Variation analysis and comparison of leaf and fruit traits of triploid hybrid progeny in jujube by Jiayuan Xuan, Quanhui Ma, Lixin Ge, Fenfen Yan, Fenfen Yan, Jun Yu, Jiurui Wang, Cuiyun Wu, Cuiyun Wu, Mengjun Liu

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Adaptive variation regulates the expression of the human SGK1 gene in response to stress. by Francesca Luca, Sonal Kashyap, Catherine Southard, Min Zou, David Witonsky, Anna Di Rienzo, Suzanne D Conzen

“…Our results suggest a novel paradigm in which hormonal responsiveness is modulated by sequence variation in the regulatory regions of nuclear receptor target genes. …”
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The Distribution of Sport Performance Gene Variations Through COVID-19 Disease Severity by Guven Yenmis, Ilayda Kallenci, Mehmet Dokur, Suna Koc, Sila Basak Yalinkilic, Evren Atak, Mahmut Demirbilek, Hulya Arkan

“…Inter-individual differences due to these genetic variations will broaden the horizon of knowledge on the pathophysiology of the disease.…”
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Evapotranspiration Partitioning of the <i>Populus euphratica</i> Forest Ecosystem in the Drylands of Northwestern China by Qi Zhang, Qi Feng, Yonghong Su, Cuo Jian

“…This study demonstrated that the underlying water use efficiency (uWUE) method effectively partitions ET into vegetation T and soil evaporation (E). …”
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An Efficient Anomalous Sound Detection System for Microcontrollers by Yi-Cheng Lo, Tsung-Lin Tsai, Chieh-Wen Yang, An-Yeu Wu

“…Finally, we evaluate our method on the DCASE dataset, and the results show that our system achieves favorable outcomes in both accuracy and resource efficiency, marking our contribution to ASD system practice.…”
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Internal control system of accounts receivable: directions of perfection by Payanok T.M.

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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Multilingual countries utilize the SLID method to facilitate speech detection. This is accomplished by determining the language of the spoken parts using language recognizers. …”
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AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

“…However, there is no efficient method for tracking leaf angles of plant canopies under field conditions. …”
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Controlling Mie scattering response to refractive index variations via light field manipulation by Jianzhi Zeng, Hanqing Cai, Jiachen Liu, Haifeng Hu

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Adaptive Total Variation Minimization-Based Image Enhancement from Flash and No-Flash Pairs by Sang Min Yoon, Yeon Ju Lee, Gang-Joon Yoon, Jungho Yoon

“…In this approach, we propose a method based on Adaptive Total Variation Minimization (ATVM) so that it has an efficient image denoising effect by preserving strong gradients of the flash image. …”
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Analyzing the Impact of Climate Change on Compound Flooding Under Interdecadal Variations in Rainfall and Tide by Jiun-Huei Jang, Tien-Hao Chang, Yen-Mo Wu, Ting-En Liao, Chih-Hung Hsu

“…However, relevant research has been limited because significant amounts of data, scenarios, and computations are often required to evaluate long-term variations in compound flood risk. In this study, a framework was proposed through efficient hydraulic simulations and a consequence-based statistical method using data projected under different general circulation models (GCMs). …”
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Testing life-cycle assessment data quality with Benford’s law reveals geographic variation by Bogdan Šinik, Aleksandar Tošić

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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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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…The original data included daily runoff from January 2005 to December 2012. [Methods] This study first employed Multivariate Variational Mode Decomposition(MVMD) to decompose the original daily runoff data from the two stations, reducing data complexity. …”
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An algorithm for variational inclusion problems including quasi-nonexpansive mappings with applications in osteoporosis prediction by Raweerote Suparatulatorn, Wongthawat Liawrungrueang, Thanasak Mouktonglang, Watcharaporn Cholamjiak

“…The proposed method exhibits weak convergence under reasonable assumptions. …”
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Experimental Study on Variation Rules of Damping with Influential Factors of Tuned Liquid Column Damper by Yang Yu, Lixin Xu, Liang Zhang

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Exploring the Trade-Off in the Variational Information Bottleneck for Regression with a Single Training Run by Sota Kudo, Naoaki Ono, Shigehiko Kanaya, Ming Huang

“…This study analyzes the Variational Information Bottleneck (VIB), a standard IB method in deep learning, in the settings of regression problems and derives its optimal solution. …”
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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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Spatial variation of soil quality in key grain-producing areas of Qitai County, Xinjiang by FAN Zikang, WANG Chunxia, YU Jing, QIN Da, YANG Yuefa, WANG Hongxin

“…Classical statistical methods were used to analyze the correlations between indicators, and geostatistical methods were used to assess the spatial variation of each indicator. …”
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Variation in the metagenomic analysis of fecal microbiome composition calls for a standardized operating approach by Zhilu Xu, Yun Kit Yeoh, Hein M. Tun, Na Fei, Jingwan Zhang, Mark Morrison, Michael A. Kamm, Jun Yu, Francis Ka Leung Chan, Siew C. Ng

“…In our study, we utilized microbial metagenomic data sets from 2,722 fecal samples generated from a single research center to examine the extent to which sample storage and DNA extraction influence the quantification of microbial composition and compared this variable with other sources of technical and biological variation. Our research highlights the impact of DNA extraction methods when analyzing microbiome data and suggests that the microbiome profile may be influenced by differences in the extraction efficiency of bacterial species. …”
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