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This study aimed to investigate the effects of social reinforcement on Iranian EFL learners’ motivation (i.e., autonomy, competence, and relatedness) within online language learning environments. Adopting an explanatory sequential mixed-methods design, the research involved 100 intermediate-level Iranian EFL learners aged 24–39. Participants were randomly assigned to either an experimental group, which received targeted social reinforcement during online activities, or a control group, which engaged in the same activities without specific reinforcement. Quantitative data, gathered via pre- and post-intervention administrations of a validated motivation scale, were analyzed using independent samples t-tests. These analyses revealed statistically significant improvements in scores for autonomy, competence, and relatedness among learners in the experimental group compared to their counterparts in the control group. Complementary qualitative findings, derived from content analysis of semi-structured interviews, further indicated that participants who received social reinforcement perceived it as positively influencing their autonomy, competence, and relatedness. These convergent results underscore the considerable potential of strategically implemented social reinforcement to foster enhanced learner motivation in online EFL contexts, offering valuable insights for pedagogical practice and the design of more supportive virtual learning spaces.

Purpose Risk perception is an essential factor affecting how individuals evaluate risk, make decisions and behave. The impact of risk perception on customer purchase behavior has been widely studied; however, the association has been debated. Therefore, the purpose of this paper is to examine the relationship between risk perception and customer purchase behavior and to examine factors that could moderate it. Design/methodology/approach This study conducted a meta-analysis of this relationship and examined factors that could moderate it. Six databases were comprehensively searched. Two reviewers independently selected the studies for inclusion, extracted data and assessed quality. Pearson's r was used as the effect estimate. A total of 33 studies were included in the meta-analysis. Findings The results revealed a negative relationship between risk perception and customer purchase behavior. The geographical region, purchase channel and country development level affected the relationship. The correlation between perceived risk and purchase behavior in European consumers was the highest, followed by the correlation in American consumers; the weakest correlation was found in Asian consumers. For consumers in developed countries, perceived risk had a stronger negative influence on customer purchase behavior than that for consumers in developing countries. The perceived risk of online purchase channels had a stronger negative impact on customer purchase behavior than that of offline purchase channels. Research limitations/implications Risk perception is a useful context in which to explain barriers to customer purchase behavior. In addition, reducing consumers’ risk perception and perfecting the market transaction process with respect to buying behavior should be further studied. Originality/value The findings of this review indicate a direct negative relationship between risk perception and customer purchase behavior. To the best of the authors’ knowledge, this review is the first to meta-analytically summarize the impact of risk perception on customer purchase behavior in social sciences research, and it also illuminates new perspectives for future studies.

Background Long noncoding RNAs (lncRNAs) have recently emerged as important regulators in governing fundamental biological processes, and many of which are likely to have functional roles in tumorigenesis. Maternally expressed gene 3 (MEG3) gene encodes a lncRNA whose expression is lost in an expanding list of primary human tumors and tumor cell lines, however its biological role and regulatory mechanism in gastric cancer (GC) development and progression are poorly defined. Methods Quantitative RT-PCR analysis was used to determine whether aberrant MEG3 expression was associated with GC patients pTNM stage and pM state. Furthermore, the effect of ectopic expression of MEG3 on cell proliferation, migration, invasion and cell apoptosis was assessed by using CCK-8, wound healing, transwell invasion assays and flow cytometric analysis, respectively, in GC cell lines HGC-27 and MGC-803. Moreover, the competing endogenous RNA (ceRNA) activity of MEG3 on miR-181a was investigated via luciferase reporter assay and immunoblot analysis. Results MEG3 is decreased in GC patients and cell lines, and its expression was associated with metastatic GC. Furthermore, ectopic expression of MEG3 in HGC-27 and MGC-803 cells inhibited cell proliferation, migration, invasion, and promoted cell apoptosis, which might be due to MEG3 sequestering oncogenic miR-181 s in GC cells. Furthermore, MEG3 could up-regulated Bcl-2 via its competing endogenous RNA (ceRNA) activity on miR-181a. Conclusions These findings suggest that lncRNA MEG3, a ceRNA of miR-181 s, could regulate gastric carcinogenesis and may serve as a potential target for antineoplastic therapies.

Coix lacryma-jobi L. is a very important economic crop widely cultivated in Southeast Asia. Drought affects more than four million square kilometers every year, and is a significant factor limiting agricultural productivity. However, relatively little is known about how Coix lacryma-jobi L. responds to drought treatments. To obtain a detailed and comprehensive understanding of the mechanisms regulating the transcriptional responses of Coix lacryma-jobi L. to drought treatment, we employed high throughput short-read sequencing of cDNA prepared from polyadenylated RNA to explore global gene expression after a seven-day drought treatment. We generated a de novo assembled transcriptome comprising 65,480 unique sequences. Differential expression analysis based on RSEM-estimated transcript abundances identified 5,315 differentially expressed genes (DEGs) when comparing samples from plants following drought-treatment and from the appropriate controls. Among these, the transcripts for 3,460 genes were increased in abundance, whereas 1,855 were decreased. Real-time quantitative PCR for 5 transcripts confirmed the changes identified by RNA-Seq. The results provide a transcriptional overview of the changes in Coix lacryma-jobi L. in response to drought, and will be very useful for studying the function of associated genes and selection of molecular marker of Coix lacryma-jobi L in the future.

According to the production process requirements of oriented silicon steel in a certain steel mill, optimization of the slag composition ratio is studied through thermodynamic calculations. The CaO-SiO2-Al2O3-FeO-MgO slag system is studied using FactSage thermodynamic software (FactSage 8.1), and a slag optimization plan is proposed based on industrial experiments involving changes in the composition ratio of the slag, calculation and analysis of the melting characteristics of RH refining slag, further verification through orthogonal experiments, and observations of the slag state, temperature, and composition relationship through phase diagrams. This study provides theoretical guidance for finding a suitable slag composition ratio based on the influence of slag on dissolved aluminum in steel liquid. Research has shown that, combined with thermodynamic analysis, slag melting characteristics, component content calculations, and industrial experiments, the range of RH refining slag composition suitable for production in this steel mill is slag in the range of 1.3~1.5 alkalinity, 25~30% Al2O3, 5~6% MgO, and 1–2% FeO.

In civil engineering, the joints of structures are complex, and their damage is generally hard to be detected. Due to the insensitivity of structural modal information to local joint damage, this paper presents a method based on additional virtual mass for damage identification of a semi-rigid joint in a frame structure. Firstly, the modeling of a semi-rigid is described. Secondly, the frequency response of the virtual structure is constructed, and the natural frequency of the constructed virtual structure is extracted by the ERA method. By adding multiple values of virtual masses at different positions, the natural frequency information sensitive to joint damage for damage identification is effectively increased. Based on the above theory, qualitative identification of joint damage is proposed to detect the potential damage, and identification of both damage location and its extent is presented, using natural frequency. Improved Orthogonal Matching Pursuit (IOMP) algorithm is employed to improve the accuracy of the natural frequency-based method for damage identification. At last, numerical simulation of a three-story frame is performed to discuss and to verify the effectiveness of the proposed method.

Structural damage identification plays an important role in providing effective evidence for the health monitoring of bridges in service. Due to the limitations of measurement points and lack of valid structural response data, the accurate identification of structural damage, especially for large-scale structures, remains difficult. Based on additional virtual mass, this paper presents a damage identification method for bridges using a vehicle bump as the excitation. First, general equations of virtual modifications, including virtual mass, stiffness, and damping, are derived. A theoretical method for damage identification, which is based on additional virtual mass, is formulated. The vehicle bump is analyzed, and the bump-induced excitation is estimated via a detailed analysis in four periods: separation, free-fall, contact, and coupled vibrations. The precise estimation of bump-induced excitation is then applied to a bridge. This allows the additional virtual mass method to be used, which requires knowledge of the excitations and acceleration responses in order to construct the frequency responses of a virtual structure with an additional virtual mass. Via this method, a virtual mass with substantially more weight than a typical vehicle is added to the bridge, which provides a sufficient amount of modal information for accurate damage identification while avoiding the bridge overloading problem. A numerical example of a two-span continuous beam is used to verify the proposed method, where the damage can be identified even with 15% Gaussian random noise pollution using a 1-degree of freedom (DOF) car model and 4-DOF model.

Fruit color is a crucial trait for bell pepper. To investigate the mechanism of color formation, three bell pepper lines with different color (yellow, orange and red) were used as materials to conduct comprehensive targeted metabolomic and transcriptomic analyses. During the process of fruit development, 54 carotenoids metabolites were discovered, exhibiting unique accumulation patterns and notable variety specificity. The types and content of carotenoids in orange fruit (OM) were notably greater compared to the other two varieties. Red pigment (capsanthin and capsorubin) was specifically enriched in red fruit (RM), and yellow pigment (lutein and zeaxanthin) is the highest in yellow fruit (YM) and OM. Five modules positively correlated with carotenoid accumulation and one negative module was determined by weighted gene co-expression network analysis (WGCNA). Additionally, transcription factors (TFs) and hub genes related to carotenoid synthesis were predicted. By elucidating the regulation of 7 key carotenoid metabolites by 14 critical genes and 5 key TFs, we constructed a comprehensive carotenoid biosynthesis metabolic network that comprehensively explains the pigment changes observed in green and mature pepper fruit. Overall, the results not only provide important insights into carotenoid synthesis pathway, but also lay a solid base for revealing the mechanism of bell pepper color transformation.

Objective To investigate associations between inflammatory markers and malnutrition-inflammation-atherosclerosis (MIA) syndrome in dialysis patients and evaluate their predictive value for cardiovascular events. Methods This retrospective cohort study enrolled 197 maintenance dialysis patients (2017–2022). Inflammatory markers (CRP, IL-6, TNF-α), nutritional parameters, and atherosclerosis indicators were collected at baseline, 6, 12, and 24 months. Multivariate regression and Cox models assessed associations with MIA syndrome and cardiovascular outcomes. Results Elevated inflammatory markers were significantly associated with MIA syndrome severity and cardiovascular events ( P  < 0.001). High-inflammation patients had higher MIA scores (8.7 ± 2.1 vs. 6.4 ± 1.9, P  < 0.001). CRP correlated negatively with albumin ( r =-0.41) and positively with carotid intima-media thickness ( r  = 0.36, both P  < 0.001). Hemodialysis patients showed higher CRP levels (8.2 ± 4.4 vs. 6.1 ± 3.7 mg/L, P  = 0.011) and cardiovascular event rates (46.3% vs. 29.2%, P  = 0.027) than peritoneal dialysis patients. Inflammatory changes correlated with MIA progression ( r  = 0.37, P  < 0.001). After adjustment, CRP (HR = 1.17, 95% CI: 1.08–1.26), IL-6 (HR = 1.12, 95% CI: 1.04–1.20), and TNF-α (HR = 1.14, 95% CI: 1.05–1.23) independently predicted cardiovascular events. Conclusion Inflammatory markers independently associate with MIA syndrome and cardiovascular events in dialysis patients. Hemodialysis patients demonstrate greater inflammatory burden than peritoneal dialysis patients, with inflammation potentially mediating this difference. Findings support inflammatory monitoring for risk stratification and targeted interventions.

Dendrobium shixingense Z. L. Chen, S. J. Zeng & J. Duan, a National Class II Protected wild plant species in China, is renowned for its rich polysaccharide content and remarkable medicinal value. Delineating priority conservation areas for this species is critically important for its sustainable conservation and management. In this study, the MaxEnt model was applied to predict its potential distribution patterns under multiple climate scenarios, while the Marxan and InVEST models were utilized to identify priority conservation zones. Results demonstrate that the primary distribution of D. shixingense is concentrated in southeastern China, particularly within Guangdong, Fujian, Guangxi, and Jiangxi provinces, with a total suitable habitat area of 79.41 × 10 4 km 2 . Future projections indicate an expansion of suitable habitats, with key environmental drivers identified as precipitation of the coldest quarter (Bio19), mean diurnal temperature range (Bio2), among others. Priority conservation areas are predominantly located in Shixing County and Ruyuan Yao Autonomous County of Shaoguan City; Xing’an County of Guilin City and other specified regions. These findings indicate that climate change will substantially impact the distribution of D. shixingense , potentially altering both the extent and quality of suitable habitats. priority conservation areas are concentrated in ecologically stable regions, necessitating enhanced protection efforts in these zones. Collectively, this research provides a robust scientific foundation for formulating effective conservation strategies and advancing the sustainable development of D. shixingense .