Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Biocatalytic Alkylation Cascades: Recent Advances and Future Opportunities for Late-Stage Functionalization

This Concept article describes the latest developments in the emerging area of late-stage biocatalytic alkylation. Central to these developments is the ability to efficiently prepare S-adenosyl methionine (SAM) cofactor analogues and couple this with enzymatic alkyl transfer. Recent developments in the enzymatic synthesis of SAM cofactor analogues are summarized first, followed by their application as alkyl transfer agents catalyzed by methyltransferases (MTases). Second, innovative methods to regenerate SAM cofactors by enzymatic cascades is reported. Finally, future opportunities towards establishing a generalized platform for late-stage alkylation are described.     

Nonhydrolyzable Heptose Bis- and Monophosphate Analogues Modulate Pro-inflammatory TIFA-NF-κB Signaling

d -Glycero-d -manno-heptose-1β,7-bisphosphate (HBP) and d -glycero-d -manno-heptose-1β-phosphate (H1P) are bacterial metabolites that were recently shown to stimulate inflammatory responses in host cells through the activation of the TIFA-dependent NF-κB pathway. To better understand structure-based activity in relation to this process, a family of nonhydrolyzable phosphonate analogues of HBP and H1P was synthesized. The inflammation modulation by which these molecules induce the TIFA-NF-κB signal axis was evaluated in vivo at a low-nanomolar concentration (6 nM) and compared to that of the natural metabolites. Our data showed that three phosphonate analogues had similar stimulatory activity to HBP, whereas two phosphonates antagonized HBP-induced TIFA-NF-κB signaling. These results open new horizons for the design of pro-inflammatory and innate immune modulators that could be used as vaccine adjuvant.     

Quantitative UPLC‐MS/MS analysis of chlorogenic acid derivatives in antioxidant fractionates from dandelion (Taraxacum officinale) root

While qualitative studies have identified chlorogenic acids in antioxidant extracts, particularly ethyl acetate‐derived extracts, of Taraxacum officinale, quantitative analysis of these phenolic compounds remains largely unreported for this species. In this study, bioactivity‐guided fractionation of an antioxidant crude ethyl acetate extract (DPPH = 295.481 ± 0.955 mg TE g^?1 extract) from T. officinale root resulted in a number of reverse‐phase fractions that demonstrated high antioxidant activity (DPPH = 1058.733–1312.136 mg TE g^?1 extract), stronger than that of the synthetic antioxidant Trolox^®. UPLC‐MS/MS screening of these fractions for the presence of selected mono‐ and di‐caffeoylquinic acids revealed large quantities of 1,5‐dicaffeoylquinic acid present in several fractions (853.052–907.324 μg mg^?1), respectively. Due to the antioxidant potency and high levels of 1,5‐dicaffeoylquinic acid observed in these fractions, it was concluded that specifically this chlorogenic acid derivative is a major contributor to the antioxidant efficacy of dandelion root.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

A Stimulation Method to Assess the Contractile Status of the Lumbar Extensors in a Seated Posture

The purpose of present study was to develop and evaluate methods to assess stimulation responses of the lumbar extensors, as part of a longer‐term goal of detecting fatigue during prolonged sitting. Three stimulation frequencies (2, 5, and 8 Hz) were tested in separate stages, which include 3 stimulation trains and 4 sampling blocks. Repeated measures analyses of variance were used to determine whether any significant differences in mean stimulation responses occurred with respect to stimulation frequency, sampling block, and stimulation train. Reliability of measured stimulation responses was assessed within and between sampling blocks using intraclass correlation coefficients. Stimulation frequencies significantly affected the stimulation responses and time‐to‐potentiation differed between the 3 stimulation frequencies; it was highest for 2 Hz stimulation. All 3 stimulation frequencies resulted in excellent reliability within and between sampling blocks. Use of the current protocol at 2 Hz is recommended as appropriate to measure the lumbar extensors status during prolonged sitting.