Classification of first embryonic division stages of multiple Caenorhabditis species by deep learning by Dhruv Khatri, Prachi Negi, Chaitanya A. Athale

“…Abstract The first embryonic division of Caenorhabditis elegans is a model for asymmetric cell division, and identifying the stages of cell division across related species could improve our understanding of the divergence of cellular events and mechanisms. …”
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Automated tick classification using deep learning and its associated challenges in citizen science by Anna Omazic, Giulio Grandi, Stefan Widgren, Joacim Rocklöv, Jonas Wallin, Jan C. Semenza, Najmeh Abiri

“…The EfficientNetV2M model achieved a macro recall of 0.60 and a Matthews Correlation Coefficient (MCC) of 0.55 on out-of-distribution, citizen-submitted data. …”
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Conceptual Perspectives on State Fragility by D. P. Elagin

“…However, these approaches tend to view fragile states as a deviation from the Europe an nation-state model and focus more on the attributes of fragility (inability to perform core functions of the state or lacking the capacity to cope with risks and crises) while failing to produce a precise explanation for its causes. …”
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Genome-Wide Association Study of Seed Quality and Yield Traits in a Soybean Collection from Southeast Kazakhstan by Botakoz Doszhanova, Alibek Zatybekov, Svetlana Didorenko, Chao Fang, Saule Abugalieva, Yerlan Turuspekov

“…The multiple-locus mixed linear model (MLMM) facilitated the identification of 38 stable MTAs: nine for protein content, nine for oil content, seven for the number of fertile nodes, six for the number of seeds per plant, four for thousand seeds weight, and three for yield per plant. …”
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A Comprehensive Review of Cryptographic Techniques in Federated Learning for Secure Data Sharing and Applications by Anik Sen, Swee-Huay Heng, Shing-Chiang Tan

“…The techniques, along with their respective strengths and weaknesses, are systematically compared to ensure the identification of appropriate application domains. This review addresses hybrid approaches that combine multiple techniques to achieve an optimal trade-off between privacy, computational efficiency, and scalability. …”
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Deep learning-based approach for extracting inflorescence morphology features in cut chrysanthemum by Shanpeng Xu, Jingshan Lu, Yin Wu, Huahao Liu, Fadi Chen, Fei Zhang, Sumei Chen, Weimin Fang, Zhiyong Guan

“…Accurate identification of floral morphological traits, such as flower type and the diameters of ligulate and bisexual flowers, is essential for the quality evaluation and varietal improvement of cut chrysanthemums (Chrysanthemum morifolium Ramat.). …”
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Enhancing Hospital Services: Achieving High Quality Under Resource Constraints by Mohammad Ali Beheshtinia, Masood Fathi, Morteza Ghobakhloo, Muhammad Faraz Mubarak

“…Results: Application of the MD-HOQ approach resulted in the identification of 50 patient needs across 5 hospital sections. …”
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SciLinker: a large-scale text mining framework for mapping associations among biological entities by Dongyu Liu, Cora Ames, Shameer Khader, Franck Rapaport

“…IntroductionThe biomedical literature is the go-to source of information regarding relationships between biological entities, including genes, diseases, cell types, and drugs, but the rapid pace of publication makes an exhaustive manual exploration impossible. In order to efficiently explore an up-to-date repository of millions of abstracts, we constructed an efficient and modular natural language processing pipeline and applied it to the entire PubMed abstract corpora.MethodsWe developed SciLinker using open-source libraries and pre-trained named entity recognition models to identify human genes, diseases, cell types and drugs, normalizing these biological entities to the Unified Medical Language System (UMLS). …”
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Application of machine learning in forensic geochemistry using presalt oil samples from the Santos basin by Gil Marcio Avelino Silva, Fernando Pellon de Miranda, Jarbas Vicente Poley Guzzo, Wagner Leonel Bastos, Ygor Rocha, Igor Viegas Alves Fernandes de Souza, Italo Oliveira Matias, Sarah Barron Torres, Francisco Fabio de Araujo Ponte

“…Abstract Identifying oil spills in offshore production areas presents a critical challenge, requiring reliable and efficient methodologies to minimize environmental and economic impacts. …”
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A New Classification Method in Ultrasound Images of Benign and Malignant Thyroid Nodules Based on Transfer Learning and Deep Convolutional Neural Network by Weibin Chen, Zhiyang Gu, Zhimin Liu, Yaoyao Fu, Zhipeng Ye, Xin Zhang, Lei Xiao

“…In this pursuit, the present study envisaged the development of an ultrasound diagnosis method for the accurate and efficient identification of thyroid nodules, based on transfer learning and deep convolutional neural network. …”
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A Mechanical Fault Diagnosis Method for On-Load Tap Changers Based on GOA-Optimized FMD and Transformer by Ruifeng Wei, Zhenjiang Chen, Qingbo Wang, Yongsheng Duan, Hui Wang, Feiming Jiang, Daoyuan Liu, Xiaolong Wang

“…The goal of this study is to develop an intelligent and accurate diagnostic approach for OLTC mechanical fault identification, particularly under the challenge of non-stationary vibration signals. …”
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Analysis of Congestion-Propagation Time-Lag Characteristics in Air Route Networks Based on Multi-Channel Attention DSNG-BiLSTM by Yue Lv, Yong Tian, Xiao Huang, Haifeng Huang, Bo Zhi, Jiangchen Li

“…First, to account for the interdependency across segments in air route networks, we construct a point–line congestion state assessment model and introduce the FCM-WBO algorithm for precise congestion state identification. …”
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Construction and Application of Intelligent O&M System for Urban Rail Transit Signaling Systems by YU Meng, LU Huaike, LIANG Zhe, FAN Zichao, GAO Ning

“…The goal is to break through the technical and managerial bottlenecks of traditional O&M models and achieve efficient, precise, and sustainable O&M system. …”
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Hybrid Vision System for Enhanced Situational Awareness in Unmanned Surface Vehicles: Decision-Level Camera-LiDAR Fusion With Supervised and Unsupervised Approaches by Yousef Abd Alhattab, Hasan F. M. Zaki, Abd Halim Bin Embong, Zulkifli Bin Zainal Abidin, Ahmed Rimaz Faizabadi, Ahmad Imran Ibrahim

“…The integration of LiDAR and cameras with an efficient data fusion approach significantly improves Enhanced Situational Awareness (ESA) for small-sized Unmanned Surface Vehicles (USVs). …”
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Improved SOM algorithm for damage characterization based on visual sensing by Hongtao Zhu, Shuyun Guo

“…The proposed enhanced model significantly augments the accuracy and efficiency of concrete damage identification, providing an effective solution for the health monitoring of concrete structures, particularly in scenarios requiring large-scale and real-time monitoring. …”
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Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection by Vikas Gaur, Gaurav Maggu, Khushboo Bairwa, Suprakash Chaudhury, Sana Dhamija, Tahoora Ali

“…High precision, recall, and accuracy align with expert evaluations, highlighting its promise for timely risk identification. The model’s efficiency in evaluating large populations swiftly indicates its clinical potential. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…This enhanced performance in practical detection surpasses that of the original YOLOv5 model. The number of observed particle chains increases following optimization by integrating the improved YOLOv5 model with the grayscale subtraction technique for detecting particle motion. …”
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A lightweight triple-modal fusion network for progressive mild cognitive impairment prediction in Alzheimer's disease by Xiangyu Shen, Xiangyang Hu, Renfeng Zhang, Yunzhan Fu, Jiamin Xu, Degang Lyu, Hongbiao Xie, Hongbiao Xie, Deen Shi, Changsheng Shi, Lisi Li, Yuantong Gao

“…TriLightNet incorporates a hybrid backbone that combines Kolmogorov-Arnold Networks with PoolFormer for efficient feature extraction. Additionally, it introduces a Hybrid Block Attention Module to capture subtle interactions between image and clinical features and employs a MultiModal Cascaded Attention mechanism to enable progressive and efficient fusion across the modalities. …”
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On the utility of immobilized phenylarsine oxide in the study of redox sensitive cardiac proteins by Asvi Arora Francois, Xiaoke Yin, Shinichi Oka, Junichi Sadoshima, Manuel Mayr, Philip Eaton

“…This together with complementary studies using a cardiac-specific FLAG-Thioredoxin-1C35S-HA transgenic ‘trap-mutant’ mouse model allowed identification of heart proteins susceptible to oxidant-induced disulfide bond formation using proteomics. …”
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Harnessing self-supervised learning to boost malicious traffic detection with enhanced attention by SUN Jianwen, ZHANG Bin, LI Hongyu, CHANG Heyu

“…Before making classification decisions, the integration ability of high-weight features was enhanced to further improve the model's detection precision. The CIC-IDS2017 dataset was employed for the experiment, and the results showed that in the multi-classification scenario for malicious traffic identification, the precision of the MTAttention method could reach an average of 98.7%, and the inference efficiency exceeded 1590 samples per second. …”
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