Asal Jameel Khudhair^#, Amenah Dahim Abbood^#,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-31, 2026, DOI:10.32604/cmc.2025.068553 - 10 November 2025

Abstract Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities. Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can. Therefore, we utilized two objective functions… More >

Masefako Andronica Gumani^*

Journal of Psychology in Africa, Vol.35, No.6, pp. 807-814, 2025, DOI:10.32604/jpa.2025.065776 - 30 December 2025

Abstract This study explored law enforcement members’ empathetic engagements with primary survivors of trauma. Informants were 15 South African Police Service members from a rural district of the Limpopo (females = 26.6%; constables = 13.3%). Unstructured open-ended and follow-up telephone interviews, field notes, and diaries were used as data-collection methods. Data were analysed following the Interpretative Phenomenological Analysis guidelines. Emergent themes indicated that law enforcement members engage in three types of empathy, namely affective, cognitive, and cognitive-affective empathy when called upon to help survivors of trauma. Their affective empathy involved police members’ emotional connection with the More >

Miah A. Robinson, Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Khalid H. Abed^*

Journal on Artificial Intelligence, Vol.7, pp. 615-632, 2025, DOI:10.32604/jai.2025.073535 - 01 December 2025

Abstract Ensuring the safety of Artificial Intelligence (AI) is essential for providing dependable services, especially in various sectors such as the military, education, healthcare, and automotive industries. A highly effective method to boost the precision and performance of an AI agent involves multi-configuration training, followed by thorough evaluation in a specific setting to gauge performance outcomes. This research thoroughly investigates the design of three AI agents, each configured with a different number of hidden units. The first agent is equipped with 128 hidden units, the second with 256, and the third with 512, all utilizing the… More >

Ayaz Hussain¹, Asad Hayat², Muhammad Hasnain^1,*

Journal on Artificial Intelligence, Vol.7, pp. 485-498, 2025, DOI:10.32604/jai.2025.071933 - 17 November 2025

Abstract Violent hate speech and scapegoating people against one another have emerged as a rising worldwide issue. But identifying and combating such content is crucial to create safer and more inclusive societies. The current study conducted research using Machine Learning models to classify hate speech and overcome the limitations posed in the existing detection techniques. Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbour (KNN) and Decision Tree were used on top of a publicly available hate speech dataset. The data was preprocessed by cleaning the text and tokenization and using normalization techniques to efficiently train the… More >

Si-Yu Gao¹, Siu-Man Ng^2,*

International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1471-1482, 2025, DOI:10.32604/ijmhp.2025.068702 - 31 October 2025

Abstract Background: Existing Chinese stigma scales focus on the perceptions of people with mental illness (PMI) without assessing the general public’s attitudes toward integrating PMI into the community. Developing a valid and reliable Chinese instrument measuring the attitude domain will be helpful to future research in this area. The current study aimed to validate a shortened Chinese version of the Community Attitudes towards the Mentally Ill Scale (C-CAMI-SF). Methods: Four hundred participants who are (1) Chinese; (2) aged 18 years and above; and (3) able to complete the Chinese questionnaire in a self-reported manner participated in… More >

Hiba Sameer Saeed^#, Amenah Dahim Abbood^#,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4375-4405, 2025, DOI:10.32604/cmc.2025.067783 - 23 October 2025

Abstract In recent years, the evolution of the community structure in social networks has gained significant attention. Due to the rapid and continuous evolution of real-world networks over time. This makes the process of identifying communities and tracking their topology changes challenging. To tackle these challenges, it is necessary to find efficient methodologies for analyzing the behavior patterns of dynamic communities. Several previous reviews have introduced algorithms and models for community detection. However, these methods have not been very accurate in identifying communities. Moreover, none of the reviewed papers made an apparent effort to link algorithms… More >

De Zhang^1,2, Yuan-Zu Ji¹, Tong Zhao¹, Jun-Ying Zhao^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2815-2838, 2025, DOI:10.32604/phyton.2025.069196 - 30 September 2025

Abstract This study investigated the effects of planting duration (1, 5, 10 and 15 years) on soil properties, bacterial community diversity, and function in the rhizosphere of Zanthoxylum bungeanum. We employed Illumina high-throughput sequencing and PICRUSt2 functional prediction to analyze the structure and functional potential of rhizosphere soil bacterial communities. The Mantel test and redundancy analysis were used to identify physicochemical factors influencing bacterial community structure and function. The results indicated significant differences in rhizosphere soil physicochemical properties across planting years: the content of organic matter, alkaline hydrolyzable nitrogen in the soil, as well as the activity… More >

Qi Chen^1,2, Yizhuo Du¹, Yingsheng Liu¹, Yue Li¹, Chuang Li¹, Zhelun Xu^1,3, Congyan Wang^1,4,5,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2873-2891, 2025, DOI:10.32604/phyton.2025.065970 - 30 September 2025

Abstract The leaves of multiple invasive plants can coexist and intermingle within the same environment. As species number of invasive plants increases, variations may occur in decomposition processes of invasive plants, soil nutrient contents, soil enzyme activities, and soil microbial community structure. Existing progress have predominantly focused on the ecological effects of one species of invasive plant compared to native species, with limited attention paid to the ecological effects of multiple invasive plants compared to one species of invasive plant. This study aimed to determine the differences in the effects of mono- and co-decomposition of four… More >

Panyu Liu¹, Tongqing Zhou^1,*, Guofeng Lu², Huaizhe Zhou³, Zhiping Cai¹

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2913-2934, 2025, DOI:10.32604/cmc.2025.069175 - 23 September 2025

Abstract The isolation of healthcare data among worldwide hospitals and institutes forms barriers for fully realizing the data-hungry artificial intelligence (AI) models promises in renewing medical services. To overcome this, privacy-preserving distributed learning frameworks, represented by swarm learning and federated learning, have been investigated recently with the sensitive healthcare data retaining in its local premises. However, existing frameworks use a one-size-fits-all mode that tunes one model for all healthcare situations, which could hardly fit the usually diverse disease prediction in practice. This work introduces the idea of ensemble learning into privacy-preserving distributed learning and presents the More >

Adnan Amin, Wajid Zaman^*

Phyton-International Journal of Experimental Botany, Vol.94, No.7, pp. 1973-1996, 2025, DOI:10.32604/phyton.2025.067885 - 31 July 2025

Abstract Plant-pathogen interactions involve complex biological processes that operate across molecular, cellular, microbiome, and ecological levels, significantly influencing plant health and agricultural productivity. In response to pathogenic threats, plants have developed sophisticated defense mechanisms, such as pattern-triggered immunity (PTI) and effector-triggered immunity (ETI), which rely on specialized recognition systems such as pattern recognition receptors (PRRs) and nucleotide-binding leucine-rich repeat (NLR) proteins. These immune responses activate intricate signaling pathways involving mitogen-activated protein kinase cascades, calcium fluxes, reactive oxygen species production, and hormonal cross-talk among salicylic acid, jasmonic acid, and ethylene. Furthermore, structural barriers such as callose deposition… More >