Prediction and Mapping of Soil Total Nitrogen Using GF-5 Image Based on Machine Learning Optimization Modeling by LIU Liqi, WEI Guangyuan, ZHOU Ping

“…Among these samples, 140 were randomly selected as the modeling sample set for calibration, and the remaining 31 samples were used as the test sample set. Three machine learning algorithms were introduced: Partial least squares regression (PLSR), backpropagation neural network (BPNN), and support vector machine (SVM) driven by a polynomial kernel function (Poly). …”
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Artificial Intelligence as Assessment Tool in Occupational Therapy: A Scoping Review by Christos Kokkotis, Ioannis Kansizoglou, Theodoros Stampoulis, Erasmia Giannakou, Panagiotis Siaperas, Stavros Kallidis, Maria Koutra, Christina Koutra, Anastasia Beneka, Evangelos Bebetsos

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Competence Profile of the Teacher from the Principal'S Perspective by Paul Lungeanu, Daniela Ionescu

“…To meet contemporary educational challenges, teachers are increasingly opting for lifelong learning. Over the past 30 years—and particularly in the most recent decade—the concept of lifelong learning has been strategically and functionally enriched in educational debates. …”
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Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges by Jielu Yan, Zhengli Chen, Jianxiu Cai, Weizhi Xian, Xuekai Wei, Yi Qin, Yifan Li

“…Recent advances in artificial intelligence—especially machine learning (ML), deep learning (DL), and pattern recognition—offer game-changing opportunities to accelerate AMP design and validation. …”
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SecFedMDM-1: A Federated Learning-Based Malware Detection Model for Interconnected Cloud Infrastructures by Daniella Mughole Kalimumbalo, Joke A. Badejo, Kennedy O. Okokpujie, Emmanuel Adetiba, Molo Mbasa Joaquim, Nzanzu Vingi Patrick, Gabriel Oyeyemi, Claude Takenga

“…This study established a federated learning-based malware detection model for interconnected cloud infrastructures. …”
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Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks? by Jowaria Khan, Rana Elfakharany, Hiba Saleem, Mahira Pathan, Emaan Shahzad, Salam Dhou, Fadi Aloul

“…Smart cities rely on these systems seamlessly functioning with one another, and any successful cyberattack could have devastating effects, including large-scale data theft. …”
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Efectividad de una metodología para contribuir a la habilidad de solucionar problemas en la asignatura Embriología Médica by Elena Vicenta Hernández Navarro, Jorge Luis Losada Guerra, Lizette Elena Leiva Suero, Marcelo Mantilla-Falcón

“…Conclusion: The methodology application was effective about the favorable transformation of dimensions and indicators of problem-solving skill, expressed in higher levels of mastery in functional invariants execution of the skill by the students.…”
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Muscle Fat and Volume Differences in People With Hip‐Related Pain Compared With Controls: A Machine Learning Approach by Chris Stewart, Evert O. Wesselink, Zuzana Perraton, Kenneth A. Weber II, Matthew G. King, Joanne L. Kemp, Benjamin F. Mentiplay, Kay M. Crossley, James M. Elliott, Joshua J. Heerey, Mark J. Scholes, Peter R. Lawrenson, Chris Calabrese, Adam I. Semciw

“…While MRI use for assessing hip muscle morphology is increasing, with automated deep‐learning techniques showing promise, studies assessing their accuracy are limited. …”
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Experimental method to predict avalanches based on neural networks by V. V. Zhdanov

“…Cherepanov was used to learn the neural networks. The trained neural network demonstrated 98% accuracy of the classification. …”
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Mechanisms mediating muscle metaboreflex control of cardiac output during exercise: Impaired regulation in heart failure by Donal S. O'Leary, Joseph Mannozzi

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Screening cognitive impairment in patients with atrial fibrillation: A deep learning model based on retinal fundus photographs by Zhen Wang, MD, Mingxiao Li, MD, Peng Xia, BS, Chao Jiang, MD, Ting Shen, MD, Jiaming Ma, MD, Yu Bai, MD, Suhui Zhang, MD, Yiwei Lai, MD, Sitong Li, MS, Hui Xu, MD, Yang Xu, MD, Tong Ma, MS, Lie Ju, PhD, Liu He, PhD, Li Dong, MD, Caihua Sang, MD, Deyong Long, MD, Yuzhong Chen, PhD, Xin Du, MD, Zongyuan Ge, PhD, Jianzeng Dong, MD, Wen-Bin Wei, MD, Changsheng Ma, MD

“…Objective: Our study aimed to develop deep learning models based on fundus photographs for easy screening of CI in AF patients. …”
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Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach by Ajit Kumar Rout, P.K. Dash, Rajashree Dash, Ranjeeta Bisoi

“…Further several evolutionary learning methods like the Particle Swarm Optimization (PSO) and modified version of its new variant (HMRPSO), and the Differential Evolution (DE) are adopted here to find the optimal weights for the recurrent computationally efficient functional link neural network (RCEFLANN) using a combination of linear and hyperbolic tangent basis functions. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

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Unsupervised machine learning revealed a correlation between low-dose statins and favorable outcomes in ICH patients by Chaohua Cui, Haoye Guan, Tonghua Long, Yuru Liang

“…Additionally, low-dose statins were linked to better functional outcomes (OR = 0.594, p < 0.001) but showed no significant association with hematoma expansion (OR = 1.056, p = 0.735).ConclusionUnsupervised machine learning revealed a correlation between low-dose statins and patient prognosis. …”
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Machine learning-driven insights into self-healing silicon-based anodes for high-performance lithium-ion batteries by Mahta Moazzenzadeh, Mahmoud Samadpour

“…Overcoming practical experimentation challenges, this study delves self-healing polymers through machine learning methods as a more practical approach. The role of structural features and functional groups within these polymers in maintaining anode integrity and prolonging battery capacity across multiple charge cycles were explored by utilization of random forest, ridge algorithms, support vector machines, and neural networks. …”
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Innovative Technologies for Enhanced Physical and Mathematical Learning in Central Europe: Contemporary Issues and Trends of Fractal Structuring of Information by Mar’yan Mykhaylo, Nataliya Yurkovych, Vladimir Seben, Nikola Tesľuková

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Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province by Li Luo, Li Luo, Bangwei Chen, Bangwei Chen, Shengyin Zeng, Shengyin Zeng, Yaxin Li, Yaxin Li, Xiaolin Chen, Xiaolin Chen, Jianguo Zhang, Xiangjie Guo, Shujin Li, Lei Ruan, Shida Zhu, Cairong Gao, Cuntai Zhang, Tao Li

“…To obtain the optimal model that can distinguish geographically close populations, three machine learning (ML) algorithms based on microbiota or functions were employed.ResultsSignificant differences in microbial α diversity and β diversity were observed. …”
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The Influence of lecturers’ verbal and non-verbal immediacy behaviour on perceived affective and cognitive learning in a multicultural context. by Lydie Terblanche, Terry Terblanche

“… The intention of the present study was to determine whether (1) the immediacy behaviour of lecturers whose home language is Afrikaans or English contributes positively to the affective and cognitive learning of learners whose home language is Afrikaans, English or one of the African languages; and (2) whether the form of immediacy behaviour displayed by English or Afrikaans lecturers functions differently for learners whose home language is one of the African languages in relation to those whose home language is Afrikaans or English. …”
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Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling by Jin Wu, Yiyun Wang, Fang Chen, Xueqi Yin, Yun He

“…Using structural equation modeling (SEM) on data collected from 118 undergraduate students, this study validates a chained mediation model in which learner engagement mediates the relationship between satisfaction with platform functionalities and perceived learning outcomes. The results show that: (1) satisfaction with key functionalities, such as dynamic content adaptation and real-time feedback, significantly enhances learner engagement; (2) learner engagement strongly predicts perceived improvements in reading skills; and (3) the platform facilitates reading comprehension through a dual intervention mechanism integrating bottom-up decoding and top-down schema activation strategies. …”
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Efficient solving of Schrödinger equation using deep convolutional neural network model with an attention mechanism and transfer learning by Ziyi Zhao, Shishun Zhao, Mingjun Zhou, Yujun Yang

“…Furthermore, we proposed a transfer learning strategy that uses the pre-trained model as a ‘large model’ and fine-tunes it using three specific potential functions: simple harmonic oscillator (ho), infinite well (iw), and double inverted negative Gaussian (ng). …”
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