Correlations, means, and standard deviations for study variables.

<p>Correlations, means, and standard deviations for study variables.</p

Direct and indirect effects and 95% confidence intervals for the mediation model.

<p>Direct and indirect effects and 95% confidence intervals for the mediation model.</p

Experiential Avoidance Mediates the Association between Emotion Regulation Abilities and Loneliness

<div><p>Experiential avoidance (EA) involves the unwillingness to remain in contact with aversive experiences such as painful feelings, thoughts, and emotions. EA is often associated with the development and maintenance of emotional problems. Since loneliness is characterized by negative emotions such as sadness and pessimism, which is often linked to emotional problems, this study aims to test the mediating effects of EA on the relationship between emotion regulation abilities (ERA) and loneliness in a sample of Chinese adults. Five hundred undergraduates completed questionnaires measuring EA (Acceptance and Action Questionnaire; AAQ-Ⅱ), ERA (Failure-relate action orientation; Action Control Scale, ACS-90) and loneliness (UCLA Loneliness Scale). Structural equation modeling showed that EA fully-mediated the relationship between ERA and loneliness. The findings suggest EA is a key mechanism in explaining why people with high ERA are prone to feeling lower levels of loneliness. In particular, these findings have important implications for designing effective psychological interventions for loneliness.</p></div

Final structural model (n = 500, standardized path coefficients).

<p><i>Note</i>: <i>ERA</i> = emotion regulation abilities; <i>EA</i> = experiential avoidance; <i>L</i> = loneliness (<i>L1–L4</i> four parcels of loneliness). *<i>p</i><0.05; **<i>p</i><0.01.</p

Effect of heat flux on metal corrosion in non-boiling media: testing system, heat transfer simulations, and corrosion study on Al alloy

A dual-circulation testing system was constructed to study the effect of heat flux density (q, −22.28 ∼ +22.54 kW m‒2) on the corrosion of an Al–Cu–Mg–Mn alloy in 0.5 M H2SO4 at a constant metal surface temperature (50°C) under different controlling heat transfer states. Their heat transfer parameters were determined quantitatively by COMSOL simulation to keep them except q in constant, highlighting the influence of q on metal corrosion. Compared with the q = 0 condition, the positive heat flux (q > 0) improved the surface layer performance of the Al alloy to inhibit its anodic corrosion process, decreasing its corrosion current density (icorr) by 56% with increasing q to 22.54 kW m‒2. While q icorr by 52% at q = −22.28 kW m‒2. Heat flux also changed the corrosion reaction’s apparent effective activation energy (Ea) and pre-factor, and Ea played a dominating role in changing icorr.</p

Table_2_Predicting the risk of distant metastasis in patients with locally advanced rectal cancer using model based on pre-treatment T2WI-based radiomic features plus postoperative pathological stage.xlsx

ObjectiveTo assess the prognostic value of a model based on pre-treatment T2WI-based radiomic features and postoperative pathological staging in patients with locally advanced rectal cancer who have undergone neoadjuvant chemoradiotherapy.MethodsRadiomic features were derived from T2WI, and a radiomic signature (RS) was established and validated for the prediction of distant metastases (DM). Subsequently, we designed and validated a nomogram model that combined the radiomic signature and postoperative pathological staging for enhanced DM prediction. Performance measures such as the concordance index (C-index) and area under the curve (AUC) were computed to assess the predictive accuracy of the models.ResultsA total of 260 patients participated in this study, of whom 197 (75.8%) were male, and the mean age was 57.2 years with a standard deviation of 11.2 years. 15 radiomic features were selected to define the radiomic signature. Patients with a high-risk radiomic signature demonstrated significantly shorter distant metastasis-free survival (DMFS) in both the development and validation cohorts. A nomogram, incorporating the radiomic signature, pathological T stage, and N stage, achieved an area under the curve (AUC) value of 0.72 (95% CI, 0.60-0.83) in the development cohort and 0.83 (95% CI, 0.73-0.92) in the validation cohort.ConclusionA radiomic signature derived from T2WI-based radiomic features can effectively distinguish patients with varying risks of DM. Furthermore, a nomogram integrating the radiomic signature and postoperative pathological stage proves to be a robust predictor of DMFS.</p