Resource allocation has always been a key technology in wireless sensor networks, but most of the traditional resource allocation algorithms are based on single interface networks. The emergence and development of multi-interface and multichannel networks solve many bottleneck problems of single interface and single channel networks, it also brings new opportunities to the development of wireless sensor networks, but the multi-interface and multichannel technology not only improves the performance of wireless sensor networks but also brings great challenges to the resource (...) allocation of wireless sensor networks. Edge computing changes the traditional centralized cloud computing processing method into a method that reduces computing storage capacity to the edge of the network and faces users and terminals. Realize the advantages of lower latency, higher bandwidth, and fast response. Therefore, this paper proposes a joint optimization algorithm of resource allocation based on edge computing. We establish a wireless sensor allocation model and then propose our algorithm model combined with the advantages of edge computing. Compared with the traditional allocation algorithm, it can further improve the resource utilization, reduce the network energy consumption, increase network capacity, and reduce the complexity of the schemes. (shrink)

Ben shu fen shang xia liang ge bu fen,Shang bian shi zhu zi yu lei wen xian yan jiu,Xia bian shi zhu zi yu lei ci hui yan jiu.Quan shu yi gong fen wei 9 zhang.Di yi zhang xu lun,Shou xian jie shao le zhu xi yu zhu zi yu lei,Qi ci jin xing le xue shu hui gu,Zong jie le jin 20 nian lai(jie zhi 2009 nian)Guo nei wai zhu zi yu lei yan jiu de sheng kuang he qu (...) de de zhu yao cheng jiu,Zui hou ti chu ben shu de yan jiu fang fa he yi yi.Di er zhang yan jiu tong xing ben zhu zi yu lei ji cheng shu zhi qian de ji ge zhong yao ban ben.Di san zhang wei zhong hua ben zhu zi yu lei yu song ke ben hui an xian sheng zhu wen gong yu lu de yi wen bi jiao.Di si zhang wei zhong hua ben zhu zi yu lei yu chao xian gu xie ben zhu zi yu lei yi wen bi jiao.Di wu zhang yan jiu zhu zi yu lei de wen xian xue jia zhi.Di liu zhang he di qi zhang ji zhong yan jiu zhu zi yu lei de fu yin ci.Di ba zhang tao lun zhu zi yu lei zhong de duo yin jie ci yu.Di jiu zhang zong jie chan shu zhu zi yu lei de yu ti te zheng,Yu yan te dian he yan jiu jia zhi. (shrink)

This book examines some possible ethical principles to resolve moral dilemmas involving water. Existing problems in current water management practices are discussed in light of these principles. Transformation of human water ethics has the potential to be far more effective, cheaper and acceptable than some existing means of “regulation”, but transformation of personal and societal ethics need time because the changes to ethical values are slow.

Recently, the pandemic caused by COVID-19 is severe in the entire world. The prevention and control of crimes associated with COVID-19 are critical for controlling the pandemic. Therefore, to provide efficient and convenient intelligent legal knowledge services during the pandemic, we develop an intelligent system for legal information retrieval on the WeChat platform in this paper. The data source we used for training our system is “The typical cases of national procuratorial authorities handling crimes against the prevention and control of (...) the new coronary pneumonia pandemic following the law”, which is published online by the Supreme People’s Procuratorate of the People’s Republic of China. We base our system on convolutional neural network and use the semantic matching mechanism to capture inter-sentence relationship information and make a prediction. Moreover, we introduce an auxiliary learning process to help the network better distinguish the relation between two sentences. Finally, the system uses the trained model to identify the information entered by a user and responds to the user with a reference case similar to the query case and gives the reference legal gist applicable to the query case. (shrink)

BackgroundCoronary heart disease is closely associated with cognitive impairment, especially in severe cases of heart failure. However, it is unclear whether cardiac systolic function plays a role in the relationship between pre-existing CHD and cognitive impairment in subjects without clinical heart failure.MethodsIn total, 208 subjects from the First Affiliated Hospital of Xi’an Jiaotong University were recruited from June 2014 to January 2015, and were divided into CHD and non-CHD groups according to the inclusion and exclusion criteria. The global cognitive function (...) of all subjects was assessed by the Mini-Mental State Examination and cognitive impairment was defined as the score lower than the cutoff value. Left ventricular ejection fraction was measured using transthoracic echocardiograms. The relationship among pre-existing CHD, LVEF, and cognitive impairment was analyzed by multivariate logistic regression.ResultsIn total, 34 subjects met the criteria of cognitive impairment. Univariate analysis showed that the cognitive impairment prevalence in the CHD group was significantly higher than that in the non-CHD group. Multivariate logistic analysis revealed that CHD was significantly associated with a higher risk of cognitive impairment after adjusting for confounds except for LVEF. However, the OR of CHD decreased when LVEF was further corrected as a continuous variable, and LVEF was negatively associated with the risk of cognitive impairment.ConclusionPre-existing CHD is associated with a higher risk of cognitive impairment, and such an association can be considerably explained by reduced LVEF. An impaired cardiac systolic function may play a key role in the relationship between CHD and cognitive impairment among patients with pre-heart failure conditions. (shrink)

The rapid improvement of technologies such as artificial intelligence in recent years has resulted in the development of smart technologies that can influence learning performance in different fields. The purpose of study is to explore the link between smart technology and learning performance. Using the S-O-R model as a framework, the researchers argue that smart technology will increase corporate trust, self-efficacy, and well-being, resulting in improved learning performance. The current model regards corporate trust and self-efficacy as relationship factors and investigates (...) their direct influence on employee well-being and learning performance and the mediating role played by these variables. Additionally, the function of employee well-being in moderating the relationship between corporate trust, self-efficacy, and employee learning performance is also explored. The respondents in the present study are made up of employees from 10 logistics companies located in China. The data analysis is conducted using the AMOS software. The results show that that smart technologies can affect learning performance through corporate trust, self-efficacy, and employee well-being. The implementation of smart technology initiatives by corporations may provide positive workplace outcomes for employees, corporations, and the relationship between employees and the companies that employ them. (shrink)

Based on ideology-infused psychological contract theory and cognitive evaluation theory, this study investigated the curvilinear relationship between ethical leadership and employee creativity. A curvilinear mediation model was proposed to explain the impact of ethical leadership on creativity, using employee intrinsic motivation as the mediator. Applying a two wave sampling design that consist 258 employees and their leaders, we found that employee creativity improved as ethical leadership increased from low to moderate levels. However, the employee creativity improvement was attenuated when ethical (...) leadership increased from moderate to high levels. Furthermore, the study also revealed that employee intrinsic motivation partially mediated this curvilinear relationship. The theoretical and managerial implications are discussed. (shrink)

IntroductionDue to the actual limitation of training conditions, the freestyle skiing aerials winter training term is short. Training tasks such as adaptability training and developing new skills are needed in summer training. When facing different training environments, freestyle skiing aerial athletes’ executive control over their abilities could be affected, which can affect their performance. Therefore, we want to research the effect of training conditions on executive control in freestyle skiing aerials athletes and its neural mechanism.Materials and methodsThirty-two freestyle skiing aerials (...) athletes were recruited. We evaluated their executive control and used fNIRS to measure oxygenated hemoglobin concentration changes in the prefrontal cortex during a rapid event-related design go/nogo task with different training condition-activated materials.ResultsAthletes’ behavior control in the summer condition has a lower accuracy than it is in the control condition. Athletes’ behavior control in the summer and winter training conditions had a longer reaction time than that in the control condition. The activation of the bilateral dlPFC and orbitofrontal cortex had a significant main effect across training conditions when freestyle skiing aerial athletes completed executive control tasks. The activation of athletes’ bilateral vlPFC and left dlPFC had an interaction between training conditions and behavioral control.ConclusionDifferent training conditions can lead to freestyle skiing aerial athletes executive control ability to drop, players in different training conditions show less activation on both sides of the vlPFC and orbitofrontal. The bilateral vlPFC and left dlPFC have an integrated effect on behavior inhibition across training conditions. (shrink)

Action video game (AVG) has attracted increasing attention from both the public and from researchers. More and more studies found video game training improved a variety of cognitive functions. However, it remains controversial whether healthy adults can benefit from AVG training, and whether young and older adults benefit similarly from AVG training. In the present study, we aimed to quantitatively assess the AVG training effect on the cognitive ability of adults and to compare the training effects on young and older (...) adults by conducting a meta-analysis on previous findings. We systematically searched video game training studies published between January 1986 and July 2015. Twenty studies were included in the present meta-analysis, for a total of 313 participants included in the training group and 323 participants in the control group. The results demonstrate that healthy adults achieve moderate benefit from AVG training in overall cognitive ability and moderate to small benefit in specific cognitive domains. In contrast, young adults gain more benefits from AVG training than older adults in both overall cognition and specific cognitive domains. Age, education, and some methodological factors, such as the session duration, session number, total training duration, and control group type, modulated the training effects. These meta-analytic findings provide evidence that AVG training may serve as an efficient way to improve the cognitive performance of healthy adults. We also discussed several directions for future AVG training studies. (shrink)

The aim of our research is to demonstrate that intentionality as a major property of consciousness and as a basic state of mind plays an important role in all the activities in which the subject is related to the objective world. This paper is based on John Searle’s theory of intentionality. Both ideological cognition and practical activity are object oriented activities. However, the objects targeted by them and the ways they are associated with their subjects are different. The function of (...) intentionality of ideological cognition is mainly reflected on its directedness, whereas in practical activities—on its motivating and regulating capacities. (shrink)

Electroacupuncture (EA) and electroconvulsive therapy (ECT) are often used in the management of schizophrenia. This study sought to determine whether additional EA and ECT could augment antipsychotic response and reduce related side effects. In this retrospective controlled study, 287 hospitalized schizophrenic patients who received antipsychotics (controls, n = 50) alone or combined with EA (n = 101), ECT (n = 55) or both (EA+ECT, n = 81) were identified. EA and ECT were conducted for 5 and 3 sessions per week, (...) respectively, with a maximum of 12 sessions for ECT during hospitalization. The Scale for the Assessment of Positive Symptoms (SAPS) and Scale for the Assessment of Negative Symptoms (SANS) were used to assess the severity of psychotic symptoms. Clinical response on SAPS and SANS, weight gain, and adverse events were compared. Survival analysis revealed that the ECT and EA+ECT groups had markedly greater clinical response rate than controls on SAPS [72.7% and 90.1% vs. 64.0%; relative risk (RR), 1.974 and 2.628, respectively, P ≤ 0.004] and on SANS (67.3% and 70.4% vs. 42.0%; RR, 1.951 and 2.009, respectively, P ≤ 0.015). A significantly greater response rate on SANS than controls was also observed in the EA group (64.4% versus 42.0%; RR = 1.938, P = 0.008). EA-containing regimens remarkably reduced weight gain and incidences of headache, insomnia, dry mouth, and electrocardiographic abnormalities. These results suggest that EA and ECT can serve as additional treatment for enhancing antipsychotic response and reduce the side effects in hospitalized patients with schizophrenia. (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)

This study examined factors including health-related anxiety, preexisting misinformation beliefs, and repeated exposure contributing to individuals’ acceptance of health misinformation. Through a large-scale online survey, this study found that health-related anxiety was positively associated with health misinformation acceptance. Preexisting misinformation beliefs, as well as repeated exposure to health misinformation, were both positively associated with health misinformation acceptance. The results also showed that demographic variables were significantly associated with health misinformation acceptance. In general, females accepted more health misinformation compared to males. (...) Participants’ age was negatively associated with health misinformation acceptance. Participants’ education level and income were both negatively associated with their acceptance of health misinformation. (shrink)

BackgroundBilateral cerebral palsy is the most common type of CP in children and is often accompanied by different degrees of communication impairment. Several studies have attempted to identify children at high risk for communication impairment. However, most prediction factors are qualitative and subjective and may be influenced by rater bias. Individualized objective diagnostic and/or prediction methods are still lacking, and an effective method is urgently needed to guide clinical diagnosis and treatment. The aim of this study is to develop and (...) validate an objective, individual-based model for the prediction of communication impairment in children with BCP by the time they enter school.MethodsA multicenter prospective cohort study will be conducted in four Chinese hospitals. A total of 178 children with BCP will undergo advanced brain magnetic resonance imaging at baseline. At school entry, communication performance will be assessed by a communication function classification system. Three-quarters of children with BCP will be allocated as a training cohort, whereas the remaining children will be allocated as a test cohort. Multivariate lesion- and connectome-based approaches, which have shown good predictive ability of language performance in stroke patients, will be applied to extract features from MR images for each child with BCP. Multiple machine learning models using extracted features to predict communication impairment for each child with BCP will be constructed using data from the training cohort and externally validated using data from the test cohort. Prediction accuracy across models in the test cohort will be statistically compared.DiscussionThe findings of the study may lead to the development of several translational tools that can individually predict communication impairment in children newly diagnosed with BCP to ensure that these children receive early, targeted therapeutic intervention before they begin school.Trial registrationThe study has been registered with the Chinese Clinical Trial Registry. (shrink)

The generalized Brans–Dicke theory (GBD), as one of the modified gravitational theories, was proposed previously and some interesting properties were found in this theory. Here we investigate the traversable-wormhole physics for GBD theory. Firstly, we derive the gravitational field equation in the framework of GBD wormhole geometry. The traversable wormhole could be gained in this theory. Secondly, using the classical reconstruction technique we originally derive an Lagrangian function for describing gravity in GBD theory. And the derived Lagrangian function for gravity (...) could be satisfied with the requirement of the viable conditions, such as the local gravity tests and the cosmological constraints, etc. Thus, the viable model for cosmology, local gravity and traversable WH can be unified in a uniform Lagrangian quantity within the framework of GBD theory. Thirdly, given that the violation of the energy conditions (ECs) often induce some problems in theory, we explore the ECs of matter in the traversable wormhole. It is shown that the null EC, the weak EC and the dominated EC for the matter can be satisfied in the traversable-wormhole physics of GBD theory, which are different from the results given in GR. It seems that the theory of GBD owns the more logic technically and consistency formally than the theory of GR. Fourthly, some other properties of GBD traversable WH are explored, such as the total gravitational energy, the volume integral quantifier, the dynamical stability of the anisotropic matter, and the difference of the propagation of sound within the matter configuration. The results support the GBD to provide an interesting candidate for traversable WH. (shrink)

Background: Cognitive impairment is one of the core symptoms of schizophrenia, which is considered to be significantly correlated to prognosis. In recent years, many studies have suggested that metabolic disorders could be related to a higher risk of cognitive defects in a general setting. However, there has been limited evidence on the association between metabolism and cognitive function in patients with early-stage schizophrenia.Methods: In this study, we recruited 172 patients with early-stage schizophrenia. Relevant metabolic parameters were examined and cognitive function (...) was evaluated by using the MATRICS Consensus Cognitive Battery (MCCB) to investigate the relationship between metabolic disorder and cognitive impairment.Results: Generally, the prevalence of cognitive impairment among patients in our study was 84.7% (144/170), which was much higher than that in the general population. Compared with the general Chinese setting, the study population presented a higher proportion of metabolic disturbance. Patients who had metabolic disturbance showed no significant differences on cognitive function compared with the other patients. Correlation analysis showed that metabolic status was significantly correlated with cognitive function as assessed by the cognitive domain scores (p < 0.05), while such association was not found in further multiple regression analysis.Conclusions: Therefore, there may be no association between metabolic disorder and cognitive impairment in patients with early-stage schizophrenia.Trial Registration: Clinicaltrials.gov, NCT02880462. Registered August 26, 2016. (shrink)

In order to investigate the competitive psychology of college students in the current context of fierce social competition, this study compiled a competition psychology scale for college students [i.e., the Competition Psychology Scale for College Students ]. The scale was administered online to 628 university students in different regions of China. After item analysis, reliability analysis, and validity analysis, a 6-item scale was finally formed. CPS-CS contains four dimensions: hypercompetitive attitude, competitive motivation, personal development, competitive attitude, and competitive interpersonal relationships. (...) The reliability and validity of the CPS-CS developed in this research meet the requirements of psychometrics. (shrink)

Based on 2010 to 2019 Chinese outward foreign direct investment panel data from 39 host countries, this paper studies the relationships between host country cultural characteristics and Chinese OFDI. The OLS regression results show that the cultural tolerance and trust in the host countries are significantly positively correlated with Chinese OFDI, which are robust according to the system GMM tests. Further analysis reveals that cultural tolerance is more positively related to Chinese OFDI in host countries with higher legislation and economic (...) freedom, while cultural trust is positively associated with Chinese OFDI in host countries with lower legislation and economic freedom. In addition, higher cultural tolerance and trust promote Chinese OFDI in countries with greater cultural distance. Unlike traditional studies based on cultural distance in international trade, using more representative cultural characteristics, this paper provides references to Chinese OFDI decision-making based on the root characteristics associated with heterogeneous cultural influences. (shrink)

Accurate and rapid defect identification based on pulsed eddy current testing plays an important role in the structural integrity and health monitoring of in-service equipment in the renewable energy system. However, in conventional data-driven defect identification methods, the signal feature extraction is time consuming and requires expert experience. To avoid the difficulty of manual feature extraction and overcome the shortcomings of the classic deep convolutional network, such as large memory and high computational cost, an intelligent defect recognition pipeline based on (...) the general Warblet transform method and optimized two-dimensional DCNN is proposed. The GWT method is used to convert the one-dimensional PECT signal to a 2D grayscale image used as the input of 2D DCNN. A compound method is proposed to optimize the baseline VGG16, a well-known DCNN, from four aspects including reducing the input size, adding batch normalization layer after every convolutional layer and fully connection layer, simplifying the FCs, and removing unimportant filters in Convs so as to reduce memory and computational costs while improving accuracy. Through a pulsed eddy current testing experiment considering interference factors including liftoff and noise, the following conclusion can be obtained. The time-frequency representation obtained by the GWT method not only has excellent ability in terms of the transient component analysis but also is less affected by the reduction of image size; the proposed optimized DCNN can accurately identify defect types without manual feature extraction. And compared to the baseline VGG16, the accuracy obtained by the optimized DCNN is improved by 7%, to about 99.58%, and the memory and computational cost are reduced by 98%. Moreover, compared with other well-known DCNNs, such as GoogLeNet, Inception V3, ResNet50, and AlexNet, the optimized network has significant advantages in terms of accuracy and computational cost, too. (shrink)

Pellet is widely used in blast furnace ironmaking. Pellet quality affects the effect of ironmaking, the existing control system of grating-rotary kiln mainly adopts manual control mode, and the quality of pellet production largely depends on the experience, fatigue, and sense of responsibility of the site operators. The use of the Internet of things technology in the integration and improvement of enterprise information level, to achieve fine, intelligent production management, at the same time, is conducive to promoting steel enterprises to (...) reduce costs and increase efficiency, energy conservation and emission reduction, transformation and upgrading, and taking a new road to industrialization. According to the working principle and technological characteristics of the grate-rotary kiln at all stages, this paper designs the management system of firing pellets based on convolutional neural network and IoT technology, so as to realize automatic recognition of image data obtained by the perceptual layer and make an intelligent analysis of it. The system can classify the working conditions of the current equipment, so as to judge whether the production process parameters of the grate-rotary kiln are up to the standard, thus achieving the goal of controlling the quality of the finished pellet. (shrink)

With the rapid development of the Internet, recommendation systems have received widespread attention as an effective way to solve information overload. Social tagging technology can both reflect users’ interests and describe the characteristics of the items themselves, making group recommendation thus becoming a recommendation technology in urgent demand nowadays. In traditional tag-based recommendation systems, the general processing method is to calculate the similarity and then rank the recommended items according to the similarity. Without considering the influence of continuous user behavior, (...) in this article, we propose a personalized recommendation algorithm based on social tags by combining the ideas of Markov chain and collaborative filtering. This algorithm splits the three-dimensional relationship of into two two-dimensional relationships of and. The user’s interest degree to the tags is calculated by the Markov chain model, and then the items corresponding to them are matched by the recommended tag set. The influence between tags is used to model the satisfaction of items based on the correlation between the tags contained in the matched items, and collaborative filtering is used to complete the sparse values when calculating the interest and satisfaction between user–tags and user–items to improve the accuracy of recommendations. The experiments show that in the publicly available dataset, the personalized recommendation algorithm proposed in this article has significantly improved in accuracy and recall rate compared with the existing algorithms. (shrink)

The rapid worldwide spread of COVID-19 forced many countries to enforce complete lockdown and strict quarantine policies. The strict lockdown and quarantine affect the psychological state of people toward cryptocurrency. The current research aims to examine the effect of COVID-19 on Bitcoin prices concerning cumulative deaths and confirmed cases. The research comprises daily data from January 20, 2020, to April 30, 2020, during the initial worldwide breakout of COVID-19. This research employed the augmented Dickey-Fuller test to check the stationarity of (...) data, the co-integration test for the interdependency of variables, and the vector error correction model for identifying the direction and long or short-run relationship between Bitcoin prices and COVID-19. The research results show that Bitcoin prices are negatively significant and related to COVID-19 in the short-run. A unidirectional relationship between Bitcoin prices and cumulative deaths is also observed. Investors and the public’s psychological state were positively significant to Bitcoin prices in the long-term because of cashless transactions, unbanked, and less risky virus traveling. The second reason behind the positive psychological relation is un-centralization and easy-to-make payments by Bitcoin. This study’s finding provides timely evidence to decision-makers on Bitcoin price volatility and its impacts on the public’s psychological states regarding COVID-19. (shrink)

Background: It has been reported that type 2 diabetes is associated with olfactory identification impairments and cognitive decline. However, the relationship between OI impairments and cognitive decline is largely unknown in T2DM patients.Methods: Sixty-eight T2DM patients and 68 healthy controls underwent 3D-T1 MRI scans, olfactory and cognitive assessments. The cortical thickness of olfaction-related brain regions, olfactory and cognitive scores were compared between groups. Correlation analyses were carried out among cognition, olfaction, and cortical thickness of olfaction-related brain regions.Results: First, the cognitive (...) and olfactory test scores of T2DM patients were lower than healthy subjects. Second, higher olfactory scores were associated with increased cortical thickness in the left parahippocampal gyrus and bilateral insula in T2DM. Third, higher olfactory scores were associated with higher cognitive performance in T2DM. Fourth, some cognitive performances were related to cortical thickness in the left parahippocampal gyrus and left insula in T2DM.Conclusion: These findings indicated that olfactory dysfunction may be useful for future applications that attempt to predict cognitive decline or develop tailored therapies in T2DM patients. (shrink)

Voluntary work behavior refers to spontaneous workplace behaviors that extend beyond role norms, including extra-role behaviors that benefit the organization and negative behaviors that may harm the organization. This study examined the relationship between self-control and VWB and the mediating role of job satisfaction. A total of 1,101 full-time employees from China completed a battery of self-report measures online. The results show that self-control positively predicts employees' OCB and negatively predicts employees' CWB. Moreover, job satisfaction significantly mediates the relationship between (...) self-control and OCB/CWB. The results confirm that employees with high self-control are more public-spirited, which previous studies have described as being “highly committed” or “less harmful”. This finding closely relates to the observation that employees with high self-control tend to have more satisfying work outcomes or higher workplace status than those with low self-control. (shrink)

BackgroundIn the early days of COVID-19 outbreak, the normally orderly health system was severely challenged by large numbers of feverish patients and shortage of healthcare workers. The outbreak played a harmful role in the mental health of these healthcare workers.ObjectiveWe aim to assess the prevalence of moderate or severe anxiety and depression symptoms of healthcare workers in different regions during COVID-19 disaster and identify the potential risk factors.MethodsWe did a cross-sectional study on ADS of healthcare workers in epicenter-Hubei province and (...) regions in lower epidemic-other provinces by questionnaire online. The data of ADS, the demographic characteristics, occupational exposure, physical condition, family situation, and coping styles were collected and analyzed.ResultsA total of 24.68% of the respondents had experienced moderate or severe ADS. Moderate or severe ADSs were in a higher prevalence in Hubei than other provinces. Suspicious symptoms on their own and in family members were independent risk factors of moderate or severe ADS of all health workers. Working on the frontline was the independent risk factor for participants in Hubei province, whereas quarantine was the independent risk factor for those in other provinces. Moreover, among all participants, those with negative coping style were more than four times more likely to have moderate or severe ADS than those with positive coping style.ConclusionModerate or severe ADSs were in a higher prevalence in healthcare workers of Hubei province during COVID-19 outbreak. The coping style may have major impact on ADS in such situation. (shrink)

The Temporal Experience of Pleasure Scale (TEPS) is a self-report instrument assessing pleasure experience. The present study aimed to confirm the factor model of the Chinese version of TEPS and test measurement invariance of the scale across gender in Chinese university students. Participants were 2977 (51% female) undergraduates aged from 16 to 27 years (Mean age = 18.9 years). Results indicated that the revised four-factor structure of the TEPS had acceptable fit in the total sample and in gender groups. Furthermore, (...) configural, metric and partial scalar invariance across gender were established. Two of the items (item 4 and 8) demonstrated different intercepts and women scored higher than men on both items. With partial scalar invariance demonstrated, test of differences in latent means indicated that men had lower levels of pleasure when compared with women. To our knowledge, this study is the first attempt to test the measurement invariance of the TEPS across gender, which provides support for future research that involves examining hedonic capacity in Chinese men and women. (shrink)

The Iowa Gambling Task (IGT) simulates uncertain gains and losses in real life situations and thus is a good measure of uncertain decision making. The role of working memory (WM) in IGT performance still remains unclear. The present study aimed to examine the effect of WM on IGT performance. Three groups of participants matched on gender ratio were randomly assigned to no WM load, low WM load, and high WM load conditions. Initially the three groups did not show significant difference (...) in WM capacity. They finished a modified version of IGT and then their implicit learning effect and explicit cognition on IGT were assessed. Results indicated a linear increasing trend of IGT performance among high WM load, low WM load and no WM load groups; participants in the no WM load and low WM load groups revealed implicit learning effect, while participants in the high WM load group did not; all participants showed explicit cognition on IGT to the same level. These results suggested that participants in the high WM load group showed good explicit cognition to IGT but showed poor performance. This pattern is similar to frontal patients. Further studies should be conducted to explore this issue. (shrink)

Information on age-related differences in affective meanings of words is widely used by researchers to study emotions, word recognition, attention, memory, and text-based sentiment analysis. To date, no Chinese affective norms for older adults are available although Chinese as a spoken language has the largest population in the world. This article presents the first large-scale age-related affective norms for 2,061 four-character Chinese words (AANC). Each word in this database has rating values in the four dimensions, namely, valence, arousal, dominance, and (...) familiarity. We found that older adults tended to perceive positive words as more arousing and less controllable and evaluate negative words as less arousing and more controllable than younger adults did. This indicates that the positivity effect is reliable for older adults who show a processing bias toward positive vs. negative words. Our AANC database supplies valuable information for researchers to study how emotional characteristics of words influence the cognitive processes and how this influence evolves with age. This age-related difference study on affective norms not only provides a tool for cognitive science, gerontology, and psychology in experimental studies but also serves as a valuable resource for affective analysis in various natural language processing applications. (shrink)

In the field of natural language processing, the task of sensitive information detection refers to the procedure of identifying sensitive words for given documents. The majority of existing detection methods are based on the sensitive-word tree, which is usually constructed via the common prefixes of different sensitive words from the given corpus. Yet, these traditional methods suffer from a couple of drawbacks, such as poor generalization and low efficiency. For improvement purposes, this paper proposes a novel self-attention-based detection algorithm using (...) the implementation of graph convolutional network. The main contribution is twofold. Firstly, we consider a weighted GCN to better encode word pairs from the given documents and corpus. Secondly, a simple, yet effective, attention mechanism is introduced to further integrate the interaction among candidate words and corpus. Experimental results from the benchmarking dataset of THUC news demonstrate a promising detection performance, compared to existing work. (shrink)

Women account for a large proportion of the hotel industry. Work-life conflict has become one of the main obstacles to the organizational commitment of women. Thus, this study investigates the relationship for women between work-life balance, as an independent variable, and organizational commitment, as a dependent variable. Specifically, we examine women's work-life balance in the hospitality industry and compare women's organizational commitment under different levels of work-life balance. Then, we assess whether women's work-life balance and organizational commitment are associated with (...) their sociodemographic characteristics. Data were collected from 525 women employees in China. Multiple linear regression analyses were conducted to identify the relationship between work-life balance and organizational commitment. The results showed that work-life balance had a significant effect on organizational commitment. There was also a significant relationship between women's sociodemographic characteristics, work-life balance, and organizational commitment. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)