A fundamental question in reading research concerns whether attention is allocated strictly serially, supporting lexical processing of one word at a time, or in parallel, supporting concurrent lexical processing of two or more words (Reichle, Liversedge, Pollatsek, & Rayner, 2009). The origins of this debate are reviewed. We then report three simulations to address this question using artificial reading agents (Liu & Reichle, 2010; Reichle & Laurent, 2006) that learn to dynamically allocate attention to 1–4 words to “read” as efficiently (...) as possible. These simulation results indicate that the agents strongly preferred serial word processing, although they occasionally attended to more than one word concurrently. The reason for this preference is discussed, along with implications for the debate about how humans allocate attention during reading. (shrink)

We investigate diagonal actions of Polish groups and the related intersection operator on closed subgroups of the acting group. The Borelness of the diagonal orbit equivalence relation is characterized and is shown to be connected with the Borelness of the intersection operator. We also consider relatively tame Polish groups and give a characterization of them in the class of countable products of countable abelian groups. Finally an example of a logic action is considered and its complexity in the Borel reducbility (...) hierarchy determined. (shrink)

This research topic (RT) focused on the impact of fitness on cognitive function and development in adolescents and elderly adults from the standpoint of lifespan neuroscience. Adolescent brain development is characterized by multimodal integration of brain anatomical features and function, according to accumulating evidence. The elderly, on the other hand, suffer from age-related cognitive deterioration. Fitness may be a major factor influencing brain growth and cognitive performance throughout these two critical times for neurological development. It is a multidimensional notion that (...) includes cardiovascular fitness, muscular strength and endurance, flexibility, and body composition, as well as motor fitness (balance, agility, speed, power, and coordination). Adolescents and older people may be responsive to intervention trials aimed at improving fitness levels, such as outdoor activities, cardiovascular exercise, and mind-body practice since brain network integration and neural efficiency are rapidly altered during this period. This RT investigates how fitness influences structural and functional brain development, particularly cognitive functions, and emotional health in adolescents and elderly people, as well as training strategies that may assist cognitive progress throughout this time. It includes a clinical trial (1) and original research papers (4) on the influence of fitness on cognitive function and development in adolescents and elderly adults from a lifespan neu... (shrink)

Background: Chinese Taoist cognitive therapy (CTCT), a culture-oriented psychological therapy for Chinese mental well-being, has been proposed for decades. However, the evidence for its effects is unclear. This study aimed to systematically assess the effect of this therapy on symptoms of depression and anxiety in Chinese adults. Methods: Relevant studies were searched from major electronic databases through November 2018 without language limits. Several search terms used include “anxiety” OR “depression” AND “Taoism” OR “Daoism” OR “Chinese Taoist Cognitive Therapy”. A total (...) of 11 clinical trials focusing on CTCT were included in this meta-analysis. Random-effects meta-analytical models were conducted. Heterogeneity and publication bias were also explored. Results: Eight clinical trials for 580 subjects were included. The majority of these studies explored samples with depressive symptoms. Overall, CTCT significantly reduced depressive symptoms with a small positive effect (SMD = 0.16, 95% CI: -0.36-0.68). Medium-to-large effect sizes were observed across individuals with clinical or nonclinical depression and chronic physical diseases (SMD = 0.70, 95%CI: 0.27-1.13 and SMD = 0.72, 95%CI: 0.09-1.35, respectively). However, the effectiveness for anxiety symptoms remains debatable. Conclusions: Our findings hold promise that CTCT can help reduce depressive symptoms in Chinese adults, including patients with chronic physical diseases and clinical or nonclinical depression. Our findings may be generalized to Chinese communities in other countries. (shrink)

With the advent of the era of artificial intelligence, deep reinforcement learning has achieved unprecedented success in high-dimensional and large-scale artificial intelligence tasks. However, the insecurity and instability of the DRL algorithm have an important impact on its performance. The Soft Actor-Critic algorithm uses advanced functions to update the policy and value network to alleviate some of these problems. However, SAC still has some problems. In order to reduce the error caused by the overestimation of SAC, we propose a new (...) SAC algorithm called Averaged-SAC. By averaging the previously learned action-state estimates, it reduces the overestimation problem of soft Q-learning, thereby contributing to a more stable training process and improving performance. We evaluate the performance of Averaged-SAC through some games in the MuJoCo environment. The experimental results show that the Averaged-SAC algorithm effectively improves the performance of the SAC algorithm and the stability of the training process. (shrink)

This review explored the investigations on the role of teacher immediacy in English as a Foreign Language learners’ foreign language enjoyment. Earlier investigations have proved that teacher immediacy, such as posture, body language, vocal variety, gestures, and smile, can significantly affect learners’ positive emotions like foreign language enjoyment. It means that teachers should try both to control the feelings of their learners and manage their feelings to enhance enjoyment among learners. Moreover, studies have shown that teacher immediacy is significantly related (...) to learner motivation which is a basis for increasing foreign language enjoyment among learners. However, specific strategies can be employed to increase learner motivation, which in return increases learner foreign language enjoyment. Furthermore, the study presented the implications and future directions of this line of research for different people, such as EFL teachers, teacher educators, and foreign language scholars. The ideas can improve their awareness of teacher-student relationships, in particular, teacher immediacy and its role in learners’ foreign language enjoyment. (shrink)

Metaverse is to build a virtual world that is both mapped and independent of the real world in cyberspace by using the improvement in the maturity of various digital technologies, such as virtual reality, augmented reality, big data, and 5G, which is important for the future development of a wide variety of professions, including education. The metaverse represents the latest stage of the development of visual immersion technology. Its essence is an online digital space parallel to the real world, which (...) is becoming a practical field for the innovation and development of human society. The most prominent advantage of the English-teaching metaverse is that it can provide an immersive and interactive teaching field for teachers and students, simultaneously meeting the teaching and learning needs of teachers and students in both the physical world and virtual world. This study constructs experiential situational English-teaching scenario and convolutional neural networks –recurrent neural networks fusion models are proposed to recognize students’ emotion electroencephalogram in experiential English teaching during the feature space of time domain, frequency domain, and spatial domain. Analyzing EEG data collected by OpenBCI EEG Electrode Cap Kit from students, experiential English-teaching scenario is designed into three types: sequential guidance, comprehensive exploration, and crowd-creation construction. Experimental data analysis of the three kinds of learning activities shows that metaverse-powered experiential situational English teaching can promote the improvement of students’ sense of interactivity, immersion, and cognition, and the accuracy and analysis time of CNN–RNN fusion model is much higher than that of baselines. This study can provide a nice reference for the emotion recognition of students under COVID-19. (shrink)

With the increase in depth of coal mining, the hydrogeological complexity largely increases and water inrush accidents happen more frequently. For the safety of coal mining, horizontal directional drilling and grouting techniques have been implemented to detect and plug the fractures and conduits that deliver high-pressure groundwater to coal mine. Taking the grouting engineering performed at Xingdong coal mine at 980 m below sea level as an example, we collected the data of grouting quantity, the loss of drilling fluid, gamma (...) value, water temperature, average water absorption, distance between grouting loss points, water pressure on coal seam floor, and aquifuge thickness at 90 boreholes in the mine to conduct grey relational analysis, first. The analysis showed that the grouting quantity was highly correlated with all other factors. Subsequently, grey system evaluation was used to evaluate the risk of water inrush from the coal seam floor. The results of risk analysis illustrated that three water inrushes from Ordovician limestone occurred in mining face 2127, 2125, and 2222 in the study area were all located in the area with a risk score higher than 65. Through grouting, the identified cracks were effectively blocked and waterproof layers beneath the coal seam floors were constructed to reduce the threat of water inrush. By comparing the risk assessment results with three water inrush cases before grouting operation, we found that water inrush areas were consistent with the area of higher risk. (shrink)

Although the management and planning of water resources are extremely significant to human development, the complexity of implementation is unimaginable. To achieve this, the high-precision water consumption prediction is actually the key component of urban water optimization management system. Water consumption is usually affected by many factors, such as weather, economy, and water prices. If these impact factors are directly combined to predict water consumption, the weight of each perspective on the water consumption will be ignored, which will be greatly (...) detrimental to the prediction accuracy. Therefore, this paper proposes a deep neural network-based complex system for urban water management. The essence of it is to formulate a water consumption prediction model with the aid of principal component analysis and the integrated deep neural network, which is abbreviated as UWM-Id. The PCA classifies the factors affecting water consumption in the original data into three categories according to their correlation and inputs them into the neural network model. The results in the previous step are assigned weights and integrated into the form of fully connected layer. Finally, analyzing the sensitivity of the proposed UWM-Id and comparing its performance with a series of commonly used baseline methods for data mining, a large number of experiments have proved that UWM-Id has good performance and can be used for urban water management system. (shrink)

Residual useful lifetime prediction plays a key role of failure prediction and health management in equipment. Aiming at the problems of residual life prediction without comprehensively considering multistage and individual differences in equipment performance degradation at present, we explore a prediction model that can fit the multistage random performance degradation. Degradation modeling is based on the random Wiener process. Moreover, according to the degradation monitoring data of the same batch of equipment, we apply the expectation maximization algorithm to estimate the (...) prior distribution of the model. The real-time remaining life distribution of the equipment is acquired by merging prior information of real-time degradation data and historical degradation monitoring data. The accuracy of the proposed model is demonstrated by analyzing a practical case of metalized film capacitors, and the result shows that a better RUL estimation accuracy can be provided by our model compared with existing models. (shrink)

Machine learning methods have been used in multifactor stock strategy for years. This paper uses three machine learning methods and linear regression method to find the most appropriate approach. First, a framework is established and 10 style factors and 30 industry factors are chosen. Second, four methods are used to forecast portfolio returns and compared by predicting returns, successful rate, and Sharpe ratio. Finally, this paper draws conclusion. The main findings are as follows: the support vector regression has the most (...) stable successful rate for predicting, while ridge regression and linear regression have the most unstable successful rate with more extreme cases; algorithm of support vector regression fitting higher-degree polynomials in Chinese A-share market is optimized, compared with the traditional linear regression both in terms of stock return and retracement control; the results of support vector regression significantly outperforming the CSI 500 index prove further. (shrink)

With the rapid development of the Internet and the normalization of COVID-19 epidemic prevention and control, Online health communities have gradually become one of the important ways for people to obtain health information, and users have to go through a series of information processing when facing the massive amount of data. Understanding the factors influencing user information processing is necessary to promote users’ health literacy, health knowledge popularization and health behavior shaping. Based on the Heuristic-Systematic Model, Information Ecology Theory, Privacy (...) Trade-Off and Self-Efficacy Theory, we constructed a model of factors influencing user information processing in online health communities. We found that information quality and emotional support had indirect effects on heuristic and systematic information processing, and these effects were mediated by privacy concerns and self-efficacy. In our research model, systematic information processing was most positively influenced directly by self-efficacy. Privacy concerns had a direct negative correlation with both dual information processing pathways. Therefore, OHCs managers should develop relevant regulations to ensure the information quality in OHCs and improve privacy protection services to promote user information processing by improving users’ self-efficacy and reducing their privacy concerns. Providing a user-friendly and interactive environment for users is also recommended to create more emotional support, thus facilitating more systematic information processing. (shrink)

ObjectiveTo confirm the effects of a transtheoretical model based on multidimensional life management on healthy behavior in patients with polycystic ovary syndrome.MethodsIn total, eighty eligible patients were recruited from March 2021 to June 2021 and randomly assigned to either the intervention or control groups. Outcome measures include health-promoting behavior, self-efficacy, anthropometrics, and the number of unplanned outpatient admissions. Data were collected at baseline, 3, and 6 months after the intervention. The chi-square test, rank-sum test, t-test, and repeated measurement analysis of (...) variance were used to analyze the data.ResultsIn total, sixty-six participants completed the study: 35 participants in the intervention group and 31 participants in the control group. After 6 months of intervention, the healthy behavior level of patients with PCOS increased from moderate [health-promoting lifestyle profile -II score of 105.37 ± 12.57] to good in the intervention group; and there was no change observed in the control group. In addition, the total self-efficacy score, PCOS-related unplanned outpatient admissions, waist circumference, and body mass index were found to have a significant difference in the intervention group at 6 months. Meanwhile, repeated measures analysis of variance showed a significantly greater improvement in health-promoting behavior and self-efficacy over time in the intervention group than in the control group.ConclusionThe transtheoretical model based on multidimensional life management positively affected healthy behavior, self-efficacy, the number of unplanned outpatient admissions, and anthropometrics in patients with PCOS.Clinical Trial Registrationwww.chictr.org.cn, ChiCTR2000034572. (shrink)

An integrated hog futures price forecasting model based on whale optimization algorithm, LightGBM, and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise is proposed to overcome the limitations of a single machine learning model with low prediction accuracy and insufficient model stability. The simulation process begins with a grey correlation analysis of the hog futures price index system in order to identify influencing factors; after that, the WOA-LightGBM model is developed, and the WOA algorithm is used to optimize the LightGBM (...) model parameters; and, finally, the residual sequence is decomposed and corrected by using the CEEMDAN method to build a combined WOA-LightGBM-CEEMDAN model. Furthermore, it is used for comparison experiments to check the validity of the model by using data from CSI 300 stock index futures. Based on all experimental results, the proposed combined model shows the highest prediction accuracy, surpassing the comparative model. The model proposed in this study is accurate enough to meet the forecasting accuracy requirements and provides an effective method for forecasting future prices. (shrink)

Background: Prenatal and postnatal mental disorders can exert severe adverse influences on mothers, fetuses, and children. However, the effect of the coronavirus disease 2019 pandemic on the mental health of pregnant and postpartum women remains unclear.Methods: Relevant studies that were published from January 1, 2019 to September 19, 2020 were identified through the systematic search of the PubMed, EMBASE, and Web of Science databases. Quality assessment of included studies, random-effects meta-analysis, sensitivity analysis, and planned subgroup analysis were performed.Results: A total (...) of 23 studies conducted with 20,569 participants during the COVID-19 pandemic and with 3,677 pregnant women before the COVID-19 pandemic were included. The prevalence rates of anxiety, depression, psychological distress, and insomnia among pregnant women during the COVID-19 pandemic were 37%, 31%, 70%, and 49%, respectively. The prevalence of postpartum depression was 22%. Multigravida women and women in the first and third trimesters of pregnancy were more vulnerable than other pregnant women. The assessment of the associations between the COVID-19 pandemic and mental health problems revealed that the pooled relative risks of anxiety and depression in pregnant women were 1.65 and 1.08, respectively.Conclusions: The prevalence rates of mental disorders among pregnant and postpartum women during the COVID-19 pandemic were high. Timely and tailored interventions should be applied to mitigate mental problems among this population of women, especially multigravida women and women in the first and third trimesters of pregnancy. (shrink)

ObjectivesTo simulate hemodynamic changes after extraluminal compression in pulsatile tinnitus patients with a prominent transverse-sigmoid sinus junction.MethodsOne patient-specific case was reconstructed based on computed tomography venography images of a PT patient. The compression degree served as a new index in this study. Cases with 10, 20, 30, 40, 50, 60, 70, 80, and 90% of the compression degree of the control subject were constructed. Steady-state computational fluid dynamics were assessed. The wall pressure distribution, wall maximum pressure and flow pattern of (...) the PTSJ were calculated to evaluate hemodynamic differences among all cases.ResultsWith increasing compression, the wall pressure at the compression point and downstream of the PTSJ decreased but increased upstream. When the compression degree exceeded 70%, the upstream pressure increased significantly. Above 50% compression, the blood flow pattern downstream of the sigmoid sinus tended to spiral, especially after 80% compression. Beyond 60% compression, the blood flow pattern under the compression axis became more medial.ConclusionMechanical compression of PTSJ changes wall pressure and blood flow patterns. The degree of compression should be carefully observed to avoid possible complications or reoccurrence. (shrink)

BackgroundExercise is increasingly recognized as a key component of Parkinson’s disease treatment strategies, but the underlying mechanism of how exercise affects PD is not yet fully understood.ObjectiveThe activation likelihood estimation method is used to study the mechanism of exercise affecting PD, providing a theoretical basis for studying exercise and PD, and promoting the health of patients with PD.MethodsRelevant keywords were searched on the PubMed, Cochrane Library, and Web of Science databases. Seven articles were finally included according to the screening criteria, (...) with a total sample size of 97 individuals. Using the GingerALE 3.0.2 software, an ALE meta-analysis was performed using seven studies that met the requirements, and the probability of the cross-experiment activation of each voxel was calculated.ResultsThe meta-analysis produced seven clusters, and major activations were found in the cerebellum, occipital lobe, parietal lobe, and frontal lobe brain regions.ConclusionExercise for PD mainly results in the enhanced activation of the cerebellum, occipital lobe, parietal lobe, and frontal lobe. Exercise for PD does not cause a change in the activation of a single brain area, and the observed improvement may result from coordinated changes in multiple brain areas. (shrink)

Previous studies have found differences in the cognitive and neural mechanisms between cognitive reappraisal and expression suppression in the regulation of various negative emotions and the recognition of regulated stimuli. However, whether these differences are valid for sadness remains unclear. As such, we investigated the effect of cognitive reappraisal and expression suppression on sadness regulation and the recognition of sad scenes adopting event-related potentials. Twenty-eight healthy undergraduate and graduate students took part in this study. In the regulation phase, the participants (...) were asked to down-regulation, expressive suppression, or maintain their sad emotion evoked by the sad images, and then to perform an immediately unexpected recognition task involving the regulated images. The behavioral results show that down-regulation reappraisal significantly diminished subjective feelings of sadness, but expressive suppression did not; both strategies impaired the participants’ recognition of sad images, and expressive suppression had a greater damaging effect on the recognition of sad images than down-regulation reappraisal. The ERP results indicate that reappraisal and expressive suppression significantly reduced the late positive potential induced by sadness. These findings suggest that down-regulation reappraisal and expression suppression can effectively decrease sadness, and that down-regulation reappraisal is a more effective regulation strategy for sadness. Both strategies impair the recognition of sad scenes, and expression suppression leads to relatively greater impairment in the recognition of sad scenes. (shrink)

This study aims to explore the role of digital education in the development of skills and employability for engineering students through researching the role of big data analytics courses. The empirical study proposes the hypothesis that both soft and hard skills have positive effects on human capital, individual attributes, and the career development dimensions of engineering students. This is achieved through constructing a framework of three dimensions of engineering students’ employability and two competency development dimensions of big data analytics courses. (...) A questionnaire survey was conducted with 155 college engineering students and a structural equation model was used to test the hypotheses. The results found that courses on big data analytics have a positive impact on engineering students’ abilities in both hard skills and soft skills dimensions, while soft skills have a more significant impact on engineering students’ employability. The study has practical and theoretical implications that further enriches the knowledge base on engineering education and broadens our understanding of the role of digitalization in enhancing the skills and employability of engineering students. (shrink)

As a rapidly growing emerging capital market, China has attracted the attention of both investors and scholars. To alleviate the expectation of external users of listed companies’ financial statements to “discount” items in levels 2 and 3 of the fair value measurement, listed companies will treat these items as conditional conservatism. It refers to the conservatism of companies when confirming bad news of unrealized gains and losses sooner than confirming good news. A sample was selected for empirical analysis to verify (...) the existence of this relationship. The results are as follows: the higher the proportion of levels 2 and 3 fair value measurements, the stronger the conditional conservatism of the company’s profit and loss; the higher the proportion of cash holding of operating activities in a company’s operating profit and the higher the audit quality, the higher the proportion of levels 2 and 3 fair value hierarchy measurements, and the stronger the conditional conservatism of the company’s profit and loss; and the lesser the internal control defects in a company, the higher the proportion of levels 2 and 3 fair value hierarchy measurements, and the stronger the conditional conservatism of its profit and loss. The findings provide empirical evidence to identify listed companies adopting conditional conservatism to alleviate discounting expectations of fair value items of financial statements’ external users and provide a reference for improving the standards and regulation of listed companies. (shrink)

BackgroundThe high incidence of post-stroke depression during rehabilitation exerts a negative effect on the treatment and functional recovery of patients with stroke and increases the risk of mortality. It is necessary to screen PSD in the rehabilitation stage and thus provide effective intervention strategies. However, existing measurements used to assess PSD in the rehabilitation stage in patients with stroke lack specificity. This study aimed to develop a clinical measure to assess symptoms of PSD in the rehabilitation stage.MethodsThe research team created (...) the initial items through a literature review and semi-structured interviews of patients with stroke. Then, the symptom-related items were estimated by three panels: healthcare professionals, Delphi experts, and patients with stroke in the rehabilitation stage.ResultsThe literature review and semi-structured interview produced 51 symptom-related items including six domains, and the items were reduced to 47 by the healthcare professionals. The symptom-related items were further reduced to 33 items by a two-round Delphi consultation. The initiative coefficients of the two Delphi rounds were 71.4 and 100%, the expert authority coefficients were both 0.85, Kendall’s W were 0.152 and 0.408, and the coefficient of variation were 0.05–0.32 and 0.00–0.18, respectively. The item-level content validity index was 0.53–1.00, the scale-level CVI/universal agreement was 0.26, and the S-CVI/average was 0.85 for the first found Delphi consultation; the I-CVI was 0.67–1.00, the S-CVI/UA was 0.61, and the S-CVI/Ave was 0.97 for the second round Delphi consultation. All content validity indicators have been significantly improved compared with the first round. Using mean ≥ 4 and full score ≥ 0.5, combined with CV ≤ 0.16 as the item criteria, a clinical measure of PSD with 33 items and 6 dimensions was finally formed after two rounds. The patients with stroke made no further revisions after evaluation.ConclusionThe research team developed a specific tool with good content validity to assess the symptoms of PSD in the rehabilitation stage. (shrink)

本书是探讨马克思主义哲学的现代发展,比较马克思主义哲学和现代西方哲学的专著。对马克思主义哲学的对象、性质、当代使命、在世界哲学中的地位均富创见。.

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

The increasing number of quick response code mobile payment users heralds the coming of a cashless society. However, the extent to which the coronavirus disease 2019 pandemic accelerated the adoption of QR code mobile payment has not been sufficiently researched. Based on social learning theory, this study models how external interaction with the environment has affected the internal appraisal and behavioral intention to adopt QR code mobile payment during COVID-19. Empirical results from 248 respondents revealed that perceived severity and social (...) influence positively affected the perception of utilitarian and health benefits of respondents, which in turn influenced the behavioral intention to use the QR code mobile payment. The theoretical contribution and managerial implications of this study are also discussed. (shrink)