Research on Mine-Personnel Helmet Detection Based on Multi-Strategy-Improved YOLOv11 by Lei Zhang, Zhipeng Sun, Hongjing Tao, Meng Wang, Weixun Yi

“…Additionally, the frames per second reached 90.3 f·s⁻¹, representing increases of 3.3% and 9.4%, respectively, compared to the baseline model. In addition, when compared to models such as YOLOv5s, YOLOv8s, YOLOv3 Tiny, Fast R-CNN, and RT-DETR, GCB-YOLOv11 demonstrates superior performance in both detection accuracy and model complexity. …”
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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

“…These components work together to streamline multimodal data integration while preserving meaningful insights.ResultsExtensive experiments conducted on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset demonstrate the effectiveness of TriLightNet, showcasing superior performance compared to state-of-the-art methods. Specifically, the model achieves an accuracy of 81.25%, an AUROC of 0.8146, and an F1-score of 69.39%, all while maintaining reduced computational costs.DiscussionFurthermore, its interpretability was validated using the Integrated Gradients method, which revealed clinically relevant brain regions contributing to the predictions, enhancing its potential for meaningful clinical application. …”
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Automatic Identification of High-Quality Channels in Distributed Acoustic Sensing Through Implementation of a Channel Quality Index by Tatiana Rodriguez, Aleix Segui, Arantza Ugalde, Melania Cubas Armas, Hugo Latorre, Sergi Ventosa, Tony Monfret

“…Trained on data from four offshore DAS experiments in the Spanish Mediterranean and Canary Islands, our model evaluates temporal, frequency, and energy-based features to assign quality scores to individual channels, reliably identifying high-quality channels with high precision (0.92–0.96) and strong performance in terms of area under the receiver operating characteristic curve (ROC–AUC, 0.92–0.98). …”
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Dysregulated ATX-LPA and YAP/TAZ signaling in dystrophic Sgcd −/− mice with early fibrosis and inflammation by Cristian Gutiérrez-Rojas, Adriana Córdova-Casanova, Jennifer Faundez-Contreras, Meilyn Cruz-Soca, Felipe S. Gallardo, Alexia Bock-Pereda, Juan Carlos Casar, Elisabeth R. Barton, Enrique Brandan

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Selective laser melted tantalum three-column porous screw: a novel design achieving both mechanical stability and biological fixation by Di Wu, Zuofa Yan, Bing Ge, Yujin Dong, Jiajun Zhao, Bin Wu, Fang Cao, Haiyao Wang, Zhijie Ma, Junlei Li, Dewei Zhao

“…In vivo osseointegration capability of TTCPS was investigated using a comminuted fracture model in New Zealand white rabbits, with histological staining and mechanical pull-out tests that performed at 1, 2, and 3 months post-surgery. …”
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A low-cost platform for automated cervical cytology: addressing health and socioeconomic challenges in low-resource settings by José Ocampo-López-Escalera, Héctor Ochoa-Díaz-López, Xariss M. Sánchez-Chino, César A. Irecta-Nájera, Saúl D. Tobar-Alas, Martha Rosete-Aguilar

“…This dataset was then used to fine-tune and test several pre-trained models for classifying between images containing normal and abnormal cell subtypes.ResultsMost of the tested models showed good performance for properly classifying images containing abnormal and normal cervical cells, with sensitivities above 90%. …”
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Employing Neural Networks, Fuzzy Logic, and Weibull Analysis for the Evaluation of Recycled Brick Powder in Concrete Compositions by Mohammad Mohtasham Moein, Komeil Rahmati, Ali Mohtasham Moein, Ashkan Saradar, Sam E. Rigby, Amin Akhavan Tabassi

“…During the numerical phase, artificial neural network models (ANN) and fuzzy logic models (FL) were used to predict the results of 28-day compressive strength. …”
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Merits of dietary patterns for China’s future food security satisfying socioeconomic development and climate change adaptation by Wencong Yue, Meirong Su, Yanpeng Cai, Qiangqiang Rong, Chao Xu, Yuanchao Hu, Jiajia Li, Shujie Yu, Donghan Chen, Zhongqi Liu, Zhenkun Tan, Zhifeng Yang

“…Crop yields per unit area were simulated with a denitrification-decomposition (DNDC) model under four climate-change scenarios. A high shortage risk for soybean and lower shortage risks for maize and wheat were predicted. …”
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Advanced and interpretable corneal staining assessment through fine grained knowledge distillation by Yuqing Deng, Pujin Cheng, Ruiwen Xu, Lirong Ling, Hongliang Xue, Shiyou Zhou, Yansong Huang, Junyan Lyu, Zhonghua Wang, Kenneth K. Y. Wong, Yimin Zhang, Kang Yu, Tingting Zhang, Xiaoqing Hu, Xiaoyi Li, Xiaoying Tang, Yan Lou, Jin Yuan

“…To address these limitations, we developed the Fine-grained Knowledge Distillation Corneal Staining Score (FKD-CSS) model. FKD-CSS integrates fine-grained features into CSS grading, providing continuous and nuanced scores with interpretability. …”
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A Novel Multi-Sensor Nonlinear Tightly-Coupled Framework for Composite Robot Localization and Mapping by Lu Chen, Amir Hussain, Yu Liu, Jie Tan, Yang Li, Yuhao Yang, Haoyuan Ma, Shenbing Fu, Gun Li

“…We propose a real-time luminance calculation model and verify its conversion accuracy. Additionally, we designed a fast approximation method for the nonlinear weighted fusion of features from infrared and RGB frames based on luminance values. …”
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Space-Based Mapping of Pre- and Post-Hurricane Mangrove Canopy Heights Using Machine Learning with Multi-Sensor Observations by Boya Zhang, Daniel Gann, Shimon Wdowinski, Chaohao Lin, Erin Hestir, Lukas Lamb-Wotton, Khandker S. Ishtiaq, Kaleb Smith, Yuepeng Li

“…Model performance of SAR and optical data differed with time period and across height classes. …”
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Modular annular photocatalytic membrane reactor for the degradation of micropollutants: Design and application by Michael S. Leupold, Max Reuschenbach, Gerrit Renner, Anam Asghar, Klaus Kerpen, Lukas Fischer, Torsten C. Schmidt

“…The reactor's modular design facilitates easy membrane replacement, supports diverse operational modes, and integrates in-line and on-line monitoring for real-time analytical insights. Amoxicillin (AMX), a model organic pollutant, was used as the probe compound to evaluate reactor performance with potassium nitrate as a UV cut-off filter (λ < 325 nm) providing precise evaluation of both photocatalytic and photolytic AMX degradation.…”
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Sentinel-2 Masking CNNs Trained on Physics-Supervised Labels by Efrain Padilla-Zepeda, Kevin Alonso, Raquel De Los Reyes, Deni Torres-Roman, Avi Putri Pertiwi, Tobias Storch

“…The model is trained using a large global training dataset from PACO, while a separate validation dataset from the same source is used to monitor performance during learning and prevent overfitting. …”
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Diseño y validación de un cuestionario de autopercepción de la excelencia en el deporte (Design and validation of a questionnaire on self-perception of excellence in sport) by Juan Ángel Simón Piqueras, Juan Gregorio Fernández Bustos, Onofre Ricardo Contreras Jordán

“…The analysis confirmed a structure based on six factors: environment, sportsman, training features, trainer, training type, and family. In the last phase, the final version of the questionnaire was administered to 1,256 athletes in order to check for model quality by means of confirmatory factorial analysis. …”
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Integrating geostatistical methods and deep learning for enhanced 87Sr/86Sr isoscape Estimation: A case study in South Korea by Hyeongmok Lee, Go-Eun Kim, Woo-Jin Shin, Yuyoung Lee, Sanghee Park, Kwang-Sik Lee, Jina Jeong, Seung-Ik Park, Sungwook Choung

“…The proposed model achieved significantly higher classification accuracy (91.67%) compared to kriging-based and CNN-based models (76.7% and 86.7%, respectively). …”
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Editorial by Christian Gütl

“…And last but not least, Ashish Ranjan Mishra, Rakesh Kumar and Rajkumar Saini from India present their study on the improvement of the effectiveness of person authentication by using deep learning techniques on electroencephalogram (EEG)&amp;nbsp;signals by applying a multiscale convolutional neural network (CNN) and a Bidirectional LSTM (BiLSTM) model to extract features and classify raw EEG data.Enjoy Reading!…”
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Machine learning-assisted wearable sensing systems for speech recognition and interaction by Tao Liu, Mingyang Zhang, Zhihao Li, Hanjie Dou, Wangyang Zhang, Jiaqian Yang, Pengfan Wu, Dongxiao Li, Xiaojing Mu

“…Finally, the speech recognition system was able to recognize everyday sentences spoken by participants with an accuracy of 99.8% through a deep learning model. With advantages including a simple fabrication process, stable performance, easy integration, and low cost, SAAS presents a compelling solution for applications in voice control, HMI, and wearable electronics.…”
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Ferroptosis-related genes mediate tumor microenvironment and prognosis in triple-negative breast cancer via integrated RNA-seq analysis by Xuantong Gong, Lishuang Gu, Di Yang, Yu He, Qian Li, Hao Qin, Yong Wang

“…This study integrates single-cell and bulk RNA sequencing data from the Gene Expression Omnibus to elucidate ferroptosis-driven TME features in TNBC, employing machine learning to develop prognostic and therapeutic response prediction models. …”
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Prediction of Alzheimer’s Disease Based on Multi-Modal Domain Adaptation by Binbin Fu, Changsong Shen, Shuzu Liao, Fangxiang Wu, Bo Liao

“…Specifically, MM-DDA comprises three primary modules: (1) the feature encoding module, which employs convolutional neural networks (CNNs) to capture detailed and abstract feature representations from MRI and PET images; (2) the multi-head attention feature fusion module, which is used to fuse MRI and PET features, that is, to capture rich semantic information between modes from multiple angles by dynamically adjusting weights, so as to achieve more flexible and efficient feature fusion; and (3) the domain transfer module, which reduces the distributional discrepancies between the source and target domains by employing adversarial learning training. …”
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Systematic Review and Meta-Analysis on the Accuracy of Artificial Intelligence Algorithms in Individuals Gender Detection Using Orthopantomograms by Mahmood Dashti, Tara Azimi, Farshad Khosraviani, Sarina Azimian, Lina Bahanan, Houyar Zahmatkesh, Heba Ashi, Zohaib Khurshid

“…The analysis focused on studies that reported accuracy, sensitivity, and specificity of AI models. Statistical analyses were performed using R software, including forest plots and funnel plots, to evaluate the diagnostic performance and potential publication bias. …”
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