Lianyuan Ji¹, Mingchen Shi¹, Zengkai Feng², Hui Yang^1,*

Journal of Renewable Materials, Vol.12, No.2, pp. 259-274, 2024, DOI:10.32604/jrm.2023.030599

Abstract

Cobalt sulphides attract much attention as anode materials for Li-ion batteries (LIBs). However, its poor conductivity, low initial column efficiency and large volume changes during cycling have hindered its further development. Herein, novel interlaced CoS nanosheets were firstly prepared on Carbon Fiber Cloth (CFC) by two hydrothermal reactions followed with carbon coating via carbonizing dopamine (CoS NS@C/CFC). As a freestanding anode, the nanosheet structure of CoS not only accommodates the volume variation, but also provides a large interface area to proceed the charge transfer reaction. In addition, CFC works as both a three-dimensional skeleton and an active substance which can… More >

Adnan Ali¹, Jinlong Li¹, Huanhuan Chen¹, Uzair Aslam Bhatti², Asad Khan^3,*

Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 241-258, 2023, DOI:10.32604/iasc.2023.041645

Abstract Spammer detection is to identify and block malicious activities performing users. Such users should be identified and terminated from social media to keep the social media process organic and to maintain the integrity of online social spaces. Previous research aimed to find spammers based on hybrid approaches of graph mining, posted content, and metadata, using small and manually labeled datasets. However, such hybrid approaches are unscalable, not robust, particular dataset dependent, and require numerous parameters, complex graphs, and natural language processing (NLP) resources to make decisions, which makes spammer detection impractical for real-time detection. For example, graph mining requires neighbors’… More >

Fady Samann^1,*, Shavan Askar²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2715-2734, 2023, DOI:10.32604/cmc.2023.043580

Abstract Clustering schemes in vehicular networks organize vehicles into logical groups. They are vital for improving network performance, accessing the medium, and enabling efficient data dissemination. Most schemes rely on periodically broadcast hello messages to provide up-to-date information about the vehicles. However, the periodic exchange of messages overwhelms the system and reduces efficiency. This paper proposes the Flag-based Vehicular Clustering (FVC) scheme. The scheme leverages a combination of Fitness Score (FS), Link Expiration Time (LET), and clustering status flags to enable efficient cluster formation in a hybrid manner. The FVC relies on the periodic broadcast of the basic safety message in… More >

Fady Samann^1,*, Shavan Askar²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2421-2444, 2024, DOI:10.32604/cmes.2023.031265

Abstract Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms. K-clustering algorithms are simplistic, with fast performance and relative accuracy. However, their implementation depends on the initial selection of clusters number (K), the initial clusters’ centers, and the clustering metric. This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time (LET) as a clustering metric. Realistic traffic flows were considered for three maps, namely Highway, Traffic Light junction, and Roundabout junction, to study the effect of road layout on… More >

Dinesh Kalla^1,*, Sivaraju Kuraku²

Journal on Artificial Intelligence, Vol.5, pp. 145-162, 2023, DOI:10.32604/jai.2023.043366

Abstract Phishing websites present a severe cybersecurity risk since they can lead to financial losses, data breaches, and user privacy violations. This study uses machine learning approaches to solve the problem of phishing website detection. Using artificial intelligence, the project aims to provide efficient techniques for locating and thwarting these dangerous websites. The study goals were attained by performing a thorough literature analysis to investigate several models and methods often used in phishing website identification. Logistic Regression, K-Nearest Neighbors, Decision Trees, Random Forests, Support Vector Classifiers, Linear Support Vector Classifiers, and Naive Bayes were all used in the inquiry. This research… More >

FAYU SHAN¹, LANLAN LIANG¹, CHONG FENG¹, HONGBAO XU¹, ZIROU WANG¹, WEILI LIU¹, LINGLING PU¹, ZHAOLI CHEN¹, GANG CHEN^2,*, XINXING WANG^1,*

Oncology Research, Vol.31, No.4, pp. 481-493, 2023, DOI:10.32604/or.2023.029064

Abstract Background: Oral squamous cell carcinoma (OSCC) is a common malignant tumor. Recently, Laminin Gamma 2 (LAMC2) has been shown to be abnormally expressed in OSCC; however, how LAMC2 signaling contributes to the occurrence and development of OSCC and the role of autophagy in OSCC has not been fully explored. This study aimed to analyze the role and mechanism of LAMC2 signaling in OSCC and the involvement of autophagy in OSCC. Methods: To explore the mechanism by which LAMC2 is highly expressed in OSCC, we used small interfering RNA (siRNA) to knock down LAMC2 to further observe the changes in the… More >

Ibrahim M. Alwayle¹, Badriyya B. Al-onazi², Mohamed K. Nour³, Khaled M. Alalayah¹, Khadija M. Alaidarous¹, Ibrahim Abdulrab Ahmed⁴, Amal S. Mehanna⁵, Abdelwahed Motwakel^6,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2947-2961, 2023, DOI:10.32604/csse.2023.034456

Abstract Online reviews regarding purchasing services or products offered are the main source of users’ opinions. To gain fame or profit, generally, spam reviews are written to demote or promote certain targeted products or services. This practice is called review spamming. During the last few years, various techniques have been recommended to solve the problem of spam reviews. Previous spam detection study focuses on English reviews, with a lesser interest in other languages. Spam review detection in Arabic online sources is an innovative topic despite the vast amount of data produced. Thus, this study develops an Automated Spam Review Detection using… More >

JUAN C. STOCKERT^1,2,*, SILVINA A. ROMERO¹, MARCELO N. FELIX-POZZI³, ALFONSO BLÁZQUEZ-CASTRO⁴

BIOCELL, Vol.47, No.4, pp. 919-928, 2023, DOI:10.32604/biocell.2023.026631

Abstract

The ¹⁰boron neutron-capture therapy (BNCT) is an emerging antitumoral method that shows increasing biomedical interest. BNCT is based on the selective accumulation of the ¹⁰boron isotope within the tumor, which is then irradiated with low-energy thermal neutrons, generating nuclear fission that produces ⁷lithium, ⁴helium, and γ rays. Simple catechol-borate esters have been rather overlooked as precursors of melanin biosynthesis, and therefore, a proof-of-concept approach for using dopamine-borate (DABO) as a suitable boron-containing candidate for potential BNCT is presented here. DABO can spontaneously oxidize and autopolymerize in vitro, giving a soluble, eumelanin-like brown-black poly-DABO product. Melanotic melanoma cell cultures treated with… More >

Xue Huang^1,*, Zeyu Chen¹, Ruizhao Yang¹, Guangzhu Feng²

Journal of Renewable Materials, Vol.11, No.5, pp. 2301-2319, 2023, DOI:10.32604/jrm.2023.025888

Abstract 1,3-Dioleoyl-2-palmitoylglycerol (OPO) has been a hotspot of functional oils research in recent years, but due to the high cost of sn-1,3 specific lipase in enzymatic synthesis and the lack of biocatalyst stability, large-scale industrial application is difficult. In this study, the prepared magnetic ZnFe₂O₄ was functionalized with dopamine to obtain ZnFe₂O₄@PDA, and the nano-biocatalyst ZnFe₂O₄@PDA@RML was prepared by immobilizing sn-1,3 specific lipase of Rhizomucor miehei lipase (RML) via a cross-linking method. The existence of RML on ZnFe₂O₄@PDA was confirmed by XRD, FTIR, SEM, and TEM. This strategy proved to be simple and effective because the lipase immobilized on magnetic nanoparticles… More > Graphic Abstract

Sujithra Kanmani^*, Surendiran Balasubramanian

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1439-1454, 2023, DOI:10.32604/csse.2023.029953

Abstract Online reviews significantly influence decision-making in many aspects of society. The integrity of internet evaluations is crucial for both consumers and vendors. This concern necessitates the development of effective fake review detection techniques. The goal of this study is to identify fraudulent text reviews. A comparison is made on shill reviews vs. genuine reviews over sentiment and readability features using semi-supervised language processing methods with a labeled and balanced Deceptive Opinion dataset. We analyze textual features accessible in internet reviews by merging sentiment mining approaches with readability. Overall, the research improves fake review screening by using various transformer models such… More >