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Woodwardia japonica is a kind of great potential edible and medicinal fern. In a previous study, it was found that flavonoid and antioxidant activity of W. japonica from different sites were different. However, the cause of the differences has still been unclear, which has restricted the utilization of W. japonica. In this paper, flavonoid and antioxidant activity of W. japonica from nine different regions were determined with the method of a colorimetric assay with UV-VIS spectrophotometry and HPLC-ESI-TOF-MS, and the effects of climate factors on flavonoids and antioxidant activities were evaluated by mathematical modeling and statistical methods. The results showed: (1) total flavonoid content (TFC) of W. japonica from Wuyi Mountain (Jiangxi) was the highest, which might be related to the low temperature; (2) the differences of antioxidant activities of W. japonica might be related to precipitation; (3) five flavonols, two flavones and one isoflavone were tentatively identified in W. japonica; (4) flavonol and isoflavone might be affected by sunshine duration, and flavones were probably related to temperature. In conclusion, the effects of climate factors on flavonoids and antioxidants are significant, which would provide an important basis for further exploring the mechanism of climate affecting secondary metabolites. [ABSTRACT FROM AUTHOR]

A direct application of autoregressive (AR) models with independent and identically distributed (iid) errors is sometimes inadequate to fit the time series data well. A natural alternative is further to assume the model errors following an AR process, whose structure however has essential impacts on the statistical inferences related to the autoregressive models. In this paper, we construct a new unified test for checking the AR error structure based on the empirical likelihood method. The proposed test is desirable because its limit distribution is always chi-squared regardless of whether the autoregressive model is stationary or non-stationary, with or without an intercept term. Some simulations are also provided to illustrate the finite sample performance of this test. Finally, we apply the proposed test to a financial real data set. [ABSTRACT FROM AUTHOR]

Testing predictability is known to be an important issue for the balanced predictive regression model. Some unified testing statistics of desirable properties have been proposed, though their validity depends on a predefined assumption regarding whether or not an intercept term nevertheless exists. In fact, most financial data have endogenous or heteroscedasticity structure, and the existing intercept term test does not perform well in these cases. In this paper, we consider the testing for the intercept of the balanced predictive regression model. An empirical likelihood based testing statistic is developed, and its limit distribution is also derived under some mild conditions. We also provide some simulations and a real application to illustrate its merits in terms of both size and power properties. [ABSTRACT FROM AUTHOR]

Autoregressive exogenous, hereafter ARX, models are widely adopted in time series-related domains as they can be regarded as the combination of an autoregressive process and a predictive regression. Within a more complex structure, extant diagnostic checking methods face difficulties in remaining validity in many conditions existing in real applications, such as heteroscedasticity and error correlations exhibited between the ARX model itself and its exogenous processes. For these reasons, we propose a new serial correlation test method based on the profile empirical likelihood. Simulation results, as well as two real data examples, show that our method has a good performance in all mentioned conditions. [ABSTRACT FROM AUTHOR]

Dryopteris crassirhizoma Nakai is a Chinese traditional medicinal fern plant for heat-clearing and detoxifying, promoting blood circulation and dissipating blood stasis. Previous researches showed that many factors could influence the components of medicinal plants, and the plant part is one of the main factors. So far, only the underground part of D. crassirhizoma, called "Mianma Guanzhong", has been widely sold in the market. However, the above-ground part was usually at low utilization, resulting in a waste of medicinal resources. In order to further develop and utilize the medicinal resources of D. crassirhizoma, the constituents, total flavonoid contents and antioxidant activity of the above-ground and underground parts of D. crassirhizoma were tentatively analyzed and compared based on HS-SPME-GC-MS and UPLC/Q-TOF-MS. The results showed that (1) the volatile components were mainly focused in the above-ground part of D. crassirhizoma, including 3-carene, isoledene, ionene, 4-amino-1-naphthol and furfural. (2) Nonvolatile components of the underground part of D. crassirhizoma contained phenolic acid, flavonoids, phloroglucinol and less fatty acid. (3) The common compounds of the above-ground and underground parts of D. crassirhizoma were phenolic acid and flavaspidic acid AB. (4) Antioxidant activity of the underground part was stronger than that of the above-ground part of D. crassirhizoma. In conclusion, both the above-ground and underground parts of D. crassirhizoma are important medicinal resources worthy of further development. [ABSTRACT FROM AUTHOR]

The Lalin River Basin (LLRB) is a major drainage basin in northeastern China, that has been significantly influenced by agricultural activities. This study focused on exploring diatom taxonomic composition linked to environmental factors at the taxonomic levels of genus and species during ice-covered periods. Nine sampling stations were divided into three groups based on trophic state index (TSI). hierarchical cluster analysis (HCA) and redundancy analysis (RDA) were performed to identify diatom distribution patterns and their relationships to environmental factors. Diatom richness, composition and distribution were analyzed at the levels of genus and species. Our results showed the epipelagic diatom Melosira varians was very abundant at most stations. Benthic diatoms Achnanthidium minutissimum, Encyonema minutum and Gomphonema parvulum were dominant in group-3, which had the highest trophic states. HCA showed the similarity of diatom taxonomic composition spatial distribution patterns between genus and species levels. RDA revealed that the key factors related to genus level distributions are COD, TP and EC, while TP was the key factor in structuring diatom taxonomic composition at the level of species. These results suggest identification of diatoms at genus level can be used as a potential indicator to assess ecological health status of agricultural-influenced rivers during ice cover periods. Further research is necessary to explore the utility of genus level diatom composition as a biological indicator in rivers. [ABSTRACT FROM AUTHOR]

In this report, we propose a novel framework to explore the activity interactions and temporal dependencies between activities in complex video surveillance scenes. Under our framework, a low-level codebook is generated by an adaptive quantization with respect to the activeness criterion. The Hierarchical Dirichlet Processes (HDP) model is then applied to automatically cluster low-level features into atomic activities. Afterwards, the dynamic behaviors of the activities are represented as a multivariate point-process. The pair-wise relationships between activities are explicitly captured by the non-parametric Granger causality analysis, from which the activity interactions and temporal dependencies are discovered. Then, each video clip is labeled by one of the activity interactions. The results of the real-world traffic datasets show that the proposed method can achieve a high quality classification performance. Compared with traditional K-means clustering, a maximum improvement of 19.19% is achieved by using the proposed causal grouping method.