In this study, we first introduce polygonal cylinder and torus using Cartesian products and topologically identifications and then find their Wiener and hyper-Wiener indices using a quick, interesting technique of counting. Our suggested mathematical structures could be of potential interests in representation of computer networks and enhancing lattice hardware security.

Language teacher research is conducive to the development of teachers’ teaching skills and professional careers. Thus, many English teacher education programs require student teachers to do research. However, some empirical findings suggest that English as a foreign language student teachers lack research motivation. Consequently, finding suitable interventions to increase their research motivation has become increasingly necessary. In light of the importance of research motivation intervention, this study involved designing an experiment to identify the effect of a value and interest intervention (...) including the sharing of positive research experiences to improve student teachers’ research motivation. Quantitative questionnaires and qualitative semi-structured interviews were used to gather evidence on the change in student teachers’ research motivation during the intervention. The interview data revealed that student teachers’ research motivation was influenced by their belief in the value of research to their teaching practice. The experiment results suggested that student teachers’ intrinsic and extrinsic research motivations both increased after the intervention. However, the intervention was not effective in curbing their failure avoidance tendency. Pedagogical implications of the results are discussed at the end of this article. (shrink)

This paper analyses the evolutionary characteristics of the interprovincial population mobility network structure in China and explores the roles of provinces from 2010 to 2015. By constructing the interprovincial population mobility network, we examine the provinces’ functions during periods of population mobility through population mobility diversity, population mobility, and population mobility intermediation. The results show that the coverage and tightness of the interprovincial population mobility network were influenced by national economic development, increasing steadily from 2010 to 2014 and then suddenly (...) falling in 2015. The regions that played essential roles in the province’s mobility diversity and intermediation showed a dispersion trend. In contrast, areas that played a vital role in the inflows or outflows were relatively concentrated and stable. Additionally, this work further explores how economic factors, e.g., GDP, residents’ consumption levels, total population, unemployment rate, and consumer price index, are used as independent variables to analyse the provinces’ roles in the interprovincial population mobility network. The analysis shows that the inflow or outflow volumes are easily affected by the five indices. These five indices are significantly related to network role indicators to different extents. (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)

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)

The impact of bilingual education and bilingual experience on working memory has been an important and controversial issue in the field of psycholinguistics. Taking Chinese-English bilinguals as an example, this study aims to investigate the differences in emotional working memory between proficient and non-proficient bilinguals by using delayed matching-to-sample task paradigm and more complex n-back task in the context of emotion. The results show that proficient bilinguals have better performance on both of the two working memory tasks than non-proficient bilinguals, (...) and the advantage effects were more apparent under high memory load conditions. Besides, the negative emotion context has a positive impact on complex n-back tasks. This study supports the notion that bilingual experience can promote the development of an individual’s cognitive ability and enable individuals to possess more advantages in working memory even in the presence of emotional distractions. (shrink)

ObjectiveTo investigate the instant impact of hemodialysis on the cerebral morphological measurements of patients with end-stage renal disease.Materials and methodsTwenty-five patients undergoing maintenance HD and twenty-eight age-, sex-, and education-matched healthy control were included. The HD group and HC group had 3D high-resolution structural magnetic resonance imaging scans twice and once, respectively. Both groups underwent neuropsychologic tests. The morphological measurements of structural MRI were measured using CAT12 and these measures were compared among three groups. The relationship between morphological measures and (...) clinical parameters and neuropsychological tests were investigated through multiple regression analysis.ResultsCompared to the HC group, the cortical thickness before HD significantly decreased in the bilateral temporal lobe and significantly decreased in the left superior temporal gyrus after HD. The cortical thickness significantly increased in the bilateral temporal lobe, frontal lobe and occipital lobe after HD compared to before HD. The sulcus depth in the bilateral insula, frontal lobe, and parietal lobe after HD significantly increased compared to before HD. No significant differences in sulcus depth between HD and HC were detected. After HD, the cortical thickness of the right parsopercularis was positively correlated with the number connection test-A. Cortical thickness in multiple regions were positively correlated with blood flow velocity and cortical thickness in the left parahippocampal gyrus was negatively correlated with ultrafiltration volume. Patients showed better performance in the digit symbol test and line tracing test after HD compared to before HD, but there were no significant differences in the comparison of neuropsychologic tests between patients and HC.ConclusionThe instant morphological changes were captured during a single hemodialysis in HD patients. There was an association between these instant changes in the brain and clinical parameters and neuropsychologic tests. This work implied the instant impact of a single hemodialysis impact on the brain in HD patients. (shrink)

OBJECTIVE: To report and analyse the pattern of end-of-life decision making for terminal Chinese cancer patients. DESIGN: Retrospective descriptive study. SETTING: A cancer clinical trials unit in a large teaching hospital. PATIENTS: From April 1992 to August 1997, 177 consecutive deaths of cancer clinical trial patients were studied. MAIN MEASUREMENT: Basic demographic data, patient status at the time of signing a DNR consent, or at the moment of returning home to die are documented, and circumstances surrounding these events evaluated. RESULTS: (...) DNR orders were written for 64.4% of patients. Patients in pain (odds ratio 0.45, 95% CI 0.22-0.89), especially if requiring opioid analgesia (odds ratio 0.40, 95% CI 0.21-0.77), were factors associated with a higher probability of such an order. Thirty-five patients were taken home to die, a more likely occurrence if the patient was over 75 years (odds ratio 0.12, 95% CI 0.04-0.34), had children (odds ratio 0.14, 95% CI 0.02-0.79), had Taiwanese as a first language (odds ratio 6.74, 95% CI 3.04-14.93), or was unable to intake orally (odds ratio 2.73, 95% CI 1.26-5.92). CPR was performed in 30 patients, none survived to discharge. CONCLUSIONS: DNR orders are instituted in a large proportion of dying Chinese cancer patients in a cancer centre, however, the order is seldom signed by the patient personally. This study also illustrates that as many as 20% of dying patients are taken home to die, in accordance with local custom. (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 the process of rapid urbanization, urban heat island effect has been showing more and more significant impacts on human well-being. Therefore, a more detailed understanding of the impact of three-dimensional building morphology on UHI effect across a continuum of spatial scales will be necessary to guide and improve the human settlement.This study selected 31 provincial capital cities of mainland China to analyze the impacts of the 3D building morphology, including the number, area, height, volume, and the surface area of (...) the buildings, on the land surface temperature. By exploring how the influence of 3D building morphology on LST changes with the increase of spatial scale, this study finally recognized which 3D building morphology index is the most significant index affecting LST in different cities, and which spatial scale these 3D building morphology indexes have the most significant impact on LST. The results showed that the building area is the most important 3D building morphology parameter affecting the LST, while the building height has the slightest influence on the LST. These effects are more significant in the spatial scale of 150 m–540 m, and the spatial scale increases with the increase of building areas in developed cities. These results highlight the necessity of considering fine-grained management in the governance and alleviating of the urban thermal environment through urban planning and urban renewal strategies. (shrink)

本书是一本研究建筑学的书籍, 全书包括有《现象学与建筑学的思考》、《建筑中的神性》等多篇文章.

Linear regression and its variants have been widely used for classification problems. However, they usually predefine a strict binary label matrix which has no freedom to fit the samples. In addition, they cannot deal with complex real-world applications such as the case of face recognition where samples may not be linearly separable owing to varying poses, expressions, and illumination conditions. Therefore, in this paper, we propose the kernel negative ε dragging linear regression method for robust classification on noised and nonlinear (...) data. First, a technique called negative ε dragging is introduced for relaxing class labels and is integrated into the LR model for classification to properly treat the class margin of conventional linear regressions for obtaining robust result. Then, the data is implicitly mapped into a high dimensional kernel space by using the nonlinear mapping determined by a kernel function to make the data more linearly separable. Finally, our obtained KNDLR method is able to partially alleviate the problem of overfitting and can perform classification well for noised and deformable data. Experimental results show that the KNDLR classification algorithm obtains greater generalization performance and leads to better robust classification decision. (shrink)

Cross-shareholding is a new type of strategic means for capital operation and is an important component of corporate governance. With the increasing complexity of business motivation, the structure of a cross-shareholding network is becoming more intricate, and it exposes various important local patterns with different economic functions. The goal of this paper is to uncover investment mechanisms and economic functions implied in cross-shareholding networks by analyzing the local characteristic patterns of company interactions. In this paper, we construct the CSNs of (...) listed companies and extract the directed triadic motifs to reveal the evolutionary characteristics of local investment patterns at the company and industry levels. On the company level, we find that companies tend to form V-shaped structures with other companies, but bidirectional shareholding patterns and circular relationships in the triads are scarce. On the industry level, we identify the characteristic linking patterns of some industries with a role analysis of the industries. Furthermore, we detect the evolutionary characteristics of industry interrelationships in three implied patterns. Such a motif evolution analysis may provide valuable information for investors and supervisory departments that make decisions about investment portfolios and policy. Meanwhile, this study is also helpful for exploring the implied information in other empirical networks. (shrink)

The study of cyber-attacks, and in particular the spread of attack on the power cyber-physical system, has recently attracted considerable attention. Identifying and evaluating the important nodes under the cyber-attack propagation scenario are of great significance for improving the reliability and survivability of the power system. In this paper, we improve the closeness centrality algorithm and propose a compound centrality algorithm based on adaptive coefficient to evaluate the importance of single-layer network nodes. Moreover, we quantitatively calculated the decouple degree of (...) cascading failures caused by exposed nodes formed by attack propagation. At last, experiments based on the IEEE 57 test system show that the proposed compound centrality algorithm can match the cyber-attack propagation scenario well, and we give the importance values of the nodes in a specific attack scenario. (shrink)

The present study critically evaluates whether school leadership influences student learning homogenously regardless of school contexts. It examined relationships between four principal leadership variables (envisioning, instructional management, promoting professional development, empowerment) and two types of student outcomes (enjoyment in learning science, science achievement,) in different school contexts (in terms of the availability of science resources, quality of science teachers, and school socioeconomic status (SES)). The sample comprised 248,620 students and 9,370 principals in 35 developed countries who participated in the Programme (...) for International Student Assessment (PISA) 2015. Latent profile analysis (LPA) showed that schools operated in three types of school contexts with different levels of science resources, proportion of quality science teachers, and school SES. There were also differences in the pattern of leadership practices across the three types of school contexts. Three-level hierarchical linear modeling (HLM) showed that among the four leadership variables, only instructional management was positively associated with students’ enjoyment of science in schools with less science resources and quality science teachers. Therefore, instructional management had compensatory effects for students in less-endowed schools. In contrast, principal leadership related to envisioning, teacher professional development, and empowerment was not positively related to students’ science learning in all three school contexts. (shrink)

Conflicts in land exploration are incisive social problems which have been the subject in many studies. Risk assessment of land conflicts is effective to resolve such problems. Specifically, fuzzy mathematics and the analytic hierarchy process were combined together to evaluate risk in land conflicts in our work, which is proved useful to solve uncertainty and imprecision problems. Based on the analysis of the principles for the risk assessment of a land conflicts index system, a set of risk assessment indexes using (...) the fuzzy analytic hierarchy process was presented. The results show that the overall risk is at medium level, and the risk of the feasibility index and controllability index need to be paid more attention to. The contribution of this article is reflected in two aspects: the application of FAHP in risk assessments of land conflicts is effective and valid; it is helpful for governments to establish a stricter management system of work safety for conflicts in land exploration based on the risk assessment results. (shrink)

The fire safety of industrial buildings has always been a great concern. An excellent evacuation indicator system can guide the personnel to escape quickly, thus reducing the casualties. In this study, we present a virtual simulation fire scene based on virtual reality to explore the impact of different colors, brightness values, and flashing frequencies on escape time in case of fire emergencies. The presented scene can help shorten the time required for evacuation in an industrial plant by identifying the escape (...) path under the fire and smoke environment and improve the escape efficiency. The results show that the green color is the most suitable color for evacuations; the escape efficiency increases with an increase in brightness, and there is no significant difference between the escape times under high and medium brightness; the evacuation time decreases with an increase in the flicker frequency. Based on these experimental results, the fire evacuation indicating system is designed. A virtual reality verification experiment is used to compare the escape efficiency of the improved design with an original factory’s indicating system. The verification results show that the improved scheme reduces the evacuation time and significantly improves the psychological stress on the evacuees. This work provides a theoretical basis for safe evacuation designs. (shrink)

ObjectiveThis study aimed to examine the effectiveness and safety of the Brain-computer interface in treatment of upper limb dysfunction after stroke.MethodsEnglish and Chinese electronic databases were searched up to July 2021. Randomized controlled trials were eligible. The methodological quality was assessed using Cochrane’s risk-of-bias tool. Meta-analysis was performed using RevMan 5.4.ResultsA total of 488 patients from 16 RCTs were included. The results showed that the meta-analysis of BCI-combined treatment on the improvement of the upper limb function showed statistical significance [standardized (...) mean difference : 0.53, 95% CI: 0.26–0.80, P < 0.05]; BCI treatment can improve the abilities of daily living of patients after stroke, and the analysis results are statistically significant ; and the BCI-combined therapy was not statistically significant for the analysis of the Modified Ashworth Scale.ConclusionThe meta-analysis indicates that the BCI therapy or BCI combined with other therapies such as conventional rehabilitation training and motor imagery training can improve upper limb dysfunction after stroke and enhance the quality of daily life. (shrink)

A human driver and an automated driving system might share control of automated vehicles in the near future. This raises many concerns associated with the assignment of responsibility for negative outcomes caused by them; one is that the human driver might be required to bear the brunt of moral and legal responsibilities. The psychological consequences of responsibility misattribution have not yet been examined. We designed a hypothetical crash similar to Uber’s 2018 fatal crash. We incorporated five legal responsibility attributions. Participants (...) chose their preferred liability attribution and then were randomly assigned into one of the five actual liability attribution conditions. They then responded to a series of questions concerning liability assignment, the crash, and AVs. Slightly more than 50% of participants thought that the human driver should bear full or primary liability. Legal responsibility misattribution negatively influenced these mentioned responses, regardless of overly attributing human or manufacturer liability. Overly attributing human liability had more negative influences. Improper liability attribution might hinder the adoption of AVs. Public opinion should not be ignored in developing a legal framework for AVs. (shrink)

The complexity of the Hedgehog (Hh) signaling cascade has increased over the course of evolution; however, it does not suffice to accommodate the dynamic yet robust requirements of differential Hh signaling activity needed for embryonic development and adult homeostatic maintenance. One solution to solve this dilemma is to apply multiple forms of post‐translational modifications (PTMs) to the core Hh signaling components, modulating their abundance, localization, and signaling activity. This review summarizes various forms of protein modifications utilized to regulate Hh signaling, (...) with a special emphasis on crosstalk between different forms of PTMs and their feedback regulation by Hh signaling. (shrink)

We propose the cosine similarity measures for intuitionistic fuzzy linguistic sets and interval-valued intuitionistic fuzzy linguistic sets, which are expressed by the linguistic scale function based on the cosine function. Then, the weighted cosine similarity measure and the ordered weighted cosine similarity measure for IFLSs and IVIFLSs are introduced by taking into account the importance of each element, and the properties of the cosine similarity measures are also given. The main advantage of the proposed cosine similarity measures is that the (...) decision-makers can flexibly select the linguistic scale function depending on the actual semantic situation. Finally, we present the application of the cosine similarity measures for intuitionistic fuzzy linguistic term sets and interval-valued intuitionistic fuzzy linguistic term sets to pattern recognition and medical diagnosis, and the existing cosine similarity measures are compared with the proposed cosine similarity measures by the illustrative example. (shrink)

The increase of ETC vehicles on expressways has changed the proportion of ETC/MTC lanes at toll stations. Based on a driving simulator, three toll gate lane warning sign schemes were proposed in this study. Driving simulation experiments were conducted to study the influence of figures in warning signs at the manual toll station on the lane change timing of drivers. It was found that the addition of arrows to the warning signs can significantly shorten the response time and guide the (...) driver to make lane change decisions earlier to reduce the congestion between MTC vehicles and the mainline ETC vehicles at the toll plaza, thereby improving the traffic capacity and safety. (shrink)

ObjectivesWuhan is the city where coronavirus disease was first reported and developed into a pandemic. However, the impact of the prolonged COVID-19 pandemic on medical staff burnout remains limited. We aimed to identify the prevalence and major determinants of burnout among medical staff 1 year after the beginning of the COVID-19 pandemic in Wuhan, China.Materials and MethodsA total of 1,602 medical staff from three hospitals in Wuhan, China, were included from November 1–28, 2021. Chi-square tests were conducted to compare the (...) prevalence of burnout across groups based on sociodemographic and professional characteristics. A multivariate analysis was performed using a forward stepwise logistic regression model.ResultsApproximately 37.39% of the medical staff experienced burnout 1 year after COVID-19 pandemic. Emotional exhaustion was the most common symptom of burnout, with 1,422 participants reporting a severe EE. Burnout was associated with insufficient social support and “neutral” or “dissatisfied” patient-physician relationships. Respondents who participated in the care of COVID-19 patients had a higher risk of burnout symptoms than those who did not participate. In particular, mental resilience was negatively associated with burnout among the medical staff.ConclusionNearly two-fifths of the participants had symptoms of burnout, with reduced personal accomplishment being the predominant symptom 1 year after COVID-19. Healthcare organizations should regularly measure and monitor burnout among the medical staff. In addition, creating positive work environments and improving the mental resilience of medical staff may be effective ways to reduce burnout. (shrink)

Based on early experiences and current conditions, a future time perspective influences college students’ behaviors, while psychological violence critically threatens college students’ health. This study explored the relationship between a future time perspective and the psychological violence of perpetrators based on an online investigation of 1424 college students aged 17 to 31 in China. The results showed that a future time perspective is significantly positively associated with psychological violence. Positive future orientation is negatively associated with psychological violence. Negative and confused (...) future orientations are positively associated with psychological violence. These findings support the need to introduce an intervention regarding a future time perspective to reduce psychological violence among college students. (shrink)

ObjectiveSchizophrenia is a mental disorder that is characterized by progressive cognitive impairment. Objective measures of cognitive function may provide reliable neurobiomarkers for patients with schizophrenia. The goal of the current work is to explore the correlation between resting theta power and cognitive performance in patients with schizophrenia.MethodsTwenty-two patients with schizophrenia and 23 age-, sex-, and education-matched healthy controls were included in this study. The MATRICS Consensus Cognitive Battery was used for cognitive evaluation and the Positive and Negative Syndrome Scale for (...) evaluation of clinical symptoms. EEGs were acquired in the resting state with closed and opened eyes. Between the two groups, we compared the relative theta power and examined their relationship with cognitive performance.ResultsCompared to healthy controls, patients with schizophrenia showed significantly higher theta power, both with eyes closed and open. When the eyes were open, negative correlations were found in patients with schizophrenia between theta power in the central and parietal regions with processing speed scores, and between the theta power of the Pz electrode and verbal learning and reasoning and problem-solving scores. In the control group, theta power over the Fz electrode was negatively correlated with processing speed.ConclusionsOur findings showed that theta activity increased in certain brain regions during resting state in schizophrenia. Negative associations between resting theta power over the parietal-occipital regions with MCCB domains scores suggest that altered theta activity can be used as a neurobiological indicator to predict cognitive performance. (shrink)

This paper is concerned with the target tracking problem of an autonomous surface vehicle in the presence of a maneuvering target. The velocity information of target is totally unknown to the follower vehicle, and only the relative distance and angle between the target and follower are obtained. First, a reduced-order extended state observer is used to estimate the unknown relative dynamics due to the unavailable velocity of the target. Based on the reduced-order extended state observer, an antidisturbance guidance law for (...) target tracking is designed. The input-to-state stability of the closed-loop target tracking guidance system is analyzed via cascade theory. Furthermore, the above result is extended to the case that collisions between the target and leader are avoided during tracking, and a collision-free target tracking guidance law is developed. The main feature of the proposed guidance law is twofold. First, the target tracking can be achieved without using the velocity information of the target. Second, collision avoidance can be achieved during target tracking. Simulation results show the effectiveness of the proposed antidisturbance guidance law for tracking a maneuvering target with the arbitrary bounded velocity. (shrink)

Efficient knowledge sharing is an important support for the continuous innovation and sustainable development of scientific research teams. However, in realistic management situations, the knowledge sharing of scientific research teams always appears to be unsustainable, and the reasons for this are the subject of considerable debate. In this study, an attempt was made to explore the interactive mechanism of knowledge hiding behaviors in scientific research teams between individual and collective knowledge hiding behaviors and its impact on knowledge sharing by adopting (...) grounded theory to comprehensively understand this situation. The results show that knowledge hiding behavior in the scientific research team is a two-phase interactive process and is capable of affecting sustainable knowledge sharing by reducing the supply of knowledge, creating a poor knowledge sharing atmosphere, and forming an interpersonal distrust relationship. This research may provide a strong basis for a deeper understanding of the interaction mechanism of knowledge hiding behavior and its impact on knowledge sharing. (shrink)

The coronavirus disease 2019 pandemic caused by severe acute respiratory syndrome coronavirus 2 is challenging the dental community to an unprecedented degree. Knowledge of the increased risk of infection in dental settings has been disseminated to the public and guidelines have been formulated to assist dental attendance decision-making. However, dental attendance behaviors incompatible with treatment need is not uncommon in clinical settings. Important gaps remain in the knowledge about how psychological factors are affecting dental attendance behaviors during the COVID-19 epidemic. (...) In this cross-sectional study, a questionnaire survey was performed during February and March 2020. A total of 342 and 294 dental patients who attended and avoided dental visits, respectively, were included. The participants were classified into four groups based on dental attendance behavior and emergent/urgent dental treatment need. Bivariate analysis was performed to investigate factors associated with dental attendance. Multivariable logistic regression based on principal component scores was performed to identify major psychological constructs associated with unnecessary dental avoidance and attendance. Among all the factors explored, inability to wear masks during dental treatment was most closely associated with the overall pattern of dental attendance among participants. Multivariable regression suggested that unnecessary dental avoidance was associated with perceived risk of infection in general and in dental settings, perceived impact of COVID-19 and dental problems on general health, and personal traits such as trust and anxiety. Unnecessary dental attendance was associated with optimism toward the epidemic and trust. Multidisciplinary efforts involving dental and medical professionals as well as psychologists are warranted to promote more widespread adoption, among the general public, of dental attendance behaviors compatible with dental treatment need during the COVID-19 epidemic. (shrink)