Extensive research has been carried out on the “Belt and Road” initiative, most of it focusing on geographical economy and international trade. However, there is a lack of research on the carbon emissions efficiency of the countries along the “Belt and Road,” especially regarding the impact of freight trade. To address this research gap, this paper first employs a metafrontier nonradial directional distance function to measure the carbon emission efficiency of 32 countries along the “Belt and Road” from 1990 to (...) 2014. It then examines the role of freight trade. Our main research findings are as follows. Firstly, the carbon emission efficiency of the countries along the “Belt and Road” is generally low. Among them, Russia and Central Asia are mainly due to the large between-group gap in carbon emission efficiency, while Southeast Asia, Western Asia and North Africa, East Asia, South Asia, and Central and Eastern Europe are mainly due to the large within-group gap. Secondly, freight trade promotes carbon emission efficiency, but it will aggravate the gap between the contemporaneous technology and the group technology. Freight trade mainly promotes the contemporaneous carbon emission efficiency and group-frontier carbon emission efficiency of low fossil energy dependent countries, and the metafrontier carbon emission efficiency of high fossil energy dependent countries. Thirdly, foreign direct investment has a significant negative effect on a host country’s ITCEI and GTCEI, and it will decrease the gap between the group technology and the metafrontier technology. However, freight trade can effectively prevent the entry of FDI, thereby indirectly improving carbon emission efficiency and reducing carbon emission gap. (shrink)

Background Ethical considerations play a prominent role in the protection of human subjects in clinical research. To date the disclosure of ethical protection in clinical research published in the international nursing journals has not been explored. Our research objective was to investigate the reporting of ethical approval and informed consent in clinical research published in leading international nursing journals. Methods This is a retrospective observational study. All clinical research published in the five leading international nursing journals from the SCI Journal (...) Citation Reports between 2015 and 2017 were retrieved to evaluate for evidence of ethical review. Results A total of 2041 citations have been identified from the contents of all the five leading nursing journals that were published between 2015 and 2017. Out of these, 1284 clinical studies have been included and text relating to ethical review has been extracted. From these, most of prospective clinical studies discussed informed consent. Only half of those reported that written informed consent had been obtained; few reported oral consent, and few used other methods such as online consent or completion and return of data collection to denote assent. Notably, 36.2% of those did not describe the method used to obtain informed consent and merely described that “consent was obtained from participants or participants agreed to join in the research”. Furthermore, whilst most of clinical studies mentioned ethical approval; 92.5% of those stated the name of ethical committee and interestingly, only 37.1% of those mentioned the ethical approval reference. The rates of reporting ethical approval were different between different study type, country, and whether financial support was received. Conclusion The reporting of ethics in leading international nursing journals demonstrates progress, but improvement of the transparency and the standard of ethical reporting in nursing clinical research is required. (shrink)

Critical evaluation of Śaṅkarapādabhūṣaṇam of Raghunāthasūri, presenting Advaita point of view against the Dvaita school in Hindu philosophy.

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)

Labels provide a quick and effective solution to obtain people interesting content from large-scale social network information. The current interest label extraction method based on the subgraph stream proves the feasibility of the subgraph stream for user label extraction. However, it is extremely time-consuming for constructing subgraphs. As an effective mathematical method to deal with fuzzy and uncertain information, rough set-based representations for subgraph stream construction are capable of capturing the uncertainties of the social network. Therefore, we propose an effective (...) approach called RS_UNITE_SS, which is suitable for large-scale social network user interest label extraction. Specifically, we first propose the subgraph division algorithm to construct a subgraph stream by incorporating a rough set. Then, the algorithm for user real-time interest label extraction based on upper approximation is proposed by using sequentially characteristics of the subgraph. Empirically, we evaluate RS_UNITE_SS over real-world datasets, and experimental results demonstrate that our proposed approach is more computationally efficient than existing methods while achieving higher precision value and MRR value. (shrink)

Online health communities have enjoyed increasing popularity in recent years, especially in the context of the COVID-19 pandemic. However, several concerns have been raised regarding the privacy of users’ personal information in OHCs. Considering that OHCs are a type of data-sharing or data-driven platform, it is crucial to determine whether users’ health information privacy concerns influence their behaviors in OHCs. Thus, by conducting a survey, this study explores the impact of users’ health information privacy concerns on their engagement and payment (...) behavior in OHCs. The empirical results show that users’ concerns about health information privacy reduce their Paid in OHCs by negatively influencing their OHC engagement. Further analysis reveals that if users have higher benefit appraisals and lower threat appraisals, the negative effect of health information privacy concerns on users’ OHC engagement will decrease. (shrink)

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)

BackgroundSolution-focused model is an intervention method that fully mobilizes patients’ initiative through their potential. We aimed to investigate the effects of SFM on anxiety and postpartum depression in nulliparous pregnant women compared with routine care services.MethodsWe chose the mothers diagnosed as depressed or with depressive tendency by Edinburgh Postpartum Depression Scale at 28 weeks of gestation and divided them into the intervention and control groups. The control group only took the routine pregnancy healthy nursing, while the SFM group took the (...) regular nursing and SFM counselling. Different assessments were conducted at 28 weeks of gestation, post-delivery, and post-intervention to evaluate the anxiety and depression levels of the patients. Finally, nursing satisfaction was evaluated by the nursing satisfaction questionnaire.ResultsCompared with the control group, SFM could decrease the scores of anxiety and depression more effectively and influence sleep quality more positively. We also found that SFM resulted in significantly higher nursing satisfaction than that in the control group.ConclusionIn conclusion, SFM could effectively alleviate anxiety and PPD in nulliparous pregnant women. (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)

As stewards of public money, government funding agencies have the obligation and responsibility to uphold the integrity of funded research. Despite an increasing amount of empirical studies examining research-related misconduct, a majority of these studies focus on retracted publications. How agencies spot funding-relevant wrongdoing and what sanctions the offenders face remain largely unexplored. This is particularly true for public funding agencies in emerging science powers. To amend this oversight, we retrieved and analyzed all publicized investigation results from China’s largest basic (...) research funding agency over the period from 2005 to 2021. Our findings reveal that both the “police patrol” and “fire alarm” approaches are used to identify misconduct and deter funding-related fraud in China. The principal triggers for investigations are journal article retractions, whistleblowing, and plagiarism detection software. Among the six funding-related misconduct types publicized and punished, the top three are: (1) fraudulent papers, (2) information fabrication and/or falsification in the research proposal, and (3) proposal plagiarism. The most common administrative sanctions are debarment and reclamation of grants. This article argues that more systematic research and cooperation among stakeholders is needed to cultivate research integrity in emerging science powers like China. Specific training and education should be provided for young scientists to help them avoid the pitfall of academic misconduct. (shrink)

Road link speed is one of the important indicators for traffic states. In order to incorporate the spatiotemporal dynamics and correlation characteristics of road links into speed prediction, this paper proposes a method based on LDA and GCN. First, we construct a trajectory dataset from map-matched GPS location data of taxis. Then, we use the LDA algorithm to extract the semantic function vectors of urban zones and quantify the spatial dynamic characteristics of road links based on taxi trajectories. Finally, we (...) add semantic function vectors to the dataset and train a graph convolutional network to learn the spatial and temporal dependencies of road links. The learned model is used to predict the future speed of road links. The proposed method is compared with six baseline models on the same dataset generated by GPS equipped on taxis in Shenzhen, China, and the results show that our method has better prediction performance when semantic zoning information is added. Both composite and single-valued semantic zoning information can improve the performance of graph convolutional networks by 6.46% and 8.35%, respectively, while the baseline machine learning models work only for single-valued semantic zoning information on the experimental dataset. (shrink)

System security is essential for the operation of the island microgrid. However, the system security is generally threatened due to the presence of physical uncertainties and cyber attacks. In this article, a novel sliding mode load control strategy is proposed for the microgrid to mitigate cyber attacks and physical uncertainties. Firstly, a high-order disturbance observer is designed to estimate the unmeasurable factors in the microgrid. Secondly, a HODO-based sliding mode control strategy is proposed where the estimated value observed by the (...) HODO is applied to the sliding mode surface and control law. It can better guarantee the security of the isolated microgrid. Then, the stability of the HODO-based SMC is demonstrated by Lyapunov stability theory. Finally, simulation results show that the proposed control strategy has excellent control performance. (shrink)

The picture-word interference paradigm has been used to investigate the time course of processes involved in word retrieval, but is challenging to implement online due to dependence on measurements of vocal reaction time. We performed a series of four experiments to examine picture-word interference and facilitation effects in a form of covert picture naming, with and without gamification. A target picture was accompanied by an audio word distractor that was either unrelated, phonologically-related, associatively-related, or categorically-related to the picture. Participants were (...) instructed to judge whether the name of the target picture ended in the phoneme assigned to the block by pressing corresponding keys as quickly and accurately as possible. Experiments 1 and 2 successfully replicated categorical interference and phonological facilitation effects at different optimal stimulus-onset-asynchronies between words and pictures. Experiment 3 demonstrated that a key gamification feature motivated faster speed at the expense of accuracy in the gamified vs. experimental format of the task. Experiment 4 adopted the optimal SOAs and verified that the gamification reveals expected interference and facilitation effects despite the speed-accuracy tradeoff. These studies confirmed that categorical interference occurs earlier than phonological facilitation, while both processes are independent from articulation and inherent to word retrieval itself. The covert PWI paradigm and its gamification have methodological value for neuroimaging studies in which articulatory artifacts obscure word retrieval processes, and may be developed into potential online word-finding assessments that can reveal word retrieval difficulties with greater sensitivity. (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.

本卷收入胡适哲学与文化方面的论文、函牍、讲演、札记80余篇。其中包括实验主义、我们对于西洋近代文明的态度等重要文章。所收文章全面反映了胡适哲学思想、学术主张和对于中西文化的态度,对于了解和研究胡适本人 以及现代中国学术史、现代中国启蒙运动等内容。.

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