The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1) by M. Buehner, J.-F. Caron, E. Lapalme, A. Caya, P. Du, Y. Rochon, S. Skachko, M. Bani Shahabadi, S. Heilliette, M. Deshaies-Jacques, W. Chang, M. Sitwell

“…The modular software design also allows the code that implements high-level components (e.g. observation operators, error covariance matrices, state vectors) to easily be used in many different ways depending on the application, such as for both variational and ensemble DA algorithms, for estimating the observation impact on short-term forecasts, and for performing various observation pre-processing procedures. …”
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Prospects of artificial intelligence for the sustainability of sugarcane production in the modern era of climate change: An overview of related global findings by Rajan Bhatt, Akbar Hossain, Debjyoti Majumder, Mandapelli Sharath Chandra, Rajiv Ghimire, Muhammad Faisal Shahzad, Krishan K. Verma, Amarinder Singh Riar, Vishnu D. Rajput, Mauro Wagner Oliveira, Adel Nisi, Riyadh S. Almalki, Viliam Bárek, Marian Brestic, Sagar Maitra

“…Artificial intelligence (AI) tools, such as machine learning algorithms, can optimize irrigation, increase yields, save water, and properly estimate sugarcane production. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…Human-computer interaction can also be revolutionized, enabling smoother and more natural interactions with emerging technologies. …”
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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…In general, the use of blockchain can affect the following: Risk: Blockchain minimizes the possibility of changing and falsifying information by using strong encryption and security algorithms. Also, by using distributed technology, the reliability of data access and visibility increases. …”
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Construction and interpretation of tobacco leaf position discrimination model based on interpretable machine learning by Ranran Kou, Cong Wang, Jinxia Liu, Ran Wan, Zhe Jin, Le Zhao, Youjie Liu, Junwei Guo, Feng Li, Hongbo Wang, Song Yang, Cong Nie

“…Chemical composition data combined with algorithmic models can also be used to discriminate tobacco leaf positions. …”
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Advanced Estimation of Winter Wheat Leaf’s Relative Chlorophyll Content Across Growth Stages Using Satellite-Derived Texture Indices in a Region with Various Sowing Dates by Jingyun Chen, Quan Yin, Jianjun Wang, Weilong Li, Zhi Ding, Pei Sun Loh, Guisheng Zhou, Zhongyang Huo

“…Following a two-step variable selection method, Random Forest (RF)-LassoCV, five machine learning algorithms were applied to develop estimation models. …”
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A novel bone metastasis-related gene signature for predicting prognosis, anti-androgen resistance, and drug choice in prostate cancer by Yu Luo, Xiaoqi Deng, Chengcheng Wei, Zhangcheng Liu, Liangdong Song, Kun Han, Yunfan Li, Jindong Zhang, Shuai Su, Delin Wang

“…The immune landscape heterogeneity of subgroups was analyzed using CIBERSORT, ESTIMATE, and xCell algorithms. Drug sensitivity and molecular docking analysis were performed to identify drugs associated with BMRPS. …”
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OpenPheno: an open-access, user-friendly, and smartphone-based software platform for instant plant phenotyping by Tianqi Hu, Peng Shen, Yongshuai Zhang, Jiafei Zhang, Xin Li, Chuanzhen Xia, Ping Liu, Hao Lu, Tingting Wu, Zhiguo Han

“…In particular, OpenPheno allows developers to contribute new algorithmic tools, further expanding its capabilities to continuously facilitate the plant phenotyping community. …”
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Earth Observation Data to Support Environmental Justice: Linking Non‐Permitted Poultry Operations to Social Vulnerability Indices by Mirela G. Tulbure, Júlio Caineta, Brooke Cox, Stephen V. Stehman, Ayse Ercumen, Rebecca Witter, Ryan Emanuel, Dana E. Powell, Kemp Burdette, Sherri White‐Williamson, Shea Tuberty

“…Notably, one‐third of NC's census tracts with high poultry CAFO density also have high SVI, primarily in rural eastern regions. …”
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Design and Operation Principles of a Wave-Controlled Reconfigurable Intelligent Surface by Gal Ben-Itzhak, Miguel Saavedra-Melo, Benjamin Bradshaw, Ender Ayanoglu, Filippo Capolino, A. Lee Swindlehurst

“…The paper provides five algorithms, two for the case of the envelope detector, one for the sample-and-hold circuit, one for pursuing the global minimum for both circuits, and one for simultaneous beam and null steering. …”
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Innovative Tailored Semantic Embedding and Machine Learning for Precise Prediction of Drug-Drug Interaction Seriousness by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Hisham Allahem, Bader Aldughayfiq, Meshrif Alruily, Alshaimaa A. Tantawy, Mohamed Ezz

“…This approach employs not only the names of the drugs but also the indications for the drugs and the active substances, forming a highly semantic network capable of capturing multiple relations between drugs. …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…It outlines the evolution of computational chemistry and the transformative role of AI in interpreting complex molecular data, automating feature extraction, and improving decision-making across the drug development pipeline. Core AI algorithms support vector machines, random forests, graph neural networks, and transformers are examined for their applications in molecular representation, virtual screening, and ADMET property prediction. …”
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Assessment and Modeling of Green Roof System Hydrological Effectiveness in Runoff Control: A Case Study in Dublin by Mehdi Gholamnia, Payam Sajadi, Salman Khan, Srikanta Sannigrahi, Saman Ghaffarian, Himan Shahabi, Francesco Pilla

“…Random Forest Regression (RF) also showed robust results, with R2 values ranging from 0.76 to 0.84 and RMSE values ranging from 0.31 to 1.29 millimeters. …”
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Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool by Juan Francisco Morales, Marian Klose, Yannick Hoffert, Jagdeep T. Podichetty, Jackson Burton, Stephan Schmidt, Klaus Romero, Inish O'Doherty, Frank Martin, Martha Campbell‐Thompson, Michael J. Haller, Mark A. Atkinson, Sarah Kim

“…Using this tool, power curves can also be generated through iterations. The web‐based tool is publicly available: https://app.cop.ufl.edu/t1d/. …”
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Vibration, current, torque, RPM dataset for multiple fault conditions in industrial-scale electric motors under randomized speed and load variationsMendeley DataMendeley DataMendel... by Wonho Jung, Junho Kim, Kangmin Jang, Sung-Hyun Yun, Daeguen Lim, Minje Jin, Yong-Hwa Park

“…Data were collected under randomized speed fluctuations (6 % and 16 %) using variable frequency drive. Data were also collected under variable load conditions, and different motor capacity. …”
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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

“…Given that lung cancer is a leading cause of cancer-related deaths globally and NSCLC accounts for the majority of lung cancer cases, understanding the relationship between TME and metabolic pathways in NSCLC is crucial for developing new treatment strategies.MethodsFinally, machine learning algorithms were employed to construct a risk signature with strong predictive power across multiple independent cohorts. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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Utilizing Artificial Intelligence (AI) for the optimal design of geothermal cogeneration systems in zero energy building by Ehsanolah Assareh, Mohammad Zoghi, Ali Zare, Hassan Bazazzadeh, Adnan Alboghobeysh, Saleh Mobayen, Nima Izadyar, Siamak Hoseinzadeh

“…As energy optimization becomes increasingly vital, this research not only focuses on enhancing the building's energy system but also evaluates the optimal directional placement of the structure. …”
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Causes of embryo implantation failure: A systematic review and metaanalysis of procedures to increase embryo implantation potential by Francesco M. Bulletti, Romualdo Sciorio, Alessandro Conforti, Roberto De Luca, Carlo Bulletti, Antonio Palagiano, Marco Berrettini, Giulia Scaravelli, Roger A. Pierson

“…Subsequent studies ought to concentrate on modulating endometrial responses immunologically and developing algorithms to improve the precision of predicting implantation success; as well as the timing of endometrial receptivity and the occurrence of dormant embryo phenomena also warrants further investigation.…”
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The Impact of the Natural Grass-Growing Model on the Development of Korla Fragrant Pear Fruit, as Well as Its Influence on Post-Harvest Sugar Metabolism and the Expression of Key E... by Mingyang Yu, Lanfei Wang, Yan Chen, Weifan Fan, Hao Wang, Kailu Guo, Shutian Tao, Xin Gong, Jianping Bao

“…A classification model was constructed using machine learning algorithms (RF, KNN, SVM), and particle swarm optimization (PSO) was employed to identify key factors. …”
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