Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis by Leonel J. R. Nunes, Sandra Silva

“…<i>Background</i>: This study investigates the vital significance of logistical cost optimization within the residual woody biomass supply chain, aiming to boost both sustainability and the efficient utilization of this resource. …”
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The Impact of Digital Technologies on Leadership in Global Processes: from Platforms to Markets? by I. V. Danilin

“…Dilemma of alternative solutions to boost the influence of third nations in the new digital, platform economy still may be resolved. …”
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Clinical learning process of surgical technologist students: A grounded theory by Mostafa Roshanzadeh, Mina Shirvani, Fatemeh Maraki, Ali Taj, Somayeh Mohammadi

“…Background & Objective: Identifying the learning process of surgical technologist students in the operating room environment can effectively reveal the factors and strategies they use to learn and enhance the quality of their education. …”
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Influence of the Un Formation Process to the Establishment of the XX Century World Order by Dmitry Guennadievich Novik

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Engine Mass Flow Estimation through Neural Network Modeling in Semi-Transient Conditions: A New Calibration Approach by T. Savioli, M. Pampanini, G. Visani, L. Esposito, C. A. Rinaldini

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Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection by Tuğçe Öznacar, Tunç Güler

“…This research aims to assess the feature extraction process from various machine learning techniques for better modelling of ovarian cancer and the selection process in ovarian cancer analysis. …”
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Adaptive optimization of natural coagulants using hybrid machine learning approach for sustainable water treatment by Pallavi Randive, Madhuri S. Bhagat, Mangesh P. Bhorkar, Rajesh M. Bhagat, Shilpa M. Vinchurkar, Sagar Shelare, Shubham Sharma, N. Beemkumar, S. Hemalatha, Parveen Kumar, Ankit Kedia, Ehab El Sayed Massoud, Deepak Gupta, Jasmina Lozanovic

“…CatBoost is effective for dealing with categorical data like diverse coagulants. …”
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Developing an IoT and ML-driven platform for fruit ripeness evaluation and spoilage detection: A case study on bananas by Rajini M, Persis Voola

“…This framework employed various machine learning algorithms to detect ripeness stages, with the CatBoost classifier exhibiting exceptional performance, demonstrating its dependability and effectiveness in assessing fruit quality. …”
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Study on the Risk of Urban Population Exposure to Waterlogging in Huang-Huai Area Based on Machine Learning Simulation Analysis—A Case Study of Xuzhou Urban Area by Shuai Tong, Jiuxin Wang, Jiahui Qin, Xiang Ji, Zihan Wu

“…Urban water accumulation is a complicated process, and the hydrological simulation analysis is highly accurate, but it is time-consuming and laborious. …”
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Investigation of predictive factors for fatty liver in children and adolescents using artificial intelligence by Aliakbar Sayyari, Amin Magsudy, Yasamin Moeinipour, Amirhossein Hosseini, Hamidreza Amiri, Mohammadreza Arzaghi, Fereshteh Sohrabivafa, Seyedeh Fatemeh Hamzavi, Ashkan Azizi, Tahereh Hatamii, AmirAli Okhovat, Naghi Dara, Negar Imanzadeh, Farid Imanzadeh, Mahmoud Hajipour

“…That is, the F1 for the CatBoost raised from 83% to 89% (AUC: 0.86–0.92), for the GradientBoosting from 76% to 81% (AUC: 0.81–0.85), and for Bernolli Naive Bayes from 78% to 82% (AUC: 0.82–0.85).ConclusionMachine learning models, particularly CatBoost, demonstrated strong predictive capabilities for NAFLD diagnosis in children.…”
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Predictive modeling of asthma drug properties using machine learning and topological indices in a MATLAB based QSPR study by Jalal Hatem Hussein Bayati, Abid Mahboob, Laiba Amin, Muhammad Waheed Rasheed, Abdu Alameri

“…The use of machine learning algorithms such as random forest and extreme gradient boosting is essential in this process. These algorithms leverage labeled data to predict complex molecular processes, aiding in the discovery of new medication options and enhancing their properties. …”
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Significant Improvement in Short-Term Green-Tide Transport Predictions Using the XGBoost Model by Menghao Ji, Chengyi Zhao

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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…Ten different machine learning models, including AdaBoost, Bagging, CatBoost, Decision Tree, Extra Trees, Gradient Boosting, HistGradientBoosting, LightGBM, Random Forest, and XGBoost, were evaluated using CuWO₄@TiO₂ as a photocatalyst. …”
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3D printing-biomimetic local stiff niche enhances glycolysis to boost PDAC cell stem-like phenotype via N6-methyladenosine-suppressed YAP1 mRNA decay by Di Wu, Xiaoqi Guan, Tao Yang, Jiashuai Yan, Biwen Zhu, Junchao Zhou, Yibing Guo, Yuhua Lu

“…The local stiff niche enhanced the stem-like phenotype of PDAC cells via YAP1-boosted glycolysis. Mechanistically, local stiff niche elevated the YAP1 level via m6A (METTL14/IGF2BP3)-stabilized YAP1 mRNA, linking mechanical inputs to glycolytic-stem-like phenotype adaptations. …”
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Natural Language, Legal Hurdles: Navigating the Complexities in Natural Language Processing Development and Application by Ilya Ilin, Aleksei Kelli

“… This article delves into the legal challenges faced in developing and deploying Natural Language Processing (NLP) technologies, focusing particularly on the European Union’s legal framework, especially the DSM Directive, the InfoSoc Directive, and the Artificial Intelligence Act. …”
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Automated detection and identification of white-backed planthoppers in paddy fields using image processing by Qing YAO, Guo-te CHEN, Zheng WANG, Chao ZHANG, Bao-jun YANG, Jian TANG

“…A new three-layer detection method was proposed to detect and identify white-backed planthoppers (WBPHs, Sogatella furcifera (Horváth)) and their developmental stages using image processing. In the first two detection layers, we used an AdaBoost classifier that was trained on a histogram of oriented gradient (HOG) features and a support vector machine (SVM) classifier that was trained on Gabor and Local Binary Pattern (LBP) features to detect WBPHs and remove impurities. …”
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A Graduate Level Personalized Learning Environment in the Field of f-NIRS Signal Processing by Dominique Persano Adorno, Giuseppe Costantino Giaconia

“…The outcomes suggest that a hands-on and student-centered laboratory, experienced through a methodical sequence of self-directed learning activities, could considerably boost the student motivation to learn and the level of engagement in bioengineering and biosciences.…”
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FPGA-based point processing for denoising of the show-through effect in scanned document images by Habibunnisha Nazeer, Nedumaran Damodaran

“…The Altera Cyclone® V DE1-SoC board was chosen for this study due to its performance, size compatibility, and real-time implementation, which are better than the programmable DSP chips. The Pixel/Point processing operations were implemented using the DSP builder tool, which boost-up better execution of computational operations involved in complex algorithms. …”
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The processing of familiar English L2 phrasal verbs in neutral and biased sentence contexts by Jianyao Yu, Jianyao Yu, Siya Wang, Siya Wang, Ping Zhang, Tai’an Chen, Tai’an Chen

“…Familiarity with PVs may be critical across proficiency levels in driving PV processing. What’s more, the preferred meaning may be bootstrapped in supporting context, but the less preferred meaning is likely suppressed even with context boost. …”
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Efficient degradation of antibiotics mixture in a solar photoelectro-Fenton system using CuFe2O4@GO@MIL-100(Fe): Boosting efficiency via enhanced charge separation by Felipe Gamboa-Savoy, Christian Onfray, Jonathan Correa-Puerta, Durga Prasad Pabba, Natalia Hassan, Abdoulaye Thiam

“…Integrating photocatalysis with these processes using photoactive nanomaterials enhances Fe2+ regeneration, boosting overall performance. …”
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