Battery Energy Storage Systems in Microgrids: A Review of SoC Balancing and Perspectives by Thales Augusto Fagundes, Guilherme Henrique Favaro Fuzato, Lucas Jonys Ribeiro Silva, Augusto Matheus dos Santos Alonso, Juan C. Vasquez, Josep M. Guerrero, Ricardo Quadros Machado

“…In this article, we present a comprehensive review of EMS strategies for balancing SoC among BESS units, including centralized and decentralized control, multiagent systems, and other concepts, such as designing nonlinear strategies, optimal algorithms, and categorizing agents into clusters. Moreover, in this article, we discuss alternatives to improve EMS and strategies regarding the topology of power converters, including redundancy-based topology, modular multilevel converter, cascaded-based converter, and hybrid-type systems. …”
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Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies by Rahul Kumar, Ethan Waisberg, Joshua Ong, Phani Paladugu, Dylan Amiri, Jeremy Saintyl, Jahnavi Yelamanchi, Robert Nahouraii, Ram Jagadeesan, Alireza Tavakkoli

“…Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. …”
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Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence by Yasin Görmez, Fatma Hilal Yagin, Burak Yagin, Yalin Aygun, Hulusi Boke, Georgian Badicu, Matheus Santos De Sousa Fernandes, Abedalrhman Alkhateeb, Mahmood Basil A. Al-Rawi, Mohammadreza Aghaei, Mohammadreza Aghaei

“…In terms of interpretability, LIME showed superior in fidelity, whereas SHAP showed improved sparsity and consistency across models, facilitating a comprehensive understanding of trait importance.ConclusionThis research demonstrates that ML algorithms, when integrated with XAI technologies, can accurately predict obesity levels and explain important contributing risk factors. …”
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AI-Powered IoT: A Survey on Integrating Artificial Intelligence With IoT for Enhanced Security, Efficiency, and Smart Applications by Vivek Menon U, Vinoth Babu Kumaravelu, Vinoth Kumar C, Rammohan A, Sunil Chinnadurai, Rajeshkumar Venkatesan, Han Hai, Poongundran Selvaprabhu

“…The various machine learning (ML) and deep learning (DL) algorithms in IoT are necessary to ensure the IoT network’s improved security and confidentiality. …”
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Aberrant fragmentomic features of circulating cell-free mitochondrial DNA enable early detection and prognosis prediction of hepatocellular carcinoma by Yang Liu, Fan Peng, Siyuan Wang, Huanmin Jiao, Kaixiang Zhou, Wenjie Guo, Shanshan Guo, Miao Dang, Huanqin Zhang, Weizheng Zhou, Xu Guo, Jinliang Xing

“…Background/Aims Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. …”
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Urban Greening Analysis: A Multimodal Large Language Model for Pinpointing Vegetation Areas in Adverse Weather Conditions by Hanzhang Liu, Shijie Yang, Chengwu Long, Jiateng Yuan, Qirui Yang, Jiahua Fan, Bingnan Meng, Zhibo Chen, Fu Xu, Chao Mou

“…The UGSAM was compared with three classic deep learning algorithms and the SAM. Experimental results show that under adverse weather conditions, the UGSAM performs best in OA (0.8615), mIoU (0.8490), recall (0.9345), and precision (0.9027), surpassing the baseline model FCN (OA improvement 28.19%) and PointNet++ (OA improvement 30.02%). …”
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Immunophenotype-guided interpretable radiomics model for predicting neoadjuvant anti-PD-1 response in stage III–IV d-MMR/MSI-H colorectal cancer by Xuan Zhang, Zhenhui Li, Yiwen Zhang, Yanli Li, Xi Zhong, Wenjing Jiang, Xiaobo Chen, Zaiyi Liu, Liebin Huang, Caixia Zhang, Lizhu Liu, Ruimin You, Xiaoping Yi

“…Background Neoadjuvant immunotherapy significantly improves the pathological complete response (pCR) rate in colorectal cancer (CRC). …”
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Identification of a potential miRNA–mRNA regulatory network for ischemic stroke by using bioinformatics methods: a retrospective study based on the Gene Expression Omnibus database... by Zhaoying Chen, Xiaodan Zhang, Xiangjun Qi, Jiyuan Zheng, Niancai He, Bohui Zheng, Nan Zhong, Chengcheng Ji, Yulan Jin, Hu Yu, Weinv Fan, Guoming Chen

“…Our findings bridge the gap between clinical observations and molecular mechanisms, paving the way for improved IS management.…”
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Domain-Adaptive and Per-Fraction Guided Deep Learning Framework for Magnetic Resonance Imaging-Based Segmentation of Organs at Risk in Gynecologic Cancers by Reza Kalantar, PhD, Manasi Ingle, FRCR, Romelie Rieu, BA, BmBCh, Sebastian Curcean, MD, Jessica Mary Winfield, PhD, Gigin Lin, MD, PhD, Christina Messiou, MD, MRCP, FRCR, Susan Lalondrelle, FRCR, Dow-Mu Koh, MD, FRCP, FRCR, Matthew David Blackledge, PhD

“…Results: The synthetic MRL-assisted model improved organ at risk segmentation accuracy on MRL images, with fraction-adapted contours displaying high anatomical fidelity. …”
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Exploring the Current Status of Risk Stratification in Hypertrophic Cardiomyopathy: From Risk Models to Promising Techniques by Alexandros Kasiakogias, Christos Kaskoutis, Christos-Konstantinos Antoniou, Stavros Georgopoulos, Dimitrios Tsiachris, Petros Arsenos, Alexandrina Kouroutzoglou, Dimitrios Klettas, Charalambos Vlachopoulos, Konstantinos Tsioufis, Konstantinos Gatzoulis

“…Improving clinical prediction of sudden cardiac death is a crucial step in the management of patients with hypertrophic cardiomyopathy. …”
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…This study aimed to develop and validate an artificial intelligence (AI)-driven diagnostic model to improve diagnostic accuracy and reduce variability. …”
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Development and Validation of Survival Prediction Models for Patients With Pineoblastomas Using Deep Learning: A SEER‐Based Study by Xuanzi Li, Shuai Yang, Yingpeng Peng, Xueqiang You, Shunli Peng, Siyang Wang, Dasong Zha, Shuyuan Zhang, Chuntao Deng

“…These results indicate the potential of DL algorithms to improve outcome prediction in patients with rare tumors.…”
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Identifying the best reference gene for RT-qPCR analyses of the three-dimensional osteogenic differentiation of human induced pluripotent stem cells by Masakazu Okamoto, Yusuke Inagaki, Kensuke Okamura, Yoshinobu Uchihara, Kenichiro Saito, Akihito Kawai, Munehiro Ogawa, Akira Kido, Eiichiro Mori, Yasuhito Tanaka

“…Our findings provide valuable insights for reference gene selection and bone tissue regeneration from hiPSCs, which could improve the treatment prospects for bone defects and other similar conditions in regenerative medicine.…”
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A novel ensemble model for multi-temporal forest vegetation classification: integrating spectral-temporal features and topographic constraints by Rongfei Duan, Chunlin Huang, Peng Dou, Jinliang Hou, Ying Zhang

“…Spectral and temporal dimensions were jointly encoded to enhance feature representation, and an ensemble learning strategy was introduced to improve model robustness and adaptability. The framework comprises a feature extraction module and an ensemble classification module. …”
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Application of precision agriculture technologies for crop protection and soil health by Emogine Mamabolo, Makgabo Johanna Mashala, Ephias Mugari, Tlou Elizabeth Mogale, Norman Mathebula, Kabisheng Mabitsela, Kwabena Kingsley Ayisi

“…This farming approach has several applications to improve productivity; for example, drones have been used to monitor crop health and detect water stress, enabling timely interventions to reduce losses. …”
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Comparative analysis of mini-open trans-thoracic transpleural and posterior approaches in thoracic disc herniation surgery: A 10-year retrospective review by Ali Baram, Giorgio Cracchiolo, Marco Riva, Gabriele Capo, Leonardo Anselmi, Carlo Brembilla, Stefania Radice, Maria Pia Tropeano, Carla Anania, Emanuela Morenghi, Maurizio Fornari, Federico Pessina

“…Despite established algorithms, the optimal surgical strategy remains debated. …”
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Orchard variable-rate spraying method integrating GNSS and wind-excited audio-conducted leaf area density by Hangxing Zhao, Hangxing Zhao, Hangxing Zhao, Shenghui Yang, Shenghui Yang, Shenghui Yang, Wenwei Li, Wenwei Li, Han Feng, Han Feng, Shijie Jiang, Shijie Jiang, Weihong Liu, Weihong Liu, Jingbin Li, Yongjun Zheng, Yongjun Zheng, Songchao Zhang

“…This system significantly improves droplet deposition uniformity while reducing environmental losses, offering a promising technical solution for the development of intelligent and sustainable plant protection equipment.…”
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Stratification system with dual human endogenous retroviruses for predicting immunotherapy efficacy in metastatic clear-cell renal cell carcinoma by Li Xu, Stephane Oudard, Catherine Sautes-Fridman, Xiaoping Su, Gabriel G. Malouf, Virginie Verkarre, Salma Kotti, Fangrong Yan, Yann-Alexandre Vano, Wolf Herve Fridman, Cheng-Ming Sun, Xiaofan Lu, Wenxuan Cheng

“…ERV expression was quantified using the ERVmap algorithm from RNA sequencing data. Our primary objective was to correlate ERV expression with progression-free survival, with overall survival and time-to-second-treatment survival as secondary endpoints. …”
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Spectroscopic photoacoustic denoising framework using hybrid analytical and data-free learning method by Fangzhou Lin, Shang Gao, Yichuan Tang, Xihan Ma, Ryo Murakami, Ziming Zhang, John D. Obayemi, Winston O. Soboyejo, Haichong K. Zhang

“…Traditional denoising techniques like frame averaging, though effective in improving SNR, can be impractical for dynamic imaging scenarios due to reduced frame rates. …”
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Approaches to Extracting Patterns of Service Utilization for Patients with Complex Conditions: Graph Community Detection vs. Natural Language Processing Clustering by Jonas Bambi, Hanieh Sadri, Ken Moselle, Ernie Chang, Yudi Santoso, Joseph Howie, Abraham Rudnick, Lloyd T. Elliott, Alex Kuo

“…This may improve outcomes for complex patients with chronic diseases. …”
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