Research on the Estimation Model of Electrical Parameters of Silver-Based Contacts Based on Surface Morphology by Chao Wang, Xiancheng Wang, Chengjun Guo

“…Parameter optimization iterations and parameter space distribution optimization are performed using a decision tree, and the optimized predictive model forecasts specific electrical parameter values. …”
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Study of the Effectiveness of Drugs Based on Molecular Complexes of Adenosine-polymer on the Model of Thermal Burn by E. D. Semivelichenko, A. A. Ermolaeva, V. V. Ponomarenko, A. V. Novoselov, G. A. Plisko, D. Yu. Ivkin, V. G. Antonov, V. E. Karev, I. A. Titovich, A. V. Eremin

“…Experimental substances based on aqueous solutions of adenosine-polymer MK showed a moderate wound healing effect comparable to the reference drug, which, however, is of sufficient interest for further study of such compositions, or their modified versions with the addition of antimicrobial components on thermal burn models, in order to creation of new, more effective drugs for the healing of wound surfaces.…”
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Modeling the Higher Heating Value of Spanish Biomass via Neural Networks and Analytical Equations by Anbarasan Jayapal, Fernando Ordonez Morales, Muhammad Ishtiaq, Se Yun Kim, Nagireddy Gari Subba Reddy

“…The optimized ANN achieved strong predictive accuracy (validation R² ≈ 0.81; mean squared error ≈ 1.33 MJ/kg; MAE ≈ 0.77 MJ/kg), representing a substantial improvement over 54 analytical models despite the known complexity and variability of biomass composition. …”
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Integrated modeling of RF-induced tungsten erosion at ICRH antenna structures in the WEST tokamak by A. Kumar, W. Tierens, T. Younkin, C. Johnson, C. Klepper, A. Diaw, J. Lore, A. Grosjean, G. Urbanczyk, J. Hillairet, P. Tamain, L. Colas, C. Guillemaut, D. Curreli, S. Shiraiwa, N. Bertelli, the WEST Team

“…Model predictions using a plasma composition of 1% oxygen and 99% deuterium show good agreement with observed W  −  I (400.9 nm) emission for discharge #57877, supporting the accuracy of the STRIPE framework. …”
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Categorization of Residential Appliances Using ZIP Load Modeling and Conservation Voltage Reduction Analysis by Mithila Seva Bala Sundaram, Wai Tong Chor, Jeyraj Selvaraj, Ab Halim Abu Bakar, ChiaKwang Tan

“…The study’s findings demonstrate a strong association between the appliance load composition determined by the ZIP load model and CVR_f. …”
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Modelling a Gasification Process for Agricultural Waste Using Gasds and Validation with Experimental Data by Muhammad S. Mansha, Francesco Negri, Cristina Moliner, Flavio Manenti, Elisabetta Arato

“…The results demonstrates that GasDS reliably predicts key gasification products trends validating the model’s accuracy. By refining the model and incorporating diverse feedstocks, its predictive accuracy might be enhanced, thereby optimizing waste conversion for improved energy efficiency. …”
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High entropy alloy property predictions using a transformer-based language model by Spyros Kamnis, Konstantinos Delibasis

“…Abstract This study introduces a language transformer-based machine learning model to predict key mechanical properties of high-entropy alloys (HEAs), addressing the challenges due to their complex, multi-principal element compositions and limited experimental data. …”
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Influence of high power ultrasound on rheological and foaming properties of model ice-cream mixtures by Verica Batur, Vesna Lelas, Anet Režek Jambrak, Zoran Herceg, Marija Badanjak

“…Also, ice cream mixtures having higher amount of proteins in composition had shown higher foam stability. It has been determined that optimal treatment time is 10 minutes.…”
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Data-Augmented Deep Learning Models for Assessing Thermal Performance in Sustainable Building Materials by Ana Carolina Rosa, Carles Mateu, Assed Haddad, Dieter Boer

“…Using inputs such as mass composition and density, the model outputs compressive strength and thermal conductivity. …”
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Models and algorithms for decision support and their use in the simulator training of air traffic control specialists by A. M. Matskevich

“…Additionally, the weaknesses of modern simulator training were identified, associated with the significant labor costs for instructors and the obvious deficiency of reserves for expanding the typical composition of risk events. With reference to the stated above, the key characteristics of an optimally built training complex were worked out, based on the use of modern decision-making support systems in the process of air traffic control specialists training. …”
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Evaluating the Wound Healing Activity of Fabricated Stingless Bee Honey Hydrogels in an Animal Model by Mohd Azri Abd Jalil, Hazrina Hadi, Muhammad Lokman Md Isa, Umar Azhan, Kamarul Ariffin Khalid, Md Abul Barkat

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High-throughput atomistic modeling of nanocrystalline structure and mechanics of calcium aluminate silicate hydrate by Yunjian Li, Cheng Chen, Zhenning Li, Zongjin Li

“…Abstract Although aluminum-containing cements have gained attention as environmentally friendly construction materials, the nanocrystalline structure and mechanical behavior of their primary hydration product, calcium aluminate silicate hydrate (C-A-S-H), remain poorly understood due to its complex chemical composition and structural disorder. Here, we present a high-throughput atomistic modeling framework to systematically investigate the structural and mechanical properties of C-A-S-H across a broad range of Ca/Si (1.3–1.9) and Al/Si (0–0.15) ratios. …”
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Investigation of the Fracturing Effect Induced by the Disturbing Stress of Hydrofracturing Using the Bonded-Particle Model by Xin Zhang, Yuqi Zhang, Bingxiang Huang

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Middle School Classroom Furniture Evaluation Model Based on Combinatorial Weighting of Game Theory by Yu Liang, Yihui Yan, Huiyuan Guan

“…To address this, this study focuses on the “demand-configuration” contradiction and constructs a composite evaluation model integrating the “game theory combined weighting method - fuzzy comprehensive evaluation method - quadrant diagram model”. …”
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Hydrogen Enhancement in Syngas Through Biomass Steam Gasification: Assessment with Machine Learning Models by Yunye Shi, Diego Mauricio Yepes Maya, Electo Silva Lora, Albert Ratner

“…Artificial intelligence (AI), particularly supervised machine learning, has revolutionized the biofuel industry by enhancing feedstock selection, predicting fluid compositions, optimizing operations, and streamlining decision-making. …”
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Thermal Degradation of β-Carotene from Macauba Palm: Mathematical Modeling and Parameter Estimation by Pedro Prates Valério, Amanda Lemette Brandão, Jesus Maria Frias Celayeta, Erika Cristina Cren

“…The kinetic parameters from both models were estimated through a hybrid optimisation method using the Particle Swarm Optimization and the Gauss-Newton method, followed by statistical analyses. …”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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Research on real time measurement model and measurement system for gas concentration in extraction drilling by Dayang Yu, Junhao Zhu, Xing Li, An He, Huaiqian Liu, Changjiang Chen, Yong Liu

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A mathematical model of the copper plating process in restoration of road transport equipment parts by A. S. Ianuta, G. S. Zadorozhnii, Yu. V. Shtephan

“…The deposition conditions in order to obtain the most productive technology for restoring collectors of electric motors of motor vehicles by depositing a copper coating have been optimized. According to the obtained model, the optimal values of the deposition conditions for obtaining the maximum deposition rate are the electrolyte temperature of 35...40 ° C, the cathode current density of more than 5 A/Dm2, the concentration of copper sulfate 200...250 g/l, the concentration of sulfuric acid 40...70 g/l.…”
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Robust asphaltene onset pressure prediction using ensemble learning by Jafar Khalighi, Alexey Cheremisin

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