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. 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. Our method, based on the 2D MF-DFA, provides a feasible and efficient procedure to identify plant species.

In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p _q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ _q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

This study was conducted to investigate the effects of dietary supplementation with ellagic acid (EA) on the performance, immune function, antioxidant activity, digestive enzyme activities, and intestinal functions in yellow-feathered broilers. In total, 288 healthy yellow-feathered broilers with an average body weight of 39 ± 0.24 g were randomly divided into four treatment groups. Broilers were given a corn-soybean meal basal diet supplemented with 0 (control group), 100, 200, or 400 mg/kg EA. In the finisher period and the overall period, the inclusion of 100, 200, and 400 mg/kg EA increased the average daily gain (P < 0.05), and the inclusion of 200 or 400 mg/kg EA decreased the feed/gain ratio compared with the control group (P < 0.05). The best immune activity (immunoglobulin G [IgG] and immunoglobulin M [IgM] concentrations) in serum was shown in the 200 mg/kg EA group (P < 0.05). Broilers fed with 200 or 400 mg/kg EA-containing diets exhibited higher serum catalase and glutathione peroxidase activities (P < 0.05) than control broilers. The inclusion of 200 mg/kg EA in the broiler diets increased intestinal chymotrypsin, pepsin, and lipase activities (P < 0.05). Broilers fed 200 mg/kg EA-containing diets had higher villus height in the jejunum and ileum, a higher ratio between villus height and crypt depth in the jejunum, and a deeper crypt in the duodenum compared to control broilers (P < 0.05). EA reduced the diamine oxidase activity and D-lactate concentration in serum. Furthermore, in birds fed EA-containing diets, the abundance of Rikenella and norank_f_norank_o_Clostridia_UCG-014 in cecum were decreased compared with control birds (P < 0.05). Moreover, in birds fed EA-containing diets, the levels of acetate, butyrate, and total short-chain fatty acids in the cecum were higher (P < 0.05) than those in control birds. These findings indicated that dietary EA had ameliorative effects on antioxidant capability, digestive enzyme activity, immune function, and intestinal functions, which led to strengthened growth performance. Broilers are susceptible to physiological stress under the environment of faster growth that may cause growth retardation, and this problem has inspired the research in alternative managements and dietary strategies to control the incidence and severity. Due to the consumer preference for natural products, the application of polyphenol compound has been increasing in appeal. Our study was conducted to determine if ellagic acid (EA, a natural four-ring polyphenol compound) added in the diet of broilers during the 1st day to 56th day may contribute to supporting growth performance, immune response, antioxidant activity, digestive enzyme activities, and intestinal functions in yellow-feathered broilers. Broilers were given a corn-soybean meal basal diet supplemented with 0, 100, 200, or 400 mg/kg EA. Our results indicated that supplementation with 200 or 400 mg/kg EA could improve anti-oxidant status, immune response, and digestive enzyme activities, which ultimately enhance growth performance. The beneficial effects for hosts associated with EA were not only due to the protective effects on the overall health and the digestion and absorption capacity, but also due to the enhanced gut health by suppressing the pathogenic bacteria via stimulating the secretion of intestinal short chain fatty acid and maintaining the integrity of intestinal barrier by decreasing intestinal permeability, which finally led to the improved health status of yellow-feathered broilers. This study demonstrated that EA has a certain protective effect on yellow-feathered broilers.

On the basis of detrended fluctuation analysis (DFA), we propose a new bivariate linear regression model. This new model provides estimators of multi-scale regression coefficients to measure the dependence between variables and corresponding variables of interest with multi-scales. Numerical tests are performed to illustrate that the proposed DFA-bsaed regression estimators are capable of accurately depicting the dependence between the variables of interest and can be used to identify different dependence at different time scales. We apply this model to analyze the PM2.5 series of three adjacent cities (Beijing, Tianjin, and Baoding) in Northern China. The estimated regression coefficients confirmed the dependence of PM2.5 among the three cities and illustrated that each city has different influence on the others at different seasons and at different time scales. Two statistics based on the scale-dependent t-statistic and the partial detrended cross-correlation coefficient are used to demonstrate the significance of the dependence. Three new scale-dependent evaluation indices show that the new DFA-based bivariate regression model can provide rich information on studied variables.