Optimal selection of tree species for ecological protection forests on the riverbank side of the lower Yellow River flood control dikes by Xiaolei Zhang, Kexin Li, Zhiheng Xu, Chaoqun Li, Zhengxiong Bai, Chen Yang

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Evolutionary search algorithm for learning activation function of an artificial neural network by Yurshin Viacheslav

“…Neural networks require careful selection of activation functions to optimize performance. …”
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YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

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Characterization and Evolutionary Analyses Reveal Differential Selection Pressures on <i>PGIc</i> and <i>PGIp</i> During Domestication in Castor Bean by Jiayu Guo, Lanxin Jiang, Anmin Yu, Bing Han, Aizhong Liu

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First Detection of Low-frequency Striae in Interplanetary Type III Radio Bursts by Vratislav Krupar, Eduard P. Kontar, Jan Soucek, Lynn B. Wilson III, Adam Szabo, Oksana Kruparova, Hamish A. S. Reid, Mychajlo Hajos, David Pisa, Ondrej Santolik, Milan Maksimovic, Jolene S. Pickett

“…By combining high-resolution radio observations with well-calibrated in situ electron velocity distribution function data from the Wind spacecraft, we characterized the plasma properties of the burst source region near 0.32 au. …”
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Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification by Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam, Mohammed Arfat Raihan Chowdhury, Md. Shamim Anower, Md. Masud Rana, Md. Shafiul Alam, Mahmudul Hasan, Md. Shohanur Islam Sobuj, Md. Babul Islam, Veerpratap Meena, Francesco Benedetto

“…The motors of EVs store and consume electrical power from renewable energy (RE) sources through interfacing connections using power electronics technology to provide mechanical power through rotation. …”
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Whole Genome Sequencing Reveals Clade‐Specific Genetic Variation in Blacklegged Ticks by Jacob Cassens, Adela S. Oliva Chávez, Danielle M. Tufts, Jianmin Zhong, Christopher Faulk, Jonathan D. Oliver

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Yield of chickpea genotypes as function of row spacing planting in northern Paraná by Guilherme Henrique Teixeira Alves, Hebert Teixeira Cândido, Silvestre Bellettini, Daniel Garbellini Duft, Oriel Tiago Kölln

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Sustainable Valorization of Jackfruit Peel Waste: Bio‐Functional and Structural Characterization by Rangina Brahma, Subhajit Ray, Prakash Kumar Nayak, Kandi Shridhar

“…In conclusion, this study identified the potential utility of A. heterophyllus peel as a valuable source of phytochemical compounds, polyphenolic antioxidants, and the antimicrobial additives that can be used in wide agri‐food‐pharma industries.…”
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Effect of cochlear implant surgery on vestibular function: meta-analysis study by Iman Ibrahim, Sabrina Daniela da Silva, Bernard Segal, Anthony Zeitouni

“…No significant effect of CI surgery was detected in HIT, posturography, or DHI scores. Overall, the clinical effect of CI surgery on the vestibular function was found to be insignificant. …”
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A study on pollen characteristics of bisexual and functionally male flowers in pomegranate by DUAN Shuyun, CHEN Lina, ZHU Juanli, LIU Ruitao, LI Haoxian, YAN Qiong, LI Songkai, YANG Qinghua, LU Zhenhua

“…[Methods] Pollen samples were collected from the National Horticultural Germplasm Resource Center. The number of anthers of bisexual flowers and functionally male flowers were collected in cultivars including Suanmeiren, Mollar, Tianshihong, Zhongshiliu 4, Huaguang and Turkmenistan. …”
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Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images by Resky Adhyaksa, Bedy Purnama

“…The purpose of this research is to determine whether or not a deep learning model called VGG16 can automatically identify bone fractures in X-ray pictures. The dataset, sourced from Kaggle, includes 10,522 images of human hand and foot bones, which underwent preprocessing steps such as normalization and resizing to 224x224 pixels to enhance data quality. …”
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Rural Water Point Functionality Estimates and Associations: Evidence From Nine Countries in Sub‐Saharan Africa and South Asia by Anna L. Murray, Gabriela Stone, Audrey R. Yang, Nicholas F. Lawrence, Hannah Matthews, Georgia L. Kayser

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All-optical nonlinear activation function based on stimulated Brillouin scattering by Slinkov Grigorii, Becker Steven, Englund Dirk, Stiller Birgit

“…However, their development towards high-performing computing alternatives is hindered by one of the optical neural networks’ key components: the activation function. Most of the reported activation functions rely on opto-electronic conversion, sacrificing the unique advantages of photonics, such as resource-efficient coherent and frequency-multiplexed information encoding. …”
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Redox-active sp2-c connected metal covalent organic frameworks for selective detection and reductive separation of uranium by Jin-Lan Liu, Zhi-Hai Peng, Jia-Xin Qi, Cheng-Rong Zhang, Zhen-Wen Zhang, Li Zhang, Ru-Ping Liang, Jian-Ding Qiu

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Repeat-induced point mutations driving Parastagonospora nodorum genomic diversity are balanced by selection against non-synonymous mutations by Darcy A. B. Jones, Kasia Rybak, Mohitul Hossain, Stefania Bertazzoni, Angela Williams, Kar-Chun Tan, Huyen T. T. Phan, James K. Hane

“…Effector predictions identified 186 candidate secreted predicted effector proteins (CSEPs), 69 of which had functional annotations and included confirmed effectors. …”
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Microhabitat Characteristics That Regulate Ant Richness Patterns: The Importance of Leaf Litter for Epigaeic Ants by Antonio Cesar Medeiros de Queiroz, Carla Rodrigues Ribas, Filipe Machado França

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Effects of Naringenin and Its Glycosides on Functional Properties of Oat Protein and Their Interaction Mechanism by Wuzhen LIU, Ti LI, Qin GENG, Jun CHEN, Jialong HAN, Chengmei LIU, Taotao DAI

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Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs by Yan LI, Weizhong QIANG, Zhen LI, Deqing ZOU, Hai JIN

“…In recent years, software vulnerabilities have been causing a multitude of security incidents, and the early discovery and patching of vulnerabilities can effectively reduce losses.Traditional rule-based vulnerability detection methods, relying upon rules defined by experts, suffer from a high false negative rate.Deep learning-based methods have the capability to automatically learn potential features of vulnerable programs.However, as software complexity increases, the precision of these methods decreases.On one hand, current methods mostly operate at the function level, thus unable to handle inter-procedural vulnerability samples.On the other hand, models such as BGRU and BLSTM exhibit performance degradation when confronted with long input sequences, and are not adept at capturing long-term dependencies in program statements.To address the aforementioned issues, the existing program slicing method has been optimized, enabling a comprehensive contextual analysis of vulnerabilities triggered across functions through the combination of intra-procedural and inter-procedural slicing.This facilitated the capture of the complete causal relationship of vulnerability triggers.Furthermore, a vulnerability detection task was conducted using a Transformer neural network architecture equipped with a multi-head attention mechanism.This architecture collectively focused on information from different representation subspaces, allowing for the extraction of deep features from nodes.Unlike recurrent neural networks, this approach resolved the issue of information decay and effectively learned the syntax and semantic information of the source program.Experimental results demonstrate that this method achieves an F1 score of 73.4% on a real software dataset.Compared to the comparative methods, it shows an improvement of 13.6% to 40.8%.Furthermore, it successfully detects several vulnerabilities in open-source software, confirming its effectiveness and applicability.…”
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Genetic Evaluation of Resilience Indicators in Holstein Cows by Eva Kašná, Ludmila Zavadilová, Jan Vařeka

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