A Systematic Review of the Advances and New Insights into Copy Number Variations in Plant Genomes by Saimire Silaiyiman, Jiaxuan Liu, Jiaxin Wu, Lejun Ouyang, Zheng Cao, Chao Shen

“…Copy number variations (CNVs), as an important structural variant in genomes, are widely present in plants, affecting their phenotype and adaptability. …”
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Photon sensor-based monitoring of spatial variations in canopy FIPAR for crop growth assessment by Jian Wang, Zhenggui Zhang, Xin Li, Lu Feng, Xiaofei Li, Minghua Xin, Shiwu Xiong, Yingchun Han, Shijie Zhang, Xiaoyu Zhi, Beifang Yang, Guoping Wang, Yaping Lei, Zhanbiao Wang, Yabing Li

“…Traditional field measurement and monitoring methods are often inefficient and provide limited, outdated information. …”
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PRED-LD: efficient imputation of GWAS summary statistics by Georgios A. Manios, Aikaterini Michailidi, Panagiota I. Kontou, Pantelis G. Bagos

“…Conclusions PRED-LD offers an efficient and accurate method for GWAS summary statistics imputation, providing faster performance, direct result interpretation, and the ability to use multiple reference panels. …”
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An Efficient Uncertainty-Driven Learning for Stochastic Super-Resolution by Daeyoung Han, Seongmin Hwang, Hoyeon Ahn, Moongu Jeon

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VOICE-BASED IDENTIFICATION AND CONTRIBUTION TO THE EFFICIENCY OF CRIMINAL PROCEEDINGS by Jadranka Otašević, Božidar Otašević

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Learning protocols for the fast and efficient control of active matter by Corneel Casert, Stephen Whitelam

“…Our results show that protocols identified by a flexible neural-network ansatz, which allows the optimization of multiple control parameters and the emergence of sharp features, are more efficient than protocols derived recently by constrained analytical methods. …”
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Efficiency of Hysteresis Rods in Small Spacecraft Attitude Stabilization by Assal Farrahi, Ángel Sanz-Andrés

“…A semiempirical method for predicting the damping efficiency of hysteresis rods on-board small satellites is presented. …”
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Efficient quantum circuits based on the quantum natural gradient by Ananda Roy, Sameer Erramilli, Robert M. Konik

“…Efficient preparation of arbitrary entangled quantum states is crucial for quantum computation. …”
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Efficient and Accurate Force Replay in Cosmological-baryonic Simulations by Arpit Arora, Robyn Sanderson, Christopher Regan, Nicolás Garavito-Camargo, Emily Bregou, Nondh Panithanpaisal, Andrew Wetzel, Emily C. Cunningham, Sarah R. Loebman, Adriana Dropulic, Nora Shipp

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Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing elec... by Natnale Sitotaw Asefa, Kiran Shahapurkar, Tilahun Nigussie, Abdulkadir Aman Hassen, Manzoore Elahi M. Soudagar, Yasser Fouad, Irfan Ali, Sagar Shelare, Shubham Sharma, V.K. Bupesh Raja, Abinash Mahapatro, Sarabjit Singh, Abhinav Kumar, Ehab El Sayed Massoud, Jasmina Lozanovic

“…This approach optimises electrical and thermal efficiency, tackling essential performance compromises overlooked by traditional methods. …”
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Impacts of high viscosity variation and internal heating on mantle convection in different aspect ratio cells by Tania S. Khaleque, Md. Shafiul A. Khan, Romana Yesmin

“…The primary goal of this research is to analyze the convection pattern at high Rayleigh number, including internal heating and significant viscosity variation across the mantle depth. Finite element method-based PDE solver is used to solve the model, incorporating viscosity based on both temperature only and temperature and pressure combined. …”
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VJDNet: A Simple Variational Joint Discrimination Network for Cross-Image Hyperspectral Anomaly Detection by Shiqi Wu, Xiangrong Zhang, Guanchun Wang, Puhua Chen, Jing Gu, Xina Cheng, Licheng Jiao

“…In this paper, a simple and lightweight unsupervised cross-image HAD method called Variational Joint Discrimination Network (VJDNet) is proposed. …”
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An Echo State Network Approach for Parameter Variation Robustness Enhancement in FCS-MPC for PMSM Drives by Xiao Zeng, Jing Li, Pengcheng Yang, Hongda Cai, Yongzhi Zhou, Daren Li

“…By leveraging the structural simplicity and application efficiency of ESNs during training, the proposed approach is well-suited to tackling complex parameter variation challenges via online learning. …”
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Seasonal variation and key factors influencing evapotranspiration partitioning in alpine ecosystems of the Qinghai Lake Basin by Wenyang Cao, Yao Wu, Jiayin Liu, Yuan Yuan, Cicheng Zhang, Shaojie Zhao, Pei Wang

“…The model’s effectiveness was validated by its consistency with observed energy fluxes, ground surface temperature, and the transpiration fraction of evapotranspiration (T/ET) derived from isotope methods, the underlying water use efficiency (uWUE) approach, and remote sensing data. …”
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Haematological profile and genetic variation of brown Caucasian dairy cattle in different ecological and geographical zones by A. A. Ozdemirov, L. N. Chizhova, A. A. Khozhokov, E. S. Surzhikova, A. K. Mikhaylenko

“…Since hematopoietic function of blood is the basis of organism’s vital functions and genetic polymorphism is the measure of its adaptability, the present study is aimed at examining haematological profile and the degree of genetic variation in the Brown Caucasian cattle.Materials and Methods. …”
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Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…Accurate and comprehensive wind speed forecasting is crucial for improving efficiency in offshore wind power operation systems in coastal regions. …”
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Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The rapid expansion of devices on the Internet of Things (IoTs) has led to a significant rise in IoT botnet attacks, creating an urgent need for advanced detection and classification methods. This study aims to evaluate the effectiveness of Kolmogorov-Arnold Networks (KANs) and their architectural variations in classifying IoT botnet attacks, comparing their performance with traditional machine learning and deep learning models. …”
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A study on slope variation of a cantilever beam under the effect of transverse and compressive forces by S.E. Ghasemi

“…Additionally, the effects of key physical parameters on slope variation are explored. The findings confirm that AGM provides an efficient and accurate analytical approximation for such nonlinear boundary value problems.…”
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Experimental Study on Rheological Properties and Strength Variation of High Concentration Cemented Unclassified Tailings Backfill by Shijiao Yang, Xing Xing, Shuai Su, Fulin Wang

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Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers by Dongyeong Kim, Geon Kim, Suyeon Kim, Jewon Park, Sinwook Kim, Hyeona Seo, Chaehyuk Lim, Sowon Kim, Juwon Lee, Jeonghyeon Yun, Hyerin Lee, Jinseok Park, Yongbok Lee, Seungchan Lee, Myoungjin Lee

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