Bacteria have a significant impact on human production and life, endangering human life and health, so rapid detection of infectious agents is essential to improve human health. Aptamers, which are pieces of oligonucleotides (DNA or RNA) have been applied to biosensors for bacteria detection due to their high affinity, selectivity, robust chemical stability, and their compatibility with various signal amplification and signal transduction mechanisms. In this review, we summarize the different bacterial aptamers selected in recent years using SELEX technology and (...) discuss the differences in optical and electrochemical bacterial aptamer sensors. In addition the technological developments and innovations in bacterial aptamer sensor technology are introduced. Combining new materials and methods, the efficiency and stability of the sensors have also been improved. This review summarizes the progress of current bacterial aptamer sensors based on their practical application status and provides an outlook on their future development. (shrink)

Purpose As digital government initiatives advance, algorithmic technologies are increasingly integrated into public governance. However, the phenomenon of “algorithmic transference” introduces complex challenges for digital governance, including erosion of public trust, service engagement decline and broader governance doubts. Drawing on social identity theory and the concept of outgroup homogeneity bias, this study aims to examine the mechanisms underlying algorithmic transference (AT) and their implications for public administration. By synthesizing empirical evidence and existing literature, the authors develop a three-dimensional governance framework (...) – prevention, intervention and repair – aimed at reconciling technological efficiency with public trust. This study further extends the application of social psychological theory to digital government governance, highlighting the critical role of cognitive, emotional and social factors in shaping citizen responses to algorithmic systems. Design/methodology/approach The study uses a mixed-method approach. It combines theoretical analysis based on social identity theory and outgroup homogeneity bias with 13 preregistered experiments. Samples from various platforms cover different groups. Statistical methods like t-tests and structural equation models are used to explore AT. Findings The research finds that the public classifies artificial intelligence (AI) systems as outgroups and generalizes single algorithm errors. This causes trust erosion, service suppression and governance doubt. Group cognition, technical experience and human supervision play important roles and a three-dimensional governance framework is proposed. Research limitations/implications Limitations include that experimental data mainly come from American samples, and people’s perception of algorithm homogeneity may not match reality. Implications suggest the need for large-scale localization verification, exploring related factors and better understanding AI knowledge’s regulatory role in AT. Practical implications For digital government, it implies constructing interpretable algorithm governance systems, enhancing public participation and setting manual intervention thresholds. This can mitigate AT, improve public trust and optimize algorithm applications, ensuring the healthy development of digital governance. Social implications AT affects social stability, as it undermines public trust in government services and governance. By understanding and addressing it, society can avoid the decline of public service acceptance, maintain harmonious government-public relations and promote positive social development. Originality/value This study is original in using social identity theory to explain AT in digital government. It uncovers the mechanism and proposes a three-dimensional governance framework, which expands the perspective of social psychology in digital government research and offers practical guidance for governance. (shrink)

As more organizations adopt telecommuting or working from home, the work-connected behavior of their employees during non-working hours increases, weakening the boundary between work and family. However, no study has clearly identified whether and how work connectivity behavior after-hours affects employees’ work and family status. Therefore, using role theory, we explored the mechanisms by which WCBA affects employees’ thriving at work and family through work–family enrichment and work–family conflict, and compared the impact of different levels of support for family members (...) on work–family enrichment and conflict, using the Johnson–Neyman method. Our analysis of two-wave data from 257 employees led to the following findings. WCBA had a positive impact on thriving at work, but not on family. There is a ‘double-edged sword’ effect on the impact of WCBA on thriving at work, meaning that work–family enrichment can positively influence thriving at work and negatively influence work–family conflict. There is a double-edged sword effect on the impact of WCBA on thriving at family, meaning that work–family enrichment can positively influence thriving at family and negatively influence work–family conflict. The support of family members moderates the double-edged sword effect between WCBA and thriving at work, in that it can strengthen the positive effects of work–family enrichment and weaken the negative effects of work–family conflicts. Support from family members reinforces the positive impact of work–family enrichment on thriving at family. Thus our study reveals the mechanisms by which WCBA affects the thriving at work and family of employees, and identifies potential methods for managing different levels of work–family enrichment and work–family conflict from the perspective of family member support. (shrink)

ObjectiveThis study took users of short-form mobile videos as research participants to explore the role of their boredom proneness in mediating the relationship between the use of mobile social media and subjective well-being.MethodsA sample of 656 users was evaluated by the Problematic Mobile Social Media Usage Assessment Questionnaire, General Well-Being Schedule, and Boredom Proneness Scale.ResultsFirstly, significant interactions were found between monthly living expenses and the UMSM of the participants, which were recognized as factors affecting SWB. Secondly, the level of living (...) expenses had little effect on the high-level and low-level groups of the UMSM but imposed a significant impact on the medium-level group. Thirdly, the UMSM showed an influence that could positively predict boredom; both the UMSM and boredom demonstrated a negative predictive effect on SWB.ConclusionThe findings indicate that the inappropriate use of mobile social media negatively affects users’ subjective well-being; boredom partially mediated the relationship between the use of mobile social media and SWB. (shrink)

A fundamental challenge for businesses globally is how to allocate limited resources between sustainability disclosure (“talk”) and practice (“walk”). Existing research either relies on aggregated ESG scores or examines disclosure or practice in isolation, failing to capture their strategic interplay and ignoring dimension-specific differences, which creates ambiguity for practice. This study fills this gap by investigating the dimension-specific interaction between ESG disclosure and practice (conceptualized as ESG strategic positioning) and its impact on financial performance. Empirically, we first employ an ANOVA (...) to identify significant performance differences across ESG strategic positions. We then apply a fixed-effects model, controlling for firm and time heterogeneity, to robustly estimate the causal effect. Results show financial returns depend on where (E/S/G) and how (“talking” vs. “walking”) firms invest. Specifically, we find that firms benefit most “talking” on environmental issues; prioritize “talking” while being cautious with “walking” on social issues; and gain value from “walking” on governance issues. These findings offer a universal economic insight: not all ESG investments are equal. At the same time, this study provides managers and investors with a strategic lens to prioritize sustainability investments for maximum financial return. (shrink)

The Global Reporting Initiative (GRI) guidelines have emerged as an important instrument used by firms to structure the content of sustainability reporting (SR). This development has led to the question of whether the elaboration of GRI SR is beneficial to a firm’s financial performance. In this study, building on signaling theory, we carry out an empirical investigation of the impact of GRI SR on firm profitability and the factors moderating that impact. Drawing from the China Stock Market and Accounting Research (...) (CSMAR), the WIND Economic, and the Chinese Research Data Services Platform (CNRDS) databases, we identified a sample of 122 listed firms with GRI SR in China. We then employed an event study method to compare the firms following GRI SR with a set of matched firms reporting sustainability without following the GRI guidelines. The results show that GRI SR significantly increases firm profitability. Moreover, firms with local political ties reap more benefits from GRI SR, while the moderating effect of central political ties is not significant. Surprisingly, the performance impact of GRI SR is negatively correlated to the firm’s internationalization level. (shrink)

Previous studies on the effects of emotional context on memory for centrally presented neutral items have obtained inconsistent results. And in most of those studies subjects were asked to either make a connection between the item and the context at study or retrieve both the item and the context. When no response for the contexts is required, how emotional contexts influence memory for neutral items is still unclear. Thus, the present study attempted to investigate the influences of four types of (...) emotional picture contexts on recognition memory of neutral words using both behavioral and event-related potential (ERP) measurements. During study, words were superimposed centrally onto emotional contexts, and subjects were asked to just remember the words. During test, both studied and new words were presented without the emotional contexts and subjects had to make “old/new” judgments for those words. The results revealed that, compared with the neutral context, the negative contexts and positive high-arousing context impaired recognition of words. ERP results at encoding demonstrated that, compared with items presented in the neutral context, items in the positive and negative high-arousing contexts elicited more positive ERPs, which probably reflects an automatic process of attention capturing of high-arousing context as well as a conscious and effortful process of overcoming the interference of high-arousing context. During retrieval, significant FN400 old/new effects occurred in conditions of the negative low-arousing, positive, and neutral contexts but not in the negative high-arousing condition. Significant LPC old/new effects occurred in all conditions of context. However, the LPC old/new effect in the negative high-arousing condition was smaller than that in the positive high-arousing and low-arousing conditions. These results suggest that emotional context might influence both the familiarity and recollection processes. (shrink)

Background Altruism is the core of nursing professionalism. Graduate nursing education in China started late and is still developing, exploring the current state of altruistic behavior and the perceived experience of altruism among graduate nursing students may have important implications for nursing education. Objective Explore the current state of altruistic behavior and the perceived experience of altruism among graduate nursing students in China. Research design This is a descriptive phenomenological qualitative research study, semi-structured in-depth interviews were conducted. Seventeen graduate nursing (...) students from three schools were selected to participate in the study. Colaizzi’s analysis method was performed with NVivo software to develop common themes from the data. Ethical considerations The research proposal was approved by the Research Ethic Committee of Yangzhou University, China. Results Four themes emerged from the analysis of the interviews of the 17 participants: “Definition of altruism,” “Altruism in the nursing profession,” “Altruism applied in practice,” and “Factors influencing altruistic behavior.” Conclusions Although participants indicated that the concept of “altruism” was relatively new to them, altruistic behavior is common in both their work and life. Many factors influence the altruistic behavior of graduate nursing students, including the environment, personal factors, education, recipient factors, occupational factors, and gains and losses. Families, schools, and hospitals should create favorable environments to foster altruistic tendencies in students. (shrink)

This paper investigates the role of knowledge culture as both a theoretical framework and practical pathway for realizing knowledge socialism in the postdigital era. Drawing on Michael A. Peters’ conceptualization of knowledge socialism, it argues that knowledge culture—understood as socially embedded, collaborative, and open knowledge practices—provides the epistemic and ethical foundation for democratizing knowledge and resisting its commodification under cognitive capitalism. The analysis traces the theoretical genealogy of knowledge culture, examines its constitutive elements, and highlights its political and ethical implications (...) for reimagining knowledge as a public good. Empirical examples, including peer-produced platforms such as Wikipedia, Open Educational Resources, and citizen science initiatives, demonstrate how knowledge culture operationalizes the principles of openness, inclusion, and collective governance, while also revealing the structural challenges posed by digital assetization and platformization. The paper concludes by emphasizing that advancing knowledge socialism requires interdisciplinary collaboration, institutional reform, and critical consciousness to counteract the constraints of technological capitalism and build a democratic, equitable, and sustainable knowledge commons. (shrink)

In the late 20th century, with the rapid development of quantum mechanics and brain neuroscience, the study of perception theory ushered in a new opportunity. However, despite progress from various perspectives, there is still no general consensus on the nature of perception. Against this backdrop, Hoffman and his team, leveraging mathematical modeling, experimental simulations, and cutting-edge quantum mechanics, innovatively constructed the Perceptual Interface Theory with the core concepts of interface metaphor and the PDA loop. They argue for the non-reality of (...) perception, analyzing the ontological and epistemological tensions between adaptive utility and representational truth in perceptual theories. They identify a key misconception in traditional perceptual theories: the conflation of adaptation and reality. From an evolutionary epistemology standpoint, they contend that under natural selection, veridical perception of mind-independent reality is not favored and is in fact likely to be eliminated; instead, natural selection favors adaptive perception. This groundbreaking viewpoint has sparked significant debate in the academic community. This paper traces the development of perception research, elucidates the core concepts and mechanisms of Interface Theory, and synthesizes three major positive implications: offering a monistic solution to Chalmers’ “hard problem of consciousness,” bridging the explanatory gap between mind and body through ontological revision, and challenging functionalism’s reductionist assumptions. At the same time, the paper presents critiques of the theory from three dimensions: Campbell, ( 2022 ) questioning the conceptual coherence of defining perception without truth-aptness; Chalmers (Journal of Consciousness Studies 2(3): 200–219, 1995 ) interrogating the metaphysical commitments of the interface metaphor; Cohen (Psychonomic Bulletin & Review 22(6): 1519–1522, 2015 ) assessing the theory’s ability to account for intersubjective objectivity despite denying perceptual realism. By situating Hoffman’s theory within the dialectic of classical philosophy (Kant, James) and contemporary debates (naïve realism, enactivism), the paper aims to clarify its philosophical significance while highlighting unresolved challenges for epistemology and philosophy of mind. (shrink)

Artificial intelligence (AI) is transforming the global knowledge economy, creating unprecedented opportunities for innovation while simultaneously reproducing structural inequalities between the Global North and South. AI development is deeply intertwined with historical patterns of resource extraction, epistemic domination, and technological dependency, which perpetuate economic and cognitive asymmetries. This article examines how AI reinforces structural disadvantages in the Global South, focusing on three interrelated challenges: economic dependence and technological subordination, digital and infrastructural disparities, and inequitable access to knowledge resources. Drawing on (...) decolonial theory and Michael A. Peters’ framework of knowledge socialism, the study argues for reconceptualizing knowledge as a public good, emphasizing collaborative production, capacity building, and inclusive governance mechanisms. By foregrounding systemic inequities and articulating practical strategies, this paper offers a normative and operational framework to promote equitable participation in the AI-driven global knowledge economy. (shrink)

This study investigates how corporate corruption management and business ethics influence ESG reporting transparency in Asian firms, utilizing a dataset comprising 663 firms across 11 countries from 2013 to 2023. Addressing a significant research gap in emerging markets, it further examines whether business ethics moderates the relationship between corruption management and ESG disclosures. Grounded in agency, legitimacy, and signaling theories, the findings yield three core insights: (1) robust anti-corruption practices are positively linked to ESG transparency; (2) firms with strong ethical (...) orientations exhibit higher ESG disclosure levels; and (3) business ethics strengthens the positive association between corruption management and ESG transparency. Methodologically, the study adopts the difference generalized method of moments (DGMM) to address endogeneity concerns, employs alternative ESG proxies, and controls for sectoral heterogeneity, regulatory differences, and the quasi-natural shock of COVID-19. The results offer robust empirical support and yield practical insights for enhancing corporate transparency and sustainability across Asia's heterogeneous institutional landscapes. (shrink)

This study reviewed the current status of interventions for medical research integrity. The forms and methods of interventions, the timing and duration of interventions, outcome indicators, and evaluation methods and time were systematically reviewed. It provided a reference for the development of intervention programs for medical research integrity. So as to improve the integrity awareness and behavior norms of researchers. Studies related to medical research integrity and intervention measures were retrieved from databases (PubMed, Web of Science, Scopus, EBSCOhost, Sinomed, China (...) National Knowledge Infrastructure, Wangfang Data, VIP Database). The time limit for retrieval extends from the establishment of the database to June 15,2024. Two researchers independently screened and analyzed the retrieved literature, and the third researcher was asked to decide if there was any doubt. The study included 17 references from 10 countries. A systematic review of the literature found that the intervention of medical research integrity runs through all stages of school and work. There were various forms of intervention measures, including policy intervention, environmental intervention, educational intervention and software intervention. Educational intervention was the most commonly used intervention for medical research integrity. Most interventions were short-lived and lack long-term follow-up and standardized assessments. Different interventions have different characteristics and advantages in promoting the integrity of medical research. At present, there is still a lack of uniform standards and long-term evaluation mechanisms for medical research integrity. In the future, various levels and forms of intervention measures should be formulated to improve the integrity of medical research. (shrink)

Building a flexible supply chain can enable the firms to manage their supply chains to adapt effectively to dynamic market demand changes and thus guarantee their accelerated growth in the future. In this vein, this study aims to address several important issues in supply chain management by considering two characteristics of blockchain technology and exploring the specific conditions under which firms are likely to develop trust in supply chain management. Furthermore, we argue that such supply chain trust is vital to (...) the success of achieving and increasing supply chain flexibility. In addition, we propose that top management teams’ digital leadership within the firms plays a vital role in moderating the contribution of each dimension of blockchain technology to supply chain trust. Using data from a large sample of 338 firms in China, we perform structural equation modeling to examine our conceptual framework empirically. Our results highlight and support the idea that blockchain technology’s information transparency and security influence the trust-building in a supply chain and supply chain flexibility and articulate the particular importance of digital leadership in explaining the contribution of different blockchain technology characteristics to trust-building. Our study advances the theoretical, empirical, and managerial analysis of critical factors to build trust and achieve flexibility in supply chains. (shrink)

Understanding learners’ translating self-efficacy belief helps predict their ability to cope and translation performance during their career. Despite this connection, the assessment of self-efficacy during learning has been largely overlooked in translation research. The purpose of this study was to develop and validate an instrument to examine belief in self-efficacy in a sample of Chinese translation learners. Scale items were collected and refined based on an expert-panel consensus opinion. Exploratory factor analysis and confirmatory factor analysis across two independent samples revealed (...) and validated a three-dimensional structure: efficacy in internal competence, efficacy in psycho-physical competence, and efficacy in external competence. These findings provide supporting evidence for scale applications in educating translators. (shrink)

Cardiovascular disease is a major complication of type 2 diabetes mellitus. In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social (...) information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve analysis was used to evaluate the model performance. Of participants, 272 were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion. (shrink)

Researchers have conducted many studies on the relationship between external rewards and intrinsic motivation. A recent study showed that, compared with delayed rewards, rewards delivered immediately after the experiment enhanced the participants’ intrinsic motivation. However, this study did not rule out the possibility of a misattribution effect of extrinsic motivation. The present research conducted three studies to explore whether immediate rewards actually enhance intrinsic motivation. To rule out the interference of the misattribution effect of extrinsic motivation, according to the different (...) characteristics of extrinsic motivation and intrinsic motivation, Study 1 and Study 2 improved the prior experimental paradigm, and the results indicated that the intrinsic motivation of participants who received extra rewards immediately after completing experimental tasks was stronger than that of participants who received the delayed extra reward. Furthermore, to rule out the potential interference of temporal discounting, Study 3 introduced a new variable—reward magnitude. The results showed that the delivery time of the extra reward had an independent effect on intrinsic motivation and that the immediacy of the extra reward could enhance intrinsic motivation. In all, the three studies strongly demonstrated that immediate external extra rewards could truly enhance intrinsic motivation. (shrink)

In this study, we used data from the second wave of Midlife in the United States Study, MIDUS Biomarkers and MIDUS 3. We applied the serial mediation model to explore the serial mediating effects of perceived stress and depressive symptoms on the relationship between sleep quality and life satisfaction. A total of 945 participants were included in our study. The total indirect effect of sleep quality on life satisfaction through perceived stress, depressive symptoms and the combination of perceived stress and (...) depressive symptoms accounted for within the overall model was 45.5%. At the intervention level, programs designed to improve the level of life satisfaction among adults should focus on perceived stress and depressive symptoms. The prevention of perceived stress and depression contributes to improving life satisfaction and wellbeing. The serial mediation results should be confirmed by further longitudinal study. (shrink)

BackgroundBilateral cerebral palsy is the most common type of CP in children and is often accompanied by different degrees of communication impairment. Several studies have attempted to identify children at high risk for communication impairment. However, most prediction factors are qualitative and subjective and may be influenced by rater bias. Individualized objective diagnostic and/or prediction methods are still lacking, and an effective method is urgently needed to guide clinical diagnosis and treatment. The aim of this study is to develop and (...) validate an objective, individual-based model for the prediction of communication impairment in children with BCP by the time they enter school.MethodsA multicenter prospective cohort study will be conducted in four Chinese hospitals. A total of 178 children with BCP will undergo advanced brain magnetic resonance imaging at baseline. At school entry, communication performance will be assessed by a communication function classification system. Three-quarters of children with BCP will be allocated as a training cohort, whereas the remaining children will be allocated as a test cohort. Multivariate lesion- and connectome-based approaches, which have shown good predictive ability of language performance in stroke patients, will be applied to extract features from MR images for each child with BCP. Multiple machine learning models using extracted features to predict communication impairment for each child with BCP will be constructed using data from the training cohort and externally validated using data from the test cohort. Prediction accuracy across models in the test cohort will be statistically compared.DiscussionThe findings of the study may lead to the development of several translational tools that can individually predict communication impairment in children newly diagnosed with BCP to ensure that these children receive early, targeted therapeutic intervention before they begin school.Trial registrationThe study has been registered with the Chinese Clinical Trial Registry. (shrink)

Internet addiction among older adults is a new problem in many countries. However, previous studies on excessive Internet use have focused more on young people, and only few studies have focused on Internet addiction in older adults. There is a need to continue to expand research on Internet addiction in older adults. This paper aimed to fill the gap in exiting literature. We adopted a self-reported questionnaire to assess the elderly’s interaction with children, loneliness, life satisfaction and Internet addiction among (...) old adults. A total of 241 old people were obtained from data collection in China via online survey with the help of a professional research company. We used OLS regression analysis and bootstrap method to test the hypothesis. The results of the empirical analysis indicated that interaction with children was significantly negatively associated with the Internet addiction of old people; loneliness mediated the relationship between interaction with children and old adults’ Internet addiction; and life satisfaction moderated the effect of interaction with children, and the indirect effect between interaction with children and old adults’ addiction via loneliness was stronger for those with low life satisfaction. Finally, we discussed the theoretical significance, practical implications, limitation of this research. Interventions to improve family function systems especially for older people with low life satisfaction can help prevent the development of Internet addiction. (shrink)

Interactions of entrepreneurs through social networks provide an available path for corporate risk contagions. However, the issue how entrepreneurs’ social networks influence on corporate risk contagion is still received limited attention from scholars. In this study, a framework is proposed to describe entrepreneurs’ interaction and corporate value creation. The main results of multiagent simulations indicate the following. First, either weak ties or strong connections of social networks can enhance density of corporate risk contagion. However, only strong connections can be moderated (...) by entrepreneurs’ risk preference. Second, weak ties improve risk exposure of individual corporations, while strong connections may probably decrease systematical risk of the market. Third, weak ties are important for mature corporations to achieve business success. However, for startups, strong connections are more valuable to maintain. The findings of this study not only provide theoretical support from some widely accepted economic phenomenon but also provide explanations for conflicting results from some previous literatures. (shrink)

Previous studies have explored the impact of the cost ratio of individual solutions versus collective solutions on people’s cooperation tendency in the presence of individual solutions. This study further explored the impact of team credibility on people’s propensity to cooperate in the presence of individual solutions. Study 1 investigated the influence of different level of altruistic tendencies or the self-interest tendencies of teammates on participants’ decision-making. Study 2 explored the influence of the distribution of altruistic tendencies or self-interest tendencies on (...) participants’ decision-making. The results of Study 1 showed that the proportion of participants who chose the collective solution increased with an increase in the altruistic tendencies of the team. When the altruistic tendencies of the teammates reached a certain value, the proportion of participants taking the collective solution showed a trend to stabilize. Furthermore, the proportion of participants who chose the individual solution increased with the increase in the self-interest tendencies of the team. When the self-interest tendencies of the teammates reached a certain value, the individual solution was stably adopted. The results of Study 2 showed that with the total altruistic tendency remaining unchanged, the more altruistic group members that altruistic tendencies were allocated to, the higher a participant’s level of trust in the team would be, which showed the decentralized effect of altruistic tendencies. In the case that the total self-interest tendency was unchanged, the fewer self-interest group members the self-interest tendencies were allocated to, the higher a participant’s level of trust in the team would be, which showed the convergent effect of self-interest tendencies. (shrink)

Transformational leadership has been becoming increasingly vital to the provision of high-quality health care, particularly during major public health emergencies. The present study aims to investigate the impact of transformational leadership on physicians’ performance and explore the cross-level underlying mechanisms with achievement motivations and coping styles among Chinese physicians. During 2017–2019, 1,527 physicians of 101 departments were recruited from six hospitals in China with a cluster random sampling method. Participants completed several questionnaires regarding their job performance, achievement motivations, coping styles, (...) and transformational leadership. Multilevel mediation effects were tested using cross-level path analysis. The result of this study indicated that transformational leadership was applied well in Chinese medical settings with a score of 101.56 ± 6.42. The hierarchical linear model showed that transformational leadership had a cross-level direct positive effect on physicians’ performance. Furthermore, results of cross-level path analyses revealed that transformational leadership contributed to physicians’ performance by sequentially influencing achievement motivations first and then coping styles. In addition, the path “transformational leadership → positive coping style → physicians’ performance” showed the strongest cross-level indirect effect. In summary, public health leaders should enhance physicians’ performance by promoting individual development, especially achievement motivation and PC style. (shrink)

Positioning accuracy of micropositioning stage in scanning ion conductance microscopy is the key to obtain high-precision scanning model. Most piezoelectric ceramic micromotion platforms are used for that, and hysteresis characteristics are the main reason for the nonlinear characteristics of piezoelectric ceramics and the influence on the control accuracy. In order to solve this problem, backpropagation algorithm based on whale optimization algorithm is used to model the hysteresis, which is directly used as a feedforward controller to compensate the hysteresis effect, and (...) the robust adaptive moving average control method is used for feedback control. The results show that the hysteresis model of backpropagation algorithm based on the whale optimization algorithm can fit the hysteresis curve well, and the maximum fitting error is 0.2050 μm, only 0.256%. By adopting feedforward and feedback, feedforward robust adaptive moving average control algorithm decreases the hysteresis from 17.64% to 2.51%, which enables the output of the piezoelectric ceramic controller to track the expected displacement well and makes it possible to improve the scanning accuracy. (shrink)

Emotion recognition plays an important role in children’s socio-emotional development. Research on children’s emotion recognition has heavily relied on stimulus sets of photos of adults posed stereotyped facial configurations. The Child Affective Facial Expression set is a relatively new stimulus set that provides researchers with photographs of a diverse group of children’s facial configurations in seven emotional categories—angry, sad, happy, fearful, disgusted, surprised, and neutral. However, the large size of the full CAFE set makes it less ideal for research in (...) children. Here, we introduce two subsets of CAFE with 140 photographs of children’s facial configurations in each set, diverse in the race and ethnicity of the models, and designed to produce variability in naïve observers. The subsets have been validated with 1000 adult participants. (shrink)

Riben Jiuzhou da xue tu shu guan cang you gu xie Huizhou ben "Zhuzi yu lei" yi bai si shi juan. Huizhou ben shang cheng "Chi lu", xia qi li bian, zai yu lu dao yu lei de xing cheng guo cheng zhong chu yu guan jian de di wei, dui xue jie yan jiu zhu xi si xiang de xing cheng guo cheng, Zhu Xi men ren de qing kuang, jin ben "Zhuzi yu lei" de xing cheng guo cheng (...) yi ji zhong gu shi qi gu Han yu bai hua, ti gong le xin de cai liao he xin de shi ye. (shrink)

Since the opening of the economy, China’s regional economy has developed rapidly, the overall national strength has been increasing, and the people’s living standards have been continuously improved. The issue of coordinated regional development has become an important issue in today’s society. Genetic algorithm is a kind of prediction algorithm that has developed rapidly in recent years and is widely used. However, when solving engineering prediction problems, there are often problems such as premature convergence and easiness to fall into local (...) optimal solutions. Therefore, on the basis of studying the related theories of genetic algorithm and artificial immune algorithm, this paper uses the advantages of the two algorithms, combines the two algorithms, and proposes an improved algorithm for genetic algorithm-adaptive immune genetic algorithm. Taking genetic algorithm as the basic framework, the operators and selection methods of artificial immune algorithm are integrated. Using the adaptive concept, the formulas of adaptive crossover probability and mutation probability are innovatively designed. Compared with the fixed value of the immune genetic algorithm, the introduction of the adaptive concept can intelligently adjust the optimization process and increase the optimization speed. Considering the double uncertain factors of product market demand and waste product recycling in the remanufacturing supply chain system, the maximization of logistics network operating profit, the minimization of environmental impact, and the maximization of customer satisfaction are the forecast goals. The market demand of uncertain products is effectively controlled through the option contract mechanism, and a multiobjective forecasting model based on the option contract mechanism is established. According to the characteristics of the model, an improved immune genetic algorithm is designed to solve the problem, and the effectiveness of the immune genetic algorithm is verified through an example. (shrink)

Objective: The objective of our current research is to compare the different psychological interventions and distinguish the most effective way to treat psychological crisis according to different clinical manifestations in people affected by coronavirus disease 2019. No previous systematic review has provided a comprehensive overview by performing a Bayesian network meta-analysis of this current topic.Method: A systematic review and a Bayesian network meta-analysis were conducted on randomized controlled trials, non-RCTs, case–control studies, self-controlled case series, cohort studies, and cross-sectional studies of (...) all the available interventions for psychological crisis in people affected by COVID-19. We searched the electronic databases EMBASE, PubMed, Web of Science, PsycINFO, and Cochrane Library, as well as the Chinese databases such as Sinomed, Chinese Biomedicine Literature, Chinese Scientific Journal Database, WanFang Database, and China National Knowledge Infrastructure, from 2019 to April 30, 2020. The main outcomes were self-rating anxiety scale, self-rating depression scale, patient health questionnaire, and symptom checklist. The study is registered with Inplasy, number 202050076.Result: Sixteen self-controlled case series comprising 1,147 participants compared five different psychological interventions with four different measurement scales were included in this study. For effectiveness, all the psychological therapies were significantly more effective than before intervention. Our results showed that supportive therapy, which is adjusted to the COVID-19-related mental crisis, is the best treatment compared with behavioral therapy, nursing-based psychological therapy, traditional Chinese medicine therapy, and COVID-19-related standard training at reducing the anxiety-related symptoms assessed by SAS. When measured by SDS, BT was better than ST and NBPT treatment for reducing the depression symptoms. And ST was better than BT and ST+BT as assessed by PHQ-9. In the end, the last network meta-analysis indicated that NBPT was more effective than ST by the measurement of SCL-90.Conclusion: Our research suggested the potential effectiveness of psychological interventions for decreasing psychological crisis in people affected by COVID-19 and try to introduce the best effective treatment options for clinical practice according to the clinical manifestations of psychological problems, but further confirmation from high-quality RCTs is needed. (shrink)

The deterministic economic system will also produce chaotic dynamic behaviour, so economic chaos is getting more and more attention, and the research of economic chaos forecasting methods has become an important topic at present. The traditional economic chaos forecasting models are mostly based on large samples, but in actual production activities, there are a large number of small-sample economic chaos problems, and there is still no effective solution. This paper proposes a combined forecasting model based on the traditional economic chaos (...) forecasting method. First of all, through the decision tree classification, priority selection of features, rough prediction is achieved. Secondly, we use BP neural network to make secondary prediction. Because the initial weight is randomly selected, it is easy to fall into the defect of local minimum. This paper optimizes the BP neural network. Finally, the decision tree model and the BP neural network model optimized by the improved genetic algorithm are combined, and the combined model is optimized by the improved GA. This method can take advantage of many prediction models and combine the prediction information of multiple different prediction models to effectively improve the fitting ability of the model and improve the prediction accuracy. (shrink)

Social behavior is closely linked to self-efficacy, which is the individual’s confidence or belief that they can successfully complete a task in a given situation. The advent of social media classified social behavior as online and offline sociality, and has cultivated inconsistency in online and offline social behavior of university students, an issue that has come to prominence in scholarly research. However, the relationship between this inconsistency and self-efficacy is worthy of investigation because this particular confluence of behavioral concepts has (...) been rarely been researched. In this paper, online and offline social behavior is integrated, a typology for university student social activities established, and the correlation between different types of social activity and student self-efficacy investigated, with a specific focus on those with notable inconsistencies in their social performance. The following findings are reported. First, as online social networking has become the dominant form of social interaction, the types of social activity have increased, with one-third of university students showing inconsistent online and offline social behavior. However, different types of social activities have varied effects on the self-efficacy of university students, with differences between general self-efficacy, which is significantly above academic self-efficacy, and social self-efficacy. These effects are also different for students with inconsistent online and offline social performance; those who are active online show higher self-efficacy than those who are active offline. This study shows online social network interactions to be more closely related to student self-efficacy than offline interactions. (shrink)

Based on applied linguistics, this study looked at the decision support system for emphasizing self-assurance in academic writing. From a generic perspective, academic writing has been considered both a process and a product. It has highlighted the planning composite processes, editing, composing, revising, and assessment, which depend upon the familiarity of someone with confidence in their capability for engagement in these activities. As a product, it has focused on the writing results through the product’s characteristics. These contain specific content areas (...) in acceptable depth and well-structured technical vocabulary. Higher education aims to support students in optimizing their potential for achieving satisfactory outcomes. For example, the assessment of grades involves academic writing, contributing to the degree course classification. Students have differences in many respects, such as expectations, background knowledge, and study and learning approaches. There were varying students’ beliefs about what academic writing is for evaluation. Modern-day motivations and theories highlight the significance of students’ confidence in their studies. The role of high confidence can support students to apply more effort toward setting challenging goals. Students may find it more difficult to succeed in higher education if they lack confidence in their academic writing abilities. A DSS has many applications in diverse areas and can play a significant role in the ranking and prioritization process. The current study has considered the DSS for prioritizing self-assurance in academic writing based on applied linguistics. Various criteria were considered for the evaluation of the research. The Super Decision software was used for the experimental process of the proposed research. The results of the study show the effectiveness of the proposed research. (shrink)