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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miRNA in Machine-Learning-Based Diagnostics of Oral Cancer by Xinghang Li, Valentina L. Kouznetsova, Igor F. Tsigelny

“…Traditional cancer diagnostic methods, such as biopsies and histopathological analyses, while effective, are invasive, costly, and require specialized skills. …”
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Image-Based Malware Detection Using Deep CNN Models by hawraa omran musa, Muhanad Tahrir Younis

“…The selection of a 64 × 64 size frame reduces network complexity while speeding up training without sacrificing important information. …”
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The contribution of X to youth environmental movements addressing climate change: Effective impact or distorting noise? by Ángela Alonso-Jurnet, Ainara Larrondo Ureta, Jordi Morales-i-Gras

“…The findings suggest that while these actions attract considerable attention, they may also contribute to a distorting effect associated with the increasingly prevalent paradigm of “climate obstructionism”, by shifting the focus away from substantive climate action towards divisive public discourse. …”
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SVF: Support Vector Federation by Mirko Polato, Roberto Esposito, Lorenzo Sciandra

“…This study addresses and overcomes this limitation by proposing an innovative approach: instead of sharing weight vectors, we advocate sharing support vectors while safeguarding client data privacy through vector perturbation. …”
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Econometric modeling for proactive risk management of financial failure in Moroccan SMEs: a stepwise logistic regression approach in python by Dina Ait Lahcen, Nour-Eddin Amghar

“…While the limited sample size is a constraint, the results underscore the continued relevance of traditional financial indicators in early warning systems. …”
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Diabetes diagnosis using a hybrid CNN LSTM MLP ensemble by Yanmin Fan

“…Convolutional neural network (CNN) is the first neural network utilized for extracting the spatial characteristics of the data, while Long Short-Term Memory (LSTM) networks—more specifically, an LSTM Stack—are used to comprehend the time-dependent flow of the data based on medical information from patients. …”
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6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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Digitalization of human resource management: current trends and challenges for Russian enterprises by Mikhail K. Chernyakov, Irina A. Chernyakova

“…These include employee resistance to change, cybersecurity risks, the need to revise labor standards, and ethical concerns related to the use of AI algorithms. Special attention is given to regional specifics: while large companies actively adopt innovations, small and medium-sized businesses lag due to high technology costs and a shortage of qualified personnel. …”
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Collocations with the Nomination ‘‘Russia’’ in the Corpus of Finno-Ugric Internet Travelogues by Natalya A. Osmak

“…The data obtained through sentiment analysis of contexts and their expert evaluation may be used in the further development of algorithms for automatic text sentiment analysis.…”
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Profiling Astroturfers on Facebook: A Complete Framework for Labeling, Feature Extraction, and Classification by Jonathan Schler, Elisheva Bonchek-Dokow

“…We then applied and compared several algorithms in the classification stage, and achieved improved results, with an F₁ score of 77% and accuracy of 92%.…”
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Liftable Point-Line Configurations: Defining Equations and Irreducibility of Associated Matroid and Circuit Varieties by Oliver Clarke, Giacomo Masiero, Fatemeh Mohammadi

“…As corollaries, we provide a geometric representation for the defining equations of two specific examples: the quadrilateral set and the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>×</mo><mn>4</mn></mrow></semantics></math></inline-formula> grid. While the polynomials for the latter were previously computed using specialized algorithms tailored for this configuration, the geometric interpretation of these generators was missing. …”
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Trajectory Aware Deep Reinforcement Learning Navigation Using Multichannel Cost Maps by Tareq A. Fahmy, Omar M. Shehata, Shady A. Maged

“…Deep reinforcement learning (DRL)-based navigation in an environment with dynamic obstacles is a challenging task due to the partially observable nature of the problem. While DRL algorithms are built around the Markov property (assumption that all the necessary information for making a decision is contained in a single observation of the current state) for structuring the learning process; the partially observable Markov property in the DRL navigation problem is significantly amplified when dealing with dynamic obstacles. …”
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