带有二元连接函数的半参数模型

提出了一种新的带有二元连接函数的广义半参数模型,即二元连接模型(简称为BLM).使用轮廓似然方法估计模型的参数和非参数部分,并给出了计算算法.证明了所得的未知参数的估计量为n~(1/2)-相合,渐近正态且具有渐近最小方差,给出了实际数据分析和模拟研究,最终采用局部功效方法来检验非参数部分的线性性.     

A new test on the conditional capital asset pricing model

Testing the validity of the conditional capital asset pricing model(CAPM) is a puzzle in the finance literatureLewellen and Nagel[14]find that the variation in betas and in the equity premium would have to be implausibly large to explain important asset-pricing anomaliesUnfortunately, they do not provide a rigorous test statisticBased on a simulation study, the method proposed in Lewellen and Nagel[14]tends to reject the null too frequently.We develop a new test procedure and derive its limiting distribution under the null hypothesis.Also, we provide a Bootstrap approach to the testing procedure to gain a good finite sample performanceBoth simulations and empirical studies show that our test is necessary for making correct inferences with the conditional CAPM.     

Flow Through Diffusion Cell Method: A Better Approach to Study Drug Release Behavior as Compared to Traditional Dissolution Test Method

Co‐polymeric hydrogels consisting of N‐vinyl‐2‐pyrrolidone (NVP) and acrylic acid (AAc) were synthesized and evaluated for release of a model drug, i.e., vitamin B₁₂. Release studies in simulated gastric fluid (pH 1.2) and intestinal fluid (pH 7.4), at 37°C, showed the hydrogels to be pH sensitive. An in vitro release study by ‘traditional dissolution test’ (TDT) showed that percent drug released from the hydrogel was nearly 8.6±2.1 and 83.2±4.8 in the media of pH 1.2 and 6.8, respectively. However, in order to incorporate in vivo GI conditions such as acidic pH and high water content in the stomach, low water content and the presence of a semi–solid mass in the large intestine, a new test model, called flow through diffusion cell (FTDC) was also used. The two approaches yielded almost different release profiles. The gels were characterized by thermogravimetric analysis and FTIR spectroscopy.     

A Tensile Strain Hardening Test Indicator of Environmental Stress Cracking Resistance

Environmental stress cracking resistance (ESCR) is an important indicator of performance for high density polyethylene (HDPE) in structural and polymer pipe applications. The commonly used test for determining ESCR of HDPE can be time consuming and rather imprecise. A tensile strain hardening test was recently proposed to offer a faster way to characterize ESCR of polyethylene. In this paper, a practical approach is adopted whereby the test is extended to room temperature and shown to relate reliably to the ESCR of HDPE. Several HDPE resins (including pipe‐grade resins) are analyzed at strain rates of 0.5 mm/min and 7 mm/min to compare the effect of strain rate. Comparisons between the conventional ESCR test method and the strain hardening test show that strain hardening can be used to rank ESCR of HDPE in a reliable fashion. In our study the more direct measure of “hardening stiffness” is used to compare resins instead of strain hardening modulus. Because no true stress‐strain measurement is needed, this is a much simpler test method than other methods previously suggested. In addition, the use of the natural drawing ratio (NDR) as ESCR ranking indicator is examined. Results show that NDR can also be employed as a strain rate‐independent indicator of ESCR of HDPE. The test proposed herein is practical, simple and precise, and hence a more reliable indicator of ESCR performance of HDPE.     

Qsar Models for Predicting the Acute Toxicity of Selected Organic Chemicals with Diverse Structures to Aquatic Non-Vertebrates and Humans

Abstract

The linear and non-linear relationships of acute toxicity (as determined on five aquatic non-vertebrates and humans) to molecular structure have been investigated on 38 structurally-diverse chemicals. The compounds selected are the organic chemicals from the 50 priority chemicals prescribed by the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme. The models used for the evaluations are the best combination of physico-chemical properties that could be obtained so far for each organism, using the partial least squares projection to latent structures (PLS) regression method and backpropagated neural networks (BPN). Non-linear models, whether derived from PLS regression or backpropagated neural networks, appear to be better than linear models for describing the relationship between acute toxicity and molecular structure. BPN models, in turn, outperform non-linear models obtained from PLS regression. The predictive power of BPN models for the crustacean test species are better than the model for humans (based on human lethal concentration). The physico-chemical properties found to be important to predict both human acute toxicity and the toxicity to aquatic non-vertebrates are the n?octanol water partition coefficient (Pow) and heat of formation (HF). Aside from the two former properties, the contribution of parameters that reflect size and electronic properties of the molecule to the model is also high, but the type of physico-chemical properties differs from one model to another. In all of the best BPN models, some of the principal component analysis (PCA) scores of the ¹³C-NMR spectrum, with electron withdrawing/accepting capacity (LUMO, HOMO and IP) are molecular size/volume (VDW or MS1) parameters are relevant. The chemical deviating from the QSAR models include non-pesticides as well as some of the pesticides tested. The latter type of chemical fits in a number of the QSAR models. Outliers for one species may be different from those of other test organisms.     

An in silico expert system for the identification of eye irritants

This report describes development of an in silico, expert rule-based method for the classification of chemicals into irritants or non-irritants to eye, as defined by the Draize test. This method was developed to screen data-poor cosmetic ingredient chemicals for eye irritancy potential, which is based upon exclusion rules of five physicochemical properties – molecular weight (MW), hydrophobicity (log P), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA) and polarizability (Pol). These rules were developed using the ADMET Predictor software and a dataset of 917 eye irritant chemicals. The dataset was divided into 826 (90%) chemicals used for training set and 91 (10%) chemicals used for external validation set (every 10th chemical sorted by molecular weight). The sensitivity of these rules for the training and validation sets was 72.3% and 71.4%, respectively. These rules were also validated for their specificity using an external validation set of 2011 non-irritant chemicals to the eye. The specificity for this validation set was revealed as 77.3%. This method facilitates rapid screening and prioritization of data poor chemicals that are unlikely to be tested for eye irritancy in the Draize test.     

Shotgun proteomics‐based clinical testing for diagnosis and classification of amyloidosis

Shotgun proteomics technology has matured in the research laboratories and is poised to enter clinical laboratories. However, the road to this transition is sprinkled with major technical unknowns such as long‐term stability of the platform, reproducibility of the technology and clinical utility over traditional antibody‐based platforms. Further, regulatory bodies that oversee the clinical laboratory operations are unfamiliar with this new technology. As a result, diagnostic laboratories have avoided using shotgun proteomics for routine diagnostics. In this perspectives article, we describe the clinical implementation of a shotgun proteomics assay for amyloid subtyping, with a special emphasis on standardizing the platform for better quality control and earning clinical acceptance. This assay is the first shotgun proteomics assay to receive regulatory approval for patient diagnosis. The blueprint of this assay can be utilized to develop novel proteomics assays for detecting numerous other disease pathologies. Copyright © 2013 John Wiley & Sons, Ltd.     

阴离子表面活性剂聚二硫二丙烷磺酸钠的合成

利用硫化钠与硫磺反应制备二硫化钠,然后将二硫化钠与1,3-丙磺酸内酯反应,合成了一种可作为电镀添加剂的阴离子表面活性剂——聚二硫二丙烷磺酸钠(SPS)。采用核磁共振氢谱对合成产物进行结构表征,确认了产物结构及产率。通过正交试验研究了产物产率与反应物配比、反应温度、溶剂加入量等因素之间的关系,找出了最优合成条件:第一步合成二硫化钠的反应中,硫化钠/硫磺物质的量比为1∶1.3,温度55℃,加水量18 mL;第二步合成SPS的反应中,1,3-丙磺酸内酯/硫化钠物质的量比为1.7∶1,温度40℃,溶剂量75 mL,产物的最高产率可达到95.8%。