Comprehensive analysis of arc methods of 3D printing of metal products: assessment of the efficiency and prospects of using TIG as a heat source by Andrii Horbenko, Constantine Zvorykin

“… In recent years, additive technologies have become increasingly important for the production of parts with complex geometries, enabling the rapid and efficient creation of objects with different shapes and configurations in industrial sectors such as medicine, aerospace and construction. …”
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Biohybrid ZnCr-LDH/Spirogyra algae composite for selective adsorption from multi-dye anionic mixtures: Toward enhanced removal of direct yellow by Alfan Wijaya, Nur Ahmad, Laila Hanum, Elda Melwita, Yulizah Hanifah, Aldes Lesbani

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Spatially optimized allocation of water and land resources based on multi-dimensional coupling of water quantity, quality, efficiency, carbon, food, and ecology by Yingbin Wang, Haiqing Wang, Jiaxin Sun, Peng Qi, Wenguang Zhang, Guangxin Zhang

“…These enhancements enable the algorithm to explore the solution space more efficiently when addressing complex multi-objective problems to validate the effectiveness and practicality of the COM-WL model, we selected the Daan Irrigation District as the study area. …”
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Sponge-like Modified White-Rot Fungi Adsorbent for Rapid Removal of Pb(II) and Cd(II) from Solution: Selective Performance and Mechanistic Insights by Chunxiao Wang, Zhirong Chen, Nana Wang, Jianqiao Wang, Runshen He, Yu Chen, Haerfosai Nuhu, Hang Chen, Zhixuan Lin, Minqi Fan, Mingdong Chang

“…Mechanistic analyses (XRD, FTIR, and XPS) revealed that removal occurs via ion exchange, complexation, and precipitation, forming stable compounds like PbS/CdS and PbCO₃/CdCO₃. …”
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Single-Entry Selective Trunk Block (S-SeTB): An Innovative Approach to Complete Upper Extremity Anesthesia in Weapon-Wounded Patients in Low-Resource Settings by Shabani M, Crespo S, Raingeval X

“…Compared to conventional selective trunk blocks or hybrid brachial plexus approaches, the S-SeTB required lower anesthetic volumes (20– 25 mL) and demonstrated reduced procedural complexity and risks (eg, pneumothorax, vascular puncture).Conclusion: The S-SeTB, combined with SCP and intercostobrachial nerve blocks, offers a reliable, resource-efficient, and safer alternative to traditional brachial plexus block techniques. …”
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Orthogonal Multi‐Swarm Greedy Selection Based Sine Cosine Algorithm for Optimal FACTS Placement in Uncertain Wind Integrated Scenario Based Power Systems by Sunilkumar P. Agrawal, Pradeep Jangir, Arpita, Sundaram B. Pandya, Anil Parmar, Mohammad Khishe, Bhargavi Indrajit Trivedi

“…This study proposes a novel hybrid metaheuristic approach, the Orthogonal Multi‐swarm Greedy Selection Sine Cosine Algorithm (OMGSCA), integrating orthogonal learning, multi‐swarm mechanisms, and greedy selection to enhance solution quality. …”
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Development of an Eco-Friendly Method for Iron Extraction and Determination in Pharmaceuticals Using Ciprofloxacin Drug as Chelating agent by Baghdad Science Journal

“…Several variables which impact on the extraction and determination of Fe (III) are optimized in order to maximize the extraction efficiency and improve the sensitivity of the method. …”
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Zn-3, a Tris[3-(2-pyridyl)-pyrazolyl]borate zinc(II) complex, shows preferential antiproliferative effects on breast cancer rather than normal breast cells via oxidative stress by Jun-Ping Shiau, Min-Yu Lee, Sodio C.N. Hsu, Sih-Ruei Tseng, Hsueh-Wei Chang

“…The antiproliferative effects of Zn-3, a tris[3-(2-pyridyl)-pyrazolyl]borate zinc(II) complex, were reported previously in triple-negative breast cancer (TNBC) cells; however, its anticancer mechanisms were not assessed. …”
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SPL-YOLOv8: A Lightweight Method for Rape Flower Cluster Detection and Counting Based on YOLOv8n by Yue Fang, Chenbo Yang, Jie Li, Jingmin Tu

“…To address these challenges, this study proposes a lightweight rape flower clusters detection model, SPL-YOLOv8. First, the model introduces StarNet as a lightweight backbone network for efficient feature extraction, significantly reducing computational complexity and parameter counts. …”
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Development of New Electricity System Marginal Price Forecasting Models Using Statistical and Artificial Intelligence Methods by Mehmet Kızıldağ, Fatih Abut, Mehmet Fatih Akay

“…Overall, this study presents a novel and comprehensive approach tailored for complex electricity markets, significantly enhancing predictive reliability by incorporating economic indicators and sophisticated feature selection methods.…”
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A Machine Learning Model for Predicting Breast Cancer Recurrence and Supporting Personalized Treatment Decisions Through Comprehensive Feature Selection and Explainable Ensemble Le... by Lee TF, Shiau JP, Chen CH, Yun WP, Wuu CS, Huang YJ, Yeh SA, Chen HC, Chao PJ

“…However, traditional risk prediction models often lack accuracy and do not fully capture the complexity of patient data.This study developed an ensemble learning model to predict breast cancer recurrence more accurately by integrating LASSO feature selection and multiple machine learning models. …”
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ITap: Index Finger Tap Interaction by Gaze and Tabletop Integration by Jeonghyeon Kim, Jemin Lee, Jung-Hoon Ahn, Youngwon Kim

“…The primary purpose of this research is to enhance interaction efficiency, reduce user fatigue, and improve accuracy in gaze-based object selection tasks, particularly in complex and cluttered XR environments. …”
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A review on atomically modified materials by atomic layer deposition for wastewater treatment by Asif Jan, Melike Begum Tanis-Kanbur, Luuk C. Rietveld, Sebastiaan G.J. Heijman

“…ALD enables nanoscale engineering of materials, offering unprecedented control over surface chemistry, pore structure, and functional properties for improved wastewater treatment efficiency. This review critically examines the advancements in ALD-modified membranes and adsorbents for industrial wastewater treatment, highlighting how ALD enhances adsorption kinetics and selectivity in adsorbents, improves hydrophilicity and antifouling behavior in polymeric membranes, and enhances chemical and mechanical stability in ceramic membranes. …”
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Rough Set Theory and Soft Computing Methods for Building Explainable and Interpretable AI/ML Models by Sami Naouali, Oussama El Othmani

“…This study introduces a novel framework leveraging Rough Set Theory (RST)-based feature selection—MLReduct, MLSpecialReduct, and MLFuzzyRoughSet—to enhance machine learning performance on uncertain data. …”
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Attention-Based Dual-Knowledge Distillation for Alzheimer’s Disease Stage Detection Using MRI Scans by Chandita Barman, Sudhanshu Singh, Manob Jyoti Saikia, Shovan Barma

“…This study presents an efficient attention-guided dual-knowledge distillation (D-KD) framework for classifying Alzheimer’s disease (AD) stages using magnetic resonance imaging (MRI) scans based on detection of the subtle anatomical differences. …”
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Design of C24 fullerene-based sensors for gamma-butyrolactone detection as advanced tools for biomedical and pharmaceutical applications by Bader Huwaimel, Saad Alqarni

“…These results highlight MgC23 as a promising candidate for sensitive and efficient GBL detection in pharmaceutical and forensic applications.…”
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Anomaly Detection Model in Network Security Situational Awareness Based on Machine Learning: Limitation, Techniques, and Future Trends by Li Zhen, Nazhatul Hafizah Kamarudin, Ven Jyn Kok, Faizan Qamar

“…Finally, this study deepens the understanding of the anomaly detection problem in NSSA and provides both theoretical and practical guidance for the development of efficient and scalable anomaly detection systems.…”
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A Unified Transformer–BDI Architecture for Financial Fraud Detection: Distributed Knowledge Transfer Across Diverse Datasets by Parul Dubey, Pushkar Dubey, Pitshou N. Bokoro

“…With the growing volume and complexity of digital transactions, the traditional rule-based and shallow learning models often fall short in detecting sophisticated fraud patterns. …”
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Signal Detection in Intelligent Reflecting Surface-Assisted NOMA Network Using LSTM Model: A ML Approach by Haleema Sadia, Hafsa Iqbal, Syed Fawad Hussain, Nasir Saeed

“…In this article, we propose a machine learning (ML)-based approach to perform joint channel estimation and signal detection in an IRS-enabled uplink NOMA network under efficient mitigation of SIC error propagation. …”
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Short and Medium-Term Power Load Anomaly Detection Method Based on Convolutional Neural Network and EL-DCC by Zhipeng Li, Shaobo Liu, Yang Zhang, Zhaowei Wang, Lu Wang, Lu Huang

“…With the increasing complexity of load patterns, it is difficult for traditional methods to meet the requirements of accurate detection. …”
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