X. Wang

_Objective_: Genetic variation, especially polymorphism of the dopamine D4 receptor gene (DRD4), has been linked to deficits in self-regulation and executive functions and to attention deficit hyperactivity disorder (ADHD), and is related to the structural and functional integrity of the default mode network (DMN), the executive control network (ECN) and the sensorimotor network (SMN). The aim of this study was to explore the effects of the 2-repeat allele of the DRD4 gene on brain network connectivity and behaviors in children with ADHD. _Methods_: Using independent component analysis (ICA) and dimension analyses, we examined resting-state functional magnetic resonance imaging (fMRI) data obtained from 52 Asian medicine-naive children with ADHD (33 2-repeat absent and 19 2-repeat present). _Results_: We found that individuals with 2-repeat absent demonstrated increased within-network connectivity in the right precuneus of the DMN, the right middle frontal gyrus (MFG) of the SMN compared with individuals with 2-repeat present. Within the ECN, 2-repeat absent showed decreased within-network connectivity in the left inferior frontal gyrus (IFG) and the left anterior cingulate cortex. A deeper study found that connectivity strength of the left IFG was directly proportional to the Stroop reaction time in 2-repeat absent group, and as well as the right MFG in 2-repeat present group. _Conclusion_: Polymorphisms of the DRD4 gene, specifically 2-repeat allele, had effects on the ECN, the SMN and the DMN, especially in the prefrontal cortex (PFC) circles. ADHD children with DRD4 2-repeat allele have aberrant resting-state within-network connectivity patterns in the left IFG and the right MFG related to dysfunction in inattention symptom. This study provided novel insights into the neural mechanisms underlying the effects of DRD4 2-repeat allele on ADHD.

Linear regression and its variants have been widely used for classification problems. However, they usually predefine a strict binary label matrix which has no freedom to fit the samples. In addition, they cannot deal with complex real-world applications such as the case of face recognition where samples may not be linearly separable owing to varying poses, expressions, and illumination conditions. Therefore, in this paper, we propose the kernel negative ε dragging linear regression method for robust classification on noised and nonlinear data. First, a technique called negative ε dragging is introduced for relaxing class labels and is integrated into the LR model for classification to properly treat the class margin of conventional linear regressions for obtaining robust result. Then, the data is implicitly mapped into a high dimensional kernel space by using the nonlinear mapping determined by a kernel function to make the data more linearly separable. Finally, our obtained KNDLR method is able to partially alleviate the problem of overfitting and can perform classification well for noised and deformable data. Experimental results show that the KNDLR classification algorithm obtains greater generalization performance and leads to better robust classification decision.

Responding to serious environmental problems, requires urgent and fundamental shifts in our day-to-day lifestyles. This paper employs a qualitative, cross-cultural approach to explore people’s subjective self-reflections on their experiences of pro-environmental behavioral spillover in three countries; Brazil, China, and Denmark. Behavioral spillover is an appealing yet elusive phenomenon, but offers a potential way of encouraging wider, voluntary lifestyle shifts beyond the scope of single behavior change interventions. Behavioral spillover theory proposes that engaging in one pro-environmental action can catalyze the performance of others. To date, evidence for the phenomenon has been mixed, and the causal processes governing relationships between behaviors appear complex, inconsistent and only partly understood. This paper addresses a gap in the literature by investigating accounts of behavioral spillover in three diverse cultural settings using qualitative semi-structured interviews. The analysis shows that while around half of participants overall who were questioned recalled spillover effects, the other half had not consciously experienced spillover. There were few significant differences across cultures, though some forms of spillover effects were reported more in some cultures than others. More environmentally-engaged participants across all three countries were significantly more likely to experience spillover than those who were less engaged. Accounts of within-domain spillovers were most commonly reported, mainly comprising waste, resource conservation and consumption-related actions. Accounts of between-domain spillover were very rare. Recollection of contextual and interpersonal spillover effects also emerged from the interviews. Our findings suggest that more conscious behavioral spillover pathways may be limited to those with pre-existing environmental values. Behavioral spillover may comprise multiple pathways incorporating conscious and unconscious processes. We conclude that targeting behavioral catalysts that generate more socially diffuse spillover effects could offer more potential than conventional spillover involving a single individual.

Using U.S. listed firms during the period from 1971 to 2010, this paper investigates the effect of religion on corporate cost behavior. We find that religion mitigates cost stickiness induced by agency or behavioral biases of managers. This result holds for several robustness tests that address endogeneity concerns. The mitigating effect of religion on cost stickiness is through the channel of reducing top managers’ overconfidence and optimistic bias regarding future demand change and promoting managers’ adherence to fiduciary responsibilities and consideration of shareholder benefits. Further evidence shows that the reduction in cost stickiness caused by religion increases firm value. Overall, our findings suggest that religion reduces the wedge between a firm’s actual and optimal resource commitments, which helps to improve firm value and resource allocation efficiency.

Lung nodules are an early symptom of lung cancer. The earlier they are found, the more beneficial it is for treatment. However, in practice, Chinese doctors are likely to cause misdiagnosis. Therefore, deep learning is introduced, an improved target detection network is used, and public datasets are used to diagnose and identify lung nodules. This paper selects the Mask-RCNN network and uses the dense block structure of Densenet and the channel shuffle convolution method to improve the Mask-RCNN network. The experimental results prove that proposed algorithm is extremely effective.

Learner control is an important instructional design in video-based learning. This study assessed two conditions: a full learner control where learners direct their learning path, and a hybrid learner control where learners follow the instructor-set path but still enjoy certain aspects of control. Two groups of university students participated in this study by learning statistics through online video courses. The findings show that the full learner control condition attained higher learning performance than the hybrid learner control condition, but spent more time than the latter. The full learner control condition scored higher than the hybrid condition in the difficult sections of video-based learning; but no significant difference was found in the easy section. There was a significant difference between the two conditions in learning agency, but no differences in cognitive load and affective and cognitive engagement. Hierarchical regression analysis indicated differences between the full and the hybrid learner control conditions in the factors predicting overall scores. The findings carry important contributions and implications for the research and practice of instructional designs in online video-based learning such as MOOCs.

Transcranial direct current stimulation has been widely utilized in research settings and modulates brain activity. The application of anodal tDCS on the prefrontal cortex has indicated improvement in cognitive functioning. The cingulate cortex, situated in the medial aspect of the prefrontal cortex, has been identified as a core region performing cognitive functions. Most of the previous studies investigating the impact of stimulation on the prefrontal cortex stimulated the dorsolateral prefrontal cortex, however, the impact of stimulation on cingulate has not been explored. The current study investigates the effect of stimulation on the resting-state functional connectivity of the anterior cingulate cortex with other regions of the brain and changes in behavioral results in a color-word Stroop task, which has repeatedly elicited activation in different regions of the cingulate. Twenty subjects were randomly assigned to the experimental and sham group, and their medial prefrontal area was stimulated using MRI compatible tDCS. Resting-state functional magnetic resonance imaging and cognitive Stroop task were monitored before, during, and after the stimulation. Neuroimaging results indicated a significant decrease in resting-state functional connectivity in the experimental group during and after stimulation as compared to before stimulation in two clusters including right insular cortex, right central operculum cortex, right frontal operculum cortex and right planum polare with the left anterior cingulate cortex selected as the seed. The behavioral results indicated a significant decrease in reaction time following stimulation in the experimental group compared to the sham group. Moreover, the change in functional connectivity in subcortical regions with L-ACC as the seed and change in RT was positively correlated. The results demonstrated that ACC has a close functional relationship with the subcortical regions, and stimulation of ACC can modulate these connections, which subsequently improves behavioral performance, thus, providing another potential target of stimulation for cognitive enhancement.Clinical Trial Registration: ClinicalTrials.gov Identifier: NCT04318522.

Background and PurposeTranscranial direct current stimulation is an emerging non-invasive neuromodulation technique for focal epilepsy. Because epilepsy is a disease affecting the brain network, our study was aimed to evaluate and predict the treatment outcome of cathodal tDCS by analyzing the ctDCS-induced functional network alterations.MethodsEither the active 5-day, −1.0 mA, 20-min ctDCS or sham ctDCS targeting at the most active interictal epileptiform discharge regions was applied to 27 subjects suffering from focal epilepsy. The functional networks before and after ctDCS were compared employing graph theoretical analysis based on the functional magnetic resonance imaging data. A support vector machine prediction model was built to predict the treatment outcome of ctDCS using the graph theoretical measures as markers.ResultsOur results revealed that the mean clustering coefficient and the global efficiency decreased significantly, as well as the characteristic path length and the mean shortest path length at the stimulation sites in the fMRI functional networks increased significantly after ctDCS only for the patients with response to the active ctDCS. Our prediction model achieved the mean prediction accuracy of 68.3% after the nested cross validation. The mean area under the receiver operating curve was 0.75, which showed good prediction performance.ConclusionThe study demonstrated that the response to ctDCS was related to the topological alterations in the functional networks of epilepsy patients detected by fMRI. The graph theoretical measures were promising for clinical prediction of ctDCS treatment outcome.

COVID-19 has made it difficult to adopt traditional face-to-face psychological intervention under this situation because of the blocked down and social distancing, which brings big psychological crisis to the public among the global. To explore the emotional change of the public in China at the outburst of the pandemic at different phases, to establish an online working platform and create a new model of an online intervention to hold public emotions under pandemic, and test its effectiveness, so to give advisement for government emergency management system. We established an online organization to work for this program ad innovated a model of online group counseling with online emotional support accompany group right after the outburst of a pandemic. We analyzed 53 OESAGs from February 10 to April 9, including 555 application forms, 253 feedback from members, and 139 feedback from group leaders by using NVivo and SPSS to explore the evolution and characteristics of public emotion during COVID-19 and the effectiveness of OESAG. Our results showed that the emotional changes of members ranged from shock to depression to positive. The public's emotions swiftly changed from stress, anxiety, and isolation, to the hope of returning to work or finding a job during the pandemic with the help of OESAG. OESAG has effectively regulated the negative emotions of members by conducting psychological crisis intervention to provide members a space to communicate with each other, especially the female and frontline staff. Policy makers can set up an online systematic psychological crisis intervention system as soon as possible to make up for the lack of psychological assistance in the emergency management system.

“Welcome Back Tourism” is an important marketing strategy to help overseas Tourism destinations quickly recover from the crisis and enhance their core competitiveness. How to translate the memorability of tourists to revisit intention is the core key to open “Welcome Back Tourism.” This study takes local residents in Guangzhou, Shenzhen and Foshan as the research objects, and tries to explore the influence relationship between memorability of a previous travel experience, nostalgia, destination attachment and revisit intention. The results of 291 valid data showed that memorability of a previous travel experience had positive influence on revisit intention; Nostalgia has a positive effect on destination attachment. Nostalgia and destination attachment play a mediating role in the influence of memorability of a previous travel experience on revisit intention. The contributions and management Recommendations of these findings are discussed.

The purpose of this study was to understand the influence mechanism of college students’ entrepreneurial intention in view of the increasing number of college students at present to alleviate college students’ employment competition. The psychological factors that influence the entrepreneurial tendency of art graduates were analyzed and studied. First, venture capital and factors affecting entrepreneurial performance were analyzed. Second, the coefficient calculation is carried out for college students majoring in art through the regression analysis of the logistic model. Finally, a team entrepreneurial performance questionnaire was designed, and team reward levels were discussed. The results show that the logistic model can well reflect the real situation of the respondents. The significance level of the entrepreneurial team was 0.02, which was correlated. Additionally, corresponding suggestions were put forward according to the questionnaire results. Clear team goals, assignment of tasks to members, good pressure resistance, and psychological quality of members are necessary qualities for successful entrepreneurship. This conclusion provides a certain theoretical basis for the current college students’ entrepreneurial learning and a reliable inspiration for helping college students to successfully start a business.

Detecting and correcting execution errors is crucial for safe and efficient goal-directed behavior. Despite intensive investigations on error processing, the cognitive foundations of this process remain unclear. Based on the presumed relation between executive attention and error processing, we implemented a seven-day EA intervention by adopting the Posner cueing paradigm to test the potential causal link from EA to error processing in healthy adults. The experimental group was trained on the Posner cueing paradigm, with a ratio of invalid cue trials to valid cue trials of 5:1 and a corresponding ratio of 1:1 in the active control group. We found that the EA intervention improved EA across intervention sessions. Critically, after the EA intervention, the HEA group showed that post-error accuracy was restored to the same level as the post-correct accuracy. However, post-error slowing and the flanker effect were not modulated by the EA intervention. Furthermore, we observed that the changes in the accuracy of VC trials positively predicted the changes in PEA and that the two groups were classified according to the changes in PEA with a 61.3% accuracy. Based on these results, we propose that EA causally drives error processing. And the capabilities of the “actively catch” more attention resources and the automatic mismatch processing developed after EA intervention is transferable to error processing, thereby directly resulting in the gains in post-error adjustments. Our work informs the potential cognitive mechanisms underlying this causal link.

Alterations in dural venous sinus hemodynamics have recently been suggested as the major contributing factors in venous pulsatile tinnitus. Nevertheless, little is known about the association between real-time alterations in hemodynamics and the subjective perception of venous PT. This study aimed to investigate the hydroacoustic correlations among diverticular vortices, mainstream sinus flow, and PT using various Doppler ultrasound techniques. Nineteen venous PT patients with protrusive diverticulum were recruited. The mainstream sinus and diverticular hemodynamics before and after ipsilateral internal jugular vein compression were investigated using an innovative retroauricular color-coded Doppler method to examine the correlation between the disappearance of PT and hemodynamic alterations. To reveal the hydroacoustic characteristics of disparate segments of venous return, a computational fluid dynamics technique combined with the transcranial color-coded Doppler method was performed. When the ipsilateral IJV was compressed, PT disappeared, as the mean velocity of mainstream sinus flow and diverticular vortex decreased by 51.2 and 50.6%, respectively. The vortex inside the diverticulum persisted in 18 of 19 subjects. The CFD simulation showed that the flow amplitude generated inside the transverse–sigmoid sinus was segmental, and the largest flow amplitude difference was 20.5 dB. The difference in flow amplitude between the mainstream sinus flow and the diverticular flow was less than 1 dB. In conclusion, the sensation of PT is closely associated with the flow of kinetic energy rather than the formation of a vortex, whereby the amplitude of PT is correlated to the magnitude of the flow velocity and pressure gradient. Additionally, the range of velocity reduction revealed by the RCCD method may serve as a presurgical individual baseline curative marker that may potentially optimize the surgical outcomes.

With the spread of the COVID-19 pandemic worldwide, university teachers are coping with and adjusting to online teaching platforms. In this concurrent mixed-methods study, 10 science and technology universities as the research sites were first chosen, and educational planning in these sites during the pandemic was examined; then, eight selected teacher participants in these sites were interviewed to report how their beliefs and practices changed during the pandemic echoing the examined educational planning. The results show that educational planning and policies assisted teachers in accommodating the new demands and changes during the pandemic; teachers' beliefs and practices generally echoed the educational planning and policies, with certain tensions still existing. The discussion part of the study is centered around emergency remote teaching and planning, tensions between teacher beliefs and practices, and the shift from emergency remote teaching to regular, sustainable online schooling. The study provides administrators and teacher educators with insights on how emergency remote teaching can be planned and implemented during an unprecedented time.

In recent years, somatosensory interaction technology, represented by Microsoft’s Kinect hardware platform, has been widely used in various fields, such as entertainment, education, and medicine. Kinect technology can easily capture and record behavioral data, which provides new opportunities for behavioral and psychological correlation analysis research. In this paper, an automatic decision-style recognition method is proposed. Experiments involving 240 subjects were conducted to obtain face data and individual decision-making style score. The face data was obtained using the Kinect camera, and the decision-style score were obtained via a questionnaire. To realize automatic recognition of an individual decision-making style, machine learning was employed to establish the mapping relationship between the face data and a scaled evaluation of the decision-making style score. This study adopts a variety of classical machine learning algorithms, including Linear regression, Support vector machine regression, Ridge regression, and Bayesian ridge regression. The experimental results show that the linear regression model returns the best results. The correlation coefficient between the linear regression model evaluation results and the scale evaluation results was 0.6, which represents a medium and higher correlation. The results verify the feasibility of automatic decision-making style recognition method based on facial analysis.

Cognitive diversity is an important concept stemming from western management research in the 1990s. With the rapid development of science and technology, there is a growing interest in the composition of an academic research team, such as team diversity. However, there is no tool available for measuring team cognitive diversity for academic research teams. Based on Van der Vegt’s theoretical model of TCD, an Academic Research Team Cognitive Diversity Scale is developed and validated for an academic research team in our research with two studies. In Study One, in-depth interviews and panel discussions were conducted to generate a preliminary questionnaire. In Study Two, the questionnaire was administered among academic research teams. Exploratory factor analysis revealed four factors regarding cognitive diversity: the way of thinking, knowledge and skills, the view of the world, and beliefs about what is right and wrong. The factor structure was further validated by confirmatory factor analysis. Moreover, correlation and regression analyses showed that academic research TCD was positively related to team creativity and performance. To sum up, our newly developed 15-item ATCDS is sufficiently reliable and valid to be used for understanding cognitive diversity among academic research teams.

Recently, scholars have begun to shift their focus toward the idea of the marketization of startups and the relationship with entrepreneurial psychology or other factors; however, the establishment of a unified and clear standard of entrepreneurship educational methods remains unfulfilled. Our study investigates 46 representative startups in four industries, including financial technology, biotechnology, education, and cultural tourism areas in Guangdong-Hong Kong-Macao Greater Bay Area and Southeast Asia to observe factors from different backgrounds but matter in common for building entrepreneurship education systems and methods in different countries. We used the fuzzy qualitative comparison method to survey startup entrepreneurs and executives through questionnaires, selecting startup key factors including entrepreneurial psychology, product advantage, market and cultural environment, entrepreneurial policy, and geographical advantage. The survey was conducted on six key variables, namely, geographical advantage, to observe the conditional grouping and paths of factors influencing the establishment of Startups from an overall perspective. This study explores the path combination that plays a key role in the establishment of new enterprises, and further uses specific industry cases to verify the rationality and credibility of the path combination. The main conclusions are as follows: There are five combination paths affecting the establishment of new enterprises, which are “psychology and market,” “psychology, product, and region,” “psychology, culture and policy,” “psychology, market, and culture,” and “market, policy, and region” combination paths; Entrepreneur psychology, market environment, and entrepreneurship policy are the core conditions to improve the effectiveness of the establishment of new enterprises, while the other three variables are non-core variables in different paths; There are different paths of entrepreneurial paths and factor combinations in different regions or industries.

It is meaningful for a researcher to find some proper collaborators in complex academic tasks. Academic collaborator recommendation models are always based on the network embedding of academic collaborator networks. Most of them focus on the network structure, text information, and the combination of them. The latent semantic relationships exist according to the text information of nodes in the academic collaborator network. However, these relationships are often ignored, which implies the similarity of the researchers. How to capture the latent semantic relationships among researchers in the academic collaborator network is a challenge. In this paper, we propose a content-enhanced network embedding model for academic collaborator recommendation, namely, CNEacR. We build a content-enhanced academic collaborator network based on the weighted text representation of each researcher. The content-enhanced academic collaborator network contains intrinsic collaboration relationships and latent semantic relationships. Firstly, the weighted text representation of each researcher is obtained according to its text information. Secondly, a content-enhanced academic collaborator network is built via the similarity of the weighted text representation of researchers and intrinsic collaboration relationships. Thirdly, each researcher is represented as a latent vector using network representation learning. Finally, top- k similar researchers are recommended for each target researcher. Experiment results on the real-world datasets show that CNEacR achieves better performance than academic collaborator recommendation baselines.

Owing to the proliferation of rumors on social media, it is necessary to disseminate debunking information to minimize the harm caused by them. Using content analysis, sentiment analysis, and regression analysis, this study examined the mediating role of follower count in the relationship between the debunker’s identity and sharing behavior, and it explored the relationship between the text sentiment of debunking information and sharing behavior based on data on the spread of three rumors that circulated extensively on social media. Using an ordinary account as a reference, we found that the mediating or suppression effect of follower count in the relationship between debunker’s identity and sharing behavior was significant. The three test identities had more followers than the ordinary account, which resulted in a significant positive effect on the number of reposts. The debunker’s identity did not have a positive effect on the sharing of debunking information when controlling for mediating variables. Debunking information with emotional overtones was shared more widely compared with information with neutral emotions, and the dominant emotional polarity was different in the three different rumors. These findings can contribute to the generation of debunking information content, which can aid in the development of effective communication strategies and improvement in the efficiency of crisis management.

Physical contact between organelles are widespread, in part to facilitate the shuttling of protein and lipid cargoes for cellular homeostasis. How do protein‐protein and protein‐lipid interactions shape organelle subdomains that constitute contact sites? The endoplasmic reticulum (ER) forms extensive contacts with multiple organelles, including lipid droplets (LDs) that are central to cellular fat storage and mobilization. Here, we focus on ER‐LD contacts that are highlighted by the conserved protein seipin, which promotes LD biogenesis and expansion. Seipin is enriched in ER tubules that form cage‐like structures around a subset of LDs. Such enrichment is strongly dependent on polyunsaturated and cyclopropane fatty acids. Based on these findings, we speculate on molecular events that lead to the formation of seipin‐positive peri‐LD cages in which protein movement is restricted. We hypothesize that asymmetric distribution of specific phospholipids distinguishes cage membrane tubules from the bulk ER.

The rapid development of computers and technology affects modern daily life. Individuals in the digital age need to develop computational thinking skills. Existing studies have shown that programming teaching is conducive to cultivating students’ CT, and various learning models have different effects on the cultivation of CT. This study proposed a problem-oriented learning model that is closely related to programming and computational thinking. In all, 60 eighth-grade students from a middle school in China were divided into an experimental group which adopted the POL model, and a control group which adopted the lecture-and-practice learning model. The results showed that the students who were instructed using the POL model performed better than those who were instructed using the LAP model on CT concepts, CT practices, and CT perspectives. Significant differences were found for CT concepts and CT perspectives, but not for CT practices. Findings have implications for teachers who wish to apply new learning models to facilitate students’ CT skills, and the study provides a reference case for CT training and Python programming teaching.

The purpose of this study was to evaluate the international scientific output on postpartum depression research during 2000–2020 through a bibliometric analysis and to explore research hotspots, frontiers, and trends in the field of postpartum depression. We searched the Web of Science Core Collection for publications on postpartum depression published between 2000 and 2020. CiteSpace, gCluto, and other software applications were used to analyze the data by year, journal, and country. A total of 2,963 publications were retrieved and 96 countries or regions published related papers. The United States had the largest number of published papers and the highest betweenness centrality, which is the dominant position in the field of postpartum depression. A total of 717 journals published papers, with the Archives of Womens Mental Health ranked first in terms of volume and betweenness centrality. In this study, 31 high-frequency main MeSH terms/subheadings were selected. The high-frequency MeSH terms were clustered into six categories: an overview of depression-related research, diagnostic and screening scales for postpartum depression, epidemiological investigation into postpartum depression, treatment and drug selection for postpartum depression, psychological research on postpartum depression, and etiology, physiopathology, complications, genetics of postpartum depression. Finally, we used strategic diagram to analyze research trends in postpartum depression. This study has identified a continuous significant increase in the publication of PPD articles. Currently, the etiology, physiological pathology, intervention and treatment of complications on PPD are immature, which provides reference for the trend of obstetric psychology.