To date, game-based learning programs that include comprehensive creativity skills and disposition training are still very limited. The present researchers developed a comprehensive game-based creativity learning program for fifth and sixth grade pupils. Further analysis presented relationship trends between mindful learning experience, flow experience, self-efficacy, and mastery experience. Eighty-three 5th and 6th grade participants undertook the six-week game-based creativity learning program. Upon the completion of experimental instruction, those who scored higher on the concerned variables improved more in self-evaluation of both (...) creativity ability and confidence, than their counterparts. Additionally, path model analysis revealed that mindful learning experience was a powerful predictor of both mastery experience and flow experience; it also influenced mastery experience through flow experience and self-efficacy during game-based creativity learning. The findings support the effectiveness of the game-based learning program developed in this study. Moreover, this study contributes to the theoretical construction of how game-based learning can be designed to facilitate mindful learning experience, flow experience, self-efficacy, and mastery experience during creativity training among pupils. Effective mechanisms include providing rewards for high-quality performance, challenging tasks, free choices of design components, immediate feedback, and idea sharing. The profound theoretical framework proposed in this study provides a valuable approach for creativity instruction through game-based learning or classroom instruction. (shrink)

With more and more investors exerting their voices through network forums or social media platforms, the relationships between online investor sentiment and stock movements have drawn more and more attention. In this paper, we crawl stock comments from China’s most popular online stock forum, East Money, and then develop a sentiment classifier using the LSTM method. Using the online investor sentiment of the stock forum, we explore the effect of online investor sentiment on the stock movements of CSI300. The results (...) show that online investor sentiment has a significant positive impact on both stock return and trading volume and remains significant after controlling book-to-market ratio, BETA, and market value. Moreover, investor sentiment has a significant positive impact on order imbalance of big trade, which represents the main flow of money in the market. As a result, investor sentiment has a positive impact on the major fund flows in the market. In other words, an increase in investor sentiment can boost the major money flows in the market to some extent. From a practical point of view, investor sentiment can assist investors to make investment decisions and help the government to regulate the stock market. (shrink)

The academic confusion caused by the "gang of four" was prominently manifested in the history of Chinese philosophy. The history of Chinese logic was also affected by the confusion. Now the "gang of four" has been smashed after a merciless trial by history. Under the leadership of Chairman Hua and the Party Central Committee, scientific research has begun to make a long stride ahead. Therefore, it is possible to conduct scientific investigations and thorough discussions on a series of issues in (...) the history of Chinese philosophy and logic. Appraisal of the book entitled the Kung-sun Lung Tzu [The Works of Kung-sun Lung] is one of the issues. (shrink)

Anxious major depressive disorder is a common subtype of major depressive disorder; however, its unique neural mechanism is not well-understood currently. Using multimodal MRI data, this study examined common and specific alterations of amygdala subregions between patients with and without anxiety. No alterations were observed in the gray matter volume or intra-region functional integration in either patient group. Compared with the controls, both patient groups showed decreased functional connectivity between the left superficial amygdala and the left putamen, and between the (...) right superficial amygdala and the bilateral anterior cingulate cortex and medial orbitofrontal cortex, while only patients with anxiety exhibited decreased activity in the bilateral laterobasal and superficial amygdala. Moreover, the decreased activity correlated negatively with the Hamilton depression scale scores in the patients with anxiety. These findings provided insights into the pathophysiologic processes of anxious major depressive disorder and may help to develop new and effective treatment programs. (shrink)

In this paper, finite-time tracking problem of nonholonomic mobile robots for a moving target is considered. First of all, polar coordinates are used to characterize the distance and azimuth between the moving target and the robot. Then, based on the distance and azimuth transported from the sensor installed on the robot, a finite-time tracking control law is designed for the nonholonomic mobile robot by the switching control method. Rigorous proof shows that the tracking error converges to zero in a finite (...) time. Numerical simulation demonstrates the effectiveness of the proposed control method. (shrink)

The growing prevalence of health care ethics consultation (HCEC) services in the U.S. has been accompanied by an increase in calls for accountability and quality assurance, and for the debates surrounding why and how HCEC is evaluated. The objective of this study was to evaluate the effectiveness of HCEC as indicated by several novel outcome measurements in East Asian medical encounters.

In this paper, we propose a method to design the pseudorandom number generator using three kinds of four-wing memristive hyperchaotic systems with different dimensions as multientropy sources. The principle of this method is to obtain pseudorandom numbers with good randomness by coupling XOR operation on the three kinds of FWMHSs with different dimensions. In order to prove its potential application in secure communication, the security of PRNG based on this scheme is analyzed from the perspective of cryptography. In addition, PRNG (...) has passed the NIST 800.22 and ENT test, which shows that PRNG has good statistical characteristics. Finally, an image encryption algorithm based on PRNG is adopted. In the encryption algorithm, the optimized Arnold matrix scrambling method and the diffusion processing based on XOR are used to obtain the final encrypted image. Through the evaluation of encryption performance, it is concluded that there is no direct relationship between the pristine image and encrypted image. The results show that the proposed image encryption scheme has good statistical output characteristics and security performance in line with cryptography. (shrink)

BackgroundAt present, adherence to antipsychotic treatment is often poor, leading to the recurrence of symptoms. This increases the likelihood of the patient experiencing disability and thus increases the disease burden for the patient, their family, and society as a whole. However, to date, there is no clear evidence regarding the effect of medication adherence interventions on outcomes for patients with schizophrenia. Moreover, the traditional intervention methods are limited by manpower and resources in low- and middle-income countries. Recent studies have demonstrated (...) that increasing a patient’s level of self-compassion may improve their treatment adherence. Online mental health care interventions have advantages in terms of feasibility and acceptability for patients with schizophrenia. In this regard, a WeChat-based self-compassion training protocol to improve patient treatment adherence was designed in this study and will be evaluated in the future to determine its impact on patients with schizophrenia.MethodsThe protocol for the randomized controlled trial is based on the SPIRIT 2013 statement. This parallel RCT will aim to recruit 392 patients with schizophrenia who will be randomized at a 1:1 ratio into a 3-week intervention or control group. Both groups will receive routine care. The intervention group will also receive WeChat-based self-compassion training, which requires participants to complete three tasks every day, including a reading task, a meditation task, and a self-compassion journal task. The control group will receive WeChat-based psychological health education, which will only require participants to read positive articles about psychological health every day. Medication adherence, self-compassion, stigma, and social support will be measured at baseline, immediately after the intervention, and 3 weeks after the intervention. Program feasibility will be evaluated throughout the course of the study, and acceptability will be measured immediately after the intervention.Expected results:The intervention described here will address the barriers to accessing mental health care for people with schizophrenia, including patients’ desire for independent management, difficulty accessing providers, and concerns about privacy and stigma. The current study provides guidance for clinical nurses to carry out psychological intervention, with the ultimate aim of addressing the problems associated with a shortage of psychological professionals in low- and middle-income countries. (shrink)

Sequential recommendation algorithm can predict the next action of a user by modeling the user’s interaction sequence with an item. However, most sequential recommendation models only consider the absolute positions of items in the sequence, ignoring the time interval information between items, and cannot effectively mine user preference changes. In addition, existing models perform poorly on sparse data sets, which make a poor prediction effect for short sequences. To address the above problems, an improved sequential recommendation algorithm based on short-sequence (...) enhancement and temporal self-attention mechanism is proposed in this paper. In the proposed algorithm, a backward prediction model is trained first, to predict the prior items in the user sequence. Then, the reverse prediction model is used to generate a batch of pseudo-historical items before the initial items of the short sequence, to achieve the goal of enhancing the short sequence. Finally, the absolute position information and time interval information of the user sequence are modeled, and a time-aware self-attention model is adopted to predict the user’s next action and generate a recommendation list. Various experiments are conducted on two public data sets. The experimental results show that the method proposed in this paper has excellent performance on both dense and sparse data sets, and its effect is better than that of the state of the art. (shrink)

Biologists have long known that animal population dynamics are regulated by a combination of bottom-up and top-down forces. Yet, economists have argued that human population dynamics can also be influenced by intraspecific cooperation. Despite awareness of the role of interspecific cooperation in influencing resource availability and animal population dynamics, the role of intraspecific cooperation under different environmental conditions has rarely been considered. Here we examine the role of what we call “lateral forces” that act within populations and interact with external (...) top-down and bottom-up forces in influencing population dynamics using an individual-based model linking environmental quality, intraspecific cooperation, and population size. We find that the proportion of cooperators is higher when the environment is poor and population sizes are greatest under intermediate resources levels due to the contrasting effects of resource availability on behavior and population size. We also show that social populations are more resilient to environmental change than non-social ones because the benefits of intraspecific cooperation can outweigh the effects of constrained resource availability. Our study elucidates the complex relationship between environmental harshness, cooperation, and population dynamics, which is important for understanding the ecological consequences of cooperation. (shrink)

Problematic smartphone use is an expanded public health heed that requires more study to clarify the influence elements of different populations. The aim of this study was to investigate the relationship between smartphone use, and sleep quality, self-perceived health, and exercise participation in university students. A total of 1,575 Taiwanese undergraduate students from 7 universities participated in the study. Three questionnaires were completed by the study individuals. The results show the overall PSU rate was 11.8%. Average smartphone users were more (...) likely to feel in good health, better sleep quality and less unsatisfactory exercise participation than those who were problematic smartphone users. Multiple logistic regression analysis indicated that PSU, low weekly exercise frequency, and poor sleep quality were significant indicators of poor self-perceived health. We concluded that both low physical activity and PSU did have negative impacts on self-perceived health and sleep quality for undergraduate students. (shrink)

Objective: Patients with hypochondriasis hold unexplainable beliefs and a fear of having a lethal disease, with poor compliances and treatment response to psychotropic drugs. Although several studies have demonstrated that patients with hypochondriasis demonstrate abnormalities in brain structure and function, gray matter volume and functional connectivity in hypochondriasis still remain unclear.Methods: The present study collected T1-weighted and resting-state functional magnetic resonance images from 21 hypochondriasis patients and 22 well-matched healthy controls. We first analyzed the difference in the GMV between the (...) two groups. We then used the regions showing a difference in GMV between two groups as seeds to perform functional connectivity analysis. Finally, a support vector machine was applied to the imaging data to distinguish hypochondriasis patients from HCs.Results: Compared with the HCs, the hypochondriasis group showed decreased GMV in the left precuneus, and increased GMV in the left medial frontal gyrus. FC analyses revealed decreased FC between the left medial frontal gyrus and cuneus, and between the left precuneus and cuneus. A combination of both GMV and FC in the left precuneus, medial frontal gyrus, and cuneus was able to discriminate the hypochondriasis patients from HCs with a sensitivity of 0.98, specificity of 0.93, and accuracy of 0.95.Conclusion: Our study suggests that smaller left precuneus volumes and decreased FC between the left precuneus and cuneus seem to play an important role of hypochondriasis. Future studies are needed to confirm whether this finding is generalizable to patients with hypochondriasis. (shrink)

E-commerce research usually focuses more on how to protect consumers’ rights and increase their purchase intention from the perspective of consumers. However, we still lack understanding of e-commerce sellers, especially cross-border e-commerce sellers. Based on the stimulus-body-response theory, this paper built a moderated mediation model to test the relationships among social support, perceived benefits, perceived usefulness and sellers’ willingness to retain. The results show that social support has a positive impact on perceived benefits and sellers’ willingness to retain; perceived benefits (...) play a partial intermediary role between social support and sellers’ willingness to retain; and perceived usefulness moderates these mediating effects. The research results further expand the perspective of e-commerce research and reveal the mechanism and boundary conditions of the influence of social support on the retention willingness of cross-border e-commerce sellers. (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)

Delineation of the subthalamic nuclei on MRI is critical for deep brain stimulation surgery in patients with Parkinson’s disease. We propose this retrospective cohort study for quantitative analysis of MR signal-to-noise ratio, contrast, and signal difference-to-noise ratio of the STN on pre-operative three-dimensional stereotactic MRI in patients with medication-refractory PD. Forty-five consecutive patients with medication-refractory PD who underwent STN-DBS surgery in our hospital from January 2018 to June 2021 were included in this study. All patients had whole-brain 3D MRI, including (...) T2-weighted imaging, T2-weighted fluid-attenuated inversion recovery, and susceptibility-weighted imaging, at 3.0 T scanner for stereotactic navigation. The signal intensities of the STN, corona radiata, and background noise were obtained after placing regions of interest on corresponding structures. Quantitative comparisons of SNR, contrast, and SDNR of the STN between MR pulse sequences, including the T2WI, FLAIR, and SWI. Subgroup analysis regarding patients’ sex, age, and duration of treatment. We used one-way repeated measures analysis of variance for quantitative comparisons of SNR, contrast, and SDNR of the STN between different MR pulse sequences, and we also used the dependent t-test for the post hoc tests. In addition, we used Mann–Whitney U test for subgroup analyses. Both the contrast and SDNR were highest on FLAIR. The SNR was highest on SWI, and both the SNR and SDNR were lowest on T2WI. Subgroup analyses demonstrated significantly lower SDNR on SWI for patients receiving medication treatment for ≥13 years. In conclusion, on 3D stereotactic MRI of medication-refractory PD patients, the contrast and SDNR for the STN are highest on FLAIR, suggesting the optimal delineation of STN on FLAIR. (shrink)

Jensen’s inequality is one of the fundamental inequalities which has several applications in almost every field of science. In 2003, Mercer gave a variant of Jensen’s inequality which is known as Jensen–Mercer’s inequality. The purpose of this article is to propose new bounds for Csiszár and related divergences by means of Jensen–Mercer’s inequality. Also, we investigate several new bounds for Zipf–Mandelbrot entropy. The idea of this article may further stimulate research on information theory with the help of Jensen–Mercer’s inequality.

Classification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. The generated training model can intelligently identify and classify file streams, improving work efficiency and accuracy of classification and (...) gradation. At the same time, the differences, advantages, and disadvantages of K-NN, DT, and LinearSVC algorithms are compared. The experimental data shows that LinearSVC algorithm is applicable to high-dimensional data, with discrete, sparse data features and large number of features, which is more suitable for classification of sensitive data of enterprises. (shrink)

Dynamic multiobjective optimization problems bring more challenges for multiobjective evolutionary algorithm due to its time-varying characteristic. To handle this kind of DMOPs, this paper presents a dynamic MOEA with multiple response strategies based on linear environment detection, called DMOEA-LEM. In this approach, different types of environmental changes are estimated and then the corresponding response strategies are activated to generate an efficient initial population for the new environment. DMOEA-LEM not only detects whether the environmental changes but also estimates the types of (...) linear changes so that different prediction models can be selected to initialize the population when the environmental changes. To study the performance of DMOEA-LEM, a large number of test DMOPs are adopted and the experiments validate the advantages of our algorithm when compared to three state-of-the-art dynamic MOEAs. (shrink)