Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome by Bin Liu, Zhiqi Mao, Xinyuan Yan, Hang Yang, Junpeng Xu, Zhebin Feng, Yanyang Zhang, Xinguang Yu

“…The results indicated that HIG showed a higher clustering coefficient, longer characteristic path length, lower small-world index, and lower global efficiency compared with LIG. …”
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Impact of coffee exports on economic growth in Ethiopia; An empirical investigation by Netsanet Gizaw, Jemal Abafita, Tesfaye Melaku Merra

“…The study employed an extended generalized Cobb–Douglas production function model using data from the National Bank of Ethiopia and World Bank data base from 1980 to 2017. …”
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An evolutionary-based optimization algorithm for truss sizing design by Pham Hoang Anh

“…Here, the constraints and objective function are treated separately so that both function and constraint evaluations can be saved. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…Deep SORT is employed for efficient vehicle tracking, while CSRNet facilitates high-density vehicle counting. …”
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clonevdjseq: A workflow and bioinformatics management system for sequencing, archiving, and analysis of VDJ sequences from clonal libraries by Keith Mitchell, Samuel Hunter, Lutz Froenicke, Karl Murray, Matthew Settles, James S. Trimmer

“…The results of this effort has yielded sequences used to develop functional recombinant monoclonal antibodies and single chain variable fragments as a part of the NeuroMabSeq initiative where thousands of hybridoma samples were processed (Mitchell et al. in Sci Rep 13(1):16200, 2023) as well as provide additional modeling and extensibility to other modalities. …”
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Improving Electrical Distance Accuracy for Cable Fault Location Based on the Prony Method by Xiang Ren, Zhiqiang Feng, Kai Zhou, Xueming Zhou, Jianjun Yuan, Yefei Xu, Li Zhang

“…By establishing a frequency-variable coupling model containing the transfer function of the cable with double joint structure, studying the mapping relationship between the cable attenuation constant and the electromagnetic wave velocity, and adopting the Prony estimation method combined with the singular value decomposition noise reduction algorithm to achieve the extraction of the attenuation constant and the decoupling of the segmented wave velocity, thus improving the electrical accuracy of fault location. …”
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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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Renal Biopsy Pathological Tissue Segmentation: A Comprehensive Review and Experimental Analysis by Yan Liu, Taiping Wang, Xinxin He, Wei Wang, Qiang He, Juan Jin

“…Traditional renal biopsy pathological analysis relies heavily on subjective judgment by pathologists, which is time-consuming and susceptible to inter-observer variability, especially in segmenting glomeruli, renal tubules, and renal vessels. …”
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Grid-connected PV inverter system control optimization using Grey Wolf optimized PID controller by Monika Gupta, P. M. Tiwari, R. K. Viral, Ashish Shrivastava, Basem Abu Zneid, Iryna Hunko

“…Conventional controllers such as P and PI are widely used in PV applications due to their simplicity, but they exhibit notable limitations in dynamic environments, including increased Total Harmonic Distortion (THD), slower transient response, and poor voltage regulation—particularly under variable irradiance conditions. The proposed GWO-PID method overcomes these limitations by leveraging the GWO algorithm’s global search capability to dynamically optimize the PID gains (Kp, Ki, Kd) based on a composite fitness function that minimizes Mean Squared Error (MSE) and THD. …”
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Research and Development Expenditures and Economic Growth in the EU: A Panel Data Analysis by Freimane Rita, Bāliņa Signe

“…The estimated model is the production function type standard growth model extended with R&D stock variable. …”
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PENDUGAAN FUNGSI KEUNTUNGAN DAN RISIKO USAHATANI SAWI PAHIT (Brasischa juncea) DI DESA SAMBIREJO KECAMATAN SELUPU REJANG KABUPATEN REJANG LEBONG by Satria Putra Utama, Redy Badrudin, Merry Rien

“…Result of this research showed that, the average of farmer’s profit from the bitter mustard farming in sambirejo village, rejang lebong region on planting season of May/Juni are Rp.914.382,33/farm or Rp.4.747.964,79/Ha, and planting season of Feb/Maret are Rp.1.025.509,72/farm or Rp.6.698.378,53/Ha. Variable which influenced negatively and  significantly  on profit function of bitter mustard farming in sambirejo village, Selupu Rejang district of Rejang Lebong region on planting season of Feb/Maret and May/Juni are the land fare (X8*), production amount (X9*) and dummy variable (season plant). whereas, variables which influenced negatively and unsignificantly are the price of seed (X1*), the price of urea (X2*), but the price of dursban (X5*) influence positively and also has tendency to increase the profit of bitter mustard profit. …”
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Dual-Stream Enhanced Deep Network for Transmission Near-Infrared Dorsal Hand Vein Age Estimation with Attention Mechanisms by Zhenghua Shu, Zhihua Xie, Xiaowei Zou

“…Simultaneously, another deep residual network is leveraged to strengthen the representation ability on subtle dorsal vein textures. Moreover, variable activation functions and pooling layers are integrated into the respective streams to enhance the nonlinearity modeling of the dual-stream model. …”
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Nonparametric Test for Logistic Regression with Application to Italian Enterprises’ Propensity for Innovation by Stefano Bonnini, Michela Borghesi

“…In this work, a nonparametric method is proposed to jointly test the significance of the regression coefficient estimates in a logistic regression model and identify which explanatory variables are effective in predicting the binary response. …”
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THE USE OF CORRELATION ANALYSIS OF TWO-DIMENSION STOCHASTIC PROCESS FOR HELICOPTER MAINTENANCE WORKABILITY ESTIMATION by Y. M. Chinyuchin, A. S. Solov’ev

“…The linear correlated dependence is considered as linear or anyconnection close to it between two variables for which the correlated analysis theorem is true.The algorithm of calculated program complex for helicopter maintenance workability estimation consists of five steps: choice of equipment that needs to be installed on the helicopter; correlation coefficient calculation for helicopters having this equipment and revealing of optimal variants of location; zone partition of the developed helicopter and analysis of possi- ble disposal of clusters in optimal order; disposal of clusters on the designed helicopter; correlation coefficient calculation, direct regression construction for the designed helicopter and comparison of these readings with helicopters-analogues. …”
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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…These parameters function as decision variables, and the objective function aimed for minimization is the sum square error (SSE) between the predicted and actual measured cell voltages. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Elastostatic analysis of tapered FGM beams with spatially varying material properties by Justín Murín, Stephan Kugler, Juraj Paulech, Juraj Hrabovský, Vladimír Kutiš, Herbert Mang, Mehdi Aminbaghai

“…In this article an effective method for elastostatic analysis of tapered beams made of functionally-graded material (FGM) is presented. The spatially variable stiffness of the beam is the consequence of the continuous longitudinal variability of the cross-sectional dimension, accompanied by the variability of the material properties in three orthogonal directions. …”
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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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An inclusive solution based on grey water footprint for performance evaluation of industrial wastewater treatment systems by Keivan Arastou, Ali Dehnavi, Shervin Jamshidi

“…These advantages are critical for assessing an industrial WWTP treating complex wastewater, with hazardous pollutants and variable inflow. Moreover, we introduced four innovative criteria based on GWF and improved it as a multi-functional index. …”
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