Aims Community College

BackgroundSelf-management is essential for coping with depressive symptoms, yet little is known about its associations with depressive symptoms and personal recovery.MethodsWe conducted a cross-sectional questionnaire survey of 183 outpatients with major depressive disorder in Japan between October 2024 and June 2025. Participants reported the use and perceived usefulness of 63 self-management strategies. Associations between the number of strategies and symptom severity and recovery were examined using Spearman’s rank correlation coefficients with the Japanese versions of the Quick Inventory of Depressive Symptomatology (QIDS-J) and the Questionnaire about the Process of Recovery (QPR-J).ResultsOf the 183 respondents (mean age 43.6 ± 12.4 years; 54.1% female), the mean QIDS-J score was 9.55 ± 5.25 and 60.7% were in remission. Fourteen of the 63 strategies were used by at least half of the participants. The most frequently used strategies were “ensure enough rest to avoid exhaustion through overexertion” (88.0%), “engage in leisure activities (e.g. reading, watching TV, cooking, traveling, and driving)” (78.9%), and “eat a healthy diet” (65.0%). The strategies rated most useful included “discuss information about depression with a therapist” (86.7%), “meet with friends with whom I can be myself” (83.5%), and “avoid or minimize contact with people who tend to make me stressed or depressed” (83.3%). Participants reported using an average of 20.8 ± 13.5 strategies, of which 13.1 ± 9.16 were rated as useful. The number of strategies rated as useful was weakly negatively correlated with the QIDS-J scores (Spearman’s ρ = −0.207, p = 0.006) and moderately positively correlated with the QPR-J scores (Spearman’s ρ = 0.472, p < 0.001).ConclusionThe number of self-management strategies rated as useful showed a stronger correlation with personal recovery than with depressive symptom severity. The use of a greater number of self-management strategies may be associated with higher levels of personal recovery.

Background: Allergic rhinitis (AR) is a prevalent, but often an underdiagnosed, chronic condition in children, which may have a negative impact on quality of life (QoL) and academic performance. Objectives were to determine the prevalence of AR in Indian school children using the score for AR (SFAR), its impact on QoL using the mini-rhino conjunctivitis QoL questionnaire (Mini-RQLQ), and to assess its effect on studies. Methods: A descriptive cross-sectional study was conducted among 300 school children (6th-12th grades) in rural Bengaluru from June to August 2025 using parent-assisted SFAR, mini-RQLQ, and academic impact structured questionnaires. Statistical analyses were conducted in SPSS v25. Associations were tested using Chi-square and ANOVA, with p&lt;0.05 considered significant. Results: AR (SFAR≥7) was found in 55 children (18.3%) with prime triggers being cold weather (68%) and house dust (63%). Children with AR experienced sleeper disturbance, fatigue and ocular symptoms at higher rates. AR was significantly associated with impaired concentration (68.5%), reduced class participation (64.3%), and poorer examination performance (70%) compared to non-AR peers (p&lt;0.001 for all). Nearly 40% of affected kids had doctor visit. Conclusions: AR is common in school children of rural Bangalore and causes considerable impact to QoL and academic performance. Regular screening and timely intervention may help to reduce educational and psychosocial impacts.

Partial discharge (PD) activities are a major factor in insulation failure, accounting for over 60% of damage to high voltage transformers. Common causes of PD are manufacturing defects, environmental stress, and high-voltage surges. In this study, the effect of PD has been examined on minor and major insulation of a Power Transformer subjected to high voltage surges. The considered test voltages are high voltage operational surges like the Standard Lightning Impulse (SLI), Standard Switching Impulse (SSI), Oscillating Lightning Impulse (OLI), and modified SLI with tail chopped or additional overshoots. The OLI and modified SLI with superimposed oscillations or tail chopped are used to simulate the real-world like stresses on the transformer. To analyze the insulation conditions, the coherence function (CF) of the winding current is calculated at the neutral end of the transformer. CF is a statistical tool that measures the linear relationship between two signals in the frequency domain. The CF values are calculated for the simulated winding current obtained when partial discharges of varying magnitude are present versus when they are absent under different high frequency test voltages. From the results, it is found that when PD occurs across the main insulation, superimposed voltages consistently show the strongest correlation, while SLI with tailchopped voltages show minimum coherence with PD activity. The effect of varying the PD magnitude is negligible for minor insulation. This preliminary simulation study establishes a foundation for future experimental research to study the interaction of PD and test voltages on winding insulation, ultimately aiming to improve transformer performance, safety, and cost-effectiveness.

The rapid increase in deepfake technology is considered a serious challenge to both digital trust and media genuineness. While deep learning models have achieved high accuracy in detecting manipulated media, most operate as "black boxes," providing predictions without justification. This lack of transparency limits their reliability in critical applications like digital forensics and journalism. This paper introduces an Explainable Deepfake Detection System designed to bridge this gap. Our system utilizes a pretrained XceptionNet model for the robust classification of images and videos. We distinguish our methodology by introducing a novel dual modal explanation pipeline that synergizes visual heatmaps (Grad-CAM) with localized textual justifications (LIME), offering superior interpretability compared to prior unimodal approaches. The system is evaluated on standard benchmarks, including FaceForensics++, Deepfake Detection Challenge (DFDC), and Celeb-DF, achieving an accuracy of 92.35%, precision of 91.27%, recall of 90.88%, and an F1-score of 91.07%. Furthermore, we address critical security vulnerabilities by evaluating how well the model handles unseen deepfake generation techniques, adversarial attacks, low quality compression, and facial occlusions, ensuring its reliability in real-world forensic scenarios.

This editorial note presents the 2025 journal report of AIMS Materials Science, which was run by AIMS Press. It provides a brief summary of the journal's development in 2025 and outlines proposed directions and priorities for its continued growth in 2026.

This study investigates the experiential perception of buying behavior among Generation Z, focusing on gender differences using an independent t-test analysis. The primary objective is to understand the gendered perspectives of experiential marketing within Gen Z consumers. The research utilizes primary data collected from 654 respondents, comprising 467 males and 177 females, all belonging to Generation Z.T test is used for checking significance level.The findings reveal that customer satisfaction correlates more strongly with females than males across several experiential marketing dimensions, including smell, act, sense, feel, word-of-mouth (WOM), and willingness to purchase. These results suggest that female consumers in Gen Z may respond more positively to sensory and emotional elements of experiential marketing, which in turn influences their buying decisions more significantly compared to their male counterparts. Despite these insights, the study is limited by its cross-sectional design, which restricts the ability to draw conclusions over time. Therefore, the generalizability of the findings may be enhanced by future longitudinal studies that track experiential perception and buying behavior trends over extended periods. Additionally, the study opens avenues for further research from the marketers’ perspective, exploring how experiential marketing strategies can be optimized to cater to the nuanced preferences of different gender groups within Gen Z. Such investigations could provide valuable insights for creating targeted, gender-sensitive marketing campaigns that effectively engage this influential consumer segment.