Advanced TSGL-EEGNet for Motor Imagery EEG-Based Brain-Computer Interfaces by Xin Deng, Boxian Zhang, Nian Yu, Ke Liu, Kaiwei Sun

“…Though the accuracy of Motor Imagery (MI) BCI systems based on the deep learning have been greatly improved compared with some traditional algorithms, it is still a big problem to clearly interpret the deep learning models. …”
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PRMT1 Promotes the Self‐renewal of Leukemia Stem Cells by Regulating Protein Synthesis by Min Zhou, Yi Huang, Ping Xu, Shuyi Li, Chen Duan, Xiaoying Lin, Shilai Bao, Waiyi Zou, Jingxuan Pan, Chang Liu, Yanli Jin

“…However, disease relapse and progression particularly due to persistent leukemia stem cells (LSCs) remain a big challenge in the clinic. Therefore, validation of the therapeutic vulnerability in LSCs is urgently needed. …”
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Construction and Optimization of Integrated Yield Prediction Model Based on Phenotypic Characteristics of Rice Grown in Small–Scale Plantations by Jihong Sun, Peng Tian, Zhaowen Li, Xinrui Wang, Haokai Zhang, Jiangquan Chen, Ye Qian

“…The above research findings demonstrate that this integrated model possesses high practical value and fills a gap in precise yield prediction for small-scale rice cultivation in the Yunnan Plateau region.…”
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Digital-based emergency prevention and control system: enhancing infection control in psychiatric hospitals by Mi Yang, Xiaojun Zhu, Fei Yan, Xincheng Huang, Zhixue Wu, Xin Jiang, Yan Huang, Zezhi Li

“…Methods The system incorporates modern technologies such as cloud computing, big data, streaming media, and knowledge graphs. …”
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Research Status and Prospect of Quality Intelligent Control Technology in Facilities Environment of Characteristic Agricultural Products by GUO Wei, WU Huarui, GUO Wang, GU Jingqiu, ZHU Huaji

“…Through the application of the Internet of Things, big data and the new generation of artificial intelligence technology, it provides technical support for the construction and application of intelligent process quality control system for the whole growth period of characteristic agricultural products.…”
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A Deep Learning Framework for the Classification of Brazilian Coins by Debabrata Swain, Viral Rupapara, Amro Nour, Santosh Satapathy, Biswaranjan Acharya, Shakti Mishra, Ali Bostani

“…We used a comprehensive dataset of Brazilian coins, comprising various denominations, minting years, and conditions, to facilitate model training and evaluation. The dataset includes high-resolution images captured under diverse lighting and environmental conditions, ensuring robust model performance in real-world scenarios. …”
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The Treatment Effect of Plantago Major on Lung Cancer Based on the Computed Tomography and Pathological Findings: A Case Report Study by Saade Abdalkareem Jasim, Bashar Mudhaffar Abdullah, Patricio Yánez-Moretta, Wesam R. Kadhum, Yasser Fakri Mustafa, Enas R. Alwaily, Munther Abosoda, Ali Alsalamy, Sada Ghalib Al-Musawi, Alaa A. Omran

“…However, more follow-up examinations on big sample sizes are needed to assess the treatment effect of PM. …”
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Universal conditional networks (UniCoN) for multi-age embryonic cartilage segmentation with Sparsely annotated data by Nishchal Sapkota, Yejia Zhang, Zihao Zhao, Maria Jose Gomez, Yuhan Hsi, Jordan A. Wilson, Kazuhiko Kawasaki, Greg Holmes, Meng Wu, Ethylin Wang Jabs, Joan T. Richtsmeier, Susan M. Motch Perrine, Danny Z. Chen

“…Tackling this segmentation task with deep learning (DL) methods is laborious due to the big burden of manual image annotation, expensive due to the high acquisition costs of 3D micro-CT images, and difficult due to embryonic cartilage’s complex and rapidly changing shapes. …”
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Establishment of reference audiometric norms for the elderly population: A community-based study on mean and median hearing thresholds by Tzong-Hann Yang, Yu-Fu Chen, Yen-Fu Cheng, Chuan-Song Wu, Yuan-Chia Chu

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Explainable AI for Healthcare 5.0: Opportunities and Challenges by Deepti Saraswat, Pronaya Bhattacharya, Ashwin Verma, Vivek Kumar Prasad, Sudeep Tanwar, Gulshan Sharma, Pitshou N. Bokoro, Ravi Sharma

“…Healthcare 5.0 focuses on real-time patient monitoring, ambient control and wellness, and privacy compliance through assisted technologies like artificial intelligence (AI), Internet-of-Things (IoT), big data, and assisted networking channels. However, healthcare operational procedures, verifiability of prediction models, resilience, and lack of ethical and regulatory frameworks are potential hindrances to the realization of Healthcare 5.0. …”
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The Disclosure of Leniency Statements and Other Evidence under Directive 2014/104/EU: An Undue Prominence of Public Enforcement? by Claudia Massa

“…Articles 5 to 8 of the Directive create a “microsystem” of the law of the evidences, which is highly specialised and based on the central role of the judge and on the principle that private enforcement must not compromise public enforcement. …”
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Yolk and Casein Sequence Self-Assembly for Low-Oil Emulsion Gel and Its Application in Low-Fat Mayonnaise by Anqi Bi, Beiwei Zhu, Ning Cong, Ming Du, Chao Wu, Ling Zhang, Yan Guo, Tingting Cheng, Pei Yu, Xianbing Xu

“…High dietary fat food such as mayonnaise (70–80% oil content) can induce obesity and cardiovascular diseases, thus reducing their oil content is required. …”
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Introduction of the single-lumen oocyte retrieval needle in an assisted reproductive technology center: Propensity score matching analysis of grouping by Tian-Jeau Huang, Hsiao-Chin Huang, Horng-Der Tsai, Chew-Teng Kor, Chueh-Ko Yang, Hsin-Hung Wu

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Assessment of Hand-Hygiene Practices Among Health Care Workers at Kisoro Hospital, Kisoro District. by Nsenga, Alex

“…The study findings revealed that 91(85.8%) of the respondents had good knowledge about hand hygiene. 83 (96.7%) of the respondents had high awareness in respect to practice of hand washing before touching a patient and lowest awareness in respect to practice of hand hygiene after exposure to immediate surroundings of a patient. …”
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Retinopathy Disease Detection and Classification Using a Coordinate Attention Module-Based Convolutional Neural Network with Leaky Rectified Linear Unit by Pravin Balaso Chopade, Prabhakar N. Kota, Bhagvat D. Jadhav, Pravin Marotrao Ghate, Shriram Sadashiv Kulkarni

“…Untuk mengatasi isu-isu ini, kertas ini mencadangkan teknik berasaskan Pembelajaran Mendalam (DL) untuk pengesanan awal dan tepat bagi DR. Modul Coordinate Attention Module (CAM) berasaskan Convolutional Neural Network (CNN) dengan Leaky Rectified Linear Unit (LReLU) dicadangkan untuk pengesanan awal dan tepat bagi DR. …”
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Characteristics of seaweed caraginan Kappaphycus alvarezii on cultivation system with different seed weight by Muhammad Rasnijal, Ardana Kurniaji, Anton Anton, Budiyati Budiyati, Diana Putri Renitasari, Achmad Suhermanto, Mugi Mulyono, Iin Siti Djunaidah, Sinung Rahardjo, Sinar Pagi Sektiana, Ridwan Ridwan

“…The purpose of this study to analyze the characteristics of carrageenan seaweed cultivated with bag and non-bag cultivation systems and different seed weights. …”
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Generation and miRNA Characterization of Equine Induced Pluripotent Stem Cells Derived from Fetal and Adult Multipotent Tissues by Laís Vicari de Figueiredo Pessôa, Pedro Ratto Lisboa Pires, Maite del Collado, Naira Caroline Godoy Pieri, Kaiana Recchia, Aline Fernanda Souza, Felipe Perecin, Juliano Coelho da Silveira, André Furugen Cesar de Andrade, Carlos Eduardo Ambrosio, Fabiana Fernandes Bressan, Flavio Vieira Meirelles

“…We were able to generate bFGF-dependent iPSCs from eADmsc, eUCmsc, and eFibros with human OSKM, and the miRNA profile revealed that clonal lines may respond differently to the reprogramming process.…”
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La gestion de l’eau à Bibracte (Saône-et-Loire), avant et après la Conquête romaine by Laetitia Borau

“…Second, huge basins were discovered around every excavated spring. Third, big reservoirs are distributed across the whole site. …”
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Brown Fat and Metabolic Health: The Diverse Functions of Dietary Components by Zachary Brown, Takeshi Yoneshiro

“…Brown and beige adipocytes utilize a variety of substrates for cold-induced thermogenesis, contributing to the clearance of metabolites in circulation and, consequently, metabolic health. …”
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