基于油藏实际的稠油层内水热催化裂解机理研究

开展了稠油层内水热催化裂解技术在胜利油田的先导实验,五口井平均周期单井增油653 t,稠油初期降黏率达79.8%,措施14周后降黏率仍大于62%。利用Brookfield DV-Ⅲ黏度计、ElementarVario EL III元素分析仪、Knauer K-700蒸气压渗透仪、Agilent 6890N气相色谱仪和EQUINOX 55傅里叶变换红外光谱仪等,对措施前后稠油的物化性质进行分析。结果表明,层内水热催化裂解后稠油黏度及平均分子量减小、轻烃含量增加、重质组分含量减少、氢碳原子比增加、杂原子含量减小。稠油层内裂解反应受催化剂体系、高温水及储层矿物因素控制,催化剂是促进稠油裂解的主要因素,供氢剂及分散剂等助剂有助于提高裂解效果,高温水的酸碱性质及储层矿物对稠油具有催化裂解作用。多因素协同作用下使稠油发生脱侧链、分子链异构、断链、加氢、开环、成环、脱硫等系列反应,使得稠油大分子分解成小分子物质,降低了稠油黏度,改善了稠油品质,证实该技术在现场应用中具有可行性。     

每课一题教学环节的研究与实践

利用“每课一题”这个教学环节从已有知识中提取基本原理，并应用于新知识的学习；提取学生的问题编制习题，让学生暴露产生问题的根源并从根本上解决。探讨了每课一题的必要性及其基本类型。     

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.     

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.     

Simultaneous determination of 11 related impurities in propofol by gas chromatography/tandem mass spectrometry coupled with pulsed splitless injection technique

A variety of related impurities, including starting materials, process impurities, and degradation products, can be detected in propofol. In this article, a sensitive and selective GC‐MS/MS method using pulsed splitless injection technique for the determination of 11 main related impurities in propofol in one chromatogram is investigated. This method is extensively validated for its linearity, recovery, precision, LOD, and LOQ, and is able to detect trace‐level related impurities (LOD = 0.2–5.6 μg/g) in propofol bulk drug. Stressed tests proposed that oxidative degradation, photolytic degradation, and heat are the main causes for the formation of degradation products in propofol.