氧化还原介体催化强化污染物厌氧降解研究进展

 由于厌氧生物处理技术具有产生剩余污泥少、可回收能源等优点而被广泛用于处理各种有机污染物，尤其在有毒、有害、难降解污染物的去除方面取得了良好的效果。然而，厌氧生物法的处理速率通常比较低，而氧化还原介体可通过自身不断的氧化和还原来传递电子，提高电子在氧化还原反应过程中的传递速率，从而促进污染物高效厌氧降解。醌类物质和腐殖酸是应用较多的氧化还原介体，在催化难降解污染物降解方面取得了一定效果。讨论了氧化还原介体的特点、作用机制，并总结了其对偶氮染料厌氧脱色、反硝化和多氯联苯厌氧降解的强化作用，提出了氧化还原介体未来的研究方向。     

Defining G protein-coupled receptor peptide ligand expressomes and signalomes in human and mouse islets

Introduction

Islets synthesise and secrete numerous peptides, some of which are known to be important regulators of islet function and glucose homeostasis. In this study, we quantified mRNAs encoding all peptide ligands of islet G protein-coupled receptors (GPCRs) in isolated human and mouse islets and carried out in vitro islet hormone secretion studies to provide functional confirmation for the species-specific role of peptide YY (PYY) in mouse islets.

Materials and methods

GPCR peptide ligand mRNAs in human and mouse islets were quantified by quantitative real-time PCR relative to the reference genes ACTB, GAPDH, PPIA, TBP and TFRC. The pathways connecting GPCR peptide ligands with their receptors were identified by manual searches in the PubMed, IUPHAR and Ingenuity databases. Distribution of PYY protein in mouse and human islets was determined by immunohistochemistry. Insulin, glucagon and somatostatin secretion from islets was measured by radioimmunoassay.

Results

We have quantified GPCR peptide ligand mRNA expression in human and mouse islets and created specific signalomes mapping the pathways by which islet peptide ligands regulate human and mouse GPCR signalling. We also identified species-specific islet expression of several GPCR ligands. In particular, PYY mRNA levels were ~ 40,000-fold higher in mouse than human islets, suggesting a more important role of locally secreted Pyy in mouse islets. This was confirmed by IHC and functional experiments measuring insulin, glucagon and somatostatin secretion.

Discussion

The detailed human and mouse islet GPCR peptide ligand atlases will allow accurate translation of mouse islet functional studies for the identification of GPCR/peptide signalling pathways relevant for human physiology, which may lead to novel treatment modalities of diabetes and metabolic disease.

     

Methods for backcasting,nowcasting and forecasting using factor‐MIDAS: With an application to Korean GDP

We utilize mixed‐frequency factor‐MIDAS models for the purpose of carrying out backcasting, nowcasting, and forecasting experiments using real‐time data. We also introduce a new real‐time Korean GDP dataset, which is the focus of our experiments. The methodology that we utilize involves first estimating common latent factors (i.e., diffusion indices) from 190 monthly macroeconomic and financial series using various estimation strategies. These factors are then included, along with standard variables measured at multiple different frequencies, in various factor‐MIDAS prediction models. Our key empirical findings as follows. (i) When using real‐time data, factor‐MIDAS prediction models outperform various linear benchmark models. Interestingly, the “MSFE‐best” MIDAS models contain no autoregressive (AR) lag terms when backcasting and nowcasting. AR terms only begin to play a role in “true” forecasting contexts. (ii) Models that utilize only one or two factors are “MSFE‐best” at all forecasting horizons, but not at any backcasting and nowcasting horizons. In these latter contexts, much more heavily parametrized models with many factors are preferred. (iii) Real‐time data are crucial for forecasting Korean gross domestic product, and the use of “first available” versus “most recent” data “strongly” affects model selection and performance. (iv) Recursively estimated models are almost always “MSFE‐best,” and models estimated using autoregressive interpolation dominate those estimated using other interpolation methods. (v) Factors estimated using recursive principal component estimation methods have more predictive content than those estimated using a variety of other (more sophisticated) approaches. This result is particularly prevalent for our “MSFE‐best” factor‐MIDAS models, across virtually all forecast horizons, estimation schemes, and data vintages that are analyzed.     

外部治理环境与公司绩效:代理成本的中介效应

中国经济发展过程中存在区域发展不平衡现象,这种不平衡现象对公司绩效产生了重要影响。基于2003-2015年沪、深两市A股上市公司数据,以管理费用率度量上市公司管理层与股东间的第一类代理成本,以其他应收款占比度量上市公司控股股东与中小股东之间的第二类代理成本,采用多元回归和中介效应检验程序,实证检验了外部治理环境通过两类代理成本的中介作用对上市公司绩效影响的内在机理。研究结果表明,外部治理环境的提升能够显著的降低两类代理成本,进而提高上市公司的绩效,两类代理成本在外部治理环境影响公司绩效的过程中发挥显著的部分中介作用。     

单快拍相干信号自适应波束形成方法

针对低快拍条件下相干信号波束形成问题,提出一种单快拍相干自适应波束形成方法。首先,构造Duvall特征消除器滤除阵列接收信号中的期望信号,再利用空间平滑方法解相关。然后,依据Hung Tuner算法对平滑后的协方差矩阵进行Gram Schmidt正交化,快速重构干扰信号子空间。最后,将静态权矢量在干扰子空间内的正交投影作为波束形成最优权矢量。该算法可有效避免协方差矩阵求逆和特征分解造成的复杂计算,且能降低由于期望信号泄露造成的子空间估计误差,在单快拍条件下性能良好。仿真分析验证了算法的优越性和理论分析的有效性。     

Forecasting economic indicators using a consumer sentiment index: Survey‐based versus text‐based data

Given the confirmed effectiveness of the survey‐based consumer sentiment index (CSI) as a leading indicator of real economic conditions, the CSI is actively used in making policy judgments and decisions in many countries. However, although the CSI offers qualitative information for presenting current conditions and predicting a household's future economic activity, the survey‐based method has several limitations. In this context, we extracted sentiment information from online economic news articles and demonstrated that the Korean cases are a good illustration of applying a text mining technique when generating a CSI using sentiment analysis. By applying a simple sentiment analysis based on the lexicon approach, this paper confirmed that news articles can be an effective source for generating an economic indicator in Korea. Even though cross‐national comparative research results are suited better than national‐level data to generalize and verify the method used in this study, international comparisons are quite challenging to draw due to the necessary linguistic preprocessing. We hope to encourage further cross‐national comparative research to apply the approach proposed in this study.     

Robustness of alternative non‐linearity tests for SETAR models

In recent years there has been a growing interest in exploiting potential forecast gains from the non‐linear structure of self‐exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR‐type non‐linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non‐linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non‐linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR‐type non‐linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd.     

生态建筑技术的发展与应用

回顾了生态建筑发展的背景，介绍了生态建筑的评价标准，系统地阐述了应用生态建筑技术的要求与原则，介绍了各种生态建筑技术的应用。     

有色金属冶炼厂回转干燥窑分布式控制系统

对于锌湿法冶炼过程中的回转干燥窑控制问题,本文提出一种温度场控制方案,它由负压控制、温度和煤气流量串级控制以及含氧量控制来实现。基于这个控制方案,一个回转干燥窑分布式控制系统已经建立在某有色金属冶炼厂。本文介绍控制系统设计中使用的理论和技术。