Identification and Characterization of Genes Associated with Intestinal Ischemia-Reperfusion Injury and Oxidative Stress: A Bioinformatics and Experimental Approach Integrating Hig... by Xie Y, Yang M, Huang J, Jiang Z

“…The least absolute shrinkage and selection operator, as well as the support vector machine with random forest algorithm, were utilized for machine learning. …”
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Development of a Ferritin-Based Nano-Allergen and Its Immunological Effects in vitro and in vivo by Zhou D, Ren Y, Zhou Y, Liao Y, Cheng Q, Chen J, Yuan C, Zeng D, Cui Y

“…Dongmei Zhou,1,* Yaning Ren,1,* Ying Zhou,2 Yuanfen Liao,1 Qi Cheng,1 Jinni Chen,3 Cunyin Yuan,1 Dan Zeng,4 Yubao Cui1 1Clinical Research Center, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi, 214023, People’s Republic of China; 2Department of Pediatrics Laboratory, The Affiliated Children´s Hospital of Jiangnan University, Wuxi, 214023, People’s Republic of China; 3Department of Respiratory, Hainan Women and Children’s Medical Center, Affiliated Pediatrics Clinical College of Hainan Medical University, Haikou, 570100, People’s Republic of China; 4Department of Allergy, Chongqing General Hospital, Chongqing University, Chongqing, 401147, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yubao Cui; Dan Zeng, Email ybcui1975@hotmail.com; zengdan@cqu.edu.cnIntroduction: We aimed to develop recombinant allergens on the nanoscale by using self-assembly property of ferritin and to investigate their immune response and protective effect.Methods: The cDNA encoding Ftn-Blo t 2 was synthesized and cloned into pET-21a (+) vector, then expressed in E. coli BL21 (DE3). …”
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Identification of Ion-kinetic Instabilities in Hybrid-PIC Simulations of Solar Wind Plasma with Machine Learning by Viacheslav M. Sadykov, Leon Ofman, Scott A. Boardsen, Yogesh, Parisa Mostafavi, Lan K. Jian, Kristopher Klein, Mihailo Martinović

“…Analysis of ion-kinetic instabilities in solar wind plasmas is crucial for understanding energetics and dynamics throughout the heliosphere, as evident from spacecraft observations of complex ion velocity distribution functions (VDFs) and ubiquitous ion-scale kinetic waves. In this work, we explore machine learning (ML) and deep learning (DL) classification models to identify unstable cases of ion VDFs driving kinetic waves. …”
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Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach by Zhengyuan Su, Huadong Jiang, Ying Yang, Xiangqing Hou, Yanli Su, Li Yang

“…ResultsThe development of machine learning models utilizing HSF acoustic features has been demonstrated to enhance recognition performance compared to models based solely on basic acoustic features. …”
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Concentrations of DDT metabolites in different food items and public health risk in Africa regions: systematic review and metal analysis by Dechasa Adare Mengistu, Abraham Geremew, Roba Argaw Tessema, Tara Wolfing

“…Meta-analysis data visualized using a forest plot. A random-effects model was applied when heterogeneity existed in overall mean concentration of DDT metabolites. …”
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Development of interest in training by creation emotional and comfortable educational environment by Olga M. Shentsova

“…Pedagogical approach to a solution consists of the following: to present in pedagogical process a possibility of interesting aspects of the educational activity; to excite and constantly maintain the students’ state of active interest by educational processes; to purposefully form and develop interest as the valuable property of the personality in training, promoting her informative activity.Interest in training – “is a form of manifestation of need of the personality for cognitive activity, owing to her emotional appeal and the vital importance, through active aspiration to knowledge acquisition, abilities, possession where in organic unity intellectual, emotional and strong-willed processes interact”.Also the personal and activity training is considered, including the personal focused and individual, informative and synergetic approaches, the levels of development of interest in training are marked out; tools for the emotional and comfortable educational environment, which influences efficiency of development of students’ interest in training at universities. The structural model of the educational environment has been developed, that includes spatial and subject, social, actionable, information and technological, substantial and spiritual components, which are considered by the authors in detail.When determining the educational environment we have used the method of the vector modeling, developed by V.Yasvin, which is based on the system of coordinates, consisting of an axis of FD “freedom-dependence” and an axis of AP “activity-passivity”. …”
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Machine Learning for Enhanced COPD Diagnosis: A Comparative Analysis of Classification Algorithms by Walaa H. Elashmawi, Adel Djellal, Alaa Sheta, Salim Surani, Sultan Aljahdali

“…<b>Conclusions</b>: The results obtained with the utilized ML models align with previous work in the field, with accuracies ranging from 67.81% to 82.06% in training and from 66.73% to 71.46% in testing.…”
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Detecting Malicious .NET Executables Using Extracted Methods Names by Hamdan Thabit, Rami Ahmad, Ahmad Abdullah, Abedallah Zaid Abualkishik, Ali A. Alwan

“…The performance of six machine learning models—XGBoost, random forest, K-nearest neighbor (KNN), support vector machine (SVM), logistic regression, and naïve Bayes—was compared. …”
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Parabolic Weighting Mechanism in Information Retrieval: A Mathematical Analogy to Lenz&#x2019;s Law by Krishnan Batri, S. Lakshmi, R. Sowrirajan

“…Experiments conducted on benchmark datasets, including BBC News and 20 Newsgroups, demonstrate that the parabolic weighting mechanism outperforms traditional techniques, yielding measurable improvements in accuracy with classification models such as the support vector classifier (0.44 percent increase) and logistic regression (0.30 percent increase). …”
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An automated approach to identify sarcasm in low-resource language. by Shumaila Khan, Iqbal Qasim, Wahab Khan, Aurangzeb Khan, Javed Ali Khan, Ayman Qahmash, Yazeed Yasin Ghadi

“…To address this challenge, we employ various baseline ML classifiers to evaluate their effectiveness in detecting sarcasm in low-resource languages. The primary models evaluated in this study are support vector machine (SVM), decision tree (DT), K-Nearest Neighbor Classifier (K-NN), linear regression (LR), random forest (RF), Naïve Bayes (NB), and XGBoost. …”
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Predicting student next-term performance in degree programs using AI-based approach: a case study from Ghana by John-Bosco Diekuu, M. S. Mekala, Ulric Sena Abonie, John Isaacs, Eyad Elyan

“…Temporal dynamics, such as semester-to-semester variations and changes in students’ academic achievements, behaviors and engagement over time, can be critical factors in designing predictive models. It can be said that most existing work focuses on one-time forecasting of student performance in specific semesters, subjects or short online courses without considering temporal elements. …”
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Inhibition of SOD1 trimerization is a novel drug target for ALS disease by Tae-Gyun Woo, Jin Han, Yuju Kim, Young jun Hwang, Mua Lee, So-mi Kang, Soyoung Park, Yeongseon Ji, Yeon-Ho Chung, Songyoung Baek, Eunbyeol Shin, Minju-Kim, Hyewon Jang, Yun-Jeong Shin, Yonghoon Kwon, Bae-Hoon Kim, Bum-Joon Park

“…Indeed, SOD1 aggregation has been reported in ALS patients, but the mechanism of SOD1 aggregation remains unclear. Our previous work showed that inhibiting SOD1 aggregation with a hit compound (PRG-A-01) could reduce the SOD1-induced cytotoxicity and extend the lifespan of ALS mouse model (SOD1G93A−Tg). …”
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Dynamic interactions and disturbance responses of the water resource, eco-hydrological, grazing, and economic composite system for a grassland-type inland river basin by Ting Liu, Yixuan Wang, Tingxi Liu, Limin Duan, Jin Sun, Shaojie Chu, Bo Zhang, Guixin Zhang, Mingyu Ji, Yixuan Zhang

“…Based on the vector autoregressive model framework, the WEGE coupling model, along with its evaluation index system, was constructed to determine the internal interactions of the composite system. …”
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Enhancing Ground Penetrating Radar (GPR) Data Analysis Utilizing Machine Learning by Mohanad Shehab, Musab T.S. Al-Kaltakchi, Ammar Dukhan, Wai Lok Woo

“…Finally, various machine learning techniques are employed to classify the collected images using models like Decision Trees,agged trees, Naive Bayes, Artificial Neural Networks, Quadratic Discriminant Analysis, Support Vector Machines, and K-nearest neighbors. …”
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Prediabetes detection in unconstrained conditions using wearable sensors by Dimitra Tatli, Vasileios Papapanagiotou, Aris Liakos, Apostolos Tsapas, Anastasios Delopoulos

“…Features are aggregated per individual using bootstrap. Support Vector Machines are used to classify normoglycemic vs. prediabetic individuals. …”
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Feature-informed machine learning for detecting material deformation and failure in aluminum pipes under bending load using acoustic emission sensors by Xiaowei Zuo, Nicholas Satterlee, Chang-Whan Lee, In-Gyu Choi, Choon-Wook Park, John S. Kang

“…The results show that the average accuracy for the feature-based ML models is 79.8 %, with the Support Vector Machine achieving the highest accuracy of 83.5 %. …”
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SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study by Abrar Yaqoob, Navneet Kumar Verma, Mushtaq Ahmad Mir, Ghanshyam G. Tejani, Nashwa Hassan Babiker Eisa, Hind Mamoun Hussien Osman, Mohd Asif Shah

“…The mean accuracies ranged from 85.35 to 94.33%, highlighting a balance between feature reduction and classification accuracy. Future work will explore the integration of other nature-inspired algorithms and deep learning models to further enhance performance and clinical applicability.…”
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Exploring the utility of social-ecological and entomological risk factors for dengue infection as surveillance indicators in the dengue hyper-endemic city of Machala, Ecuador. by Catherine A Lippi, Anna M Stewart-Ibarra, Timothy P Endy, Mark Abbott, Cinthya Cueva, Froilán Heras, Mark Polhemus, Efraín Beltrán-Ayala, Sadie J Ryan

“…The management of mosquito-borne diseases is a challenge in southern coastal Ecuador, where dengue is hyper-endemic and co-circulates with other arboviral diseases. Prior work in the region has explored social-ecological factors, dengue case data, and entomological indices. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

“…<b>Conclusions</b>: The study concludes that NRO is a promising gene selection approach, particularly effective in certain datasets, and suggests that future work should explore hybrid models and feature reduction techniques to further enhance its accuracy and efficiency.…”
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Fault Classification in Power Transformers via Dissolved Gas Analysis and Machine Learning Algorithms: A Systematic Literature Review by Vuyani M. N. Dladla, Bonginkosi A. Thango

“…At the same time, limited effort is put into other key metrics such as precision, Mean Squared Error, and R-Squared, and also, current works surveyed do not explore regularization techniques for preventing overfitting and underfitting of the proposed models.…”
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