Enhanced spectral signatures with Ag nanoarrays in hyperspectral microscopy for CNN-based microplastics classfication by Xinwei Dong, Xinwei Dong, Xu Zhao, Jianing Xu, Qianqian Chen, Hanwen Luo, Fuxin Zheng, Tao Zhang, Yansheng Liu

“…This study demonstrates the potential of combining Ag nanoarrays with 3D-2D CNN models to enhance micro-HSI performance, offering a novel and effective solution for precise microplastics detection and advancing chemical analysis, environmental monitoring, and related fields.…”
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Methodology of Using CAx and Digital Twin Methods in the Development of a Multifunctional Portal Centre in Its Pre-Production Phase by Petr Bernardin, Zdenek Hajicek, Petr Janda, Josef Kozak, Frantisek Sedlacek, Vaclava Lasova, Jiri Kubicek

“…The proposed methodology was used on a specific machine, namely, a multifunctional portal centre, where features of computer-aided engineering (modelling, topology optimisation, stiffness and stress analyses, modal analyses, and analytical calculations) were combined with tools using the digital twin. …”
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Differential Adjuvant Activity by Flagellins from <i>Escherichia coli</i>, <i>Salmonella enterica</i> Serotype Typhimurium, and <i>Pseudomonas aeruginosa</i> by Shengmei Pang, Mei Liu, Longlong Wang, Mingqing Shao, Guoqiang Zhu, Qiangde Duan

“…This study aims to analyze the amino acid sequences and structural features of flagellins from <i>Escherichia coli</i> (FliC<i>_E.C</i>), <i>Salmonella enterica</i> serotype Typhimurium (FliC<i>_S.T</i>), and <i>Pseudomonas aeruginosa</i> (FliC<i>_P.A</i>), and to evaluate their adjuvant activities in terms of Toll-like receptor 5 (TLR5) activation, antibody production, and cytokine responses in a murine model. (2) <b>Methods</b>: Bioinformatics analysis was conducted to compare the amino acid sequences and structural domains (D0, D1, D2, and D3) of flagellins from the three bacterial species. …”
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Cancelable finger vein authentication using multidimensional scaling based on deep learning by Mohamed Hammad, Mohammed ElAffendi, Ahmed A. Abd El-Latif

“…Our method addressed the limitations of previous biometric authentication systems by integrating MDS with a lightweight convolutional neural network (CNN) model for feature extraction. The cancelable approach ensured privacy and security by generating distinct templates for each user. …”
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Comparative Analysis of Multi-Resolution Remote Sensing Data for Accurate Road Segmentation in Urban Environments by M. R. Çevikalp, B. Mutlu, M. Yanalak, N. Musaoğlu

“…Recent advances in satellite technology have alleviated these issues by providing ultra-high-resolution (sub-meter) imagery, which is vital for accurately representing road networks. Deep learning models like U-Net have enhanced road segmentation by accurately capturing complex features. …”
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Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques by Shoayee Dlaim Alotaibi, Abeer A. K. Alharbi

“…Next, the EADCD-TIPAIT technique performs a binary greylag goose optimization (BGGO)-based feature selection approach to efficiently identify relevant features that distinguish between normal and dementia-affected brain regions. …”
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Using Graph-Enhanced Deep Reinforcement Learning for Distribution Network Fault Recovery by Yueran Liu, Peng Liao, Yang Wang

“…The restoration problem is modeled as a partially observable Markov decision process (POMDP), where each agent employs graph neural networks to extract topological features and enhance environmental perception. …”
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AER-Net: Attention-Enhanced Residual Refinement Network for Nuclei Segmentation and Classification in Histology Images by Ruifen Cao, Qingbin Meng, Dayu Tan, Pijing Wei, Yun Ding, Chunhou Zheng

“…In addition, the imbalance of various nuclei classes exacerbates the difficulty of nuclei classification and segmentation using deep learning models. To address these challenges, we present a novel attention-enhanced residual refinement network (AER-Net), which consists of one encoder and three decoder branches that have same network structure. …”
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Criteria of evaluating augmented reality applications by M. R. Ablyaev, A. N. Abliakimova, Z. S. Seidametova

“…That will give an opportunity to decide on specific development tools, methods, models and technologies before starting work on a project. …”
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Development of design methodology of technological process of ball-rod hardening with account for formation of compressive residual stresses by M. A. Tamarkin, E. E. Tishchenko, S. A. Novokreshchenov, S. A. Morozov

“…The tool circuit diagram is given. Features, technological advantages, and the application area of the ball-rod hardening are specified.Materials and Methods. …”
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Evaluation of the Accuracy and Applicability of Reanalysis Precipitation Products in the Lower Yarlung Zangbo Basin by Anqi Tan, Ming Li, Heng Liu, Liangang Chen, Tao Wang, Binghui Yang, Min Wan, Yong Shi

“…Results indicate TPMFD performed best overall, capturing spatiotemporal patterns effectively (correlation coefficients 0.6–0.8, low RBIAS). …”
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Leveraging commonality across multiple tissue slices for enhanced whole slide image classification using graph convolutional networks by Sakonporn Noree, Willmer Rafell Quinones Robles, Young Sin Ko, Mun Yong Yi

“…Methods We propose a novel technique that leverages inter-slice commonality to enhance classification performance. Our method constructs graphs for each tissue slice, extracts relevant features, and connects these graphs based on spatial relationships and feature similarities, creating a comprehensive representation of the entire tissue sample, which is then used for WSI classification using graph convolutional networks. …”
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MACNet: A Multidimensional Attention-Based Convolutional Neural Network for Lower-Limb Motor Imagery Classification by Ling-Long Li, Guang-Zhong Cao, Yue-Peng Zhang, Wan-Chen Li, Fang Cui

“…The experimental results show that MACNet achieves state-of-the-art performance and outperforms alternative models for the subject-specific mode. …”
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Health Workers’ Perspectives on Mobile Health Care Learning Stickiness: Mixed Methods Study by Sabila Nurwardani, Putu Wuri Handayani

“…Quantitative data processing was conducted using covariance-based structural equation modeling, whereas qualitative analysis was conducted on the data from 15 respondents using the content analysis method. …”
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SDNet: Sandwich Decoder Network for Waterbody Segmentation in Remote Sensing Imagery by Hao Ni, Jianfeng Li, Chenxu Wang, Zhiquan Zhou, Xinsheng Wang

“…Although self-attention (SA) and convolutional neural networks have demonstrated strong modeling capabilities on RS image recognition, their efficiency and expressiveness still deserve further optimization. …”
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IMViT: Adjacency Matrix-Based Lightweight Plain Vision Transformer by Qihao Chen, Yunfeng Yan, Xianbo Wang, Jishen Peng

“…This paper proposes a non-hierarchical transformer network which can capture both long-range and short-range as non-hierarchical transformers, and keep its performance on small-sized transformers. First, we discard the framework of progressively reduced feature maps but design two separate stages, i.e., multi-scale feature preparatory stages and multi-scale feature perception stages, where the first stage uses the lightweight multi-branch structure to extract multi-scale features, and the second stage leverages the non-hierarchical networks to learn semantic information for downstream tasks. …”
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Stem cell-based therapeutic strategies for down syndrome and Alzheimer’s disease by Osama Hamadelseed, Thomas Skutella

“…Preclinical trials using neural, mesenchymal, and induced pluripotent stem cells have shown their potential to mitigate disease pathology, restore neuronal function, modulate neuroinflammation, enhance neurogenesis, and improve cognitive performance in DS and AD models; these findings suggest the viability of stem cell-based interventions as a disease-modifying strategy. …”
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Risk-based innovations in cancer screening and diagnosis: a discrete choice experiment to explore priorities of the UK public by Stephen Morris, Jo Waller, Juliet Usher-Smith, Stuart Wright, Rebecca Dennison, Reanna J Clune

“…Participants were randomly allocated to consider the choice in an asymptomatic or symptomatic context.Setting Members of the public in the UK.Participants 1202 participants completed the DCE.Outcome measures Conditional logistic regression and latent class analysis informed modelling of predicted preferences for a range of innovations with different features.Results Overall, participants preferred risk assessments over opting out and prioritised sensitivity, with test method and specificity also important. …”
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Research Progress of Dangerous Driving Behavior Recognition Methods Based on Deep Learning by Junjian Hou, Bingyu Zhang, Yudong Zhong, Wenbin He

“…Then, the collected big data are utilized to extract the features related to dangerous driving behavior. The paper mainly classifies the deep learning models employed for dangerous driving behavior recognition into three categories: Deep Belief Network (DBN), Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN). …”
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Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images by Kaiyuan Long, Shibo Li, Jiangping Long, Hui Lin, Yang Yin

“…Lastly, our proposed Siblings Detection Head reduces computational burden while significantly improving detection performance. Ablation experiments demonstrate that compared to baseline models, YOLO-PH exhibits notable improvements of 1.3% in mAP50 and 1.1% in mAP50:95 while simultaneously achieving a reduction of 48.8% in FLOPs and an impressive increase of 26.8 FPS (frames per second) in detection speed. …”
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