[Multifractal Analysis of Rapeseed Spectrum for Chlorophyll Diagnosis Modeling].

One of the most important topics in crop information science is how to make use of the crop's information for non-destructive nutrient diagnosis which can be solved with spectrum analysis. The canopy's spectrum feature is a key indicator to describe the nutritional status for the rapeseeds. The original spectrum is to be disturbed with external factors such as environment and climate; however, it is difficult to be directly used for rapeseed biomass diagnosis due to its huge fluctuation. However, the multifractal feature of the spectra remains stable relatively. In order to study the relationship between the canopy's spectrum of the rapeseed and its chlorophyll, based on the multifractal theory, a quantitative model of chlorophyll prediction and a qualitative model of planting pattern identification were proposed in this paper to study the high oleic acid rapeseed samples in 24 transplanting regions and 24 direct planting regions. At first, the generalized Hurst exponent and mass exponents together with other relevant multifractal parameters of the spectra were extracted with popular multifractal detrended fluctuation analysis (MF-DFA) in different six considered wavelength ranges. It shows that all of them possess representative multifractal nature. However, there are some differences of the multifractal characteristics between the two kinds of regions with different planting pattern in some bands. In addition, by correlation analysis and detection between the multifractal parameters of the spectra and the SPAD values in six considered ranges of bands, it demonstrates that there is some difference of the effective information content in the different ranges of bands. In the quantitative model of chlorophyll prediction, for each groups of samples in transplanting regions and direct planting regions and mixed together in each significant bands, a selected multifractal parameter was used to establish the univariate model for predicting the rapeseed leaf's SPAD values, respectively. The results of all the relative root mean square errors are small than 5%. Finally, the qualitative model was proposed to distinguish the samples by the two planting pattern. Youden index, as the identification accuracy was calculated for the six considered ranges of bands by the Fisher's linear discriminant analysis. The best Youden index is 0.902 5 and the corresponding band range is 350~1 350 nm. The significant work provides a theoretical and practical method for predicting rapeseed leaf's SPAD and also provides effective way to find the sensitive bands of the spectra for identification diagnosis.

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis.

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF-XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF-XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

[Oxidative Stress Status and Its Effect on Regulation of Hepcidin in Patients with HbHCS].

OBJECTIVE: To investigate the oxidative stress status and its effects on hepcidin in patients with hemoglobin H Constant Spring disease (HbH-CS). METHODS: A total of 35 patients were enrolled in the study, including 15 splenectomized cases and 20 non-splenectomized cases. 20 healthy volunteers were selected as controls. Serum superoxide dismutase (SOD), malondialdehyde (MDA), glutathione (GSH), oxidized glutathione (GSSG) levels, erythropoietin (EPO), serum free transferrin receptor (sFTR), growth differentiation factor 15 (GDF15) as well as the level of hepcidin were detected. Correlation analysis and multiple factor regression analysis were performed to investigate the factors affecting the iron metabolism and erythropoiesis. RESULTS: Compared with healthy control, the SOD and GSH levels in patients with HbHCS decreased, while MDA and GSSG levels increased. The levels of SOD, MDA, GSG and GSSG were not significantly different between the patients with splenectomy and those without splenectomy. Correlation analysis showed that inpatients with HbHCS, EPO, sFTR and GDF15 correlated negatively with SOD level and positively with MDA level. EPO and sFTR levels negatively correlated with Hepcidin. CONCLUSION: Excessive oxidative stress is present in patients with HbHCS, and hepcidin is inhibited by the upregulation of EPO and sFTR, and hence involved in iron overload in patients.

Two-dimensional multifractal detrended fluctuation analysis for plant identification.

BACKGROUND: In this paper, a novel method is proposed to identify plant species by using the two- dimensional multifractal detrended fluctuation analysis (2D MF-DFA). Our method involves calculating a set of multifractal parameters that characterize the texture features of each plant leaf image. An index, I 0, that characterizes the relation of the intra-species variances and inter-species variances is introduced. This index is used to select three multifractal parameters for the identification process. The procedure is applied to the Swedish leaf data set containing leaves from fifteen different tree species. RESULTS: The chosen three parameters form a three-dimensional space in which the samples from the same species can be clustered together and be separated from other species. Support vector machines and kernel methods are employed to assess the identification accuracy. The resulting averaged discriminant accuracy reaches 98.4% for every two species by the 10 - fold cross validation, while the accuracy reaches 93.96% for all fifteen species. CONCLUSIONS: Our method, based on the 2D MF-DFA, provides a feasible and efficient procedure to identify plant species.