Do global health networks facilitate innovation, learning and sharing? A qualitative analysis of the Quality-of-Care Network in Bangladesh, Ethiopia, Malawi, and Uganda. by Kondwani Mwandira, Seblewengel Lemma, Albert Dube, Kohenour Akter, Asebe Amenu Tufa, Agnes Kyamulabi, Gloria Seruwagi, Catherine Nakidde, Kasonde Mwaba, Nehla Djellouli, Charles Makwenda, Tim Colbourn, Yusra Ribhi Shawar

“…Nevertheless, there was evidence that QCN improved their functionality. We provide evidence of how learning, sharing, and innovation among and within countries can be fostered for improving maternal and child health; and limitations. …”
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Machine learning based multi-stage intrusion detection system and feature selection ensemble security in cloud assisted vehicular ad hoc networks by C. Christy, A. Nirmala, A. Mary Odilya Teena, A. Isabella Amali

“…Regarding feature selection, MLIDS-RFA uses machine-learning approaches to enhance the detection process. …”
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Computational modelling and neural correlates of reinforcement learning following three-week escitalopram: a double-blind, placebo-controlled semi-randomised study by Christelle Langley, Graham K. Murray, Sophia Armand, Franziska Knolle, Rudolf N. Cardinal, Annette Johansen, Peter S. Jensen, Jianfeng Feng, Dea S. Stenbæk, Gitte M. Knudsen, Patrick M. Fisher, Barbara J. Sahakian

“…Consequently, we aimed to investigate the effect of a three-week administration of the SSRI, escitalopram, on a reinforcement learning paradigm during functional magnetic resonance imaging. …”
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SOME ISSUES OF TEACHING AND LEARNING OF CORPORATE GOVERNANCE IN LAW INSTITUTIONS AND UNIVERSITIES IN THE CONTEXT OF THE INTERNATIONAL MASTER’S DOUBLE DEGREE PROGRAM «EUROPEAN AND I... by Sergey Yu. Marochkin, Marina I. Shunevich

“…The research findings and results of the study can be used as for the development of both the level of students’ knowledge and expand the professional level of teachers’ skills, as well as to solve the problems of improvement of corporate management business entity of any organizational-legal form, in which the functions are separated by ownership and management.…”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

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Comprehensive bioinformatics analysis identifies metabolic and immune-related diagnostic biomarkers shared between diabetes and COPD using multi-omics and machine learning by Qianqian Liang, Yide Wang, Zheng Li, Zheng Li, Zheng Li, Zheng Li

“…By using weighted gene correlation network analysis (WGCNA), key gene modules for COPD and diabetes were identified, and various machine learning algorithms were employed to identify shared biomarkers. …”
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Deciphering mitochondrial dysfunction in keratoconus: Insights into ACSL4 from machine learning-based bulk and single-cell transcriptome analyses and experimental validation by Yuchen Cai, Tianyi Zhou, Xueyao Cai, Wenjun Shi, Hao Sun, Yao Fu

“…Based on transcriptomics datasets of KC, mitochondria-related differentially expressed genes (mDEGs) were identified and analyzed for potential functional pathways, protein-protein interaction (PPI), and gene regulatory networks. …”
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stGRL: spatial domain identification, denoising, and imputation algorithm for spatial transcriptome data based on multi-task graph contrastive representation learning by Xin Lu, Murong Zhou, Bo Gao, Fang Wang, Shuilin Jin, Qiaoming Liu, Guohua Wang

“…Additionally, it integrates graph contrastive representation learning to enhance the consistency of node embeddings, thereby improving clustering performance. …”
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Mapping Wetlands with High-Resolution Planet SuperDove Satellite Imagery: An Assessment of Machine Learning Models Across the Diverse Waterscapes of New Zealand by Md. Saiful Islam Khan, Maria C. Vega-Corredor, Matthew D. Wilson

“…(1) Background: Wetlands are ecologically significant ecosystems that support biodiversity and contribute to essential environmental functions such as water purification, carbon storage and flood regulation. …”
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A Hybridization of Machine Learning and NSGA-II for Multi-Objective Optimization of Surface Roughness and Cutting Force in ANSI 4340 Alloy Steel Turning by Anh-Tu Nguyen, Van-Hai Nguyen, Tien-Thinh Le, Nhu-Tung Nguyen

“…A hybridization of Machine Learning (ML) algorithms and a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is applied to find the Pareto solution. …”
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Modeling of concrete-filled PVC tube columns confined with CFRP strips under uniaxial eccentric compression: machine learning and finite element approaches by Yan Wang, Mohamed A. Elmeligy, Haytham F. Isleem, Asmaa Y. Hamed, Diyar N. Qader, Mohamed Sharaf, Pradeep Jangir, Arpita, Ghanshyam G. Tejani

“…Analytical models were developed to express the confined concrete strength and strain as functions of the constituent properties and dimensionless confinement parameters. …”
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High-throughput method for improving rice AGB estimation based on UAV multi-source remote sensing image feature fusion and ensemble learning by Jinpeng Li, Jinpeng Li, Jinxuan Li, Jinxuan Li, Dongxue Zhao, Dongxue Zhao, Qiang Cao, Qiang Cao, Fenghua Yu, Fenghua Yu, Fenghua Yu, Yingli Cao, Yingli Cao, Yingli Cao, Shuai Feng, Shuai Feng, Shuai Feng, Tongyu Xu, Tongyu Xu, Tongyu Xu

“…The relationships between AGB and the selected features were then analyzed using multiple fitting functions. Both single-type and multi-type features were used to develop individual and ensemble machine learning (ML) models for rice AGB estimation.ResultsThe findings indicate that: (i) Single-type features result in significant errors and low accuracy within the same sensor, but multi-feature fusion improves performance. …”
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Evaluation of the impact of ecological factors on the habitat suitability and bioactive components accumulation of the medicinal holoparasitic plant Cynomorium songaricum using mac... by Jiacheng Ji, Jiacheng Ji, Xinxin Wei, Xinxin Wei, Huan Guan, Huan Guan, Zikang Jin, Zikang Jin, Xin Yue, Zhuoran Jiang, Youla Su, Youla Su, Shuying Sun, Shuying Sun, Guilin Chen, Guilin Chen

“…BIO6 served as a key shared positive regulator for catechin and total phenolics, while functioning as a key negative regulator for ursolic acid. …”
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Identification of Potential Inhibitors Targeting Non-Structural Proteins NS3 and NS5 of Dengue Virus Using Docking and Deep Learning Approaches by Alomgir Hossain, Faria Tasnin Joti, Md. Shohag Hossain, Abdullah Al-Noman, Chomong Thowing, Mehjabin Mursona, Md. Robiul Islam, Md. Ekhtiar Rahman, Mohammad Nurul Matin, Md Azizul Haque

“…Non-structural (NS) proteins amongst serotypes show analogous functions. Among NS proteins, NS3 and NS5 are frequently used as targets for antiviral drugs due to their multifunctional roles. …”
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Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer by Zhenwei Wang, Zhihong Dai, Yuren Gao, Zhongxiang Zhao, Zhen Li, Liang Wang, Xiang Gao, Qiuqiu Qiu, Xiaofu Qiu, Zhiyu Liu

“…The model, validated in the DFKZ cohort, stratified patients into high- and low-risk groups, with the high-risk group exhibiting worse PFS and higher tumor mutation burden (TMB). Functional enrichment analysis revealed distinct pathway activities, with high-risk patients showing enrichment in immune-related and proliferative pathways, while low-risk patients were enriched in metabolic pathways. …”
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Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

“…Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. The optimal model was selected based on various performance metrics, including the area under the curve (AUC), accuracy, precision, recall, and F1 score. …”
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Feasibility of occlusal plane in predicting the changes in anteroposterior mandibular position: a comprehensive analysis using deep learning-based three-dimensional models by Bingran Du, Kaichen Li, Zhiling Shen, Yihang Cheng, Jiayan Yu, Yaopeng Pan, Ziyan Huang, Fei Hu, Xiaohui Rausch-Fan, Yuanpeng Zhu, Xueyang Zhang

“…Conclusions Constructing the OP using deep learning-based 3D models from CBCT data is feasible. …”
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Exploring the Impact of and Perceptions about Interactive, Self-Explaining Environments in Molecular- Level Animations by David A. Falvo, Michael J. Urban, Jerry P Suits

“…Results with students (n=189) showed that science majors scored higher than non-science majors in retention measures (i.e., structure and function) but not in transfer. Significant main effects were found for treatment in function questions and spatial ability in structure questions. …”
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Exploring the Impact of and Perceptions about Interactive, Self-Explaining Environments in Molecular- Level Animations by David A. Falvo, Michael J. Urban, Jerry P Suits

“…Results with students (n=189) showed that science majors scored higher than non-science majors in retention measures (i.e., structure and function) but not in transfer. Significant main effects were found for treatment in function questions and spatial ability in structure questions. …”
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Availability and functioning of neonatal care units and neonatal mortality across five regions in Tanzania: a baseline cross-sectional study in 127 CEmONC health facilities by Hege Ersdal, Nahya Salim, Siren Rettedal, Castory Munishi, Robert Moshiro, Felix Ambrose Bundala, Benjamin A Kamala, Godfrey Guga, Habib R Ismail, Paschal Francis Mdoe

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