Electrical discharge machining: Recent advances and future trends in modeling, optimization, and sustainability by Muhamad Taufik Ulhakim, Sukarman, Khoirudin, Dodi Mulyadi, Hendri Susilo, Rohman, Muji Setiyo

“…Advanced modeling techniques, such as finite element analysis (FEA) and artificial intelligence (AI)-driven simulations, have improved the accuracy of process predictions, enabling real-time adjustments and precise control of machining parameters. …”
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Does the hepatologist still need to rely on aminotransferases in clinical practice? A reappraisal of the role of a classic biomarker in the diagnosis and clinical management of chr... by Patrizia Burra, Calogero Cammà, Pietro Invernizzi, Fabio Marra, Maurizio Pompili

“…ALT, a sensitive and cost-effective marker of liver injury, remains pivotal in predicting clinical outcomes and guiding interventions in several chronic liver diseases including metabolic dysfunction-associated steatotic liver disease, and chronic viral hepatitis. …”
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A Golden Jackal based optimal operation and optimization of a virtual power plant involving renewable resources by Anubhav Kumar Pandey, Chaima Mansour, Nandini K. K., Vinay Kumar Jadoun, Jayalakshmi N. S.

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MODERN APPROACHES TO CLINICAL AND LABORATORY DIAGNOSTICS OF RHEUMATOID ARTHRITIS EARLY ONSET by D. G. Rekalov, S. Y. Dotsenko, A. V. Kylinich

“…It was shown prognostic value of the main serological markers of RA, and the predictive value for early detection of antibodies to the circulating peptide as a marker of the severity of bone-destructive changes in patients with certain clinical manifestations. …”
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Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI by Insu Jeon, Minjoong Kim, Dayeong So, Eun Young Kim, Yunyoung Nam, Seungsoo Kim, Sehoon Shim, Joungmin Kim, Jihoon Moon

“…XAI techniques were employed to improve model transparency, offering insights into how features contribute to predictions, thereby enhancing clinician trust. <b>Results:</b> Rigorous data-preprocessing improved the models’ generalizability and real-world applicability across diverse clinical datasets, ensuring a robust performance. …”
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SPA-Net: An Offset-Free Proposal Network for Individual Tree Segmentation from TLS Data by Yunjie Zhu, Zhihao Wang, Qiaolin Ye, Lifeng Pang, Qian Wang, Xiaolong Zheng, Chunhua Hu

“…Deep learning methodologies proffer more efficacious and automated solutions, but their segmentation accuracy is restricted by imprecise center offset predictions, particularly in intricate forest environments. …”
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Proteomic analysis of blood plasma as a tool for personalized diagnosis of lung adenocarcinoma by D. N. Korobkov, A. S. Kononikhin, S. D. Semenov, H. L. Kordzaya, A. G. Brzhozovskiy, A. E. Bugrova, E. Yu. Vasilieva, D. Yu. Kanner, E. N. Nikolaev, A. A. Komissarov

“…Additionally, we identified three proteins that predict the presence of distant metastases among patients with LAC. …”
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NeuroRF FarmSense: IoT-fueled precision agriculture transformed for superior crop care by Tarun Vats, Shrey Mehra, Uday Madan, Amit Chhabra, Akashdeep Sharma, Kunal Chhabra, Sarabjeet Singh, Utkarsh Chauhan

“…This integrative approach harnesses the advantages of NN’s ReLU activation and dropout regularization alongside the robustness of RF. By utilizing NN predictions as input features for RF training and refining RF through grid search with cross-validation, the ensemble model produces highly precise predictions, facilitating strategic crop cultivation for optimal yields across diverse environmental conditions. …”
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A Comprehensive Framework for Transportation Infrastructure Digitalization: TJYRoad-Net for Enhanced Point Cloud Segmentation by Zhen Yang, Mingxuan Wang, Shikun Xie

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A Capacity Optimization Configuration Method for Photovoltaic and Energy Storage System of 5 G Base Station Considering Time-of-Use Electricity Price by Ziyan HAN, Shouxiang WANG, Qianyu ZHAO, Zhijie ZHENG

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Biomarker levels, left ventricular dysfunction, and severity of coronary pathology in elderly patients with coronary heart disease by L. R. Mirzakhanova, F. A. Kuliev, E. I. Shorikov

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Automated 3D defect inspection in shield tunnel linings through integration of image and point cloud data by Hongwei Huang, Shuyi Liu, Mingliang Zhou, Hua Shao, Qingtong Li, Phromphat Thansirichaisree

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Correction of CAMS PM₁₀ Reanalysis Improves AI-Based Dust Event Forecast by Ron Sarafian, Sagi Nathan, Dori Nissenbaum, Salman Khan, Yinon Rudich

“…A correction model that links pixel-wise errors with atmospheric and meteorological variables was taught using gradient-boosting algorithms. This model is then utilized to predict CAMS error in previously unobserved pixels across the Eastern Mediterranean, generating CAMS error fields. …”
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Integrative analysis of semaphorins family genes in colorectal cancer: implications for prognosis and immunotherapy by Jiahao Zhu, Benjie Xu, Zhixing Wu, Zhixing Wu, Zhiwei Yu, Shengjun Ji, Jie Lian, Haibo Lu

“…Additionally, knocking down SEMA4C significantly inhibits the proliferation and invasion of CRC cells, while promoting apoptosis in vitro.ConclusionSRS could serve as an effective tool to predict survival and identify potential patients benefiting from immunotherapy in CRC. …”
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Deep learning approach with ConvNeXt-SE-attn model for in vitro oral squamous cell carcinoma and chemotherapy analysis by Abhay Nath, Om Roy, Priyanka Silveri, Sanskruti Patel

“…Oral squamous cell carcinoma (OSCC) continues to present a major worldwide healthcare problem because patients have poor survival outcomes alongside frequent disease returns. Globocan predicts that, OSCC will result in 389,846 new cases and 188,438 deaths globally during 2022 while maintaining an extremely poor 5-year survival rate at about 50%. …”
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Computational Evaluation and Multi-Criteria Optimization of Natural Compound Analogs Targeting SARS-CoV-2 Proteases by Paul Andrei Negru, Andrei-Flavius Radu, Ada Radu, Delia Mirela Tit, Gabriela Bungau

“…Notably, CHEMBL4069090 emerged as a lead compound with favorable drug-likeness and predicted binding to PLpro. Overall, the applied in silico framework facilitated the rational prioritization of bioactive analogs with promising pharmacological profiles, supporting their advancement toward experimental validation and therapeutic exploration against SARS-CoV-2.…”
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Impacts of climate change on the global spread and habitat suitability of Coxiella burnetii: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat, Niloufar Lorestani, Farzin Shabani

“…By 2090, a 44.56 % (range: 33–57.9 %) across the models, increase in suitable habitat is predicted, accompanied by a 27.66 % (range: 22.4–31.7 %) loss of current habitats. …”
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Comparison of light gradient boosting and logistic regression for interactomic hub genes in Porphyromonas gingivalis and Fusobacterium nucleatum-induced periodontitis with Alzheime... by Pradeep Kumar Yadalam, Shubhangini Chatterjee, Prabhu Manickam Natarajan, Carlos M. Ardila, Carlos M. Ardila

“…Logistic regression and light gradient boosting were used to predict interactomic hub genes, with outliers removed and machine learning algorithms applied.ResultsThe data were cross-validated and divided into training and testing segments. …”
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Machine learning-based identification of histone deacetylase-associated prognostic factors and prognostic modeling for low-grade glioma by Keshan Wen, Weijie Zhu, Ziyi Luo, Wei Wang

“…This study aims to develop a prognostic model based on HDAC-related genes to aid in risk stratification and predict therapeutic responses. Methods Expression data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) were analyzed to identify an optimal HDAC-related risk signature from 73 genes using 10 machine learning algorithms. …”
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DMFFNet: Dual-Mode Multiscale Feature Fusion-Based Pedestrian Detection Method by Ruizhe Hu, Ting Rui, Yan Ouyang, Jinkang Wang, Qunyan Jiang, Yinan Du

“…Most contemporary pedestrian detection algorithms are based on visible light image detection. …”
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