Lessons Learned from Crisis Management and Amputation Decisions in the Aftermath of High-magnitude Earthquakes in Kahramanmaras on 6 February 2023 by Atilla Orhan

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Interactive Learning Tool for System of Linear Equations: Bridging the Gap Between Novice and Expert Through MATLAB-Based Solutions by Reem A. Alnanih, Lamiaa A. Elrefaei

“…Interactive learning tools are increasingly used to visually convey complex concepts, enhancing students’ understanding and engagement during the learning process. …”
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Social media interaction and built environment effects on urban walking experience: A machine learning analysis of Shanghai Citywalk. by Xingrui Chen, Yu Sun, Filzani Illia Binti Ibrahim, Myzatul Aishah Binti Kamarazaly, Siti Norzaini Binti Zainal Abidin, Suqiu Tang

“…Additionally, spatial autocorrelation analysis of emotional scores reveals spatial clustering patterns, underscoring the critical role of interactions between virtual social behavior and physical spatial elements in emotional generation. In comparison, functional diversity and transit accessibility exhibit weaker but complementary effects on emotional scores. …”
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Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy’s impact on ART adherence by Abraham Keffale Mengistu, Kelemua Aschale Yeneakale, Nebebe Demis Baykemagn, Zelalem Yitayal Melese, Andualem Enyew Gedefaw

“…Using observational data from 4152 HIV patients in Ethiopia (2005–2024), we applied causal inference methods, including Adjusted Logistic Regression, Propensity Score Matching, and Causal Forest Double Machine Learning (DML), to estimate TPT’s effect on ART adherence. …”
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Deep learning-guided structural analysis of a novel bacteriophage KPP105 against multidrug-resistant Klebsiella pneumoniae by Seyoung Ko, Jaehyung Kim, Jae-Hyun Cho, Youngju Kim, Donghyuk Kim

“…Structural similarity analysis indicated that its RBP facilitates interactions with host receptors and exhibits unique sequence patterns distinguishing Klebsiella strains from other bacteria. Structure-based functional analysis provided comprehensive insights into cell wall degradation with various peptidoglycan fragments. …”
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DLBWE-Cys: a deep-learning-based tool for identifying cysteine S-carboxyethylation sites using binary-weight encoding by Zhengtao Luo, Zhengtao Luo, Zhengtao Luo, Qingyong Wang, Qingyong Wang, Qingyong Wang, Yingchun Xia, Yingchun Xia, Yingchun Xia, Xiaolei Zhu, Xiaolei Zhu, Xiaolei Zhu, Shuai Yang, Shuai Yang, Shuai Yang, Zhaochun Xu, Zhaochun Xu, Lichuan Gu, Lichuan Gu, Lichuan Gu

“…Our experimental results show that our model architecture outperforms other machine learning and deep learning models in 5-fold cross-validation and independent testing. …”
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Research on Wind Turbine Main Shaft Bearing Fault Diagnosis Method Based on Unity 3D and Transfer Learning by Shuai Wang, Wenlei Sun, Han Liu, Shenghui Bao, Yunhao Wang, Xin Zhao

“…Experimental results validate the effectiveness and superiority of the proposed method in fault diagnosis across various transfer learning tasks.…”
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Developing an Urban Landscape Fumigation Service Robot: A Machine-Learned, Gen-AI-Based Design Trade Study by Prithvi Krishna Chittoor, Bhanu Priya Dandumahanti, Prabakaran Veerajagadheswar, S. M. Bhagya P. Samarakoon, M. A. Viraj J. Muthugala, Mohan Rajesh Elara

“…Generative AI (Gen-AI) revolutionizes design by leveraging machine learning to generate innovative solutions. It analyzes data to identify patterns, creates tailored designs, enhances creativity, and allows designers to explore complex possibilities for diverse industries. …”
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Key RNA-binding proteins in renal fibrosis: a comprehensive bioinformatics and machine learning framework for diagnostic and therapeutic insights by Jie Chen, Binghan Zhang, Qixuan Huang, Ronghua Fang, Ziyu Ren, Dongfang Liu

“…The integration of bioinformatics and machine learning emphasizes their translational potential in kidney care.…”
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Exploring the molecular mechanisms of huperzine a in the treatment of rosacea through network pharmacology, machine learning, and molecular dynamics simulations by Xin Luo, Suhan Yang, Lian Zhong, Peng Zhang

“…IntroductionRosacea is a common chronic inflammatory skin disorder and dysregulation of neuroimmune functions and neurovascular loops play critical roles in the development of rosacea. …”
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IoT Integrated Graphene Derivative-Based Capacitive Sensors with Machine Learning Classification for Precision Soil Moisture Monitoring Process by Ukani Neema Amish, Khera Shelej, Chakole Saurabh S.

“…Nanomaterials were selected on account of superior electrical conductivity, large surface area, and tunable functional groups that allow for larger sensitivity changes in moisture variations. …”
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A natural bacterial pathogen of C. elegans uses a small RNA to induce transgenerational inheritance of learned avoidance. by Titas Sengupta, Jonathan St Ange, Rachel Kaletsky, Rebecca S Moore, Renee J Seto, Jacob Marogi, Cameron Myhrvold, Zemer Gitai, Coleen T Murphy

“…C. elegans can learn to avoid pathogenic bacteria through several mechanisms, including bacterial small RNA-induced learned avoidance behavior, which can be inherited transgenerationally. …”
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Machine Learning-Based Classification and Statistical Analysis of Liver Cancer: A Comprehensive Study of Model Performance and Clinical Significance by Pratyush Kumar MAHARANA, Tapan Kumar BEHERA, Pradeep Kumar NAIK

“…It performs numerous functions that are essential for metabolism, digestion, detoxification, and nutrient storage. …”
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Identification and verification of immune and oxidative stress-related diagnostic indicators for malignant lung nodules through WGCNA and machine learning by Zhou An, Meichun Zeng, Xianhua Wang

“…Shared DEGs from these analyses were subjected to functional enrichment analysis. To develop a diagnostic model for LNs, we investigated 113 combinations of 12 machine-learning algorithms, employing 10-fold cross-validation on the training set, followed by external validation of the test set. …”
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Salp Navigation and Competitive based Parrot Optimizer (SNCPO) for efficient extreme learning machine training and global numerical optimization by Oluwatayomi Rereloluwa Adegboye, Afi Kekeli Feda, Ghanshyam G. Tejani, Aseel Smerat, Pankaj Kumar, Ephraim Bonah Agyekum

“…To validate the efficacy of SNCPO, rigorous experimental evaluations were conducted on CEC2015 and CEC2020 benchmark functions, four engineering design optimization problems, and Extreme Learning Machine (ELM) training tasks across 14 datasets. …”
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Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree‐Based Machine Learning Model by Md. Siddikur Rahman, Miftahuzzannat Amrin, Md. Abu Bokkor Shiddik

“…Conclusion Our proposed ML model functions as an early warning system, improving comprehension of the factors that precipitate dengue outbreaks and providing a framework for sophisticated analytical techniques in public health.…”
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Primary Mediastinal B-Cell Lymphoma and [18F]FDG PET/CT: What We Learned and What Is New by Anna Giulia Nappi, Francesco Dondi, Achille Lazzarato, Lorenzo Jonghi-Lavarini, Joana Gorica, Flavia La Torre, Giulia Santo, Alberto Miceli

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Where to act, when to think, and how to feel: The ABC + model of learning engagement and its relationship to the components of academic performance by Eric T. McChesney, Christian D. Schunn, Linda DeAngelo, Erica McGreevy

“…Abstract Background This study breaks new ground by presenting a new, more sophisticated model of learning engagement that goes beyond the current state of the art embodied in the widely used Affective-Behavioral-Cognitive (ABC) model. …”
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System for assessment and prediction of the technical condition of power oil-filled transformer equipment of distribution networks using machine learning by A. R. Galyautdinova, I. V. Ivshin, S. A. Solovev

“…The data obtained as a result of modeling helps to increase the accuracy of forecasting the technical condition and determine the longterm prospects for the functioning of POTE the equipment management system, timely maintenance and repairs over the course of years and months.…”
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Identification of biomarkers in Alzheimer's disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms. by Juntu Li, Linfeng Tao, Yanyou Zhou, Yue Zhu, Chao Li, Yiyuan Pan, Ping Yao, Xuefeng Qian, Jun Liu

“…GO enrichment analysis revealed that these genes mainly affect inflammation, cytokines, immune-related functions, and signaling pathways related to metal ions. …”
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