Desempenho de cultivares de cebola em função do manejo da irrigação por gotejamento Performance of onion cultivars as a function of drip irrigation management by Renato C Vilas Boas, Geraldo M Pereira, Rovilson J. de Souza, Rodrigo Consoni

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Spatiotemporal Evolution and Multi-Driver Dynamics of Sea-Level Changes in the Yellow–Bohai Seas (1993–2023) by Lujie Xiong, Fengwei Wang, Yanping Jiao, Yunqi Zhou

“…Temporal and spatial variations were examined through nonlinear least squares fitting to capture interannual variability and decadal amplitude distributions. Empirical orthogonal function (EOF) analysis identified the first three modes, explaining 90.40%, 2.78%, and 1.47% of the total variance, respectively, and their spatial patterns and temporal coefficients were derived. …”
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Reliability and Accuracy of Ultrasonographic Muscle Thickness Measurements: Evaluating Key Postural Stabilisers in Rehabilitation by Arkadiusz Żurawski, Natalia Barańska, Aleksandra Tomala, Edyta Majorczyk, Joanna Macierzyńska

“…Its capacity to provide real-time visualisation of muscle structure and function underpins its utility in clinical practice and scientific research. …”
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MULTI-OBJECTIVE OPTIMIZATION OF VEHICLE/TRACK PARAMETERS BASED ON RBF NEURAL NETWORK SURROGATE MODEL by XIAO Qian, LUO Chao, OUYANG ZhiXu, CHANG Chao, LUO JiaWen

“…The RBF（ Radial Basis Function） neural network surrogate model that employed to explore the multi-objective optimization problems of vehicle and track parameters is to improve the dynamic performance of vehicles. …”
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Defining the logistics performance as factor of production: an evidence based analysis from developing countries by Zunaira Khadim, Irem Batool, Minhas Akbar, Veronika Zidova, Asokan Vasudevan, Jin Zhang

“…The other control variables are capital stock, employed labor force, and financial development. …”
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Development of Recurrent Neural Networks for Thermal/Electrical Analysis of Non-Residential Buildings Based on Energy Consumptions Data by Elisa Belloni, Flavia Forconi, Gabriele Maria Lozito, Martina Palermo, Michele Quercio, Francesco Riganti Fulginei

“…This study proposes a neural network-based approach to characterize the thermal–energy relationship in commercial buildings, aiming to provide an efficient and scalable solution for performance prediction. …”
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Predicting and Controlling Multiple Transmissions of Rotavirus Using Computational Biomedical Model in Smart Health Infrastructures by Titus Ifeanyi Chinebu, Kennedy Chinedu Okafor, Omowunmi Mary Longe, Kelvin Anoh, Henrietta Onyinye Uzoeto, Victor Onukwube Apeh, Ijeoma Peace Okafor, Bamidele Adebisi, Chukwunenye Anthony Okoronkwo

“…An efficiency test is conducted using RI control parameters B and V. …”
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Sensitivity Analysis of Distribution Network Reconfiguration Optimization for Electric Vehicle and Renewable Distributed Generator Integration by Mahmoud Ghofrani

“…This approach aims to minimize power losses and enhance overall operational efficiency. To model the variability of wind and solar DGs, probability distribution functions (PDFs) are employed, which allow for a more accurate representation of their performance. …”
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An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system by Md. Naiem-Ur-Rahman, Md. Mahmudul Hasan, Afsana Mimi Raka, Md. Fayzur Rahman, Md. Masud Rana, Ahmed Al Mansur, Md. Abdur Razzak

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Integrated deep eutectic solvent (DES) extraction and microwave-assisted process for algal protein extraction: Process improvement, characterizations, functional properties, and an... by May Thu Zin, Thida Kaewkod, Jeeraporn Pekkoh, Wasu Pathom-aree, Supakit Chaipoot, Gochakorn Kanthakat, Phisit Seesuriyachan, Yan-Yu Chen, Kuan Shiong Khoo, Benjamas Cheirsilp, Sirasit Srinuanpan

“…These findings highlight the potential of Spirulina and Chlorella proteins as sustainable, algal-based ingredients for functional foods and nutraceutical applications while addressing challenges in optimization, scalability, and biomass variability.…”
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Logical minimization for combinatorial structure in FPGA by P. N. Bibilo, Yu. Yu. Lankevich, V. I. Romanov

“…The paper describes the research results of application efficiency of minimization programs of functional descriptions of combinatorial logic blocks, which are included in digital devices projects that are implemented in FPGA. …”
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DESIGN OF BAND-PASS FILTERS WITH NON-EQUIRIPPLE FREQUENCY RESPONSES by Evgeniy N. Chervinskiy

“…The equations are formed by equating coefficients of variables raised to the same powers in transfer function (TF) expressions of designed and realized filters. …”
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Mathematical modeling describing the performance of open loop multivariable vapor compression chiller model: implications for sustainable HVAC in social housing development by Basim Touqan, Basim Touqan, Muna Salameh

“…IntroductionThis study introduces a simplified multi-variable state-space model of a vapour compression chiller system, focusing on key components such as the condenser and evaporator.MethodsThe model is based on a previously validated state-space framework and has been further developed to generate a transfer function matrix with two inputs (refrigerant and cold carrier flow rates) and two outputs (cooling capacity and outlet temperature). …”
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Stochastic solutions of the geophysical KdV equation: Numerical simulations and white noise impact by Areej A. Almoneef, Abd-Allah Hyder, Mohamed A. Barakat, Abdelrheem M. Aly

“…This research explored stochastic soliton and periodic wave (SPW) solutions for the geophysical Korteweg-de Vries (KdV) equation with variable coefficients, incorporating the effects of Earth's rotation, fluid stratification, and topographical variations. …”
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An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control by Caixia Huang, Wu Tang, Jiande Wang, Zhiyong Zhang

“…By estimating these maximum speeds and transmitting them to individual follower vehicles via vehicle-to-vehicle communication, the model promotes smooth acceleration and deceleration behavior, reduces headway variability, and mitigates shockwave propagation within the platoon. …”
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Research on Small-Target Detection of Flax Pests and Diseases in Natural Environment by Integrating Similarity-Aware Activation Module and Bidirectional Feature Pyramid Network Mod... by Manxi Zhong, Yue Li, Yuhong Gao

“…Additionally, this paper adopts the EIOU loss function to further optimize the model’s bounding box regression, reducing the distortion of bounding boxes caused by high sample variability. …”
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Effects of stand age and soil microbial communities on soil respiration throughout the growth cycle of poplar plantations in northeastern China by Xiangrong Liu, Xiangrong Liu, Lingyu Hou, Lingyu Hou, Changjun Ding, Changjun Ding, Xiaohua Su, Xiaohua Su, Weixi Zhang, Weixi Zhang, Zhongyi Pang, Yanlin Zhang, Yanlin Zhang, Qiwu Sun, Qiwu Sun

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Forecasting Industrial Electricity Consumption in Iran: A Novel Hybrid Approach for Sustainable Energy Management by Mohsen Rezaei

“…Accurately predicting industrial electricity consumption is essential for optimizing energy efficiency, and reducing costs in industrial operations. …”
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Comparative Evaluation of Feed-Forward Neural Networks for Predicting Uniaxial Compressive Strength of Seybaplaya Carbonate Rock Cores by Jose W. Naal-Pech, Leonardo Palemón-Arcos, Youness El Hamzaoui

“…This work presents a comprehensive evaluation of four feed-forward artificial neural network (ANN) architectures—radial basis function (RBF), Bayesian regularized (BR), scaled conjugate gradient (SCG), and Levenberg–Marquardt (LM)—to predict UCS from three readily measured variables: water content, interconnected porosity, and real density. …”
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A Novel Method for Inverting Deep-Sea Sound-Speed Profiles Based on Hybrid Data Fusion Combined with Surface Sound Speed by Qiang Yuan, Weiming Xu, Shaohua Jin, Xiaohan Yu, Xiaodong Ma, Tong Sun

“…By constructing a high-resolution regional sound speed field through WOA23 and historical SSP fusion, this method effectively mitigates spatiotemporal heterogeneity and seasonal variability. The artificial lemming algorithm (ALA) is introduced to optimize the inversion of empirical orthogonal function (EOF) coefficients, enhancing global search efficiency while avoiding local optimization. …”
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