Xixi Chu¹, Run Guo¹, Yujin Wang^2,*, Zhong Li³

Journal of Psychology in Africa, Vol.36, No.2, pp. 153-159, 2026, DOI:10.32604/jpa.2026.072738 - 29 April 2026

Abstract Bootleg innovation serves as a vital supplement to routine innovation, yet strengths-based leadership mechanisms driving such informal behavior remain underexplored. This study examined the mediation mechanism of growth need strength, as well as the boundary condition set by work centrality, in the association between strengths-based leadership and bootleg innovation. We employed a time-lagged design across two waves to gather data from 375 employees within the technology sector (Wave 1, n = 583; Wave 2, n = 425). The final sample consisted of 47.5% males, with 67.7% aged between 30 and 40. Hierarchical regression results found More >

Mataanana Mulavu^1,*, Dana Seale², J. Paul Seale³, Sion K. Harris⁴, Tulani Francis L. Matenga¹, Mwitwa Mugode¹, Shimeo Sakanya¹, Jonathan M. Tirrell⁵, Phillip Chimponda⁶, Wilbroad Mutale⁷, Mutale Sampa⁸, Oliver Mweemba¹

Journal of Psychology in Africa, Vol.36, No.2, pp. 219-230, 2026, DOI:10.32604/jpa.2026.071580 - 29 April 2026

Abstract Unhealthy substance use is high among adolescents and young people in Zambia. Conceivably, a character strength approach could help reduce alcohol and other psychoactive substance use among young adults. We tested the efficacy of a positive psychology based group-based character strengths prevention and recovery program for alcohol risk reduction among Zambian young adults. The primary study participants included schoolchildren and community members. We conducted 8 focus group discussions (FGDs) with school students (aged 13 to 17) and community youth (ages 18–24), 12 FGDs with parents, teachers, family, friends, and group leaders. Moreover, we conducted 8… More >

Ros Syazmini Mohd Ghani^1,2,3,*, Mohamad Saiful Sulaiman^1,2,3, Sofiyah Mohd Razali^2,4, Madihan Yusof², Ellisha Iling^1,2,3

Journal of Renewable Materials, Vol.14, No.4, 2026, DOI:10.32604/jrm.2025.02025-0174 - 24 April 2026

Abstract The increasing demand for sustainable construction materials has driven research into non-wood biomass for engineered composites. This study reports the preliminary fabrication and evaluation of cross-laminated panels (CLPs) made from Nipah palm (Nypa fruticans) petioles bonded with a bio-epoxy resin adhesive. Panels were manufactured at three target densities (400, 600, and 800 kg/m³) and evaluated for their physical, mechanical, and microstructural properties. Physical tests included moisture content, water absorption, and thickness swelling, while mechanical tests measured compressive and flexural strength in accordance with JIS A 5908:2022 and ASTM D1037 standards. The results showed that higher panel density More > Graphic Abstract

Wei Kang^1,*, Juan Jin²

Chalcogenide Letters, Vol.23, No.3, 2026, DOI:10.32604/cl.2026.077859 - 03 April 2026

Abstract A sulfate–chloride electrolyte was used to deposit alloy layers on AISI 1018 coupons while co-introducing ZnS nanoparticles (5–20 g/L) to tune microstructure and durability under combined saline exposure and dry sliding. Cross-sectional SEM confirmed continuous deposits of ~24–26 μm, and XRD indicated γ-phase dominance with pronounced grain refinement: crystallite size decreased from 42 ± 3 nm (particle-free) to 28 ± 2 nm at 15 g/L. In 3.5 wt% NaCl, polarization data showed a progressive ennoblement of E_corr from −1.032 to −0.981 V (vs. SCE) together with a reduction of i_corr from 8.47 to 1.82 μA/cm² at 15… More >

Supriyanto^1,*, Chatarina Niken¹, Suripto Dwi Yuwono², Mohd Isneini¹, Suyadi Kartorono¹

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2026.073449 - 31 March 2026

Abstract This study investigates the impact of Type D additive, Plastiment 83 AM, on the compressive strength and microstructure of Portland Composite Cement (PCC) concrete with a target compressive strength of 18.7 MPa, utilizing a mixing, stirring, and treatment model that simulates batching plant conditions. The study investigated additive dosages of 0%, 0.15%, 0.25%, 0.35%, and 0.40%, with stirring durations of 15 min, 2, 4, 6, and 6.5 h. Compressive strength tests were conducted at the ages of 7, 14, 28, 56, and 90 days on cylindrical specimens, and at 24 h for setting time tests.… More >

Ehsan Momeni¹, Mohammad Dehghannezhad¹, Fereydoon Omidinasab¹, Danial Jahed Armaghani^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.077300 - 30 March 2026

Abstract In the last decade, the importance of sustainable construction and artificial intelligence (AI) in civil engineering has been underlined in many studies. Numerous studies highlighted the superiority of AI techniques over simple and mathematical regression analyses, which suffer from relatively poor generalization and an inability to capture highly non-linear relationships among inputs and output(s) parameters. In this study, to evaluate the compressive strength of concrete with glass powder (GP) and recycled aggregates, 600 concrete samples were tested in the laboratory, and their results were evaluated. For intelligent assessment of concrete compressive strength (CCS), the study… More >

Chae-Young Lee¹, Yun-Jung Choi^2,*

International Journal of Mental Health Promotion, Vol.28, No.3, 2026, DOI:10.32604/ijmhp.2026.077116 - 31 March 2026

Abstract Background: Adolescent suicide remains a pressing public health concern in South Korea and worldwide, ranking as one of the leading causes of death among youth. Identifying modifiable risk and protective factors is critical for prevention strategies. Physical activity has been suggested as one such factor due to its potential mental health benefits. This study aimed to examine whether associations between physical activity and suicidality differ by activity type and by stage of suicidal behavior, distinguishing suicidal ideation, planning, and attempts among Korean adolescents. Methods: This cross-sectional secondary analysis used data from the 20th Korea Youth Risk… More >

Ahmed Mohammed Awad Mohammed^1,*, Omayma Husain², Mosab Hamdan³, Abdalmomen Mohammed⁴, Abdullah Ansari^5,6,7, Atef Badr¹, Abubakar Elsafi⁸, Abubakr Siddig⁹

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.2, 2026, DOI:10.32604/cmes.2026.075720 - 26 February 2026

Abstract Unconfined Compressive Strength (UCS) is a key parameter for the assessment of the stability and performance of stabilized soils, yet traditional laboratory testing is both time and resource intensive. In this study, an interpretable machine learning approach to UCS prediction is presented, pairing five models (Random Forest (RF), Gradient Boosting (GB), Extreme Gradient Boosting (XGB), CatBoost, and K-Nearest Neighbors (KNN)) with SHapley Additive exPlanations (SHAP) for enhanced interpretability and to guide feature removal. A complete dataset of 12 geotechnical and chemical parameters, i.e., Atterberg limits, compaction properties, stabilizer chemistry, dosage, curing time, was used to… More >

Tianxia Zou^1,*, Yilin Sun², Fuhao Fan¹, Zhen Zheng¹, Yanjin Xu², Baoshuai Han²

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074121 - 10 February 2026

Abstract Ultra-high-strength aluminum alloy profile is an ideal choice for aerospace structural materials due to its excellent specific strength and corrosion resistance. However, issues such as uneven metal flow, stress concentration, and forming defects are prone to occur during their extrusion. This study focuses on an Al-Zn-Mg-Cu ultra-high-strength aluminum alloy profile with a double-U, multi-cavity thin-walled structure. Firstly, hot compression experiments were conducted at temperatures of 350°C, 400°C, and 450°C, with strain rates of 0.01 and 1.0 s⁻¹, to investigate the plastic deformation behavior of the material. Subsequently, a 3D coupled thermo-mechanical extrusion simulation model was established… More >

Sicheng Ma¹, Lixiang Zhang^2,*, Guocai Chen³, Zeyu Dai³, Junru Zhu⁴, Wei Fang^1,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073572 - 10 February 2026

Abstract Community detection is a fundamental problem in network analysis for identifying densely connected node clusters, with successful applications in diverse fields like social networks, recommendation systems, biology, and cyberattack detection. Overlapping community detection refers to the case of a node belonging to multiple communities simultaneously, which is a much more meaningful and challenging task. Graph representation learning with Evolutionary Computation has been studied well in overlapping community detection to deal with complex network structures and characteristics. However, most of them focus on searching the entire solution space, which can be inefficient and lead to inadequate… More >