Objectives: Autism spectrum disorder (ASD) is a juvenile onset neurodevelopmental disorder with social impairment and stereotyped behavior as the main symptoms. Unaffected relatives may also exhibit similar ASD features due to genetic factors. Although previous studies have demonstrated atypical brain morphological features as well as task-state brain function abnormalities in unaffected parents with ASD children, it remains unclear the pattern of brain function in the resting state.Methods: A total of 42 unaffected parents of ASD children (pASD) and 39 age-, sex-, (...) and handedness-matched controls were enrolled. Multiple resting-state fMRI (rsfMRI) analyzing methods were applied, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC), to reveal the functional abnormalities of unaffected parents in ASD-related brain regions. Spearman Rho correlation analysis between imaging metric values and the severity of ASD traits were evaluated as well.Results: ALFF, ReHo, and DC methods all revealed abnormal brain regions in the pASD group, such as the left medial orbitofrontal cortex (mOFC) and rectal gyrus (ROI-1), bilateral supplementary motor area (ROI-2), right caudate nucleus head and right amygdala/para-hippocampal gyrus (ROI-3). FC decreasing was observed between ROI-1 and right anterior cingulate cortex (ACC), ROI-2, and bilateral precuneus. FC enhancing was observed between ROI-3 and right anterior cerebellar lobe, left medial temporal gyrus, left superior temporal gyrus, left medial frontal gyrus, left precentral gyrus, right postcentral gyrus in pASD. In addition, ALFF values in ROI-1, DC values in ROI-3 were positively correlated with AQ scores in pASD (ρ1 = 0.298, P1 = 0.007; ρ2 = 0.220, P2 = 0.040), while FC values between ROI-1 and right ACC were negatively correlated with AQ scores (ρ3 = −0.334, P3 = 0.002).Conclusion: rsfMRI metrics could be used as biomarkers to reveal the underlying neurobiological feature of ASD for unaffected parents. (shrink)

We have refined entropy theory to explore the meaning of the increasing sequence data on nucleic acids and proteins more conveniently. The concept of selection constraint was not introduced, only the analyzed sequences themselves were considered. The refined theory serves as a basis for deriving a method to analyze non-coding regions (NCRs) as well as coding regions. Positions with maximal entropy might play the most important role in genome functions as opposed to positions with minimal entropy. This method was tested (...) in the well-characterized coding regions of 12 strains of Classical Swine Fever Virus (CSFV) and non-coding regions of 20 strains of CSFV. It is suitable to analyze nucleic acid sequences of a complete genome and to detect sensitive positions for mutagenesis. As such, the method serves to formulate the basis for elucidating the functional mechanism. (shrink)

Learning burnout is an important indicator that reflects an individual’s learning state. Understanding the influencing factors and mechanism of learning burnout of medical students has practical significance for improving their mental health. This study aimed to explore the mediating roles of school identity and collective self-esteem between school psychological environment and learning burnout in medical students. A total of 2,031 medical students were surveyed using the School Psychological Environment Questionnaire, School Identity Questionnaire, Collective Self-esteem Scale, and Learning Burnout Scale. The (...) results showed the following: school psychological environment had a negative effect on learning burnout among medical students, and school identity and collective self-esteem played significant mediating roles between school psychological environment and learning burnout [95% CI = ]. Specifically, there were three paths that school psychological environment and learning burnout: first, through the independent mediating role of school identity; second, through the independent mediating role of collective self-esteem; and third, through the chain mediating roles of school identity and collective self-esteem. The findings reveal that school psychological environment not only directly influences the learning burnout of medical students but also indirectly influences it through school identity and collective self-esteem. Thus, this study has some important implications for prevention and intervention of learning burnout among medical students. (shrink)

In the present research, based on the game research paradigm, the research tools are the dictator game and the trust game, and the research objects are Chinese university students. We adopt 2 × 2 between-subjects design experiment to investigate the influence of social class on university students’ prosocial behavior. Across the experimental study, we find that in the two situations of dictator game and trust game, self-social class has no significant influence on university students’ prosocial behavior; in the situation of (...) dictator game, target social class has a significant influence on university students’ prosocial behavior, and it is regulated by self-social class. Under the condition of low self-social class, the higher the target social class, the more prosocial behavior of university students, which confirms the perspective of status and negates “if you are poor, you will be good for yourself.” Under the condition of high self-social class, the lower the target social class, the more prosocial the behavior of university students, which confirms the perspective of fairness and echoes “if you are good, you will be good at the world”; in the context of the trust game, target social class has a significant influence on university students’ prosocial behavior, and there is no interaction effect with self-social class. (shrink)

Based on social exchange theory and attribution theory, this paper explores the role of affective commitment and organizational support in the relationship between career growth and the engagement of knowledge workers. The results show that career growth has a positive impact on knowledge workers’ organizational engagement; career goal progress and professional ability development promote job engagement; career growth has a positive effect on affective commitment, which in turn influences employee engagement; affective commitment plays a mediating role in the effect of (...) career growth on engagement; and perceived organizational support positively moderates the relationship between career growth and affective commitment. (shrink)

The harm of horizontal knowledge hiding behavior to individuals and organizations has been discussed and confirmed by many studies. The negative consequences of top-down knowledge hiding have now emerged as a new focus of research. This study aims to enrich the understanding of the consequences of supervisor knowledge hiding by exploring its trickle-down effect and mechanism. Based on the displaced aggression theory in psychology, this paper analyses and examines the cognitive psychological process and mechanism informing employee knowledge hiding from colleagues (...) when faced with their supervisor’s malicious knowledge hiding behavior. Using a three-stage time-lag questionnaire survey strategy, we collect 233 valid samples of full-time employees from representative provinces and cities in China, covering multiple industries. The following findings are observed: Supervisor knowledge hiding from subordinates positively affects subordinate knowledge hiding from colleagues ; Revenge motivation plays a mediating role; Traditionality weakens the influence of supervisor knowledge hiding on a subordinates’ revenge motivation. This study confirms the trickle-down effects of supervisor knowledge hiding behavior, extends research on the consequences of top-down knowledge hiding and its mechanism and provides new insights for organizational practice. (shrink)

Agricultural water management provides the basic support and guarantee for targeted poverty alleviation. This paper presents a 3E + 1 evaluation model for the performance of agricultural water management in targeted poverty alleviation based on 3E theory, which is more scientific, reasonable, and reliable. On this basis, an evaluation index system including three levels of indicators is designed, and the weight of each evaluation index and performance evaluation model is determined. A case study of a county in the old district (...) of Maoshan in Jiangsu province was conducted using the proposed evaluation theory and methods. The results show that the overall performance of agricultural water management for targeted poverty alleviation in this area was good but needs more improvement in innovation. The evaluation results are roughly consistent with the evaluations of higher authorities, experts, and scholars, which proves that the evaluation system is scientific and reasonable. (shrink)

Existing theory has not documented the potential benefits of facing the challenges of underdog entrepreneurs, who may succeed unexpectedly. This research explains why, and under what circumstances, the underdog status of entrepreneurs can promote entrepreneurial success rather than just hinder it. We predict that the underdog effect has the potential to boost entrepreneurial resource efficiency when entrepreneurs hold an incremental theory, enter a low-barrier industry, and are in a favorable business environment. Study 1 provides support for the positive relationship between (...) underdog status and resource efficiency through an ordinary least squares regression analysis, which is accompanied by a moderating effect of the implicit theory, industry context, and business environment. The data was obtained from two nationwide surveys. By extending a qualitative comparative analysis of multiple case studies, Study 2 reveals support for a synergistic effect of the above factors. Our research results examine the assumption that perceiving underdog status is detrimental and offer meaningful insights into why and when underdog entrepreneurs have good performance in entrepreneurial resource efficiency. We provide a psychological and behavioral explanation for the underdog effect, extending the underdog effect theory to the field of entrepreneurship for the first time from the perspective of the actors. Finally, theoretical contributions and practical implications are discussed by indicating the limitations of the research. (shrink)

Patients with bipolar disorder may experience family dysfunction, which might result in worse psychosocial functioning through environmental and psychological factors. Research investigating the mediating role of social support, resilience and suicidal ideation on family and psychosocial functioning in BD is rare. The study aims to explore the predicting and mediating effects of social support, resilience and suicidal ideation on family and psychosocial functioning in BD patients. Two hundred forty-six patients with BD and sixty-nine healthy controls were recruited. The Family Assessment (...) Device, Functioning Assessment Short Test, Social Support Rating Scale, Connor-Davidson Resilience Scale and Beck Scale for Suicide Ideation were used to assess family functioning, psychosocial functioning, social support, resilience and suicidal ideation, respectively. Bipolar patients exhibited worse family and psychosocial functioning than healthy controls. Family functioning, social support, resilience and suicidal ideation significantly predict psychosocial functioning in the bipolar group. Social support, resilience and suicidal ideation indirectly mediate the effect of family functioning on psychosocial functioning in bipolar patients. Cross-sectional design and mixed sample including acute and remitted stages. Treatments for patients with bipolar disorder should be combined with family strategies that are formulated to improve psychosocial functioning. An emphasis should be placed on enhancing social support and resilience while paying attention to suicidal ideation. (shrink)

Photovoltaic power forecasting can provide strong support for the safe operation of the power system. Existing forecasting methods are ineffective for grid scheduling decisions or risk analysis. The novel multicluster interval prediction method is proposed to consider the volatility and randomness of PV power output. First, this method utilizes the sparse autoencoder and Bayesian regularized NARX network for point forecasting of PV power. Second, density peak clustering improved by kernel Mahalanobis distance is applied to classify the dataset into multiple clusters, (...) including forecasting error and meteorological factors. Finally, the joint probability density is established by multivariate kernel density estimation to accomplish the PV power interval prediction. The proposed hybrid method is applied for the interval prediction of PV power at Yulara, Australia. Comparative research of point forecasting is implemented to evaluate the machine learning and deep learning methods, with the proposed SAE-BRNARX under four different periods. Results shows that the average values of nRMSE, MRE, nMAE, and R2 for the four periods are 4.45%, 0.90%, −0.15%, 3.39%, and 95.93%, respectively. Moreover, the results of interval prediction obtained by the other interval prediction approaches are compared with the proposed KMDDPC-MKDE. It shows that the average values of PICP, PINAW, ACE, and nMPICD for four periods are 93.93%, 9.50%, 3.93%, and 7.10% at 90% confidence level, respectively. Outcomes demonstrate that the proposed method can obtain more accuracy, a higher coverage rate, narrower average bandwidth, and a closer distance between the middle of interval and actual value than other methods. (shrink)

BackgroundThe Basal ganglia (BG) played a crucial role in the brain-level mechanisms of chronic pain disorders. However, the functional changes of BG in chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) are still poorly understood. This study investigated the BG subregions’ resting-state functional connectivity (rs-FC) in CP/CPPS patients compared with healthy controls.MethodsTwenty eight patients with CP/CPPS and 28 age- and education-matched healthy males underwent clinical measurements and 3T brain MR imaging, including T1-weighted structural images and resting-state functional imaging. The data were analyzed (...) by the seeded-based rs-FC analysis. Then, a machine learning method was applied to assess the feasibility of detecting CP/CPPS patients through the changed rs-FC.ResultsCompared with healthy males, patients presented decreased rs-FC between the BG subregions and right middle cingulate cortex, and correlated with pain (r = 0.51, p-uncorrected = 0.005) and urinary symptoms (r = –0.4, p-uncorrected = 0.034). The left superior temporal gyrus and right supramarginal gyrus showed decreased rs-FC with the BG subregions as well. The area under the receiver operating characteristic curve of 0.943 (accuracy = 80%, F1-score = 80.6%) was achieved for the classification of CP/CPPS patients and healthy males with support vector machine (SVM) based on the changed rs-FC.ConclusionThese findings provide evidence of altered BG subregions’ rs-FC in CP/CPPS, which may contribute to our understanding of the BG’s role in CP/CPPS. (shrink)

This paper uses WIOD data to calculate and analyze the dominant comparative advantage of Chinese manufacturing global value chain based on the WWZ method and empirically studies the influence of digitization on the competitiveness of manufacturing GVC. The main findings are as follows: The competitiveness of Chinese manufacturing GVC has been improved as a whole. The GVC competitiveness of different types of industries is quite different: GVC in middle- and low-knowledge-intensive industries have the highest competitiveness, while those with middle- and (...) high-knowledge-intensive industries have the lowest competitiveness and apparent shortboard industries. Digitization is conducive for enhancing the competitiveness of manufacturing GVC. In terms of industries, digitization has a significant positive effect on the GVC competitiveness of middle and high-knowledge-intensive industries but not on low knowledge ones. As for the sources of digital input, the positive effect is more outstanding. Also, it is more remarkable when it comes to the software and information technology service industry. As for the mechanism of action, labor productivity is an effective way to improve the manufacturing GVC competitiveness digitally. Finally, after a robustness test, the positive effect of the digital input remains robust. (shrink)

Economy is one of the major issues in the United States presidential election campaign. In order to investigate the impact of the US presidential election on the economy, this paper first constructs an analysis model of the economic impact on the United States based on stepwise regression and principal component analysis to analyze the focus of different candidates’ attention on the economic issues and its possible impact on the US economy in the election year and after the election; secondly, a (...) Chinese economic impact analysis model based on factor analysis and machine learning logistic regression was constructed to analyze the impact of the US presidential election on the Chinese economy. At the same time, the future economic development of the United States and China based on the time series prediction model is forecast and analyzed, respectively. Finally, the countermeasures and policy suggestions on China’s related economic development are put forward. (shrink)

Adopting fair value measurement may bring more earnings fluctuations and induce irrational psychology and radical financing behavior of managers. Based on behavioral corporate governance theory, using the sample of Chinese A-share nonfinancial listed companies during 2007–2017, this paper empirically examines the regulatory effect of fair value measurement, that is, whether fair value measurement affects the company's financing decisions when managers have irrational psychological characteristics, i.e., overconfidence. The study found that overconfident managers of the company that have fair value measurement assets (...) will be more aggressive for debt decisions, indicating that fair value measurement has a positively regulatory effect on overconfident managers. (shrink)

This paper first extracted 11 indicators from four aspects of infrastructure, educational equity, teaching quality, and scientific research level and established a multidimensional higher education evaluation system. After that, according to TOPSIS and the entropy method, a comprehensive score of the development of higher education was obtained, and a comprehensive index of higher education was proposed. According to the level of the score, we divide the development status into 5 categories, and use discrete Hopfield neural network for verification. In addition, (...) we applied the model to many countries and chose Vietnam to conduct an in-depth analysis of the model, including reforming policies and evaluating policy effects based on cobweb model. Finally, we found that the application of the model is very universal, but in reality the reform is very difficult. (shrink)

With the continuous development of the stock market, designing a reasonable risk identification tool will help to solve the irrational problem of investors. This paper first selects the stocks with the most valuable investment value in the future through the random forest algorithm in the nine-factor model and then analyzes them by using the higher-order moment model to find that different investors’ preferences will make the weight of the portfolio change accordingly, which will eventually make the optimal return and risk (...) set of the composition of the portfolio change. The risk identification system designed in this paper can provide an effective risk identification tool for investors and help them make rational judgments. (shrink)

Herring and mackerel are two of the most important pillars of Scottish fisheries. In recent years, global warming has caused a gradual rise in ocean temperatures. In order to survive and reproduce, herring and mackerel populations will migrate. This will have a huge impact on Scotland’s fisheries. Therefore, we need to predict the relocation of fish stocks in advance, make timely adjustments to the fishing range, and minimize the loss of the fishing industry. In this article, we subdivide the research (...) target sea area into 39 regions, establish the optimal SARIMA model for each region based on the collected seawater temperature time series data, and take region 13 and region 15 as examples to fit the ARIMA and ARIMA models with a period of 12. The results show that the SARIMA model fits well in all regions and predicts the temperature changes in the studied sea area from 2021 to 2050. Finally, according to the predicted sea temperature in different periods, the migration position of the fish school is predicted. (shrink)

本书包括四篇内容:第一篇总论;第二篇北宋的理学;第三篇南宋、元代的理学;第四篇明代的理学。.