Responsible risk management is central to banking ethics. With the 1999 publication of the Basel Committee's proposal, Basel II, for a New Capital Accord to replace the 1988 agreement, Basel I, an attempt has been made to address the problem of correlating banks' risk management with their capital requirements. The Basel II framework, finalised in June 2004, is designed to improve risk management by using models based on past performance to help set the amount of capital banks are required to (...) hold by regulators, with the purpose of improving the efficiency of capital allocation. The objectives of this study are to investigate how banks generally, but particularly those located in China, could improve their risk management systems and what the implications of these new regulations are for them. Three relevant propositions were formulated, namely, Basel II will improve risk management; Basel II will improve capital allocation efficiency; and compliance with advanced risk management systems is biased in favour of the large banks. Evidence was assembled with which to evaluate these three propositions by gathering relevant primary data by means of a representative survey of Chinese banking executives involved in risk management. The findings strongly support the first two of the above propositions and partly support the third proposition. (shrink)

The uncovering of several recent corporate scandals has brought to light unethical pro-organizational behavior (UPB) in organizations. A growing body of research has provided insights into employees’ UPB and its antecedents. However, our understanding of leader UPB and its effects remains limited. In this study, we develop and test a theoretical model that explains employees’ responses to their leader UPB. By drawing on the theory of motivated reasoning and the trust literature, we posit that, in general, leader UPB is linked (...) to unfavorable responses from employees such as a lower perception of leaders’ trustworthiness, which, in turn, reduces the citizenship behaviors of employees. However, our model also shows that these effects do not emerge automatically but depend on a crucial boundary condition—followers’ outcome favorability, or the extent to which followers personally benefit from leader UPB. Specifically, we contend that negative responses to leader UPB arise mainly when followers’ outcome favorability is low but decrease significantly when followers’ outcome favorability is high. The results of two multi-wave, multi-source field studies support our hypothesized model. These findings offer a new, instrumental perspective on followers’ responses to unethical leader behaviors, with valuable theoretical and practical implications. (shrink)

The current research aims to prove the impact of resilience on sleep quality and to investigate the mediating function of perceived stress in the paths from resilience to sleep quality among disabled Chinese elders. The participants were 196 elders with visual and physical disability who resided in the nursing houses in Shanghai, including 102 males and 94 females whose mean age was 74.5 years old. All the elders were measured with the 10-item Connor-Davidson Resilience Scale, Pittsburgh Sleep Quality Index, and (...) Perceived Stress Scale. The results showed that all the demographic variables were significantly related to perceived stress and PSQI scores. High levels of resilience could significantly enhance the quality of sleep in disabled Chinese elders. In addition, the two-step mediation models also confirmed the impact of resilience on sleep quality as mediated through perceived stress in this special aged population. Better knowledge on the mechanisms of sleep quality among older adults could benefit the prevention and treatment of some geriatric diseases. (shrink)

Introduction: Few studies are available on the prevalence and sleep-related factors of dementia with Lewy bodies (DLB) in Chinese older adults, aiming to explore the associations between sleep characteristics and DLB.Methods: A cross-sectional study with 7,528 individuals aged ≥65 years in 106 communities in Northern China was conducted from April 2019 to January 2020. Questionaries (including demographic characteristics, comorbidities, lifestyles, and sleep characteristics) were administered, and neuropsychological assessments and physical examination were conducted in phase I; screening for probable DLB was (...) done in phase II. Logistic regressions were used to assess associations.Results: A total of 919 (12.2%, 919/7,528) participants had dementia, and 101 (1.3%, 101/7,528) participants were diagnosed with DLB. The prevalence of dementia and DLB were slightly higher or equal in women, increased with age, and roughly decreased with nighttime sleep duration. Of the 101 participants, all of them (100.0%) had cognitive impairment, 46 (44.54%) displayed fluctuating cognition, 72 (71.29%) of them showed visual hallucination, 22 (21.78%) individuals reported RBD, and 27.71% showed Parkinsonism. Sleeping for 8 h had combined diagnostic value for DLB (AUC = 0.783, 95%CI: 0.734–0.831, p < 0.001).Conclusions: The current prevalence of DLB is 1.3% in Northern China. Short or long nighttime sleep duration is independently associated with the occurrence of dementia and DLB. (shrink)

In recent years, precise high flow oxygen therapy as a new type of oxygen therapy machine has gradually attracted people’s attention and has been widely used in hospital emergency and clinical treatment of respiratory diseases; especially in recent years, severe coronavirus disease has played an important role in the treatment of patients. This paper presents a new type of precise high flow oxygen therapy machine with electromagnetic pneumatic flow valve as the core control element. A sliding mode control strategy based (...) on the system is proposed to realize the accurate control of oxygen concentration and output flow of oxygen therapy mixture. The physical equipment of the precision high flow system is established, and its working performance is verified through the test platform. The optimization design goal of the precision high flow equipment is achieved. (shrink)

The vigorous development of online education has produced massive amounts of education data. How to mine and analyze education big data has become an urgent problem in the field of education and big data knowledge engineering. As for the dynamic learning data, knowledge tracing aims to track learners’ knowledge status over time by analyzing the learners’ exercise data, so as to predict their performance in the next time step. Deep learning knowledge tracking performs well, but they mainly model the knowledge (...) components while ignoring the personalized information of questions and learners, and provide limited interpretability in the interaction between learners’ knowledge status and questions. A context-aware attentive knowledge query network model is proposed in this paper, which combines flexible neural network models with interpretable model components inspired by psychometric theory. We use the Rasch model to regularize the embedding of questions and learners’ interaction tuples, and obtain personalized representations from them. In addition, the long-term short-term memory network and monotonic attention mechanism are used to mine the contextual information of learner interaction sequences and question sequences. It can not only retain the ability to model sequences, but also use the monotonic attention mechanism with exponential decay term to extract the hidden forgetting behavior and other characteristics of learners in the learning process. Finally, the vector dot product is used to simulate the interaction between the learners’ knowledge state and questions to improve the interpretability. A series of experimental results on 4 real-world online learning datasets show that CAKQN has the best performance, and its AUC value is improved by an average of 2.945% compared with the existing optimal model. Furthermore, the CAKQN proposed in this paper can not only track learners’ knowledge status like other models but also model learners’ forgetting behavior. In the future, our research will have high application value in the realization of personalized learning strategies, teaching interventions, and resource recommendations for intelligent online education platforms. (shrink)

With the development of deep neural networks, automatic music composition has made great progress. Although emotional music can evoke listeners' different auditory perceptions, only few research studies have focused on generating emotional music. This paper presents EmotionBox -a music-element-driven emotional music generator based on music psychology that is capable of composing music given a specific emotion, while this model does not require a music dataset labeled with emotions as previous methods. In this work, pitch histogram and note density are extracted (...) as features that represent mode and tempo, respectively, to control music emotions. The specific emotions are mapped from these features through Russell's psychology model. The subjective listening tests show that the Emotionbox has a competitive performance in generating different emotional music and significantly better performance in generating music with low arousal emotions, especially peaceful emotion, compared with the emotion-label-based method. (shrink)

Emotion recognition plays an important part in human-computer interaction. Currently, the main challenge in electroencephalogram -based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through (...) TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness, anger, and fear on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness, anger, and fear on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition. (shrink)

In this study, we aimed to address three comments proposed by Ogihara on a recent study where we found that unique names in China have become increasingly popular from 1950 to 2009. Using a large representative sample of Chinese names, we replicated the increase in uniqueness of Chinese names from 1920 to 2005, especially since the 1970s, with multiple uniqueness indices based on name-character frequency and name-length deviation. Over the years, Chinese characters that are rare in daily life or naming (...) practice were more often used in given names, and the length of given names became more deviant from typical practice. Taken together, these findings not only reconfirmed the increasing prevalence of unique names but also demonstrated the validity of various indices in assessing name uniqueness in China. (shrink)

Background and ObjectivesAnxiety plays an important role in psychology. An exploration of anxiety and its associated reactions may provide insight into measures for addressing mental health problems caused by the coronavirus disease 2019 pandemic. Data from this study provide potential correlational responses to anxiety.MethodsA cross-sectional study using data collected via an online self-reported questionnaire was conducted in Japan during the COVID-19 pandemic. Using the State-Trait Anxiety Inventory, we assessed anxiety levels and explored the relationship between anxiety STAI-6 score, sources of (...) COVID-19 information, the influences of COVID-19, social anxiety symptoms, discrimination, and evaluation of the government.ResultsA total of 4,127 participants were included in the analysis. The level of anxiety was not equally distributed across the general population with respect to age, gender, educational level, occupation, income, presence of underlying disease, and location. The number of sources of information on COVID-19 had a positive correlation with the STAI-6 score. The influence of the pandemic was correlated with moderate–severe anxiety. A high level of anxiety added to social anxiety and discriminatory behavior. Being female and from a non-emergency area was related to higher STAI scores, and higher education, and income decreased the STAI score. The respondents who had a lower evaluative score of the preventive activities undertaken by the national and local governments had higher STAI-6 scores.ConclusionOur findings provide statistical evidence for the associated reaction of anxiety and that anxiety reactions may vary in predictable ways. Further studies should focus on the strategic interventions that may decrease the associated responses to anxiety, to address mental health issues due to the pandemic. (shrink)

This study investigated the mediating roles of self-acceptance and self-esteem in the relationship between body image dissatisfaction and impulse buying, and tested the moderating effect of gender on the relationships. A sample of 374 college students and graduate students participated in the study. Results revealed that body image dissatisfaction positively associated with impulse buying; self-esteem plays a mediating role between body image dissatisfaction and impulsive buying; a serial indirect pathway emerged; the mediation path from self-acceptance to self-esteem was stronger for (...) female than that from male. The results underscore the importance of identifying the mechanisms that moderate the mediated path between body image dissatisfaction and impulse buying among students. These findings point to the potential implications about how to reduce impulse buying through improving body image satisfaction. (shrink)

Buddhisms and Deconstructions considers the connection between Buddhism and Derridean deconstruction, focusing on the work of Robert Magliola. Fourteen distinguished contributors discuss deconstruction and various Buddhisms—Indian, Tibetan, and Chinese —followed by an afterword in which Magliola responds directly to his critics.

Nowadays, depression is the world’s major health concern and economic burden worldwide. However, due to the limitations of current methods for depression diagnosis, a pervasive and objective approach is essential. In the present study, a psychophysiological database, containing 213 subjects, was constructed. The electroencephalogram signals of all participants under resting state and sound stimulation were collected using a pervasive prefrontal-lobe three-electrode EEG system at Fp1, Fp2, and Fpz electrode sites. After denoising using the Finite Impulse Response filter combining the Kalman (...) derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. Then, the minimal-redundancy-maximal-relevance feature selection technique reduced the dimensionality of the feature space. Four classification methods distinguished the depressed participants from normal controls. The classifiers’ performances were evaluated using 10-fold cross-validation. The results showed thatK-Nearest Neighbor had the highest accuracy of 79.27%. The result also suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression. This study proves the feasibility of a pervasive three-electrode EEG acquisition system for depression diagnosis. (shrink)

Evidence suggests that perceived school culture is the most powerful predictor of teachers’ work performance. However, studies to date have paid little attention to the potential mechanisms behind this association. On the basis of the job demands–resources model, the present study explored the mediating role of affective empathy and the moderating role of job tenure in the association between perceived school culture and teachers’ work engagement. 647 primary and secondary school teachers completed questionnaires measuring perceived school culture, affective empathy, and (...) work engagement. After gender and educational level were included as covariates, the results showed that perceived school culture positively correlated with teachers’ work engagement, and more importantly, this association was partially mediated by affective empathy. In addition, job tenure significantly moderated the direct association between perceived school culture and work engagement. Specifically, there was a stronger association between perceived school culture and work engagement for teachers with shorter job tenure than those with longer job tenure. The findings suggested the direct effect of perceived school culture on work engagement, and the indirect effect of perceived school culture on work engagement through the mediating role of affective empathy. These findings enrich our understanding of how perceived school culture associates with work engagement, and highlight the moderating role of job tenure in the direct association between perceived school culture and work engagement. (shrink)

The brain-computer interface based on functional near-infrared spectroscopy has received more and more attention due to its vast application potential in emotion recognition. However, the relatively insufficient investigation of the feature extraction algorithms limits its use in practice. In this article, to improve the performance of fNIRS-based BCI, we proposed a method named R-CSP-E, which introduces EEG signals when computing fNIRS signals’ features based on transfer learning and ensemble learning theory. In detail, we used the Independent Component Analysis algorithm for (...) the correspondence between the sources of the two signals. We then introduced the EEG signals when computing the spatial filter based on a modified Common Spatial Pattern algorithm. Experimental results on public datasets show that the proposed method in this paper outperforms traditional methods without transfer. In general, the mean classification accuracy can be increased by up to 5%. To our knowledge, it is an innovation that we tried to apply transfer learning between EEG and fNIRS. Our study’s findings not only prove the potential of the transfer learning algorithm in cross-model brain-computer interface, but also offer a new and innovative perspective to research the hybrid brain-computer interface. (shrink)

Point-of-interest recommendations are a popular form of personalized service in which users share their POI location and related content with their contacts in location-based social networks. The similarity and relatedness between users of the same POI type are frequently used for trajectory retrieval, but most of the existing works rely on the explicit characteristics from all users’ check-in records without considering individual activities. We propose a POI recommendation method that attempts to optimally recommend POI types to serve multiple users. The (...) proposed method aims to predict destination POIs of a user and search for similar users of the same regions of interest, thus optimizing the user acceptance rate for each recommendation. The proposed method also employs the variable-order Markov model to determine the distribution of a user’s POIs based on his or her travel histories in LBSNs. To further enhance the user’s experience, we also apply linear discriminant analysis to cluster the topics related to “Travel” and connect to users with social links or similar interests. The probability of POIs based on users’ historical trip data and interests in the same topics can be calculated. The system then provides a list of the recommended destination POIs ranked by their probabilities. We demonstrate that our work outperforms collaborative-filtering-based and other methods using two real-world datasets from New York City. Experimental results show that the proposed method is better than other models in terms of both accuracy and recall. The proposed POI recommendation algorithms can be deployed in certain online transportation systems and can serve over 100,000 users. (shrink)

In the recent years, gesture recognition based on the surface electromyography (sEMG) signals has been extensively studied. However, the accuracy and stability of gesture recognition through traditional machine learning algorithms are still insufficient to some actual application scenarios. To enhance this situation, this paper proposed a method combining feature selection and ensemble extreme learning machine (EELM) to improve the recognition performance based on sEMG signals. First, the input sEMG signals are preprocessed and 16 features are then extracted from each channel. (...) Next, features that mostly contribute to the gesture recognition are selected from the extracted features using the recursive feature elimination (RFE) algorithm. Then, several independent ELM base classifiers are established using the selected features. Finally, the recognition results are determined by integrating the results obtained by ELM base classifiers using the majority voting method. The Ninapro DB5 dataset containing 52 different hand movements captured from 10 able-bodied subjects was used to evaluate the performance of the proposed method. The results showed that the proposed method could perform the best (overall average accuracy 77.9%) compared with decision tree (DT), ELM, and random forest (RF) methods. (shrink)

Stressful life events and subjective well-being are negatively related, but there is little research in the current literature exploring the mediating and moderating mechanisms underlying this association, especially for female adolescents in vocational schools who are subjected to undesirable life events. In the present study, we examined the mediating role of depression in the association between stressful life events and female adolescents’ subjective well-being, as well as the moderating role of perceived social support in the direct and indirect relations involved. (...) The participants were 1,096 vocational school female adolescents, who completed the questionnaires regarding stressful life events, subjective well-being, depression, and perceived social support. The results showed that depression partially mediated the relation between stressful life events and subjective well-being. Importantly, perceived social support moderated the direct link between stressful life events and subjective well-being, and the indirect link between stressful life events and depression, but not the indirect link between depression and subjective well-being. Especially, female adolescents high in perceived social support displayed higher levels of subjective well-being and lower levels of depression in facing with stressful life events than those low in perceived social support. These findings highlight the mechanisms underlying the relationship between stressful life events and subjective well-being in vocational school female adolescents. (shrink)

Previous studies have demonstrated that orientation-specific deprivation in early life can lead to neural deficits of spatial vision in certain space, and can even result in meridional amblyopia. Individuals with astigmatism are the optimal and natural models for exploring this asymmetric development of spatial vision in the human visual system. This study aims to assess the contrast sensitivity function and EEG signals along two principal meridians in participants with regular astigmatism when being optimal optical corrected. Twelve participants with astigmatism and (...) thirteen participants with were recruited in the current study. CSFs and spatial sweep visual evoked potentials were measured with vertical and horizontal sinewave gratings along two principal meridians monocularly. Area under log CSF, spatial frequency threshold corresponding to 80% contrast gratings, and CSF acuity were calculated from CSF test. In addition, sVEP amplitudes and thresholds were calculated with the recursive least square method. Participants with astigmatism exhibited marked vertical-horizontal resolution disparities even after they were corrected with optimal optical corrections. CSF tests showed that AULCSF along weak meridian was lower than that along strong meridian in both groups. Significant meridional disparity of CSF acuity was also found in both groups. In addition, the MA group showed larger meridional disparity compared to the AST group. Spatial sVEP thresholds also supported the existence of marked meridional disparity. Our results suggest that meridian-specific partial deprivation in early life might lead to monocularly asymmetric development of spatial vision in the human visual system. In terms of application, we tested the feasibility and reliability of adopting psychophysical and EEG scalings to investigate the asymmetric development of spatial vision related to astigmatism. These paradigms are potentially applicable to reduce and even eliminate the meridional disparity in the primary visual cortex by adopting perceptual learning or other vision-related interventions. (shrink)

Improvements of the happiness of the rural population are an essential sign of the effectiveness of relative poverty governance. In the context of today’s digital economy, assessing the relationship between digital literacy and the subjective happiness of rural low-income groups is of great practicality. Based on data from China Family Panel Studies, the effect of digital literacy on the subjective well-being of rural low-income groups was empirically tested. A significant happiness effect of digital literacy on rural low-income groups was found. (...) Digital literacy promotes the subjective happiness of rural low-income groups through income increase and consumption growth effects. The observed happiness effect is heterogeneous among different characteristic groups, and digital literacy significantly positively impacts the subjective happiness of rural low-income groups. Decomposition of subjective happiness into life satisfaction and job satisfaction shows that digital literacy significantly positively affects the job and life satisfaction of rural low-income groups. This paper demonstrates that digital literacy induces a practical happiness effect. To further strengthen the subjective welfare effect of digital literacy in the construction of digital villages, the government should focus on cultivating digital literacy among low-income groups from the demand side. The construction of digital infrastructure should be actively promoted from the supply side. (shrink)

Saethre‐Chotzen syndrome (SCS), a human autosomal dominant condition with limb defects and craniosynostosis, is caused by haploinsufficiency of TWIST1, a basic helix–loop–helix (bHLH) transcription factor. Until recently, the molecular pathogenesis of the limb defects in SCS has not been well understood. Now, Firulli et al.1 show in mouse and chick that ectopic expression of a related bHLH protein, Hand2, results in phenocopies of the limb defects caused by Twist1 loss‐of‐function mutations. These two proteins interact in a dosage‐dependent antagonistic manner, and (...) both can be regulated through phosphorylation at conserved helix I amino acid residues. These findings provide an important link between the misregulation of Twist1 dimerization and the limb phenotypes observed in SCS. BioEssays 27:1102–1106, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

BackgroundAging and type 2 diabetes mellitus are important risk factors for the development of cognitive deterioration and dementia. The objective of this research was to investigate the effects of an exercise intervention on cognitive function in older T2DM patients.MethodsEight literature databases were searched from inception to 20 January 2022. The researchers examined randomized controlled trials that evaluated the impact of exercise on the cognitive performance of older T2DM patients. The Cochrane risk-of-bias tool for RCTs was used to assess each study. (...) The quality of evidence was assessed using the GRADE approach. The mini-mental state examination, Modified MMSE, and Montreal cognitive assessment were used to evaluate the cognitive outcomes. We performed a subgroup analysis with stratification according to exercise intervention modality, duration, and cognitive impairment.ResultsFive trials were eligible, with a total of 738 T2DM patients. The combined findings revealed that exercise improved global cognitive function significantly. In the studies that were included, no relevant adverse events were reported.ConclusionExercise is beneficial in improving global cognitive function in older adults with T2DM. Studies with bigger sample sizes and higher quality are additionally expected to draw more definite conclusions.Systematic Review Registration[https://www.crd.york.ac.uk/PROSPERO/#recordDetails], identifier [CRD42022296049]. (shrink)

Epidemiological studies have confirmed that long-term exposure to road traffic noise can cause cardiovascular diseases, and when noise exposure reaches a certain level, the risk of related CDs significantly increases. Currently, a large number of Chinese residents are exposed to high noise exposure, which could greatly increase the risk of cardiovascular disease. On the other hand, relevant studies have found that people with high noise sensitivity are more susceptible to noise. And it is necessary to pay more attention to the (...) high noise-sensitive people. This study investigated the acute physiological effect of different noise-sensitive groups by indoor-level noise stimulus experiments under laboratory conditions, by observing heart rate variability indicators, including standard deviation of NN intervals, low frequency/high frequency, and heart rate. The results showed that there was no significant difference in HRV between the high-sensitive group and the low-sensitive group at the physiological baseline and the different stimulating noise levels. Then, based on the theory of cumulative effect of noise proposed by WHO Regional Office for Europe, non-significant but observable differences between groups were further discussed. By analyzing differences of the variation trends and the within-group significant changes of SDNN and HR between the two groups, the results tended to show that the high-sensitive group is more affected by road traffic noise. In addition, the values of SDNN and HR showed observable between-group differences at 55 dB and 65 dB which corresponding to the SPL associated with a significantly increased risk of cardiovascular disease concerned by epidemiological studies. According to the cumulative effect theory, these differences in HRV caused by short-term noise stimulation may have the potential to produce physiological response and lead to between-groups differences in prevalence after long-term recurrent effect, and deserve attention and further research. (shrink)

According to the conflict monitoring hypothesis, conflict monitoring and inhibitory control in cognitive control mainly cause activity in the anterior cingulate cortex and control-related prefrontal cortex in many cognitive tasks. However, the role of brain regions in the default mode network in cognitive control during category induction tasks is unclear. To test the role of the ACC, PFC, and subregions of the DMN elicited by cognitive control during category induction, a modified category induction task was performed using simultaneous fMRI scanning. (...) The results showed that the left middle frontal gyrus and bilateral dorsal ACC/medial frontal gyrus were sensitive to whether conflict information appears, but not to the level of conflict. In addition, the bilateral ventral ACC, especially the right vACC, a part of the DMN, showed significant deactivation with an increase in cognitive effort depending on working memory. These findings not only offer further evidence for the important role of the dorsolateral PFC and dorsal ACC in cognitive control during categorization but also support the functional distinction of the dorsal/ventral ACC in the category induction task. (shrink)

Hormonal changes across the menstrual cycle have been shown to influence reward-related motivation and impulsive behaviors. Here, to compare neural mechanisms of cognitive impulse control during the mid-luteal phase (LP) versus during the late follicular phase (FP), we employed functional magnetic resonance imaging (fMRI) with an event-related monetary delay discounting (EMDD) behavioral task (study 1) and then employed resting state (RS)-fMRI (study 2). The imaging data were analyzed and related to behavior-associated neural activation. In study 1, women in the late (...) FP showed a preference for sooner rewards while exhibiting enhanced activity in the dorsal striatum (DS), whereas women in the mid-LP showed a preference for delayed, higher-value rewards with enhanced activity in the dorsolateral prefrontal cortex (dlPFC). Discount rate (transformed k) in the EMDD task correlated with functional connectivity (FC) of the DS-dlPFC circuitry, consistent with the possibility that DS-dlPFC circuitry may regulate impulsivity. In study 2, the right dlPFC was significantly more active in mid-LP than in late FP, and this effect was sensitive to estradiol (E2) and relative E2 levels during mid-LP. The magnitude of DS-dlPFC FC correlated negatively with psychometric impulsivity scores during the late FP. These results replicated findings from study 1 and further indicated that relative E2 levels may play an important role in increasing cognitive control during the mid-LP, which provides new insight into the treatment of conditions characterized by hyper-impulsivity, such as obsessive-compulsive disorder, Parkinson disease, and attention deficit hyperactivity disorder. In conclusion, our results suggest that cyclical gonadal hormones affect cognitive control on impulsive behavior periodically, possibility via DS-dlPFC circuitry. (shrink)

The current study aims to compare compliance with the COVID-19 prevention guidelines among citizens from 13 districts in Wuhan and to explore the influence of individual-level psychological factors and district-level factors on compliance. A total of 811 participants from 13 districts in Wuhan were invited to complete surveys regarding demographics, psychosocial factors and compliance with epidemic prevention guidelines. Individual-level characteristics were combined with district-level measures to create multilevel predictive models of compliance with prevention guidelines, and used the Hierarchical Linear Model (...) to analyze the data. Findings revealed that there were significant differences in the compliance of citizens from 13 districts of Wuhan. Hierarchical linear model analysis revealed that the risk factors case growth rate, COVID-19-related perceived stress, anxiety, significantly negatively predicted compliance. Hope and conscientiousness significantly positively predicted compliance with prevention guidelines, and the negative predictive effect of anxiety disappeared. Overall, we found significant differences in compliance with prevention guidelines among different districts. Risk factors at the individual level have had a negative impact on individuals’ compliance with prevention guidelines, but this impact can be mitigated by the positive role of personal protective factors such as conscientiousness and hope. (shrink)

This study adopts an intrapersonal perspective to explore how and when employees shift roles from help giver to help seeker by investigating the relationship between their help-giving and following help-seeking behavior. Based on self-regulation theory, we hypothesize two contradictory psychological processes (i.e., consistency vs. licensing) via which employees determine whether to seek help after giving help. Importantly, we differentiate autonomous help-seeking from dependent help-seeking and propose stronger effects of help-giving on dependent help-seeking. Further, we identify leader respect as a moderator (...) to solve the opposite effects of employees’ help-giving on their subsequent help-seeking indicated by the two contradictory mechanisms. Results of two field studies consistently showed that the negative (positive) relationship between help-giving and dependent help-seeking was serially mediated by personal reputation and reputation maintenance concerns (perceived increase of moral credits and help-seeking justification). Results regarding autonomous help-seeking were inconsistent and help-giving only positively affected autonomous help-seeking via perceived increase of moral credits and help-seeking justification in Study 2. Leader respect weakened the positive (in Study 1) but strengthened the negative relationship (in Study 1 and 2). We discuss theoretical implications for helping literature, self-regulation theory, and moral behavior research. (shrink)