Relevant biochar characteristics influencing compressive strength of biochar-cement mortars by Julia Hylton, Aaron Hugen, Steven M. Rowland, Michael Griffin, Lori E. Tunstall

“…This work presents a reliable method to replace 10% of the cement mass with a vast selection of biochars without decreasing ultimate compressive strength, and in many cases significantly improving it. By carefully quantifying the physical and chemical properties of each biochar used, machine learning algorithms were used to elucidate the three most influential biochar characteristics that control mortar strength: initial saturation percentage, oxygen-to-carbon ratio, and soluble silicon. …”
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Enhancing Sports Team Management Through Machine Learning by Ling Zhang, Yifan An

“…Sports like basketball and baseball have seen significant improvements through the effective use of sports analytics. …”
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Morphometric analysis of pancytokeratin-negative neoplastic damages of the lymphatic nodes of the neck. by O. V. Poslavska, I. S. Shponka, P. O. Gritsenko, O. A. Alekseenko

“…The aim of the study was to analyze the complex of morphological, morphometric and immu­no­histochemical characteristics of Cytokeratin, Ran negative phenotypes of neoplastic lesions of lymph nodes of the neck for the improvement of diagnostic algorithms. Results. The authors have adjusted the objective parameters of nuclei of tumor cells (area, perimeter, coefficient of "roundness"), in comparison with the size of ordinary lymphocytes, the dependence of the size of the nuclei on morphological characteristics and the immunophenotype of the neoplastic damage of the lymph nodes of the neck has been analyzed.…”
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Treatment of Patients with Rotator Cuff Injuries (Review of Literature) by D. V. Menshova, I. A. Kuklin, N. S. Ponomarenko

“…Among the conservative methods of treatment aimed at reducing pain and improving the quality of life, injections of corticosteroids, hyaluronic acid, and autoplasma therapy are used. …”
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The constrained-disorder principle defines the functions of systems in nature by Yaron Ilan

“…The paper reviews variability-based CDP algorithms and CDP-based second-generation artificial intelligence systems and their potential for improving systems’ prediction and efficiency by using variability.…”
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DeepBase: A Deep Learning-based Daily Baseflow Dataset across the United States by Parnian Ghaneei, Hamid Moradkhani

“…The dataset can be used as a new benchmark for future studies aimed at improving hydrological predictions and managing water resources more effectively.…”
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Enhancing Predictive Capabilities for Identifying At-Risk Stocks Using Multivariate Time-Series Classification: A Case Study of the Thai Stock Market by Katsamapol Petchpol, Laor Boongasame

“…The study identifies models that effectively balance predictive accuracy with computational efficiency, with performance varying based on forecasting horizons. Despite improvements from specialized techniques, the study identifies challenges in long-term financial risk prediction. …”
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Artificial intelligence in drug development: reshaping the therapeutic landscape by Sarfaraz K. Niazi, Zamara Mariam

“…AI has boosted pharmaceutical R&D (research and development) by identifying new therapeutic targets, improving chemical designs, and predicting complicated protein structures. …”
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The Potential Merits and Risks of Deploying Artificial Intelligence as a Pedagogical Tool for Teacher Education in Kenya by Hellen Chelangat Sang

“…In Kenya for instance, its integration in teacher education has enhanced learning experiences thereby improving pedagogical outcomes and fostering innovation. …”
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Emerging Role of Artificial Intelligence by Mohammad Ilyas

“…How far AI can go in improving our lives and how significant and deep its interference can be in our existence, remains to be seen. …”
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Synergistic Integration of LQR Control and PSO Optimization for Advanced Active Suspension Systems Utilizing Electro-Hydraulic Actuators and Electro-Servo Valves by Trong Tu

“…The results demonstrate substantial improvements in ride comfort and road-holding stability compared to traditional passive suspension systems. …”
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Identification of podocyte molecular markers in diabetic kidney disease via single-cell RNA sequencing and machine learning. by Hailin Li, Quhuan Li, Zuyan Fan, Yue Shen, Jiao Li, Fengxia Zhang

“…Our findings elucidate podocyte function in DKD and provide viable therapeutic targets, potentially improving diagnostic accuracy and treatment outcomes.…”
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Exploring the Impact of Predictive Analytics and AI in STEM Education by Tai Ki Kim

“…Through a systematic literature review of studies published between 2020 and 2023, this paper highlights the effectiveness of predictive analytics in improving STEM education outcomes while emphasizing the importance of inclusive practices. …”
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MultiLTR: Text Ranking with a Multi-Stage Learning-to-Rank Approach by Hua Yang, Teresa Gonçalves

“…This study improves ranking accuracy and offers new insights into enhancing multi-stage ranking strategies.…”
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Design and Development of IoT-based Harvesting Robo-Vec by Sadiq Ur Rehman, Yasmin Abdul Wahab

“…Experimental results show that Harvesting Robo-Vec improves efficiency, reduces labor costs, and enhances productivity compared to manual methods. …”
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A systematic review of machine learning approaches in cochlear implant outcomes by Anu Prasad Sreenivasan Nair, Srikanta K. Mishra, Pedro Andres Alba Diaz

“…Additionally, ML-based speech enhancement algorithms showed promise in improving speech recognition in noisy environments, a major challenge for CI users. …”
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Research on Error Propagation Law of Flood Routingby Fourth-order Runge - Kutta Method by ZHOU Bin

“…The fourth-order Runge-Kutta method is one of the commonly used algorithms for solvingordinary differential equations of reservoir flood routing. …”
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REAL-TIME SIMULATIVE MODELING FOR GEAR CHANGE CONTROL STRATEGY RESEARCH by A. A. Filimonov, V. A. Kusyak

“…The paper contains conclusions about efficiency of the analyzed gear change control strategy. A strategy for improvement of automated mechanical transmission controlling algorithms has been proposed in the paper.…”
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Combined impact of semantic segmentation and quantitative structure modelling of Southern pine trees using terrestrial laser scanning by Jinyi Xia, Timothy A. Martin, Gary F. Peter, Kody M. Brock, Jeff W. Atkins, Matthew A. Gitzendanner, Inacio Bueno, Kim Calders, Ana Paula Dalla Corte, Andrew T. Hudak, Monique Bohora Schlickmann, Michael G. Andreu, Caio Hamamura, Carine Klauberg, Carlos A. Silva

“…Addressing this gap, our study evaluates the performance of multiple segmentation algorithms on TLS data from southern pines, providing valuable insights into improving structural analysis and supporting more precise and efficient forest research and monitoring methodologies. …”
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Enhancing Pollen Prediction in Beijing, a Chinese Megacity: Leveraging Ensemble Learning Models for Greater Accuracy by Wenxi Ruan, Ziming Li, Zhaobin Sun, Xingqin An, Yuxin Zhao, Shuwen Zhang, Yinglin Liang, Yaqin Bu, Jingyi Xin, Xiaoyi Hang

“…The findings reveal that the CatBoost, Extra Trees, and XGBoost algorithms perform well for three-day consecutive pollen predictions. …”
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