How to improve mental health in the older adults through AI-enhanced physical activity: an emerging research topic by Wen Fang, Sijing Fan, Hongyun Zheng, Zijian Fang, Yanwei You, Bo Yin, Baixia Li, Xinming Ye

“…These interventions were supported in their effectiveness by biomarkers of BDNF, serotonin, and increased physical activity levels.The present study combines insights on AI, physical activity, and mental health to facilitate emerging research opportunities and practical applications. …”
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An Application of SEMAR IoT Application Server Platform to Drone-Based Wall Inspection System Using AI Model by Yohanes Yohanie Fridelin Panduman, Radhiatul Husna, Noprianto, Nobuo Funabiki, Shunya Sakamaki, Sritrusta Sukaridhoto, Yan Watequlis Syaifudin, Alfiandi Aulia Rahmadani

“…In this paper, we present an application of <i>SEMAR</i> to a drone-based wall inspection system using an object detection AI model called <i>You Only Look Once (YOLO)</i>. …”
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Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors by Congying Pu, Hui Cui, Huaxing Yu, Xin Cheng, Man Zhang, Luoheng Qin, Zhilin Ning, Wen Zhang, Shan Chen, Yuhang Qian, Feng Wang, Ling Wang, Xiaoxia Lin, David Gennert, Frank W. Pun, Feng Ren, Alex Zhavoronkov

“…Our findings provide evidence supporting ENPP1 as an innate immune checkpoint across solid tumors and reports an AI design-aided ENPP1 inhibitor, ISM5939, as a cutting-edge STING modulator for cancer therapy, paving a path for immunotherapy advancements.…”
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SmartScreen‐AIS: A High‐Throughput qPCR Chip for Nationwide Surveillance of Aquatic Invasive Species by John A. Kronenberger, Taylor M. Wilcox, Michael K. Schwartz

“…Here, we help meet this need with SmartScreen‐AIS: a high‐throughput qPCR (HT‐qPCR) chip with 46 assays targeting aquatic invasive species of widespread concern. …”
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PassAI: An Explainable Machine Learning Framework for Predicting Soccer Pass Outcomes Using Multimodal Match Data by Ryota Takamido, Jun Ota, Hiroki Nakamoto

“…PassAI addresses these challenges with an original dual-stream architecture that processes image-based and tabular features separately and then combines them for final prediction. …”
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Healthcare professionals’ perspectives on artificial intelligence (AI)-based mobile applications (apps) for diabetes education and behavioural management by Phei-Ching Lim, Yung-Wey Chong, Qiu-Ting Chie, Hadzliana Zainal, Kok-Lim Alvin Yau, Soo-Huat Teoh

“…Artificial intelligence (AI) integrated into mobile health applications (apps) presents a promising avenue for enhancing diabetes management through personalized patient education and behaviour modification. …”
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Screening and Validation: AI-Aided Discovery of Dipeptidyl Peptidase-4 Inhibitory Peptides from Hydrolyzed Rice Proteins by Cheng Cheng, Huizi Cui, Xiangyu Yu, Wannan Li

“…Natural peptides derived from rice offer a promising alternative due to their favorable biocompatibility and development potential. In this study, an AI-assisted virtual screening pipeline integrating machine learning, molecular docking, and molecular dynamics (MD) simulations was established to identify and evaluate rice-derived DPP-4 inhibitory peptides. …”
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Connecting self-esteem to problematic AI chatbot use: the multiple mediating roles of positive and negative psychological states by Ruiqi Yao, Guijie Qi, Dongfang Sheng, Hua Sun, Jiacheng Zhang

“…Incorporating flow experience into the compensatory internet use theory, this study presents a multiple mediation model to investigate how social anxiety, escapism, and AI chatbot flow influence the relationship between self-esteem and PACU. …”
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AI-Driven Identification of Grapevine Fungal Spores via Microscopic Imaging and Feature Optimization with Cuckoo Search Algorithm by Xin Shi, Seyed Mohamad Javidan, Yiannis Ampatzidis, Zhao Zhang

“…Early, intelligent detection of fungal spores is vital for effective disease management. This study presents a high-accuracy classification model that uses microscopic images to differentiate among four closely related grapevine pathogens: Lasiodiplodia brasiliensis, L. crassispora, L. exigua, and L. gilanensis. …”
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Advanced predictive modeling of shear strength in stainless-steel column web panels using explainable AI insights by Sina Sarfarazi, Rabee Shamass, Federico Guarracino, Ida Mascolo, Mariano Modano

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Design and Validation of an Edge-AI Fire Safety System with SmartThings Integration for Accelerated Detection and Targeted Suppression by Seung-Jun Lee, Hong-Sik Yun, Yang-Bae Sim, Sang-Hoon Lee

“…This study presents the design and validation of an integrated fire safety system that leverages edge AI, hybrid sensing, and precision suppression to overcome the latency and collateral limitations of conventional smoke detection and sprinkler systems. …”
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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…In the rapidly evolving domain of Unmanned Aerial Vehicles (UAVs), precise altitude estimation remains a significant challenge, particularly for lightweight UAVs. This research presents an innovative approach to enhance altitude estimation accuracy for UAVs weighing under 2 kg without cameras, utilizing advanced AI Deep Learning algorithms. …”
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Effectiveness of AI for Enhancing Computed Tomography Image Quality and Radiation Protection in Radiology: Systematic Review and Meta-Analysis by Subo Zhang, Zhitao Zhu, Zhenfei Yu, Haifeng Sun, Yi Sun, Hai Huang, Lei Xu, Jinxin Wan

“… BackgroundArtificial intelligence (AI) presents a promising approach to balancing high image quality with reduced radiation exposure in computed tomography (CT) imaging. …”
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Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI by Khan Muhammad Adnan, Taher M. Ghazal, Muhammad Saleem, Muhammad Sajid Farooq, Chan Yeob Yeun, Munir Ahmad, Sang-Woong Lee

“…To address this issue, the present study applies Explainable AI (XAI) alongside deep learning for accurate and interpretable brain Tumour prediction. …”
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A comprehensive survey on AI-enabled secure social industrial Internet of Things in the agri-food supply chain by Sajal Halder, Md Rafiqul Islam, Quazi Mamun, Arash Mahboubi, Patrick Walsh, Md Zahidul Islam

“…The rapid evolution of Artificial Intelligence (AI) and the Social Industrial Internet of Things (SIIoT) has significantly impacted the agri-food supply chain, offering transformative solutions for security, efficiency, and sustainability. …”
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Mapping the Global Research on Drug–Drug Interactions: A Multidecadal Evolution Through AI-Driven Terminology Standardization by Andrei-Flavius Radu, Ada Radu, Delia Mirela Tit, Gabriela Bungau, Paul Andrei Negru

“…Using advanced tools, including VOSviewer version 1.6.20, Bibliometrix 5.0.0, and AI-enhanced terminology normalization, global research trajectories, knowledge clusters, and collaborative dynamics were systematically mapped. …”
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Improving breast ultrasonography education: the impact of AI-based decision support on the performance of non-specialist medical professionals by Sangwon Lee, Hye Sun Lee, Eunju Lee, Won Hwa Kim, Jaeil Kim, Jung Hyun Yoon

“…Methods In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. …”
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BrAIn Jam: neural signal-informed adaptive system for drumming collaboration with an AI-driven virtual musician by Torin Hopkins, Torin Hopkins, Ruojia Sun, Suibi Che Chuan Weng, Shih-Yu Ma, Shih-Yu Ma, James Crum, Leanne Hirshfield, Ellen Yi-Luen Do, Ellen Yi-Luen Do

“…However, utilizing musical information from the human brain has only been explored in limited social and musical contexts. This paper presents “BrAIn Jam,” utilizing functional near-infrared spectroscopy to monitor human drummers' brain states during musical collaboration with an AI-driven virtual musician. …”
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Towards Context-Rich Automated Biodiversity Assessments: Deriving AI-Powered Insights from Camera Trap Data by Paul Fergus, Carl Chalmers, Naomi Matthews, Stuart Nixon, André Burger, Oliver Hartley, Chris Sutherland, Xavier Lambin, Steven Longmore, Serge Wich

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AI-driven demand forecasting for enhanced energy management in renewable microgrids: A hybrid LSTM-CNN approach by Bashiru olalekan ariyo, mutalub adesina lambe, olalekan ogunbiyi, musa abdulwaheed, bilkisu jimada ojuolape, monsurat omolara balogun

“…However, the inherent unpredictability of renewable energy sources presents significant challenges in energy management. …”
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