MPAR-RCNN: a multi-task network for multiple person detection with attribute recognition by S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, Jayashree Shetty, Praveen Gurunath Bharathi

“…This study introduces an innovative MTL framework designed to incorporate Multi-Person Attribute Recognition (MPAR) within a single-model architecture. Named MPAR-RCNN, this framework unifies object detection and attribute recognition tasks through a spatially aware, shared backbone, facilitating efficient and accurate multi-label prediction. …”
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Influence of Side-Polished Fiber Surface Topography on Surface Plasmon Resonance Wavelengths and the Full Width at Half-Maximum by Zhiyong Bai, Mingquan Li, Jing Zhao, Shaoqing Cao, Ying Wang, Changrui Liao, Yiping Wang

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Improved decomposition of cloud feedback and corresponding pattern change under uniform surface ocean warming: I. Anomalous mean method by Jing Feng, Jian Ma

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A Deep Learning Method for Improving Community Multiscale Air Quality Forecast: Bias Correction, Event Detection, and Temporal Pattern Alignment by Ioannis Stergiou, Nektaria Traka, Dimitrios Melas, Efthimios Tagaris, Rafaella-Eleni P. Sotiropoulou

“…The model is trained here, using data from ten stations in Texas, enabling it to capture both spatial and temporal patterns in atmospheric behavior. …”
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Neuropsychological and clinical variables associated with cognitive trajectories in patients with Alzheimer's disease by Marianna Riello, Monica Moroni, Stefano Bovo, Flavio Ragni, Manuela Buganza, Raffaella Di Giacopo, Marco Chierici, Lorenzo Gios, Matteo Pardini, Matteo Pardini, Federico Massa, Federico Massa, Monica Dallabona, Elisa Vanzetta, Cristina Campi, Cristina Campi, Michele Piana, Michele Piana, Sara Garbarino, Manuela Marenco, Venet Osmani, Giuseppe Jurman, Antonio Uccelli, Antonio Uccelli, Bruno Giometto, Bruno Giometto, NeuroArtP3 Network, Filippo Gerli, Guido Pasquini, Claudia Niccolai, Matteo Betti, Emilio Portaccio, Maria Pia Amato, Rossi Andrea, Parodi Costanza, Ramaglia Antonia, Tortora Domenico, Severino Mariasavina, Andrea Falini, Antonella Castellano, Nicolò Pecco, Paola Scifo, Sonia Calloni

“…Model interpretability analysis revealed that the global cognitive state progression in AD patients is associated with: low spatial memory (Corsi block-tapping), verbal episodic long-term memory (Babcock's story recall) and working memory (Stroop Color) performances, the presence of hypertension, the absence of hypercholesterolemia, and functional skills inabilities at the IADL scores at baseline.ConclusionThis is the first AI study to predict cognitive trajectories of AD patients using routinely collected clinical data, while at the same time providing explainability of factors contributing to these trajectories. …”
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Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer by Sepideh Azarianpour, Sirvan Khalighi, Arpit Aggarwal, Vidya Sankar Viswanathan, Pingfu Fu, Stefanie Avril, Anant Madabhushi

“…Our study findings suggest the need for population-specific risk prediction models for women with endometrial cancer.…”
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A novel deep learning approach to field-road semantic segmentation by Bei Wang, Wenze Wang

“…This study presents a deep learning framework that implements a novel semantic segmentation model designed to segment field-road trajectories, addressing the marked differences in spatial characteristics. …”
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LMD-YOLO: A lightweight algorithm for multi-defect detection of power distribution network insulators based on an improved YOLOv8. by Weiyu Han, Zixuan Cai, Xin Li, Anan Ding, Yuelin Zou, Tianjun Wang

“…Experimental results show that LMD-YOLO achieves a 2% higher average accuracy on the insulator dataset compared to YOLOv8n, with a 24.6% reduction in model parameters, offering an effective solution for smart grid inspections.…”
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Colonization in North American Arid Lands: The Journey of Agarito (Berberis trifoliolata) Revealed by Multilocus Molecular Data and Packrat Midden Fossil Remains. by Diego F Angulo, Leonardo D Amarilla, Ana M Anton, Victoria Sosa

“…The most important prediction of packrat middens palaeomodelling lies in the Mexican Plateau, a finding congruent with current and past niche modelling predictions for agarito and genetic results. …”
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Hourglass attention for image super-resolution by Ling Xu, Yian Huang, Xiaoping Lin

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Elemental Associations with Groundwater Nitrate in Northeastern Region of Saudi Arabia: Implications for Sustainable Water Management by Al Mamun

“…Future research should focus on elucidating factors influencing nitrate distribution in groundwater systems and developing more robust predictive models based on readily measurable water quality parameters.…”
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Factor structure and validation of the Motor Imagery Vividness Scale (MIV-S) by Nobuchika Yamaki

“…Future research should explore its predictive validity and applicability across diverse populations to further enhance its contribution to motor imagery research and practice.…”
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Virtual Reality in Building Evacuation: A Review by Ming-Chuan Hung, Ching-Yuan Lin, Gary Li-Kai Hsiao

“…Future research should integrate VR with artificial intelligence and machine learning for predictive and adaptive evacuation models. Expanding VR applications to underrepresented groups, including individuals with disabilities and the elderly, and collaborating with policymakers and urban planners are vital for translating research into practice. …”
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Whole genome resequencing reveals the evolutionary history and geographic isolation of the eastern Asian Hickory (Carya) by Da Zhang, Rui‐Feng Yang, Jia‐Hui Chen, Lang‐Bo Pan, Wei Duan, Guo‐Hua Xia, Qi‐Xiang Zhang, You‐Jun Huang

“…Species distribution modeling predicted suitable habitats for five EA Carya species, revealing the potential distribution of endangered C. kweichowensis. …”
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Numerical Analysis of the Preloading Consolidation of the Soft Foundation with a Plastic Drainage Plate by Linjie Li, Shuaidong Yang, Tong Su

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A sub-meter resolution urban surface albedo dataset for 34 U.S. cities based on deep learning by Shengao Yi, Xiaojiang Li, Yixuan Liu, Xinyu Dong, Wei Tu

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Evaluation of Landslide Risk Using the WoE and IV Methods: A Case Study in the Zipaquirá–Pacho Road Corridor by Sandra Velazco, Álvaro Rodríguez, Martín Riascos, Fernando Nieto, Dayana Granados

“…Of these, 70% were used to build the models, while the remaining 30% were reserved for validation, ensuring spatial representativeness. …”
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The use of artificial intelligence-based Siamese neural network in personalized guidance for sports dance teaching by Yi Xie, Yao Yan, Yuwei Li

“…The results show that the proposed GCN-SNN model achieves an accuracy of 96.72% and an F1 score of 86.55%, significantly outperforming other comparison models. …”
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Nondestructive estimation of leaf chlorophyll content in banana based on unmanned aerial vehicle hyperspectral images using image feature combination methods by Weiping Kong, Weiping Kong, Lingling Ma, Huichun Ye, Huichun Ye, Jingjing Wang, Chaojia Nie, Binbin Chen, Xianfeng Zhou, Wenjiang Huang, Zikun Fan

“…We concluded that the nonlinear Gaussian process regression model with the VIs and TFs-PC1 combination selected by maximal information coefficient as input achieved the highest accuracy in LCC prediction for banana, with the highest R2 of 0.776 and lowest RMSE of 2.04. …”
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Spatio-Temporal Characteristics and Driving Forces of Landscape Ecological Risks in Highly Urbanized Areas: A Case Study of Suzhou City by Lingyue LU, Dawei SHAO, Dianming WU

“…A large amount of research has concentrated on risk evolution, the identification of influencing factors or drivers, and the simulation and prediction of risks in natural areas such as watersheds, coastal zones, wetlands, and ecological reserves. …”
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