While it is generally recognized that the introduction of environmental policy can effectively control carbon emissions, the green paradox hypothesis puts forth a new warning about the validity of ...this policy's implementation. This study uses panel data on 29 Chinese provinces from 1995 to 2012 to investigate the impact of fiscal decentralization on the functional mechanisms of environmental policy while controlling for the spatial correlations of carbon emission. The empirical results indicate that environmental policy alone can achieve the objective of reducing carbon emissions. However, the Chinese style fiscal decentralization makes the environmental policy significantly promote carbon emissions, leading to a green paradox. Moreover, we find that the impact of fiscal decentralization on environmental policy varies greatly among different geographical regions and the direct-controlled municipalities. In addition, our study confirms the spatial correlations in China's carbon emissions by using a spatial integration term. Finally, we recommend that emission reduction efforts should be incorporated into the local government's performance evaluation system to improve the institutional environment. Further, differentiated environmental policies and measures should be considered for different provinces to maximize the emission reduction potential.
•We consider the spatial correlations of carbon emissions in neighboring provinces.•The impacts of environmental regulation on carbon emissions are examined.•Fiscal decentralization is not beneficial to environmental policy implementation.•The effects of fiscal decentralization vary greatly among different regions.
According to different application scenarios of blockchain system, it is generally divided into public chain, private chain and consortium chain. Consortium chain is a typical multi-center ...blockchain, because it has better landing, it is supported by more and more enterprises and governments. This paper analyzes the advantages and problems of Practical Byzantine Fault Tolerance (PBFT) algorithm for the application scenarios of the consortium chain. In order to be more suitable for consortium chains, this paper proposes a new optimized consensus algorithm based on PBFT. Aiming at the shortcomings of PBFT, such as the inability to dynamically join nodes, low multi-node consensus efficiency, and primary master node selection, our optimized algorithm has designed a hierarchical structure to increase scalability and improve consensus efficiency. The simulation results show that compared with PBFT and RAFT, our new consensus algorithm increases the data throughput while supporting more nodes, and effectively reducing the consensus delay and the number of communication times between nodes.
Abstract Helicobacter pylori ( H. pylori ) infect over half of the world’s population. The prevalence of H. pylori infection and the predominant genotype of H. pylori virulence factors vary ...considerably across different geographical regions. H. pylori could uniquely persist for decades in the harsh stomach environment, where it damages the gastric mucosa and changes the pattern of gastric hormone release, thereby affects gastric physiology. By utilizing various virulence factors, H. pylori targets different cellular proteins to modulate the host inflammatory response and initiate multiple “hits” on the gastric mucosa, resulting in chronic gastritis and peptic ulceration. Among the long-term consequences of H. pylori infection is gastric malignancies, particularly gastric cancer (GC) and gastric mucosa-associated lymphoid tissue (MALT) lymphoma. As such, H. pylori has been recognized as a class I carcinogen by the International Agency for Research on Cancer. Despite a close causal link between H. pylori infection and the development of gastric malignancies, the precise mechanisms involved in this process are still obscure. Studies over the past two decades have revealed that H. pylori exert oncogenic effects on gastric mucosa through a complex interaction between bacterial factors, host factors, and environmental factors. Numerous signaling pathways can be activated by H. pylori. In this review, we aim to elaborate on the recent developments in the pathophysiological mechanisms of H. pylori -induced gastric inflammation and gastric cancer.
A carbon nanotube (CNT)/polyaniline (PANI) composite is evaluated as an anode material for high-power microbial fuel cells (MFCs). Fourier transform infrared spectroscopy (FTIR) and scanning electron ...microscopy (SEM) are employed to characterize the chemical composition and morphology of plain PANI and the CNT/PANI composite. The electrocatalytic behaviour of the composite anode is investigated by means of electrochemical impedance spectroscopy (EIS) and discharge experiments. The current generation profile and constant current discharge curves of anodes made from plain PANI, 1
wt.% and 20
wt.% CNT in CNT–PANI composites reveal that the performance of the composite anodes is superior. The 20
wt.% CNT composite anode has the highest electrochemical activity and its maximum power density is 42
mW
m
−2 with
Escherichia coli as the microbial catalyst. In comparison with the reported performance of different anodes used in
E. coli-based MFCs, the CNT/PANI composite anode is excellent and is promising for MFC applications.
Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic analysis of large cohorts of samples. However, sample-specific spectral libraries built by data-dependent ...acquisition (DDA) experiments are required prior to DIA analysis, which is time-consuming and limits the identification/quantification by DIA to the peptides identified by DDA. Herein, we propose DeepDIA, a deep learning-based approach to generate in silico spectral libraries for DIA analysis. We demonstrate that the quality of in silico libraries predicted by instrument-specific models using DeepDIA is comparable to that of experimental libraries, and outperforms libraries generated by global models. With peptide detectability prediction, in silico libraries can be built directly from protein sequence databases. We further illustrate that DeepDIA can break through the limitation of DDA on peptide/protein detection, and enhance DIA analysis on human serum samples compared to the state-of-the-art protocol using a DDA library. We expect this work expanding the toolbox for DIA proteomics.
Effective international cooperation is an important measure to mitigate climate change. The purpose of this study is to clarify the research progress in the field of cooperation on emission ...reduction, identify the influential authors and articles, and reveal the main research topics. Based on the bibliometric method and the Web of Science database, this study analyzes the literature in the field of cooperation on emission reduction. The results show that the publications in this field have increased significantly over the past decade, with the USA and China are the most influential countries. Keyword co-occurrence and frequency analysis show that the most important research topics are as follows: burden-sharing and equity, the stability of the climate coalition and international environmental agreements, technology transfer and climate finance, the linkage of carbon markets, and the response to noncooperation behavior. The main methods involved are game theory model, integrated assessment models, and computable general equilibrium model. Equitable distribution of mitigation responsibilities is the basis for cooperation on carbon reduction. Specific rulebooks for carbon market linkage is the key to its successful implementation. This study helps researchers to clarify the current research status in the field of cooperation on emission reduction and provide valuable information for future research.
Display omitted
•A bibliometric review of cooperation on climate mitigation was conducted.•Highly cited articles and references are discussed to explore the research theme.•Collaboration networks between countries are shown with the visualization tools.•The research hotspots are discussed based on the keywords co-occurrence analysis.
A strategy that informs on countries' potential losses due to lack of climate action may facilitate global climate governance. Here, we quantify a distribution of mitigation effort whereby each ...country is economically better off than under current climate pledges. This effort-sharing optimizing approach applied to a 1.5 °C and 2 °C global warming threshold suggests self-preservation emissions trajectories to inform NDCs enhancement and long-term strategies. Results show that following the current emissions reduction efforts, the whole world would experience a washout of benefit, amounting to almost 126.68-616.12 trillion dollars until 2100 compared to 1.5 °C or well below 2 °C commensurate action. If countries are even unable to implement their current NDCs, the whole world would lose more benefit, almost 149.78-791.98 trillion dollars until 2100. On the contrary, all countries will be able to have a significant positive cumulative net income before 2100 if they follow the self-preservation strategy.
In order to realize the collaborative resource allocation optimization of mobile edge computing (MEC) and reduce the delay of edge server in the transmission process, based on software-defined ...network (SDN) technology, two optimal edge server deployment schemes of Enumeration-Based Optimal Edge Server Placement Algorithm (EOESPA) and Ranking-based Near-optimal Edge Server Placement Algorithm (RNOESPA) are proposed. Performance comparison experiment simulation is conducted with K-Means cluster algorithm (KMCA) to verify the minimum access delay of edge server under different conditions. After the deployment of edge servers, three collaborative resource allocation optimization algorithms of Optimal Enumeration Service Deployment Algorithm (OESDA), Latency Aware Heuristic Service Deployment Algorithm (LAHSDA), and Clustering Enhanced Heuristic Service Deployment Algorithm (CEHSDA) are proposed, and simulation experiments are carried out to verify the performance of the proposed algorithm under different conditions. The results show that, under different conditions, when the number of deployments increases from 1 to 4, the average access delay of EOESPA can be at least 1ms, and the average access delay obtained by RNOESPA is close to the best performance obtained by EOESPA and better than that obtained by KMCA. When the number of network nodes increases to 50, the minimum average access delay obtained by RNOESPA is closer to the optimal value, which is about 1.42ms. The same performance is shown in relation to the average number of requests, the number of mobile devices, and the average access delay. Among the three collaborative resource allocation optimization algorithms, the minimum average response delay obtained by LAHSDA is close to the optimal average response delay obtained by OESDA, but all of them are lower than CEHSDA, and CEHSDA has the best performance in minimizing the total allocation cost. When the number of service types increases to 8, the total service configuration cost of CEHSDA is about 0.89. It can be concluded that by optimizing the deployment of the edge server, the collaborative optimal allocation of its resources can be realized.
Microfluidics based biochemical analysis shows distinctive advantages for fast detection of pathogenic microorganisms. This Feature summarizes the progress in the past decade on microfluidic methods ...for purification and detection of pathogenic bacteria and viruses as well as their applications in food safety control, environmental monitoring, and clinical diagnosis.
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