Emerging trends in sustainable energy system assessments: integration of machine learning with techno-economic analysis and lifecycle assessment by Ebrahimpourboura Zahra, Mosalpuri Manish, Jonas Baltrusaitis, Dubey Pallavi, Mba Wright Mark

“…Key case studies demonstrate the transformative potential of ML in improving economic viability and environmental sustainability, highlighting its role in predicting system performance, optimizing configurations, and reducing costs and impacts. …”
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A novel biochemical analysis for ApoE4 quantification in plasma and discrimination of homozygous and heterozygous APOE ε4 carriers by Andrés Rodríguez, Olga Calero, Sergio Veiga, Miriam Menacho-Román, Ignacio Arribas, Lluís Cano, Guillermo García-Ribas, Miguel Calero

“…Discussion The e4Quant assay offers a rapid, cost-effective, and highly accurate biochemical alternative to APOE genotyping, suitable for clinical and research settings, particularly in assessing AD risk and optimizing anti-amyloid therapeutic strategies. …”
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Enhancing grid-connected PV-EV charging station performance through a real-time dynamic power management using model predictive control by Aziz Watil, Hamid Chojaa

“…It also provides flexibility in BEV power sizing, optimizing the use of power electronics converters to reduce costs and complexity. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Model performance was evaluated using metrics including the mean absolute error (MAE) and root mean squared error (RMSE) for regression models, while accuracy, F1-score, and area under the curve (AUC) were used for classification models. …”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Moreover, YOLORM exhibited significant reductions in parameter count and computational cost while maintaining or enhancing detection performance relative to state-of-the-art algorithms. …”
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Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…Our findings highlight the superior performance of the qEHVI acquisition function in identifying the optimal Pareto front across 1-, 2-, and 3-objective aluminum alloy optimisation problems, all within a constrained evaluation budget and reasonable computational cost. …”
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Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction. by André G Coimbra, Cleiane G Oliveira, Matheus P Libório, Hasheem Mannan, Laercio I Santos, Elisa Fusco, Marcos F S V D'Angelo

“…The application of these techniques aims to improve the quality of life for individuals, reduce healthcare costs, and allocate available resources more efficiently, making it a preventive action.…”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Economically, catalytic pyrolysis shows near-term viability with a break-even cost of 0.8 – 1.2 $/L for diesel-range fuels, while photocatalysis requires a 50% – 70% reduction in catalyst synthesis costs (e.g., replacing Pt with Fe-Ni sulfides). …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Further research is needed to evaluate cost-effectiveness, real-world applications, and strategies (e.g., clinician training and the integration of explainable AI) to improve trust and broaden clinical adoption.…”
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Research and Application of a Health Management Device for the Electrical Control Cabinet of the EMU by Yongshen WU, Jian FENG, Mingshuai ZHANG, Chaoyue JU, Feihong YI

“…The usage of the device can also beneficial to the intelligent maintenance of electrical cabinets and optimize maintenance costs.…”
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PP-QADMM: A Dual-Driven Perturbation and Quantized ADMM for Privacy Preserving and Communication-Efficient Federated Learning by Anis Elgabli

“…We provide a rigorous theoretical proof of convergence, showing that PP-QADMM converges to the optimal solution for convex problems while achieving a convergence rate comparable to standard ADMM, but with significantly lower communication and energy costs, and robust privacy protection. …”
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A Novel Temperature Reconstruction Method for Acoustic Pyrometry Under Strong Temperature Gradients and Limited Measurement Points by Jingkao Tan, Lehang Chen, Na Li, Qulan Zhou, Zhongquan Gao, Jie Zhou

“…The proposed AGES-AHK method implements adaptive hybrid kernel adjustments on AGES-optimized nonuniform grids, achieving significant improvements in both reconstruction fidelity and hotspot characterization. …”
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Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends by Chen Boshan

“…Second, the research focuses on key AI applications in quantitative investment, including multi-factor model optimization, high-frequency market risk management, multimodal data integration, and algorithmic trading enhancement. …”
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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…MobileNet displayed the lowest computational cost. Grad-CAM analysis demonstrated discrepancies between the best-performing model and the highest explainability model. …”
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Reinforcement Learning-driven Mechanism Study of Ecological Compensation to Suppress Carbon Lock-in by Yongxin Zhou

“…Specifically, RL-MEC-CL, in a continuous action space, leverages an actor-critic architecture with experience replay and target networks to optimize compensation strategies adaptively, balancing carbon reduction benefits, sequestration enhancement, and policy costs. …”
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TECHNOLOGICAL ADVANCES IN ELECTROPLATING: ARTIFICIAL INTELLIGENCE TO PREDICT ZINC COATING THICKNESS ON SAE 1008 LOW CARBON STEELS by Luciano M. L. de Oliveira, Fabiana L. da Silva, Paulo R. Janissek, Juliano C. Toniolo

“…This ultimately reduces costs and improves product quality.…”
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PENC: a predictive-estimative nonlinear control framework for robust target tracking of fixed-wing UAVs in complex urban environments by Shiji Hai, Xitai Na, Zhihui Feng, Jinshuo Shi, Qingbin Sun

“…This necessitates tracking algorithms capable of both target state estimation and prediction. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…The ability to infer these variables through a singular measurable soil property, soil resistivity, can potentially improve sub-surface characterization. This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. …”
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Design and Implementation of a Deep Learning-Based Hand Gesture Recognition System for Rehabilitation Internet-of-Things (RIoT) Environments Using MediaPipe by Nurul Hanis Mohd Dhuzuki, Ahmad Anwar Zainuddin, Nur Anis Sofea Kamarul Zaman, Alin Nur Maisarah Ahmad Razmi, Wonderful Shammah Kaitane, Asmarani Ahmad Puzi, Mohd Naqiuddin Johar, Maslina Yazid, Nor Azlin Mohd Nordin, Shahrul Naim Sidek, Hasan Firdaus Mohd Zaki

“…Several limitations, including latency and distance sensitivity, are addressed in this system with edge computing alongside adaptive algorithms. The key contributions of this research are as follows: First, developing a real-time and cost-effective solution for remote stroke rehabilitation. …”
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