The Genetic Puzzle of the Stress-Induced Cardiomyopathy (Takotsubo Syndrome): State of Art and Future Perspectives by Domenico Lio, Letizia Scola, Giusi Irma Forte, Loredana Vaccarino, Manuela Bova, Patrizia Di Gangi, Giorgia Santini, Daniela di Lisi, Cristina Madaudo, Giuseppina Novo

“…Takotsubo syndrome (TS), also known as stress-induced cardiomyopathy, is classically characterized by an acute onset mimicking myocardial infarction and by distinctive transient wall motion abnormalities detectable via echocardiography, often resembling a Japanese octopus trap (the so-called “takotsubo”). …”
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Reinforcement learning for vehicle-to-grid: A review by Hongbin Xie, Ge Song, Zhuoran Shi, Jingyuan Zhang, Zhenjia Lin, Qing Yu, Hongdi Fu, Xuan Song, Haoran Zhang

“…However, with the random integration of a large number of electric vehicles into the grid, the uncertainty and complexity of the system have significantly increased, posing substantial challenges to traditional algorithms. Reinforcement learning has shown great potential in addressing these high-dimensional dynamic scheduling optimization problems. …”
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Behavior Analysis With Integrated Visual-Motor Tracking for Developmental Coordination Disorder by Ruimin Li, Hong Fu, Yang Zheng, Shuiping Gou, Jane Jie Yu, Xiaowei Kong, Hongmin Wang

“…First, visual components of interest are detected and extracted using a series of intelligent algorithms. Then, the kinematic features are defined and calculated to describe the children behavior, including eye movement, body movement, and interacting object trajectory. …”
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Interpretable machine learning for stability and electronic structure prediction of Janus III–VI van der Waals heterostructures by Yudong Shi, Yinggan Zhang, Jiansen Wen, Zhou Cui, Jianhui Chen, Xiaochun Huang, Cuilian Wen, Baisheng Sa, Zhimei Sun

“…However, many conventional ML algorithms operate as “black‐boxes”, lacking transparency in revealing explicit relationships between material features and target properties. …”
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The role of advanced machine learning in COVID-19 medical imaging: A technical review by Abdul Muiz Fayyaz, Said Jadid Abdulkadir, Shahab Ul Hassan, Safwan Mahmood Al-Selwi, Ebrahim Hamid Sumiea, Lareib Fatima Talib

“…It focuses on approaches such as Deep Learning (DL) algorithms and Transfer Learning, which have demonstrated significant potential in developing automated, accurate COVID-19 detection systems. …”
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Experimental Validation of a Modular Skid for Hydrogen Production in a Hybrid Microgrid by Gustavo Teodoro Bustamante, Jamil Haddad, Bruno Pinto Braga Guimaraes, Ronny Francis Ribeiro Junior, Frederico de Oliveira Assuncao, Erik Leandro Bonaldi, Luiz Eduardo Borges-da-Silva, Fabio Monteiro Steiner, Jaime Jose de Oliveira Junior, Claudio Inacio de Almeida Costa

“…Future work will address large-scale validation and performance optimization, including advanced energy management algorithms to ensure economic viability and sustainability in diverse industrial contexts.…”
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SpectralEarth: Training Hyperspectral Foundation Models at Scale by Nassim Ait Ali Braham, Conrad M. Albrecht, Julien Mairal, Jocelyn Chanussot, Yi Wang, Xiao Xiang Zhu

“…Experimental results support the versatility of our models and their generalizability across different tasks and sensors. We also highlight computational efficiency during model fine-tuning.…”
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Augmenting brain-computer interfaces with ART: An artifact removal transformer for reconstructing multichannel EEG signals by Chun-Hsiang Chuang, Kong-Yi Chang, Chih-Sheng Huang, Anne-Mei Bessas

“…Tackling this problem demands advanced algorithms, extensive noisy-clean training data, and thorough evaluation strategies. …”
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Position-Aware Graph Neural Network for Few-Shot SAR Target Classification by Jia Zheng, Ming Li, Peng Zhang, Yan Wu, Hongmeng Chen

“…In addition, the position and deformation variations of SAR targets can also affect the feature extraction capabilities of CNN. …”
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AI-Driven Advancements in Orthodontics for Precision and Patient Outcomes by David B. Olawade, Navami Leena, Eghosasere Egbon, Jeniya Rai, Aysha P. E. K. Mohammed, Bankole I. Oladapo, Stergios Boussios

“…While AI offers tremendous potential, challenges remain in areas such as data privacy, algorithmic bias, and the cost of adopting AI technologies. …”
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Comprehensive Review of Intrusion Detection Techniques: ML and DL in Different Networks by Imane Rakine, Aziz Oukaira, Kamal El Guemmat, Issam Atouf, Sara Ouahabi, Mohamed Talea, Tarik Bouragba

“…The strengths and limitations of ML and DL algorithms, which are frequently used for intrusion detection, are highlighted. …”
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Fatigue failure mechanisms and life prediction of additive manufactured metallic lattices: a comprehensive review by Hao Xin, Dingcheng Tang, Linwei Dang, Lei Gao, Zhenyu Yang, Bin Wu, Xiaofan He, Zhixin Zhan

“…It reviews common manufacturing methods and post-processing techniques, with particular emphasis on the unique process-induced defects found in lattice structures. The study also delves into the fatigue behaviours influenced by specific configurations and loading conditions, categorises the factors impacting fatigue failure in lattice materials, and presents a comprehensive review of fatigue life prediction methods, derived from an enhanced understanding of the fatigue process and the development of progressive fatigue failure algorithms. …”
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Variational formulation of active nematic fluids: theory and simulation by W Mirza, A Torres-Sánchez, G Vilanova, Marino Arroyo

“…We show that the variational principle enables a direct and transparent derivation not only of the governing equations, but also of the finite element numerical scheme. We exercise this model in two representative examples of active nemato-hydrodynamics relevant to the actin cytoskeleton during wound healing and to the dynamics of confined colonies of elongated cells.…”
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Synthesis and characterization of machine learning designed TADF molecules by Weimei Shi, Yan Li, Ziying Zhang, Zheng Tan, Shiqing Yang

“…This interdisciplinary approach not only accelerates the pace of TADF molecule development but also provides a scalable framework for future material innovation especially in the OLED research field.…”
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AI Dermatochroma Analytica (AIDA): Smart Technology for Robust Skin Color Classification and Segmentation by Abderrachid Hamrani, Daniela Leizaola, Nikhil Kumar Reddy Vedere, Robert S. Kirsner, Kacie Kaile, Alexander Lee Trinidad, Anuradha Godavarty

“…AIDA demonstrated superior performance, achieving a 97% accuracy rate compared to 87% for a supervised convolutional neural network (CNN). The system also segments skin images into clusters based on color similarity, providing detailed spatial mapping aligned with dermatological standards. …”
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Deep learning in next-generation vaccine development for infectious diseases by Manojit Bhattacharya, Yi-Hao Lo, Srijan Chatterjee, Arpita Das, Zhi-Hong Wen, Chiranjib Chakraborty

“…Similarly, the article discusses different tools and technologies, from epitope mapping and vaccine construct development to characterization. Again, it also highlighted recent paradigm shifts, DL-based strategies in vaccine development, and different DL-based tools used for epitope mapping and vaccine construct development. …”
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Using triaxial accelerometry to detect hunts and kills by African wild dogs by James Redcliffe, Scott Creel, Scott Creel, Ben Goodheart, Ben Goodheart, Johnathan Reyes de Merkle, Johnathan Reyes de Merkle, Stephani S. Matsushima, Michelo Mungolo, Ruth Kabwe, Emmanuel Kaseketi, Will Donald, Adrian Kaluka, Clive Chifunte, Matthew S. Becker, Matthew S. Becker, Rory Wilson

“…Here, we used this method and then iteratively improved algorithms by testing them on observed hunts and kills of collared packs. …”
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Artificial intelligence in prostate cancer by Wei Li, Ruoyu Hu, Quan Zhang, Zhangsheng Yu, Longxin Deng, Xinhao Zhu, Yujia Xia, Zijian Song, Alessia Cimadamore, Fei Chen, Antonio Lopez-Beltran, Rodolfo Montironi, Liang Cheng, Rui Chen, Yuanyuan Ji

“…The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. …”
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Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare by Jeremy Y. Ng, Holger Cramer, Myeong Soo Lee, David Moher

“…This integration of TCIM and AI introduces exciting opportunities but also noteworthy challenges. AI may augment TCIM by assisting in early disease detection, providing personalized treatment plans, predicting health trends, and enhancing patient engagement. …”
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Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes by ZHANG Zihang, XING Bo, MA Zhongqing, HU Yanjun, ZHANG Zhixiao, YUAN Shizhen, LU Rufei, CHEN Yingquan, WANG Shurong*

“…This allowed for explaining the relationship between feedstock properties and HHV. It also enabled explaining the connection between product distribution and pyrolysis characteristics. …”
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