Assimilating Satellite-Based Biophysical Variables Data into AquaCrop Model for Silage Maize Yield Estimation Using Water Cycle Algorithm by Elahe Akbari, Ali Darvishi Boloorani, Jochem Verrelst, Stefano Pignatti

“…In this paper, the AquaCrop model, a water-driven crop growth model, was selected for recalibration and assimilation of satellite-derived biophysical products due to its simplicity and lack of computational complexity. To this end, field samples of soil (sampled before cultivation) and crop features were collected during the growing season of silage maize. …”
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Software Using in Digital Design Under Hybrid Training by O. L. Akhremchik, A. R. Chabarov

“…The software of the device being developed is considered as a component of a laboratory workshop. A feature of hybrid learning is noted that is associated with the complexity of prototyping and the need to ensure compatibility of project files created online with computer software modules in the university laboratory. …”
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Prevalence, Geometry, and Hemodynamics of Small and Medium-Sized Intracranial Aneurysms With and Without Blebs in the Chinese Han Population by Xiaopeng Cui, Yan Zhao, Liang Wang, Yujing Jin, Zhenglong Yang, Yaohua Li, Zilin Zhao, Hengrui Zhang, Kai Wei, Zhennan Sun, Peng Huai, Lei Chen, Xinyu Yang

“…Objectives To investigate the prevalence, distribution, and associated clinical, geometric, and hemodynamic features of blebs in small- and medium-sized IAs among Chinese patients, and to identify predictors of aneurysm rupture and bleb formation. …”
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Hydrogeochemical analysis of groundwater quality during the pre- monsoon season of Manipur, India by Rakshita Chaudhary, Nisha Gaur, Mohit Yadav

“…Water samples were collected in 2022 during the pre-monsoon season. To compute the water quality index for drinking water, the basic chemical parameters of total hardness, pH, electrical conductivity, total dissolved solids, Calcium, Sodium, Iron, Magnesium, Manganese, Chlorine, and Hydrogen Carbonate were used. …”
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Decoding communicative action vitality forms in social contexts by Radoslaw Niewiadomski, Radoslaw Niewiadomski, Amrita Suresh, Alessandra Sciutti, Giuseppe Di Cesare, Giuseppe Di Cesare

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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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Handwritten Urdu Characters and Digits Recognition Using Transfer Learning and Augmentation With AlexNet by Aqsa Rasheed, Nouman Ali, Bushra Zafar, Amsa Shabbir, Muhammad Sajid, Muhammad Tariq Mahmood

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Optimizing Time Series Models for Water Demand Forecasting by Gal Perelman, Yaniv Romano, Avi Ostfeld

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Expression of cell-wall related genes is highly variable and correlates with sepal morphology by Hartasánchez, Diego A., Kiss, Annamaria, Battu, Virginie, Soraru, Charline, Delgado-Vaquera, Abigail, Massinon, Florian, Brasó-Vives, Marina, Mollier, Corentin, Martin-Magniette, Marie-Laure, Boudaoud, Arezki, Monéger, Françoise

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Thermal dynamics of nanofluids with aggregating nanoparticles and magnetic heating: Utilization of Maxwell-Bruggeman and Kreiger-Dougherty models by Muhammad Idrees Afridi, Abdullah Alhushaybari, Ali J. Chamkha

“…Additionally, the study examines the entropy generation within a local non-similar nanofluid flow featuring nanoparticle aggregation. The pseudo-similarity variable, stream-wise transformed coordinates, dimensionless velocity components, and temperature are used to transform the set of governing equations and associated boundary conditions into dimensionless form. …”
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Sinusoidal exponential distribution for modeling elevated creatinine kinase level as the initial presentation of Covid-19 by N. M. Kilany, A. M. Alharpy

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Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

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Transfer Learning Estimation and Transferability of LNC and LMA Across Different Datasets by Yingbo Wang, Mengzhu He, Lin Sun, Yong He, Zengwei Zheng

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Artificial intelligence for prediction of atrial fibrillation in the stroke unit: a retrospective derivation validation cohort studyResearch in context by Maximilian Schoels, Laura Krumm, Alexander Nelde, Manuel C. Olma, Christian H. Nolte, Jan F. Scheitz, Markus G. Klammer, Christoph Leithner, Andreas Meisel, Franziska Scheibe, Michael Krämer, Karl Georg Haeusler, Matthias Endres, Christian Meisel

“…The most valuable input features and most effective model design for AF prediction are also unclear. …”
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Improving the Capacity of NOMA Network Using Multiple Aerial Intelligent Reflecting Surfaces by Le Si Phu, Tan N. Nguyen, Miroslav Voznak, Ba Cao Nguyen, Tran Manh Hoang, Bui Vu Minh, Phuong T. Tran

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Deep Neural Emulation of the Supermassive Black Hole Binary Population by Nima Laal, Stephen R. Taylor, Luke Zoltan Kelley, Joseph Simon, Kayhan Gültekin, David Wright, Bence Bécsy, J. Andrew Casey-Clyde, Siyuan Chen, Alexander Cingoranelli, Daniel J. D’Orazio, Emiko C. Gardiner, William G. Lamb, Cayenne Matt, Magdalena S. Siwek, Jeremy M. Wachter

“…As a result, we can predict strain distributions that mirror underlying simulations very closely while also capturing frequency covariances in the strain distributions as well as statistical complexities such as tails, non-Gaussianities, and multimodalities that are otherwise not learnable by existing techniques. In particular, we feature various comparisons between the NF-based emulator and the GP approach used extensively in past efforts. …”
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Determining large hyperfine interactions of a model flavoprotein in the semiquinone state using pulse EPR (electron paramagnetic resonance) techniques by J. I. Martínez, J. I. Martínez, S. Frago, M. Medina, I. García-Rubio, I. García-Rubio

“…<p>Flavoproteins are a versatile class of proteins involved in numerous biological processes, including redox reactions, electron transfer, and signal transduction, often relying on their ability to stabilize different oxidation states of their flavin cofactor. A critical feature of flavin cofactors is their capacity to achieve, within particular protein environments, a semiquinone state that plays a pivotal role in mediating single-electron transfer events and that is key to understanding flavoprotein reactivity.…”
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Deep reinforcement learning applications and prospects in industrial scenarios by JING TAN, Ligang YANG, Xiaorui LI, Zhaolin YUAN, Yunduan CUI, Chao YAO, Zongjie WANG, Xiaojuan BAN

“…Deep reinforcement learning (DRL), which integrates the high-dimensional feature extraction of deep learning with the adaptive decision-making capabilities of reinforcement learning, has emerged as a transformative technology in intelligent industrial control. …”
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SOLEDGE3X full vessel plasma boundary simulations of ITER non-active phase plasmas by N. Rivals, P. Tamain, Y. Marandet, X. Bonnin, J.-S. Park, H. Bufferand, R.A. Pitts, G. Falchetto, H. Yang, G. Ciraolo

“…The onset of detachment in the ITER machine is analyzed in this work through the help of 2D-axisymmetric boundary plasma simulations with the SOLEDGE3X-EIRENE code, which features a numerical domain for the plasma solver extending up to the first wall. …”
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Jumping knowledge graph attention network for resource allocation in wireless cellular system by Qiushi Sun, Zhou Fang, Yin Li, Ovanes Petrosian

“…Abstract Next-generation wireless networks are characterized by two essential features: ubiquitous connectivity and high-speed data transmission. …”
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