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

“…Therefore, this study aimed at the bio‐functional and structural characterization of A. heterophyllus peel waste for unlocking its potential for food applications. …”
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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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Automatic Recognition of Authors Identity in Persian based on Systemic Functional Grammar by Fatemeh Soltanzadeh, Azadeh Mirzaei, Mohammad Bahrani, Shahram Modarres Khiabani

“…First, a corpus composed of documents written by seven contemporary Iranian authors was collected. Second, a list of function words was extracted from the corpus. Moreover, conjunction, modality and comment adjunct system networks were applied to form a lexicon using linguistics resources. …”
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Novel electrochemical sensor for the determination of potassium ions based on silver diethyldithiocarbamate as sensor material by Oguz Özbek, Mehmet Alperen Şahin

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The valorization of poppy seed cake for Pickering stabilization of functional ice creams by Nujamee Ngasakul, Michaela Freyová, Ali Kozlu, Diana Karina Baigts Allende, Iveta Klojdová

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Multi-Function Evaluation and Internal Land Use Optimization of Rural Settlements by Nan Wang, Lei Zhang, Jinmin Hao, Jinyi Zhang

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Progress in functional covalent organic frameworks as advanced materials for sample pretreatment by Hui Cao, WeiKang Guo, Ke Liu, Qin Shuai, Lijin Huang, Zhaochu Hu

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Development of the recipe and technology of semi-finished mock cutlets of functional purpose by A. B. Tkhaishaova, Z. N. Khatko, N. A. Loban

“…Mechanically deboned poultry meat is characterized by less technological potential and is in need of increase its functional and technological properties in the formation of food systems with specified properties.The article shows the possibility of expanding the assortment of meat chopped semi-finished products (cutlets) of functional purpose using a compositional mixture in a recipe that helps to increase biological and nutritional value.The purpose of the research is to develop the recipe and technology of mechanically deboned poultry meat semi-finished products (cutlets) of functional purpose using non-traditional raw materials, namely compositional mixture (CM).The qualitative and quantitative composition of the compositional mixture for cutlets of functional purpose from mechanically deboned poultry meat has been substantiated and selected.The influence of the dosage of the compositional mixture consisting of a solid Adygh cheese«Mate» (powder), oatmeal and garlic powder, on the consumer properties of mechanically deboned poultry meat has been investigated. …”
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Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network by Noor Habib Khan, Yong Wang, Raheela Jamal, Sheeraz Iqbal, Mohamed Ebeed, Yazeed Yasin Ghadi, Z. M. S. Elbarbary

“…Nowadays, thermal generators are no longer utilized and renewable resources (RERs) have been integrated owing to their marvellous benefits. …”
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Electronic–Oxygen Synergy at Ca-Fe Dual-Metal Interfaces for Selective Syngas Regulation in Biomass Chemical Looping Gasification by Yijie Wang, Jiajie Li, Sitao Zhu, Michael Hitch

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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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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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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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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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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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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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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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A Comparative Analysis of Machine Learning and Pedotransfer Functions Under Varying Data Availability in Two Greek Regions by Panagiotis Tziachris, Panagiota Louka, Eirini Metaxa, Miltiadis Iatrou, Konstantinos Tsiouplakis

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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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