Influence of the first wave of COVID-19 on Chinese students' psychology and behavior: a case study approach.

During the first wave of COVID-19, China demonstrated a strong commitment to epidemic prevention and control. This case study focuses on Z University, which adopted closed management when the epidemic was serious, and examines the influence of COVID-19 on students' psychology and behavior through interviews with 10 students. The research reveals that while students perceive closed management during the epidemic as enhancing safety and promoting learning engagement to some extent, the epidemic also has adverse effects on their physical health, psychology, and social life. These impacts included deteriorating physical health, feelings of rebellion and depression regarding college life, alongside concerns and aspirations regarding future job stability. In the discussion, we suggest that higher education institutions can utilize this information to shape policies and procedures, particularly concerning mental health and risk communication, not only during the current pandemic but also in future emergency or disaster scenarios.

A novel bounded loss framework for support vector machines.

This paper introduces a novel bounded loss framework for SVM and SVR. Specifically, using the Pinball loss as an illustration, we devise a novel bounded exponential quantile loss (Leq-loss) for both support vector machine classification and regression tasks. For Leq-loss, it not only enhances the robustness of SVM and SVR against outliers but also improves the robustness of SVM to resampling from a different perspective. Furthermore, EQSVM and EQSVR were constructed based on Leq-loss, and the influence functions and breakdown point lower bounds of their estimators are derived. It is proved that the influence functions are bounded, and the breakdown point lower bounds can reach the highest asymptotic breakdown point of 1/2. Additionally, we demonstrated the robustness of EQSVM to resampling and derived its generalization error bound based on Rademacher complexity. Due to the Leq-loss being non-convex, we can use the concave-convex procedure (CCCP) technique to transform the problem into a series of convex optimization problems and use the ClipDCD algorithm to solve these convex optimization problems. Numerous experiments have been conducted to confirm the effectiveness of the proposed EQSVM and EQSVR.

Do Adolescents Adopt the Prosocial Behaviors of the Classmates They Like? A Social Network Analysis on Prosocial Contagion.

While the influence of high-status peers on maladaptive behaviors is well-documented, socialization processes of prosocial behavior through high-status peers remain understudied. This study examined whether adolescents' prosocial behavior was influenced by the prosocial behavior of the peers they liked and whether this effect was stronger when the peers they liked were also well-liked by their classmates. Three waves of data, six months apart, were collected among Chilean early adolescents who completed peer nominations and ratings at Time 1 (n = 294, Mage = 13.29, SD = 0.62; 55.1% male), Time 2 (n = 282), and Time 3 (n = 275). Longitudinal social network analyses showed that adolescents adopted the prosocial behavior of the classmates they liked - especially if these classmates were well-liked by peers in general. In addition, adolescents low in likeability were more susceptible to this influence than adolescents high in likeability. The influence resulted both in increases and - especially - decreases in prosocial behavior, depending on the level of prosociality of the liked peer. Findings suggest that likeability represents an important aspect of peer status that may be crucial for understanding the significance of peer influence with respect to prosocial behaviors during adolescence. Pre-Registration: https://osf.io/u4pxm .

An application of the Bayesian network model based on the EN-ESL-GA algorithm: Exploring the predictors of heart disease in middle-aged and elderly people in China.

BACKGROUND: The morbidity and mortality of heart disease are increasing in middle-aged and elderly people in China. It is necessary to explore relationships and interactive associations between heart disease and its risk factors in order to prevent heart disease. OBJECTIVE: To establish a Bayesian network model of heart disease and its influencing factors in middle-aged and elderly people in China, and explore the applicability of the elite-based structure learner using genetic algorithm based on ensemble learning (EN-ESL-GA) algorithm in etiology analysis and disease prediction. METHODS: Based on the 2013 national tracking survey data from China Health and Retirement Longitudinal Study (CHARLS) database, EN-ESL-GA algorithm was used to learn the Bayesian network structure. Then we input the data and the learned network structure into the Netica software for parameter learning and inference analysis. RESULTS: The Bayesian network model based on the EN-ESL-GAalgorithm can effectively excavate the complex network relationships and interactive associations between heart disease and its risk factors in middle-aged and elderly people in China. CONCLUSIONS: The Bayesian network model based on the EN-ESL-GA algorithm has good applicability and application prospect in the prediction of diseases prevalence risk.

Applying Social Network Theory to Vaping in High School: Implications for Person-Centered Intervention.

BACKGROUND: Peer influence on risky behavior is particularly potent in adolescence and varies by gender. Smoking prevention programs focused on peer-group leaders have shown great promise, and a social influence model has proven effective in understanding adult smoking networks but has not been applied to adolescent vaping until 2023. This work aims to apply a social influence model to analyze vaping by gender in a high school network. METHODS: A high school's student body was emailed an online survey asking for gender, age, grade level, vape status, and the names of three friends. Custom Java and MATLAB scripts were written to create a directed graph, compute centrality measures, and perform Fisher's exact tests to compare centrality measures by demographic variables and vape status. RESULTS: Of 192 students in the school, 102 students responded. Students who vape were in closer-knit friend groups than students who do not vape (p < .05). Compared to males who vape, females who vape had more social ties to other students who vape, exhibiting greater homophily (p < .01). Compared to females who do not vape, females who vape were in closer-knit friend groups (p < .05) and had more ties to other students who vape (p < .01). CONCLUSION: Differences in vaping by social connectedness and gender necessitate school and state policies incorporating the social aspect of vaping in public health initiatives. Large-scale research should determine if trends can be generalized across student bodies, and more granular studies should investigate differences in motivations and social influence by demographic variables to individualize cessation strategies.

Exploring surface charge dynamics: implications for AFM height measurements in 2D materials.

An often observed artifact in atomic force microscopy investigations of individual monolayer flakes of 2D materials is the inaccurate height derived from topography images, often attributed to capillary or electrostatic forces. Here, we show the existence of a Joule dissipative mechanism related to charge dynamics and supplementing the dissipation due to capillary forces. This particular mechanism arises from the surface conductivity and assumes significance specially in the context of 2D materials on insulating supports. In such scenarios, the oscillating tip induces in-plane charge currents that in many circumstances constitute the main dissipative contribution to amplitude reduction and, consequently, affect the measured height. To investigate this phenomenon, we conduct measurements on monolayer flakes of co-deposited graphene oxide and reduced graphene oxide. Subsequently, we introduce a general model that elucidates our observations. This approach offers valuable insights into the dynamics of surface charges and their intricate interaction with the tip.

They approve but they don't act: promoting sustainable minority behavior with (conflicting) social norm appeals.

Background: Social norm appeals are effective in promoting sustainable majority behavior but could backfire when the target behavior is only performed by a minority of people. However, emphasizing that an increasing number of people have started engaging in the behavior or that the majority approve the behavior might prevent such negative effects. However, only a few studies have investigated the combination of descriptive minority and injunctive majority social norm appeals, with inconsistent results. Some studies of minority behavior suggest that the characteristics of recipients might determine the inconsistent results regarding the impact of minority social norm appeals and that social norm appeals could have a greater impact on individuals with weaker environment related dispositions. Method: Two two-wave studies investigated how descriptive minority appeals, injunctive majority appeals, and their combination can be used to motivate sustainable minority behavior and what role environment related dispositions play in this context. In the first part, perceived social norms, environment related dispositions, behavioral intentions, and pre-attitudes were measured. Two weeks later, respondents participated in a 3 (descriptive social norm appeal: static vs. dynamic vs. absent) × 2 (injunctive majority social norm appeal: present vs. absent) between-subjects experiment and watched an explainer video on voluntary carbon offsets that included various social norm appeals. Results: In both studies, we found that social norm appeals influenced perceived social norms. However, persuasive effects were only observed in the first study, and an injunctive majority appeal increased persuasive outcomes, but there were no differences between the descriptive conditions and no differences in their impact depending on individuals' environment related dispositions in either study. Discussion: A single exposure may be insufficient to exert persuasive effects and the change in perceived social norms may first need to be internalized. In online explainer videos, the effects of social norm appeals could be amplified by algorithm-based suggestions and when social norm appeals draw attention to norm-conforming content. However, further research is required on the long-term effects and their possible amplification via social media.

Would you bet on the vet? Influences on dairy farmers' vaccination choices, with a spotlight on the Veterinarian impact.

Ensuring effective vaccination is crucial for epidemic control, particularly in voluntary vaccination scenarios. Though highly important for planning voluntary vaccination programs, we lack insights into the effectiveness of veterinarian communication and the impact of disease-specific traits on farmer vaccination intentions. To fill this void, our study compared five diseases affecting Israeli dairy cattle (Botulism, Bovine Ephemeral Fever (BEF), Brucellosis, Lumpy Skin Disease (LSD), and Rabies). Using questionnaires grounded in the theory of planned behavior, we surveyed 340 Israeli dairy farmers to understand their vaccination intentions for each disease.Simultaneously, veterinarians overseeing these farms provided insights into their opinions and perceived influence on vaccination decisions. Results revealed varying levels of farmer vaccination intention, with Botulism showing the highest and BEF the lowest. Social pressure significantly influenced farmers' vaccination intentions, with distinct patterns across diseases. Veterinarian opinions had the highest influence only for LSD, while other factors played crucial roles in different diseases. Intriguingly, there was no correlation between veterinarians' recommendations and farmers' perceptions of these recommendations. In conclusion, the optimization of voluntary vaccination programs necessitates tailoring interventions to the unique characteristics of each disease. Additionally, improving communication between veterinarians and farmers is essential, with an emphasis on effective risk communication training.

Exploring the mechanisms driving elderly Fintech engagement: the role of social influence and the elderly's digital literacy.

Objective: This study aims to investigate the elderly digital engagement (acceptance and utilization of technology), with a focus on the widespread application of financial technology: mobile banking (m-banking). Methods: Guided by social influence theory, the research examines the various social dynamics that encourage elderly engagement with m-banking and the moderating effects of their digital literacy. Data was gathered online utilizing a disjunctive approach and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results: The study reveals that both word-of-mouths (WOMs) and peer engagement significantly influence the elderly's perceived usefulness of the platform, thereby influencing their m-banking engagement. Additionally, the level of digital literacy among older adults was found to impact their perceived usefulness of m-banking services. Interestingly, digital literacy among older adults negatively moderates the positive associations of WOMs and peer engagement on perceived usefulness. Discussion: These insights advance our understanding of how social interactions can steer technological engagement, particularly for the silver generation with diverse levels of digital literacy. As society ages and becomes increasingly digitized, it is imperative to promote digital engagement among the elderly and foster a more inclusive digital environment.

Digital technology and mental health: Chinese university students' perspectives on the impact of social media.

Background: To address the growing concerns about mental health issues among Chinese university students, our study investigates the impact of social media on their mental health. This study intends to shed light on how these students' use of social media platforms contributes to these mental health issues, given that it has been estimated that up to 30% of university students in China suffer from mental health issues. Methods: We investigate the extent of this issue by looking at how Chinese social media platforms like WeChat, Weibo, and QQ impact students' mental health. To gain a comprehensive insight into students' perspectives, this study's sole methodology is qualitative semi-structured interviews. Our core claim asserts that social media considerably affects Chinese university students' mental health, with both positive and negative consequences. Results: The findings show how closely social media use and Chinese university students' mental health are related. These networks let people connect and get support but also encourage social comparison and stigma towards mental illness. Students use a variety of coping skills, such as self-regulation techniques, digital detoxification techniques, and looking for emotional support in online networks. These results highlight the need for a complex understanding of social media's effects on mental health. Our study also recognizes students' capacity for adaptation and resilience as they traverse the digital world, offering theoretical and practical applications for successfully juggling online and offline lives. Conclusion: In the end, our study contributes to a thorough and culturally sensitive understanding of how social media affects the mental health of Chinese university students.

Influence of hypocalcemia on the prognosis of patients with multiple trauma.

BACKGROUND: Hypocalcemia is highly common in hospitalized patients, especially in those with trauma, On the other hand, abnormal calcium metabolism is an important metabolic challenge; however, it is often neglected and untreated, and certain factors may induce serious neurological and cardiovascular complications. AIM: To retrospectively analyze the impact of hypocalcemia on the prognosis of patients with multiple traumas. METHODS: The study was conducted from January 2020 to December 2021. Ninety-nine patients with multiple injuries were treated at the critical care medicine department of Fuyang People's Hospital. The selected indicators included sex, age, and blood calcium and hematocrit levels. Many indicators were observed, including within 24 h of hospitalization, and the prognosis was collected after 28 d. Based on the blood calcium levels, the patients were divided into the following two groups: Normocalcemia and hypocalcemia. Of the 99 patients included, 81 had normocalcemia, and 18 had hypocalcemia. Separate experiments were conducted for these two groups. RESULTS: There was an association between serum calcium levels and the prognosis of patients with polytrauma. CONCLUSION: Clinically, the prognosis of patients with multiple traumas can be preliminarily evaluated based on serum calcium levels.

Influence of additive and maternal effects on production and reproduction traits in Murrah buffaloes: Insights from Bayesian analysis.

The aim of this research was to assess genetic parameters for first lactation production and reproduction traits in Murrah buffaloes by employing additive and maternal effects. Data on pedigree and specific traits of 640 Murrah buffaloes were gathered from 1997 to 2020. These traits encompassed first lactation milk yield (FLMY), 305-day first lactation milk yield (305FLMY), first lactation length (FLL), first lactation peak yield (FPY), first service period (FSP), first calving interval (FCI) and first dry period (FDP). Genetic evaluations employed six univariate animal models, accounting for both direct and maternal effects, facilitated by THRGIBBS1F90 and POSTGIBBSF90 programs. Fixed factors included in the analysis were period of calving, season of calving and age at first calving. The Bayesian estimates for direct heritability, derived from the most suitable model, were as follows: FLMY: 0.28 ± 0.01, 305FLMY: 0.30 ± 0.01, FLL: 0.19 ± 0.01, FPY: 0.18 ± 0.01, FSP: 0.12 ± 0.01, FCI: 0.14 ± 0.01 and FDP: 0.12 ± 0.01. Maternal effects were found significant, ranging from 5% to 10%, in first lactation traits under Model 2 and Model 5. Additionally, positive and significant genetic and phenotypic correlations were observed among the studied traits. In conclusion, selection based on 305-day first lactation milk yield suggests potential for genetic enhancement in Murrah buffaloes, advocating its inclusion in breeding programmes to bolster early performance. Also, consideration of maternal influences is necessary for genetic progress of animals.

The process of developing and implementing health and nursing policy: Implications of research and opportunities to influence.

AIM: To provide insight into the process of developing health and nursing policy and how that process can be influenced by both researchers and nursing leaders. BACKGROUND: Nurses care for people across the life course from birth to death, in our communities, hospitals, care homes and schools. They have unique insight into how people live their lives and how this affects their health. Despite being well placed to influence health policy, nurses often fail to capitalise on this. At the same time, academics often struggle to identify the policy implications of their research resulting in further missed opportunities to use policy influence. SOURCES OF EVIDENCE: Classical policy theory, which is predominantly drawn from economics and public administration together with a range of contemporary nursing and health policy studies, is used in this paper to discuss the policy process and opportunities to influence. DISCUSSION: Researchers need to focus on realistic policy suggestions that aim to raise awareness, highlight policy problems or set the agenda. In turn, nursing leaders, from National Nursing Associations, need to harness evidence to support their efforts to influence policy. In terms of influence, a range of approaches exist, and each lends itself to different parts of the policy cycle. CONCLUSION: The role nurses can play in health policy is not well developed in many countries. Nursing researchers and leaders are well placed to influence policy but must do so in a clear and pragmatic way recognising that policymakers make decisions despite being faced with conflicting evidence, competing demands and economic imperatives. IMPLICATIONS FOR NURSING PRACTICE: Recognising that nurses can offer much in terms of policy development, the paper argues that a pragmatic approach based on different forms of influence at different stages is likely to be most successful. IMPLICATIONS FOR NURSING AND HEALTH POLICY: The evidence reviewed in this paper suggests that nursing academics and leaders need to identify realistic policy interventions when examining their own empirical work or identifying ways to individually or collectively influence policymakers.

Black shale bedrock control of soil heavy metal typical high geological background in China Loushao Basin: Pollution characteristics, source and Influence assessment based on spatial analysis.

During the process of black shale weathering, multiple heavy metal elements are concentrated in the soil, causing pollution. This study selected soil and black shale bedrock samples from high geological background areas to investigate the control of heavy metal element pollution by bedrock using spatial analysis. The research results indicate that the heavy metal content in black shale bedrock is extremely high, ranging from 2.3 to 13.1 times the background values of rock heavy metal elements. The heavy metal content in the soil formed through weathering is positively correlated with the bedrock, ranging from 1.1 to 21.3 times the background values. The coefficient of variation of rock samples ranges from 1.09 to 7.18, indicating significant variability.The analysis reveals that the control ability of pure rock over heavy metal elements is mainly moderate and high, accounting for over 70 %, with d being the most affected metal element. Except for As, the other seven elements exhibit strong spatial autocorrelation, showing distinct regional distribution characteristics. The soil elements demonstrate high homogeneity, with heavy metal elements from black shale bedrock primarily released through weathering serving as the main source of these elements.

Prejudice and Fear as Influences in Relation to a Successful Organ Donation - Experiences of Immigrants Living in Sweden.

OBJECTIVES: The purpose of this study was to determine whether fear and prejudice in relation to organ donation and the transplantation of organs may influence the decision to become an organ donor. MATERIALS AND METHODS: Data were collected through four group interviews using open-ended questions and qualitative content analysis. Forty participants, 16 males and 24 females from seven countries, participated in the focus group interviews. RESULTS: The analysis resulted in three main categories, and nine subcategories. Fears and prejudice caused by tradition and customs, approval of organ donation by family members, perception of the body as a gift from parents, the influence of religious leaders, knowledge about the religious understanding of organ donation, influence of social ambience on respondents, knowledge of the donation process in the healthcare system, including knowing about life after eventual organ donation, were some of predictors in the decision to agree to organ donation. CONCLUSION: More education on the factors that influence organ donation, more information in schools, health institutions and through the media, as well as more research with the aim of "dispelling" fears and prejudice about organ donation would significantly improve the current situation and result in a larger number of potential organ donors.

Network analysis of gut microbial communities reveal key genera for a multiple sclerosis cohort with Mycobacterium avium subspecies paratuberculosis infection.

BACKGROUND: In gut ecosystems, there is a complex interplay of biotic and abiotic interactions that decide the overall fitness of an individual. Divulging the microbe-microbe and microbe-host interactions may lead to better strategies in disease management, as microbes rarely act in isolation. Network inference for microbial communities is often a challenging task limited by both analytical assumptions as well as experimental approaches. Even after the network topologies are obtained, identification of important nodes within the context of underlying disease aetiology remains a convoluted task. We therefore present a network perspective on complex interactions in gut microbial profiles of individuals who have multiple sclerosis with and without Mycobacterium avium subspecies paratuberculosis (MAP) infection. Our exposé is guided by recent advancements in network-wide statistical measures that identify the keystone nodes. We have utilised several centrality measures, including a recently published metric, Integrated View of Influence (IVI), that is robust against biases. RESULTS: The ecological networks were generated on microbial abundance data (n = 69 samples) utilising 16 S rRNA amplification. Using SPIEC-EASI, a sparse inverse covariance estimation approach, we have obtained networks separately for MAP positive (+), MAP negative (-) and healthy controls (as a baseline). Using IVI metric, we identified top 20 keystone nodes and regressed them against covariates of interest using a generalised linear latent variable model. Our analyses suggest Eisenbergiella to be of pivotal importance in MS irrespective of MAP infection. For MAP + cohort, Pyarmidobacter, and Peptoclostridium were predominately the most influential genera, also hinting at an infection model similar to those observed in Inflammatory Bowel Diseases (IBDs). In MAP- cohort, on the other hand, Coprostanoligenes group was the most influential genera that reduces cholesterol and supports the intestinal barrier. CONCLUSIONS: The identification of keystone nodes, their co-occurrences, and associations with the exposome (meta data) advances our understanding of biological interactions through which MAP infection shapes the microbiome in MS individuals, suggesting the link to the inflammatory process of IBDs. The associations presented in this study may lead to development of improved diagnostics and effective vaccines for the management of the disease.

Prediction of influential nodes in social networks based on local communities and users' reaction information.

Identifying influential nodes is one of the basic issues in managing large social networks. Identifying influence nodes in social networks and other networks, including transportation, can be effective in applications such as identifying the sources of spreading rumors, making advertisements more effective, predicting traffic, predicting diseases, etc. Therefore, it will be important to identify these people and nodes in social networks from different aspects. In this article, a new method is presented to identify influential nodes in the social network. The proposed method utilizes the combination of users' social characteristics and their reaction information to identify influential users. Since the identification of these users in the large social network is a complex process and requires high processing power and time, clustering and identifying communities have been used in the proposed method to reduce the complexity of the problem. In the proposed method, the structure of the social network is divided into its constituent communities and thus the problem of identifying influential nodes (in the entire network) turns into several problems of identifying an influential node (in each community). The suggested method for predicting the nodes first predicts the links that may be created in the future and then identifies the influential nodes based on an iterative strategy. The proposed algorithm uses the criteria of centrality and influence domain to identify this category of users and performs the identification process both at the community and network levels. The efficiency of the method has been evaluated using real databases and the results have been compared with previous works. The results demonstrate that the proposed method provides a more suitable performance in detecting the influential nodes and is superior in terms of accuracy, recall and processing time.

Can remotely sensed catchment to lake area ratios predict mercury levels in subarctic fishes?

Mercury concentrations ([Hg]) in fish reflect a complex array of interacting biogeochemical and ecological variables. In northern regions where fish are a critical subsistence food, understanding and predicting fish [Hg] can be particularly difficult, largely due to a paucity of comprehensive data associated with the logistical challenges of field sampling. Building on previous work where we elucidated causal relationships between fish [Hg] and a variety of catchment, water quality, and ecological variables in subarctic lakes, we investigated whether using only ratios of catchment area to lake area (CA:LA) can predict [Hg] in northern freshwater fish species. As CA:LA can be sensed remotely, they may be more feasible and practical to obtain than field data in far northern regions. Our study included thirteen remote lakes that represent a CA:LA gradient of 6.2-423.5 within an ∼66,000 km2 subarctic region of Northwest Territories, Canada. We found that size-standardized [Hg] in three widespread fish species, including Lake Whitefish (Coregonus clupeaformis), Walleye (Sander vitreus), and Northern Pike (Esox lucius), were significantly and positively related to CA:LA (p < 0.007, r2 = 67-80%), indicating higher fish [Hg] in smaller lakes surrounded by relatively larger catchments. Our findings provide compelling evidence that remotely sensed CA:LA can be used to predict [Hg] in northern fishes and aid in prioritizing understudied and subsistence fishing lakes of the Canadian subarctic for [Hg] monitoring programs.

Evaluation of the vaginal and urinary microbiota of healthy cycling bitches.

BACKGROUND: While the urogenital microbiota has recently been characterized in healthy male and female dogs, the influence of sex hormones on the urogenital microbiome of bitches is still unknown. A deeper understanding of the cyclic changes in urinary and vaginal microbiota would allow us to compare the bacterial populations in healthy dogs and assess the impact of the microbiome on various urogenital diseases. Therefore, the aim of this study was to characterize and compare the urogenital microbiota during different phases of the estrous cycle in healthy female dogs. DNA extraction, 16 S rDNA library preparation, sequencing and informatic analysis were performed to determine the vaginal and urinary microbiota in 10 healthy beagle dogs at each phase of the estrous cycle. RESULTS: There were no significant differences in alpha and beta diversity of the urinary microbiota across the different cycle phases. Similarly, alpha diversity, richness and evenness of vaginal bacterial populations were not significantly different across the cycle phases. However, there were significant differences in vaginal beta diversity between the different cycle phases, except for between anestrus and diestrus. CONCLUSION: This study strongly suggests that estrogen influences the abundance of the vaginal microbiota in healthy female dogs, but does not appear to affect the urinary microbiome. Furthermore, our data facilitate a deeper understanding of the native urinary and vaginal microbiota in healthy female dogs.