Siti Rahayu Nadhiroh^1,*, Ira Nurmala², Iqbal Pramukti³, Kamolthip Ruckwongpatr⁴, Laila Wahyuning Tyas², Afina Puspita Zari², Warda Eka Islamiah¹, Yan-Li Siaw⁵, Marc N. Potenza^{6,7,8,9,10,11}, Chung-Ying Lin^{12,13,14,15,*}

International Journal of Mental Health Promotion, DOI:10.32604/ijmhp.2025.072115

Abstract Objectives: Problematic use of the internet (PUI) has been increasingly associated with various mental health issues, highlighting the need for accurate assessment tools. The Assessment of Criteria for Specific Internet-use Disorder (ACSID-11) is a validated psychometric instrument designed to measure distinct forms of PUI across multiple online activities. However, its applicability and validity have not yet been established within the Indonesian context. Therefore, this study aimed to translate and validate the ACSID-11 for use among Indonesian populations. Methods: The translation procedure of the ACSID-11 involved forward translation, back translation, and expert panel discussions. This research involved… More >

Ramazan İnci^1,*, Davut Açar², Osman Tayyar Çelik³, Yunus Tunç⁴

International Journal of Mental Health Promotion, DOI:10.32604/ijmhp.2025.072072

Abstract Background: Bullying during adolescence is shaped by numerous psychosocial factors such as family dynamics, attachment, and peer relationships. This study aims to examine parental acceptance-rejection, attachment styles, and social exclusion factors as key psychosocial variables predicting bullying behavior in adolescents. Methods: In a cross-sectional study conducted with 349 high school students in Hakkari, Türkiye. Data were collected using the Olweus Bullying Scale, the Parental Acceptance-Rejection Scale, the Social Exclusion Scale, and the Three-Dimensional Attachment Styles Scale. Independent samples t-tests, one-way ANOVAs, Pearson correlations, and hierarchical regression analyses were performed. Results: Research findings reveal that peer bullying varies… More >

Zhengqiang Peng^1,*, Rendong Feng¹, Fang Han¹, Jing Guo¹, Shen Chi¹, Wenao Huang¹, Jie Luo²

FDMP-Fluid Dynamics & Materials Processing, DOI:10.32604/fdmp.2025.073281

Abstract Jet pumps often suffer from efficiency losses due to the intense mixing of power and suction fluids, which leads to significant kinetic energy dissipation. Enhancing the efficiency of such pumps requires careful optimization of their structural parameters. In this study, a computational fluid dynamics (CFD) model of a hydraulic jet sand-flushing pump is developed to investigate the effects of throat-to-nozzle distance, area ratio, and throat length on the pump’s sand-carrying performance. An orthogonal experimental design is employed to optimize the structural parameters, while the influence of sand characteristics on pumping performance is systematically evaluated. Complementary… More >

Xian Shi^1,2,*, Botao Zhang^1,2, Weidong Zhang^1,2, Zenghua Ma³, Bo Zhang³, Ahmad Ramezanzadeh⁴, Bin Li⁵, Jian Mao⁵

Energy Engineering, DOI:10.32604/ee.2025.073586

Abstract To investigate the mechanism governing the continuous decline in fracture conductivity of unconsolidated sandstone reservoirs post-hydraulic fracturing, this study centers on the synergistic effects of two key mechanisms—particle migration and proppant embedment. Through the integration of laboratory experiments and computational fluid dynamics-discrete element method (CFD-DEM) coupled numerical simulations, this study systematically examines the influence patterns of varying closure pressures, particle concentrations, fluid properties, and proppant parameters on fracture conductivity. The experimental results demonstrate that particle migration induces pore blockage within the proppant packing layer. When the fines mass concentration reaches 10%, fracture conductivity is almost… More >

Taotao Zhu, Pai Pang, Yang Wang^*

Energy Engineering, DOI:10.32604/ee.2025.073516

Abstract Frequent extreme weather events and the increasing popularity of renewable energy have exacerbated the frequency spatiotemporal imbalance in the new power system. To address these issues, this paper proposes a collaborative optimization strategy for virtual inertia spatiotemporal distribution replenishment, aiming to enhance nodal frequency stability through targeted virtual inertia allocation. This strategy integrates the nodal inertia characteristics with frequency response dynamics to establish a spatiotemporal quantitative model for evaluating the equivalent inertia distribution across nodes, thereby overcoming the limitations of conventional global inertia assessments. Furthermore, by implementing differentiated virtual inertia supplementation from renewable energy power More >

K. Naga Venkata Siva¹, Damodhar Reddy², P. Krishna Murthy³, Kiran Kumar Pulamolu⁴, M. Dharani⁵, T. Venkatakrishnamoorthy^6,*

Energy Engineering, DOI:10.32604/ee.2025.072982

Abstract Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components, particularly at elevated voltage levels. Addressing these shortcomings, this work presents a robust 15-level Packed U Cell (PUC) inverter topology designed for renewable energy and grid-connected applications. The proposed system integrates a sensor less proportional-resonant (PR) controller with an advanced carrier-based pulse width modulation scheme. This approach efficiently balances capacitor voltage, minimizes steady-state error, and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation. Additionally, More >

Jian Wang¹, Gongqiang Yang^1,*, Yufeng Sun², Gangui Yan¹, Jie Long³

Energy Engineering, DOI:10.32604/ee.2025.072828

Abstract Given that the power grid partitioning method relying mainly on line reactive power flow information sees frequent changes in partitioning results with reactive power flow fluctuations under high-proportion fixed-power-factor PV-connected distribution networks, and traditional distributed PV collaborative optimization fails to adapt due to such changes, a stable partitioning and distributed PV collaborative optimization method for this scenario is proposed. Firstly, the Gaussian mixture model (GMM) is used to characterize the characteristics of PV reactive power output, obtaining the typical curve of PV reactive power output. Secondly, the Monte Carlo Simulation (MCS) probabilistic power flow calculation… More >

Mohammed Benamara^1,2, Boumediene Touati³, Said Bennaceur⁴, Bendjillali Ridha Ilyas^5,*

Energy Engineering, DOI:10.32604/ee.2025.072641

Abstract This study explores the thin-layer convective solar drying of Marrubium vulgare L. leaves under conditions typical of sun-rich semi-arid climates. Drying experiments were conducted at three inlet-air temperatures (40°C, 50°C, 60°C) and two air velocities (1.5 and 2.5 m·s⁻¹) using an indirect solar dryer with auxiliary temperature control. Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient (r), root-mean-square error (RMSE), and Akaike information criterion (AIC). A complementary heat-transfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance, and an… More > Graphic Abstract

Guo-Feng Fan^1,2, Jia-Jing Qian¹, Li-Ling Peng¹, Xin-Hang Jia¹, Ling-Han Zuo¹, Jia-Can Yan¹, Jiang-Yan Chen¹, Anantkumar J. Umbarkar³, Wei-Chiang Hong^4,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.073615

Abstract Accurate prediction of perovskite photovoltaic materials’ optoelectronic properties is crucial for developing efficient and stable materials, advancing solar technology. To address poor interpretability, high computational complexity, and inaccurate predictions in relevant machine learning models, this paper proposes a novel methodology. The technical route of this paper mainly centers on the random forest-knowledge distillation-bidirectional gated recurrent unit with attention technology (namely RF-KD-BIGRUA), which is applied in perovskite photovoltaic materials. Primarily, it combines random forest to quantitatively assess feature importance, selecting variables with significant impacts on photoelectric conversion efficiency. Subsequently, statistical techniques analyze the weight distribution of More >

Ahmad Zia¹, Nazia Azim², Bekarystankyzy Akbayan³, Khalid J. Alzahrani⁴, Ateeq Ur Rehman^5,*, Faheem Ullah Khan⁶, Nouf Al-Kahtani⁷, Hend Khalid Alkahtani^8,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.073818

Abstract The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous computing networks. Finding an optimal computational resource for task offloading and then executing efficiently is a critical issue to achieve a trade-off between energy consumption and transmission delay. In this network, the task processed at fog nodes reduces transmission delay. Still, it increases energy consumption, while routing tasks to the cloud server saves energy at the cost of higher communication delay. Moreover, the… More >