Variability of Interpolation Errors and Mutual Enhancement of Different Interpolation Methods by Yunxia He, Mingliang Luo, Hui Yang, Leichao Bai, Zhongsheng Chen

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Challenges and future perspectives in using mesenchymal stem cells for efficient bone fracture healing by Dong Han, Weiwei Liu, Jinpeng Gong, Yupeng Ma, Zhengwen Sun

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Efficient techno-economic modelling of smart parking lots within the electricity distribution networks by Seyed Ashkan Nejati, David Greenwood, Sanchari Deb, Saman Nikkhah

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Automated protocol templates with efficient schedule of activities table generation for healthy volunteer trials by Kyongeun Shin, Sungpil Han, Hyerim Choe, Suein Choi, Seunghoon Han

“…Additionally, a web-based SoA generator (developed with React.js) was created, featuring user-friendly functions for flexible start day adjustments, trial parameter settings, and automatic annotations. …”
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Predicting renal function using fundus photography: role of confounders by Hyun-Woong Park, Hae Ri Kim, Ki Yup Nam, Bum Jun Kim, Taeseen Kang

“…Conclusions Fundus photographs are a valuable tool for screening renal function using deep neural network models, demonstrating the role of noninvasive imaging in medical diagnostics. …”
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SARE: an optimized method for detection functional regulatory elements in genome by Mohammadjavad Hosseinpoor

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Physical function evaluation in volleyball training based on intelligent GRNN by Kaiyuan Dong, Borhannudin bin Abdullah, Hazizi bin Abu Saad, Chenxi Lu

“…Abstract This study aims to improve both the evaluation accuracy and the real-time feedback capability in monitoring athletes’ physical function changes during volleyball training. Firstly, based on the framework of the generalized regression neural network, a variable-structure generalized regression neural network (VSGRNN) is proposed and developed. …”
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Viscosity modelling of chlorinated brines in three-component systems with a continuously variable temperature range between 293-323 K by Andrés Soto-Bubert, Rashmi Bhardwaj, Satheeshkumar Rajendran, Roberto Acevedo

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An efficient Quantum Approximate Optimization Algorithm with fixed linear ramp schedule for truss structure optimization by Junsen Xiao, Naruethep Sukulthanasorn, Reika Nomura, Shuji Moriguchi, Kenjiro Terada

“…As a result, the objective function is in a simple format, enabling efficient optimization using QAOA. …”
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Method of restoring multivariable Boolean function from its derivative by Alexander V. Mazurenko, Nadezhda S. Mogilevskaya

“…Introduction. Boolean functions of several variables are of paramount importance in the coding theory and cryptography. …”
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Standard Deviation of Fiber-Coupling Efficiency for Free-Space Optical Communication Through Atmospheric Turbulence by Woohyeon Moon, Hoon Kim

“…Due to atmospheric turbulence, however, the coupling efficiency, which is defined by the ratio of the fiber-coupled optical power to the optical power reaching the aperture, fluctuates over time, and thus should be treated as a random variable. …”
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Bringing Executive Function Testing Online: Assessment Validation Study by Mouna Attarha, Ana Carolina de Figueiredo Pelegrino, Lydia Ouellet, Sarah-Jane Grant, Etienne de Villers-Sidani, Thomas Van Vleet

“…Performance on Freeze Frame was analyzed in relation to self-reported demographic variables and neuropsychological function, using a standardized measure of executive function, the National Institutes of Health Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research (NIH EXAMINER). …”
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Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study by Min Yang, Huiqin Zhang, Minglan Yu, Yunxuan Xu, Bo Xiang, Xiaopeng Yao

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Variational Autoencoder Transfer Functions for Onshore Tsunami Hazard Curves by Willington Renteria, Patrick Lynett, Maile McCann, Behzad Ebrahimi, Hong Kie Thio, Ian Robertson, Chris Siverd, Betsy Hicks

“…Once encoded, the data are represented by a normal distribution of latent variables. The VAE then uses a trained decoder to sample the distribution created by the latent variables and reconstruct a continuous hazard function at the onshore location. …”
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Mixed Cost Function and State Constrains Optimal Control Problems by Hugo Leiva, Guido Tapia-Riera, Jhoana P. Romero-Leiton, Cosme Duque

“…In this paper, we analyze an optimal control problem with a mixed cost function, which combines a terminal cost at the final state and an integral term involving the state and control variables. …”
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Modeling creep for a closed cylindrical shell under hydrostatic pressure by M. A. Magomedov, V. V. Kuznetsov, B. M. Yazyev, S. V. Litvinov

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Exploring Flexible Penalization of Bayesian Survival Analysis Using Beta Process Prior for Baseline Hazard by Kazeem A. Dauda, Ebenezer J. Adeniyi, Rasheed K. Lamidi, Olalekan T. Wahab

“…Therefore, this study is motivated to adopt the idea of a penalized semi-parametric Bayesian Cox (PSBC) model through elastic-net and group lasso penalty functions (PSBC-EN and PSBC-GL) to incorporate the grouping structure of the covariates (genes) and optimally perform variable selection. …”
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Handling Multiple-Fuel Options in Economic Dispatch of Thermal Power Plants Through a Tight Model Applying Indicator Variables by Hossein Sharifzadeh

“…Thermal power plants play a central role in present power systems because of their high efficiency, fast startup capability, and flexibility to integrate the variability of renewable generations. …”
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The efficiency of Amil Zakat Institutions (LAZ) in Indonesian Islamic Banks: Data Envelopment Analysis Approach by Rofiul Wahyudi, Agus Susetyohadi

“…The Amil Zakat Institution (LAZ), based on Islamic bank corporations, has shown a significant role based on the mandate of the 2008 law on the social functions of Islamic banks. However, a performance evaluation is needed to see how efficient the LAZ is in its operations. …”
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Spacecraft Intelligent Fault Diagnosis under Variable Working Conditions via Wasserstein Distance-Based Deep Adversarial Transfer Learning by Gang Xiang, Kun Tian

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