Antonios Chrysargyris^1,*, Demetris Antoniou², Timos Boyias², Nikolaos Tzortzakis^1,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.076565 - 30 January 2026

Abstract Cyprus has an extensive record in grape production and winemaking. Grapevine is essential for the economic and environmental sustainability of the agricultural sector, as it is in other Mediterranean regions. Intensive agriculture can overuse and exhaust natural resources, including soil and water. The current study evaluated how conservation strategies, including no tillage and semi-tillage (as a variation of strip tillage), affected grapevine growth and grape quality when compared to conventional tillage application. Two cultivars were used: Chardonnay and Maratheftiko (indigenous). Soil pH decreased, and EC increased after tillage applications, in both vineyards. Tillage lowered soil… More >

Francisco Daniel García^1,2, Solange Nicole Aigner^1,2, Natalia Raffaeli³, Antonio José Barotto³, Eleana Spavento³, Mariano Martín Escobar^1,4, Marcela Angela Mansilla^1,4, Alejandro Bacigalupe^1,4,*

Journal of Renewable Materials, Vol.14, No.1, 2026, DOI:10.32604/jrm.2025.02025-0181 - 23 January 2026

Abstract This study explores the use of black soldier fly larvae protein as a bio-based adhesive to produce particleboards from sugarcane bagasse. A comprehensive evaluation was conducted, including rheological characterization of the adhesive and physical–mechanical testing of the panels according to European standards. The black soldier fly larvae-based adhesive exhibited gel-like viscoelastic behavior, rapid partial structural recovery after shear, and favorable application properties. Particleboards manufactured with this adhesive and sugarcane bagasse achieved promising mechanical performance, with modulus of rupture and modulus of elasticity values of 30.2 and 3500 MPa, respectively. Internal bond strength exceeded 0.4 MPa,… More > Graphic Abstract

Fei Tang^1,*, Ping Wang¹, Jiang Yu¹, Huihui Zhu¹, Mengxue Qin¹, Ling Yang²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073423 - 12 January 2026

Abstract Attribute-Based Encryption (ABE) has emerged as a fundamental access control mechanism in data sharing, enabling data owners to define flexible access policies. A critical aspect of ABE is key revocation, which plays a pivotal role in maintaining security. However, existing key revocation mechanisms face two major challenges: (1) High overhead due to ciphertext and key updates, primarily stemming from the reliance on revocation lists during attribute revocation, which increases computation and communication costs. (2) Limited universality, as many attribute revocation mechanisms are tailored to specific ABE constructions, restricting their broader applicability. To address these challenges,… More >

Misbah Anwer^1,*, Ghufran Ahmed¹, Maha Abdelhaq², Raed Alsaqour³, Shahid Hussain⁴, Adnan Akhunzada^5,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.068673 - 10 November 2025

Abstract The exponential growth of the Internet of Things (IoT) has introduced significant security challenges, with zero-day attacks emerging as one of the most critical and challenging threats. Traditional Machine Learning (ML) and Deep Learning (DL) techniques have demonstrated promising early detection capabilities. However, their effectiveness is limited when handling the vast volumes of IoT-generated data due to scalability constraints, high computational costs, and the costly time-intensive process of data labeling. To address these challenges, this study proposes a Federated Learning (FL) framework that leverages collaborative and hybrid supervised learning to enhance cyber threat detection in… More >

Yungui Guo^*, Xuan Fan

Journal of Psychology in Africa, Vol.35, No.6, pp. 791-796, 2025, DOI:10.32604/jpa.2025.067238 - 30 December 2025

Abstract This study examined the moderating role of employees’ learning orientation on the relationship between leaders’ artificial intelligence symbolization behavior (LAISB), employees’ attitude towards digital transformation (ATDT), and enterprise digital transformation. The sample consisted of 261 employees from five enterprises in China (female = 34.5%; primary industry includes the internet and transportation; mean age = 42.51 years, SD = 8.63 years; bachelor’s degree or above = 72.8%). The results of structural equation modeling and simple slope test indicated that LAISB predicted higher enterprise digital transformation, with ATDT partial mediation. Furthermore, employees’ learning orientation weakened the relationship More >

Md Sabir Hossain¹, Md Mahfuzur Rahman^1,2,*, Mufti Mahmud^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 1087-1116, 2025, DOI:10.32604/cmes.2025.068779 - 30 October 2025

Abstract This article presents a human fall detection system that addresses two critical challenges: privacy preservation and detection accuracy. We propose a comprehensive framework that integrates state-of-the-art machine learning models, multimodal data fusion, federated learning (FL), and Karush-Kuhn-Tucker (KKT)-based resource optimization. The system fuses data from wearable sensors and cameras using Gramian Angular Field (GAF) encoding to capture rich spatial-temporal features. To protect sensitive data, we adopt a privacy-preserving FL setup, where model training occurs locally on client devices without transferring raw data. A custom convolutional neural network (CNN) is designed to extract robust features from More > Graphic Abstract

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 >

Hanyong Lee^#, Ye-Chan Park^#, Jaesung Lee^*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4977-4993, 2025, DOI:10.32604/cmc.2025.068156 - 23 October 2025

Abstract Restoring texts corrupted by visually perturbed homoglyph characters presents significant challenges to conventional Natural Language Processing (NLP) systems, primarily due to ambiguities arising from characters that appear visually similar yet differ semantically. Traditional text restoration methods struggle with these homoglyph perturbations due to limitations such as a lack of contextual understanding and difficulty in handling cases where one character maps to multiple candidates. To address these issues, we propose an Optical Character Recognition (OCR)-assisted masked Bidirectional Encoder Representations from Transformers (BERT) model specifically designed for homoglyph-perturbed text restoration. Our method integrates OCR preprocessing with a… More >

Ayman Noor^1,2, Hanan Almukhalfi^1,2, Arthur Souza^2,3, Talal H. Noor^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3085-3111, 2025, DOI:10.32604/cmes.2025.068393 - 30 September 2025

Abstract People with visual impairments face substantial navigation difficulties in residential and unfamiliar indoor spaces. Neither canes nor verbal navigation systems possess adequate features to deliver real-time spatial awareness to users. This research work represents a feasibility study for the wearable IoT-based indoor object detection assistant system architecture that employs a real-time indoor object detection approach to help visually impaired users recognize indoor objects. The system architecture includes four main layers: Wearable Internet of Things (IoT), Network, Cloud, and Indoor Object Detection Layers. The wearable hardware prototype is assembled using a Raspberry Pi 4, while the… 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 >