Exploring patterns of heart rate variability in major depressive disorder: A short-term study in Jaipur, Rajasthan by Sunidhi sharma, Sudhanshu Kacker, Neha Saboo

“…Methods: This observational study was conducted at RUHS College of Medical Sciences and Associated Hospitals, Jaipur, from July 2022 to January 2023, on a major depressive disorder population of either sex in the age group of 20-40 years. Cognitive functions were assessed using a questionnaire, and AD instruments recorded heart rate variability variables (time & frequency domain) using a digital physiograph (MLT004/ST). …”
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Correlation and path analysis of interaction between snap beans yield and its components with crop management by N. Shaban

“…Results showed that fresh weight of pod/studied variant (+++0.99), fresh weight of one pod (+++0.77), fresh weight of pods/ plant (+++0.67), calcium content in bean pods (++0.57), pods number /plant (++0.51), pollen fertility (++0.44) had positive impact on yield. The partial function of the studied parameters on variability of bean yield is 98.9%. …”
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Genetic and molecular basis of abnormal BOLD signaling variability in patients with major depressive disorder after electroconvulsive therapy by Siyu Fan, Yulin Zhang, Rui Qian, Jie Hu, Hao Zheng, Wentao Dai, Yang Ji, Yue Wu, Xiaohui Xie, Si Xu, Gong-Jun Ji, Yanghua Tian, Kai Wang

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An efficient eigenvector-based crossover for differential evolution: Simplifying with rank-one updates by Tae Jong Choi

“…We propose a new approach to enhancing the efficiency of the differential evolution (DE) algorithm, specifically targeting rotational invariance. …”
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On a geometric approach to the estimation of interpolation projectors by Mikhail V. Nevskii, Alexey Y. Ukhalov

“…Here $\sigma S$ is the result of homothety of $S$ with respect to the center of gravity with coefficient $\sigma$. Let $d\geqslant n+1,$ $\varphi_1(x),\ldots,\varphi_d(x)$ be linearly independent monomials in $n$ variables, and $\varphi_1(x)\equiv 1,$ $\varphi_2(x)=x_1,\ \ldots, \varphi_{n+1}(x)=x_n.$ Put $\Pi:=$lin$(\varphi_1,\ldots,\varphi_d).$ The interpolation projector $P: C(\Omega)\to \Pi$ with a set of nodes $x^{(1)},\ldots, x^{(d)} \in \Omega$ is defined by equalities $Pf\left(x^{(j)}\right)=f\left(x^{(j)}\right).$ Denote by $\|P\|_{\Omega}$ the norm of $P$ as an operator from $C(\Omega)$ to $C(\Omega)$ . …”
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Photocatalytic Efficiency of TiO2-Biomass Loaded Mixture for Wastewater Treatment by Devagi Kanakaraju, Soon Pang Wong

“…Surface morphology, functional groups, and elemental analysis supported observations of the ability of TiO2/MSB mixture to remove COD. …”
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Demonstrating Efficient and Robust Bosonic State Reconstruction via Optimized Excitation Counting by Tanjung Krisnanda, Clara Yun Fontaine, Adrian Copetudo, Pengtao Song, Kai Xiang Lee, Ni-Ni Huang, Fernando Valadares, Timothy C.H. Liew, Yvonne Y. Gao

“…In this work, we introduce an efficient and robust technique of optimized reconstruction with excitation-number sampling (ORENS) based on the idea of the generalized Q function. …”
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A domain free of the zeros of the partial theta function by V. Kostov

“…For each $q$ fixed, $\theta$ is an entire function of order $0$ in the variable~$x$. When $q$ is real and $q\in (0,0.3092\ldots )$, $\theta (q,.)$ is a function of the Laguerre-P\'olya class $\mathcal{L-P}I$. …”
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Comparison of Different Numerical Models for Solidification of Paraffin-Based PCMs and Evaluation of the Effect of Variable Mushy Zone Constant by Milad Tajik Jamalabad, Cristobal Cortes, Javier Pallarés, Antonia Gil, Inmaculada Arauzo

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Multi-UAV Cooperative Suspension Control Strategy Considering Variable Rope Length and Load Posture Coupling Effect by Yi Wang, Kang Li, Xuefu Li, Jingyu Wang, Pengbo Yu

“…On this basis, the traditional dynamic model is improved, with a focus on the impact of variable rope length, analyzing the dynamic coupling relationship between rope length and swing angle, and constructing related coupling error functions to improve the stability and control accuracy of the system. …”
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Experimental Study on Desorption Characteristics of Coalbed Methane under Variable Loading and Temperature in Deep and High Geothermal Mine by Haifeng Ma, Lingjie Wang, Housheng Jia, Jucai Chang, YingMing Li, Xiangyang Zhang, Zuxiang Hu, Zhiqiang Yin

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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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Beyond Global Metrics: The U-Smile Method for Explainable, Interpretable, and Transparent Variable Selection in Risk Prediction Models by Katarzyna B. Kubiak, Agata Konieczna, Anna Tyranska-Fobke, Barbara Więckowska

“…Variable selection (VS) is a critical step in developing predictive binary classification (BC) models. …”
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The Role of Profitability and Liquidity in Meeting the Feasibility Standards of Sharia Banking with Capital Adequacy as A Moderating Variable in Indonesia by Padli Pawaid Yahya, Joko Setyono

“…Control variables include Net Profit Margin (NPM), Operational Efficiency (BOPO), and Loan to Deposit Ratio (LDR). …”
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Model-Based Control Allocation During State Transitions of a Variable Recruitment Fluidic Artificial Muscle Bundle by Jeong Yong Kim, Matthew Bryant

“…FAMs can be bundled together in parallel to exhibit variable recruitment functionality, which is an activation strategy inspired by how motor units (MUs) in skeletal muscle are recruited. …”
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THE PROBLEM OF ENERGY EFFICIENCY OF SYSTEMS BASED ON ARTIFICIAL INTELLIGENCE OF THE INTERNET OF THINGS (AIOT) by С. В. Войтко

“…The emphasis is on allocating conventionally fixed and conventionally variable costs for AIoT. It was determined that integrating artificial intelligence functionality into the IoT infrastructure provides the opportunity to store big data for processing using artificial intelligence elements capable of conducting predictive analysis to make informed management decisions. …”
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Enhancing CAR T‐cell therapy manufacturing efficiency through semi‐automated bioprocessing by Jason Isaacson, Prajakta Bhanap, Nicholas Putnam, Jasmine Padilla, Nujhat Fatima, Max Dotson, Danny Hayoun, Moloud Ahmadi, Gertrude Nonterah, Yongchang Ji

“…Automated CAR T‐cell manufacturing methods that use software to control the equipment used in the process can help overcome the roadblocks associated with manual manufacturing, ultimately enabling a reduction in variability, increased efficiency, improved product quality and better data management. …”
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Modeling fin efficiency considering transverse temperature gradients in rocket engine cooling channels by Volodymyr Sliusariev, Valerii Bucharskyi

“…This study aims to improve the accuracy of methods for determining fin efficiency. Its goal is to derive calculation relationships for finning coefficients that account for transverse temperature non-uniformity within the fin cross-section. …”
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Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

“…These models are commonly used to predict outputs based on a combination of fixed parameters and adjustable variables. A key transition in optimization involves moving beyond simple prediction to determine optimal variable values. …”
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How Can We Manage Repairing a Broken Finite Vibrating String? Solutions to the Problem I by Vladimir L. Borsch

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