Dongbo Wu^1,#, Shuang Qu^2,#, Lianwen Shen², Shengqun Chen², Xia Jiang^2,3, Ai Rao¹, Yuxue Zhao^2,*, Yueyun Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1455-1466, 2024, DOI:10.32604/phyton.2024.051652

Abstract Cymbidium goeringii is an economically important ornamental plant, and flower color is one of the main features of C. goeringii that contributes to its high economic value. To clarify the molecular mechanisms underlying the role of anthocyanins in mediating differences in color among varieties, liquid chromatography–tandem mass spectrometry was used to perform anthocyanin-targeted metabolomics of seven C. goeringii varieties, including ‘Jin Qian Yuan’ (JQY), ‘Jin Xiu Qian Yuan’ (JXQY), ‘Miao Jiang Su Die’ (MJSD), ‘Qian Ming Su’ (QMS), ‘Shi Chan’ (SC), and ‘Yang Ming Su’ (YMS), as well as the C. goeringii. We detected 64 anthocyanins, including cyanidins, delphinidins,… More >

Wenjie Dong^1,2,#, Zhibin Hong^1,#, Aqian Wang², Kaiyu Jiang², Hai Zhu², Fu zhang², Zhaoxia Guo², Hongling Su^2,*, Yunshan Cao^3,*

Congenital Heart Disease, Vol.19, No.3, pp. 325-339, 2024, DOI:10.32604/chd.2024.052267

Abstract Background: Current guidelines for managing pulmonary arterial hypertension (PAH) recommend a risk stratification approach. However, the applicability and accuracy of these strategies for PAH associated with congenital heart disease (PAH-CHD) require further validation. This study aims to validate the reliability and predictive accuracy of a simplified stratification strategy for PAH-CHD patients over a three-year follow-up. Additionally, new prognostic variables are identified and novel risk stratification methods are developed for assessing and managing PAH-CHD patients. Methods: This retrospective study included 126 PAH-CHD patients. Clinical and biochemical variables across risk groups were assessed using Kruskal-Wallis and Fisher’s… More > Graphic Abstract

S. F. Ismael^1,2,*, A. H. Alias¹, N. A. Haron¹, B. B. Zaidan³, Abdulrahman M. Abdulghani⁴

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 525-551, 2024, DOI:10.32604/sdhm.2024.050088

Abstract In this review paper, we present a thorough investigation into the role of pavement technologies in advancing urban sustainability. Our analysis traverses the historical evolution of these technologies, meticulously evaluating their socio-economic and environmental impacts, with a particular emphasis on their role in mitigating the urban heat island effect. The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making (MCDM) framework to choose the optimal pavement application are at the heart of our research. Which serves to assess a spectrum of pavement options, revealing insights into the most More >

Ao Lu¹, Ming Xiong¹, Chen Chen¹, Liangjiang Li¹, Haibei Tan¹, Xiong Xu^2,3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1633-1646, 2024, DOI:10.32604/fdmp.2024.051010

Abstract Traditional asphalt rejuvenators, like aromatic oil (AO), are known to be effective in improving the low-temperature properties and fatigue performances of aged SBS (styrene-butadiene-styrene) modified asphalt (SBSMA) binders and mixtures. However, these rejuvenators inevitably compromise their high-temperature properties and deformation resistances because they dilute asphalt binder but do not fix the damaged structures of aged SBS. In this study, a highly-active chemical called polymerized 4,4-diphenylmethane diisocyanate (PMDI) was used to assist the traditional AO asphalt rejuvenator. The physical and rheological characteristics of rejuvenated SBSMA binders and the moisture-induced damage and rut deformation performances of corresponding… More > Graphic Abstract

Nisreen Innab¹, Ahmed Abdelgader Fadol Osman², Mohammed Awad Mohammed Ataelfadiel², Marwan Abu-Zanona^3,*, Bassam Mohammad Elzaghmouri⁴, Farah H. Zawaideh⁵, Mouiad Fadeil Alawneh⁶

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1325-1345, 2024, DOI:10.32604/cmc.2024.051778

Abstract Phishing, an Internet fraud where individuals are deceived into revealing critical personal and account information, poses a significant risk to both consumers and web-based institutions. Data indicates a persistent rise in phishing attacks. Moreover, these fraudulent schemes are progressively becoming more intricate, thereby rendering them more challenging to identify. Hence, it is imperative to utilize sophisticated algorithms to address this issue. Machine learning is a highly effective approach for identifying and uncovering these harmful behaviors. Machine learning (ML) approaches can identify common characteristics in most phishing assaults. In this paper, we propose an ensemble approach… More >

BIOCELL, Vol.48, Suppl.3, pp. 1-15, 2024

Abstract This article has no abstract. More >

BIOCELL, Vol.48, Suppl.2, pp. 1-71, 2024

Abstract This article has no abstract. More >

Oncology Research Editorial Office

Oncology Research, Vol.32, No.8, pp. 1381-1381, 2024, DOI:10.32604/or.2024.055035

Abstract This article has no abstract. More >

Deema Mohammed Alsekait^1,*, Asif Nawaz², Ayman Nabil³, Mehwish Bukhari², Diaa Salama AbdElminaam^3,4,5,6,*

Computer Systems Science and Engineering, Vol.48, No.4, pp. 1031-1054, 2024, DOI:10.32604/csse.2024.051847

Abstract The article describes a novel method for sentiment analysis and requirement elicitation from social media feedback, leveraging advanced machine learning techniques. This innovative approach automates the extraction and classification of user requirements by analyzing sentiment in data gathered from social media platforms such as Twitter and Facebook. Utilizing APIs (Application Programming Interface) for data collection and Graph-based Neural Networks (GNN) for feature extraction, the proposed model efficiently processes and analyzes large volumes of unstructured user-generated content. The preprocessing pipeline includes data cleaning, normalization, and tokenization, ensuring high-quality input for the sentiment analysis model. By classifying… More >

Yue Wan, Nan Jiang^*, Ziyu Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3017-3034, 2024, DOI:10.32604/cmes.2024.051101

Abstract The Social Internet of Things (SIoT) integrates the Internet of Things (IoT) and social networks, taking into account the social attributes of objects and diversifying the relationship between humans and objects, which overcomes the limitations of the IoT’s focus on associations between objects. Artificial Intelligence (AI) technology is rapidly evolving. It is critical to build trustworthy and transparent systems, especially with system security issues coming to the surface. This paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT, aiming to build an SIoT hypergraph generation… More >