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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Utilizing Photothermal Effect Enhances Photocatalytic Water Splitting Coupled with Selective Benzyl Alcohol Oxidation over Schottky Junctions by Bojing Sun, Mengjia Ye, Yachao Xu, Ying Jiang, Dongfang Hou, Xiu‐qing Qiao, Meidi Wang, Yunchen Du, Dong‐Sheng Li

“…Herein, WC quantum dots decorated defective ZnIn2S4 nanosheets (DZIS/WCQDs) dual‐functional photocatalysts are fabricated. Its unique Schottky junctions and photothermal effect significantly promote the separation and transport efficiency of photogenerated carriers, as well as achieving synergistic enhancement of photocatalytic water splitting coupled with selective oxidation of benzyl alcohol (BA). …”
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A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys by Letizia Lamperti, Olivier François, David Mouillot, Laëtitia Mathon, Théophile Sanchez, Camille Albouy, Loïc Pellissier, Stéphanie Manel

“…We present a spatial matrix factorization method that identifies optimal eDNA sample assemblages—called pools—assuming that taxonomic unit composition is based on a fixed number of unknown sources. These sources, in turn, represent taxonomic units sharing similar habitat properties or characteristics. …”
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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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Detecting and routing of dust event using remote sensing and numerical modeling in Isfahan Province by Mehdii Jafari, Gholamreza Zehtabian, Hasan Ahmadi, Tayebeh Mesbahzadeh, Ali Akbar Norouzi

“…In addition, numerical weather models alone are not capable of storm detection, which requires the use of dust detection methods based on data remote sensing. …”
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Crop domestication and improvement reshape root traits and the structure and function of their associated microbiome by Xiaoming HE, Frank HOCHHOLDINGER, Xingping CHEN, Peng YU

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Determination of the fit growth curve model and relationships among growth parameters by nonlinear functions in Kaçkar hair goats by S. Yüksel, F. Yüksel, E. Sezgin

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Whole-Genome Sequencing Identifies Functional Genes for Environmental Adaptability in Chinese Geese by Xufang Ren, Jincheng Yu, Xiurong Zhao, Xinye Zhang, Gang Wang, Xiaoyu Jiang, Xianyao Li, Changqing Qu, Lujiang Qu

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The Ecosystem Services Assessment of Wetlands based on the Classification of Hydrological-ecological Structures and Functions (Case study: Shadegan Wetland) by leila Rahimi, Bahram Malekmohammadi, Ahmad reza Yavari

“…Selecting Shadegan International Wetland as a case study in this research, the ecosystem services approach have been applied to ecological conditions assessment of the wetland based on biophysical structures, processes, functions and ecosystem services in a hydrological-ecological framework, which provides a valuable tool for optimal allocation of wetland resources and their effective management, as well as adopting rational and sustainable policies. 2-Materials and Methods The proposed framework can be considered as a hierarchical approach based on the characteristics of biophysical structure, functions and ecosystem services. …”
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Characteristics of soil microbial phospholipid fatty acids in artificial, black-soil mountain degraded, and natural grasslands in the source region of the Three Rivers by Lele Xie, Yushou Ma, Yanlong Wang, Yuan Ma, Xiaoli Wang, Ying Liu

“…Background The source region of the Three Rivers is a concentrated distribution area of alpine grassland. …”
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Serum albumin nanoparticles: Ligand functionalization for enhanced targeted therapeutics in precision medicine by Sakshi Shahapurmath, Bhuvaneshwari R. Sharannavar, Rahul Koli

“…This review serves as a critical resource for researchers, fostering advancements in the rational design and optimization of albumin-based nanocarriers for precision drug delivery.…”
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Construction of Evaluation Model for Soil and Water Conservation Function of Vegetation at Community Scale by Zhang Hongda, Zhao Chuanpu, Dai Yuting, Yuan Li, Yang Qimengdi, Wu Ao, Liu Xia

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The proteome of circulating extracellular vesicles and their functional effect on platelets vary with the isolation method by Eva M. Fernández-Sáez, Susana B. Bravo, Carmen Pena, Ángel García

“…Abstract Extracellular vesicles (EVs) play a crucial role in cell-to-cell communication and serve as a source of biomarkers in several pathologies. In this study, we aimed to characterize plasma-derived EVs isolated by ultracentrifugation (UC) or size exclusion chromatography (SEC) to define the best method for proteomic and functional studies. …”
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Legume-based rotation alters soil eukaryotic community and improves soil multifunctionality by Tingwei Meng, Yi Fan, Yiheng Tao, Yi Wu, Shuang Pang, Wei Yang, Xiaoyu Guo, Ximei Zhang

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FsDAOD: Few-shot domain adaptation object detection for heterogeneous SAR image by Siyuan Zhao, Yong Kang, Hang Yuan, Guan Wang, Hui Wang, Shichao Xiong, Ying Luo

“…Heterogeneous Synthetic Aperture Radar (SAR) image object detection task with inconsistent joint probability distributions is occurring more and more frequently in practical applications. …”
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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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ZnCl2-activated S/N-doped biochar for low-temperature NH3-SCR of NOx: Performance and pathway analysis by Shuangshuang Yan, Dongmei Bi, Chengxizi Zhang, Zhisen He, Yu Ni, Kang Yue, Shanjian Liu

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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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Network security traffic detection and legal supervision based on adaptive metric learning algorithm by Liu Zhen

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App-DDoS detection method using partial binary tree based SVM algorithm by Bin ZHANG, Zihao LIU, Shuqin DONG, Lixun LI

“…As it ignored the detection of ramp-up and pulsing type of application layer DDoS (App-DDoS) attacks in existing flow-based App-DDoS detection methods,an effective detection method for multi-type App-DDoS was proposed.Firstly,in order to fast count the number of HTTP GET for users and further support the calculation of feature parameters applied in detection method,the indexes of source IP address in multiple time windows were constructed by the approach of Hash function.Then the feature parameters by combining SVM classifiers with the structure of partial binary tree were trained hierarchically,and the App-DDoS detection method was proposed with the idea of traversing binary tree and feedback learning to distinguish non-burst normal flow,burst normal flow and multi-type App-DDoS flows.The experimental results show that compared with the conventional SVM-based and naïve-Bayes-based detection methods,the proposed method has more excellent detection performance and can distinguish specific App-DDoS types through subdividing attack types and training detection model layer by layer.…”
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