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Abstract Given the increasing global concerns about aggressive behaviors and the pressing need for effective psychological interventions, this study delves into the potential of a concept deeply rooted in positive and Buddhist psychology but largely researched in Western contexts, as a mitigating factor against aggression in Chinese adults. Through three core studies involving 652 participants (age: 30.52±8.16), our research illuminated the intricate relationship between self-compassion, perceived stress, and aggression. Study 1 identified a negative correlation among these variables, setting the empirical foundation. In Study 2, participants exposed to a self-compassion exercise reported enhanced self-compassion and reduced aggression. Study 3 further consolidated these findings, with participants in the self-compassion writing group, showing notable increases in self-compassion and decreases in aggression compared to a control group. Critically, perceived stress emerged as a significant mediator between self-compassion and aggression, elucidating its central role in this dynamic. Together, our findings underscore the promise of self-compassion as a strategy to curb aggression tendencies, especially in light of its influential relationship with perceived stress, suggesting vital implications for future mental health interventions.

Abstract As the capacity of medium or large hydroelectric generators increases, conventional grounding methods face challenges in effectively limiting single‐phase to earth fault current and neutral displacement voltage within acceptable range. Excessive fault current and neutral displacement voltage pose threats to the stability and safety of power generation and transmission systems. Inherent design deficiencies in conventional grounding methods lead to failures in meeting fault current and voltage requirements. To address this, this paper proposes a novel grounding method utilizing high impedance to restrict excessive fault current and neutral displacement voltage. The method minimizes both fault current and neutral displacement voltage by optimally selecting device parameters through minimal iterative trials. Additionally, a novel indicator is introduced to evaluate the effectiveness of grounding method by monitoring changes in neutral displacement voltage. The method is tested through theoretical calculation and field experiments, successfully implemented in large‐size hydroelectric generator.

Abstract Leveraging the synergy between causal knowledge graphs and a large language model (LLM), our study introduces a groundbreaking approach for computational hypothesis generation in psychology. We analyzed 43,312 psychology articles using a LLM to extract causal relation pairs. This analysis produced a specialized causal graph for psychology. Applying link prediction algorithms, we generated 130 potential psychological hypotheses focusing on “well-being”, then compared them against research ideas conceived by doctoral scholars and those produced solely by the LLM. Interestingly, our combined approach of a LLM and causal graphs mirrored the expert-level insights in terms of novelty, clearly surpassing the LLM-only hypotheses (t(59) = 3.34, p = 0.007 and t(59) = 4.32, p

Many previous studies in moral psychology have described people as moral believers, who treat morality as universal sacred beliefs and show moral outrage and social exclusion toward people with different opinions. At the same time, moral relativism tends to make people more tolerant but also makes them question their own beliefs and leads to more immoral behavior. We propose moral pragmatism as an alternative, which treats morality as a tool for solving specific problems, thus making morality situational instead of universal, practical instead of sacred, and tolerant instead of exclusive. Through four empirical studies, we demonstrate that when moral issues are presented as practical problems rather than abstract beliefs, people consider morality to be less universal, treat dissidents with more tolerance and less outrage, and do not perform more immoral behavior at the same time. These findings highlight moral pragmatism as a flexible and culturally sensitive moral approach, promoting diverse moral perspectives and constructive cross-cultural discourses.

Abstract Background Inhibition of Serum Amyloid A-like 1 (SAAL1) expression could inhibit cancer progression and improve the prognosis of cancer patients. At present, the correlation between SAAL1 and lung adenocarcinoma (LAC) remains unclear. Therefore, this study surveyed the worth and pathway of SAAL1 in LAC progression and immunity. Methods Bioinformatics and immunohistochemistry were used to identify the SAAL1 expression in LAC. The roles of SAAL1 expression in the existence values of LAC patients were explored, and the nomograms were constructed. Clinical values of SAAL1 co-expressed genes were evaluated by COX regression, survival, and Receiver operating characteristic (ROC) analysis. EDU and western blotting methods were used to inquiry the functions and pathways of the SAAL1 in cell growths. The correlation between the SAAL1 level and immune microenvironment was visualized using correlation research. Results SAAL1 level was elevated in LAC tissues, and was observed in cancer tissues of dead patients. SAAL1 overexpression had something to do with shorter overall survival, progression-free interval, and disease-specific survival in LAC. The area under the curve of SAAL1 was 0.902 in normal tissues and cancer tissues. Inhibition of SAAL1 expression could inhibit cancer cell proliferation, which may be related to the decreased expression of cyclin D1 and Bcl-2 proteins. In LAC, SAAL1 level had something to do with stromal, immune, and estimate scores, and correlated with macrophages, T cells, Th2 cells, CD8 T cells, NK CD56dim cells, DC, eosinophils, NK CD56bright cells, pDC, iDC, cytotoxic cells, Tgd, aDC cells, B cells, Tcm, and TFH levels. SAAL1 overexpression had something to do with existence values and the immunity in LAC. Conclusions Inhibition of SAAL1 expression could regulate cancer growth via cyclin D1 and Bcl-2. SAAL1 is a promising prognostic biomarker in LAC patients.

Immunotherapy can improve the survival of patients with advanced lung squamous cell carcinoma (LUSC). T cytotoxic cells are one of the main members of the immune microenvironment. Herein, we aimed to identify the roles of T-cell cytotoxic markers interleukin 18 (IL18) receptor 1 (IL18R1) in the LUSC progression using bioinformatics, clinical tissue specimen, and cell experiment. We assessed the association between the IL18R1 expression and immune infiltration and IL18R1-related competing RNA network. The IL18R1 expression was downregulated in the LUSC tissues. The IL18R1 expression downregulation was associated with diagnosis and short overall survival and disease-specific survival, and it was also an independent risk factor for dismal survival time in LUSC. IL18R1-related nomograms predicted the survival time of patients with LUSC. IL18R1 overexpression inhibited the proliferation, migration, and invasion of LUSC cells. The IL18R1 expression was significantly associated with the microenvironment (stromal, immune, and estimate scores), immune cells (such as the T cells, cytotoxic cells, CD8 T cells), and immune cell markers (such as the CD8A, PD-1, and CTLA4) in LUSC. AC091563.1 and RBPMS-AS1 downregulation was positively associated with the IL18R1 expression, negatively associated with the miR-128-3p expression, and associated with short disease-specific survival and progression in LUSC. In conclusion, IL18R1 was significantly downregulated and associated with the prognosis and immune microenvironment. IL18R1 overexpression inhibits the growth and migration of cancer cells in LUSC. Furthermore, AC091563.1 and RBPMS-AS1 might compete with IL18R1 to bind miR-128-3p for participating in LUSC progression. These results showed that IL18R1 is a biomarker for evaluating the prognosis of patients with LUSC.

The roles and mechanisms of T-cell receptor (TCR)-associated transmembrane adaptor 1 (TRAT1) in lung adenocarcinoma (LAC) have not yet been reported in the relevant literature. Therefore, this study aimed to understand the roles and mechanisms of TRAT1 in LAC using bioinformatics and in vitro experiments. TRAT1 expression levels in LAC samples were analysed using various databases. TRAT1 co-expressed genes were acquired by the correlation analysis of LAC tissues. The functional mechanisms and protein network of TRAT1 co-expressed genes were analysed using bioinformatics analysis. The expression of TRAT1 was activated in LAC cells, and the roles of TRAT1 overexpression in the growth and migration of cancer cells was investigated using flow cytometry, Cell Counting Kit-8 (CCK-8), and migration and invasion assays. The relationship between TRAT1 overexpression, the immune microenvironment, and RNA modification was evaluated using correlation analysis. TRAT1 expression levels were significantly abnormal at multiple mutation sites and were related to the prognosis of LAC. TRAT1 co-expressed genes were involved in cell proliferation, adhesion, and differentiation, and TRAT1 overexpression significantly inhibited cell viability, migration, and invasion and promoted apoptosis of A549 and H1299 cells, which might be related to the TCR, B cell receptor (BCR), MAPK, and other pathways. TRAT1 expression levels were significantly correlated with the ESTIMATE, immune, and stromal scores in the LAC microenvironment. Additionally, TRAT1 expression levels were significantly correlated with the populations of B cells, CD8 T cells, cytotoxic cells, and other immune cells. TRAT1 overexpression was significantly correlated with the expression of immune cell markers (such as PDCD1, CD2, CD3E) and genes involved in RNA modification (such as ALKBH1, ALKBH3, ALKBH5). In conclusions, TRAT1 overexpression inhibited the growth and migration of LAC cells, thereby delaying cancer progression, and was correlated with the LAC microenvironment and RNA modifications.

The global population is inevitably aging due to increased life expectancy and declining birth rates, leading to an amplified demand for innovative social and healthcare services. One promising avenue is the introduction of companion robots. These robots are designed to provide physical assistance as well as emotional support and companionship, necessitating effective human–robot interaction (HRI). This study explores the role of cognitive empathy within HRI, focusing on the influence of robot facial animacy and emotional expressions on perspective-taking abilities—a key aspect of cognitive empathy—across different age groups. To this end, a director task involving 60 participants (30 young and 30 older adults) with varying degrees of robot facial animacy (0%, 50%, 100%) and emotional expressions (happy, neutral) was conducted. The results revealed that older adults displayed enhanced perspective-taking with higher animacy faces. Interestingly, while happiness on high-animacy faces improved perspective-taking, the same expression on low-animacy faces reduced it. These findings highlight the importance of considering facial animacy and emotional expressions in designing companion robots for older adults to optimize user engagement and acceptance. The study’s implications are pertinent to the design and development of socially effective service robots, particularly for the aging population.

The tumor microenvironment (TME) plays an important regulatory role in the progression of non-small cell lung cancer (NSCLC). Mesenchymal stem cells (MSCs) in the TME might contribute to the occurrence and development of cancer. This study evaluates the role of differentially expressed genes (DEGs) of MSCs and the development of NSCLC and develops a prognostic risk model to assess the therapeutic responses. The DEGs in MSCs from lung tissues and from normal tissues were analyzed using GEO2R. The functions and mechanisms of the DEGs were analyzed using the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Additionally, the Cancer Genome Atlas (TCGA) database was used to determine the expression levels of the DEGs of MSCs in the NSCLC tissues. The prognostic factors of NSCLC related to MSCs were screened by survival analysis, meta-analysis, Cox regression analysis, and a prognostic risk model and nomogram was developed. The signaling mechanisms and immune roles that risk model participate in NSCLC development were determined via Gene Set Enrichment Analysis and CIBERSORT analysis. Compared to the normal tissues, 161 DEGs were identified in the MSCs of the lung tissues. These DEGs were associated with mechanisms, such as DNA replication, nuclear division, and homologous recombination. The overexpression of DDIT4, IL6, ITGA11, MME, MSX2, POSTN, and TRPA1 were associated with dismal prognosis of NSCLC patients. A high-risk score based on the prognostic risk model indicated the dismal prognosis of NSCLC patients. The nomogram showed that the age, clinical stage, and risk score affected the prognosis of NSCLC patients. Further, the high-risk model was associated with signaling mechanisms, such as the ECM-receptor interaction pathways, cytokine-cytokine receptor interaction, and MAPK pathways, involved in the progression of NSCLC and was also related to the components of the immune system, such as macrophages M0, T follicular helper cells, regulatory T cells. Therefore, the risk model and nomogram that was constructed on the basis of MSC-related factors such as POSTN, TRPA1, and DDIT4 could facilitate the discovery of target molecules that participate in the progression of NSCLC, which might also serve as new candidate markers for evaluating the prognosis of NSCLC patients.

Emerging research revealed that the view-type of photos is not only related to the field of data sciences, such as the sentiment brought forth by sightseeing spots, but also in the field of social sciences about human emotions and behaviors. These potential usages of view-types trigger a challenging problem, that is to automatically distinguish them into wide or narrow. In this paper, we present a computational model to classify them inspired by the human visual system. We found two cues that can represent the visual attention, i.e., focus cue and scale cue. The focus cue is modeled in the frequency domain using the non-sampled contourlet transform (NSCT) and speeded up robust features (SURF). The scale cue is modeled by defining the spatial size and conceptual sizes of an object in the image, whereby AdobeBING and convolutional neural network are used for the respective measurements. By integrating these focus and scale models, a robust scheme is hence proposed for this non-trivial task. The experiments on a newly established dataset, which has 5050 natural images, show better performance by our proposal when compared to the state-of-the-arts.

This paper presents a fast discrete Curvelet transform (FDCT)-based technique for multi-focus image fusion to address two problems: texture selection in FDCT domain and block effect in spatial-based fusion. First, we present a frequency-based model by performing FDCT on the input images. Considering the human visual system characteristics, a union of pulse coupled neural network and sum-modified-Laplacian algorithms are proposed to extract the detailed information of frequencies. Then, we construct a hybrid spatial-based model. Unlike other spatial-based methods, we combine the image difference and the detailed information extracted from input images to detect the focused region. Finally, to evaluate the robustness of proposed method, we design a completed evaluation process considering the misregistration, noise error, and conditional focus situations. Experimental results indicate that the proposed method improves the fusion performance and has less computational complexity compared with various exiting frequency-based and spatial-based fusion methods.

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs.

In this study the LCx assay (a nucleic acid amplification assay) for Chlamydia trachomatis in endocervical samples was compared with the Gen-Probe PACE2 assay (a nucleic acid probe assay) for endocervical samples, and with endocervical culture. In addition, the efficacy of the LCx assay was determined for midstream clean-catch urine samples because it is often necessary to obtain such a sample for routine urine culture and it is simpler to collect only a single sample without also collecting a first-void urine for LCx. Endocervical specimens from 205 patients were tested for C. trachomatis via LCx and PACE2. Of these patients, 203 were tested by culture. Midstream cleancatch urine samples from 75 of these patients were tested by LCx. The sensitivities and specificities for these assays, after discrepant analysis, were 100 and 98.9% for LCx of endocervical samples, 52.4 and 100% for PACE2; and 71.4 and 100% for culture. The sensitivity/specificity of LCx for midstream clean-catch urines was 66.7/98.5%. The apparent prevalence of C. trachomatis in our population was 10.2%. These data indicate that among the methods tested, LCx of endocervical samples had the highest sensitivity for C. trachomatis in this population. The senstivity of the urine LCx assay using midstream clean-catch collected urines was considerably less than that reported in other studies that used first-void urines but was higher than that of PACE2. Infect. Dis. Obstet. Gynecol. 8:112–115, 2000.

In this paper, the foamed polylactic acid (PLA) composites with different ratios of titanium dioxide (TiO2) and lignin (Lg) are prepared. Molecular dynamics simulation analysis indicates that the fillers enhance the mechanical properties of the composites. The optimal foaming temperatures for PLA/Lg and PLA/TiO2 composites are found to be 110 and 100°C, respectively. The supercritical carbon dioxide foaming process is applied to get the foamed composites, and their mechanical and thermal properties are analyzed. The results show that the addition of TiO2 improves the melting point and compression properties of the PLA composites. Furthermore, the inclusion of Lg increases the molecular chain mobility, foaming multiplicity, and compression strength of the composite materials. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) interactions with multiscale objects widely exist in practice and high-order accuracy of solutions for the problem is very desirable for accurate analysis. The combined field integral equation (CFIE) is used to describe the problem in the integral equation approach since it can remove the internal resonance problem. The Nyström method is a robust solver for EM integral equations, but its high-order scheme is less extensively studied. This work aims at the multiscale EM problems and develops a high-order Nyström method (HONM) to solve the governing CFIE. The accurate evaluation of hypersingular and near-hypersingular integrals is a key in the HONM and new formulations are developed for multiscale structures based on Green's theorem. Numerical examples for EM scattering by multiscale conducting objects are provided to illustrate the approach and good results are acquired. [ABSTRACT FROM AUTHOR]