Studies have shown that internal whistleblowing could be utilized as an effective way to stop an organization’s unethical behaviors. This study investigates the relationship between ethical leadership and internal whistleblowing by focusing on the mediating role of employee-perceived organizational politics and the moderating role of moral courage. An analysis of data collected at three phases indicates that employee-perceived organizational politics partly mediates the relationship between ethical leadership and internal whistleblowing. Also, moral courage is found to moderate the effect of employee-perceived (...) organizational politics on internal whistleblowing and the indirect effect of ethical leadership on internal whistleblowing via employee-perceived organizational politics. Theoretical and practical implications of these results are discussed. (shrink)

The coronavirus pandemic (COVID-19) has badly affected the social, physical, and emotional health of workers, especially those working in the healthcare sectors. Drawing on social exchange theory, we investigated the effects of participative leadership on employees’ workplace thriving and helping behaviors among frontline workers during the COVID-19 pandemic. In addition, we examined the moderating role of a leader’s behavioral integrity in strengthening the relationship between participative leadership, and employees’ workplace thriving and helping behaviors. By using a two-wave time-lagged design and (...) data collected from 244 healthcare workers, a moderated hierarchal regression was implemented to test the proposed hypotheses. As hypothesized, participative leadership predicted employees’ workplace thriving and helping behaviors. The leader’s behavioral integrity strengthened the relationship between participative leadership and employees’ thriving and moderated the relationship between participative leadership helping behaviors. Implications for research, theory, and practice are discussed. (shrink)

Previous literature has demonstrated that ethical leadership could predict employees’ voice behavior. However, it’s not clear how to heighten these positive effects of ethical leadership on employees’ voice behavior. Building on the AET and moral disengagement studies, we developed an integrated model. A three-wave field study investigated the relationship between ethical leadership and voice behavior by focusing on the mediating role of employees’ affective commitment and the moderating role of employees’ moral disengagement. Our matched data analysis results indicated that: employees’ (...) affective commitment partly mediated the relationship between ethical leadership and employees’ voice behavior. In addition, employees’ moral disengagement moderated the effect of ethical leadership on employees’ affective commitment and the effect of employees’ affective commitment on voice behavior, similarly, the indirect effect of ethical leadership on employees’ voice behavior via employees’ affective commitment. Theoretical and practical implications of these results are discussed. (shrink)

Several functional magnetic resonance imaging studies have demonstrated abnormalities in static intra- and interhemispheric functional connectivity among diverse brain regions in patients with major depressive disorder. However, the dynamic changes in intra- and interhemispheric functional connectivity patterns in patients with MDD remain unclear. Fifty-eight first-episode, drug-naive patients with MDD and 48 age-, sex-, and education level-matched healthy controls underwent resting-state fMRI. Whole-brain functional connectivity, analyzed using the functional connectivity density approach, was decomposed into ipsilateral and contralateral functional connectivity. We computed (...) the intra- and interhemispheric dynamic FCD using a sliding window analysis to capture the dynamic patterns of functional connectivity. The temporal variability in functional connectivity was quantified as the variance of the dFCD over time. In addition, intra- and interhemispheric static FCD patterns were calculated. Associations between the dFCD variance and sFCD in abnormal brain regions and the severity of depressive symptoms were analyzed. Compared to HCs, patients with MDD showed lower interhemispheric dFCD variability in the inferior/middle frontal gyrus and decreased sFCD in the medial prefrontal cortex/anterior cingulate cortex and posterior cingulate cortex/precuneus in both intra- and interhemispheric comparisons. No significant correlations were found between any abnormal dFCD variance or sFCD at the intra- and interhemispheric levels and the severity of depressive symptoms. Our results suggest intra- and interhemispheric functional connectivity alterations in the dorsolateral prefrontal cortex and default mode network regions involved in cognition, execution and emotion. Furthermore, our study emphasizes the essential role of altered interhemispheric communication dynamics in the DLPFC in patients with MDD. These findings contribute to our understanding of the pathophysiology of MDD. (shrink)

Based on the conservation of resources theory, this study developed a model linking social undermining to employees helping behaviors and work role performance via expression of guilt, with religious faith possessed by employees as a first-stage moderator. We argue that individuals will feel guilty if they perceive themselves as the perpetrators of the social undermining against their coworkers. Feeling guilt can potentially trigger prosocial responses (i.e., helping coworkers) and enhance work role performance for improving the situation. We contend that religious (...) faith that commands doing good with others further provides resources for managing these negative emotions to unleash a positive side of social undermining, such that the relation of social undermining with an expression of guilt will be strengthened. A multisource (supervisor-supervisee), multi-wave, and multi-context (education, healthcare, and banking) survey involving 281 employees largely supports our study hypotheses. The results indicated that social undermining is associated with more guilt expressions amid religious individuals, revealing higher prosocial and work role performance. For business ethics research, the current study unveils an important mediator—guilt expressions about wrongdoing—via which individuals’ social undermining behaviors at work, somewhat counterintuitively, lead to boost performance outcomes, and an employee’s religious faith helps a facilitator of this relationship. (shrink)

Alcohol use disorder is one of the most common substance use disorders contributing to both behavioral and cognitive impairments in patients with AUD. Recent neuroimaging studies point out that AUD is a typical disorder featured by altered functional connectivity. However, the details about how voxel-wise functional coordination remain unknown. Here, we adopted a newly proposed method named functional connectivity density to depict altered voxel-wise functional coordination in AUD. The novel functional imaging technique, FCD, provides a comprehensive analytical method for brain's (...) “scale-free” networks. We applied resting-state functional MRI toward subjects to obtain their FCD, including global FCD, local FCD, and long-range FCD. Sixty-one patients with AUD and 29 healthy controls were recruited, and patients with AUD were further divided into alcohol-related cognitive impairment group and non-cognitive impairment group. All subjects were asked to stay stationary during the scan in order to calculate the resting-state gFCD, lFCD, and lrFCD values, and further investigate the abnormal connectivity alterations among AUD-NCI, ARCI, and HC. Compared to HC, both AUD groups exhibited significantly altered gFCD in the left inferior occipital lobe, left calcarine, altered lFCD in right lingual, and altered lrFCD in ventromedial frontal gyrus. It is notable that gFCD of the ARCI group was found to be significantly deviated from AUD-NCI and HC in left medial frontal gyrus, which changes probably contributed by the impairment in cognition. In addition, no significant differences in gFCD were found between ARCI and HC in left parahippocampal, while ARCI and HC were profoundly deviated from AUD-NCI, possibly reflecting a compensation of cognition impairment. Further analysis showed that within patients with AUD, gFCD values in left medial frontal gyrus are negatively correlated with MMSE scores, while lFCD values in left inferior occipital lobe are positively related to ADS scores. In conclusion, patients with AUD exhibited significantly altered functional connectivity patterns mainly in several left hemisphere brain regions, while patients with AUD with or without cognitive impairment also demonstrated intergroup FCD differences which correlated with symptom severity, and patients with AUD cognitive impairment would suffer less severe alcohol dependence. This difference in symptom severity probably served as a compensation for cognitive impairment, suggesting a difference in pathological pathways. These findings assisted future AUD studies by providing insight into possible pathological mechanisms. (shrink)

This paper firstly designs a five-dimensional model of learners’ characteristics and a three-dimensional model of English reading resources’ characteristics in a fragmented learning environment through literature research. At the same time, to make the learning resources meet the characteristics of fragmented learning time and space, the English Level 4 reading resources are reasonably designed and segmented to adapt to the needs of learners’ mobile fragmented learning. Then, combined with machine learning algorithms, an adaptive recommendation model of learning resources in English (...) fragmented reading is constructed. The algorithm-based adaptive recommendation algorithm for English fragmented reading resources is designed. Based on the generated decision trees, the expression rules are parsed to achieve adaptive pushing of resources. The results of this study show that adaptive recommendation of learning resources in English fragmented reading can help teachers to develop future resource recommendation strategies through effective data collection to adaptively push resources that are close to learners’ individual needs. The use of mobile by English learners to learn to read in a fragmented learning context enables targeted training in weak areas of English reading, thus enhancing different aspects of learners’ reading skills. (shrink)

Meta-analytical research has demonstrated the benefits brought by telecommuting to wellbeing. However, we argue that such a setup in the course of the coronavirus disease pandemic exerts negative effects. On the basis of conservation of resources theory, this study determined how telecommuting depletes wellbeing through obstructing psychological detachment from work. Moreover, we incorporated family interfering with work and family–work enrichment as moderators that can buffer the negative effect of telecommuting on psychological detachment from work. Time-lagged field research was conducted with (...) 350 Chinese employees, and findings largely supported our theoretical hypotheses. The elevated level of telecommuting results in minimal psychological detachment from work, which then leads to low wellbeing. Meanwhile, the negative effect of the extent of telecommuting on psychological detachment from work is reduced by family interfering with work. These findings extend the literature on telecommuting and psychological detachment from work through revealing why teleworkers present negative feelings during the pandemic. (shrink)

中道思想在我国源远流长, 自上古尧、舜开始, 一脉相承于禹、汤、文、武、周公、孔子、孟子、以及汉唐、宋、明、清乃至近代, 延续了几千年, 有着极为丰富的内涵, 可以说, 历代社会的治乱兴衰, 均逃不出执政者的得中与失中的因果规律. 因此, 认真探索一下中国古代的中道即中和思想的产生与发展及其在各方面的表现形式, 不仅具有重要的学术价值, 同时也对于当今构建和谐社会具有重大的现实意义.

本書通過選取「自然」、「靜」、「靈」、「適」、「化」等主體審美心境范疇為研究的切入點，結合中國審美心境歷史發展的脈絡，厘清范疇內涵，同時兼與其他相關范疇比較，揭示各范疇間的內在邏輯聯系，從而探討其中蘊 含着的我們民族獨特的審美思維方式、心靈境界和修養方法等。主體審美心境范疇的研究，不僅在中國美學和文論范疇研究上有重要意義（因為除個別主體論范疇已有人作過研究外，整體性的理論觀照還相當薄弱），而且對西方 當代藝術及理論的發展，以及現代人性心靈的建構，也具有相當的參考價值。.

This paper conducts a numerical simulation of the antiseismic performance for single-layer masonry structures, completes a study on crack distributions and detailed characteristics of masonry structures, and finally verifies the correctness of the numerical model by experimental tests. This paper also provides a reinforced proposal to improve the antiseismic performance of single-layer masonry structures. Results prove that the original model suffers more serious damage than the reinforced model; in particular, longitudinal cracks appear on bottoms of two longitudinal walls in the (...) original model, while these cracks appear later in the reinforced model; a lot of cracks appear on the door hole of the original model, and no crack appears in the reinforced model till the end of seismic waves; seismic damage of walls in the reinforced model is obviously lighter than that in the original model; dynamic responses at all observed points of the reinforced masonry are obviously less than those of the original model. Strains at all positions of the reinforced model are obviously smaller than those of the original model. From macroscopic and microscopic perspectives, the computational results prove that the reinforced proposal proposed in this paper can effectively improve the antiseismic performance of the masonry structure. (shrink)

BackgroundTemporal lobe epilepsy is the most prevalent refractory focal epilepsy and is more likely accompanied by cognitive impairment. The fully understanding of the neuronal activity underlying TLE is of great significance.ObjectiveThis study aimed to comprehensively explore the potential brain activity abnormalities affected by TLE and detect whether the changes were associated with cognition.MethodsSix static intrinsic brain activity indicators [amplitude of low-frequency fluctuation, fractional ALFF, regional homogeneity, degree centrality, global signal correlation, and voxel-mirrored homotopic connectivity ] and their corresponding dynamic indicators, (...) such as dynamic ALFF, dynamic fALFF, dynamic ReHo, dynamic DC, dynamic VMHC, and dynamic GSCorr, in 57 patients with unilateral TLE and 42 healthy volunteers were compared. Correlation analyses were also performed between these indicators in areas displaying group differences and cognitive function, epilepsy duration, and severity.ResultsMarked overlap was present among the abnormal brain regions detected using various static and dynamic indicators, primarily including increased ALFF/dALFF/fALFF in the bilateral medial temporal lobe and thalamus, decreased ALFF/dALFF/fALFF in the frontal lobe contralateral to the epileptogenic side, decreased fALFF, ReHo, dReHo, DC, dDC, GSCorr, dGSCorr, and VMHC in the temporal neocortex ipsilateral to the epileptogenic foci, decreased dReHo, dDC, dGSCorr, and dVMHC in the occipital lobe, and increased ALFF, fALFF, dfALFF, ReHo, and DC in the supplementary motor area ipsilateral to the epileptogenic foci. Furthermore, most IBA indicators in the abnormal brain region significantly correlated with the duration of epilepsy and several cognitive scale scores.ConclusionThe combined application of static and dynamic IBA indicators could comprehensively reveal more real abnormal neuronal activity and the impairment and compensatory mechanisms of cognitive function in TLE. Moreover, it might help in the lateralization of epileptogenic foci and exploration of the transmission and inhibition pathways of epileptic activity. (shrink)

With the rapid emergence of the technology of deep learning, it was successfully used in different fields such as the aquatic product. New opportunities in addition to challenges can be created according to this change for helping data processing in the smart fish farm. This study focuses on deep learning applications and how to support different activities in aquatic like identification of the fish, species classification, feeding decision, behavior analysis, estimation size, and prediction of water quality. Power and performance of (...) computing with the analyzed given data are applied in the proposed DL method within fish farming. Results of the proposed method show the significance of contributions in deep learning and how automatic features are extracted. Still, there is a big challenge of using deep learning in an era of artificial intelligence. Training of the proposed method used a large number of labeled images got from the Fish4Knowledge dataset. The proposed method based on suitable feature extracted from the fish achieved good results in terms of recognition rate and accuracy. (shrink)