Hyunyup Lee^1,*, Sungrok Kang¹, Yoonyoung Choi¹, Eric S. Cerino²

International Journal of Mental Health Promotion, Vol.28, No.7, 2026, DOI:10.32604/ijmhp.2026.080017 - 30 July 2026

Abstract Background: Despite growing concerns about the mental health of professional military personnel, little is known about protective factors for mental health among military officers and non-commissioned officers (NCOs). The present study aimed to examine the differential and interaction effects of extrinsic and intrinsic protective factors on depression and mental well-being among Korean professional military personnel. Methods: A total of 500 Korean officers and NCOs completed a self-administered questionnaire that assessed extrinsic factors (salary satisfaction, work environment satisfaction), intrinsic factors (occupational calling, positive appraisals of military service), and the two mental health outcomes. Results: Hierarchical regression revealed that… More >

Chang Xu^*

International Journal of Mental Health Promotion, Vol.28, No.7, 2026, DOI:10.32604/ijmhp.2026.078865 - 30 July 2026

Abstract Objectives: Postmenopausal women experience hormonal and psychosocial changes that can affect emotion regulation. Although exercise may enhance cognitive control during emotion regulation, evidence on prefrontal activation in this population is limited. This study examined whether acute moderate-intensity aerobic exercise influences emotion regulation and prefrontal activation in postmenopausal women. Methods: Postmenopausal women (≥12 months since last menstruation) were randomised to a moderate-intensity aerobic exercise condition or a time-matched sedentary control condition (n = 102). Analyses included participants with usable behavioural and fNIRS data (exercise n = 32; control n = 35). The exercise group completed 30 min of cycling… More >

Abuzar Khan¹, Abid Iqbal^2,*, Ghassan Husnain^1,*, Fahad Masood¹, Mohammed Al-Naeem³, Sajid Iqbal⁴

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077222 - 09 April 2026

Abstract Cloud computing now supports large-scale maritime analytics, yet offloading rich Automatic Identification System (AIS) data to the cloud exposes sensitive operational patterns and complicates compliance with cross-border privacy regulations. This work addresses the gap between growing demand for AI-driven vessel intelligence and the limited availability of practical, privacy-preserving cloud solutions. We introduce a privacy-by-design edge-cloud framework in which ports and vessels serve as federated clients, training vessel-type classifiers on local AIS trajectories while transmitting only clipped, Gaussian-perturbed updates to a zero-trust cloud coordinator employing secure and robust aggregation. Using a public AIS corpus with realistic… More >

Raquel Hidalgo-Sanz, María-Ángeles Del-Castillo-Alonso, Laura Monforte, Rafael Tomás-Las-Heras, Encarnación Núñez-Olivera, Javier Martínez-Abaigar^*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3453-3470, 2025, DOI:10.32604/phyton.2025.070087 - 01 December 2025

Abstract Grapevine (Vitis vinifera L.) is one of the main crops worldwide, and ultraviolet-B (UV-B, 280–315 nm) radiation is emerging as a promising technical tool to enhance secondary metabolites that can contribute to the quality and health-promoting properties of both grapes and the resulting wines. However, few studies have assessed the effectiveness of UV-B supplements under field conditions. Here, we compared the effects of two different field UV-B treatments (a single supplement applied at pre-harvest, and a double supplement applied at both veraison and pre-harvest) on the phenolic composition of Tempranillo grape skins and the resulting wines.… More >

Xiao Li^*, Junxiang Liu, Weinan Fan, Shiying Xu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.012284

Abstract Flooding is one of the most common types of natural hazards leading to wide-spread disturbances and damages to human communities and natural environment across the world. Flood forecasting is an effective means to provide timely hazard information to relevant government decision-makers and practitioners as well as those residents at risk, which plays an important role in flood risk reduction. A complete flood forecasting system normally includes at least two components, that is precipitation predictions and a hydrological or hydraulic model for flooding processes simulation. However, the current flood forecasting especially for urban floods face obvious… More >

Uzair Abbas¹, Zahid Maqbool¹, Muhammad Adnan Shahid^1,2,*, Muhammad Safdar^1,2, Saif Ullah Khan^1,3

Revue Internationale de Géomatique, Vol.34, pp. 655-668, 2025, DOI:10.32604/rig.2025.064279 - 11 August 2025

Abstract This study was conducted to devise an integrated methodology for retrieval of surface soil moisture (SSM) using Landsat 8 TIRS data. For this purpose, Landsat 8 images of 15 May 2021 (pre-monsoon) and 20 November 2021 (post-monsoon) were processed for retrieval of soil moisture index (SMI) based on land surface temperature (LST). Moreover, field-based SM in the laboratory was also determined and correlated with satellite-based SMI. A moderate correlation between field-based SM and satellite-based SMI with R² = 0.60 was obtained. Based on this relationship, SSM maps of Tehsil Faisalabad Saddar for the pre-and post-monsoon seasons… More >

Josef Walek^*, Petr Lichý

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3135-3153, 2025, DOI:10.32604/cmes.2025.059889 - 03 March 2025

Abstract Plastometric experiments, supplemented with numerical simulations using the finite element method (FEM), can be advantageously used to characterize the deformation behavior of metallic materials. The accuracy of such simulations predicting deformation behaviors of materials is, however, primarily affected by the applied rheology law. The presented study focuses on the characterization of the deformation behavior of AISI 1045 type carbon steel, widely used e.g., in automotive and power engineering, under extreme conditions (i.e., high temperatures, strain rates). The study consists of two main parts: experimentally analyzing the flow stress development of the steel under different thermomechanical… More >

Léonor Fasse^1,2,*, François Blot²

Psycho-Oncologie, Vol.18, No.4, pp. 367-375, 2024, DOI:10.32604/po.2024.049544 - 04 December 2024

Abstract Arrière-plan: L’information sur la possibilité de rédiger des Directives Anticipées (DA) est une nécessité et représente un enjeu majeur sur les plans médical, éthique, légal. Les difficultés sont nombreuses, organisationnelles ou culturelles, et c’est aussi vrai dans l’univers de la cancérologie, où les DA (et plus largement les discussions anticipées) revêtent une importance cruciale. Sujet éminemment sensible, l’abord des DA (donc d’une réflexion sur la fin de vie) nécessite un travail d’acculturation à la fois sociétale et médico-soignante. Une démarche institutionnelle a donc été élaborée, dans l’objectif d’un déploiement d’outils d’information, de formation des professionnels,… More >

Jian-Hong Ye^1,2, Yuting Cui^3,*, Li Wang⁴, Jhen-Ni Ye⁵

International Journal of Mental Health Promotion, Vol.26, No.10, pp. 805-815, 2024, DOI:10.32604/ijmhp.2024.055814 - 31 October 2024

Abstract Background: With the global popularity of short videos, particularly among young people, short video addiction has become a worrying phenomenon that poses significant risks to individual health and adaptability. Self-regulated learning (SRL) strategies are key factors in predicting learning outcomes. This study, based on the SRL theory, uses short video addiction as the independent variable, SRL strategies as the mediating variable, and learning well-being as the outcome variable, aiming to reveal the relationships among short video addiction, self-regulated learning, and learning well-being among Chinese college students. Methods: Using a cross-sectional study design and applying the… More >

Umar Zaman¹, Junaid Khan², Eunkyu Lee^1,3, Sajjad Hussain⁴, Awatef Salim Balobaid⁵, Rua Yahya Aburasain⁵, Kyungsup Kim^1,2,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1789-1808, 2024, DOI:10.32604/cmc.2024.056222 - 15 October 2024

Abstract Maritime transportation, a cornerstone of global trade, faces increasing safety challenges due to growing sea traffic volumes. This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System (AIS) data and advanced deep learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Bidirectional LSTM (DBLSTM), Simple Recurrent Neural Network (SimpleRNN), and Kalman Filtering. The research implemented rigorous AIS data preprocessing, encompassing record deduplication, noise elimination, stationary simplification, and removal of insignificant trajectories. Models were trained using key navigational parameters: latitude, longitude, speed, and heading. Spatiotemporal aware processing through trajectory segmentation… More >