On solutions of certain compatible systems of quadratic trinomial Partial differential-difference equations by R. Mandal, R. Biswas

“…Appl. 483(2), 2020) and then construct some systems of certain quadratic trinomial partial differential-difference equations with arbitrary coefficients. Our objective is to investigate the forms of the finite order transcendental entire functions of several complex variables satisfying the systems of certain quadratic trinomial partial differential-difference equations on $\mathbb{C}^n$. …”
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An Algorithm for the Solution of Integro-Fractional Differential Equations with a Generalized Symmetric Singular Kernel by Sameeha A. Raad, Mohammed A. Abdou

“…Next, to solve this <b>MIE</b>, the authors apply a special technique to separate the variables and produce an integral equation in position with coefficients, in the form of an integral operator in time. …”
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Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation by Gemma Gerber, Ursula M. Scharler

“…However, little information exists on how each LIM-MCMC algorithm parameter affects the degree of empirical data variability introduced into the ensemble. Further, post hoc algorithm quality diagnostics with commonly used trace plots and the coefficient of variation (CoV) rarely address critical aspects of algorithm quality, such as (1) if the returned ensemble successfully targeted the solution space distribution (stationarity), (2) correlation between ensemble solutions (mixing), and (3) if the ensemble contains enough solutions to adequately capture input data variability (sampling efficiency). …”
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Modeling of an automated recruitment planning system for educational organizations by S. A. Mishin, E. Yu. Nikulina, E. A. Rogozin, R. A. Solodukha

“…The advantage of the proposed approach gives a clear idea of the structure and functional purpose of the system.Conclusion. The system will automate the process of recruiting educational organizations in order to increase the efficiency of decision support in the field of training specialists for the Russian Ministry of Internal Affairs.…”
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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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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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Three-dimensional design, simulation and optimization of a centrifugal compressor impeller with double-splitter blades by Mohammadjavad Tasharrofi, Mojtaba Heidarian Shahri, Ali Madadi

“…Since the optimization process only using genetic algorithms is very time-consuming and has high computational costs, artificial neural networks were used to reduce costs. The objective function in this optimization process was to increase efficiency while maintaining the flow rate and pressure ratio at the design point. …”
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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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Multifractal analysis of Bitcoin price dynamics by Cristian Bucur, Bogdan-George Tudorică, Adela Bâra, Simona-Vasilica Oprea

“… This research employs Multifractal Detrended Fluctuation Analysis (MFDFA) to investigate multifractal properties in financial variables, including Bitcoin prices and economic indicators. …”
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Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

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Experimental investigation of solar PVT collector with the dryer on mass and temperature of dried red chili with Machine Learning Models by Miroslav Mahdal, K. Rajathi, Muniyandy Elangovan, Prabhukumar Sellamuthu, Amit Verma

“…Machine learning (ML) models, namely the Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Decision Tree (DT), were used to forecast the temperature and mass dryness variables.The RBF model showed the best performance with 0.98, 0.95, and 0.92 for temperature dryness, above MLP and DM. …”
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Natural assets, changes, and variations of the socioeconomic-environmental systems along the Asian drylands belt by Jiquan Chen, Ranjeet John, Venkatesh Kolluru, Elizabeth A Mack, Peilei Fan, Jing Yuan, Zutao Ouyang, Jingyan Chen, Pavel Groisman, Changliang Shao, Amarjargal Amartuvshin, Garik Gutman

“…We found increased variability as well as spikes in extreme values in each of these three measures of SES function among the 23 PEs over the study period. …”
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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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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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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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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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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

“…Traditional models generally assume a fixed maximum speed within the optimal velocity function, which constrains effective platoon speed regulation across road segments with varying speed limits and lacks adaptability to dynamic scenarios such as changes in the platoon leader’s speed or substitution of the lead vehicle. …”
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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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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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Diabetes mellitus type 2: the relationship of baseline clinical, laboratory and echocardiographic parameters with long-term major adverse cardiovascular events by I. A. Bondar, A. A. Demin, D. V. Grazhdankina

“…The plasma level of the N-terminal propeptide of natriuretic hormone B-type (NT-proBNP) was determined. The variability of fasting blood glucose and intraday glycemic variability were measured by calculating the standard deviation (SD) and the coefficient of variation (CV) of at least 3 blood glucose values for 3 days. …”
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