The human brain shows neuroplastic adaptations induced by motor skill training. However, the description of the plastic architecture of the whole-brain network in resting-state is still limited. In the present study, we aimed to detect how motor training affected the density distribution of whole-brain resting-state functional connectivity (FC) brain in fast-ball student-athletes using resting-state functional magnetic resonance imaging (fMRI) data of student-athletes (SA), and non-athlete healthy controls (NC). The voxel-wise data-driven graph theory approach, namely global functional connectivity density (gFCD) mapping (...) was applied. The results showed that the SA group exhibited significantly decreased gFCD in brain regions centered at left triangular part of inferior frontal gyrus (IFG), extending to opercular part of left IFG and middle frontal gyrus (MFG) compared with NC group. The findings supported the idea of an increased neural efficiency of athletes’ brain in the brain regions associated with attentional-motor modulation and executive control. Furthermore, the behavioral results demonstrated that in the SA group, faster executive control reaction time was associated with smaller gFCD values in left IFG. The findings implied that the motor skill training would decrease the numbers of FC in IFG to accelerate the execution control with high attentional demands, and focus the attention to the target detection the athletes are interested in. (shrink)

Window opening behavior in residential buildings has important theoretical significance and practical value for improving energy conservation, indoor thermal comfort, and indoor air quality. Climate and cultural differences may lead to different window opening behavior by residents. Currently, research on residential window opening behavior in northwest China has focused on indoor air quality, and few probabilistic models of residential window behaviors have been established. Therefore, in this study, we focused on an analysis of factors influencing window opening behavior and the (...) establishment of a predictive model for window opening behavior. Four typical residential buildings in different locations and building types in Xi’an were selected. The indoor and outdoor environments and window opening states were measured. Subsequently, a multivariate analysis of variance was used to determine the factors that had a significant effect on window opening behavior. Single- and multiparameter logistic regression models for window opening behavior were established. Of all the measured factors, we found that indoor temperature and CO2 concentration, outdoor temperature, and relative humidity had significant effects on window opening behavior, and indoor relative humidity and noise did not. Meanwhile, the temperature was positively correlated with the window opening probability, whereas indoor CO2 concentration and outdoor relative humidity were negatively correlated. The prediction accuracy of the multiparameter model was promising, at almost 75%, and the model can provide theoretical support for modelling residential buildings in Xi’an. (shrink)

Due to the currently insufficient consideration of task fitness and task coordination for task allocation in collaborative customized product development, this research was conducted based on the analysis of collaborative customized product development process and task allocation strategy. The definitions and calculation formulas of task fitness and task coordination efficiency were derived, and a multiobjective optimization model of product customization task allocation was constructed. A solution based on adaptive genetic algorithm was proposed, and the feasibility and effectiveness of the task (...) allocation algorithm were tested and verified using a 5-MW wind turbine product development project as example. (shrink)

Following the recent call for advancement in knowledge about business ethics in East Asia, this study proposes a complementary perspective on business ethics in South Korea. We challenge the conventional view that South Korea is a strictly collectivist country, where group norms and low trust determine the norms and values of behavior. Using the concept of civil religion, we suggest that the center of the South Korean civil religion can be seen in the affective ties and networks pervading the economic, (...) political, and social institutions, embedded in and guided by Confucian ideals. We argue that South Korea should be seen not as a collectivist low-trust society, but rather as an affective-relational society, in which the relational context determines whether collectivism or individualism prevails. Further, we assert that trust, the cohesive factor of affective ties and networks, has until now been inadequately captured by conventional surveys. Our proposed perspective contributes to a more holistic picture and a more firmly grounded understanding of business ethics in South Korea. (shrink)

This article presents two studies that examine cause-related marketing promotions that require consumers’ active participation. Requiring a follow-up behavior has very valuable implications for maximizing marketing expenditures and customer relationship management. Theories related to ethical behavior, like motivated reasoning and defensive denial, are used to explain when and why consumers respond negatively to these effort demands. The first study finds that consumers rationalize not participating in CRM by devaluing the sponsored cause. The second study identifies a tactic marketers can utilize (...) to neutralize consumers’ use of defensive denial. Allowing the consumer to choose the sponsored cause seems to effectively refocus their attention and increases consumers’ threshold for campaign requirements. Implications for nonprofits and marketing managers include a tendency for consumers to be more likely to perceive a firm as ethical and socially responsible when they are allowed to choose the specific cause that is supported. (shrink)

The stock market is a chaotic, complex, and dynamic financial market. The prediction of future stock prices is a concern and controversial research issue for researchers. More and more analysis and prediction methods are proposed by researchers. We proposed a hybrid method for the prediction of future stock prices using LSTM and ensemble EMD in this paper. We use comprehensive EMD to decompose the complex original stock price time series into several subsequences which are smoother, more regular and stable than (...) the original time series. Then, we use the LSTM method to train and predict each subsequence. Finally, we obtained the prediction values of the original stock price time series by fused the prediction values of several subsequences. In the experiment, we selected five data to fully test the performance of the method. The comparison results with the other four prediction methods show that the predicted values show higher accuracy. The hybrid prediction method we proposed is effective and accurate in future stock price prediction. Hence, the hybrid prediction method has practical application and reference value. (shrink)

We show that the structure R of recursively enumerable degrees is not a Σ₁-elementary substructure of Dn, where Dn (n > 1) is the structure of n-r.e. degrees in the Ershov hierarchy.

This study evaluated the biological dimension of meditation and self-transcendent states. A convenience sample of 513 participants was drawn from attendees at a 4-day guided meditation workshop. Half were randomly assigned to an active placebo control intervention. All were assessed on a variety of measures, both psychological [anxiety, pain, posttraumatic stress disorder, positive emotions, and transcendent states], and physiological. Additional biological assessments including salivary immunoglobulin-A, cortisol, and Quantitative Electroencephalography were obtained from subset of the Experimental group. No significant difference in (...) psychological symptoms or positive emotions was observed between Experimental and placebo groups at baseline. At post-test, significant improvements were noted in the Experimental group, including a 49.5% median increase in SIgA, though cortisol remained unchanged. qEEG z-score analysis identified sustained stress reduction, including delta frequency band amplitude increases, high beta decreases, and faster acquisition of sustained alpha states. Psychological symptoms also improved on all measures. At 6-month follow-up, PTSD and somatic symptoms significantly improved from baseline, and post-test versus 6-month follow-up results indicated significant increases in happiness and spiritual and physical oneness, along with decreases in depressive symptoms. These findings suggest that autonomic self-regulation and transcendent states may be measured in both biological and psychological dimensions and are associated with pervasive health benefits. (shrink)

Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium (...) traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole. (shrink)

PurposeBased on social exchange theory, this study aimed to investigate, from the cost-benefits perspective, the intention to co-create open educational resources.Design/Methodology/ApproachParticipants in the study included 311 undergraduate students selected from those enrolled in a course on the China University MOOC platform. Regression analysis was conducted to examine cost and benefits factors that influenced participants’ intentions to co-create OER.Findings From the perspective of benefits, expected reciprocity, increase in knowledge self-efficacy, and creative self-efficacy were found to significantly and positively impact the intention (...) to co-create OER, while increase in internet self-efficacy was not. From the perspective of cost, perceived effort and perceived privacy were found to significantly and negatively impact the intention to co-create OER, while perceived intellectual property risks were not significant.Originality/ValueThree strategies are recommended to promote the intention to co-create OER based on the findings of this study: focusing on OER communities and developing reciprocity norms; popularizing and promoting knowledge and use of Creative Commons copyright licenses; providing easy-to-use online resource editing tools for use with OER repositories.Research Limitations/ImplicationsFuture research should explore other ages, cultural backgrounds, and types of online learning experience to help broaden the universality of the results. (shrink)

Objective: Pulmonary complications could badly affect the recovery of neurological function and neurological prognosis of neurological critically ill patients. This study evaluated the effect of high-flow nasal cannula therapy on decreasing pulmonary complications in neurologically critically ill patients.Patients and Methods: The patients admitted to the intensive care unit with serious neurological disease and receiving oxygen therapy were retrospectively reviewed. Patients were divided into the HFNC group and the conventional oxygen therapy group. We analyzed the data within these two groups, including (...) patients’ baseline data, short-term outcomes of respiratory complications, general outcomes including hospital stay, ICU stay and mortality, and neurological functions. To analyze the relevant factors, we performed multivariable logistic regression analysis.Results: A total of 283 patients met the criteria, including 164 cases in the HFNC group and 119 cases in the COT group. The HFNC group had remarkably less mechanical ventilation requirement with lower phlegm viscosity. Even more, ICU stay and total hospital stay were significantly shortened in the HNFC group.Conclusion: HFNC decreased pulmonary complications in neurologically critically ill patients and improved recovery of neurological function and neurological prognosis. (shrink)

Despite extinction-based processes demonstrating efficacy in the animal extinction and human anxiety literatures, extinction for substance use disorders has shown poor efficacy. Reasons for this lack of success include common threats to extinction, such as renewal and reinstatement. In recent decades, research on mindfulness for SUD has flourished, and a key aspect of these mindfulness-based interventions includes teaching individuals to stay present with whatever experience they have, even if unpleasant, without trying to change/escape/avoid it. Similarly, CET teaches individuals to not (...) escape/avoid conditioned responses by engaging in drug use behavior. This paper discusses how mindfulness-based research and practices could positively influence CET through future research, with the long-term goal of improving SUD treatment. (shrink)

The purpose of this note is to study impulsive control and synchronization of memristor based chaotic circuits shown by Muthuswamy. We first establish a less conservative sufficient condition for the stability of memristor based chaotic circuits. After that, we discuss the effect of errors on stability. Meanwhile, we also discuss impulsive synchronization of two memristor based chaotic systems. Our results are more general and more applicable than the ones shown by Yang, Li, and Huang. Finally, several numerical examples are (...) given to show the effectiveness of our methods. (shrink)

Yang returns to the problem of referential ambiguity, addressed in the opening paper by Gleitman and Trueswell. Using a computational approach, he argues that “big data” approaches to resolving referential ambiguity are destined to fail, because of the inevitable computational explosion needed to keep track of contextual associations present when a word is uttered. Yang tests several computational models, two of which depend on one‐trial learning, as described in Gleitman and Trueswell’s paper. He concludes that such models outperform (...) cross‐situational learning models, thereby formalizing, reinforcing, and advancing the conclusions offered by Gleitman and Trueswell. (shrink)

The target article (Nelson et al. 2023) offers a valuable contribution to the “paradox of experience,” which was illustrated by using examples about access to unproven medical products and disabili...

Building a flexible supply chain can enable the firms to manage their supply chains to adapt effectively to dynamic market demand changes and thus guarantee their accelerated growth in the future. In this vein, this study aims to address several important issues in supply chain management by considering two characteristics of blockchain technology and exploring the specific conditions under which firms are likely to develop trust in supply chain management. Furthermore, we argue that such supply chain trust is vital to (...) the success of achieving and increasing supply chain flexibility. In addition, we propose that top management teams’ digital leadership within the firms plays a vital role in moderating the contribution of each dimension of blockchain technology to supply chain trust. Using data from a large sample of 338 firms in China, we perform structural equation modeling to examine our conceptual framework empirically. Our results highlight and support the idea that blockchain technology’s information transparency and security influence the trust-building in a supply chain and supply chain flexibility and articulate the particular importance of digital leadership in explaining the contribution of different blockchain technology characteristics to trust-building. Our study advances the theoretical, empirical, and managerial analysis of critical factors to build trust and achieve flexibility in supply chains. (shrink)

This paper presents an adaptive neural tracking control approach for a two-joint robotic manipulator with unknown time-varying delays. In order to work out the effect of unknown time-varying delays on the two-joint robotic manipulator, the appropriate Lyapunov–Krasovskii functionals and separation technology are chosen to settle this matter. The neural networks work as an approximator that has the advantage of estimating the unknown function in the system. In this paper, Lyapunov stability analysis can prove that all signals of the closed-loop system (...) are semiglobal uniformly ultimately bounded and the tracking error can converge to a compact neighborhood with respect to zero. The simulation consequences demonstrate the availability of the feedforward control approach. (shrink)

The brain-computer interface based on functional near-infrared spectroscopy has received more and more attention due to its vast application potential in emotion recognition. However, the relatively insufficient investigation of the feature extraction algorithms limits its use in practice. In this article, to improve the performance of fNIRS-based BCI, we proposed a method named R-CSP-E, which introduces EEG signals when computing fNIRS signals’ features based on transfer learning and ensemble learning theory. In detail, we used the Independent Component Analysis algorithm for (...) the correspondence between the sources of the two signals. We then introduced the EEG signals when computing the spatial filter based on a modified Common Spatial Pattern algorithm. Experimental results on public datasets show that the proposed method in this paper outperforms traditional methods without transfer. In general, the mean classification accuracy can be increased by up to 5%. To our knowledge, it is an innovation that we tried to apply transfer learning between EEG and fNIRS. Our study’s findings not only prove the potential of the transfer learning algorithm in cross-model brain-computer interface, but also offer a new and innovative perspective to research the hybrid brain-computer interface. (shrink)

In the presence of heterogeneity between the randomized controlled trial (RCT) participants and the target population, evaluating the treatment effect solely based on the RCT often leads to biased quantification of the real-world treatment effect. To address the problem of lack of generalizability for the treatment effect estimated by the RCT sample, we leverage observational studies with large samples that are representative of the target population. This article concerns evaluating treatment effects on survival outcomes for a target population and considers (...) a broad class of estimands that are functionals of treatment-specific survival functions, including differences in survival probability and restricted mean survival times. Motivated by two intuitive but distinct approaches, i.e., imputation based on survival outcome regression and weighting based on inverse probability of sampling, censoring, and treatment assignment, we propose a semiparametric estimator through the guidance of the efficient influence function. The proposed estimator is doubly robust in the sense that it is consistent for the target population estimands if either the survival model or the weighting model is correctly specified and is locally efficient when both are correct. In addition, as an alternative to parametric estimation, we employ the nonparametric method of sieves for flexible and robust estimation of the nuisance functions and show that the resulting estimator retains the root- n n consistency and efficiency, the so-called rate-double robustness. Simulation studies confirm the theoretical properties of the proposed estimator and show that it outperforms competitors. We apply the proposed method to estimate the effect of adjuvant chemotherapy on survival in patients with early-stage resected non-small cell lung cancer. (shrink)

The present study examined the effects of transcranial direct current stimulation using Halo Sport on the time to exhaustion in relation with muscle activities and corticomuscular coupling of agonist and antagonist muscles during a sustained isometric fatiguing contraction performed with the elbow flexors. Twenty healthy male college students were randomly assigned to tDCS group and control group. The two group participants performed two experimental sessions which consisted of pre-fatigue isometric maximal voluntary contraction, sustained submaximal voluntary contractions performed to exhaustion, and (...) post-fatigue MVC with the right elbow flexor muscles. Sham stimulation and tDCS were applied for control and tDCS group participants 20 min prior to the second session test, respectively. MVC strength in pre- and post-fatigue test, TTE, electroencephalogram, and electromyography of biceps brachii and triceps brachii were recorded during the tests. It was found that tDCS using the Halo Sport device significantly increased TTE and thus improved muscular endurance performance. The improvement may be partly related to the improvement of neuromuscular efficiency as reflected by decrease of antagonistic muscle coactivation activities, which may be related to cortical originated central processing mechanism of neuromuscular activities. (shrink)

Background and ObjectiveThere is a paucity of research that has explored “False Alarm” mechanisms. In order to remedy this deficiency in knowledge, the present study used event-related potential technology to reveal the mechanisms underlying False Alarm in response to fear stimuli.MethodsThis study selected snakes as experimental materials and the “oddball paradigm” was used to simulate the conditions of False Alarm. The mechanism underlying False Alarm was revealed by comparing cognitive processing similarities and differences between real snakes and toy snakes.ResultsEvent-related potential (...) findings demonstrated that there was no significant difference between N1 and P2 components induced by real and toy snakes in the early processing stage. Compared with toy snakes, real snakes induced smaller N2 amplitude, larger P3 amplitude, and a shorter P3 latency at the late processing stage. The results of brain topographic mapping analysis showed that the brain regions activated by a real or toy snake were basically the same within the time windows of 110–150 and 220–270 ms, respectively. In the time window of 300–360 and 400–500 ms, the degree of brain regions activation with a real snake was significantly greater than that induced by a toy snake.ConclusionFalse Alarm is caused by the brain’s inability to distinguish, in the early stage of cognitive processing, stimulus objects with similar appearances. When the brain is able to distinguish the differences between different stimulus objects in the late stage of cognitive processing, False Alarm disappears. (shrink)

The political environment has a significant impact on the sustainable development of enterprises. This manuscript aims to investigate the effect of policy uncertainty and official social capital on enterprises’ effective tax rate due to the change of officials. Based on the panel data from the Chinese Industrial Enterprise Database from 1998 to 2009, it is shown that the policy uncertainty caused by the change of local government officials significantly increases the ETR of enterprises. Meanwhile, municipal officials who have social ties (...) with provincial officials in their province also tend to raise the ETR of industrial enterprises, and this tendency is more evident when the officials take office. Further research shows that the effects vary in many aspects for policy uncertainty and social capital on the ETR of enterprises. The findings of this manuscript provide support for a deeper understanding of the change in local government fiscal policies and give suggestions to strengthen political environmental governance for the sustainable development of enterprises. (shrink)

Mental representations are more than emulations. Different types of representations, including external representations, various mental models (distorted and abstract), and emulative models, can all play important roles in human cognition. To explain cognitive performance in a specific task, a systematic analysis of the underlying representational structures and their interactions is needed.

Many industrial processes are operated in multiple modes due to different manufacturing strategies. Multimodality of process data is often accompanied with nonlinear and non-Gaussian characteristics, which makes data-driven monitoring more complicated. In this paper, statistics pattern analysis is introduced to extract low- and high-order statistics from raw process data. Support vector data description, which can deal with nonlinear and non-Gaussian problems, is applied to monitor multimode process in this paper. To improve detection performance of SVDD for training multimode data with (...) outliers, modified local reachability density ratio is proposed as a weight factor to be embedded in the weighted-SVDD model, in which the local neighbors in terms of both space and time are considered. Finally, the effectiveness and superiority of our proposed method are demonstrated by the Tennessee-Eastman process and wastewater treatment process. (shrink)

This paper proposes a super-twisting terminal sliding mode-based robust impedance controller to improve the compliance and robustness in robot-environment interaction. Based on the desired impedance dynamics, an impedance reference trajectory is constructed. Then, based on a super-twisting terminal sliding-mode, the robust impedance controller is designed to guarantee the achievement of the desired impedance dynamics in finite-time through the finite-time convergence of an impedance error. The main contribution of this paper is that the proposed control improves impedance control robustness by using (...) the super-twisting nonsingular terminal sliding-mode without causing the chattering problem. The finite-time stability of the closed-loop control system is validated by theoretical analysis based on the Lyapunov theory, and the control effectiveness is illustrated by simulations on a two-link robot manipulator. (shrink)

Lachlan observed that any nonzero d.c.e. degree bounds a nonzero c.e. degree. In this paper, we study the c.e. predecessors of d.c.e. degrees, and prove that given a nonzero d.c.e. degree , there is a c.e. degree below and a high d.c.e. degree such that bounds all the c.e. degrees below . This result gives a unified approach to some seemingly unrelated results. In particular, it has the following two known theorems as corollaries: there is a low c.e. degree isolating (...) a high d.c.e. degree [S. Ishmukhametov, G. Wu, Isolation and the high/low hierarchy, Arch. Math. Logic 41 259–266]; there is a high d.c.e. degree bounding no minimal pairs [C.T. Chong, A. Li, Y. Yang, The existence of high nonbounding degrees in the difference hierarchy, Ann. Pure Appl. Logic 138 31–51]. (shrink)

Yang Guorong is one of the most prominent Chinese philosophers working today and is best known for using the full range of Chinese philosophical resources in connection with the thought of Kant, Hegel, Marx, and Heidegger. In The Mutual Cultivation of Self and Things, Yang grapples with the philosophical problem of how the complexly interwoven nature of things and being relates to human nature, values, affairs, and facts, and ultimately creates a world of meaning. Yang outlines how (...) humans might live more fully integrated lives on philosophical, religious, cultural, aesthetic, and material planes. This first English translation introduces current, influential work from China to readers worldwide."--Page [4] of cover. (shrink)

The study of literature from the point of view of the search for archetypal images and the study of artistic creativity from the standpoint of structuralism are two important trends. Both of these trends have emerged in the contexts of different scientific paradigms. The origin of archetypal criticism is associated with the figure of Herman Northrop Fry, and the basis of archetypal criticism is psychology, namely the concept of psychoanalysis, founded by Sigmund Freud and Carl Gustav Jung. While the origin (...) of structuralism is associated with linguistics and the name of Ferdinand de Saussure, who first began to consider language as a system of signs in which each element defines other elements and is itself determined by them. With all the difference in origin, in general, both theories do not contradict each other - on the contrary, they complement each other. Archetypal literary criticism and structuralist theory of art have deep internal theoretical connections in several ways: both theories look for repetitive elements in literature, both consider literature as a space of memory about the past. Archetypal literary criticism and the structuralist theory of art direct the appeal to the psychology of man as the creator of works of art. Both directions are also largely based on the idea of binary oppositions: within the framework of the archetypal criticism of the pair, many archetypes are grouped into pairs, whereas within the framework of structuralism, the idea of structure itself is based on elementary concepts opposed to each other; finally, both methods have been criticized for the same shortcomings, such as the denial of author subjectivity and the denial of human progress. This article attempts to show that the theory of archetypes in literature and the structuralist theory of art complement each other, and how exactly this complementarity is achieved. (shrink)