Influence of EEG-based functional connectivity and inhibitory control on educational web search performance among adolescents by Надежда Владимировна Сутормина

“…EEG was recorded at rest with eyes closed to determine the metrics of functional connectivity in the EEG sensor space. The following connectivity metrics were used for further analysis: global efficiency, modularity, and assortativity. …”
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Unveiling potential: Hybrid nanofluid-driven strategies for maximizing electrical efficiency in Photovoltaic Thermal Systems with trapezoidal flow channel for coolant purposes by A.A. Alderremy, Abid A. Memon, A.M. Obalalu, T.H. El-Ghareeb, Amsalu Fenta

“…The PV/T system features a simple configuration, with mono-crystalline silicon above the flow channel, copper functioning as the absorber, and a trapezoidal-shaped flow channel. …”
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A Focusing Algorithm in Automatic Microscope by LIANG Long-kai, ZHAO Jing, HE Yong-jun

“…Then the proposed evaluation functions are applied to realize the variable step climbing search strategy． …”
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On Estimation of Distribution Function Using Dual Auxiliary Information under Nonresponse Using Simple Random Sampling by Saddam Hussain, Mi Zichuan, Sardar Hussain, Anum Iftikhar, Muhammad Asif, Sohail Akhtar, Sohaib Ahmad

“…In this paper, we proposed two new families of estimators using the supplementary information on the auxiliary variable and exponential function for the population distribution functions in case of nonresponse under simple random sampling. …”
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Finding quadratic underestimators for optimal value functions of nonconvex all-quadratic problems via copositive optimization by Markus Gabl, Immanuel M. Bomze

“…Modeling parts of an optimization problem as an optimal value function that depends on a top-level decision variable is a regular occurrence in optimization and an essential ingredient for methods such as Benders Decomposition. …”
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Efficient Solar Cell Design through Grey Wolf Optimization: Multi-Layer Thickness Optimization for Enhanced Short-Circuit Current Density by Hamed Kargaran, Hassan Alipour, Maryam Amirhoseiny, Ghasem Alahyarizadeh

“…Optimization problems can be classified as discrete or continuous, depending on the nature of the decision variables. Using continuous algorithms for problems that are inher-ently discrete can pose challenges in achieving optimal efficiency. …”
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Method and Algorithm for Processing Large Volume Images by O. N. Andreichuk, N. I. Listopad

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Multi-function composite data generation and PIMamba model for fault diagnosis in sucker-rod pumping wells by Senhao Ren, Wenqiang Tang, Chao Ma, Li Hou, Xiaodong Chen, Jiashan Lin, Jie Yang, Yun Yang, Xiao Huo, Guoxin Li, Daowei Zhang

“…To overcome these challenges, we propose a multi-function composite data generation paradigm that integrates diverse functional characteristics, generating 11 classes of highly interpretable single-condition images as training data for a prior model. …”
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A MATHEMATICAL APPROACH TO INVESTMENT WITH CHARGE ON BALANCE AND VOLUNTARY CONTRIBUTIONS UNDER WEIBULL MORTALITY FORCE FUNCTION by Edikan Edem Akpanibah, Peter Benneth, Ase Matthias Esabai

“…By applying the variable separation technique and mean variance utility, the optimal control strategy (OCS) and the efficient frontier are obtained. …”
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ANALYTICAL SYNTHESIS OF FORCED PULSE ELECTRONIC DRIVE CONTROL OF A TRACKING SYSTEM by A. S. Abufanas, A. A. Lobaty, Y. F. Yacina

“…Key words: forced control, target function, electric drive, pulse train. The use of forced control makes it possible to synthesize the control law in the form of a sequence of rectangular pulses of constant amplitude determined by the power source, variable duty cycle and polarity. …”
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Software-Defined Workpiece Positioning for Resource-Optimized Machine Tool Utilization by Robin Ströbel, Yannik Probst, Louisa Hutt, Jürgen Fleischer

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Evaluation the correlation between Inulin and Cystatin C with kidney function tests and GFR in patients with renal disorders by Nawar Mohsin Abd-alaziz, Wasan Nazhan Hussein

“… Background: Kidneys are important organs in the human body because of their great importance in assisting the body to remove waste products that resulting from food metabolism through renal filtration of blood plasma from unwanted substances and excreted through diuresis and recover substances that body needs to the blood, relative effectiveness of the kidney can be estimated by measuring the efficiency of glomerular filteration rate (GRF), represented by amount of inulin filtrate into renal tubules for a specified period of time, any difference in normal value indicates the presence of a disorder in the kidney, which affects on performance of its functions and occurrence of imbalance in internal environment of the body, and leads to disrupting functions of other parts of the body, measuring rate of renal filtration is one of the best ways to know function of the kidneys and diagnose various kidney diseases and prevent their development. …”
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Functional role of cell classes in monkey prefrontal cortex after learning a working memory task by Amirreza Asadi, Christos Constantinidis, Mohammad Reza Daliri

“…Another broad-spiking subtype showed decreased baseline firing rate and variability, which may optimize neural coding efficiency. …”
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Impact of Standardised Order Sets on Functional Outcome of Acute Ischaemic Stroke Patients: A Research Protocol by Sarang Dilip Videkar, Tushar Patil

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Coordinated regulation of water use-efficiency-cost in a winter wheat-summer maize rotation system and optimization of water allocation strategies by Li Zhao, Congying Han, Yinong Li, Baozhong Zhang, Yulu Zheng, Jiabing Cai

“…A multi-objective nonlinear programming model was developed, incorporating triangular fuzzy numbers, accuracy functions, and credibility constraints, to balance actual yield (AY), irrigation water productivity (IWP), and total cost (TC). …”
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Identification of time-varying parameters of a monthly Budyko function in US MOPEX catchments and its implications by Weibo Liu, Pan Liu, Lei Cheng, Xiaojing Zhang, Liting Zhou

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Innovative machine learning-based prediction of early airway hyperresponsiveness using baseline pulmonary function parameters by Hua Yang, Xingru Zhao, Zhuochang Chen, Lihong Yang, Guihua Zhao, Chenxiao Xu, Jinyi Xu

“…This study explores the potential of baseline pulmonary function parameters, particularly small airway indices, in predicting AHR and develops a machine learning-based model to improve screening efficiency and reduce unnecessary BPT referrals.MethodsThis retrospective study analyzed baseline pulmonary function data and BPT results from Henan Provincial People’s Hospital (May to September 2024). …”
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Main indicators of the credit organizations of the Russian Federation: vectors of changes by T. V. Grishina

“…In recent years, changes in the structure of the banking system and the profi tability of operations conducted by banks. Analysis of the functioning of the system shows a reduced role of banking indicators in the formation of the Russian GDP. …”
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Detecting changes in retinal function: Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS). by Haogang Zhu, Richard A Russell, Luke J Saunders, Stefano Ceccon, David F Garway-Heath, David P Crabb

“…Furthermore, the spatial correlation utilised in ANSWERS was shown to improve the ability to detect deterioration, compared to equivalent models without spatial correlation, especially in short follow-up series. ANSWERS is a new efficient method for detecting changes in retinal function. …”
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Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

“…The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.MethodsWe conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes. …”
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