Chinese science diplomacy in Arctic climate governance based on a survey and interviews with Chinese scientists

Science diplomacy is attracting increasing attention in the international relations literature. This study investigates how Chinese scientists understand this term and explores China’s dynamic praxis in Arctic climate governance. It conducts a theoretical and practical examination of science diplomacy in terms of three dimensions—science in diplomacy, diplomacy for science, and science for diplomacy—thus achieving a high degree of consistency. A multi-method approach, combining qualitative and quantitative research methodologies and involving the adoption of a literature review, participant interviews, and questionnaires, is adopted. Data were collected from interviews with 16 Chinese scientists involved in Arctic climate governance and from 130 valid questionnaires collected from Chinese natural scientists working in the climate change field. Drawing on qualitative and quantitative findings, the study reveals that the three-dimensional framework of science diplomacy can provide insight into Chinese scientists’ understandings of the topic. In contrast to the participants’ vague theoretical responses, the outlines of China’s Arctic climate governance can be clearly identified within this framework. The study concludes by underlining the tension between theory and practice in terms of science diplomacy and highlighting the emerging challenges for China in developing its Arctic science diplomacy against the background of the COVID-19 pandemic and Russia-Ukraine conflict. Moreover, it is suggested that, to further develop China’s Arctic science diplomacy, it is vital to take account of the deficiencies in China’s science diplomacy. The study’s empirical results contribute to an understanding of the dynamic nature of science diplomacy in the Chinese context

Physical and virtual water transfers for regional water stress alleviation in China

Water can be redistributed through, in physical terms, water transfer projects and virtually, embodied water for the production of traded products. Here, we explore whether such water redistributions can help mitigate water stress in China. This study, for the first time to our knowledge, both compiles a full inventory for physical water transfers at a provincial level and maps virtual water flows between Chinese provinces in 2007 and 2030. Our results show that, at the national level, physical water flows because of the major water transfer projects amounted to 4.5% of national water supply, whereas virtual water flows accounted for 35% (varies between 11% and 65%at the provincial level) in 2007. Furthermore, our analysis shows that both physical and virtualwater flows do not play a major role in mitigating water stress in the water-receiving regions but exacerbate water stress for the water-exporting regions of China. Future water stress in the main water-exporting provinces is likely to increase further based on our analysis of the historical trajectory of the major governing socioeconomic and technical factors and the full implementation of policy initiatives relating to water use and economic development. Improving water use efficiency is key to mitigating water stress, but the efficiency gains will be largely offset by the water demand increase caused by continued economic development. We conclude that much greater attention needs to be paid to water demand management rather than the current focus on supply-oriented management

Three-point Step Size Gradient Method with Relaxed Generalized Armijo Step Size Rule

Based on differences of points and differences of gradients over the most recent three iterations, together with the Taylor's theorem, two forms of the quasi-Newton equations at the recent iteration are constructed. By using the two forms of the quasi-Newton equation and the method of least squares, three-point step size gradient methods for solving unconstrained optimization problem are proposed. It is proved by using the relaxed generalized Armijo step size rule that the new method is of global convergence properties if the gradient function is uniformly continuous. Moreover, it is shown that, when the objective function is pseudo-convex (quasi-convex) function, the new method has strong convergence results. In addition, it is also shown under some suitable assumptions that the new method is of super-linear and linear convergence. Although multi-piont information is used, TBB has the feature of simplicity, low memory requirement and only first order information being used, the new method is very suitable for solving large-scale optimization problems. Numerical experiments are provided and the efficiency, robustness and analysis of TBB are confirmed

Microscopic observation of lateral and vertical charge transportation in Si nanocrystals sandwiched by amorphous SiC layers

Charge injection and transportation process is a fundamental problem to Si nanocrystals (Si-ncs) based electric and photonic devices. In the manuscript, a single layer of Si-ncs sandwiched by amorphous Si carbide (a-SiC) was prepared by excimer laser annealing of a-SiC/a-Si/a-SiC multilayers, and the charging effect was then characterized by Kelvin probe force microscopy (KPFM) on the microscopic scale. Opposite charges were injected into Si-ncs through the biased tip and formed a core-ring or up-down shaped distribution. The decay characteristics showed that these opposite charges would not only vertically tunnel through the bottom a-SiC layer to substrate but also laterally transport and recombine with each other driven by the attractive Coulomb force. Besides, the charge retention time was also found dependent on the injection biases, which is tentatively ascribed to the charge trapping by the Si-ncs/a-SiC interface states under high bias scanning. The analysis was further supported by conductive atomic force microscopy (CAFM) measurement, in which the current-voltage curves gradually shifted during the repetition test, probably because of bias screening by the trapped charges at these interface states

Research on Sentiment Classification of Online Travel Review Text

In recent years, the number of review texts on online travel review sites has increased dramatically, which has provided a novel source of data for travel research. Sentiment analysis is a process that can extract tourists’ sentiments regarding travel destinations from online travel review texts. The results of sentiment analysis form an important basis for tourism decision making. Thus far, there has been minimal concern as to how sentiment analysis methods can be effectively applied to improve the effect of sentiment analysis. However, online travel review texts are largely short texts characterized by uneven sentiment distribution, which makes it difficult to obtain accurate sentiment analysis results. Accordingly, in order to improve the sentiment classification accuracy of online travel review texts, this study transformed sentiment analysis into a multi-classification problem based on machine learning methods, and further designed a keyword semantic expansion method based on a knowledge graph. Our proposed method extracts keywords from online travel review texts and obtains the concept list of keywords through Microsoft Knowledge Graph. This list is then added to the review text to facilitate the construction of semantically expanded classification data. Our proposed method increases the number of classification features used for short text by employing the huge corpus of information associated with the knowledge graph. In addition, this article introduces online travel review text preprocessing, keyword extraction, text representation, sampling, establishment classification labeling, and the selection and application of machine learning-based sentiment classification methods in order to build an effective sentiment classification model for online travel review text. Experiments were implemented and evaluated based on the English review texts of four famous attractions in four countries on the TripAdvisor website. Our experimental results demonstrate that the method proposed in this paper can be used to effectively improve the accuracy of the sentiment classification of online travel review texts. Our research attempts to emphasize and improve the methodological relevance and applicability of sentiment analysis for future travel research

Investigation into Influence of Wall Roughness on the Hydraulic Characteristics of an Axial Flow Pump as Turbine

Pump as turbine (PAT) is a factual alternative for electricity generation in rural and remote areas where insufficient or inconsistent water flows pose a threat to local energy demand satisfaction. Recent studies on PAT hydrodynamics have shown that its continuous operations lead to a progressive deterioration of inner surface smoothness, serving the source of near-wall turbulence build-up, which itself depends on the level of roughness. The associated boundary layer flow incites significant friction losses that eventually deteriorate the performance. In order to study the influence of wall roughness on PAT hydraulic performance under different working conditions, CFD simulation of the water flow through an axial-flow PAT has been performed with a RNG k-ε turbulence model. Study results have shown that wall roughness gradually decreases PAT’s head, efficiency, and shaft power. Nevertheless, the least wall roughness effect on PAT hydraulic performance was experienced under best efficiency point conditions. Wall roughness increase resulted in the decrease of axial velocity distribution uniformity and the increase of velocity-weighted average swirl angle. This led to a disorderly distribution of streamlines and backflow zones formation at the conduit outlet. Furthermore, the wall roughness impact on energy losses is due to the static pressure drop on the blade pressure surface and the increase of turbulent kinetic energy near the blade. Further studies on the roughness influence over wider range of PAT operating conditions are recommended, as they will lead to quicker equipment refurbishment

<i>Flammulina velutipes</i> Mycorrhizae Attenuate High Fat Diet-Induced Lipid Disorder, Oxidative Stress and Inflammation in the Liver and Perirenal Adipose Tissue of Mice

Flammulina velutipes (FV) is edible mushroom that has nutritional and medicinal values. FV mycorrhizae, the by-products of FV, are an abundant source and receive less attention. The objective of this study was to investigate the composition of FV mycorrhizae, and its effects on high fat diet (HFD)-induced lipid disorder, oxidative stress, and inflammatory cytokines, both in the liver and perirenal adipose tissue (PAT) of mice. The results showed that FV mycorrhizae contain abundant trace elements, polysaccharide, amino acids and derivatives, and organic compounds. It was found that 4% FV mycorrhizae (HFDFV) supplementation decreased HFD-induced liver weight and triglyceride (TG) in the plasma, liver and PAT, altered plasma and hepatic fatty acids profiles, promoted gene expression involved in lipid hydrolysis, fatty acid transportation and β-oxidation in the liver and reduced lipid synthesis in the liver and PAT. HFDFV attenuated HFD-induced oxidative stress and pro-inflammatory cytokine by increasing GSH/GSSG, and decreasing levels of MDA and IL6 both in the liver and PAT, while it differentially regulated gene expression of IL1β, IL6, and CCL2 in liver and PAT. The results indicated that FV mycorrhizae are effective to attenuate HFD-induced lipid disorder, oxidative stress and inflammation in the liver and PAT, indicating their promising constituents for functional foods and herbal medicine

The effects and mechanisms of natural products on Helicobacter pylori eradication

Helicobacter pylori (H. pylori) eradication is pivotal for alleviating gastric mucosal inflammation and preventing the progression of gastric diseases. While antibiotic-based therapies have achieved significant success in H. pylori eradication, challenges such as antibiotic resistance, drug toxicity, side effects, nonadherence, inapplicability, and disruption of gastrointestinal microflora have emerged. Updated therapies are urgently needed to suppress H. pylori. Nature has provided multitudinous therapeutic agents since ancient times. Natural products can be a potential therapy endowed with H. pylori eradication efficacy. We summarize the basic information, possible mechanisms, and the latest research progress of some representative natural products in H. pylori eradication, highlighting their safety, accessibility, efficiency, and ability to overcome limitations associated with antibiotic application. This review highlights the potential therapeutic advantages of incorporating ethnomedicine into anti-H. pylori regimens. The findings of this review may provide insights into the development of novel natural products and expand the therapeutic options available for H. pylori eradication

Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality

In order to improve the quality of fingerprint with large noise, this paper proposes a fingerprint enhancement method by using a sparse representation of learned multi-scale classification dictionaries with reduced dimensionality. Multi-scale dictionary is used to balance the contradiction between the accuracy and the anti-noise ability, which has been shown to be an ideal solution to reconcile the demands of enhancement quality and computational performance. Principal component analysis (PCA)is applied in our technique for dimension reduction of multi-scale classification dictionaries. Under the quality grading scheme and multi-scale composite windows, the fingerprint patches are enhanced by using a sparse representation of learned multi-scale classification dictionaries with reduced dimensionality according to their priorities. In addition, the multi-scale composite windows help the more high quality spectra diffuse into the low quality fingerprint patches and this can greatly improve the spectra quality of them. Experimental results and comparisons on FVC 2000 and FVC 2004 databases are reported.And it shows that the proposed method yields better result in terms of the robustness of fingerprint enhancement as compared with latest techniques.Moreover, the results show that the proposed algorithm can obtain better identification performanc