A Miniaturized Preconcentration Method Based on Dispersive Liquid–Liquid Microextraction for the Spectrophotometric Determination of Aziridine in Food Simulants

In this work a simple, rapid and sensitive method using dispersive liquid–liquid microextraction (DLLME) combined with UV–Vis spectrophotometry has been developed for the preconcentration and determination of trace amounts of aziridine in food simulants. The method is based on derivatization of aziridine with Folin's reagent (1,2-naphthoquione-4-sulphonic acid) and extraction of color product using DLLME technique. Some important parameters, such as reaction conditions, and type and volume of extraction solvent and disperser solvent were studied and optimized. Under optimum conditions, a linear calibration curve in the range of 2.0–350 ng mL^?1 of aziridine was obtained. Detection limit based on 3S_b was 1.0 ng mL^?1, and the relative standard deviation for 50 ng mL^?1 of aziridine was 2.49c (n?=?7). The proposed method was applied for the determination of aziridine in food simulants.     

Topological aspects of meshless methods and nodal ordering for meshless discretizations

The meshless element‐free Galerkin method (EFGM) is considered and compared to the finite‐element method (FEM). In particular, topological aspects of meshless methods as the nodal connectivity and invertibility of matrices are studied and compared to those of the FE method. We define four associated graphs for meshless discretizations of EFGM and investigate their connectivity. The ways that the associated graphs for coupled FE‐EFG models might be defined are recommended. The associated graphs are used for nodal ordering of meshless models in order to reduce the bandwidth, profile, maximum frontwidth, and root‐mean‐square wavefront of the corresponding matrices. Finally, the associated graphs are numerically compared. Copyright © 2001 John Wiley & Sons, Ltd.     

Oxidative Stress-Related Signaling Pathways Predict Oocytes’ Fertilization In Vitro and Embryo Quality

Oocyte development and fertilization are largely influenced by the microenvironment of the follicular fluid (FF), and the exploration of its molecular/metabolic composition may help in improving in vitro fertilization (IVF) outcomes. Here, the concentrations of molecules related to oxidative stress/inflammation were measured in FF from follicles at oocyte retrieval during IVF. Here, the FF antioxidant potential was correlated with the number of retrieved/mature oocytes and the number of fertilized ones. FF collected from the follicles of normal fertilized oocytes presented an elevated antioxidant capability, lower levels of pro-inflammatory molecules (i.e., IL-6, IL-8, IL-12, TGF-β, and HIF-1α), and a higher IL-10 concentration. FF samples from follicles at oocyte retrieval that resulted in top-quality embryos displayed a peculiar antioxidant capability and a further decrease in proinflammatory molecules when compared with FF, giving rise to poor-quality embryos. Finally, pro-inflammatory molecules were lower and accompanied by a high antioxidant capability in samples giving rise to successful embryo implantation. The antioxidant capability and IL-10 displayed a good predictive ability for fertilization and embryo quality. Overall, our data showed the great influence of oxidative stress on the oocytes’ fertilization, and shed light on the importance of controlling the inflammatory and oxidative status of FF to obtain good-quality embryos with significant implantation potential.     

Steel frame optimal design using MHBMO algorithm

Various deterministic and stochastic algorithms have been used as optimization tools in different engineering problems over the last decade. In this regard, the Modified Honey Bee Mating Optimization (MHBMO) algorithm may be considered as a typical swarm-based approach for optimizing numerous problems in engineering fields. In this paper, a design procedure based on the MHBMO technique was developed for discrete optimization of frames consisting W-shapes. The objective function in this research is to obtain the minimum weight of frames subjected to both strength and displacement requirements imposed by the American Institute for Steel Construction (AISC) and Load Resistance Factor Design (LRFD). Several frame examples from the literature were examined to verify not only the suitability of the design procedure but also the robustness of the MHBMO algorithm for frame structure design. The optimum results obtained by the MHBMO algorithm performs the best in comparison with other available techniques in the literature for all three steel frames. In conclusion, the results shows that the MHBMO algorithm is a powerful and applicable optimization method for design of frames consisting W-shapes.     

A Parametric Methodology in Tuning the Peng-Robinson (PR) Equation of State for Gas Condensate Systems

A tuned equation of state (EOS) is used in reservoir engineering for the evaluation of gas and condensate reserves, desired production methods, and facilities for field development. Publications show that the two most widely used sets of parameters from the EOS that are tuned are the binary interaction coefficient (BIC) with the critical properties and acentric factor or BIC and the constants called the omegas (Ωs). A volume shift parameter (VSP) can also be used in cubic EOS as a tuning parameter to correct for the prediction of liquid density. However, the open literature does not demonstrate if the VSP could be used with one or both parameter sets. In this study, the Peng-Robinson EOS was tuned and tested to predict constant volume depletion (CVD) data for six gas condensate samples. The two sets of tuning parameters were used with and without the VSP. Our parametric study demonstrated that the VSP should not be applied with the Ωs when tuning the Peng-Robinson EOS. With weight factors of 1 for liquid volume and 10 for gas compressibility, without the VSP, the Ωs give better prediction of CVD data than the critical properties and acentric factor even with the VSP included. This tuning technique with one regression step showed consistency in tuning the Peng-Robinson EOS with the Ωs and could be used for simulation studies of gas condensate systems.     

Novel Sensor Fabrication for the Determination of Nanomolar Concentrations of Hg2+ in Some Foods and Water Samples Based on Multi-walled Carbon Nanotubes/Ionic Liquid and a New Schiff Base

The air and water stable room temperature ionic liquid 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide, [BMP]Tf₂N, multi-walled carbon nanotubes (MWCNTs), graphite powder and also a new synthesized Schiff base have been used to fabricate a new carbon composite electrode with very attractive sensing behavior. The new Schiff base was synthesized to apply as a selective agent in electrochemical responses of the voltammetric sensor for the determination of mercury (II) ions in aqueous solutions. The proposed sensor allowed the determination of mercury (II) in the wide linear dynamic range of 0.2–260.0 nmol l^?1. The limit of detection (LOD) was noticed to be 0.05 nmol l^?1. The prepared electrode was used for mercury (II) determination in the real samples.     

Cardiovascular disease—risk benefits of clean fuel technology and policy: A statistical analysis

The hypothesis of this study is that there is a statistical relationship between the cardiovascular disease mortality rate and the intensity of fuel consumption (measured in gallons/square mile) at a particular location. We estimate cross-sectional regressions of the mortality rate due to cardiovascular disease against the intensity of fuel consumption using local data for the entire US, before the US Clean Air Act (CAA) in 1974 and after the most recent policy revisions in 2004. The cardiovascular disease rate improvement estimate suggests that up to 60 cardiovascular disease deaths per 100,000 residents are avoided in the largest urban areas with highest fuel consumption per square mile. In New York City, for instance, the mortality reduction may be worth about $30.3 billion annually. Across the US, the estimated Value of Statistical Life (VSL) benefit is $202.7 billion annually. There are likely three inseparable reasons that contributed importantly to this welfare improvement. First, the CAA regulations banned leaded gasoline, and mandated reduction in specific chemicals and smog components. Second, technologies such as the Catalytic Converter (CC) for the automobile and the low particulate diesel engine were adopted. Third, biofuels have had important roles, making the adoption of clean air technology possible and substituting for high emission fuels.