Failure Law of Sandstone and Identification of Premonitory Deterioration Information Based on Digital Image Correlation–Acoustic Emission Multi-Source Information Fusion by Zhaohui Chong, Guanzhong Qiu, Xuehua Li, Qiangling Yao

“…Additionally, by introducing the derivative functions of the multi-source information function for quantitative analysis, a comprehensive evaluation method was proposed based on the multi-source information fusion monitoring to forewarn red sandstone failure by levels during loading. …”
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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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A Contrast-Enhanced Approach for Aerial Moving Target Detection Based on Distributed Satellites by Yu Li, Hansheng Su, Jinming Chen, Weiwei Wang, Yingbin Wang, Chongdi Duan, Anhong Chen

“…This method compensates for the range difference rather than the target range. In the detection period, we develop two weighting functions, i.e., the Doppler frequency rate (DFR) variance function and smooth spatial filtering function, to extract prominent areas and make efficient detection, respectively. …”
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Yarn-electrospun PVDF-HFP/CNC smart textiles for self-powered sensor in wearable electronics by Jiawei Chen, Subhamoy Mahajan, Manisha Gupta, Cagri Ayranci, Tian Tang

“…The success of developing such sensor-integrated touchscreen gloves paves new avenues for human-technology interactions, highlights the dual functionality of these yarns as power sources and sensors, and represents a milestone in broadening the applications of wearable technologies.…”
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Rapid Spectral Evolution of SGR 1935+2154 during Its 2022 Outburst by Chin-Ping Hu, Zorawar Wadiasingh, Wynn C. G. Ho, Matthew G. Baring, George A. Younes, Teruaki Enoto, Sebastien Guillot, Tolga Güver, Marlon L. Bause, Rachael Stewart, Alex Van Kooten, Chryssa Kouveliotou

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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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DETECTIVE STORY: TO THE PROBLEM OF VARIABILITY OF THE MAIN EVENT AND CHARACTERS (BY THE CASE OF A. SARAKHOV’S STORIES) by I. A. KAZHAROVA

“…The functionality of stereotypes of perception and «memory of the genre» is briefly presented, which manifests itself in the history of understanding a domestic detective story as a constant appeal to the foreign sources of the genre. …”
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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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Study on Point Spread Function of Perovskite Fast Neutron Scintillation Imaging Screen by FENG Zhelin1, LIU Linyue2, , SONG Yan2, DUAN Baojun2, BAO Zizhen3, OUYANG Xiaoping2

“…Additionally, the limited availability of experimental machines for fast neutron imaging and the high cost of imaging systems hinders the efficient detection of large number of materials by using common fast neutron sources. …”

A powerful molecular marker to detect mutations at sorghum LOW GERMINATION STIMULANT 1 by Adedayo O. Adeyanju, Patrick J. Rich, Gebisa Ejeta

“…The LGS1 marker is useful for both detecting sources of lgs1 and introgressing Striga resistance into new genetic backgrounds.…”
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Specific detection of tartaric acid chiral isomers based on centrosymmetric terahertz metamaterial sensors by Xujun Xu, Zhen Sun, Guocui Liu, Jianjun Liu, Yong Du

“…Traditional detection methods, such as fluorescence detection, have problems such as destructive and non-specific characters. …”
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The Relevance of Osteoscintigraphy Technique in Early Detection of Bone Metastatic Lesions: a Systematic Review by E. A. Litvinenko, I. V. Burova

“…OSG is an effective and informative technique for early detection of bone metastases, allowing to assess the functional state of the tumor and its surrounding tissues, even before the appearance of structural disorders visible by other diagnostic methods. …”
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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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National occupational safety and health systems: Exploring the underlying networks for future sustainable development by Gaia Vitrano, Guido J.L. Micheli

“…These findings provide valuable insights into how these functions are carried out differently across countries, detecting potential shareable best practices and improvement directions for the future sustainability of national OSH systems.…”
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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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Morphological and functional characteristics of Trichinella sp. larvae in bears and badgers in the Kirov Region by O. B. Zhdanova, I. I. Okulova, A. V. Uspensky, L. A. Napisanova

“…For postmortem diagnosis of trichinellosis in the obtained bears and badgers, we can use trichinelloscopy and peptolysis methods which are aimed at detecting infection sources and preventing zoonosis in humans.…”
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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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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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Design and investigation of charge plasma-based TMD heterojunction TFET biosensor for ultrasensitive detection by Monika Kumari, Niraj Kumar Singh, Vinay Kantipudi, Manodipan Sahoo

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