traffic stability studies primarily concentrate on the evolution of disturbances in vehicle motion but seldom consider how collision risk changes spatially and temporally. This study bridges the gap by extending the principles of traffic stability analysis to the field of traffic safety, focusing specifically on the temporal and spatial dynamics of collision risk. Leveraging the concepts of local and string stability, we formulate conditions under which collision risk behaves in a stable manner over time and space through the transfer function approach. A comparative analysis between conventional traffic stability and the newly introduced concept of collision risk stability reveals that while conditions for local stability are largely aligned in both domains, the criteria for string stability differ. These theoretical insights are substantiated through microscopic simulations using a variety of car-following models. The simulations also indicate that the consistency between theoretical and simulation outcomes diminishes as the disturbance magnitude increases, which is attributed to the linearization errors inherent in applying the transfer function in the theoretical derivations. Full article
(This article belongs to the Section Transportation and Future Mobility)
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<p>Demonstration of a vehicle platoon.</p>
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<p>Block diagram of risk local stability.</p>
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<p>Block diagram of risk string stability.</p>
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<p>Visualizaiton of the numerical solutions of risk string stability.</p>
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<p>Visualizaiton of the numerical solutions of risk string stability with specific parameters.</p>
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<p>Demonstration of acceleration and velocity profiles of the leading vehicle (<span class="html-italic">A</span> = 0.1 m/s<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>, <math display="inline"><semantics> <mi>ω</mi> </semantics></math> = 0.5 rad/s, <math display="inline"><semantics> <msup> <mi>v</mi> <mrow> <mi>e</mi> <mi>q</mi> </mrow> </msup> </semantics></math> = 20 m/s).</p>
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<p>Speed and collision risk profile in different scenarios.</p>
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23 pages, 13922 KiB  
Article
A Novel Method Using 3D Interest Points to Place Markers on a Large Object in Augmented Reality
by Su Young Kim and Yoon Sang Kim
Appl. Sci. 2024, 14(2), 941; https://doi.org/10.3390/app14020941 - 22 Jan 2024
Cited by 1 | Viewed by 1415
Abstract
Multiple markers are generally used in augmented reality (AR) applications that require accurate registration, such as medical and industrial fields. In AR using these markers, there are two inevitable problems: (1) geometric shape discrepancies between a real object and a virtual object, and [...] Read more.
Multiple markers are generally used in augmented reality (AR) applications that require accurate registration, such as medical and industrial fields. In AR using these markers, there are two inevitable problems: (1) geometric shape discrepancies between a real object and a virtual object, and (2) the relative positions of the markers placed on the virtual object and markers placed on the real object are not consistent. However, studies on applying multiple markers to a large object are still insufficient. Additionally, most studies did not consider these inevitable problems because the markers were subjectively placed (hereafter conventional method). In consideration of these problems, this paper proposes a method for placing multiple markers to provide accurate registration on a large object. The proposed method divides a virtual object evenly and determines the positions of multiple markers automatically using 3D interest points within the divided areas. The proposed method was validated through a performance comparison with the conventional method of subjectively placing markers, and it was confirmed to have more accurate registration. Full article
(This article belongs to the Special Issue Virtual/Augmented Reality and Its Applications)
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<p>Prerequisite for attaching markers to the real object: (<b>a</b>) non-attachable; (<b>b</b>) attachable (=face).</p>
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<p>Example of the upscaling process: (<b>a</b>) before; (<b>b</b>) after.</p>
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<p>Example of inner and outer surface determination.</p>
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<p>Determination of how to create faces based on ROI boundaries: (<b>a</b>) intersecting the ROI boundary through the face; (<b>b</b>) new faces created by vertex conditions.</p>
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<p>Example of segmenting a virtual object: (<b>a</b>) preprocessed source; (<b>b</b>) <span class="html-italic">k</span> = 4; (<b>c</b>) <span class="html-italic">k</span> = 6; (<b>d</b>) <span class="html-italic">k</span> = 8.</p>
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<p>The expected CoA and mean position in <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="bold-italic">F</mi> </mrow> <mrow> <mi mathvariant="bold-italic">j</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Example of CSA computation.</p>
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<p>Example of interest points extracted from virtual large objects: (<b>a</b>) A-segment car model; (<b>b</b>): C-segment car model; (<b>c</b>): D-segment car model.</p>
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<p>Example of DoI computation.</p>
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<p>Example of MPS score calculation according to <span class="html-italic">k</span> and <span class="html-italic">w</span>: (<b>a</b>) <span class="html-italic">k</span> = 4; (<b>b</b>) <span class="html-italic">k</span> = 6; (<b>c</b>) <span class="html-italic">k</span> = 8.</p>
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<p>Indoor parking lot of the Future-Learning Center, Korea University of Technology and Education, where the experiments were conducted.</p>
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<p>Real objects used in the experiments: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">D</mi> <mi mathvariant="normal">M</mi> </mrow> <mrow> <mi mathvariant="normal">R</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">D</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">R</mi> </mrow> </msub> </mrow> </semantics></math>. where an object with the subscript R denotes a real object.</p>
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<p>Marker placement process in the developed experimental content: (<b>a</b>) real-time tracking of the right index fingertip; (<b>b</b>) placing virtual marker when controlling the mouse with the left hand.</p>
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<p>Simple test result using a physical marker (unit: cm).</p>
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<p>Marker placement process: (<b>a</b>) reference image; (<b>b</b>) marker placement.</p>
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<p>Augmented registration results (<span class="html-italic">k</span> = 4, <span class="html-italic">w</span> = 0.5): (<b>a</b>) DM; (<b>b</b>) DA.</p>
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<p>Spatial awareness of real world objects: (<b>a</b>) DM; (<b>b</b>) DA.</p>
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<p>Surrounding space collection for spatial awareness (DA).</p>
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<p>Examples of reference points (clearly recognizable positions, red circles) for measuring the error between the positions of virtual and real objects (DA).</p>
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<p>Method for measuring registration errors: (<b>a</b>) reference points; (<b>b</b>) measurement process.</p>
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<p>Preliminary experimental procedure for determining valid weight.</p>
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<p>Visualized results of the preliminary experiment.</p>
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<p>Main experimental procedure for validating performance of the proposed method.</p>
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<p>Creating markers using the subjective marker placement program.</p>
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<p>Visualized main experimental results: box whiskers (outliers are excluded from this figure).</p>
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<p>Difference in MRE between the proposed and conventional methods.</p>
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22 pages, 37048 KiB  
Article
Hydrodynamic Analysis-Based Modeling of Coastal Abrasion Prevention (Case Study: Pulau Baai Port, Bengkulu)
by Mudji Irmawan, Muhammad Hafiizh Imaaduddiin, Rizki Robbi Rahman Alam, Afif Navir Refani and Anissa Nur Aini
Appl. Sci. 2024, 14(2), 940; https://doi.org/10.3390/app14020940 - 22 Jan 2024
Cited by 1 | Viewed by 1441
Abstract
Pulau Baai Port, located strategically in the Indian Ocean and considered a vital maritime hub in Indonesia, grapples with persistent challenges related to abrasion and sedimentation, which negatively impact its maritime infrastructure. One of the affected components is the exposed gas pipeline installation [...] Read more.
Pulau Baai Port, located strategically in the Indian Ocean and considered a vital maritime hub in Indonesia, grapples with persistent challenges related to abrasion and sedimentation, which negatively impact its maritime infrastructure. One of the affected components is the exposed gas pipeline installation along the port’s coastline. The sedimentation rate along Pulau Baai’s coastline is alarming, ranging from 600,000 to 800,000 m3/year, resulting in coastal abrasion at a rate of up to 20 m/year. This study focuses on three scenarios using MIKE 21, including a baseline without alternatives, shore protection alternatives, and jetty protection alternatives. A comprehensive dataset, incorporating bathymetric maps, wave patterns, current data, and sediment characteristics, supports the analysis of coastal dynamics, emphasizing the urgency for intervention. The research introduces the novelty of analyzing coastal abrasion through the exposure of underground pipelines, establishing a relationship between impacting factors such as wave height, tides, sedimentation, and coastal abrasion. Mitigation alternatives, particularly alternative model-2 with jetty protection, are recommended based on a thorough evaluation of the model performance and actual measurements. The results show that Pulau Baai’s sediment, primarily sandy, experiences substantial abrasion and coastline changes, notably in alternatives-2 and -3. The study anticipates potential sedimentation in certain sections of the subsea exposed pipelines in the absence of shore protection. The outcomes of this research provide a foundational guide for informed decision making and strategies to ensure the sustainable functionality of maritime infrastructure in Pulau Baai and similar coastal regions. Full article
(This article belongs to the Section Civil Engineering)
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<p>Flowchart of the assessment scheme for the study.</p>
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<p>Research location and the comparison of the coastline over the past four years (A–D) around Pulau Baai Port, Bengkulu (Source: Google Earth Pro, 2022).</p>
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<p>Condition of exposed pipeline installations in the Port Area.</p>
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<p>Scheme of the bathymetric survey study area locations.</p>
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<p>Model area.</p>
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<p>Bathymetric survey data (<b>left</b>) and global navionic bathymetric map (<b>right</b>).</p>
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<p>Wave height (Hs) and wave period (Ts) graphs from 2012 to 2022.</p>
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<p>Wind speed graph from 2012 to 2022.</p>
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<p>Wave rose model ADCP 2021 (<b>left</b>) and wave rose model ADCP 2022 (<b>right</b>).</p>
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<p>Field and model tidal comparison graphs.</p>
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<p>Observation and model current velocity graph.</p>
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<p>Shore protection as alternative-1 shown by a horizontal line.</p>
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<p>Jetty protection as alternative-2 shown by a vertical line.</p>
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<p>Dominant flow patterns of alternative-1 (<b>left</b>), alternative-2 (<b>center</b>), and alternative-3 (<b>right</b>).</p>
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<p>Morphological change model over 5 year (<b>A</b>,<b>C</b>,<b>E</b>) and 10 year (<b>B</b>,<b>D</b>,<b>F</b>) within coastal area ((<b>A</b>,<b>B</b>) represents alternative-1; (<b>C</b>,<b>D</b>) represents alternative-2; (<b>E</b>,<b>F</b>) represents alternative-3).</p>
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<p>Bathymetric conditions model over 5 year (<b>A</b>,<b>C</b>,<b>E</b>) and 10 year (<b>B</b>,<b>D</b>,<b>F</b>) in each alternative (Alternative-1 shown in (<b>A</b>,<b>B</b>); Alternative-2 is shown in (<b>C</b>,<b>D</b>); and Alternative-3 is shown in (<b>E</b>,<b>F</b>)).</p>
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<p>Changes in coastlines for alternatives-1, -2, and- 3 over a 10-year simulation.</p>
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<p>Alternative wave propagation model-1.</p>
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<p>Alternative wave propagation model-2.</p>
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<p>Alternative wave propagation model-3.</p>
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14 pages, 1755 KiB  
Article
The Effects of Systemic Vitamin D Level on the Healing of Different Graft Materials: An Experimental Histological Study
by Mehmet Sefa Hacibektasoglu, Huseyin Avni Balcioglu, Yigit Uyanikgil and Nilufer Bolukbasi Balcioglu
Appl. Sci. 2024, 14(2), 939; https://doi.org/10.3390/app14020939 - 22 Jan 2024
Viewed by 1441
Abstract
The aim of this study is to investigate the effects of serum vitamin D levels on the healing of different bone graft materials. Thirty-six male rats were divided into three groups and fed special feeds containing different amounts of vitamin D for 6 [...] Read more.
The aim of this study is to investigate the effects of serum vitamin D levels on the healing of different bone graft materials. Thirty-six male rats were divided into three groups and fed special feeds containing different amounts of vitamin D for 6 weeks before the surgical phase: the high serum vitamin D level group (group H) 10,000 iu/kg vitamin D3; the standard serum vitamin D level group (group C) 1000 iu/kg D3; and the low-level vitamin D group (group L) 100 iu/kg vitamin D3. Under general anesthesia, four defects with a diameter of 5 mm were created in the calvaria of the rats. The defects were augmented with autogenous grafts, allografts, xenografts, or left empty. The serum vitamin D level was measured before the surgery and before sacrifice. At the end of the 6th week, the subjects were sacrificed, and histological and histomorphometric analyses were performed. Study results show that in all graft types, as vitamin D levels increase, the number of new bone formations increases. There was no significant difference between the graft materials in terms of new bone formation criteria in group L. In group H and group C, the highest new bone formation was seen in the allograft group (1.48 ± 0.07, 0.66 ± 0.19, respectively). Prospective randomized clinical studies are required to evaluate the effect of vitamin D dose on the success of augmentation procedures in the clinic. Full article
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<p>Flowchart of this study.</p>
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<p>Views of surgically created defects. (<b>a</b>) View of before grafting; (<b>b</b>) view of after grafting. The first defect was left empty (ED group). The second defects were filled with autogenous bone particles (AuG group). The third defects were filled with xenograft particles (XG group). Fourth defects were filled with allograft particles (AlG group).</p>
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<p>Histopathological views of the groups (H&amp;E staining X20). The blue arrow shows the defect area and the yellow star shows PMNL infiltration.</p>
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21 pages, 5790 KiB  
Article
PRC-Light YOLO: An Efficient Lightweight Model for Fabric Defect Detection
by Baobao Liu, Heying Wang, Zifan Cao, Yu Wang, Lu Tao, Jingjing Yang and Kaibing Zhang
Appl. Sci. 2024, 14(2), 938; https://doi.org/10.3390/app14020938 - 22 Jan 2024
Cited by 6 | Viewed by 2854
Abstract
Defect detection holds significant importance in improving the overall quality of fabric manufacturing. To improve the effectiveness and accuracy of fabric defect detection, we propose the PRC-Light YOLO model for fabric defect detection and establish a detection system. Firstly, we have improved YOLOv7 [...] Read more.
Defect detection holds significant importance in improving the overall quality of fabric manufacturing. To improve the effectiveness and accuracy of fabric defect detection, we propose the PRC-Light YOLO model for fabric defect detection and establish a detection system. Firstly, we have improved YOLOv7 by integrating new convolution operators into the Extended-Efficient Layer Aggregation Network for optimized feature extraction, reducing computations while capturing spatial features effectively. Secondly, to enhance the performance of the feature fusion network, we use Receptive Field Block as the feature pyramid of YOLOv7 and introduce Content-Aware ReAssembly of FEatures as upsampling operators for PRC-Light YOLO. By generating real-time adaptive convolution kernels, this module extends the receptive field, thereby gathering vital information from contexts with richer content. To further optimize the efficiency of model training, we apply the HardSwish activation function. Additionally, the bounding box loss function adopts the Wise-IOU v3, which incorporates a dynamic non-monotonic focusing mechanism that mitigates adverse gradients from low-quality instances. Finally, in order to enhance the PRC-Light YOLO model’s generalization ability, we apply data augmentation techniques to the fabric dataset. In comparison to the YOLOv7 model, multiple experiments indicate that our proposed fabric defect detection model exhibits a decrease of 18.03% in model parameters and 20.53% in computational load. At the same time, it has a notable 7.6% improvement in mAP. Full article
(This article belongs to the Special Issue Collaborative Learning and Optimization Theory and Its Applications)
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<p>The network structure of YOLOv7.</p>
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<p>The principle of PConv.</p>
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<p>The structure of the RFB.</p>
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<p>Upsampling process on CARAFE.</p>
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<p>Activation function output curves.</p>
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<p>The PRC-Light YOLO structure.</p>
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<p>Defective fabric image samples.</p>
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<p>Change curve of <span class="html-italic">mAP</span> value.</p>
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<p>Loss Function. The loss function of the model consists of three parts, (<b>a</b>), (<b>b</b>) and (<b>c</b>), respectively, show the change curves of the BoxLoss, ClsLoss and ObjLoss for YOLOv7 and PRC-Light YOLO. (<b>d</b>) shows the total loss function variation curve.</p>
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<p>Precision–Recall. (<b>a</b>) and (<b>b</b>), respectively, show the PR curves of YOLOv7 and PRC-Light YOLO on the fabric dataset.</p>
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<p>Detection effect of the YOLOv7.</p>
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<p>Detection effect of the PRC-Light YOLO.</p>
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<p>Detection system UI.</p>
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<p>Application effect of the PRC-Light YOLO model.</p>
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<p>PRC-Light YOLO model checking effect.</p>
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19 pages, 6326 KiB  
Article
ForecastNet Wind Power Prediction Based on Spatio-Temporal Distribution
by Shurong Peng, Lijuan Guo, Haoyu Huang, Xiaoxu Liu and Jiayi Peng
Appl. Sci. 2024, 14(2), 937; https://doi.org/10.3390/app14020937 - 22 Jan 2024
Cited by 1 | Viewed by 1509
Abstract
The integration of large-scale wind power into the power grid threatens the stable operation of the power system. Traditional wind power prediction is based on time series without considering the variability between wind turbines in different locations. This paper proposes a wind power [...] Read more.
The integration of large-scale wind power into the power grid threatens the stable operation of the power system. Traditional wind power prediction is based on time series without considering the variability between wind turbines in different locations. This paper proposes a wind power probability density prediction method based on a time-variant deep feed-forward neural network (ForecastNet) considering a spatio-temporal distribution. First, the outliers in the wind turbine data are detected based on the isolated forest algorithm and repaired through Lagrange interpolation. Then, based on the graph attention mechanism, the features of the proximity node information of the individual wind turbines in the wind farm are extracted and the input feature matrix is constructed. Finally, the wind power probability density prediction results are obtained using the ForecastNet model based on three different hidden layer variants. The experimental results show that the ForecastNet model with a hidden layer as a dense network based on the attention mechanism (ADFN) predicts better. The average width of the prediction intervals at achieved confidence levels for all interval coverage is reduced by 34.19%, 35.41%, and 35.17%, respectively, when compared to the model with the hidden layer as a multilayer perceptron. For different categories of wind turbines, ADFN also achieves relatively narrow interval average widths of 368.37 kW, 315.87 kW, and 299.13 kW, respectively. Full article
(This article belongs to the Special Issue Renewable Energy Systems 2023)
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<p>Detection and repair of wind power outliers.</p>
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<p>Characteristic correlation heat map.</p>
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<p>Results of K-sums clustering.</p>
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<p>Multilayer feedforward neural network structure.</p>
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<p>The interleaved output properties of ForecastNet.</p>
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<p>Hidden layer structure of MLPFN.</p>
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<p>Hidden layer structure of CNNFN.</p>
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<p>Hidden layer structure of ADFN.</p>
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<p>Schematic of multi-step prediction.</p>
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<p>A wind power prediction framework based on spatio-temporally distributed ForecastNet.</p>
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<p>Multi-step prediction error curves for different numbers of THPO.</p>
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<p>Comparison of wind power prediction intervals for different ForecastNet models.</p>
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<p>Comparison of interval prediction results for different models for turbine #1.</p>
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<p>Comparison of interval prediction results for different models for turbine #96.</p>
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<p>Comparison of interval prediction results for different models for turbine #128.</p>
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<p>Probability density function of wind power at different moments.</p>
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11 pages, 2743 KiB  
Article
Main Nuclear Responses of the DEMO Tokamak with Different In-Vessel Component Configurations
by Jin Hun Park and Pavel Pereslavtsev
Appl. Sci. 2024, 14(2), 936; https://doi.org/10.3390/app14020936 - 22 Jan 2024
Viewed by 1002
Abstract
Research and development of the DEMOnstration power plant (DEMO) breeder blanket (BB) has been performed in recent years based on a predefined DEMO tritium breeding ratio (TBR) requirement, which determines a loss of wall surface due to non-breeding in-vessel components (IVCs) which consume [...] Read more.
Research and development of the DEMOnstration power plant (DEMO) breeder blanket (BB) has been performed in recent years based on a predefined DEMO tritium breeding ratio (TBR) requirement, which determines a loss of wall surface due to non-breeding in-vessel components (IVCs) which consume plasma-facing wall surface and do not contribute to the breeding of tritium. The integration of different IVCs, such as plasma limiters, neutral beam injectors, electron cyclotron launchers and diagnostic systems, requires cut-outs in the BB, resulting in a loss of the breeder blanket volume, TBR and power generation, respectively. The neutronic analyses presented here have the goal of providing an assessment of the TBR losses associated with each IVC. Previously performed studies on this topic were carried out with simplified, homogenized BB geometry models. To address the effect of the detailed heterogeneous structure of the BBs on the TBR losses due to the inclusion of the IVCs in the tokamak, a series of blanket geometry models were developed for integration in the latest DEMO base model. The assessment was performed for both types of BBs currently developed within the EUROfusion project, the helium-cooled pebble bed (HCPB) and water-cooled lead–lithium (WCLL) concepts, and for the water-cooled lead and ceramic breeder (WLCB) hybrid BB concept. The neutronic simulations were performed using the MCNP6.2 Monte Carlo code with the Joint Evaluated Fission and Fusion File (JEFF) 3.3 data library. For each BB concept, a 22.5° toroidal sector of the DEMO tokamak was developed to assess the TBR and nuclear power generation in the breeder blankets. For the geometry models with the breeder blanket space filled only with blankets without considering IVCs, the results of the TBR calculations were 1.173, 1.150 and 1.140 for the HCPB, WCLL and WLCB BB concepts, respectively. The TBR impact of all IVCs and the losses of the power generation were estimated as a superposition of the individual effects. Full article
(This article belongs to the Special Issue Advances in Fusion Engineering and Design Volume II)
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<p>The scheme of the IVCs arrangement in the DEMO.</p>
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<p>Horizontal and vertical 3D slice of inboard side of the HCPB (<b>a</b>), WCLL (<b>b</b>), and WCLB (<b>c</b>) DEMO geometry model.</p>
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<p>Integration of the IML, UL, OML + OLL in one toroidal segment on 3D (<b>a</b>) and 2D (<b>b</b>) plot.</p>
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<p>The integration of the EC system (<b>a</b>) with DEMO toroidal segment (<b>b</b>).</p>
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<p>The NBI system (<b>a</b>) and ducts integration in the DEMO tokamak (<b>b</b>).</p>
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<p>Cuts of the 22.5° MCNP geometry models for the HCPB DEMO: UL (<b>a</b>) and integration of IML, UL and OML without OLL (<b>b</b>).</p>
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15 pages, 1413 KiB  
Article
StructSim: Meta-Structure-Based Similarity Measure in Heterogeneous Information Networks
by Yuyan Zheng, Jianhua Qu and Jiajia Yang
Appl. Sci. 2024, 14(2), 935; https://doi.org/10.3390/app14020935 - 22 Jan 2024
Viewed by 1267
Abstract
Similarity measures in heterogeneous information networks (HINs) have become increasingly important in recent years. Most measures in such networks are based on the meta path, a relation sequence connecting object types. However, in real-world scenarios, there exist many complex semantic relationships, which cannot [...] Read more.
Similarity measures in heterogeneous information networks (HINs) have become increasingly important in recent years. Most measures in such networks are based on the meta path, a relation sequence connecting object types. However, in real-world scenarios, there exist many complex semantic relationships, which cannot be captured by the meta path. Therefore, a meta structure is proposed, which is a directed acyclic graph of object and relation types. In this paper, we explore the complex semantic meanings in HINs and propose a meta-structure-based similarity measure called StructSim. StructSim models the probability of subgraph expansion with bias from source node to target node. Different from existing methods, StructSim claims that the subgraph expansion is biased, i.e., the probability may be different when expanding from the same node to different nodes with the same type based on the meta structure. Moreover, StructSim defines the expansion bias by considering two types of node information, including out-neighbors of current expanded nodes and in-neighbors of next hop nodes to be expanded. To facilitate the implementation of StructSim, we further designed the node composition operator and expansion probability matrix with bias. Extensive experiments on DBLP and YAGO datasets demonstrate that StructSim is more effective than the state-of-the-art approaches. Full article
(This article belongs to the Topic Distributed Optimization for Control)
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<p>A toy example of a heterogeneous information network, meta path, and meta structure.</p>
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<p>The process of subgraph expansion based on the meta structure.</p>
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<p>A toy example of the Node-Composition operator.</p>
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<p>Meta path and meta structure on entity resolution and clustering tasks.</p>
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<p>The results of the linear combination of the meta path in the entity resolution task.</p>
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14 pages, 4221 KiB  
Article
A Novel Continuous-Variable Quantum Key Distribution Scheme Based on Multi-Dimensional Multiplexing Technology
by Shuai Zhang, Heng Wang, Yan Pan, Yun Shao, Tao Zhang, Wei Huang, Yang Li and Bingjie Xu
Appl. Sci. 2024, 14(2), 934; https://doi.org/10.3390/app14020934 - 22 Jan 2024
Viewed by 1226
Abstract
Dual-polarization division multiplexing (DPDM) is considered to be a potential method to boost the secure key rate (SKR) of the continuous-variable quantum key distribution (CV-QKD) system. In this article, we propose a pilot alternately assisted local local oscillator (LLO) CV-QKD scheme based on [...] Read more.
Dual-polarization division multiplexing (DPDM) is considered to be a potential method to boost the secure key rate (SKR) of the continuous-variable quantum key distribution (CV-QKD) system. In this article, we propose a pilot alternately assisted local local oscillator (LLO) CV-QKD scheme based on multi-dimensional multiplexing, where time division multiplexing and frequency division multiplexing are combined with dual-polarization multiplexing techniques to dramatically isolate the quantum signal from the pilot tone. We establish a general excess noise model for the LLO CV-QKD system to analyze the influence mechanism of various disturbances (e.g., time-domain diffusion, frequency-domain modulation residual, and polarization perturbation) on the key parameters, such as the channel transmittance and excess noise. Specifically, the photon leakage noise from the reference path to the quantum path and that between quantum signals with two different polarization paths are simultaneously analyzed in the dual-polarization LLO CV-QKD scheme for the first time. Furthermore, a series of simulations are established to verify the performance of the proposed scheme. The results show that the maximal isolation degree achieves 84.0 dB~90.4 dB, and the crosstalk between pilot tones and quantum signals can be suppressed to a very small range. By optimizing the system parameters (e.g., modulation variance and repetition frequency), the SKR with 12.801 Mbps@25 km is achieved under the infinite polarization extinction ratio (PER) and 30 dB residual ratio of the frequency modulation in the nanosecond-level pulse width. Moreover, the performance of the proposed DPDM CV-QKD scheme under relatively harsh conditions is simulated; the results show that the SKR with 1.02 Mbps@25 km is achieved under a relatively low PER of 17 dB with the nanosecond-level pulse width and 20 dB residual ratio of the frequency modulation. Our work lays an important theoretical foundation for the practical DPDM LLO CV-QKD system. Full article
(This article belongs to the Special Issue Advanced Technologies in Data and Information Security III)
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<p>Schematic diagram of the previous pilot-assisted dual-polarization and time multiplexing scheme in the time domain. Pilot tones and quantum signals are placed in the proportion of 1:2. The GMCS quantum signal 1,3 (QS1,3) and pilot tone 1 (PT1)/pilot tone 3 (PT3) are modulated at vertical polarization. Signal 2,4 (QS2,4) and pilot tone 2 (PT2)/pilot tone 4 (PT4) are modulated at horizontal polarization.</p>
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<p>(<b>a</b>) Schematic diagram of the pilot alternately assisted orthogonal scheme of dual polarization by the time and frequency multiplexing in the time domain. The GMCS quantum signals 1 (QS1) and 3 (QS3) together with PT1 are modulated at the vertical polarization. The quantum signal 2 (QS2) and 4 (QS4) together with the PT2 are modulated at the horizontal polarization. (<b>b</b>) Schematic diagram of the pilot alternately assisted orthogonal scheme of dual polarization by the time and frequency multiplexing in the frequency domain. The frequency of pilot tones, including PT1 and PT2, is shifted in the frequency domain by the single-sideband modulation. The center frequency of PT1 and PT2 is <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>A</mi> </mrow> </msub> <mo>+</mo> <msub> <mrow> <mi>f</mi> </mrow> <mrow> <mi>m</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Schematic diagram of the multi-dimensional multiplexing LLO CV-QKD scheme. AM, MZ amplitude modulator; PM, phase modulator; BS, beam splitter; PBS, polarizing beam splitter; VOA, variable optical attenuator; PBC, polarizing beam combiner; SMF, single mode fiber; BHD, balanced homodyne detector; PMOC, polarization maintaining optical couplers; DSO, digital storage oscilloscope.</p>
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<p>Secure key rates versus polarization extinction ratio curves corresponding to different transmission distances. (The repetition frequency is 300 MHz, the pulse width is 1 ns, and the modulation variance VA = 14.94 at 15 km, VA = 8 at 25 km, VA = 4.55 at 50 km, s = 0.01, VA = 3.78 at 100 km. The reverse reconciliation efficiency β is 0.95, the electrical noise in shot noise unit is <span class="html-italic">v<sub>ele</sub></span>/<span class="html-italic">N</span><sub>0</sub> = 0.1, and the quantum efficiency η is 0.56.)</p>
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<p>Secure key rates versus different modulation variance VA and transmission distance curves corresponding to 20 dB PER. (The repetition frequency is 300 MHz, the pulse width is 1 ns, and the reverse reconciliation efficiency β is 0.95. s = 0.01, <span class="html-italic">v<sub>ele</sub></span>/<span class="html-italic">N</span><sub>0</sub> = 0.1, and the quantum efficiency η is 0.56.)</p>
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<p>Secure key rates versus pulse repetition frequency curves under s = 0.01 corresponding to different polarization extinction ratios. (The transmission distance is 25 km, the pulse width is 1 ns, s = 0.01, the finite-size block is <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mn>11</mn> </mrow> </msup> </mrow> </semantics></math>, and VA = 1.6).</p>
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<p>Secure key rates versus pulse repetition frequency curves under s = 0.001 corresponding to different polarization extinction ratios. (The transmission distance is 25 km, the pulse width is 1 ns, s = 0.01, the finite-size block is <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mn>11</mn> </mrow> </msup> </mrow> </semantics></math>, and VA = 1.6).</p>
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<p>Secure key rate versus transmission distance curves corresponding to different polarization extinction ratios under optimal parameters. (The repetition frequency is 292.5 MHz, s = 0.01, and the pulse width is 1 ns. The modulation variance VA = 1.6.)</p>
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22 pages, 19047 KiB  
Article
Electroencephalography (EEG)-Based Comfort Evaluation of Free-Form and Regular-Form Landscapes in Virtual Reality
by Hongguo Ren, Ziming Zheng, Jing Zhang, Qingqin Wang and Yujun Wang
Appl. Sci. 2024, 14(2), 933; https://doi.org/10.3390/app14020933 - 22 Jan 2024
Cited by 2 | Viewed by 1979
Abstract
Urban landscape parks play a crucial role in providing recreational opportunities for citizens. Different types of landscapes offer varying levels of comfort experiences. However, the assessment of landscape comfort primarily relies on subjective evaluations and basic physiological measurements, which lack sufficient quantification of [...] Read more.
Urban landscape parks play a crucial role in providing recreational opportunities for citizens. Different types of landscapes offer varying levels of comfort experiences. However, the assessment of landscape comfort primarily relies on subjective evaluations and basic physiological measurements, which lack sufficient quantification of relevant data. This study employed electroencephalography (EEG) technology and subjective questionnaire evaluation methods. Participants observed two sets of landscape demonstration videos using virtual reality (VR) devices, and EEG alpha values and subjective evaluation scores were collected to assess the comfort levels of free-form landscape and regular-form landscape. Additionally, this study explored the correlation between landscape characteristics and physiological comfort. The analysis of the results showed that: 1. The average amplitude of EEG alpha waves recorded from 11 electrodes in the left temporal lobe and right parietal lobe of the participants was higher after they watched the free-form landscape demonstration. The increased alpha values suggest that free-form landscapes are more likely to induce physiological comfort in these specific brain regions. In contrast, regular-form landscape was found to induce higher alpha values at seven specific electrodes located in the occipital cortex, right temporal lobe, and central regions of the participants. In general, free-form landscape provided physiological comfort to a greater number of brain regions. 2. The two groups of landscapes exhibit distinct subjective cognitive differences in terms of their landscape characteristics. These differences, ranked in order of magnitude, include rhythmicity, sense of order, sense of security, and sense of dependence. 3. This study examined the α-waves of specific brain regions, including the right and left temporal lobe and occipital lobe, as well as subjective scoring. It discovered that the rhythmicity, degree of variation, degree of color, and sense of nature of a landscape impact the α-wave value of electrodes in different brain regions. Moreover, there exists a certain linear relationship between the four landscape features and the α-wave values in different regions of the brain. The results of this study provide some reference for the creation of a comfortable landscape design. Full article
(This article belongs to the Special Issue Research on Environmental Health: Sustainability and Innovation)
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<p>Landscape plan experimental video production process.</p>
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<p>Experimental equipment and brain electrode distribution.</p>
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<p>Experiment process.</p>
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<p>EEG data processing flow.</p>
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<p>The number of people inclined toward the D1 and D2 plans for each electrode and the electrode area distribution.</p>
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<p>The number of people inclined toward D1 and D2 plans for all electrodes and the distribution of all electrode areas.</p>
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<p>Average and difference analysis of electrode alpha waves in each brain region. Note: ***—<span class="html-italic">p</span> ≤ 0.001, **—<span class="html-italic">p</span> ≤ 0.005, *—<span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Average and difference analysis of electrode alpha waves in each brain region. Note: ***—<span class="html-italic">p</span> ≤ 0.001, **—<span class="html-italic">p</span> ≤ 0.005, *—<span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Comparison of the electrode difference value (<span class="html-italic">p</span> value) of each brain region and the α value of electrodes in each brain region of the two groups of plans.</p>
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<p>Analysis of alpha value correlation between electrodes of D1 and D2 designs.</p>
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<p>Plan D1 subjective evaluation score and standard deviation.</p>
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<p>Plan D2 subjective evaluation score and standard deviation.</p>
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<p>The mean scores and difference test results of 15 groups of subjective evaluation factors.</p>
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<p>Subjective factor scores correlate with EEG α. Note: *—<span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Comparison of α values and subjective factor scores of electrodes in design D1 and D2.</p>
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16 pages, 5932 KiB  
Article
New Concept of Dual-Sinusoid Distributed Fiber-Optic Sensors Antiphase-Placed for the SHM of Smart Composite Structures for Offshore
by Hao Su, Monssef Drissi-Habti and Valter Carvelli
Appl. Sci. 2024, 14(2), 932; https://doi.org/10.3390/app14020932 - 22 Jan 2024
Cited by 2 | Viewed by 1622
Abstract
This work is a follow-up to previous research by our team and is devoted to studying a dual-sinusoidal placement of distributed fiber-optic sensors (FOSs) that are embedded inside an adhesive joint between two composite laminates. The constructed smart continuous fiber-reinforced polymer composite structure [...] Read more.
This work is a follow-up to previous research by our team and is devoted to studying a dual-sinusoidal placement of distributed fiber-optic sensors (FOSs) that are embedded inside an adhesive joint between two composite laminates. The constructed smart continuous fiber-reinforced polymer composite structure is well suited to the structural health monitoring (SHM) system for offshore wind turbine blades. Three main drawbacks of SHM through embedded distributed FOSs, however, have been identified in this article, so their impact must be analyzed. Despite existing research, the influence of the dual-sinusoidal placement under various loading conditions on structural mechanical behavior and sensing functionality has not been considered yet since its introduction. Thus, this study aims to identify the resulting strain patterns and sensing capabilities from an optimized dual-sinusoidal placement of FOSs in various loading cases through finite element modeling. Ultimately, this work illustrates the strain-measuring advantages of dual-sinusoidal FOSs, explains the correspondence between the strains measured by FOSs and that of host structures, and discusses the balance among mechanical influences, sensing functions, and monitoring coverage. It is worth noting that the current work is a still introductory concept that aims at refining key parameters that have been emphasized in previous research, before starting an applied study that will consider both numerical and validation steps on real large smart composite structures. Full article
(This article belongs to the Special Issue Advances in Reinforced Concrete Structural Health Monitoring)
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<p>Schematic of typical FOS cross-section.</p>
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<p>Numerical model with dual-sinusoidal FOSs embedded (dimensions in mm).</p>
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<p>Geometric characteristic of the numerical model (upper CFRP face panel and adhesive hidden for clarity, dimensions in mm).</p>
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<p>Mesh of the numerical model with dual-sinusoidal FOSs embedded.</p>
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<p>U1 = 0.5 mm applied on YZ-top-end-plane (arrows indicating the loading direction).</p>
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<p>U3 = −0.5 mm applied on the top row of nodes (arrows indicating the loading direction).</p>
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<p>Torsional moment applied to RP-1, linked to YZ-top-end-plane by coupling constraint.</p>
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<p>Three key placement parameters of a sinusoidal placement pattern [<a href="#B3-applsci-14-00932" class="html-bibr">3</a>].</p>
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<p>Tension loading case: (<b>a</b>) plan view of the numerical model under tension; (<b>b</b>) the maximum principal strain contours of FOS cores; (<b>c</b>) <span class="html-italic">E</span><sub>11</sub> strain component of epoxy adhesive; (<b>d</b>) <span class="html-italic">E</span><sub>22</sub> strain component of epoxy adhesive.</p>
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<p>Cantilever bending case: (<b>a</b>) Iso view of the numerical model under cantilever bending; (<b>b</b>) the maximum principal strain contours of FOS cores.</p>
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<p>Cantilever bending case: (<b>a</b>) Iso view of the numerical model under cantilever bending; (<b>b</b>) the maximum principal strain contours of FOS cores.</p>
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<p>Torsion case: (<b>a</b>) Iso view of the numerical model under torsion; (<b>b</b>) the maximum principal strain contours of FOS #2; (<b>c</b>) <span class="html-italic">E</span><sub>23</sub> strain component of FOS #2; (<b>d</b>) <span class="html-italic">E</span><sub>13</sub> strain component of FOS #2; (<b>e</b>) <span class="html-italic">E</span><sub>11</sub> strain component of FOS #2.</p>
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<p>Torsion case: (<b>a</b>) Iso view of the numerical model under torsion; (<b>b</b>) the maximum principal strain contours of FOS #2; (<b>c</b>) <span class="html-italic">E</span><sub>23</sub> strain component of FOS #2; (<b>d</b>) <span class="html-italic">E</span><sub>13</sub> strain component of FOS #2; (<b>e</b>) <span class="html-italic">E</span><sub>11</sub> strain component of FOS #2.</p>
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<p>Dual-sinusoidal FOSs’ placement embedded on a glass composite specimen [<a href="#B3-applsci-14-00932" class="html-bibr">3</a>].</p>
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<p>Bending strain measurement carried out with dual-sinusoidal FOSs alignment on a glass-fiber composite specimen [<a href="#B3-applsci-14-00932" class="html-bibr">3</a>].</p>
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25 pages, 16468 KiB  
Article
Computerized Generation and Surface Deviation Correction of Ruled Surface for Face Gear Drives
by Xianlong Peng and Yikai Wu
Appl. Sci. 2024, 14(2), 931; https://doi.org/10.3390/app14020931 - 22 Jan 2024
Cited by 1 | Viewed by 1317
Abstract
In order to solve the problems of low efficiency and complex cutting tools in conventional face gear machining, this paper presents a machining method of ruled surface face gears with conical cutters and proposes a new pinion to correct deviation and its machining [...] Read more.
In order to solve the problems of low efficiency and complex cutting tools in conventional face gear machining, this paper presents a machining method of ruled surface face gears with conical cutters and proposes a new pinion to correct deviation and its machining method. Firstly, the mathematical models of ruled surface face gears and conical cutters are established, the motion rules of the conical cutter are derived, and the influence of basic parameters on the tooth surface deviation between ruled surface and conventional surface is analyzed. Secondly, for the sake of correction of tooth surface deviation, reverse conjugation is applied to the ruled surface to obtain a corrected pinion. On the basis of hobbing cylindrical gears, the purpose of machining corrected pinions is achieved by increasing CNC motions. Finally, the manufacturing process is simulated by VERICUT software, the results demonstrate that the machining error of ruled surface and pinion do not exceed 10 μm, and through LTCA, the meshing performance of the ruled surface face gear pair is basically the same as that of conventional face gear pair, proving the feasibility of replacing the latter with the former. This study provides a new manufacturing method for face gears. Full article
(This article belongs to the Special Issue Transmission Mechanics: From Theory to Application)
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<p>Generation of the face gear.</p>
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<p>Schematic diagrams of ruled surface and the special contact line of conventional face gear pair: (<b>a</b>) definition of ruled surface, and (<b>b</b>) a special contact line in surfaces Σ<sub>c</sub> and Σ<sub>f</sub>.</p>
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<p>Schematic diagram of the development of ruled surface: (<b>a</b>) generation coordinate system of ruled surface, and (<b>b</b>) generating result of ruled surface for face gear.</p>
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<p>The conical cutter.</p>
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<p>Coordinate systems for ruled surface generation.</p>
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<p>The deviation between the tooth surface machined by conical cutters and the theoretically developed tooth surface: (<b>a</b>) case 1, and (<b>b</b>) case 2.</p>
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<p>Tooth surface deviations of the ruled surface: (<b>a</b>) definition of the tooth surface deviation, and (<b>b</b>) tooth surface deviation morphology.</p>
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<p>The influence of basic parameters on the deviation of face gears: (<b>a</b>) transmission ratio and tooth surface deviation, and (<b>b</b>) module and tooth surface deviation.</p>
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<p>Generation of conjugated pinion.</p>
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<p>Deviation between conjugate surface and involute surface: (<b>a</b>) tooth surface deviation morphology; and (<b>b</b>) transmission ratio and tooth surface deviation.</p>
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<p>Theory of gear hobbing and modified hob: (<b>a</b>) hob equals an infinite rack, and (<b>b</b>) geometric shape of the cross section of the worm shaft.</p>
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<p>Coordinate systems for pinion generation.</p>
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<p>The machining motions of conjugate surface and overcutting phenomenon.</p>
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<p>The cutting edge approaches conjugate tooth profile without overcutting: (<b>a</b>) case 1, (<b>b</b>) case 2.</p>
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<p>Tooth surface deviation with a transmission ratio of 1 and CNC machining result: (<b>a</b>) deviation between involute surface and conjugate surface, and (<b>b</b>) CNC machining error.</p>
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<p>Tooth surface deviation with a transmission ratio of 3 and CNC machining result: (<b>a</b>) deviation between involute surface and conjugate surface, and (<b>b</b>) CNC machining error.</p>
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<p>Finite element model of face gear pair.</p>
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<p>Contact stresses of two gear pairs: (<b>a</b>) contact stresses of face gears, and (<b>b</b>) contact stresses of pinions.</p>
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<p>Bending stresses of two gear pairs: (<b>a</b>) bending stresses of face gears, and (<b>b</b>) bending stresses of pinions.</p>
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<p>Load imprints and load transmission errors of conventional face gear pair: (<b>a</b>) load imprints of face gears, and (<b>b</b>) load transmission error.</p>
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<p>Load imprints and load transmission errors of ruled surface face gear pair: (<b>a</b>) load imprints of ruled surface face gears, and (<b>b</b>) load transmission error.</p>
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<p>Simulation model of face gear generated by conical cutter on a machining center.</p>
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<p>Simulation result and error: (<b>a</b>) tooth surface generated in VERICUT, (<b>b</b>) theoretical tooth surface, (<b>c</b>) STL model and topography for measurements, and (<b>d</b>) simulation error in machined STL model.</p>
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<p>CNC machine tool model.</p>
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<p>Simulation result and error: (<b>a</b>) tooth surface generated in VERICUT, and (<b>b</b>) simulation error in machined STL model.</p>
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19 pages, 13948 KiB  
Article
Material-Structure Integrated Design and Optimization of a Carbon-Fiber-Reinforced Composite Car Door
by Huile Zhang, Zeyu Sun, Pengpeng Zhi, Wei Wang and Zhonglai Wang
Appl. Sci. 2024, 14(2), 930; https://doi.org/10.3390/app14020930 - 22 Jan 2024
Cited by 4 | Viewed by 2632
Abstract
This paper develops a material-structure integrated design and optimization method based on a multiscale approach for the lightweight design of CFRP car doors. Initially, parametric modeling of RVE is implemented, and their elastic performance parameters are predicted using the homogenization theory based on [...] Read more.
This paper develops a material-structure integrated design and optimization method based on a multiscale approach for the lightweight design of CFRP car doors. Initially, parametric modeling of RVE is implemented, and their elastic performance parameters are predicted using the homogenization theory based on thermal stress, exploring the impact of RVE parameters on composite material performance. Subsequently, a finite element model of the CFRP car door is constructed based on the principle of equal stiffness, and a parameter transfer across microscale, mesoscale, and macroscale levels is achieved through Python programming. Finally, the particle generation and updating strategies in the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm are improved, enabling the algorithm to directly solve multi-constraint and multi-objective optimization problems that include various composite material layup process constraints. Case study results demonstrate that under layup process constraints and car door stiffness requirements, plain weave, twill weave, and satin weave composite car doors achieve weight reductions of 15.85%, 14.54%, and 15.35%, respectively, compared to traditional metal doors, fulfilling the requirements for a lightweight design. This also provides guidance for the lightweight design of other vehicle body components. Full article
(This article belongs to the Special Issue Structural Optimization Methods and Applications)
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<p>Flow chart of multiscale design for CFRP car door.</p>
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<p>Schematic view of microscale cell.</p>
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<p>Equivalent stress contour result of different thermal stress conditions: (<b>a</b>) <span class="html-italic">S</span><sup>11</sup>; (<b>b</b>) <span class="html-italic">S</span><sup>22</sup>; (<b>c</b>) <span class="html-italic">S</span><sup>33</sup>; (<b>d</b>) <span class="html-italic">S</span><sup>12</sup>; (<b>e</b>) <span class="html-italic">S</span><sup>13</sup>; (<b>f</b>) <span class="html-italic">S</span><sup>23</sup>.</p>
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<p>Equivalent stress contour result of different thermal stress conditions: (<b>a</b>) <span class="html-italic">S</span><sup>11</sup>; (<b>b</b>) <span class="html-italic">S</span><sup>22</sup>; (<b>c</b>) <span class="html-italic">S</span><sup>33</sup>; (<b>d</b>) <span class="html-italic">S</span><sup>12</sup>; (<b>e</b>) <span class="html-italic">S</span><sup>13</sup>; (<b>f</b>) <span class="html-italic">S</span><sup>23</sup>.</p>
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<p>The influence of fiber volume fraction on the elastic properties of CFRP: (<b>a</b>) <span class="html-italic">E</span><sub>1</sub>; (<b>b</b>) <span class="html-italic">E</span><sub>2</sub>; (<b>c</b>) <span class="html-italic">G</span><sub>12</sub>; (<b>d</b>) <span class="html-italic">μ</span><sub>12</sub>.</p>
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<p>The plain weave mesoscale cell structure: (<b>a</b>) Plain weave mesoscale cell structure parameters; (<b>b</b>) Equivalent stress contour result of plain weave mesoscale cell structure.</p>
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<p>Mesoscale cell structure: (<b>a</b>) The twill weave mesoscale cell structure; (<b>b</b>) The satin weave mesoscale cell structure.</p>
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<p>Schematic view of plain weave mesoscale cell structure.</p>
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<p>The influence of yarn volume fraction on the elastic properties of CFRP: (<b>a</b>) <span class="html-italic">E</span><sub>1</sub>; (<b>b</b>) <span class="html-italic">E</span><sub>3</sub>; (<b>c</b>) <span class="html-italic">G</span><sub>12</sub>; (<b>d</b>) <span class="html-italic">μ</span><sub>12</sub>.</p>
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<p>The influence of yarn volume fraction on the elastic properties of CFRP: (<b>a</b>) <span class="html-italic">E</span><sub>1</sub>; (<b>b</b>) <span class="html-italic">E</span><sub>3</sub>; (<b>c</b>) <span class="html-italic">G</span><sub>12</sub>; (<b>d</b>) <span class="html-italic">μ</span><sub>12</sub>.</p>
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<p>Exploded view of the door assembly.</p>
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<p>Loading and boundary conditions for car door stiffness.</p>
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<p>Flow chart of the design and optimization of material-structure integration.</p>
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<p>Pareto solutions for integrated design of plain weave.</p>
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<p>Pareto solutions for integrated design of twill weave.</p>
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<p>Pareto solutions for integrated design of satin weave.</p>
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22 pages, 10453 KiB  
Article
Landscape Ecology Analysis of Traditional Villages: A Case Study of Ganjiang River Basin
by Yuchen Zhou, Mu Liu, Guanhong Xie and Chunqing Liu
Appl. Sci. 2024, 14(2), 929; https://doi.org/10.3390/app14020929 - 22 Jan 2024
Cited by 8 | Viewed by 1544
Abstract
Traditional villages, rich in historical and cultural value, hold a high level of preservation value. In the process of urbanization, traditional villages face the crisis of decline, making it difficult to perpetuate the carried cultural heritage. The Ganjiang River Basin hosts numerous traditional [...] Read more.
Traditional villages, rich in historical and cultural value, hold a high level of preservation value. In the process of urbanization, traditional villages face the crisis of decline, making it difficult to perpetuate the carried cultural heritage. The Ganjiang River Basin hosts numerous traditional villages with rich research value, making the study of their preservation and development in this region a significant topic. This paper, from the perspective of landscape ecology, employs geographic detectors to analyze the driving factors behind the emergence of traditional villages in the Ganjiang River Basin, summarizing the spatial distribution characteristics of traditional villages. A classification method based on village landscape features is adopted to categorize traditional villages in the Ganjiang River Basin, providing a reference for planning the preservation and development of traditional villages. The research results show that plain areas are more suitable for the continuation of traditional villages; a single suitable environmental element cannot provide an environment conducive to the development of traditional villages, which is the result of the combined effect of multiple suitable elements; the study has divided traditional village landscapes into nine types, with clear distribution differences among different types of villages; for different regions and types of traditional villages, it is necessary to balance development and protection tendencies and plan differently according to environmental characteristics. Full article
(This article belongs to the Section Ecology Science and Engineering)
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<p>Research roadmap.</p>
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<p>Location of the Gan River Basin.</p>
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<p>Collection of environmental elements of traditional villages: (<b>a</b>) rivers and basin range; (<b>b</b>) river buffer range; (<b>c</b>) land use distribution; (<b>d</b>) elevation distribution; (<b>e</b>) slope distribution; (<b>f</b>) terrain roughness distribution.</p>
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<p>Histogram of traditional village river distance and average terrain elements value distribution around villages: (<b>a</b>) river distance; (<b>b</b>) average elevation; (<b>c</b>) average slope; (<b>d</b>) average terrain roughness.</p>
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<p>Histogram of land use type area proportion distribution around traditional villages: (<b>a</b>) forest land; (<b>b</b>) cultivated land; (<b>c</b>) water bodies; (<b>d</b>) construction land.</p>
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<p>Divergence and factor detection of traditional villages.</p>
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<p>Correlation analysis of the distribution of traditional villages, all villages, and construction land: the <b>lower left corner</b> is a scatter plot, the <b>center</b> shows a curve of the distribution of single elements, and the <b>upper right corner</b> displays the Pearson coefficient and significance. The ‘*’ following the number denotes the level of statistical significance, with ‘***’ indicating <span class="html-italic">p</span> &lt; 0.001, signifying a high level of significance.</p>
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<p>Analysis of distribution characteristics of traditional villages in Ganjiang River Basin: (<b>a</b>) kernel density analysis of traditional villages and overlay of traditional village point elements; (<b>b</b>) kernel density analysis of all villages and overlay of traditional village point elements; (<b>c</b>) kernel density analysis of construction land and overlay of traditional village point elements.</p>
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<p>Correlation between land use types and topography. The ‘*’ following the number denotes the level of statistical significance, with ‘***’ indicating <span class="html-italic">p</span> &lt; 0.001, signifying a high level of significance.</p>
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<p>Clustering tree of landscape types of traditional villages in Ganjiang River Basin: different colors and annotations represent the defined traditional village landscape types, and the numbers represent the traditional village codes.</p>
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<p>Range of land use element values for traditional village types in the Ganjiang River Basin: the <span class="html-italic">X</span>-axis represents the types of traditional villages; (<b>a</b>) cultivated land area; (<b>b</b>) forest land area; (<b>c</b>) water area; (<b>d</b>) construction land area.</p>
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<p>Range of terrain element values for traditional village types in the Ganjiang River Basin: the <span class="html-italic">X</span>-axis represents the types of traditional villages; (<b>a</b>) average elevation; (<b>b</b>) average slope; (<b>c</b>) average relief amplitude.</p>
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<p>Spatial distribution of traditional village landscape types: types A1-F represent the kernel density analysis of the spatial distribution of village types A1-F.</p>
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18 pages, 1824 KiB  
Article
Design and Control Simulation Analysis of Tender Tea Bud Picking Manipulator
by Peng Xue, Qing Li and Guodong Fu
Appl. Sci. 2024, 14(2), 928; https://doi.org/10.3390/app14020928 - 22 Jan 2024
Cited by 3 | Viewed by 1511
Abstract
Aiming at the current complex problem of the mechanized high-quality picking of tender tea buds, this paper designs a tender tea bud-picking manipulator. In the picking process, the quality of the petiole and leaf blade of the tender tea bud is crucial, as [...] Read more.
Aiming at the current complex problem of the mechanized high-quality picking of tender tea buds, this paper designs a tender tea bud-picking manipulator. In the picking process, the quality of the petiole and leaf blade of the tender tea bud is crucial, as the traditional cutting picking method destroys the cell structure of the tender tea buds, resulting in rapid oxidation of the cuts, thus losing the bright green appearance and pure taste. For this reason, this paper draws on the quality requirements of tender tea buds and traditional manual picking technology, simulating the process of the manual picking action, putting forward a ‘rotary pull-up’ clamping and ripping picking method, and designing the corresponding actuating structure. Using PVDF material piezoelectric thin-film sensors to detect the clamping force of the tender tea bud picking, the corresponding sensor hardware circuit is designed. In addition, the finite element analysis method is also used to carry out stress analysis on the mechanical fingers to verify the rationality of the automatic mechanism to ensure the high-quality picking of tender tea buds. In terms of the control of the manipulator, an SMC-PID control method is designed by using MATLAB/Simulink 2021 and Adam 2020 software for joint simulation. The way to control the closed-loop system angle and angular velocity error feedback is by adjusting the PID parameters, which quickly converts the sliding mode control to the sliding mode surface. The simulation results show that the SMC-PID control method proposed in this paper can meet the demand in tender tea bud picking and simultaneously has high control accuracy, response speed, and stability. Full article
(This article belongs to the Section Robotics and Automation)
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<p>Schematic diagram of the decomposition of traditional manual picking of tender tea buds.</p>
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<p>Schematic of SolidWorks modeling of a picking manipulator.</p>
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<p>Workflow diagram of the premium tea bud-picking manipulator.</p>
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<p>4-DOF picking manipulator planar schematic diagram.</p>
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<p>Stress cloud diagram.</p>
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<p>Maximum stress cloud diagram.</p>
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<p>Displacement cloud diagram.</p>
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<p>Structure of PVDF film.</p>
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<p>PVDF cut-out structure.</p>
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<p>Dimensioning drawing of PVDF sensor.</p>
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<p>Signal acquisition and processing hardware circuit structure.</p>
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<p>Schematic diagram of clamping simulation.</p>
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<p>Schematic diagram for model an SMC-PID control system in Simulink.</p>
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<p>Schematic diagram for modeling an SMC-PID control system in Simulink.</p>
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<p>Comparison diagram of picking manipulator clamping force control.</p>
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<p>Comparison of the effect of picking manipulator lifting 30° control.</p>
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<p>Comparison of the effect of lifting 45° control of the picking manipulator.</p>
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<p>Comparison of angular velocity control for a 30° rotation of a picking manipulator.</p>
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<p>Comparison of angular velocity control of a picking manipulator lifting at 45°.</p>
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<p>Displacement distance of the X-axis of the manipulator.</p>
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<p>Displacement distance of the Y-axis of the manipulator.</p>
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<p>Manipulator and displacement distance.</p>
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15 pages, 1538 KiB  
Article
The Role of Salivary Biomarkers in Monitoring Oral Health in Patients with Implants and Periodontitis
by Pia López-Jornet, Joonas Nikolai Hynninen, Francisco Parra-Perez, Camila Peres-Rubio, Eduardo Pons-Fuster and Asta Tvarijonaviciute
Appl. Sci. 2024, 14(2), 927; https://doi.org/10.3390/app14020927 - 22 Jan 2024
Cited by 3 | Viewed by 1653
Abstract
Oxidative stress, a physiological process that can damage cells, is known to affect various aspects of oral health. Oxidative stress can influence dental implant longevity and health. Assessing biomarkers of oxidative stress in saliva is beneficial for diagnosing and tracking the progression of [...] Read more.
Oxidative stress, a physiological process that can damage cells, is known to affect various aspects of oral health. Oxidative stress can influence dental implant longevity and health. Assessing biomarkers of oxidative stress in saliva is beneficial for diagnosing and tracking the progression of oral diseases. A study is made of salivary oxidative stress in patients with dental implants with or without periodontitis. The study consisted of the following groups: Group1 (healthy without dental implants); Group 2 (subjects undergoing periodontal maintenance without dental implants); Group 3 (healthy patients with implants older than six months); and Group 4 (patients undergoing periodontal maintenance with implants older than six months). A complete examination of the oral cavity was made in each patient and a questionnaire was used to assess habits of hygiene, quality of life, and information about the implants. The following parameters were recorded in unstimulated whole saliva: ferric reducing antioxidant power (FRAP), Trolox equivalent antioxidant capacity (TEAC), cupric reducing antioxidant capacity (CUPRAC), advanced oxidation protein products (AOPP), and total proteins (TP). A total of 160 patients were studied, with 40 patients per group. The mean oxidative stress biomarker values obtained in the patients without implants and with implants were FRAP 0.590 ± 0.514 and 0.588 ± 0.334 mmol/L (p = 0.974); TEAC 0.320 ± 0.223 and 0.315 ± 0.172 mmol/L (p = 0.879); CUPRAC 0.286 ± 0.216 and 0.288 ± 0.151 mmol/L (p = 0.956); AOPP 456.04 ± 789.75 and 430.65 ± 752.05 µmol/L (p = 0.838); and TP 73.90 ± 50.83 and 70.36 ± 56.93 mg/dL (p = 0.684), respectively. No substantial variations were noted in the salivary oxidative stress biomarker levels between patients with controlled periodontal disease and/or dental implants compared to healthy individuals. Full article
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<p>Diagram flowchart.</p>
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<p>Panoramic radiographic image 1: Healthy patients without implants; 2: Patients undergoing periodontal maintenance without dental implant; 3: Healthy patients with dental implants; 4: Patients undergoing periodontal maintenance with dental implants.</p>
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<p>Periodontal Examination.</p>
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<p>Unstimulated whole saliva.</p>
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11 pages, 667 KiB  
Article
Oral Health-Related Quality of Life among Complete Denture Stomatitis Patients Treated with Methylene-Blue-Mediated Photodynamic Therapy
by Mai M. Alhamdan and Ghadeer I. Basunbul
Appl. Sci. 2024, 14(2), 926; https://doi.org/10.3390/app14020926 - 22 Jan 2024
Cited by 1 | Viewed by 1103
Abstract
Aim: The aim was to assess the effect of antimicrobial photodynamic therapy (a-PDT) on the oral health-related quality of life (OHRQoL) of denture stomatitis patients. Methods: Forty patients were randomly selected to participate. Candidal proliferation was confirmed by using a CHROMagar culture and [...] Read more.
Aim: The aim was to assess the effect of antimicrobial photodynamic therapy (a-PDT) on the oral health-related quality of life (OHRQoL) of denture stomatitis patients. Methods: Forty patients were randomly selected to participate. Candidal proliferation was confirmed by using a CHROMagar culture and Gram staining. The denture surface and palatal mucosa were sprayed with a methylene blue photosensitizer prior to the photobiomodulation application. Laser therapy was applied two times a week at 72 h intervals for a period of 8 weeks. The OHIP-EDENT questionnaire was used to analyze the improvement in the OHRQoL. A Wilcoxon test was used to perform the candidal colony-forming unit’s count and comparison. A t-test was applied to evaluate the OHRQoL responses. Results: The overall CFU/mL values were higher in the dentures of the patients compared to a palatal mucosa swab. For instance, the CFU count was reduced from 5.56 ± 2.15 (baseline) to 3.17 ± 2.77 CFU/mL on day 60 on the palates. Similarly, the a-PDT application on the intaglio surface of the denture showed a reduction from 38.83 ± 14.71 to 29.05 ± 15.52 CFU/mL. A significant difference (p < 0.05) was found in function improvement as well as a reduction in physical pain, psychological discomfort, physical disability, and social interaction among the participants after photobiomodulation treatment. Conclusions: The OHRQoL was significantly improved in the DS patients. The Candida albicans abundance was radically reduced after the a-PDT application. Full article
(This article belongs to the Section Applied Dentistry and Oral Sciences)
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<p>Flow diagram of the study’s methodology and patient recruitment process.</p>
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<p>The distribution of OHIP-EDENT pre- and post-PBM treatment scores.</p>
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18 pages, 6358 KiB  
Article
Experimental Study on the Pre-Peak Mechanical and Seepage Characteristics of Granite
by Xinyan Zeng, Wancang Lin, Xinyi Chen and Qinglong Zhou
Appl. Sci. 2024, 14(2), 925; https://doi.org/10.3390/app14020925 - 22 Jan 2024
Viewed by 861
Abstract
The Sanshandao Gold Mine is currently in the deep mining stage. The ground pressure on the surrounding rocks is gradually becoming more considerable, and at the same time, threatened by the overlying seawater, the possibility of mine water inrush accidents is increasing. In [...] Read more.
The Sanshandao Gold Mine is currently in the deep mining stage. The ground pressure on the surrounding rocks is gradually becoming more considerable, and at the same time, threatened by the overlying seawater, the possibility of mine water inrush accidents is increasing. In this study, the MTS815 rock triaxial seepage test system was employed for the triaxial compression testing and stress–seepage coupled testing of granite under different confining pressures. The results show that granite’s pre-peak mechanical evolution under different confining pressures is divided into four stages (the crack closure stage, linear elasticity stage, stable crack expansion stage, and unstable crack expansion stage). With the increase in the confining pressure, the crack initiation threshold, crack damage threshold, and peak threshold gradually increased, but the closure threshold had no corresponding change. Moreover, in the loading process, the permeability curve first decreased and then increased, and the confining pressure suppressed the peak permeability of granite. Finally, based on the test results, stress sensitivity analysis was carried out, and it was found that polynomials fit the relationship between permeability and effective stress better. Granite’s permeability showed strong stress sensitivity at medium confining pressures. The stress sensitivity of the permeability of granite decreased with increasing effective stress at medium and high confining pressures, while it tended to increase at low confining pressures. Full article
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<p>Rock triaxial seepage test system.</p>
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<p>Schematic diagram of stress–seepage loading of rock samples.</p>
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<p>Flow chart of granite conventional triaxial test.</p>
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<p>Schematic diagram of progressive failure process in rocks.</p>
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<p>Determination of axial strain difference using stress–strain curve.</p>
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<p>Stress–axial strain difference curve.</p>
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<p>Stress threshold under three confining pressures.</p>
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<p>The volumetric curves of rock under different confining pressures.</p>
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<p>The volumetric curves of rock under different confining pressures.</p>
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<p>Evolution process of rock permeability in pre-peak process.</p>
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<p>Evolution process of rock permeability in pre-peak process.</p>
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<p>Permeability and effective stress curves.</p>
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<p>Effective stress and effective stress sensitivity coefficient under different confining pressures.</p>
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11 pages, 1831 KiB  
Article
A Comparative Assessment of the Bonding Characteristics of Three-Dimensional Custom-Printed Polycrystalline Alumina Brackets and Conventional Brackets
by Luay Jabr, P. Emile Rossouw, Dimitrios Michelogiannakis, Shaima Malik, Timothy T. Wheeler and Abdul Basir Barmak
Appl. Sci. 2024, 14(2), 924; https://doi.org/10.3390/app14020924 - 22 Jan 2024
Cited by 1 | Viewed by 1552
Abstract
Objective: The objective was to compare the shear bond strength (SBS) and the adhesive remnant index (ARI) amongst six orthodontic bracket groups. Materials and Methods: Three-dimensional printed polycrystalline alumina brackets (3DBs), ceramic brackets (CBs), and metal brackets (MBs), divided into six groups, were [...] Read more.
Objective: The objective was to compare the shear bond strength (SBS) and the adhesive remnant index (ARI) amongst six orthodontic bracket groups. Materials and Methods: Three-dimensional printed polycrystalline alumina brackets (3DBs), ceramic brackets (CBs), and metal brackets (MBs), divided into six groups, were bonded to bovine incisors using different bonding procedures. The SBSs were obtained using a universal testing machine, and the ARIs were assessed with a stereomicroscope. The statistical analyses included one-way analysis of variance (ANOVA) for SBS differences and Fisher’s exact test to show ARI differences amongst the groups (p < 0.05). Results: No significant differences (p > 0.05) were measured amongst the SBSs of the 3DB groups (12.3 MPa, 12.6 MPa, 12.3 MPa, 11.0 MPa, respectively). The latter four groups generally had significantly lower SBSs (p < 0.001) than the conventional bracket groups, CB and MB (16.9 MPa and 19.3 MPa, respectively). Also, there was no significant difference in SBSs for the CB and MB groups (p > 0.05). A high ARI for CBs and MBs (2) indicated that more than 50% of the adhesive remained on the enamel surface. The four 3DB groups had no residual adhesive or less than 50% adhesive on the enamel surface after debonding (ARI scores 0 and 1). A significant difference in ARI levels existed across the types of brackets (p < 0.05). Conclusion: Three-dimensional printed polycrystalline alumina brackets exhibited adequate SBS values for successful bonding. However, the values were lower compared to those for conventional ceramic and metal brackets. The majority of the adhesive remnant for the 3D-printed brackets was mainly located on the bracket base. Full article
(This article belongs to the Special Issue Present and Future of Orthodontics - 2nd Edition)
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<p>(<b>A</b>) Imbedded tooth (polyvinyl chloride (PVC) cylinders filled with self-cure acrylic resin). (<b>B</b>) Prepared bracket insert into universal test machine.</p>
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<p>(<b>A</b>) Universal test machine (New Day Research, West Chicago, IL, USA) and (<b>B</b>) closeup of the blade and bracket in the test machine ready for debonding.</p>
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<p>Diagram of shear bond strength (SBS) setup for testing.</p>
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<p>Top view of the residual amount of composite on the bracket base. (<b>A</b>) Metal base surface, (<b>B</b>) ceramic base surface, and (<b>C</b>) 3D-printed base surface.</p>
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<p>Top view of the residual amount of composite on the bracket base. (<b>A</b>) Metal base surface, (<b>B</b>) ceramic base surface, and (<b>C</b>) 3D-printed base surface.</p>
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26 pages, 1181 KiB  
Article
Advanced Medical Image Segmentation Enhancement: A Particle-Swarm-Optimization-Based Histogram Equalization Approach
by Shoffan Saifullah and Rafał Dreżewski
Appl. Sci. 2024, 14(2), 923; https://doi.org/10.3390/app14020923 - 22 Jan 2024
Cited by 6 | Viewed by 2688
Abstract
Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy of particle swarm optimization (PSO) combined with histogram equalization (HE) preprocessing for medical image segmentation, focusing on lung CT scan [...] Read more.
Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy of particle swarm optimization (PSO) combined with histogram equalization (HE) preprocessing for medical image segmentation, focusing on lung CT scan and chest X-ray datasets. Best-cost values reveal the PSO algorithm’s performance, with HE preprocessing demonstrating significant stabilization and enhanced convergence, particularly for complex lung CT scan images. Evaluation metrics, including accuracy, precision, recall, F1-score/Dice, specificity, and Jaccard, show substantial improvements with HE preprocessing, emphasizing its impact on segmentation accuracy. Comparative analyses against alternative methods, such as Otsu, Watershed, and K-means, confirm the competitiveness of the PSO-HE approach, especially for chest X-ray images. The study also underscores the positive influence of preprocessing on image clarity and precision. These findings highlight the promise of the PSO-HE approach for advancing the accuracy and reliability of medical image segmentation and pave the way for further research and method integration to enhance this critical healthcare application. Full article
(This article belongs to the Special Issue Artificial Intelligence in Biomedical Image Processing)
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<p>Overview of the proposed PSO-HE approach for enhanced medical image segmentation.</p>
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<p>Sample of lung CT scan image: (<b>a</b>) original image and (<b>b</b>) the high-resolution image from the dataset with (<b>c</b>) its complement.</p>
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<p>Sample chest X-ray images with different classes: (<b>a</b>) normal, (<b>b</b>) COVID-19, (<b>c</b>) lung opacity, and (<b>d</b>) pneumonia.</p>
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<p>Sample ground-truth (GT) annotations from the (<b>a</b>) lung CT scan and (<b>b</b>) chest X-ray COVID-19 datasets.</p>
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<p>Flowchart of the proposed particle swarm optimization (PSO) algorithm for medical image segmentation based on updated parameters.</p>
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<p>Histogram equalization (HE) preprocessing for lung CT scan and chest X-ray images demonstrating the resulting histogram distributions. Grayscaling 8-bit images of (<b>a</b>) lung CT scan and (<b>c</b>) chest X-ray images followed by HE preprocessing in (<b>b</b>) and (<b>d</b>), respectively, with histograms illustrating the outcome in each case.</p>
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<p>Initial process of parameter setting for PSO based on optimal iterations vs. population size (<span class="html-italic">nPop</span>) vs. computation time (s). The evaluation was conducted using MATLAB R2023 via Windows 10 Pro 64-bit powered by an Intel Core i7 processor running at 2.9 GHz with eight CPU cores.</p>
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<p>Comparison of best-cost values of the PSO segmentation approach for lung CT scan and chest X-ray images with and without histogram equalization (HE) preprocessing.</p>
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<p>Comparison of preprocessing approaches based on histogram analysis with samples of (<b>a</b>) lung CT scans and (<b>b</b>) chest X-rays. The figure illustrates the outcomes of various histogram-based preprocessing methods, including histogram equalization (HE), adaptive histogram equalization (AHE), contrast-limited adaptive histogram equalization (CLAHE), bi-histogram equalization (BBHE), and quadrants dynamic histogram equalization (QDHE).</p>
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13 pages, 2050 KiB  
Article
Inverse Problem Protocol to Estimate Horizontal Groundwater Velocity from Temperature–Depth Profiles in a 2D Aquifer
by Francisco Alhama, José Antonio Jiménez-Valera and Iván Alhama
Appl. Sci. 2024, 14(2), 922; https://doi.org/10.3390/app14020922 - 22 Jan 2024
Viewed by 978
Abstract
A general and precise protocol that follows the standards of an inverse problem in engineering is proposed to estimate groundwater velocity from experimental lectures of temperature vertical profiles in a 2D aquifer. Several values of error in the temperature measurements are assumed. Since [...] Read more.
A general and precise protocol that follows the standards of an inverse problem in engineering is proposed to estimate groundwater velocity from experimental lectures of temperature vertical profiles in a 2D aquifer. Several values of error in the temperature measurements are assumed. Since a large quantity of parameters and initial conditions influence the solution of this process, the protocol is very complex and needs to be tested to ensure its reliability. The studied scenario takes into account the input temperature of the water as well as the isothermal conditions at the surface and bottom of the aquifer. The existence of an input region, in which profiles develop to become linear, allows us to eliminate experimental measurements beyond such a region. Once the protocol is developed and tested, it is successfully applied to estimate the regional (lateral) groundwater velocity of the real aquifer and the result compared with estimations coming from the piezometric map. Full article
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<p>Physical scheme and boundary conditions.</p>
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<p>Block diagram of the inverse problem protocol.</p>
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<p>Location and limits of Agua Amarga coastal aquifer with wells P-3 and P-4 (Google Earth Pro).</p>
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<p>Cross-section of the aquifer on the line defined by wells P-3 and P-4.</p>
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<p>Real temperature–depth profiles measured in wells P-3 and P-4 of the Agua Amarga aquifer in March 2019.</p>
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<p>Vertical profiles of electrical conductivity recorded in March 2019 in boreholes P-3 and P-4.</p>
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