Logging Components Extraction Method and Anisotropy Recognition Based on 3D Holographic LWD Instrument by Shuyu Guo, Jie Wang, Xiangyu Xing, Jiaqi Xiao, Xiao Liu

“…By integrating extracting algorithms with the specific antenna configuration of the 3D holographic LWD tool, high-fidelity extraction and complete separation of all nine electromagnetic logging components are achieved. …”
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A New Approach of Dynamic Complexity Analysis for a Planar Manipulator With Clearance and Lubrication in Joint by Wenhua Ding, Mingjian Yang, Mian Jiang, Mu Chai, Guiming Liang

“…On the other hand, the effectiveness of control algorithms is largely dependent on the dynamic complexity of the robotics, while its complexity analysis is an important prerequisite for achieving high-performance control. …”
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Low-Light Image and Video Enhancement for More Robust Computer Vision Tasks: A Review by Mpilo M. Tatana, Mohohlo S. Tsoeu, Rito C. Maswanganyi

“…The review also analyzes how popular computer vision tasks are improved and made more robust when coupled with light enhancement algorithms. Results show that deep learners outperform traditional enhancers, with supervised learners obtaining the best results followed by zero-shot learners, while computer vision tasks are improved with light enhancement coupling. …”
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A Transformation of the Way of Thinking: Key Principles in Programming Education Inspired by Pascal by Valentina Dagienė, Gintautas Grigas, Tatjana Jevsikova

“…For this purpose, a compiler for a subset of Pascal was developed for students taking their first steps towards programming, or more precisely, algorithmic thinking. Many innovations were developed and brought into practice. …”
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A Systematic Literature Review on Sustainability Integration and Marketing Intelligence in the Era of Artificial Intelligence by Md Mehedi Hasan Emon, Tahsina Khan

“…The conversation delves into the difficulties and moral aspects involved in using AI in marketing, such as issues related to data privacy, algorithmic bias, and the importance of a strategic framework that focuses on sustainable development goals. …”
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Using artificial intelligence for sustainable crop production – a comprehensive review with a focus on potato production by Magdalena Piekutowska

“…These advancements are especially crucial in addressing the rising food demand posed by global population growth, while simultaneously managing limited environmental resources. …”
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Enhanced Brain Tumor Segmentation Using CBAM-Integrated Deep Learning and Area Quantification by Rafiqul Islam, Sazzad Hossain

“…Furthermore, the proposed framework enhances segmentation precision while simultaneously incorporating tumor area measurement, making it a comprehensive tool for early-stage tumor analysis. …”
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Pioneering the Security of EHRs Using an Immersive Blockchain Conceptual Framework by Rihab Benaich, Youssef Gahi, Saida El Mendili

“…Methods/Analysis involve a novel combination of Advanced Encryption Standard (AES) and quantum cryptographic algorithms CRYSTALS-Dilithium and CRYSTALS-Kyber within a hybrid blockchain architecture to secure EHRs. …”
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Understanding visitor flow and behaviour in developing tourism-service-oriented villages by space syntax methodologies: a case study of Tabian Rural Section of Qingshan Village, Ha... by Shuqin Wang, Yan Huang, Tianjie Li

“…The methodologies employed in this study are based on two space syntax algorithms: 3-D isovist analysis and agent-based models (ABMs). …”
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A Multi-Model Machine Learning Framework for Identifying Raloxifene as a Novel RNA Polymerase Inhibitor from FDA-Approved Drugs by Nhung Thi Hong Van, Minh Tuan Nguyen

“…We developed a multi-model machine learning framework combining five traditional algorithms (ExtraTreesClassifier, RandomForestClassifier, LGBMClassifier, BernoulliNB, and BaggingClassifier) with a CNN deep learning model to identify potential RdRP inhibitors among FDA-approved drugs. …”
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A Study Investigating Interpretable Deep Learning Models for Predicting Mortality and Survival in Patients with Primary Thyroid Lymphomas by Zihan Yu, Rong Hu, Jiaqing Chen

“…Primary thyroid lymphoma (PTL) is a rare malignancy, and this study aimed to develop a prognostic prediction model for PTL using deep learning algorithms while providing interpretable analyses. Machine learning models were employed for mortality risk prediction, with the SHAP framework introduced for feature interpretation, and a DeepSurv model was constructed for comparison with the Cox proportional hazards (Cox-PH) model. …”
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Architectural Gaps in Generative AI: Quantifying Cognitive Risks for Safety Applications by He Wen, Pingfan Hu

“…<b>Conclusions</b>: These findings suggest that such distances represent not only algorithmic abstraction but also potential safety risks when generative AI is deployed in practice. …”
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Water Quality Monitoring: A Water Quality Dataset from an On-Site Study in Macao by Jiawei Gao, Bochao Chen, Su-Kit Tang

“…The collected data were analyzed and validated using machine learning algorithms, including Isolation Forest, Random Forest, Logistic Regression, and Local Outlier Factor. …”
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Towards a Sustainable Disruptive Growth Model: Integrating Foresight, Wild Cards and Weak Signals Analysis by Rafael Popper, Yuli Villarroel, Raimund Popper

“…In environmental systems, this may involve tracking early deforestation signals before tipping points, while in economics, it could mean analyzing how small policy shifts trigger market changes. …”
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Hybrid machine learning and physics-based model for estimating lettuce (Lactuca sativa) growth and resource consumption in aeroponic systems by Benedetta Fasciolo, Nicolò Grasso, Giulia Bruno, Paolo Chiabert

“…Traditional farming methods struggle with efficiently managing nutrients and water while ensuring high-quality products, leading to resource wastage and food safety concerns. …”
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Advancements in Glucose Monitoring: From Traditional Methods to Wearable Sensors by Koyel Dey, Tuhin Subhra Santra, Fan Gang Tseng

“…Minimally invasive methods, such as fluorescence sensors, Raman sensors, and microneedle arrays, aim to reduce discomfort while providing more precise measurements than non-invasive devices. …”
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Energy-Efficient Cooperative Transmission in Ultra-Dense Millimeter-Wave Network: Multi-Agent Q-Learning Approach by Seung-Yeon Kim, Haneul Ko

“…To satisfy the quality of service (QoS) requirements of users and decrease the energy consumption of networks, we define a reward function while considering the outage and energy efficiency of each BS. …”
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The Method of Images Revisited: Approximate Solutions in Wedge‐Shaped Aquifers of Arbitrary Angle by I. A. Nikoletos, K. L. Katsifarakis

“…Moreover, the solutions fully observe the boundary conditions, while they preserve the continuity of the drawdown, which can be calculated directly at any point of the flow field. …”
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Elucidating Early Radiation-Induced Cardiotoxicity Markers in Preclinical Genetic Models Through Advanced Machine Learning and Cardiac MRI by Dayeong An, El-Sayed Ibrahim

“…Cardiac MRI was performed 8 and 10 weeks post-treatment to assess global and regional cardiac function. ML algorithms were applied to differentiate sham-treated and irradiated rats based on early changes in myocardial function. …”
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Presepsin in Hepatic Pathology: Bridging the Gap in Early Sepsis Detection by Dana-Maria Bilous, Mihai Ciocîrlan, Cătălina Vlăduț, Carmen-Georgeta Fierbințeanu-Braticevici

“…Its utility extends to differentiating bacterial infections from fungal infections and monitoring treatment response. While preliminary evidence is compelling, further prospective, multicenter studies are required to validate its integration into standard care algorithms. …”
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