Topological energy of networks.

Energy is an important network indicator defined by the eigenvalues of an adjacency matrix that includes the neighbor information for each node. This article expands the definition of network energy to include higher-order information between nodes. We use resistance distances to characterize the distances between nodes and order complexes to extract higher-order information. Topological energy ( T E), defined by the resistance distance and order complex, reveals the characteristics of the network structure from multiple scales. In particular, calculations show that the topological energy can be used to distinguish graphs with the same spectrum well. In addition, topological energy is robust, and small random perturbations of edges do not significantly affect the T E values. Finally, we find that the energy curve of the real network is significantly different from that of the random graph, thus showing that T E can be used to distinguish the network structure well. This study shows that T E is an indicator that distinguishes the structure of a network and has some potential applications for real-world problems.

Dynamics of Information Flow between the Chinese A-Share Market and the U.S. Stock Market: From the 2008 Crisis to the COVID-19 Pandemic Period.

The relationship between the Chinese market and the US market is widely concerned by researchers and investors. This paper uses transfer entropy and local random permutation (LRP) surrogates to detect the information flow dynamics between two markets. We provide a detailed analysis of the relationship between the two markets using long-term daily and weekly data. Calculations show that there is an asymmetric information flow between the two markets, in which the US market significantly affects the Chinese market. Dynamic analysis based on weekly data shows that the information flow evolves, and includes three significant periods between 2004 and 2021. We also used daily data to analyze the dynamics of information flow in detail over the three periods and found that changes in the intensity of information flow were accompanied by major events affecting the market, such as the 2008 financial crisis and the COVID-19 pandemic period. In particular, we analyzed the impact of the S&P500 index on different industry indices in the Chinese market and found that the dynamics of information flow exhibit multiple patterns. This study reveals the complex information flow between two markets from the perspective of nonlinear dynamics, thereby helping to analyze the impact of major events and providing quantitative analysis tools for investment practice.

Hurst analysis of dynamic networks.

The sequence of network snapshots with time stamps is an effective tool for describing system dynamics. First, this article constructs a multifractal analysis of a snapshot network, in which the Hurst integral is used to describe the fractal structure hidden in structural dynamics. Second, we adjusted the network model and conducted comparative analysis to clarify the meaning of the Hurst exponent and found that the snapshot network usually includes multiple fractal structures, such as local and global fractal structures. Finally, we discussed the fractal structure of two real network datasets. We found that the real snapshot network also includes rich dynamics, which can be distinguished by the Hurst exponent. In particular, the dynamics of financial networks includes multifractal structures. This article provides a perspective to study the dynamic networks, thereby indirectly describing the fractal characteristics of complex system dynamics.

Dynamics of the price-volume information flow based on surrogate time series.

This paper uses transfer entropy and surrogates to analyze the information flow between price and transaction volume. We use random surrogates to construct local random permutation (LRP) surrogates that can analyze the local information flow in detail. The analysis based on the toy models verifies the effectiveness of the LRP method. We further apply it to analyze three financial datasets, including two index datasets and one stock dataset. Empirical analysis shows that both the S&P500 index data and SSEC index data include rich information flow dynamics. There was a stronger information flow during the stock bubble burst or the financial crisis. In addition, tests based on stock data suggest that market crises may lead to changes in the relationship between prices and trading volume. This paper provides a new way to analyze the price-volume relationship, which can effectively detect the drastic changes in the local information flow, thereby providing a method for studying the impact of events.

Relationship between Entropy and Dimension of Financial Correlation-Based Network.

We analyze the dimension of a financial correlation-based network and apply our analysis to characterize the complexity of the network. First, we generalize the volume-based dimension and find that it is well defined by the correlation-based network. Second, we establish the relationship between the Rényi index and the volume-based dimension. Third, we analyze the meaning of the dimensions sequence, which characterizes the level of departure from the comparison benchmark based on the randomized time series. Finally, we use real stock market data from three countries for empirical analysis. In some cases, our proposed analysis method can more accurately capture the structural differences of networks than the power law index commonly used in previous studies.

[Studies on chemical constituents of leaves of Aquilaria sinensis].

OBJECTIVE: To investigate the chemical constituents of the leaves of Aquilaria sinensis, and provide a certain of basis for the comprehensive uses of the plant of A. sinensis. METHOD: The chemical constituents were isolated by various column chromatographic method. The structures were identified by spectral analyses of NMR, MS, et al. RESULT: Thirteen compounds were isolated and identified as 7-hyroxy-5, 4'-dimethoxy flovone (1), 5-hydroxy-7, 4'-dimethoxy flavone (2), luteolin-7-3',4'-trimethyl (3), isocorydine (4), 4-hydroxybenzoic acid (5), triacontenoic (6), hentriacontane (7), alpha-stigmasterol (8), epifriedelanol (9), friedelan (10), friedelin (11), genkwanin (12), 5, 4'-dihyroxy-7, 3'-dimethoxy flovone (13). CONCLUSION: Compound 4 was obtained from this genus for the first time, compounds 1, 6-11, 13 were obtained from this species for the first time.

[Determination of carnosic acid in rat stomach and intestine by high performance liquid chromatography method].

OBJECTIVE: To establish a HPLC method to determine the carnosic acid in the stomach and intestine of rats and study its tissue distribution characteristics. METHOD: After intragastric administration of carnosic acid (90 mg x kg(-1)), rats for each time-point were sacrificed by decapitation. After removal of the blood, various tissues were rapidly removed and weighted, all tissues were treated with a series of pretreatment before HPLC. Chromatographic separation was achieved on a Kromasil C18 column (4.6 mm x 150 mm, 5 microm) protected by an ODS guard column at 25 degrees C, using acetonitrile-0.1% phosphoric acid solution (55:45) as mobile phase, at a flow rate of 1 mL x min(-1). The wavelength of the UV detector was set at 210 nm for carnosic acid and internal standard. RESULT: Good linearities were obtained in every tissue over a range of 0.3212-160.6 mg x L(-1). The recovery, intra-day and inter-day precision and accuracy of three concentrations of carnosic acid in tissues met the requirements of methodology. And the stability of the tissue samples were also validated. The results of distribution in stomach and intestine showed that the highest concentration was (307.1 +/- 119.2) microg x g(-1) in stomach and (33.32 +/- 17.70) microg x g(-1) in intestine after intragastric administration of carnosic acid. CONCLUSION: The HPLC method was established to determine the concentration of carnosic acid in tissues. This method is quick, precise, and reproducible. It is the first time to study the tissue distribution of carnosic acid in rats after intragastric administration.