Enterococcus faecalis strains derived from wild bird provide protection against Clostridium perfringens challenge in locally-sourced broilers by Gerui Zhang, Ainul Zahra, Tianrui Yang, Qiyu Guo, Yan Sun, Yuhang Zhang, Yupeng Gao, Yuxi Zhang, Mingyue Wang, Jingshuo Gong, Haibin Huang, Zhannan Wang, Chunfeng Wang, Yanlong Jiang

“…IntroductionNecrotic enteritis (NE), caused by Clostridium perfringens, has seen a surge in chicken populations recently due to the ban on antibiotic growth promoters in feed.MethodsIn this research, screening and identification of probiotics with strong antagonistic ability against C. perfringens from 34 wild bird fecal isolates, followed by analysis of probiotic characteristics and carbon source metabolic activity. Strains exhibiting favorable antagonistic activity against C. perfringens were subsequently employed in vivo study to evaluate their protective efficacy against C. perfringens challenge in locally-sourced broilers.ResultsThe results showed that Enterococcus faecalis strains YL-EF25 and YL-EF32 were selected based on their ability to inhibit the growth and biofilm formation of C. perfringens. …”
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Pisum sativum L. as an alternative protein and starch source in Italian Mediterranean buffaloes’ feeding plan: in vitro evaluation of different varieties by Alessandro Vastolo, Roberta Matera, Giulia Passarelli, Serena Calabrò, Matteo Santinello, Gianluca Neglia, Monica Isabella Cutrignelli

“…After multivariate cluster analysis, Ganster, Poisedon and Peps were selected for the second trial in function of highest organic and protein degradability. …”
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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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Optimization of Protein Extraction from Sunflower Meal Using Taguchi Design and Regression Modeling for Human Nutrition Applications by Anca Becze, Marin Senila, Lacrimioara Senila, Lucian Dordai, Oana Cadar, Vanda Liliana Fuss-Babalau, Marius Roman, Levente Levei, Paul Uiuiu, Mihai Octavian Naghiu

“…Safety analyses confirmed the absence of detectable aflatoxins and very low PAH levels. These results support the use of sunflower protein concentrate as a sustainable, nutritionally valuable, and safe ingredient for functional food applications. …”
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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

“…Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable principles embraced by smart cities. …”
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Isolation and Functional Characterization of Yeasts from Fermented Plant Based Products by Dilara Devecioglu, Anı Kuscu, Funda Karbancioglu-Guler

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ANTHOCYANIN AS NATURAL COLORANT: A REVIEW by Winda Nurtiana

“…Today, natural colorant is consumer’s selection because it has functional function. One of natural colorant is anthocyanin. …”
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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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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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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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Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

“…Therefore, the findings of this paper could be used when designing a custom wood detection network. With the growing availability of flood-related videos featuring wood uploaded to the internet, this methodology facilitates the quantification of wood transport across a wide variety of data sources.…”
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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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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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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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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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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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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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