Through empirical studies or laboratory tests, previous studies have shown that sport-confidence, attention, and emotion regulation are key factors in archery performance. The present study aims to further identify the effects and pathways of sport-confidence, attention, and cognitive reappraisal on real-world archery performance by constructing a hypothesized model to provide a basis for scientific training of athletes to improve sport performance. A survey design was utilized on a sample of 61 athletes from the Chinese National Archery Team to test the (...) model. The measurement and hypothesized models were tested using partial least squares structural equation modeling. The results indicate that the model fit well and explained 33.6% of the variance in archery performance. Sport-confidence and attention were important predictive indicators of archery performance, while the relationship between cognitive reappraisal and archery performance showed considerable complexity. We conclude that the development of sport-confidence and attention of archery athletes should be strengthened, but athletes who use cognitive reappraisal in archery competition should be mindful of its potential appropriation of cognitive resources and should be directed to improve sport-confidence or develop a positive orientation to arouse excitement. (shrink)

l‐Lactate is emerging as a crucial regulatory nexus for energy metabolism in the brain and signaling transduction in synaptic plasticity, memory processes, and drug addiction instead of being merely a waste by‐product of anaerobic glycolysis. In this review, the role of lactate in various memory processes, synapse plasticity and drug addiction on the basis of recent studies is summarized and discussed. To this end, three main parts are presented: first, lactate as an energy substrate in energy metabolism of the brain (...) is described; second, lactate as a novel signaling molecule in synaptic plasticity, neural circuits, memory, and drug addiction is described; and third, in light of the above descriptions, it is plausible to speculate that lactate is predominantly a signaling molecule in specific memory processes and partly acts as an energy substrate. The future perspective in lactate signaling involving microglia and associated precise signaling pathways in the brain is highlighted. (shrink)

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume and the complex modeling requirements increase the difficulty of deep learning modeling, and the classical centralized deep learning modeling scheme has encountered bottlenecks in the improvement of model performance (...) and the diversification of smart application scenarios. The parallel processing system in deep learning links the virtual information space with the physical world, although the distributed deep learning research has become a crucial concern with its unique advantages in training efficiency, and improving the availability of trained models and preventing privacy disclosure are still the main challenges faced by related research. To address these above issues in distributed deep learning, this research developed a clonal selective optimization system based on the federated learning framework for the model training process involving large-scale data. This system adopts the heuristic clonal selective strategy in local model optimization and optimizes the effect of federated training. First of all, this process enhances the adaptability and robustness of the federated learning scheme and improves the modeling performance and training efficiency. Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy. (shrink)

Although the target article provides strong evidence against the locationist view, evidence for the constructionist view is inconclusive, because co-activation of brain regions does not necessarily imply connectivity between them. We propose a rigorous approach wherein connectivity between co-activated regions is first modeled using exploratory Granger causality, and then confirmed using dynamic causal modeling or Bayesian modeling.

With the expansion of the digital business line, the network flow behind the digital power grid is also exploding. To prevent network congestion, this article proposes a novel network flow forecasting model, which is composed of variational mode decomposition, GRU-xgboost block, and a forecasting adjustment block, to grasp the changing patterns and trends of network flow in advance, and to formulate reasonable and effective flow management strategies and meet the requirements of users for network service quality. The network flow series (...) in power grid enterprise always contain complex patterns and outliers, and VMD is applied to adaptively process complex net flow time series into several subseries with simpler patterns. A GRU-xgboost block is designed to reconstruct the features of historical series. Then, xgboost model is applied to generate predictions for all decomposed subsignals. For the final predictions, we design a forecasting adjustment block to further remove the influence of random noise. Finally, the empirical results show the superior performance of the proposed model on network flow forecasting task. (shrink)

Adaptive dynamic programming, which belongs to the field of computational intelligence, is a powerful tool to address optimal control problems. To overcome the bottleneck of solving Hamilton–Jacobi–Bellman equations, several state-of-the-art ADP approaches are reviewed in this paper. First, two model-based offline iterative ADP methods including policy iteration and value iteration are given, and their respective advantages and shortcomings are discussed in detail. Second, the multistep heuristic dynamic programming method is introduced, which avoids the requirement of initial admissible control and achieves (...) fast convergence. This method successfully utilizes the advantages of PI and VI and overcomes their drawbacks at the same time. Finally, the discrete-time optimal control strategy is tested on a power system. (shrink)

This chapter contains section titled: Literary Revolution and its Meaning The Naturalistic Conception of the Universe and the Experimentalist Method History of Chinese Philosophy and Systematizing the National Heritage Political Philosophy and Liberalism Hu Shi as an Enlightenment Philosopher.

di yi juan. Wen yi mei xue -- di er juan. Zhongguo gu dian wen yi xue -- di san juan. Bi jiao wen yi xue --di si juan. Wen hua mei xue -- di wu juan. Mei de zhui xun.

On the qualities considered to be negative in a woman as per Islamic teachings.

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and (...) made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

ABSTRACT Academic dishonesty has remained high in Chinese college students. We examined Chinese college senior students’ everyday academic practices, especially academic dishonesty, considering the contextual changes inside and outside higher learning settings in China. Data were collected from 120 college seniors from four universities and were analyzed using a qualitative content-based exploratory approach in NVivo 10. Three themes were identified, including college seniors’ perceptions of academic dishonesty, contextual influences on academic dishonesty, and seniors’ personal attitudes about academic misconduct. Interview results (...) indicated that the contextual changes have reduced cheating both at the national level and at the college level; however, some contextual factors stubbornly remain unchanged, suggesting that the current, contextual climate on and beyond the Chinese college campuses should be restructured, not necessarily exclusively using top-down approaches. A theoretical model was provided to illustrate mechanisms associated with these students’ academic misconduct. Suggestions are discussed regarding future research and implications made for university personnel practice. (shrink)

ABSTRACT: According to a traditional account, understanding why X occurred is equivalent to knowing that X was caused by Y. This paper defends the account against a major objection, viz., knowing-that is not sufficient for understanding-why, for understanding-why requires a kind of grasp while knowledge-that does not. I discuss two accounts of grasp in recent literature and argue that if either is true, then knowing that X was caused by Y entails at least a rudimentary understanding of why X occurred. (...) If my defense is successful, it would cast doubt on an influential account of the epistemic value of understanding. (shrink)

In our socialist motherland today, the broad masses of women are no longer staying inside their homes; rather, they have walked out of the doors and the gates of their houses, and have joined the ranks of the great army of laborers in all professions and occupations in the society.

The Cambridge Analytica–Facebook scandal led to widespread concern over the methods deployed by Cambridge Analytica to target voters through psychographic profiling algorithms, built upon Facebook user data. The scandal ultimately led to a record-breaking $5 billion penalty imposed upon Facebook by the Federal Trade Commission in July 2019. The FTC action, however, has been criticized as failing to adequately address the privacy and other harms emanating from Facebook’s release of approximately 87 million Facebook users’ data, which was exploited without user (...) authorization. This Essay summarizes the FTC’s response to the Cambridge Analytica–Facebook scandal. It concludes that the scandal focuses attention on the need to explore the potential for embedding due process-type inquiries and protections within the enforcement actions by regulatory agencies such as the FTC. These protections are increasingly important in addressing the problem of “black boxing the voter” that is now presented by data- and algorithmic-driven companies such as Cambridge Analytica and Facebook. (shrink)