Circular Animal Protein Hydrolysates: A Comparative Approach of Functional Properties by Marta Monteiro, Luciano Rodrigues-dos-Santos, Andreia Filipa-Silva, Diana A. Marques, Manuela Pintado, André Almeida, Luisa M. P. Valente

“…Conversely, SHARK and FISH supported opportunistic bacteria growth, suggesting a potential use as nitrogen sources in microbial media. These findings highlight the nutritional and functional versatility of animal-derived protein hydrolysates and support their integration into sustainable feed strategies within a circular bioeconomy.…”
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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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Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

“…Key findings are summarized in a comparative matrix, highlighting trends, gaps, and inconsistencies across publication sources. This review identifies critical research gaps—including the underuse of hybrid models, lack of benchmark datasets, and limited integration between detection and control layers—and offers concrete recommendations for future research. …”
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An optimization method of multiscale storage tank target detection introducing an attention mechanism by Wenjia Sun, Chunchun Hu, Nianxue Luo, Qiansheng Zhao

“…As containers for chemical storage, storage tanks are potential sources of hazards. Conducting target detection for hazard risk analysis is essential. …”
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Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images by Resky Adhyaksa, Bedy Purnama

“…The training and testing phases utilized an 80:20 split of the data, employing binary cross-entropy as the loss function and the Adam optimizer for efficient weight updates. …”
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Multi-Person Fall Detection Using Data Assimilation Method With Kalman Filter by Jinmo Yang, Ye Jin Jin, R. Young Chul Kim

“…Fall detection is an essential technology for ensuring the safety of elderly individuals, as falling accidents are critical and can cause significant functional damage in old age. …”
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Detection of Elementary White Mucosal Lesions by an AI System: A Pilot Study by Gaetano La Mantia, Federico Kiswarday, Giuseppe Pizzo, Giovanna Giuliana, Giacomo Oteri, Mario G. C. A. Cimino, Olga Di Fede, Giuseppina Campisi

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Joint planning of energy storage site selection and line capacity expansion in distribution networks considering the volatility of new energy by Xu Feifei, Pan Xia, Chen Bowei, Li Xiaoshuang, Nie Zhi, Feng Miaoyong, Feng Miaoyong

“…This technology uses CHk-means clustering calculations based on actual large-scale operation data of new energy sources to generate typical operating curves. Then, it finely constructs an objective function considering power transmission in the transmission-distribution network, abandonment of new energy, line limits, and energy storage construction. …”
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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

“…In addition, the superiority of the proposed fault detection and classification approaches using ML tools was assessed by comparing the detection and classification efficiency through some statistical performance parameter comparisons among the classifiers.…”
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Stimuli Selection Criteria for the Experiment “Visual Perception of Imitative Words in Native and Non-Native Language by the Method Lexical Decision” by M. A. Flaksman, Yu. V. Lavitskaya, Yu. G. Sedelkina, L. O. Tkacheva

“…The authors also use psycho-semantic methods such as the method of lexical decision. The main sources of stimuli selection are The Russia Etymological Dictionary by M. …”
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New Horizon in Selective Tocols Extraction from Deodorizer Distillates Under Mild Conditions by Using Deep Eutectic Solvents by Dian Maria Ulfa, Asep Bayu, Siti Irma Rahmawati, Peni Ahmadi, Masteria Yunovilsa Putra, Surachai Karnjanakom, Guoqing Guan, Abdul Mun’im

“…The basic principles of intermolecular interactions (H-bond, van der Walls bond, and misfit interaction) between DESs or their components with tocols are discussed to understand the mechanism by which DESs selectively extract tocols from the mixture. This is mainly observed to be a function of the intrinsic properties of DESs and/or tocols, which could be beneficial for tuning the appropriate DESs for extracting tocols selectively and effectively under mild operation conditions. …”
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Passport fee – its legal nature, structure, functions and purpose of proceeds by Zbigniew Ofiarski

“…Author identifies its legal nature, performed functions and analyses rules of collection of this fee which are regulated in the provisions of the Passport Documents Act. …”
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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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A Susceptible Cell‐Selective Delivery (SCSD) of mRNA‐Encoded Cas13d Against Influenza Infection by Zhuanli Wu, Chengcheng Zhao, Hui Ai, Zhen Wang, Mingyue Chen, Yanli Lyu, Qi Tong, Litao Liu, Honglei Sun, Juan Pu, Ran Zhang, Xiaoxiang Hu, Jinhua Liu, Xiaowei Ma, Yipeng Sun

“…Given that the virus targets cells with specific receptors but is not limited to a single organ, a Susceptible Cell Selective Delivery (SCSD) system is developed by modifying a lipid nanoparticle with a peptide mimicking the function of the hemagglutinin of influenza virus to target sialic acid receptors. …”
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Synthesis of Molecularly Imprinted Polymers for Selective Extraction Followed by Solid Phase Determination of Metformin in Pharmaceutical Preparation and in Human Serum by Rana A. Kamal Aldeen, Yehya K. Al-Bayati

“…A solid-phase extraction (SPE) syringe packed with molecular imprinted polymers (MIPs) was employed to selectively separate and pre-concentrate the Metformin in multiple pharmaceutical drugs from several sources. …”
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The functions of religion and science in utopian thinking in the middle ages and the early modern period by Hope Steffen

“…The selection of sources includes both widely-known utopian texts and materials that are rarely used in discussions of utopian thinking. …”
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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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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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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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