COOPER-framework: A unified process for non-parametric projects

Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the ‘COOPER-framework’ a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly.     

Real‐Time Measurement of the Size Distribution of Diesel Exhaust Particles using a Portable 4‐stage Electrical Low Pressure Impactor

For this study, a 4 stage electrical low pressure impactor was designed to measure the real‐time size distribution of diesel particulate matter (DPM). For the performance evaluation, sodium chloride (NaCl) particles and dioctyl sebacate (DOS) particles were used. After evaluating the collection efficiency of each stage of the impactor, the size distributions of test particles were estimated using electrical current data and their inversion algorithm, and this was found to agree with the results obtained by a scanning mobility particle sizer (SMPS). For measurement of DPM, a common‐rail direct injection (CRDI) diesel engine, for engine speeds of 1,200 rpm and 1,500 rpm at 2.7 kgf·m, was used. Therefore, it was found that the size distribution of the DPM could be easily obtained, with the currents measured by the impactor and the data inversion algorithm, in less than 5 seconds. Furthermore, the effective density of the DPM could be obtained using the calculated results and the SMPS data.     

A trading mechanism contingent on several indices

We introduce a trading mechanism where the execution of an order on a security can be made contingent on the relation between the clearing price of the security and the clearing price of one or several indices. A mechanism similar to ours, but limited to only one index, was implemented on the Tel Aviv Stock Exchange. We argue that it is in some cases crucial to make the execution of an order contingent on several indices. Our mechanism consists of a particular implementation of a double-sided multi-unit combinatorial auction with substitutes (or DMCS auction), which we introduced in an earlier article.     

Photovoltaic Cells Involving the Nonconjugated Conductive Polymer Iodine-Doped Styrene-Butadiene-Rubber (SBR)

Novel photovoltaic cells involving a nonconjugated conductive polymer have been fabricated using titanium dioxide/doped styrene-butadiene-rubber/carbon on ITO coated PET substrates. Photocurrents and photo-voltages for different intensities of light (emission at 300–700 nm) have been measured. These cells have shown significantly higher photocurrents and photo-voltages compared to previous reports. A photocurrent density of about 0.25 mA/cm² and a photo-voltage of 0.74 V have been measured for a light intensity of ～4 mW/cm².     

骨架结构多孔TiO2薄膜增强染料敏化太阳能电池性能

以空心球状TiO₂为基体、以片状TiO₂为骨架,采用刮刀法制备了染料敏化太阳能电池的多孔TiO₂光阳极薄膜。光电转化效率测试结果表明,当作为骨架支撑材料的片状TiO₂含量为20wt%时,光阳极薄膜组装成太阳能电池的光电转化效率达到最高值4.53%,比商业P25制备的无孔无骨架TiO₂薄膜电池(4.06%)及无骨架结构的多孔TiO₂薄膜电池(4.17%)的性能均有显著提高。当片状TiO₂的最佳含量为20wt%电池薄膜厚度为33 μm时,太阳能电池光电转化效率进一步提升为7.06%。光电性能增强的原因是骨架结构有利于快速传输电子并增大染料吸附量。本研究通过设计制备具有骨架结构的多孔TiO₂薄膜为提高染料敏化太阳能电池性能提供了新的思路。     

Comparison of sample preparation methods combined with gas chromatography with electron‐capture detection for the analysis of multipesticide residues in lotus seeds

Sample preparation is always the major bottleneck in analytical chemistry for the determination of pesticide residues. Different sample preparation methods have been proposed due to the wide variety of pesticides used and the inherent complexity of the matrices. In this study, different sample preparation methods including SPE, matrix solid‐phase dispersion, the quick, easy, cheap, efficient, rugged, and safe method, and a one‐step completion method were compared and evaluated for extracting pesticides from lotus seeds. Analysis was carried out using GC with electron‐capture detection. The results showed that good recoveries for tested pesticides were obtained by using Florisil in the four methods, and the extraction efficiency of the one‐step completion method was superior to the other three methods. The one‐step completion method was confirmed to have good linearity, reproducibility, stability, and recovery for the detection of 36 pesticides in lotus seed samples. The data collected from this study are expected to prove useful in regulating the concentration of the residues in lotus seeds, as well as in protecting human health from the hazards posed by these residues.     

SPE of 5‐lipoxygenase metabolites and the effect of head‐column field‐amplified sample stacking in MEKC

The SPE of leukotrienes and eicosatetraenoic acids using anion exchange materials was compared to the classical extraction with C₁₈ columns. A silica‐based strong anion exchanger, a polymer‐based weak anion exchanger, and a polymer‐based mixed‐mode strong anion exchanger were studied. All anion exchange materials displayed a higher recovery of the analytes with values between 70 and 90% when extracting standard solutions and analyzing by HPLC. The effect was less pronounced for the analysis of the compounds in incubations of polymorphonuclear leukocytes. Using MEKC with head‐column field‐amplified sample stacking for analyte quantification, much lower values of the peak areas were observed compared to the determination of the recovery of the analytes by HPLC. Using MEKC analysis, the highest values were found for the polymer‐based weak anion exchange material, while values below 10% were found for the polymer‐based mixed mode strong anion exchanger. This could be attributed to the presence of electrolytes in the eluates that compromised the stacking efficiency. The extent of residual electrolytes depended on the SPE protocol, resulting in large differences of the amount of analyte determined by MEKC when applying head‐column field‐amplified sample stacking for online analyte concentration.     

Automation of dimethylation after guanidination labeling chemistry and its compatibility with common buffers and surfactants for mass spectrometry-based shotgun quantitative proteome analysis

Isotope labeling liquid chromatography–mass spectrometry (LC–MS) is a major analytical platform for quantitative proteome analysis. Incorporation of isotopes used to distinguish samples plays a critical role in the success of this strategy. In this work, we optimized and automated a chemical derivatization protocol (dimethylation after guanidination, 2MEGA) to increase the labeling reproducibility and reduce human intervention. We also evaluated the reagent compatibility of this protocol to handle biological samples in different types of buffers and surfactants. A commercially available liquid handler was used for reagent dispensation to minimize analyst intervention and at least twenty protein digest samples could be prepared in a single run. Different front-end sample preparation methods for protein solubilization (SDS, urea, Rapigest™, and ProteaseMAX™) and two commercially available cell lysis buffers were evaluated for compatibility with the automated protocol. It was found that better than 94% desired labeling could be obtained in all conditions studied except urea, where the rate was reduced to about 92% due to carbamylation on the peptide amines. This work illustrates the automated 2MEGA labeling process can be used to handle a wide range of protein samples containing various reagents that are often encountered in protein sample preparation for quantitative proteome analysis.     

Temperature Effect on the Phase Behavior of the Systems Water/Sucrose Laurate/Ethoxylated‐mono‐di‐glyceride/Oil

The phase behavior of the systems water/sucrose laurate/ethoxylated mono‐di‐glyceride/oil was investigated as function of temperature and the weight ratio of EMDG in the mixed surfactants. The oils were R (+)‐limonene, isopropylmyristate, and caprylic‐capric triglyceride. This study demonstrates that the phase inversion temperature (PIT) decreases and the efficiency of the mixed surfactants (γ¯) increase as the weight ratio of the EMDG in the mixed surfactants increases. R (+)‐limonene gave lower phase inversion temperatures and higher efficiencies compared to isopropylmyristate, and caprylic‐capric triglyceride. The solubilization capacity of the system water/sucrose laurate/oil increased upon the addition of ethoxylated mono‐di‐ glyceride which stabilize the surfactant layer and increase the interfacial area.