APBIO: bioactive profiling of air pollutants through inferred bioactivity signatures and prediction of novel target interactions by Eva Viesi, Ugo Perricone, Patrick Aloy, Rosalba Giugno

“…Moreover, the interactivity between biological entities can be represented through combined feature vectors that can be given as input to a machine learning (ML) model to capture the underlying interaction. …”
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Monitoring Yield and Quality of Forages and Grassland in the View of Precision Agriculture Applications—A Review by Abid Ali, Hans-Peter Kaul

“…At a larger scale, we discuss coupling of remote sensing with weather data (synergistic grassland yield modelling), Sentinel-2 data with radiative transfer modelling (RTM), Sentinel-1 backscatter, and Catboost–machine learning methods for digital mapping in terms of precision harvesting and site-specific farming decisions. …”
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Data Mining of Infertility and Factors Influencing Its Development: A Finding From a Prospective Cohort Study of RaNCD in Iran by Hosna Heydarian, Masoumeh Abbasi, Farid Najafi, Mitra Darbandi

“…Methods In this study, we examined the impact of lifestyle factors on infertility using machine learning and data mining techniques, specifically Association Rules. …”
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GENOME POLITICS: STRATEGY AND TACTICS by Jonas Rubikas

“…Human mental and consciousness activity, brain functions obtained by learning mask the dependence of these activities on the genome. …”
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Chronic nitrogen legacy in the aquifers of China by Xin Liu, Fu-Jun Yue, Li Li, Feng Zhou, Hang Wen, Zhifeng Yan, Lichun Wang, Wei Wen Wong, Cong-Qiang Liu, Si-Liang Li

“…Here we used machine learning and decision tree-heatmap analysis by compiling nitrate concentrations and isotope data from 4047 groundwater sites across China to understand their dynamics and drivers across gradients of geographical, climate, and human factors. …”
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Practice Variability Combined with Task-Oriented Electromyographic Biofeedback Enhances Strength and Balance in People with Chronic Stroke by Peih-Ling Tsaih, Ming-Jang Chiu, Jer-Junn Luh, Yea-Ru Yang, Jiu-Jenq Lin, Ming-Hsia Hu

“…Our findings highlight the importance of task-oriented and motor learning principles while using the EMGBFB as an adjunct therapy in stroke rehabilitation. …”
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The Impact of Strategic Quality Orientation and Absorptive Capacity on Sustainable Business Growth: The Mediating Role of Innovation by Fatemeh Ashourijirkol, Mehrdad Hosseini Shakib, Abbas khamseh

“…While growing a business and exploring exploratory innovation is not easy and requires a lot of resources for organizational learning, harnessing existing capabilities may not lead to sustainable competitive advantage.Originality/Value: The concept of strategic quality orientation is derived from the general principles of total quality management and significantly impacts sustainable business performance. …”
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Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS) by Kara M. Joseph, Anna K. Boatman, James N. Dodds, Kaylie I. Kirkwood-Donelson, Jack P. Ryan, Jian Zhang, Paul A. Thiessen, Evan E. Bolton, Alan Valdiviezo, Yelena Sapozhnikova, Ivan Rusyn, Emma L. Schymanski, Erin S. Baker

“…This information will provide the scientific community with essential characteristics to expand analytical assessments of PFAS and augment machine learning training sets for discovering new PFAS.…”
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Neural Network-Based Parameter Estimation and Compensation Control for Time-Delay Servo System of Aeroengine by Hongyi Chen, Qiuhong Li, Zhifeng Ye, Shuwei Pang

“…The estimated delay was embedded into an online sequential extreme learning machine, and a nonlinear model predictive controller was designed to obtain an optimal control sequence. …”
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Mpox in sports: A comprehensive framework for anticipatory planning and risk mitigation in football based on lessons from COVID-19 by Karim Chamari, Helmi Ben Saad, Wissem Dhahbi, Jad Washif, Abdelfatteh El Omri, Piotr Zmijewski, Ismail Dergaa

“…We propose innovative risk assessment methods using global positioning system tracking and machine learning for contact analysis, alongside tailored testing and hygiene protocols. …”
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ZleepNet: A Deep Convolutional Neural Network Model for Predicting Sleep Apnea Using SpO2 Signal by Hnin Thiri Chaw, Thossaporn Kamolphiwong, Sinchai Kamolphiwong, Krongthong Tawaranurak, Rattachai Wongtanawijit

“…We conducted experiments to evaluate the performance of the proposed CNN using real patient data and compared them with traditional machine learning methods such as least discriminant analysis (LDA) and support vector machine (SVM), baggy representation tree, and artificial neural network (ANN) on publicly available sleep datasets using the same parameter setting. …”
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Electromagnetic design, sensitivity analysis, optimization and Multiphysics capability of rare-earth-free synchronous reluctance motor for electric trike vehicle by V Rajini, VS Nagarajan, Karunya Harikrishnan, Mohan Lal Kolhe

“…Furthermore, an Extreme Learning Machine (ELM)-based interpolation technique is employed for estimating the performance parameters during each step of the optimization routine. …”
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Modeling and designing enhancers by introducing and harnessing transcription factor binding units by Jiaqi Li, Pengcheng Zhang, Xi Xi, Liyang Liu, Lei Wei, Xiaowo Wang

“…Here we propose the concept of transcription factor binding unit (TFBU) to modularly model enhancers by quantifying the impact of context sequences surrounding TFBSs using deep learning models. Based on this concept, we develop DeepTFBU, a comprehensive toolkit for enhancer design. …”
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Causation Analysis of Hazardous Material Road Transportation Accidents by Bayesian Network Using Genie by Xiaoli Ma, Yingying Xing, Jian Lu

“…The Bayesian network structure was established by experts’ knowledge using Dempster-Shafer evidence theory. Parameter learning was conducted by the Expectation-Maximization (EM) algorithm in Genie 2.0. …”
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Fecal occult blood affects intestinal microbial community structure in colorectal cancer by Wu Guodong, Wu Yinhang, Wu Xinyue, Shen Hong, Chu Jian, Qu Zhanbo, Han Shuwen

“…Characteristic gut bacteria were screened, and various machine learning algorithms were applied to construct CRC risk prediction models. …”
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Comparison of three-dimensional digital exoscope to standard operating microscope in minimally-invasive lumbar decompression: A cohort study in a community setting by Daniel E. Fulkerson, Evan Medich, Dale F. Szpisjak, Daniel H. Fulkerson

“…Surgical time for exoscope groups showed a non-significant downward trend of 9–14 % in the later cases of the study period compared to the earlier cases, suggesting the presence of a learning curve. Conclusion: The exoscope is a viable alternative to the surgical microscope for MISS in a community-based neurosurgical practice.…”
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The role of multifocal visual evoked potential in detection of minimal hepatic encephalopathy in patients with compensated liver cirrhosis by Reem M. Sabry, Osama Hamad, Hossam Eldin Mohamed Khalil, Sahar Ibrahim Mohammed, Ragaey Ahmad Eid, Hanan Hosny

“…The aim of this study was to detect minimal hepatic encephalopathy among cirrhotic patients using the mfVEP in comparison to the validated psychometric hepatic encephalopathy score (PHES), paired associative learning (PAL) and the Benton visual retention test (BVRT). …”
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Benchmarking protein language models for protein crystallization by Raghvendra Mall, Rahul Kaushik, Zachary A. Martinez, Matt W. Thomson, Filippo Castiglione

“…Several in silico deep learning methods have been developed to overcome the high attrition rate, cost of experiments and extensive trial-and-error settings, for predicting the crystallization propensities of proteins based on their sequences. …”
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When Remote Sensing Meets Foundation Model: A Survey and Beyond by Chunlei Huo, Keming Chen, Shuaihao Zhang, Zeyu Wang, Heyu Yan, Jing Shen, Yuyang Hong, Geqi Qi, Hongmei Fang, Zihan Wang

“…Most deep-learning-based vision tasks rely heavily on crowd-labeled data, and a deep neural network (DNN) is usually impacted by the laborious and time-consuming labeling paradigm. …”
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Transforming precision medicine: The potential of the clinical artificial intelligent single‐cell framework by Christian Baumgartner, Dagmar Brislinger

“…The article explores development strategies such as data expansion, machine learning advancements, and interpretability improvements. …”
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