This study investigated whether emotion regulation mediates, and marital self-efficacy moderates, the associations between attachment dimensions and loneliness. A quantitative descriptive–correlational design was used and the model was tested with structural equation modeling. The population comprised mothers of single, toddler-aged children in Tehran, Iran, in 1403 (2024/2025); sample size was determined using G*Power. Participants completed the DiTommaso et al. (2004) Loneliness Scale, the Collins and Read (1990) Adult Attachment Scale, the Lopez et al. (2007) Marital Self-Efficacy Scale, and the Gross and John (2003) Emotion Regulation Questionnaire. Path analyses showed a significant interaction between marital self-efficacy and secure attachment in predicting loneliness (p = .031), such that at above-mean self-efficacy, the secure attachment–loneliness association was more strongly negative. Significant indirect paths were observed for anxious/ambivalent attachment via marital self-efficacy to cognitive reappraisal (β = −.066, p < .01) and to expressive suppression (β = −.069, p < .01), and via marital self-efficacy to loneliness (β = .135, p < .01), indicating that higher anxious/ambivalent attachment was linked to lower self-efficacy, which in turn related to greater loneliness. Mediation by reappraisal and suppression in the attachment–loneliness relationship was not supported; however, suppression had a significant direct effect on loneliness. Overall, marital self-efficacy and attachment styles play key roles in explaining loneliness, and suppression may function as an interpersonal risk factor. These findings inform counseling and prevention. Interventions that strengthen marital self-efficacy, reduce suppression, and enhance relational security are recommended.
The aim of the present study was to analyze the constitutive constructs of the career story of perfectionist gifted students by applying Savickas's career construction theory (2013) as both a theoretical and methodological framework. This research was conducted using a qualitative phenomenological method. The statistical population consisted of tenth-grade female students in gifted schools of Isfahan city in the academic year 2024–2025. Initially 100 students were selected through convenience sampling and completed Hill's Perfectionism Questionnaire (2004). Subsequently students with a score one standard deviation above the mean were purposively selected (10 participants), and the semi-structured "My Career Story" interview (Savickas, 2015), aligned with the five core components of career story through the lens of career construction theory (role models, interests, favorite stories, life mottos, and early memories), was conducted. Qualitative data were analyzed using the Colaizzi method. Findings from the analysis of the career stories revealed six main themes: Counseling and self-help needs (self-knowledge and independent learning; acceptance and psychological safety), Ideal ego (independence, perseverance, courage, intelligence, justice, moral responsibility, faith, and spirituality), Interests and motivational orientation (personal, academic and motivational learning; psychological and physical balance), Authorial self-reflection (independence, courage, justice-seeking, empathy, inner growth, innovation, success, and stability), Inner advisor and life mottos (progress, resilience, self-belief, spirituality, authenticity, and self-acceptance), and Meaning reconstruction of memories (early challenges, growth and agency strategies, positive relationships, and trust). In sum, conscious guidance of perfectionism through career construction interventions can strengthen identity development and promote more conscious career choices among gifted students.
This study aims to numerically assess fuel-air premixing in an industrial dry-low emission (DLE) combustor with a radial swirler. Compressible Reynolds-Averaged Navier-Stokes (RANS) simulations were performed under reacting condition, non-reacting condition, and three turbulence models were assessed. Among these, the k-omega SST model was selected as the final turbulence closure, as it provides more satisfactory predictions. To accurately evaluate heat transfer, the conjugate-heat-transfer (CHT) method was applied. The analysis focuses on the mainfuel wall-injection line, with varying (i) injection side (pressure vs. suction), (ii) hole count at fixed total area (2 vs. 3 per passage), and (iii) lateral hole position across the slot. Six configurations were obtained (as results). For clarification, "1/2/3" denotes the three lateral layouts and "a/b" denotes the pressure/suction-side injection. Mixing was quantified by the measurement of the unmixedness parameter. Compared to 1a, 1b improved mixing at the swirler slot exit by 26.7%, enabling deeper penetration (approximate to 70% of slot width) and producing lower unmixedness variation along the passage (47.5% vs. 77.2%). Increasing the hole count to 3 resulted in a 6% rise in jet velocity and a 12.4% increase in the jet-to-crossflow momentum-flux ratio. However, the prevailing influence of counter-rotating vortex-pair interactions led to reduced penetration depth compared with the two-hole configuration. Under reacting conditions, Case 1b exhibits the largest reductions in peak flow temperature (3.1%) and burner tip temperature (9.2%). For Case 3b, these are 1.3% and 5.1%. Overall, configuration 3b provides the most uniform temperature field, whereas 1b minimizes burner-tip and domain-peak temperatures.
Carbonic anhydrases (CAs) are zinc metalloenzymes responsible for the catalysis of the reversible hydration of carbon dioxide and play pivotal roles in many physiological and pathological processes. The complexity of CA isoforms with distinct expression patterns and catalytic characteristics has aroused fierce interest in the development of isoform-selective inhibitors and activators for therapeutic purposes and diagnostics. In this review, a systematic overview of computational and theoretical methods utilized to determine the structure, mechanism, inhibition, and activation of CAs was given. It reviews the evolution and utilization of computational methods in deciphering catalytic and proton transfer mechanisms as well as active-site interactions into atomic resolution and also features recent developments in drug design and screening strategies engineered for CA isoforms, particularly those involved in cancers and Alzheimer’s disease. This study can be a reference for multidisciplinary researchers and inspire the future rational design of CA modulators. This review summarizes the literature that employed QM and QM/MM by using like B3LYP, BE0-D3BJ, and MD simulations, GROMACS and Desmond packages, and various force fields: OPLS-AA, AMBER14, and CHARMM36. Molecular docking was performed using such as Glide, AutoDock Vina, and GOLD. Machine learning and AI techniques including SVM, LightGBM, SHAP, and neural networks were also reviewed. This review addresses the limitations in these models as well as prospects with newly emerging instruments such as polarizable force fields and real-time DFT as well as explainable AI frameworks, too. Incorporating data-driven insights with physics-based simulations, the next era of work is primed to provide predictive, scalable platforms for rational design of next-generation CA modulators.
Artificial lighting is extensively utilized in controlled-environment agriculture to optimize photosynthetic efficiency and enhance the production of specialized metabolites. This research analyzed the effects of different light-emitting diode (LED) spectra (white, UVA, blue, red, and red + blue) on in vitro-grown Damiana (Turnera diffusa) cultured on hormone-free MS solid medium, using a completely randomized design with three replicates per treatment over 30 days. Red + blue light treatment increased most agro-morphological parameters, wherein the highest values of fresh and dry weight, number of branches and leaves, and leaf length and width were obtained in this treatment. Red (4.40 ± 0.34 cm) and UVA lights (2.69 ± 0.35) led to the maximum and minimum values for stem length, respectively. LED lighting significantly influenced the synthesis of phenolic chemicals, including quercetin, chlorogenic acid, caffeic acid, ferulic acid, and catechin. Essential oil analysis revealed 28 constituents, predominantly sesquiterpenes (22.36
