Nutrigenomic and Nutritional Analyses Reveal the Effects of Pelleted Feeds on Asian Seabass (Lates calcarifer). by Si Yan Ngoh, Daniel Tan, Xueyan Shen, Purushothaman Kathiresan, Junhui Jiang, Woei Chang Liew, Natascha May Thevasagayam, Hsiao Yuen Kwan, Jolly M Saju, Sridatta R S Prakki, Chin Heng Goh, Hong Ching Wong, Tai Teck Chan, Miklós Mézes, László Orbán

“…When the liver-based transcriptomes were analyzed, a complex set of differentially expressed genes were detected between groups fed pelleted feeds and controls as well as among the pellet-fed groups themselves. …”
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Behavioral Biases in Investor Decision-Making: A Comparative Meta-Analysis of Behavioral Finance Research by Seyed Amir Sabet, Saeed Aibaghi esfahani, Abdolmajid Abdolbaghi Ataabadi

“…This study conducts a meta-analysis of 61 empirical studies (24 domestic, 37 international) to compare the effects of 12 prominent behavioral biases, selected based on their prevalence and diversity in the literature. …”
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Current Trends and Advances in Extractive Text Summarization: A Comprehensive Review by Maryam Azam, Shah Khalid, Sulaiman Almutairi, Hasan Ali Khattak, Abdallah Namoun, Amjad Ali, Hafiz Syed Muhammad Bilal

“…Notable challenges include expanding summarization for complex tasks, multiple documents, multimodal user input, multi-format and multilingual data, refining the stopping criteria, and improving the evaluation metrics.…”
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Apple Yield Estimation Method Based on CBAM-ECA-Deeplabv3+ Image Segmentation and Multi-Source Feature Fusion by Wenhao Cui, Yubin Lan, Jingqian Li, Lei Yang, Qi Zhou, Guotao Han, Xiao Xiao, Jing Zhao, Yongliang Qiao

“…Apple yield estimation is a critical task in precision agriculture, challenged by complex tree canopy structures, growth stage variability, and orchard heterogeneity. …”
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Research on a Lightweight Arrhythmia Classification Model Based on Knowledge Distillation for Wearable Single-Lead ECG Monitoring Systems by Xiang An, Shiwen Shi, Qian Wang, Yansuo Yu, Qiang Liu

“…Deep learning models, trained on ECG signals across twelve or more leads, are the predominant approach for automated arrhythmia detection in the AI-assisted medical field. While these multi-lead ECG-based models perform well in automatic arrhythmia detection, their complexity often restricts their use on resource-constrained devices. …”
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Cu2+/Cu+ redox-cycling-driven dual-mode sensor for simultaneous monitoring of acetylcholinesterase activity and pesticide exposure by Sitong Lai, Sitong Lai, Kunhui Sun, Kunhui Sun, Yun Wu, Xueyuan Wu, Yiqi Yan, Yiqi Yan, Guojing Liu, Xiaoyi Liu, Yuanyuan Ge, Lina Zeng, Ziyu Guo, Shuhong Wang, Ping Wang, Bing Wang, Han Zhang, Xie-an Yu

“…IntroductionThe procedural complexity and time-consuming of conventional pesticide residue detection methods in traditional Chinese medicines (TCMs) significantly impeded their application in modern systems. …”
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Toward Robust Security Orchestration and Automated Response in Security Operations Centers with a Hyper-Automation Approach Using Agentic Artificial Intelligence by Ismail, Rahmat Kurnia, Zilmas Arjuna Brata, Ghitha Afina Nelistiani, Shinwook Heo, Hyeongon Kim, Howon Kim

“…By integrating AI-driven automation with the IVAM framework, our solution enhances investigation quality, improves response accuracy, and increases SOC efficiency in addressing modern cybersecurity threats.…”
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Multimodal approaches and AI-driven innovations in dementia diagnosis: a systematic review by Revati M. Wahul, Sarita Ambadekar, Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Manisha A. Dudhedia, Varsha Gaikwad, Bhavana Kanawade, J. R. Pansare, Balaji Bodkhe, S. H. Gawande

“…This survey will compare the study’s algorithms or frameworks on sensitivity, specificity, interpretability, computational efficiency, and clinical transnationality concerning early detection and monitoring progression. …”
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Cost-Effective Multitask Active Learning in Wearable Sensor Systems by Asiful Arefeen, Hassan Ghasemzadeh

“…Multitask learning models provide benefits by reducing model complexity and improving accuracy by concurrently learning multiple tasks with shared representations. …”
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HIV integration targeting: a pathway involving Transportin-3 and the nuclear pore protein RanBP2. by Karen E Ocwieja, Troy L Brady, Keshet Ronen, Alyssa Huegel, Shoshannah L Roth, Torsten Schaller, Leo C James, Greg J Towers, John A T Young, Sumit K Chanda, Renate König, Nirav Malani, Charles C Berry, Frederic D Bushman

“…Genome-wide siRNA screens have identified host cell factors important for efficient HIV infection, among which are nuclear pore proteins such as RanBP2/Nup358 and the karyopherin Transportin-3/TNPO3. …”
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ResTreeNet: A Height-Aware LiDAR Tree Classification Model With Explainable AI for Forestry Applications by Asrat Kaleab Taye, Jeong-Mook Park, Hyung-Ju Cho, Jin-Taek Kang, Yeon-Ok Seo

“…However, applying deep learning models to LiDAR-based tree classification remains challenging due to the computational complexity of existing 3D architectures, which often struggle with scalability and practical large-scale implementation. …”
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Study on spatial characteristics of coal seam water injection diffusion and fracture network flow patterns based on B-GFP fluorescent bacteria tracing by Dong XIAO, Suping PENG, Xuechen LI, Hailun HE

“…As mining depths increase, the complexity of fracture formation under the influence of in-situ stress and tectonic forces grows, limiting the accuracy of traditional detection methods in tracing fracture flow paths during hydraulic operations. …”
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APPLIED ASPECTS OF MODERN ANTI-CRISIS FINANCIAL MANAGEMENT by Zoia S. Pestovska, Кateryna S. Romanova, Olesya S. Rosenberg

“…The analysis showed almost the lowest limit of satisfactory efficiency of MS Trade Ukraine LLC and the fact that the biggest problems are with the financial component. …”
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Trusted Energy-Aware Hierarchical Routing (TEAHR) for Wireless Sensor Networks by Vikas, Charu Wahi, Bharat Bhushan Sagar, Manisha Manjul

“…Trust-based routing mechanisms are usually associated with high computation and storage complexity and susceptibility to collusive attacks such as spoofing. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…This model is designed to enhance the modeling capabilities for complex time-series data, improve the accuracy of missing data reconstruction, and ensure the reliability of health monitoring, ultimately guaranteeing wind turbines' safe and efficient operation. …”
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Molecular Modification Strategies for Enhancing CO₂ Electroreduction by Yali Wang, Leibing Chen, Guoying Li, Jing Mei, Feng Zhang, Jiaxing Lu, Huan Wang

“…Electrocatalytic CO₂ reduction reaction (CO₂RR) is a crucial technology for achieving carbon cycling and renewable energy conversion, yet it faces challenges such as complex reaction pathways, competition for intermediate adsorption, and low product selectivity. …”
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Improvement of the perovskite photodiodes performance via advanced interface engineering with polymer dielectric by Andrey P. Morozov, Lev O. Luchnikov, Sergey Yu. Yurchuk, Artur R. Ishteev, Pavel A. Gostishchev, Sergey I. Didenko, Nikita S. Saratovsky, Dmitry O. Balakirev, Ivan V. Dyadishchev, Andrey A. Romanov, Ekaterina A. Ilicheva, Anton A. Vasilev, Sergey S. Kozlov, Dmitry S. Muratov, Yuriy N. Luponosov, Danila S. Saranin

“…Halide perovskite-based photodiodes are promising for efficient detection across a broad spectral range. …”
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SWIPT-Enabled Cooperative Wireless IoT Networks With Friendly Jammer and Eavesdropper: Outage and Intercept Probability Analysis by Dinh Tung Vo, Trinh Van Chien, Tan N. Nguyen, Dinh-Hieu Tran, Miroslav Voznak, Byung Seo Kim, Lam Thanh Tu

“…In this context, a low-complexity, sub-optimal, but efficient relay selection method is proposed. …”
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Computational nanobody design through deep generative modeling and epitope landscape profiling by Liyun Huo, Tian Tian, Yanqin Xu, Qin Qin, Xinyi Jiang, Qiang Huang

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A Hybrid Deep Learning Framework for Early-Stage Alzheimer’s Disease Classification From Neuro-Imaging Biomarkers by Samina Akram, Muhammad Amjad Iqbal, Muhammad Rashid, Muhammad Shahid Bhatti, Benish Fida

“…Our ensemble methodology deciphers complex patterns within Magnetic Resonance Imaging, mapping them to specific AD early stages. …”
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