Reinforcement Learning-Based Generative Security Framework for Host Intrusion Detection by Yongsik Kim, Su-Youn Hong, Sungjin Park, Huy Kang Kim

“…HIDS can quickly identify potential security threats by closely monitoring and analyzing system logs, configurations, file integrity, and events specific to a host machine. It helps maintain the security and integrity of individual systems by detecting unauthorized activities or policy violations. …”
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MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data by Katarzyna Arturi, Eliza J. Harris, Lilian Gasser, Beate I. Escher, Georg Braun, Robin Bosshard, Juliane Hollender

“…Abstract MLinvitroTox is an automated Python pipeline developed for high-throughput hazard-driven prioritization of toxicologically relevant signals detected in complex environmental samples through high-resolution tandem mass spectrometry (HRMS/MS). MLinvitroTox is a machine learning (ML) framework comprising 490 independent XGBoost classifiers trained on molecular fingerprints from chemical structures and target-specific endpoints from the ToxCast/Tox21 invitroDBv4.1 database. …”
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Exploring the Connectivity Between Education 4.0 and Classroom 4.0: Technologies, Student Perspectives, and Engagement in the Digital Era by Kapil Joshi, Rajesh Kumar, Salil Bharany, Dilip Kumar Jang Bahadur Saini, Rajiv Kumar, Ashraf Osman Ibrahim, Abdelzahir Abdelmaboud, Wamda Nagmeldin, Mohammad Awad Medani

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New Insights into the Role of Inflammatory Pathways and Immune Cell Infiltration in Sleep Deprivation-Induced Atrial Fibrillation: An Integrated Bioinformatics and Experimental Stu... by Liang J, Tang B, Shen J, Rejiepu M, Guo Y, Wang X, Shao S, Guo F, Wang Q, Zhang L

“…Studies emphasizing functional enrichment have highlighted the significance of inflammation pathways, particularly the NOD-like receptor signaling route. The application of machine learning uncovered four crucial genes—CDC5L, MAPK14, RAB5A, and YBX1—with YBX1 becoming the predominant gene in diagnostic processes. …”
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Effect of Different Surface Treatments on the Micro-Shear Bond Strength and Surface Characteristics of Zirconia: An In Vitro Study by Ann Sales, Shobha J. Rodrigues, M. Mahesh, Kishore Ginjupalli, Thilak Shetty, Umesh Y. Pai, Sharon Saldanha, Puneeth Hegde, Sandipan Mukherjee, Vignesh Kamath, Prashant Bajantri, N. Srikant, Ravindra Kotian

“…A micro-shear bond strength test was performed in a universal testing machine at a crosshead speed of 0.5 mm/min. The fracture surfaces were assessed under a compound microscope. …”
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Comprehensive pan-cancer analysis reveals NTN1 as an immune infiltrate risk factor and its potential prognostic value in SKCM by Fuxiang Luan, Yuying Cui, Ruizhe Huang, Zhuojie Yang, Shishi Qiao

“…To further elucidate the influence of genes on tumors, we utilized a variety of machine learning techniques and found that NTN1 is strongly linked to multiple cancer types, suggesting it as a potential therapeutic target. …”
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Patients with Age-related Macular Degeneration Have Increased Susceptibility to Valvular Heart Disease by Natan Lishinsky-Fischer, Itay Chowers, MD, PhD, Yahel Shwartz, MSc, Jaime Levy, MD

“…Moreover, a supervised machine learning model successfully detected the presence of AMD based solemnly on the patient’s history of VHD. …”
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Imaging and Clinical Characteristics of 8 Cases of COVID-19 Complicated with Pneumomediastinum in Children by FU Qiang, REN Zuolei, LIN Zhiqiang, GONG Jianfeng, WANG Changzheng, WANG Ting, HU Yalan, TAN Jufang

“…After 3 days, the symptoms improved and the machine was successfully withdrawn. 5 cases were treated with intravenous immunoglobulin (IVIG), and 3 cases were treated with glucocorticoids. a week after the review of chest CT, pneumomethinum were completely absorbed, and lung lesions significantly improved. …”
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Trends and Gaps in Digital Precision Hypertension Management: Scoping Review by Namuun Clifford, Rachel Tunis, Adetimilehin Ariyo, Haoxiang Yu, Hyekyun Rhee, Kavita Radhakrishnan

“…The most commonly used digital technologies were mobile phones (33/46, 72%), blood pressure monitors (18/46, 39%), and machine learning algorithms (11/46, 24%). In total, 45% (21/46) of the studies either did not report race or ethnicity data (14/46, 30%) or partially reported this information (7/46, 15%). …”
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Evaluation of the Effects of Retro-Cavity Preconditioning with or Without Ethylenediaminetetraacetic Acid on Root Surface pH and Dislodgement Resistance of NeoMTA2 and Mineral Trio... by Sedigheh Khedmat, Seyyed Ali Abaee, Hadi Assadian, Antonio Signore, Stefano Benedicenti

“…Subsequently, the push-out bond strength (PBS) of the retro-filling materials was measured by a universal testing machine, and their failure modes were visualized under 64× magnification. …”
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Providing a General Model for the Successful Implementation of Digital Transformation in Organizations by Haidar Ahmadi, Najme Parsaei, Seyyed Hamed Hashemi, Hamidreza Nematollahi

“…Conclusion Digital transformation extends beyond the mere adoption of emerging technologies such as artificial intelligence and machine learning; it represents a paradigm shift in how traditional management and operational practices are conducted across various functions, including product development, engineering, marketing, sales, and service delivery. …”
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Effect of Implant Positions and Angulations on Retentive Strength of 2-Implant Mandibular Overdentures: An In Vitro Study with the New 3D-Printed Simulation Method by Pravinkumar G. Patil, Liang Lin Seow, Rashmi Uddanwadikar, Allan Pau, Piyush D. Ukey

“…A total of 4 simulated overdenture model sets for each of the 10 study groups were subjected to the universal testing machine thrice to measure a peak load (N) to disengage the attachments vertically. …”
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Genetic Biomarkers and Circulating White Blood Cells in Osteoarthritis: A Bioinformatics and Mendelian Randomization Analysis by Yimin Pan, Xiaoshun Sun, Jun Tan, Chao Deng, Changwu Wu, Georg Osterhoff, Nikolas Schopow

“…The bioinformatics methods utilized include the Limma package, WGCNA, PPI network analysis, and machine learning algorithms. Genetic variants were used as instrumental variables to evaluate the potential causal impact of circulating white blood cell (WBC) counts on OA. …”
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L’utilisation du bois dans les aménagements portuaires antiques de Narbonne/Narbo Martius (Aude) by Corinne Sanchez, Jean-Michel Fabre, Sophie Coadic, Julie Labussière, Benoit Favennec, Marie-Pierre Jézégou, Stéphanie Wicha

“…AD; - the phases of reconstruction/repair, especially during Late Antiquity ; - finally, the remains of a probable unloading machine. The first dykes are made up of alignments of planks supported by piles, stabilising the sand levees along the river. …”
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Equalizer Design: HBOA-DE-trained radial basis function neural networks by Santosh Kumar Das, Satya Ranjan Pattanaik, Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Abdulaziz S. Almazyad, Muhammed Basheer Jasser, Guojiang Xiong, Ali Wagdy Mohamed

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New bitongling regulates gut microbiota to predict angiogenesis in rheumatoid arthritis via the gut-joint axis: a deep neural network approach by Yin Guan, Xiaoqian Zhao, Yun Lu, Yue Zhang, Yan Lu, Yue Wang

“…The study employed 16S ribosomal DNA (16S rDNA) sequencing to analyze gut microbiota composition, machine learning techniques to identify characteristic microbial taxa, and transcriptomic analysis (GSVA) to assess the impact on the VEGF signaling pathway. …”
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Exploring sex differences in Alzheimer’s disease: a comprehensive analysis of a large patient cohort from a memory unit by Maitee Rosende-Roca, Fernando García-Gutiérrez, Yahveth Cantero-Fortiz, Montserrat Alegret, Vanesa Pytel, Pilar Cañabate, Antonio González-Pérez, Itziar de Rojas, Liliana Vargas, Juan Pablo Tartari, Ana Espinosa, Gemma Ortega, Alba Pérez-Cordón, Mariola Moreno, Sílvia Preckler, Susanna Seguer, Miren Jone Gurruchaga, Lluís Tárraga, Agustín Ruiz, Sergi Valero, Mercè Boada, Marta Marquié

“…We employed various statistical techniques to assess the impact of sex on cognitive evolution in these dementia patients, accounting for other sex-related risk factors identified through Machine Learning methods. Results The study cohort comprised a total of 6108 individuals diagnosed with AD dementia during the study period (28.4% males and 71.6% females). …”
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Lipids as key biomarkers in unravelling the pathophysiology of obesity-related metabolic dysregulation by Anis Adibah Osman, Siok-Fong Chin, Lay-Kek Teh, Noraidatulakma Abdullah, Nor Azian Abdul Murad, Rahman Jamal

“…The predictive model underwent evaluation across four machine learning algorithms consistently demonstrated the highest predictive accuracy of 0.821, aligning with the findings from the classical logistic regression statistical model. …”
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Empirical estimation of saturated soil-paste electrical conductivity in the EU using pedotransfer functions and Quantile Regression Forests: A mapping approach based on LUCAS topso... by Calogero Schillaci, Simone Scarpa, Felipe Yunta, Aldo Lipani, Fernando Visconti, Gábor Szatmári, Kitti Balog, Triven Koganti, Mogens Greve, Giulia Bondi, Georgios Kargas, Paraskevi Londra, Fuat Kaya, Giuseppe Lo Papa, Panos Panagos, Luca Montanarella, Arwyn Jones

“…In this work, using the LUCAS 2018 dataset, we provide an empirically-derivedpedotransfer function to convert diluted EC1:5 to saturated ECe using the LUCAS soil texture and soil organic carbon, and a framework for ECe mapping with a machine-learning algorithm named Quantile Regression Forest. …”
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Ovarian Reserve: A Critical Indicator of Female Reproductive Health by Julia Ufnal, Anna Wolff, Maria Morawska, Dominika Lewandowska, Dominika Rosińska-Lewandoska, Marcelina Szewczyk, Klaudia Kożuchowska, Dawid Pilarz, Kinga Jarosz, Szymon Gruszka

“…Newly approaches, like machine learning models and AMH-based screening programs in countries like Portugal emerge. …”
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