Search

Mobility as a Service (MaaS) has become an emerging trend in transportation planning and management due to its potential to overcome the challenges of urban mobility toward the achievement of sustainable mobility goals. This requires people to be willing to use MaaS apps. However, given their relative novelty, there is still a lack of research on the factors that influence the use of these apps, as well as the possible role of gender in such use. In this context, this study aims to explore the complex relationships between a set of relevant factors and their influence on the intention to adopt MaaS apps, with special attention to the role of gender as a moderating variable. For this purpose, a survey was conducted in the Madrid Metropolitan Area (Spain), comprising 8358 respondents (3627 men and 4731 women), and a four-step methodological procedure was adopted: (i) Exploratory Factor Analysis (EFA), (ii) Confirmatory Factor Analysis (CFA), (iii) Structural Equation Model (SEM) on the total sample (iv) Gender-sensitive analysis, including a Multi-group analysis – SEM. The results demonstrate that technophilia, perceived usefulness and perceived ease of use are determining factors. Green values and attitudes toward shared modes have a notable total positive effect. However, contrary to expected, attitudes toward public transport, car and bicycle hardly explain the intention to adopt MaaS apps. Our analysis also reveals significant gender differences in the causal relationships hypothesized in the model. These findings allow us to outline the policy initiatives that could favor the use of MaaS apps, with a gender-sensitive approach. • Development and validation of a structural model on the intention to use MaaS apps. • Technophilia, perceived usefulness and perceived ease of use are crucial factors. • Green values and attitudes toward shared modes have a notable total positive effect. • Attitudes toward public transport, car and bicycle hardly explain MaaS apps usage. • Gender plays a moderating role in the structural model proposed. [ABSTRACT FROM AUTHOR]

While conflict pervades virtually every aspect of society, there have been relatively few crossovers between Regional Science and Peace Science. This paper pays tribute to Walter Isard, pioneer of peace science research, and Kieran Donaghy, who has contributed to research on arms race dynamics and macroeconomic stability. We review studies that examine the impact of (i) trade on conflict, (ii) the economy on militarized disputes, and (iii) conflict on economic development. The analysis develops a structural equation model (SEM) to test the hypotheses simultaneously using the Correlates of War project data. Consistent with the liberal proposition, we found that the pacifying effect of trade is robust across alternative SEM specifications. Controlling for standard explanatory variables, the SEM estimates reveal that the indirect impact of economic development on conflict mediated by trade is statistically significant at the 0.1-percent level. Trade is, therefore, a critical intervening variable that transforms conflict-inducing economic expansion into a pacifying influence on militarized disputes. The spatial version of the SEM confirms that democracies do not attack each other. While trade does not appear to have a local spillover effect on conflict, proximity to neighboring democracies does lead to fewer conflicts. The final hypothesis argues that conflict affects national economic performance, which Donaghy refuted in his 1995 Conflict Management and Peace Science paper. Consistent with Donaghy's finding, the estimates reject the claim that conflict disrupts economic stability. The conclusion section discusses the implications for Kieran Donaghy's larger body of work. [ABSTRACT FROM AUTHOR]

This study aimed to validate the influence of latent variables on human trust in autonomous vehicles and elucidate the underlying psychological framework. A survey with 114 queries, drawn from previous studies on trust factors, was conducted online, gamering 195 valid responses. Employing correlation and factor analysis, 51 queries were identified as significantly impacting trust levels. A structural equation model incorporating these 51 variables was constructed, revealing five higher-level psychological constructs: "Interpersonal," "System Feature," "Risk Perception," "Behavioral Intention," and "Trust," each comprising sub-factors derived from associated queries. Notably, the "Interpersonal" construct exhibited the greatest influence on "Behavioral Intention" and "Trust," while "Risk Perception" showed a negative correlation with trust, indicating higher perceived risk diminishes trust. The findings highlight the importance Ofunderstanding user interpersonal characteristics in enhancing trust in autonomous vehicles. Unlike previous studies focusing on individual variables, this research unveiled a comprehensive psychological structure by categorizing variables, factors, and constructs hierarchically. The developed model facilitates comprehension, prediction, and enhancement of user trust, guiding the development of tailored trust-fostering strategies and interventions for specific user groups and contexts. [ABSTRACT FROM AUTHOR]

\nHIGHLIGHTSExisting mental health studies usually disregard people’s neighborhood experiences in the past, which may have long-lasting mental health effects. This may particularly be true for migrants. To assess how the perceived pre- and post-migration neighborhood environment shapes migrants’ mental health later on in life, a quasi-longitudinal survey (N = 591) among migrants was conducted in Shenzhen, China. The risk of poor mental health was screened with the General Health Questionnaire (GHQ). Perceptions of the pre- and post-migration neighborhood environment were measured retrospectively and assessed with structural equation models. The results show that the direct pathways linking the perceived post-migration neighborhood physical (NPE) and social environment (NSE) to migrants’ mental health are significant. No direct association is found between the pre-migration neighborhood environments and mental health. The indirect path between the pre-migration NPE/NSE and mental health is significantly mediated by the post-migration NPE and NSE. Migrants’ SES development and their neighborhood attainment interplay overtime which have long-term impacts on their mental health. Our findings suggest that the pre-migration neighborhood plays a crucial role in migrants’ mental health. This confirms a path dependency of migrants’ neighborhood environment throughout their migrations. Future mental health studies are advised to incorporate neighborhood characteristics along migrants’ residential histories. Pre- and post-migration neighborhood environment play a role for migrants’ mental health.No direct pathways exist between pre-migration neighborhood physical or social environment and mental health.Pre-migration neighborhood physical and social environment are indirectly related to mental health.Migrants’ pre- and post-migration SES are directly and indirectly related to mental health.Inter-city and intra-city mobility are differently related to migrants’ mental health.Pre- and post-migration neighborhood environment play a role for migrants’ mental health.No direct pathways exist between pre-migration neighborhood physical or social environment and mental health.Pre-migration neighborhood physical and social environment are indirectly related to mental health.Migrants’ pre- and post-migration SES are directly and indirectly related to mental health.Inter-city and intra-city mobility are differently related to migrants’ mental health. [ABSTRACT FROM AUTHOR]

Background: Postoperative patients with primary hepatocellular carcinoma (HCC) confront not only physiological challenges but also psychological and social adaptation issues. It is imperative to enhance psycho-social adjustment (PSA) levels and further improve the quality of life among this population. However, research on PSA levels in postoperative HCC patients is lacking, and investigations into its associations with psychological resilience, social support, and fear of progression (FoP) remain unexplored currently. Objectives: This study aims to: (1) investigate the current status of PSA and analyze its influencing factors among postoperative HCC patients; (2) explore the interrelationships among psychological resilience, social support, FoP and PSA based on the Chronic Illness Adaptation Model employing a structural equation model. Methods: Convenience sampling methods were employed to recruit participants from the Department of Hepatobiliary Surgery at a tertiary hospital in Xi'an, Shaanxi, China, and a total of 399 patients completed the surveys. The survey instruments included a general information questionnaire, Connor-Davidson Resilience Scale (CD-RISC), Social Support Rating Scale (SSRS), Fear of Progression Questionnaire-Short Form (FoP-Q-SF), and Psychosocial Adjustment to Illness Scale Self-report (PAIS-SR). Data entry was conducted using Epidata 3.1 with dual verification, followed by statistical analyses performed using SPSS 27.0 and Amos 28.0. Results: The structural equation model revealed two paths. In Path 1 (psychological resilience → FoP → PSA), the direct effect was -0.383 (95% CI [-0.589, -0.112]), with an indirect effect of -0.075 (95% CI [-0.170, -0.018]). In Path 2 (social support → FoP → PSA), the direct effect was -0.297 (95% CI [-0.587, -0.063]), with an indirect effect of -0.069 (95% CI [-0.156, -0.019]). Conclusion: Postoperative patients with primary HCC exhibit lower levels of PSA. Higher levels of psychological resilience and social support correspond to elevated PSA levels. Conversely, advanced age, greater financial burden, and increased FoP are associated with lower PSA levels. FoP serves as a partial mediator between psychological resilience and PSA, as well as between social support and PSA. Future research would benefit from longitudinal designs to elucidate the developmental trajectories and causal links among these variables. [ABSTRACT FROM AUTHOR]

BACKGROUND: Studying the professional commitment of a student in an 8-year medical training program of China, especially its association with academic performance, can enhance the understanding of professional loyalty in future doctors. This study aimed to investigate the self-efficacy, academic performance, professional commitment, and learning engagement of 8-year program medical students, and explore the mediating roles of professional commitment and learning engagement on the associations between self-efficacy and academic performance. METHODS: We conducted a cross-sectional study in a Chinese medical university and collected the General Self-Efficacy Scale, Professional Commitment of Undergraduates Scales, and the Utrecht Work Engagement Scale-Student from self-reported students. Academic performance was ascertained using course examination scores in the most recent year. We conducted a structural equation model (SEM) analysis to examine the mediating roles of professional commitment and learning engagement on the relationship between self-efficacy and academic performance. RESULTS: A total number of 402 medical students were included in this study. Students in the clinical practice stage had significantly lower professional commitment and learning engagement than students in the pre-medical and medical course stages. The professional commitment of students from low-income families was significantly lower than that of students from high-income families. Professional commitment and learning engagement were mediators in the relationship between self-efficacy and academic performance. CONCLUSIONS: This study is the first to investigate professional commitment among students in the China 8-year medical program. Professional commitment plays an intermediary role between self-efficacy and academic performance. [ABSTRACT FROM AUTHOR]

Cyberspace has evolved into a hub for the dissemination of large amounts of tendentious information, posing significant challenges to the role of mainstream value information. As netizens' are the main recipients of tendentious information, their personal cognition, attitude, and behavioral ability affect their willingness to re-disseminate information, making them an inalienable force in the promotion of information dissemination. Exploring the dissemination mechanism of tendentious information in cyberspace can help to understand the law of information dissemination and predict the trend of information diffusion, which is of great significance to maintaining information security and social stability. However, the existing research has overlooked the potential influence of the attribute characteristics of information in terms of content, and has failed to overcome the methodological constraints of traditional statistical analysis to accurately describe the variables and mechanisms influencing the dissemination of tendentious information at the cognitive level. Therefore, using structural equation modeling, we propose a research index system based on the Theory of Planned Behavior and the characteristics of tendentious information. To this end, confirmatory factor and model fitting analyses were conducted to develop a tendentious information dissemination mechanism model, which we validated through testing and comparative experiments. Path analysis revealed that Attitude Toward Dissemination, Information Dissemination Intention, and Information Dissemination Behavior are the main links in the information dissemination process. Moreover, Information Sentiment Orientation was found to strongly promote the dissemination of tendentious information, while Subject Norm of Dissemination had a minor inhibiting effect. [ABSTRACT FROM AUTHOR]

Teachers’ integration of technology has been a critical focus for both teachers and researchers over the past three decades. This emphasis has intensified due to the COVID-19 pandemic, where technology integration has become a key factor in the success of classroom teaching and learning processes. Despite this attention, previous studies have shown limited exploration of the relationship between teachers’ technology integration and meaning in work as an internal variable. Therefore, using AMOS-structural equation modeling (SEM) analysis, this study aimed to develop a conceptual model examining the mediating role of meaning in work in the relationship between digital leadership, self-efficacy, and teachers’ technology integration. The study involved 200 junior high school teachers from Balikpapan City, East Kalimantan Province, a region in eastern Indonesia projected to become the new capital. A total of four variables were analyzed in this study: meaning in work, digital leadership, self-efficacy, and teachers’ technology integration (Z, X, and Y, respectively). The results showed that (1) digital leadership affected meaning in work and teachers’ technology integration, (2) self-efficacy affected meaning in work and teachers’ technology integration, (3) meaning in work affected teachers’ technology integration, and (4) meaning in work could mediate the relationship between digital leadership and self-efficacy in teachers’ technology integration. These findings contribute to a deeper understanding of the relationships among digital leadership, self-efficacy, and meaning in work, and their collective impact on teachers’ technology integration. Furthermore, the study highlights the significant role of meaning in work as a mediator in these relationships, providing a foundation for the development of digital leadership strategies and training programs aimed at improving technology integration in education. [ABSTRACT FROM AUTHOR]

Background: Cancer patients' health-related quality of life (HRQoL) has always been a hot discussion spot. Loneliness and psychological resilience are considered to be significant psychosocial factors impacting the HRQoL of the cancer population. However, there is a lack of studies on the interrelationship among loneliness, resilience, and HRQoL in patients with nasopharyngeal carcinoma (NPC). This study aims to explore the relationship between resilience and HRQoL among NPC patients and to recognize the potential mediating role of loneliness in this relationship. Methods: A cross-sectional study was performed in this study. A convenience sampling method was conducted to recruit participants. A total of 155 patients with nasopharyngeal carcinoma were required to complete the socio-demographic questionnaire, the Cancer Loneliness Scale (CLS), the 10-item Connor-Davidson Resilience Scale (CD-RISC-10), and the European Organization for Research and Treatment of Quality of Life Questionnaire C-30 (EORTC QLQ-C30) from April 2022 to August 2022 in a tertiary grade A hospital in Guangzhou, China. The multiple linear regression analysis was used to identify influencing factors, and structural equation modeling with the bootstrap method was performed to test the mediating role of loneliness. This study complied with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: HRQoL was at a median level among NPC patients, with a mean score of 64.19 (24.38) on the Global health status/quality of life (GHS/QoL) scale. Monthly household income (B = 4.973, P < 0.001), cancer stage (B=-4.342, P = 0.004), psychological resilience (B = 0.914, P < 0.001), and loneliness (B =-1.083, P < 0.001) were independent factors related to HRQoL, explaining 36.7% of the variance of HRQoL. Psychological resilience exerted its direct negative impact on loneliness (β = -0.199, BC95%CI = -0.318/-0.089), and it also had a both direct and indirect positive impact on HRQoL (β = 0.653, BC95%CI = 0.423/0.912; β = 0.142, BC95%CI = 0.046/0.296). Loneliness exerted a partially mediating impact on the relationship between psychological resilience and HRQoL. Conclusions: NPC patients with higher monthly household, early stages of cancer, higher resilience, and lower loneliness show a better HRQoL. Resilience has an indirect positive impact on HRQoL by influencing loneliness in NPC patients. It is suggested that healthcare staff should strive to enhancing resilience and reducing loneliness as new strategies to promote NPC patients' HRQoL further. [ABSTRACT FROM AUTHOR]

This study took a comprehensive approach to considering residents' demands and investigated the intentions of residents in Hebei Province to participate in LTCI, exploring the potential for individual participation. By integrating the unique Chinese context and existing literature, this study established a theoretical framework for research hypotheses concerning the influencing factors of residents' participation intentions. Leveraging a sample of 516 survey responses, we employed structural equation modeling (SEM) and hierarchical regression analysis (HRA) for validation. The research revealed that the heterogeneity of resident attributes has a significant influence on their participation intentions, and a gap exists between residents' attitudes and intentions, leading to a scenario where attitudes are high but intentions are low. Moreover, perceived usefulness, risk perception, and perceived trust were found to directly affect residents' intentions and could indirectly affect intentions through the mediating effect of attitudes. Additionally, the moderating role of policy support is instrumental in facilitating the translation of attitudes into actual intentions, bridging the gap between attitudes and participation intentions. These findings will assist researchers in gaining a deeper understanding of Chinese residents' participation intentions and their underlying influencing factors, ultimately providing a solid foundation for government policy formulation and insurance companies' strategic adjustments. [ABSTRACT FROM AUTHOR]

The relationship between tree radial growth and climate factors is intricate and affected by various factors related to global climate change. Chinese fir [Cunninghamia lanceolata (Lamb.) Hook.)] is a crucial fast-growing timber species in subtropical China. Its productivity, primarily determined by radial growth, has been influenced by climate change. Our study aimed to explore growth patterns and elucidate the correlation between radial growth and climate factors in Chinese fir plantations across four distinct climatic regions. Through correlation analysis and structural equation model (SEM), we explained the relationship between radial growth trends and climate factors. The results showed that monthly radial growth differed among the four production areas, with an "unimodal curve" in Fujian and Jiangxi, a "bimodal curve" in Hunan, and a "trimodal curve" in Yunnan. Radial growth was positively correlated with temperature and precipitation. The dryness index had a weak correlation with radial growth in Fujian and Jiangxi but a significant positive correlation in Hunan and Yunnan. SEM analyses indicated path coefficients for biological factors influencing radial growth (0.352 in Fujian, 0.616 in Jiangxi, 0.595 in Hunan, and 0.528 in Yunnan) and climate factors (-0.003 in Fujian, 0.150 in Jiangxi, 0.265 in Hunan, and 0.005 in Yunnan). The factors affecting radial growth were the least in Fujian and the most in Yunnan, indicating greater climate sensitivity in the radial growth of Chinese fir from coastal to inland areas. These results enhance our understanding of climate impacts on forest productivity and offer a scientific basis for sustainably managing subtropical plantations under climate change. [ABSTRACT FROM AUTHOR]

Mendelian randomization (MR) analysis is increasingly popular for testing the causal effect of exposures on disease outcomes using data from genome-wide association studies. In some settings, the underlying exposure, such as systematic inflammation, may not be directly observable, but measurements can be available on multiple biomarkers or other types of traits that are co-regulated by the exposure. We propose a method for MR analysis on latent exposures (MRLE), which tests the significance for, and the direction of, the effect of a latent exposure by leveraging information from multiple related traits. The method is developed by constructing a set of estimating functions based on the second-order moments of GWAS summary association statistics for the observable traits, under a structural equation model where genetic variants are assumed to have indirect effects through the latent exposure and potentially direct effects on the traits. Simulation studies show that MRLE has well-controlled type I error rates and enhanced power compared to single-trait MR tests under various types of pleiotropy. Applications of MRLE using genetic association statistics across five inflammatory biomarkers (CRP, IL-6, IL-8, TNF- α ⁠ , and MCP-1) provide evidence for potential causal effects of inflammation on increasing the risk of coronary artery disease, colorectal cancer, and rheumatoid arthritis, while standard MR analysis for individual biomarkers fails to detect consistent evidence for such effects. [ABSTRACT FROM AUTHOR]

Sea level rise induced flooding is projected to cause significant damage to the low-lying coastal areas of many countries around the planet. Many households located in vulnerable areas have already started to adapt to flooding, although some empirical studies indicate that informal adaptation is reaching its limit and that more formal countermeasures by governments will be necessary to cope with the increased flood risks. In such cases, public support for flood adaptation policy is crucial to ensure a successful and timely adaptation, as these strategies can directly affect coastal residents. However, there is limited understanding on the mechanisms and factors that determine public support for flood adaptation policy. Thus, this study proposes a new model – the Foundation of Adaptation Policy Support (FAPS) – which integrates the Protection Motivation Theory and the Risk Information Seeking and Processing models. FAPS was tested using structural equation modelling with latent variables and data that was collected from a household questionnaire survey conducted in the Tokyo lowland areas (n = 388), with the super levee representing a policy that could be applied to sea level rise adaptation. The proposed FAPS model showed a good fit with the collected data, indicating that the strongest predictors of policy support include the perceived effectiveness of the policy and the importance of the issue of flooding to individuals. Other important predictors of policy support include knowledge about flooding, the opinions of surrounding people (i.e. family and friends), and the systematic processing by respondents of information related to floods. The FAPS model sets the foundation for understanding the mechanisms of public support for adaptation policy and provides new insights into designing and planning such policies in practice. Key policy insights Perceived policy effectiveness and the importance of addressing floods are the strongest predictors of public support for adaptation policy. Increasing people's knowledge about flooding is essential to communicate the importance of adaptation policy. Investigating people's knowledge and the perceived importance of the issue of flooding prior to designing policies can predict public preferences for certain countermeasures. [ABSTRACT FROM AUTHOR]

While many effects of forest fragmentation are reasonably well understood, knowledge of interspecific interactions in fragmented ecosystems is much more limited, particularly for high diversity tropical forests. Using nearly 40 years of data from the Biological Dynamics of Forest Fragments Project in Central Amazonia, we assessed whether forest fragment area and time since isolation impact mutualistic interactions between frugivorous birds and their food resources. We used structural equation modeling to analyze the complex pathways between four main variables determining these interactions: fruiting tree abundance, frugivorous bird abundance, forest fragment area, and time since fragment isolation. Our results confirm that fragment area alters the abundance of some tree resources, with successional plant families increasing in abundance with decreasing fragment size. However, these changes do not drive alterations in the abundance of frugivorous birds. We also tested if bird species with a greater relative diet breadth are less vulnerable to forest fragmentation and found that specialist frugivores are more vulnerable to forest fragmentation immediately after isolation but are not differentially impacted within the long term. Collectively, our results demonstrate the need to further evaluate human‐driven habitat change across multiple timescales to fully understand its impacts on complex species interactions. [ABSTRACT FROM AUTHOR]

The increase in crop yield can be primarily attributed to the combined effect of genetic advancements, as well as increased contributions from nitrogen (N) and water. The accumulation of dry matter plays a crucial role in determining grain yield in winter wheat. The current study aimed to better understand the source‐sink dynamics, analyse the dry matter transport (DMT) before and after anthesis and calculate its ratio to grain yield. In this experiment, eight main cultivars of winter wheat that have been widely cultivated in Shaanxi Province since the 1940s were selected as planting material. Field examinations were conducted using three levels of both irrigation and N. The yield‐related parameters, dry matter accumulation, dry matter distribution, DMT and DMT efficiency were measured. The results showed that irrigation prolonged the time of dry matter accumulation, and the application of N fertiliser increased the rate of dry matter accumulation. The analysis of the dynamic characteristic parameters of dry matter in winter wheat showed that irrigation and N had a significant impact on rate of dry matter accumulation. The proportion of stems, leaves and spikes of new varieties increased significantly (p < 0.05), which increased by 56.67%–69.7%, 13.26%–18.07% and 15.78%–28.26%, respectively, with the varietal improvement. The DMT efficiency increased with varietal improvement and also with increased irrigation and N application. The response of irrigation treatment to DMT and dry matter was more significant. In addition, the irrigation treatment had a higher effect on the DMT efficiency of vegetative organs after anthesis. The logistic equation analysis revealed that water stress accelerated the fulfilment of maximum daily temperature (Tmax), while both the maximum growth rate (Gmax) and dry matter weight (Wmax) decreased as water stress increased. There was a positive linear relationship between dry matter accumulation after anthesis and grain yield. The structural equation model showed that varieties, N application and irrigation had significant positive effects on DMT, post‐anthesis dry matter and grain yield, while irrigation had significant negative effects on DMT efficiency. The accumulation of dry matter in winter wheat after anthesis showed a significant increase with the succession of varieties. The combination of moderate deficit irrigation and fertilisation improved transportation and dry matter accumulation after anthesis in winter wheat, thereby enhancing its production capacity. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. The rumen microbiome is crucial for converting feed into absorbable nutrients used for milk synthesis, and the efficiency of this process directly affects the profitability and sustainability of the dairy industry. Recent studies have found that the rumen microbial composition explains part of the variation in feed efficiency traits, including dry matter intake, milk energy, and residual feed intake. The main goal of this study was to reveal relationships between the host genome, the rumen microbiome, and dairy cow feed efficiency using structural equation models. Our specific objectives were to (1) infer the mediation effects of the rumen microbiome on feed efficiency traits, (2) estimate the direct and total heritability of feed efficiency traits, and (3) calculate the direct and total breeding values of feed efficiency traits. Data consisted of dry matter intake, milk energy, and residual feed intake records, SNP genotype data, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows from 2 research farms. We implemented structural equation models such that the host genome directly affects the phenotype (G P → P) and the rumen microbiome (G M → P), and the microbiome affects the phenotype (M → P), partially mediating the effect of the host genome on the phenotype (G → M → P). We found that 7% to 30% of microbes within the rumen microbial community had structural coefficients different from zero. We classified these microbes into 3 groups that could have different uses in dairy farming. Microbes with heritability <0.10 but significant causal effects on feed efficiency are attractive for external interventions. On the other hand, 2 groups of microbes with heritability ≥0.10, significant causal effects, and genetic covariances and causal effects with the same or opposite sign to feed efficiency are attractive for selective breeding, improving or decreasing the trait heritability and response to selection, respectively. In general, the inclusion of the different microbes in genomic models tends to decrease the trait heritability rather than increase it, ranging from −15% to +5% depending on the microbial group and phenotypic trait. Our findings provide more understanding to target rumen microbes that can be manipulated, either through selection or management interventions, in order to improve feed efficiency traits. [ABSTRACT FROM AUTHOR]

Public transport ridership has been hit hard by the COVID-19 pandemic in many countries. Investigating passengers' public transport mode choice behavior during large-scale public health incidents can uncover the major influential factors and help propose policies and strategies to reduce the pandemic transmission and recover the public transport revenue. This study develops an integrated choice and latent variables (ICLV) model by income based on structural equation model to model passengers' public transport choice behavior during the normalized stage of the pandemic. The model considers passengers' socioeconomic attributes, travel attributes, and attitude-perception attributes, and can appropriately capture passengers' psychological latent attributes. Taking Beijing China as an example, we collect some revealed preference survey data online. The modeling results show that the risk perception as a mediator variable has a significant impact on mode preference. Moreover, the convenience of public transport has the largest influence on risk perception. These findings suggest that risk perception and the convenience of public transport play a major role in passengers' mode choice behavior. In addition, the impacts of the various influential factors on the public transport mode choices are significantly different across different income groups. Further, the ICLV model can achieve better performance and is superior to the traditional Multinomial Logit model. The modeling framework can help propose targeted and instructive strategies during the normalized stage of the pandemic by uncovering the major influential factors in passengers' public transport mode choices, which is applicable to similar pandemics in the future. • The socioeconomic attributes, travel attributes, and attitude-perception attributes are systematically considered to study passengers' public transport mode choice behavior during the normalized stage of the pandemic. • The integrated choice and latent variables (ICLV) model can appropriately capture the psychological latent attributes. • Risk perception has statistically significant impact on passengers' public transport mode choice behavior while the convenience of public transport mode has the largest influence on risk perception. • The ride-hailing and shared bike are commonly acknowledged as being less risky than subway and bus. • The effectiveness of the ICLV model considering different income groups is demonstrated through numerical experiments. [ABSTRACT FROM AUTHOR]

Childhood trauma is a risk factor for self-harm/suicidal behavior, but research on the potential association linking sleep quality and anxiety symptoms to childhood trauma and self-harm attempt is limited. The aim of this study was to describe the mediating role of sleep quality and anxiety symptoms between childhood trauma and self-harm attempt, and to provide a scientific basis for the prevention of self-harm behaviors. This study ultimately included 11,063 study participants who participated in the baseline survey of this large prospective cohort study of the UK Biobank. We used structural equation modeling (SEM) to analyze the chain mediating role of sleep quality and anxiety symptoms in childhood trauma and self-harm attempt while controlling for covariates. A total of 19.58 % of study participants self-reported self-harm attempt. Sleep quality was negatively correlated with childhood trauma, anxiety symptoms, and self-harm attempt (p < 0.01). Childhood trauma, anxiety symptoms, and self-harm attempt were positively correlated (p < 0.01). In addition, after adjusting for confounders, anxiety symptoms were able to partially mediate the association between childhood trauma and self-harm attempt (effect value: 0.042, p < 0.01), and sleep quality and anxiety symptoms can chain mediate the association between childhood trauma and self-harm attempt (effect value:0.002, p < 0.01), with a total mediating effect of 65.67 % of the total effect. Subgroup analyses further showed that the mediating effects of sleep quality and anxiety symptoms on childhood trauma and self-harm attempt differed across age, gender, ethnicity, and smoking and drinking subgroups. This study found a complex relationship between childhood trauma, sleep quality, anxiety symptoms, and self-harm attempt, with sleep quality and anxiety symptoms mediating the relationship between childhood trauma and self-harm attempt. Multiple avenues of intervention, such as the provision of professional psychological interventions and timely monitoring, should be used to improve the sleep quality and mental health of individuals with traumatic childhood experiences and to prevent the occurrence of emotionally harmful behaviors such as self-harm/suicide. • Childhood trauma can negatively influence anxiety symptoms and self-harm attempt, and positively influence sleep quality. Anxiety symptoms can positively influence self-harm attempt. Sleep quality can negatively influence self-harm attempt and anxiety symptoms. • Anxiety symptoms were able to partially mediate the association between childhood trauma and self-harm attempt. And sleep quality and anxiety symptoms can chain mediate the association between childhood trauma and self-harm attempt. • Subgroup analyses showed that the mediating effects of sleep quality and anxiety symptoms on childhood trauma and self-harm attempt differed across characteristics. [ABSTRACT FROM AUTHOR]

Research has demonstrated that engagement in any learning environment improves learning and may even boost performance. Consequently, numerous scholars have examined various approaches to raising student engagement in learning. Gamification is one such approach because it is thought to increase motivation and reduce cognitive load to ultimately improve learning outcomes. However, some studies have called into question its benefits, prompting more research to be conducted to properly understand the phenomenon. Hence, the study examined gamification's influence on motivation and cognitive load for enhancing learning engagement. The study was underpinned by the integration of the Attention, Relevance, Confidence, and Satisfaction (ARCS) model, self-determination theory (SDT), and cognitive load theory (CLT) in developing a conceptual framework. A sample of 407 university students who participated in five gamified courses were involved in the study. The data collected through a questionnaire were analyzed using SmartPLS structural equation modeling software. According to the study's findings, both motivation and cognitive load influence engagement in learning, with cognitive load being the stronger influence. The study contributes to our knowledge by elucidating the relationship between gamification and students' cognitive load and motivation to learn, as well as how these elements ultimately engage students in the learning process. [ABSTRACT FROM AUTHOR]

While pedestrian crashes on suburban roads have received more attention over recent years, the role of pedestrian crossing risk in areas adjacent to pedestrian crossing facilities, such as pedestrian overpasses, has been neglected. Most pedestrians in suburban areas tend to avoid pedestrian overpasses, exhibiting crossing behaviors that increase the likelihood of pedestrian-involving crashes. As a result of the presence of overpasses, drivers may think that there are no pedestrians in the surroundings, so they choose a speed based only on the prevailing traffic and road environment without accounting for potential interactions with pedestrians. Consequently, crashes will occur, with pedestrians typically being the most seriously affected casualties. In this study, using video recordings from a suburban road in Amol-Babol, Iran, the risk of pedestrian crossing behavior in areas near pedestrian overpasses is investigated. The speed selection behavior of drivers in these areas has also been examined using speedometer cameras. To quantify the level of risk for pedestrians when interacting with approaching vehicles during the crossing movements, the post encroachment time (PET) was used as a surrogate safety measure. Based on critical thresholds of PET, three different risk levels were identified using a K-means algorithm: high, medium, and low risk. To identify the elements affecting the risk of pedestrian crossing behavior, structural equation models were estimated for all three risk levels. The results showed that human factors, relating to both drivers and pedestrians, have a dominant impact on pedestrian safety, especially in high and medium risk contexts. Road and vehicle factors were also found to have statistically observable effects on pedestrian safety, but to a milder extent compared to human factors. The findings of this study highlight the need for intervening in several aspects of vehicle-pedestrian interactions with critical importance for pedestrian safety, including road users' performance and compliance, state of alertness, and interaction with road infrastructure. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the acceptance and factors influencing acceptance of rubella-containing vaccine (RCV) among women of reproductive age in Guangdong, Henan, Hubei, Liaoning, Shanxi, Sichuan and Zhejiang provinces of China. Methods: Using a stratified sampling method, we selected one urban and one rural community health services center in each of two cities in seven provinces. From these centers, we recruited women 15–49 years of age to complete a questionnaire on their willingness to receive RCV and factors influencing willingness. The survey instrument was adapted from the behavioral and social drivers (BeSD) of vaccination survey tool developed by the World Health Organization. Results: Among 1286 participants, 981 (76.3%) were willing to receive RCV. Awareness of rubella ranged from 12.4% to 70.6%. Willingness to receive RCV differed significantly by region, occupation, vaccination history, and awareness. All latent variables of the structural equation model (SEM) were positively correlated with willingness, and all standardized paths were statistically significant (p < 0.001). Thinking and Feeling had direct positive effects on Social Processes (β = 0.789) and Practical Issues (β = 0.542), thereby indirectly affecting motivation. Conclusions: Women of reproductive age had high willingness to receive the rubella vaccination, but their general awareness of rubella was relatively low. It is necessary to strengthen the health education of women of reproductive age regarding rubella to improve RCV coverage. [ABSTRACT FROM AUTHOR]

Exploring the factors that drive changes in biodiversity is a hot and critically important topic in landscape ecology and biogeography. In this study, semi-structured citizen science data and bird distribution maps were employed to gather data from 2015 to 2020 for the calculation of bird species richness, the Shannon index, and the Pielou index in Anhui Province. These metrics were utilized to assess avian biodiversity and to elucidate the spatial patterns of biodiversity distribution across the region. In this research, a structural equation model (SEM) was utilized to investigate the relationships between the three dimensions of landscape spatial structure, urban development intensity, and environmental factors on bird biodiversity, and a conceptual framework was established to identify the key driving factors. The validity, reliability, and fit of the hypothesized model were substantiated through rigorous testing, demonstrating its reasonableness. The results indicate the following: (1) In landscape spatial structure, landscape composition and configuration play crucial roles in influencing bird diversity. An increased proportion of cultivated land negatively impacts bird diversity, whereas the expansion of forested areas promotes it. At the configuration level, the Largest Patch Index (LPI) significantly enhances bird diversity, serving as the primary driving force. Landscape spatial structure affects bird diversity both directly, through its composition, and indirectly, through its configuration. (2) The dimension of urban development intensity generally shows significant negative impacts; among these, GDP has the greatest comprehensive impact and shows a significant negative impact. (3) Topography has the greatest overall impact on bird diversity among the environmental factors, with a predominantly direct positive effect. (4) Overall, urban landscape spatial structure and urban development intensity are the main driving forces of bird diversity in Anhui Province, the greatest of which is the direct effect of the urban development intensity. These results provide an important scientific basis for landscape planning and ecological protection and provide inspiration for assessing the driving factors of animal and plant diversity in other regions. [ABSTRACT FROM AUTHOR]

Copyright of New Perspectives in Translation Studies is the property of New Perspectives in Translation Studies Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Modern Educational Technology is the property of Editorial Board of Modern Educational Technology, Tsinghua University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: Long-term care assistants are taking on more important roles in the healthcare system. The purpose of this study was to investigate what demographic factors influence the core competencies of nursing assistants, as well as to investigate the levels of organizational support, self-efficacy, and core competencies among nursing assistants in China, to explore the relationship between them. Methods: This is a cross-sectional study with prospective data collection based on a self-report questionnaire. A total of 320 long-term care assistants from two healthcare institutions. We collected socio-demographic characteristics and measured their perceived organizational support, self-efficacy, and core competency levels of the participants. Pearson correlation tests were conducted to examine the relationships among three variables, and a structural equation model was developed to test the interrelationships among these variables. Results: The results indicated that age, employment type, licensing status, monthly income, pre-job training, and training methods were associated with core competency, with nursing knowledge identified as a weak area in core competencies. There were significant associations among each dimension of perceived organizational support, self-efficacy, and core competencies (p < 0.01). The structural equation model demonstrated good fit: X2/df = 2.486, GFI = 0.974, CFI = 0.988, IFI = 0.988, TLI = 0.977, RMSEA = 0.068, SRMR = 0.013. The direct effect of organizational support on core competencies was 0.37, with self-efficacy mediating the relationship between organizational support and core competencies, yielding an indirect effect of 0.122 and a total effect coefficient of 0.492 (all p < 0.001). Conclusion: Training in core competencies should prioritize nursing knowledge. Enhanced perceived organizational support and self-efficacy among nursing assistants were associated with higher core competencies. [ABSTRACT FROM AUTHOR]

To solve the problems of unstable chain and poor supply chain (SC) function in the China’s agriculture industry, the relevant study is carried out on the function evaluation of the sustainable agricultural SC by structural equation modelling (SEM) under the background of digital technology. Primarily, the analysis is implemented on the research status of the sustainable SC and SC function. Then, starting with the relationship among big data (BD) application, information sharing, and sustainable SC function of agricultural production, a function evaluation model is implemented for the sustainable SC of SEMbased agricultural production. Next, a questionnaire is designed for the research on the impact of BD applications on the function of the sustainable agricultural SC. Ultimately, the statistical analysis of the obtained data reveals the correlation between the interaction and influence among the BD application, information sharing, and sustainable SC function of agricultural production. The results show that the BD application dimension, information sharing dimension, and all sub-dimensions have is beneficial to the function of the agricultural sustainable SC. The application of multidimensional cloud technology in BD has no obvious relationship with the dimensionality and level of information sharing, and the relationship between other corresponding dimensions shows a significant positive impact. A referenceable method is provided for the practice of sustainable SC management of agricultural production. [ABSTRACT FROM AUTHOR]

This study aims to analyse the determinants of sustainable consumption behaviour (SCB) of guests in luxury hotels by extending the Theory of Planned Behaviour (TPB). This study adopted a quantitative cross-sectional approach to analyse the determinants of guests' SCB. Data for the study were collected between November 2021 to January 2022 from 298 respondents using Google Forms. The result indicates that the SCB of guests at luxury hotels is predominantly influenced by the guest's attitude towards sustainability. Other significant factors that determine the sustainable consumption behaviour of guests at luxury hotels are perceived cost, perceived benefit, and perceived behavioural control. The study also demonstrates the applicability of TPB and the need for its extension to understand individuals' SCB from the perspective of perceived cost and benefit. [ABSTRACT FROM AUTHOR]

Background: E-health systems have the potential to improve healthcare delivery and access to medical services in resource-constrained settings. Despite its impact, the system exhibits a low level of consumer acceptance and intention to use it. This research paper aims to analyze the intention of health service employees to use e-health systems in southwest Ethiopia using the UTAUT-2 model. Method: Institutional-based cross-sectional studies were conducted at four referral hospitals (two private and two public) to examine the acceptance of e-health among consumers. Employees who had previous experience with diagnostic information systems and the health logistic information system were given structured questionnaires based on the UTAUT-2 model. The data were analyzed using the PLS-SEM method to identify the key factors that influence the intention to use e-health systems. The data were analyzed using SPSS version 20 and SmartPLS 3 software. Result: Out of the 400 surveyed employees, 225 (56.25%) valid questionnaires were collected. The findings indicate that three factors—effort expectancy (β = 0.276, t = 3.015, p = 0.001), habit (β = 0.309, t = 3.754, p = 0), and performance expectancy (β = 0.179, t = 1.905, p = 0.028)—had a significant positive impact on employees' intention to use e-health systems. On the other hand, factors such as social influence, facilitating conditions, hedonic motivation, and price values did not appear as significant predictors of intention to use e-health. The study model was able to predict 63% of employees' intentions to use e-health systems. Conclusion: Effort expectancy, habit, and performance expectancy were significant predictors of employees' intention to use e-health systems among health service employees in southwest Ethiopia. The study supports the ideas that ease of use, experience with information systems, and the role of the systems in improving job performance contribute to employees' intention to use e-health. Policymakers and healthcare organizations in the region can use these findings to develop strategies for successful implementation and adoption of e-health systems, ultimately improving healthcare services and outcomes for the population. [ABSTRACT FROM AUTHOR]

In recent years, the rapid rise of short video e-commerce live-streaming has led to new interactive relationships and user consumption patterns, leading to the development of more social and interactive live-streaming methods. To deeply explore the influence path of short video e-commerce live-streaming on users' interactive behavior, this study combines the chain theory of interactive rituals with the stimulus-organism-response theoretical model, and constructs a chain model mediated by perceived value and perceived trust. A total of 451 research questionnaires were collected through live simulation experiments, and structural equation modeling was used for testing. It was found that (1) the interactive ritual elements in short video e-commerce live-streaming have a positive influence on user interaction behavior; (2) perceived value and perceived trust have a positive mediating role between interactive ritual elements and user interaction behavior and play a chain mediating role in the influence of interactive ritual elements on social behaviors; and (3) affective energy positively influences user interactions, and exerts a positive moderating role. [ABSTRACT FROM AUTHOR]

As China increasingly focuses on sustainable development, understanding and influencing urban residents’ energy-saving behaviors becomes vital for addressing high energy consumption issues. Thus, this research chooses the residents in China as its object, and studies the factors influencing residents’ habitual energy-saving behaviors. We establish a comprehensive theoretical model suitable for this study based on the Stimulus-Organism-Response (SOR) theory. Utilizing on-the-spot investigations, extensive data collection and model establishment, our research reveals that “altruism” – defined here as actions driven by concern for societal expectations – predominantly motivates daily energy-saving behaviors. In addition, external factors (cost of energy-saving measures) have a significant impact on residents’ energy-saving investment behaviors. Based on our findings, we propose specific policy recommendations focusing on publicity on environmental pollution, the platform for sharing energy conservation experiences and formulation of group-differentiated energy conservation policies. Therefore, this study provides policy implications for motivating residents to take energy-saving actions. [ABSTRACT FROM AUTHOR]

Students' Emotional Intelligence and academic motivation are theorized to shape student learning engagement activities. Nevertheless, there is limited knowledge regarding the mediating mechanisms that explain this relationship. Based on Self System Model of Motivational Development, this study examined whether teachers' support mediated the relationship between Emotional Intelligence and learning engagement, as well as the connection between academic motivation and learning engagement among college students. Totally, 336 students (female: 63.4%, male: 36.6%, mean: 1.63, Std.:0.482) were recruited from two public vocational education institutes in China. The expert questionnaire was sent via email to 10 experts in order to collect their thoughts on the aspects that influenced learning engagement. The factors that influenced students' learning engagement were identified based on the Fuzzy Delphi method. Hence, the quantitative (questionnaire survey) design was used to gather students' data on demographic variables, emotional intelligence, academic motivation, teachers' support and learning engagement. The structural equation model (PLS-SEM) was used to analyse the data. The findings of this study reveal the positive impact of students' Emotional Intelligence and academic motivation on learning engagement in the educational field by adopting teachers' support as a mediating variable. The results highlighted vital internal and external factors in the process of creating an academic environment that motivated students to learn. This will improve the performance of the teaching faculty and lead to the student's academic success. This research proposed a new instrument to assess the students' engagement, which contributed to carrying out new research in the university educational context from a new research perspective. [ABSTRACT FROM AUTHOR]

With the widespread application and deep penetration of digital technology, its empowering role in multiple fields is becoming increasingly evident. Especially in the southwestern border areas of China, digital empowerment has brought new opportunities and momentum to promote homecoming entrepreneurship. This study focuses on exploring how digital empowerment can repair homecoming entrepreneurship in the region, and deeply analyzes the repair mechanism through structural equation modeling combined with empirical data. Research has found that digital empowerment has had a positive effect on repairing the flow and accessibility of entrepreneurial information in the assistance of government agencies and affiliated enterprises in the region. Meanwhile, when digital empowerment is combined with regional affiliated enterprises and investment institutions, it has a significant positive impact on repairing and promoting the implementation and operation of entrepreneurial projects. In addition, government agencies and non-governmental organizations in the region have effectively supplemented and repaired the knowledge structure and abilities of entrepreneurs with the support of digital empowerment. [ABSTRACT FROM AUTHOR]

Student satisfaction in online live classes is considered an important criterion to evaluate the effectiveness of this instructional system. This study aims to develop a performance evaluation index to measure the satisfaction of students who have mastered Chinese language and literature through online live classes. Guided by survey techniques and related theories, a questionnaire on satisfaction in online live classes for students majoring in Chinese language and literature was developed. The reliability and validity of the measurement instrument were assessed through testing, and the results showed good reliability and validity. Exploratory factor analysis and confirmatory factor analysis were used to establish a performance evaluation model. The findings of this study contribute to the field of online education by providing a structured method to assess student satisfaction with the Chinese language and literature through online live classes. The performance evaluation index developed in this study can be used by educational institutions to improve the quality of their online instructional programs and improve the overall learning experience for students. Thus, the novelty of the study is to develop an evaluation model that helps educational institutions to evaluate the effectiveness of online live classes and guide the improvement of instructional practices. [ABSTRACT FROM AUTHOR]

With the expansion of virtual spaces, the role of virtual influencers has become more important. Although virtual influencers are imaginary characters, people can become interested in their attractive appearances and human characteristics and values on social media. However, most existing studies on virtual influencers deal with external factors, such as their appearance. This study aimed to investigate whether virtual influencers and users' self-congruity including their actual and ideal selves on emotional attachment and to verify the effects of emotional attachment to virtual influencers on attitudes towards virtual influencers. A survey was conducted of 344 users, and empirical results from structural equation modeling indicated that significant impacts of actual self-congruity between virtual influencers and users were found on emotional attachment when virtual influencers were divided into external and internal images. Additionally, the congruity between internal images of the virtual influencers and the user's ideal self-congruity significantly affected emotional attachment. The study results demonstrated that self-congruity theory provides an accurate framework for describing the role of emotional attachment to virtual influencers. [ABSTRACT FROM AUTHOR]

Recently, quantile-based structural equation model has enjoyed increasing popularity in various fields and applications. As we know, structural equation model consists of structural model and measurement model in total. In our quantile-based measurement model, the observed variables are considered to be manifestations of an underlying construct with changing relationships going from the latent variable to its observed variables at different quantiles. Based on our model, we propose a quantile-based partial least square algorithm with bag of little bootstraps. All of our model and algorithm are compared to our quantile-based partial least square algorithms with traditional bootstrap in simulations, and applied to part of IMD (International Institute for Management Development) World Competitiveness Yearbook datasets. [ABSTRACT FROM AUTHOR]

This study investigates the intricate causal mechanisms of university students' sustained use of artificial intelligence (AI) tools for self-directed learning (SDL) within the theoretical framework of self-determination theory (SDT). Employing a convenience sampling strategy, 387 university students from China were included in the study. Methodologically, we employed structural equation modeling (SEM) for the measurement and causal analysis, and we employed fuzzy-set qualitative comparative analysis (fsQCA) for the configurational analysis. The research results emphasize several important insights. Perceived usefulness, intrinsic motivation, and satisfaction play important roles in encouraging university students' continuance intentions. Satisfaction emerges as a pivotal mediator, bridging the connection between perceived usefulness, intrinsic motivation, and continuance intention. The system quality, the information quality, and social interaction have significant positive influences on perceived usefulness. Perceived autonomy and perceived competence display strong correlations with both intrinsic motivation and satisfaction. Moreover, the results from the fsQCA show five configurations, in which the key factors collectively shape students' continuance intentions through complex interactions through various configurations. The findings reveal diverse configurations by which university students form continuance intentions towards using AI tools for SDL, providing detailed insights into the profound and indirect impacts on forming continuance intention behaviors. This enriches and advances the current theoretical understanding. [ABSTRACT FROM AUTHOR]

Green finance, innovation, and resource efficiency have gained significant traction recently, particularly in resource-rich countries. This study investigates the role of green finance and innovation in resource efficiency with the mediating lens of environmental regulations and market rules. The study employs a structural equation model on a panel of 15 resource-rich countries from 1995 to 2023. The findings illustrate a complicated interplay between the variables. First, the findings show that green financing positively and negatively affects resource efficiency. In contrast, green innovation constantly improves resource efficiency. Market rules have a favorable impact on resource efficiency. Environmental laws, however, hurt resource efficiency. Furthermore, the study reveals that green financing favors market regulations, implying that financial expenditures in green initiatives might strengthen regulatory frameworks that promote market efficiency. In contrast, green finance harms environmental rules, and green innovation harms both market and environmental regulations. In addition, we divided the sample into developed and developing nations and offered a sub-group analysis to take into consideration the variations in the degree of national development and green advances to further improve the analysis. Overall, the study emphasizes the multifaceted role of green finance and innovation in increasing resource efficiency within regulatory frameworks. These findings are critical for policymakers and stakeholders in resource-rich countries seeking to reconcile economic growth with sustainable development. [ABSTRACT FROM AUTHOR]

Urban form is a key factor affecting carbon emissions. Accurately estimating the impact of urban form on the carbon emissions of residents (CER) is an important prerequisite for China to adopt effective low-carbon spatial planning strategies and respond to climate change. However, counties mainly account for China's energy consumption, and the relationship between their urban form and the CER remains unclear, limiting their low-carbon development. Therefore, in this study, the PLS-SEM model and data from 90 counties in the Yangtze River Delta are used to determine the extent and ways that urban form affects the CER. The model considers the impact of both geometric-aspect urban form factors (urban scale, compactness, spatial structure, and urban shape) and built environment-aspect urban form factors (public service facilities, urban greening, road traffic, public transportation, and urban energy infrastructure) on the CER. The results indicate that urban form factors related to the built environment (public service facilities, urban greening, road systems, and municipal infrastructure) have a direct impact on the CER. Geometric-aspect urban form factors (size, compactness, spatial structure, and shape) not only directly affect the CER but also indirectly affect the CER by altering built environment-aspect urban form factors. This study identifies the complex relationship between urban form and the CER, facilitating the coordinated integration of multiple elements and providing a basis for the formulation of low-carbon spatial planning strategies for counties. [ABSTRACT FROM AUTHOR]

The understory herbaceous flora plays a pivotal role in regulating the structural stability, complexity, and ecological function of forest communities. It is crucial to investigate the impact of the intricate connections between these factors and the forces driving the diversity of herbaceous species within natural broadleaf understory forests can assist forest managers in developing optimal forest structure optimization techniques, allowing them to adjust the forest species diversity. In this study, Pearson correlation analysis, conventional correlation analysis, and multiple linear regression were employed to elucidate the relationship between stand structure, soil nutrients, and understory herbaceous species richness in natural broadleaved forests. Structural equation modeling was utilized to ascertain the influence of multiple factors on understory herbaceous species diversity and to evaluate the underlying pathways. The results indicated a significant negative correlation between stand closure and the Simpson's and Shannon-Wiener's indices, and between the mixing degree and the Pielou evenness index, Simpson's index, and Shannon-Wiener's index (p<0.05). Furthermore, a significant positive correlation was observed between soil nutrients, specifically organic matter and total phosphorus, and the Pielou evenness index and Shannon-Wiener's index (p<0.05). It was found that total phosphorus was significantly positively correlated with both the Pielou evenness index and the Shannon-Wiener index (p<0.05). The correlation coefficients of the first group of typical variables in the typical correlation analysis were 0.498 and 0.585, respectively (p<0.05). From the set of typical variables of stand structure, it can be seen that the Hegyi competition index and the canopy density affected the diversity of understory herbaceous plants. The composite index demonstrated the greatest impact, with loadings of 0.872 and -0.506, respectively. The Simpson and Shannon-Wiener indices exhibited the most sensitive loadings of -0.441 and -0.408, respectively. The soil nutrients of SOM and TN affected the understory herbaceous plant species diversity composite index, with greater loadings of -0.184 and 1.002, respectively. The path coefficient of the understory herbaceous diversity stand structure was 0.35. The path coefficient with soil nutrient content was found to be 0.23 following structural equation analysis and the path coefficient between stand structure and soil nutrient content was 0.21, which indirectly affect the diversity of understory herbaceous species. To enhance the diversity of herbaceous species, it is recommended that the canopy density and tree density of the upper forest be reduced appropriately, while the degree of mixing and the level of spatial distribution of trees be adjusted in a manner that maintains a reasonable stand structure. Furthermore, a comprehensive forest management program for improving soil nutrients should be considered. [ABSTRACT FROM AUTHOR]

The increasing availability and scale of biobanks and "omic" datasets bring new horizons for understanding biological mechanisms. PathGPS is an exploratory data analysis tool to discover genetic architectures using Genome Wide Association Studies (GWAS) summary data. PathGPS is based on a linear structural equation model where traits are regulated by both genetic and environmental pathways. PathGPS decouples the genetic and environmental components by contrasting the GWAS associations of "signal" genes with those of "noise" genes. From the estimated genetic component, PathGPS then extracts genetic pathways via principal component and factor analysis, leveraging the low-rank and sparse properties. In addition, we provide a bootstrap aggregating ("bagging") algorithm to improve stability under data perturbation and hyperparameter tuning. When applied to a metabolomics dataset and the UK Biobank, PathGPS confirms several known gene–trait clusters and suggests multiple new hypotheses for future investigations. [ABSTRACT FROM AUTHOR]

The foliar application of biostimulants at specific concentrations under magnetic–electric water irrigation has a positive effect on water and fertilizer use efficiency and yield of cotton, which is crucial for green and sustainable agricultural development. As a new type of fertilizer, biostimulants have demonstrated remarkable effects in improving crop yield and quality by enhancing nutrient uptake, promoting plant growth, and increasing resilience to environmental stress. In this study, the effects of magnetic–electric-activated water irrigation and foliar biostimulant application on cotton growth and yield were investigated, with the aim of understanding the underlying mechanisms. The field experiment included various irrigation treatments (brackish water, fresh water, magnetic–electric brackish water, and magnetic–electric fresh water) and biostimulant concentrations (1600, 1200, 800, 400 times dilution, and no spraying). SEM analysis indicated that under magnetoelectric water irrigation, the foliar application of biostimulants enhances physiological growth of cotton, improving the water and nutrient uptake efficiency, and thereby increasing yield. Specifically, the effective boll number and single boll weight under magnetic–electric fresh water irrigation with an 800 times biostimulant concentration increased by 21.84–48.78% and 5.50–18.91%, respectively, compared to the no-spraying treatment. The seed cotton yield rose by 16.61–38.63%, water-use efficiency improved by 24.35%, the harvest index reached 0.33, and nitrogen absorption increased by 76.21%. Thus, integrating magnetic–electric water irrigation with foliar biostimulants offers a theoretical and technical foundation for advancing green, high-quality agriculture and sustainable production. [ABSTRACT FROM AUTHOR]

Despite increasing rent price burdens throughout Europe, many eligible households for rental subsidies do not use them. Understanding determinants of low take‐up is crucial for evaluating program effectiveness and anticipating fiscal implications. To identify those determinants, we built an extended version of the theory of planned behaviour, incorporating dimensions from the claiming costs scale. In an online survey, participants comprising renting households likely eligible for the housing subsidy from Germany (n = 862) and Spain (n = 1032) completed measures of behavioural intention, rental cost burdens, theory of planned behaviour constructs (attitudes, subjective norms, perceived behavioural control, and past behaviour), and claiming costs constructs (information costs, process costs, and stigma). Results supported a multi‐group model, showing different paths for Germany and Spain. Several similar paths were identified for both countries, such as the indirect association of stigma with intention to apply for rental subsidies via attitude, the positive and strong association of subjective norms, and the positive association between perceived behavioural control and intention. The indirect relationship involving information costs was observed for Spain but not Germany, and rental cost burdens operated differently as well. These findings suggest that multiple dimensions, both psychological and policy‐related, should be considered when investigating claiming behaviours for rental subsidies, while emphasizing the need to acknowledge the unique characteristics of each country. This evidence is also relevant to policymakers, offering insights into leveraging established policy tools. Please refer to the Supplementary Material Section to find this article's Community and Social Impact Statement. [ABSTRACT FROM AUTHOR]

Schools and universities insisted on using live instructions and synchronous learning for the main strategy of learning during the global crisis. For this reason, it may be critical to investigate the students' use and acceptance of live instruction behaviors to see if they use it or not. The purpose of this research is to investigate the factors affecting undergraduate students' acceptance and use of learning in live instructions during the global crisis in Turkey within the context of the Unified Theory of Acceptance and Use of Technology Model (UTAUT). This model examined whether students' gender, grade, experience, and major moderated BI and use live interaction. PE and SI were the primary determinants of BI. However, EE and FC had no effect on live instruction acceptance. Students' lack of knowledge or confidence in the live instruction environment may influence effort expectancy and facilitating conditions. [ABSTRACT FROM AUTHOR]

Nowadays, academics and industrial practitioners widely consider additive manufacturing systems to enhance overall production and operational effectiveness and efficiency, owing to the concepts of Industry 4.0 and 5.0. This paper proposes a structural equation model to evaluate the impact of customisation experience and perceived value within a data-driven additive manufacturing system. To deepen the understanding of customer-perceived value and its connection to additive manufacturing, this study defines four new sources of perceived value: reliability, performance, aesthetics, and features. All of these new values are based on utilitarian value, and four of them exhibit statistical significance in relation to utilitarian value. In order to apply these new values to additive manufacturing, it is necessary to conduct mechanical testing and studies to identify the ideal parameter set for 3D printing that aligns with customer-perceived value regarding these new values. [ABSTRACT FROM AUTHOR]

Preservice teachers' self‐regulation skills are key to being role models to their students in gaining this affective skill. The study aims to develop a structural equation model (SEM) that shows the relationship between preservice science teachers' perceived role modeling and self‐regulation skills. This study has been conducted using the predictive correlational design, a quantitative research method. The sample of the study consists of 242 volunteer preservice science teachers from two state universities in Türkiye. Data were collected using the Perceived Role Models Scale and the Self‐Regulation Scale for Science. The study used the SEM's model development strategy to determine whether a relationship exists between preservice science teachers' perceptions of role modeling and their self‐regulation levels regarding science and whether the relationship if any is significant or not. As a result, a model was developed that shows preservice science teachers' perceived role modeling to predict their self‐regulation skills in science significantly. This result shows role modeling to be important in developing preservice teachers' self‐regulation skills. Therefore, we have concluded that self‐regulation is an ongoing process at early ages and adulthood. Practitioner Points: Role models can improve preservice teachers' self‐regulation skills.Developing self‐regulation skills is a lifelong process.The education system should also develop affective skills such as self‐regulation. [ABSTRACT FROM AUTHOR]

Due to the complex nature of mega construction projects (MCPs), technological innovation risks have signifi- cantly increased. Cooperation is widely accepted as a proactive approach to resolving these risks. An in-depth study of technological innovation cooperative behavior (TICB) helps understand the underlying reasons, but studies need to pay more attention to it. This study explored the factors affecting TICB for MCPs and developed a conceptual model based on the Theory of planned behavior (TPB). It established a structural equation model to verify the relationship between influencing factors. An example verified the feasibility of the model. The results show that cooperative attitude, subjective cooperative norm, perceived cooperative behavior control, and cooperative scenarios positively affect cooperative behavior through cooperative intention. Cooperative attitude plays a mediating role between cooperative scenarios and cooperative intention. Perceived cooperative behavior control has no direct effect on cooperative behavior. This study provides a theoretical reference to guide future empirical studies and enriches the knowledge of TICB for MCPs. [ABSTRACT FROM AUTHOR]

Schizophrenia is a severe psychiatric disorder, characterized by positive symptoms, negative symptoms, and cognitive deficits. Elucidating the mechanism of negative symptom and cognitive deficits could contribute to the treatment and prognosis of schizophrenia. We hypothesized that abnormal functional connectivity would be involved in the indirect effects of negative symptoms on cognitive function. A total of 150 schizophrenia male patients and 108 healthy controls matched for age, education and gender were enrolled in the study. The scores of Brief Negative Symptom Scale were divided into two factors: motivation and pleasure deficits (MAP) and diminished expression (EXP). Subsequently, a series of classic neurocognitive tests were used to evaluate cognitive functions. Resting-state fMRI data was collected from all participants. The Anatomical Automatic Labeling template was employed to establish regions of interest, thereby constructing the functional connectivity network across the entire brain. Eventually, scores of patients' negative symptoms scale, cognitive function, and strengths of abnormal functional connectivity were incorporated into a structural equation model to explore the interactions among variables. MAP exhibited a distinctly and significantly negative impact on cognitive function. The functional connectivity between the left insula and left precuneus, along with that between the left precuneus and right angular gyrus, collectively served as intermediaries, contributing to the indirect effects of MAP and EXP on cognitive function. Our findings demonstrated the moderating role of aberrant brain functional connectivity between negative symptoms and cognitive function, providing clues about the neural correlates of negative symptoms and cognitive deficits in schizophrenia. [ABSTRACT FROM AUTHOR]