Prior research on employee–organization relationships has exclusively focused on the positive consequences of high-inducement EORs. Drawing from social exchange theory, we develop a model theorizing employee unethical pro-organizational behavior as one potential negative outcome of high-inducement EORs, as mediated by high-quality social exchange relationship between the employee and the employer. Empirical findings from two field studies provided convergent support to the mediation relationship between mutual-investment EORs and employee UPB via perceived social exchange. Moreover, the results in Study 2 further revealed (...) that the relationship was less significant among employees with higher levels of moral identity, because the positive relationship between perceived social exchange and employee UPB was weakened by high moral identity. The theoretical and managerial implications were discussed. (shrink)

The product presentation videos on E-commerce platforms have a significant influence on consumers' purchase decisions, and enterprises have focused on choosing the type of product presentation videos. Based on the resource matching theory, mental imagery theory and cue utilization theory, this study investigated the influence of product presentation videos type on consumers' purchase intention and the moderating effect of product rating. Through three pre-experiments and two formal experiments, the results showed that the product usage video has a stronger effect on (...) consumers' purchase intention more than the product appearance video, which is mediated by perceived diagnosticity and mental imagery. In addition, product rating moderated the influence of product presentation videos type on consumers' purchase intention. The product usage video would improve consumers' purchase intention more than the product appearance video when the product rating is high; however, there is no significant difference in the impact of two types of videos on consumers' purchase intention when the product rating is low. This study supplements the research on product presentation videos and provides a reference for online retailers to select effective product presentation videos. (shrink)

This paper is expected to introduce a novel memductor-based chaotic system. The local dynamical entities, such as the basic dynamical behavior, the divergence, the stability of equilibrium set, and the Lyapunov exponent, are all investigated analytically and numerically to reveal the dynamic characteristics of the new memductor-based chaotic system as the system parameters and the initial state of memristor change. Subsequently, an active control method is derived to study the synchronous stability of the novel memductor-based chaotic system through making the (...) synchronization error system asymptotically stable at the origin. Further to these, a memductor-based chaotic circuit is designed, realized, and applied to construct a new memductor-based secure communication circuit by employing the basic electronic components and memristor. Furthermore, the design principle of the memductor-based chaotic circuit is thoroughly analyzed and the concept of “the memductor-based chaotic circuit defect quantification index” is proposed for the first time to verify whether the chaotic output is consistent with the mathematical model. A good qualitative agreement is shown between the simulations and the experimental validation results. (shrink)

The study was designed to explore the relationships among character strengths, strengths use, future self-continuity and subjective well-being. A total of 225 undergraduates completed paper-and-pencil questionnaires assessing character strengths, strengths use, future self-continuity and subjective well-being. Results suggested several character strengths were correlated with subjective well-being and the strongest correlations were found for hope, curiosity, zest, perseverance and love. All character strengths were significantly correlated with strengths use. Strengths use and future self-continuity were robustly correlated with subjective well-being. The mediation (...) analysis showed that strengths use mediates the relationship between character strengths and subjective well-being, and specifically, the indirect effects of strengths use varies from different character strengths. The moderated mediator suggested that future self-continuity moderated the mediation of strengths use because future self-continuity moderates the effect of strengths use on subjective well-being. Furthermore, the indirect effect of strengths use was stronger with high level of future self-continuity than those with low level of future self-continuity. The present findings make a contribution to understand the underlying mechanisms involving in character strengths are associated with higher level of well-being. Additionally, the findings expand knowledge about future self-continuity and its relation to strengths use and subjective well-being among undergraduates, having significant implications in the educational context. (shrink)

Because of the impact of close partner's touch on psychological and physical well-being by alleviating stress, it is important to explore the influence factors that underlie the stress-alleviating effect of close partner's touch. Previous studies suggested that the stress-alleviating effect was different when individuals were touched by different persons. Specifically, the stress was reduced significantly when the individual was touched by the close partner compared with the acquaintance and the stranger. However, whether the stress-alleviating effect of touch was modulated by (...) the close relationship quality is unknown. To examine this question, the participants performed a 3 × 2 within-subjects experiment. The results revealed that the stress of the participants alleviated significantly while close partners present with touch compared with without touch during facing a threat. We also found that the relationship quality of couple-members modulated touch-induced stress alleviation. Participants perceiving the low quality of alternatives and the high partners' commitment level showed stronger touch-induced stress-alleviating effect than participants perceiving the high quality of alternatives and the low partners' commitment level. The explained variance was around 16.8% jointly for actor and partner effects. These findings provide evidence for explaining the reasons for touch-induced alleviating stress and have important implications for predicting the future effect of interactive behaviors. (shrink)

The examination of the complex cell biology of the human malaria parasite Plasmodium falciparum usually relies on the time‐consuming generation of transgenic parasites. Here, metabolic labeling and click chemistry are employed as a fast transfection‐independent method for the microscopic examination of protein S‐palmitoylation, an important post‐translational modification during the asexual intraerythrocytic replication of P. falciparum. Applying various microscopy approaches such as confocal, single‐molecule switching, and electron microscopy, differences in the extent of labeling within the different asexual developmental stages of P. (...) falciparum and the host erythrocytes over time are observed. (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)

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)

To meet the stability requirements for moving quadruped robots, it is important to design a rational structure for a single leg and plan the trajectory of the foot. First, a novel electrically driven leg mechanism for a quadruped robot is designed in this paper to reduce the inertia of the leg swing. Second, a modified foot trajectory based on a compound cycloid is proposed, which has swing-back and retraction motion and continuous velocity in the x-axis direction. Third, a Simulink platform (...) is built to verify the correctness of the proposed foot trajectory. The simulation result shows that when the flight phase and the stand phase switch, the impact of torque is smaller than the foot trajectory before modification. Finally, an experimental platform is constructed, and a control algorithm is written into the controller to realize the foot proposed trajectory. The results of the experiment prove the feasibility of the leg mechanism and the rationality of the proposed foot trajectory. (shrink)

The brain-computer interface of steady-state visual evoked potential is one of the fundamental ways of human-computer communication. The main challenge is that there may be a nonlinear relationship between different SSVEP in other states. For improving the performance of SSVEP BCI, a novel CNN algorithm model is proposed in this study. Based on the discrete Fourier transform to calculate the signal's power spectral density, we perform zero-padding in the signal's time domain to improve its performance on the PSD and make (...) it more refined. In this way, the frequency point interval in the PSD of the SSVEP is consistent with the minimum gap between the stimulation frequency. Combining the nonlinear transformation capabilities of CNN in deep learning, a zero-padding frequency domain convolutional neural network model is proposed. Extensive experiments based on the SSVEP dataset validate the effectiveness of our method. The study verifies that the proposed ZPFDCNN method can improve the effectiveness of the SSVEP-based high-speed BCI ITR. It has massive potential in the application of BCI. (shrink)

Preservice mathematics teachers’ accurate understanding of mathematical problem solving and its teaching is key to the performance of their professional quality. This study aims to investigate preservice mathematics teachers’ understanding of problem solving and its teaching and compares it with the understanding of in-service mathematics teachers. After surveying 326 in-service mathematics teachers, this study constructs a reliable and valid tool for the cognition of mathematical problem solving and its teaching and conducts a questionnaire survey on 26 preservice mathematics teachers. Survey (...) results reveal that preservice mathematics teachers have a good understanding of mathematical problem solving and its teaching and are more confident in the transfer value of problem solving ability. By contrast, in-service teachers are more optimistic that problem solving requires exploration, continuous thinking, and the participation of metacognition. This article concludes that preservice mathematics teachers should focus more on the initiative and creativity of students and put students at the center of education. In addition, teacher educators should provide more teaching practice opportunities for preservice teachers. The findings also show that in-service teachers’ understanding of problem solving and its teaching is inferior to that of preservice teachers on some indicators, implying the importance of post-service training for in-service teachers. (shrink)

A link prediction model for weighted networks based on Dempster–Shafer evidence theory and the influence of common neighbours is proposed in this paper. First, three types of future common neighbours and their topological structures are proposed. Second, the concepts of endpoint weight influence, link weight influence, and high-strength node influence are introduced. Then, the similarity based on the impacts of current common neighbours and FCNs is defined, respectively. Finally, the two similarity indices are fused by the DS evidence theory. This (...) model effectively integrates multisource information and completely exploits the influence of all CCNs and FCNs on similarity. Experiments are performed on 9 real and 40 simulation-weighted datasets, and these findings are compared with several classic algorithms. Results show that the proposed method has higher precision than other methods, which can achieve good performance in link prediction in weighted networks. (shrink)

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume and the complex modeling requirements increase the difficulty of deep learning modeling, and the classical centralized deep learning modeling scheme has encountered bottlenecks in the improvement of model performance (...) and the diversification of smart application scenarios. The parallel processing system in deep learning links the virtual information space with the physical world, although the distributed deep learning research has become a crucial concern with its unique advantages in training efficiency, and improving the availability of trained models and preventing privacy disclosure are still the main challenges faced by related research. To address these above issues in distributed deep learning, this research developed a clonal selective optimization system based on the federated learning framework for the model training process involving large-scale data. This system adopts the heuristic clonal selective strategy in local model optimization and optimizes the effect of federated training. First of all, this process enhances the adaptability and robustness of the federated learning scheme and improves the modeling performance and training efficiency. Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy. (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)

Extreme events, which are usually characterized by generalized extreme value models, can exhibit long-term memory, whose impact needs to be quantified. It was known that extreme recurrence intervals can better characterize the significant influence of long-term memory than using the GEV model. Our statistical analyses based on time series datasets following the Lévy stable distribution confirm that the stretched exponential distribution can describe a wide spectrum of memory behavior transition from exponentially distributed intervals to power-law distributed ones, extending the previous (...) evaluation of the stretched exponential function using Gaussian/exponential distributed random data. Further deviation and discussion of a historical paradox are also provided, based on the theoretical analysis of the Bayesian law and the stretched exponential distribution. (shrink)

Event cameras which transmit per-pixel intensity changes have emerged as a promising candidate in applications such as consumer electronics, industrial automation, and autonomous vehicles, owing to their efficiency and robustness. To maintain these inherent advantages, the trade-off between efficiency and accuracy stands as a priority in event-based algorithms. Thanks to the preponderance of deep learning techniques and the compatibility between bio-inspired spiking neural networks and event-based sensors, data-driven approaches have become a hot spot, which along with the dedicated hardware and (...) datasets constitute an emerging field named event-based data-driven technology. Focusing on data-driven technology in event-based vision, this paper first explicates the operating principle, advantages, and intrinsic nature of event cameras, as well as background knowledge in event-based vision, presenting an overview of this research field. Then, we explain why event-based data-driven technology becomes a research focus, including reasons for the rise of event-based vision and the superiority of data-driven approaches over other event-based algorithms. Current status and future trends of event-based data-driven technology are presented successively in terms of hardware, datasets, and algorithms, providing guidance for future research. Generally, this paper reveals the great prospects of event-based data-driven technology and presents a comprehensive overview of this field, aiming at a more efficient and bio-inspired visual system to extract visual features from the external environment. (shrink)

This paper provides an in-depth analysis and discussion of the key issues of quality management, evaluation, and detection contained in big data for automotive application scenarios. A generalized big data quality management model and programming framework are proposed, and a series of data quality detection and repair interfaces are built to express the processing semantics of various data quality issues. Through this data quality management model and detection and repair interfaces, users can quickly build custom data quality detection and repair (...) tasks for different data quality requirements. To improve the operational efficiency of complex data quality management algorithms in large-scale data scenarios, corresponding parallelization algorithms are studied and implemented for detection and repair algorithms with long computation time, including priority-based multiconditional function-dependent detection and repair algorithms, entity detection, and extraction algorithms based on semantic information and chunking techniques, and plain Bayesian-based missing value filling algorithms, and this paper proposes a data validity evaluation algorithm and enhances the validity of the original data in practical applications by adding temporal weights, and finally it passed the experimental validation. Through the comprehensive detection process of data importance, network busyness, duration of transmission process, and failure situation, the efficiency has been increased by 20%, and an adaptive data integrity detection method based on random algorithm and encryption algorithm is designed. After experimental verification, this method can effectively detect the integrity of the data transmission process and improve the application of data value, and the final effect is increased by 30.5%. (shrink)

BackgroundThe cognitive level of post-stroke aphasia patients is generally lower than non-aphasia patients, and cognitive impairment affects the outcome of stroke. However, for different types of PSA, what kind of cognitive assessment methods to choose is not completely clear. We investigated the Montreal Cognitive Assessment, the Mini-Mental State Examination, and the Non-language-based Cognitive Assessment to observe the evaluation effect of CI in patients with fluent aphasia and non-fluent aphasia.Methods92 stroke patients were included in this study. Demographic and clinical data of (...) the stroke group were documented. The language and cognition were evaluated by Western Aphasia Battery, MoCA, MMSE, and NLCA. PSA were divided into FA and NFA according to the Chinese aphasia fluency characteristic scale. Pearson’s product–moment correlation coefficient test and multiple linear regression analysis were performed to explore the relationship between the sub-items of WAB and cognitive scores. The classification rate of CI was tested by Pearson’s Chi-square test or Fisher’s exact test.ResultsThe scores of aphasia quotient, MoCA, MMSE, and NLCA in NFA were lower than FA. AQ was positively correlated with MoCA, MMSE, and NLCA scores. Stepwise multiple linear regression analysis suggested that naming explained 70.7% of variance of MoCA and 79.9% of variance of MMSE; comprehension explained 46.7% of variance of NLCA. In the same type of PSA, there was no significant difference in the classification rate. The classification rate of CI in NFA by MoCA and MMSE was higher than that in FA. There was no significant difference in the classification rate of CI between FA and NFA by NLCA.ConclusionMoCA, MMSE, and NLCA can be applied in FA. NLCA is recommended for NFA. (shrink)

This paper presents a nonlinear trajectory controller with improved performances for a general model of the waverider based on feedback linearization theory and composite nonlinear feedback technique. First, a nonlinear controller is presented using the dynamic inversion and CNF technique for the MIMO Model, and the robust stability of the proposed controller is proved. Then, the nonlinear model is established on the basis of hypersonic aerodynamic principle, and the dynamic characteristics are analyzed accordingly, and the periodic trajectory is designed and (...) optimized in combination with a fuel optimization problem. Furthermore, the nonlinear controller is applied to the trajectory tracking of the waverider model, and the general design steps are provided the flight controller using this nonlinear control method. Finally, an illustrative example is given to verify the effectiveness of the nonlinear controller of the waverider, and the flight performances are improved accordingly, including system stability, robustness, and tracking ability. (shrink)

Background and ObjectiveThere is vast published literature proposing repetitive transcranial magnetic stimulation technology on the motor cortex for the treatment of neuropathic pain. Systematic reviews focus on a specific problem and do not provide a comprehensive overview of a research area. This study aimed to summarize and analyze the evidence of rTMS on the M1 for NP treatment through a new synthesis method called evidence mapping.MethodsSearches were conducted in PubMed, EMBASE, Epistemonikos, and The Cochrane Library to identify the studies that (...) summarized the effectiveness of rTMS for NP. The study type was restricted to SRs with or without meta-analysis. All literature published before January 23, 2021, was included. Two reviewers independently screened the literature, assessed the methodological quality, and extracted the data. The methodological quality of the included SRs was assessed by using the A Measurement Tool to Assess Systematic Reviews. Data were extracted following a defined population, intervention, comparison, and outcome framework from primary studies that included SRs. The same PICO was categorized into PICOs according to interventions [frequency, number of sessions ] and compared. The evidence map was presented in tables and a bubble plot.ResultsA total of 38 SRs met the eligibility criteria. After duplicate primary studies were removed, these reviews included 70 primary studies that met the scope of evidence mapping. According to the AMSTAR-2 assessment, the quality of the included SRs was critically low. Of these studies, 34 SRs scored “critically low” in terms of methodological quality, 2 SR scored “low,” 1 SR scored “moderate,” and 1 SR scored “high.”ConclusionEvidence mapping is a useful methodology to provide a comprehensive and reliable overview of studies on rTMS for NP. Evidence mapping also shows that further investigations are necessary to highlight the optimal stimulation protocols and standardize all parameters to fill the evidence gaps of rTMS. Given that the methodological quality of most included SRs was “critically low,” further investigations are advised to improve the methodological quality and the reporting process of SRs. (shrink)

本书着重探讨黄宗羲所坚持的、潜藏在政治现象背后的、并对政治现象产生决定性作用的基本理念,以及这些理念与黄宗羲各种政治主张之间的关系,试图较系统的把握黄宗羲政治哲学思想的性质及全貌,揭示其对中国社会产生 影响的根源,预示其对中国社会的未来意义.

本书探索了民事证据的有关问题。全书介绍了证据适格及证据排除原理、证据裁判主义原理、证据方法原理、证明责任原理、证据规则原理、司法认知原理及民事自认原理等内容。.

本书共分七章,通过对证据评判规则及其内在机理的研究,系统地阐述了民事证据的采信制度。.