Multiscale Fluctuation Features of the Dynamic Correlation between Bivariate Time Series

The fluctuation of the dynamic correlation between bivariate time series has some special features on the time-frequency domain. In order to study these fluctuation features, this paper built the dynamic correlation network models using two kinds of time series as sample data. After studying the dynamic correlation networks at different time-scales, we found that the correlation between time series is a dynamic process. The correlation is strong and stable in the long term, but it is weak and unstable in the short and medium term. There are key correlation modes which can effectively indicate the trend of the correlation. The transmission characteristics of correlation modes show that it is easier to judge the trend of the fluctuation of the correlation between time series from the short term to long term. The evolution of media capability of the correlation modes shows that the transmission media in the long term have higher value to predict the trend of correlation. This work does not only propose a new perspective to analyze the correlation between time series but also provide important information for investors and decision makers

Correction: Surface Vulnerability of Cerebral Cortex to Major Depressive Disorder

Major depressive disorder (MDD) is accompanied by atypical brain structure. This study first presents the alterations in the cortical surface of patients with MDD using multidimensional structural patterns that reflect different neurodevelopment. Sixteen first-episode, untreated patients with MDD and 16 matched healthy controls underwent a magnetic resonance imaging (MRI) scan. The cortical maps of thickness, surface area, and gyrification were examined using the surface-based morphometry (SBM) approach. Increase of cortical thickness was observed in the right posterior cingulate region and the parietal cortex involving the bilateral inferior, left superior parietal and right paracentral regions, while decreased thickness was noted in the parietal cortex including bilateral pars opercularis and left precentral region, as well as the left rostral-middle frontal regions in patients with MDD. Likewise, increased or decreased surface area was found in five sub-regions of the cingulate gyrus, parietal and frontal cortices (e.g., bilateral inferior parietal and superior frontal regions). In addition, MDD patients exhibited a significant hypergyrification in the right precentral and supramarginal region. This integrated structural assessment of cortical surface suggests that MDD patients have cortical alterations of the frontal, parietal and cingulate regions, indicating a vulnerability to MDD during earlier neurodevelopmental process

Altered brain network modules induce helplessness in major depressive disorder

The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD

Diet Mediate the Impact of Host Habitat on Gut Microbiome and Influence Clinical Indexes by Modulating Gut Microbes and Serum Metabolites

The impact of external factors on the human gut microbiota and how gut microbes contribute to human health is an intriguing question. Here, the gut microbiome of 3,224 individuals (496 with serum metabolome) with 109 variables is studied. Multiple analyses reveal that geographic factors explain the greatest variance of the gut microbiome and the similarity of individuals' gut microbiome is negatively correlated with their geographic distance. Main food components are the most important factors that mediate the impact of host habitats on the gut microbiome. Diet and gut microbes collaboratively contribute to the variation of serum metabolites, and correlate to the increase or decrease of certain clinical indexes. Specifically, systolic blood pressure is lowered by vegetable oil through increasing the abundance of Blautia and reducing the serum level of 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1), but it is reduced by fruit intake through increasing the serum level of Blautia improved threonate. Besides, aging-related clinical indexes are also closely correlated with the variation of gut microbes and serum metabolites. In this study, the linkages of geographic locations, diet, the gut microbiome, serum metabolites, and physiological indexes in a Chinese population are characterized. It is proved again that gut microbes and their metabolites are important media for external factors to affect human health

Locating the Principal Sectors for Carbon Emission Reduction on the Global Supply Chains by the Methods of Complex Network and Susceptible–Infective Model

How to locate the reasonable targets for carbon emission reduction in the complex global supply chain remains a big challenge for policy makers. This paper proposed a novel framework for finding more accurate carbon emission reduction targets, combining multi-regional input-output analysis, complex network approach and an improved susceptible–infective model called the influence spreading model. The results showed that the global embodied carbon emission flow network had the characteristic of being significantly scale-free, and there were a few important industrial sectors in the network with different capabilities, including strength-out, closeness-out, betweenness and clustering coefficient. The simulation results of the influence spreading process showed that the effective infection thresholds were relatively low, which were between 0 and 0.005 due to the significant scale-free characteristic of the global embodied carbon emission flow network. With the change of the infection thresholds, the proportion of the infected sectors significantly decreased from about 0.95 to 0.10 on average, and spread time also decreased from about three rounds to about eight rounds. In the aspects of the spreading scope and spreading speed, the industrial sectors with high closeness-out and betweenness had better performance than the ones with high strength-out. This indicated that the spreading capabilities of industrial sectors which exported significant carbon emissions, such as petroleum, chemicals and non-metallic mineral products in China, were commonly weaker than industrial sectors which occupied the most important positions in the entire supply chain, such as transport equipment in Germany. Hence, the industrial sectors with high global spreading capability and media capability were important for global carbon emission reduction. Such information suggested that the policies for carbon emission reduction should be made based on a global perspective of the supply chain system. This work proved that the policies for carbon emission reduction should be based on a global perspective of supply chain system

A Game-Theoretic Approach to Solve Competition between Multi-Type Electric Vehicle Charging and Parking Facilities

This paper investigates the competition problem between electric vehicle charging and parking desks for different owners using a non-cooperative Bertrand game. There is growing attention on electric vehicles from both policy makers and the public charging service provider, as well as the electric vehicle owners. The interaction between different entities forms a competition (game), especially between multi-type electric vehicle charging and parking facilities. Most of the existing studies on charging platforms are about the optimization of the charging platform scheduling strategy or the game relationship between charging platforms and EV users, but there is a lack of exploration on the revenue game between charging platforms. In this paper, the competitive interactions between different charging decks are studied and analyzed using a general game-theoretic framework, specifically the Nikaido–Isoda solution. In the pricing competition model, the pricing strategies of all players and physical constraints, such as distribution line capacity, are taken into consideration. Through the case studies, it is clearly indicated that the game played between different electric vehicle charging/parking decks will always converge to a Nash equilibrium point. Both charging service providers and customers could benefit from such an open and fully competitive energy service ecosystem, which enhances the overall social welfare

The Multiscale Fluctuations of the Correlation between Oil Price and Wind Energy Stock

Wind energy is considered a clear and sustainable substitution for fossil fuel, and the stock index of the wind energy industry is closely related to the oil price fluctuation. Their relationship is characterized by multiscale and time-varying features based on a variety of stakeholders who have different objectives within various time horizons, which makes it difficult to identify the factor in which time scale could be the most influential one in the market. Aiming to explore the correlation between oil price and the wind energy stock index from the time–frequency domain in a dynamic perspective, we propose an algorithm combining the wavelet transform, complex network, and gray correlation analyses and choose the Brent oil price and the international securities exchange (ISE) global wind energy index from January 2006 to October 2015 in daily frequency as data sample. First, we define the multiscale conformation by a set of fluctuation information with different time horizons to represent the fluctuation status of the correlation of the oil–wind nexus rather than by a single original correlation value. Then, we transform the multiscale conformation evolution into a network model, and only 270 multiscale conformations and 710 transmissions could characterize 2451 data points. We find that only 30% of conformations and transmissions work as a backbone of the entire correlation series; through these major conformations, we identify that the main factor that could influence the oil–wind nexus are long-term components, such as policies, the status of the global economy and demand–supply issues. In addition, there is a clustering effect and transmissions among conformations that mainly happen inside clusters and rarely among clusters, which means the interaction of the oil–wind nexus is stable over a short period of time

Detecting the significant nodes in two-layer flow networks: an interlayer non-failure cascading effect perspective

Detecting the significant nodes in multilayer networks is crucial for preventing the large-scale spread of disaster events. However, the existing model can hardly simulate the ubiquitous non-failure cascading effect process in social and economic systems. To solve this problem, first, we propose a mathematical method of constructing a two-layer network model. Then we define the non-failure cascading effect process in the two-layer network. Based on the model and spreading process, we propose a non-failure cascading effect index by using each node's non-failure cascading affecting in uential degree on the two-layer network. We then applied the detecting model in theoretical two-layer networks. We find there exist significant nodes, and also exist several in uential factors of the interlayer cascading effect process. The detecting model is applied in the two-layer industrial input{ output networks between the U.S. and China for testing the validity of the theoretical model. The hybrid network combination is relatively more sensitive to in uential factors; the significant nodes are more prominent in scale-free networks. Our research provides a solution for finding the significant nodes in two-layer social or economic networks based on the non-failure cascading effect process