A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. …”
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A LINEAR SIMULATION MODEL FOR OPTIMIZING CROP STRUCTURE IN ORDER TO MAXIMIZE INCOME IN A VEGETAL AGRICULTURAL FARM by Sorin IONITESCU

“…The model included: the 8 unknown variables for the cultivated area with 8 crops: wheat, rye, barley, peas, rape, soybean, maize and sunflower, 14 restrictions regarding Diesel fuel, fertilizers, herbicides, total surface, expenditures, income, and area per each crop, and objective - function f(Max) Income. …”
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Sensitivity Analysis of the Thermal Structure Within Subduction Zones Using Reduced‐Order Modeling by Gabrielle M. Hobson, Dave A. May

“…Our analysis highlights the strong effect of variability in the apparent coefficient of friction, with previously published ranges resulting in pronounced variability in estimated rupture limit depths.…”
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Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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PM21-particle stimulation augmented with cytokines enhances NK cell expansion and confers memory-like characteristics with enhanced survival by Jeremiah L. Oyer, Tayler J. Croom-Perez, Md Faqrul Hasan, Javier A. Rivera-Huertas, Sarah B. Gitto, Joanna M. Mucha, Xiang Zhu, Deborah A. Altomare, Robert Y. Igarashi, Alicja J. Copik

“…This is typically done by ex vivo stimulation with cytokines to enhance functionality or expansion for 10-14 days to increase both their activity and quantity. …”
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Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times by N. Micheal Mathavavisakan, K. Indhira, Aliakbar Montazer Haghighi

“…Using the supplementary variable technique (SVT), the probability generating functions (PGFs) and steady-state probabilities for the system's states, have been obtained enabling the development of comprehensive performance measures. …”
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Optimal Power Flow using An Optimally Tuned Pattern Search Algorithm by Firmansyah Nur Budiman, Taufal Hidayat, Rudi Uswarman

“…The tuning process, performed using the classical interior point method (IPM), provides optimal initial control variable values for the standard pattern search (PS) algorithm. …”
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Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…Demonstrated effectively in China Southern Grid’s island microgrid setup, LE-LFC emerges as an advanced solution for modern grid variability, offering superior robustness, adaptability, and learning speed, thus enabling flexible and efficient energy system management.…”
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Experimental Optimization of the Energy Characteristics of a Ground Penetrating Radar with Continuous Linear-Frequency-Modulated Radiation by I. Yu. Malevich, A. S. Lopatchenko

“…The responses of the system to an increase in the durtion of the probing pulse and a change in the type of window function were evaluated. An empirical dependence of signal losses during propagation in radio channels of LFM GPR has been established. …”
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Reconfiguration of dynamic brain networks in heart failure with preserved ejection fraction: Linking neurovascular coupling and cardiac dysfunction by Xiulin Liang, Qinghua Zhang, Chuanlong Zhang, Jingjing Liu, Pengcheng Sang, Qing Mao, Lei Wang

“…Results: (1) Static network topology properties exhibited significantly decreased local network efficiency among patients with HFpEF. The connectivity strength and information processing efficiency were diminished in the left parahippocampal gyrus, left cingulate gyrus, and right insular gyrus brain regions, and improved in the left thalamus, right fusiform gyrus, and right precuneus regions. (2) Dynamic network topology properties of patients with HFpEF showed decreased variability in critical nodes and brain subregions (e.g., the superior frontal gyrus, left amygdala, and left fusiform gyrus) and compensatory increases in the variability of specific regions (e.g., right insular gyrus, right postcentral gyrus, and right temporal gyrus). (3) In HFpEF, the static and dynamic functional brain network topology properties of the fusiform gyrus, cingulate gyrus, superior temporal gyrus, precuneus, parahippocampal gyrus, insular gyrus, and amygdala regions were significantly correlated with cardiac structural and functional indices, such as LVDd, LVMI, and E/e′ ratio. …”
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Modeling and optimizing the atmospheric water harvesting System: Application of PAN-PDMS polymeric membrane by Sepehr Sanaye, Pouya Rezvani Gil Kalaee, Javad Mahmoudimehr

“…The water production rate and the total annual cost rate were considered as two objective functions. Also, five design variables are selected after considering their effects on the objective functions. …”
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Classification of traffic accidents’ factors using TrafficRiskClassifier by Wei Sun, Lili Nurliyana Abdullah, Fatimah binti Khalid, Puteri Suhaiza binti Sulaiman

“…Furthermore, the TrafficRiskClassifier model delineates a functional nexus between accident risk and variables such as weather, road conditions, and personal factors, employing a polynomial regression approach. …”
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Indirect sliding mode adaptive fractional order nonlinear observer based controller with fractional order single-ended primary inductor converter by Sena Alemu Wondimu, Desalegn Tsega Dagne, Kinde Anlay Fante

“…The SEPIC converter is non-inverting and can both step up and step down the voltage with low ripple current. It is a nonlinear variable structure that uses sliding mode control (SMC) for stable operation. …”
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Field Testing of a Smart Geomat Based on Fiber Optic Sensors and Sensor Fusion for Levee Monitoring by Manuel Bertulessi, Francesca Ceccato, Francesco Ioli, Federico Barbieri, Livio Pinto, Paolo Simonini, Giovanni Menduni

“…ABSTRACT Real‐time monitoring of the functionality of river embankments, especially during flood events, is an increasingly important topic in the new scenario outlined by climate change. …”
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Office-in-the-Loop: an investigation into Agentic AI for advanced building HVAC control systems by Tomoya Sawada, Masahiro Mizuno, Takaomi Hasegawa, Keiichi Yokoyama, Mayuka Kono

“…Regression analysis confirmed the robustness of our approach against confounding variables like outdoor conditions and occupancy levels. …”
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Achievement motivation and attitude of medical laboratory assistants to continuing education by K. S. Kichukova, T. G. Taneva

“…The applicability of the results is very clearly visible in the formulated thesis of the necessary change in the educational policy in the country through new forms of continuous education of medical laboratory assistants which would update their achievement motivation and would result in increase in the efficiency of their professional functioning.…”
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A self-powered millifluidic device driven by triboelectric generator for the label-free and real-time detection of DNA hybridization by Tara Ghafouri, Sheida Bagherzadeh‑Nobari, Negin Manavizadeh

“…In line with the heterogeneous genoassay modeling, flow variables are tuned to attain the optimal hybridization efficiency equal to 92%. …”
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On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis by Banamali Panigrahi, Saman Razavi, Lorne E. Doig, Blanchard Cordell, Hoshin V. Gupta, Karsten Liber

“…Unlike many methods for explainable artificial intelligence (XAI), this method (a) accounts for complex multi‐variate distributional properties of data, common in environmental systems, (b) offers a global assessment of the input‐output response surface formed by ML, rather than focusing solely on local regions around existing data points, and (c) is scalable and data‐size independent, ensuring computational efficiency with large data sets. We apply this method to a suite of ML models predicting various water quality variables in a pilot‐scale experimental pit lake. …”
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Cross-Sectional Evaluation of Hydroxyapatite-Coated Titanium Implants: Insights into Biocompatibility and Osseointegration by Tayyaba Rafiq, Iqra Amin, Atiq Ur Rehman, Amna Mehwish Ikram, Khurram Anwar, Arsalan Ahmed, Ayesha Ali Khawaja

“…Conclusion: The implant recipients with HA coatings experienced fewer complications and better outcomes in terms of functionality. …”
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Minimally Invasive Surgery in Modern Medicine: A Review of Laparoscopic Techniques, Indications, and Postoperative Outcomes by Maksymilian Czarnota, Martyna Adamowicz, Aleksandra Górniak

“…Elderly and frail patients experienced lower pulmonary morbidity and faster functional return, while paediatric and fertility-preserving gynaecologic procedures maintained safety and sustained quality of life. …”
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