In vitro evaluation of potential complexation between bovine insulin and bovine serum albumin

The objective of this study was to examine the possible binding of bovine insulin (BI) with bovine serum albumin (BSA) to form a new potential diabetogenic irreversible complex protein. Several preparations of BSA and BI were prepared. Both capillary electrophoresis and spectrophotometric analysis were undertaken to test the possibility of complexation between BI and BSA. HPLC was used to test whether the potential complex of BI and BSA is reversible or irreversible. The optimum deviation between the real and calculated absorbances was observed at a BI/BSA ratio of 2. Moreover, the migration time of BI decreased substantially with increasing ratio of BI to BSA until it became almost constant at equal molar ratio of BI/BSA. While the majority of the 2:1 BI–BSA sample detached during the HPLC analysis, which confirms the reversible character of BI–BSA binding, the HPLC chromatogram also emphasizes the formation of an irreversible complexation between the two proteins. This study provides evidence of the formation of reversible and irreversible new BI–BSA complexes under physiological conditions. This highlights the importance of examining the possible diabetogenicity of BI–BSA complex in genetically susceptible people. Copyright © 2013 John Wiley & Sons, Ltd.     

Reconstruction of physics objects at the Circular Electron Positron Collider with Arbor

After the Higgs discovery, precise measurements of the Higgs properties and the electroweak observables become vital for the experimental particle physics. A powerful Higgs/Z factory, the Circular Electron Positron Collider (CEPC) is proposed. The Particle Flow oriented detector design is proposed to the CEPC and a Particle Flow algorithm, Arbor is optimized accordingly. We summarize the physics object reconstruction performance of the Particle Flow oriented detector design with Arbor algorithm and conclude that this combination fulfills the physics requirement of CEPC.     

Silver nanoclusters doped in zeolite to decontaminate water resources from the quinalphos pesticide

Ag (I) nanoclusters doped in mordenite zeolite were prepared and spectroscopically analyzed. Strong luminescence emission that is dependent on the excitation wavelength was observed. These variations in the emission modes are due to the site selective luminescence where various luminophores might be excited upon selecting the proper excitation wavelength. The selected material was found to have strong affinity to remove the quinalphos pesticide, which is widely used for the protection of several vegetable and fruit crops, from water bodies. HPLC and GC–MS techniques were used to follow the kinetic data and to identify the photodecomposition products, respectively. The photodecomposition of quinalphos in the presence of the silver doped mordenite catalyst gives different products compared to the irradiation of quinalphos without catalyst. The presence of the Ag-mordenite catalyst not only adsorbs the quinalphos from the solution but it also reduces its toxic effect as tested on the fruit fly (Drosophila melanogaster).     

Supply chain optimization of petroleum organization under uncertainty in market demands and prices

A multi-period stochastic planning model has been developed and implemented for a supply chain network of a petroleum organization operating in an oil producing country under uncertain market conditions. The proposed supply chain network consists of all activities related to crude oil production, processing and distribution. Uncertainties were introduced in market demands and prices. A deterministic optimization model was first developed and tested. The impact of uncertainty on the supply chain was studied by performing a sensitivity analysis in which ±20% deviations were introduced in market demands and prices of different commodities. A stochastic formulation was then proposed, which is based on the two-stage problem with finite number of realizations. The proposed stochastic programming approach proved to be quite effective in developing resilient production plans in light of high degree of uncertainty in market conditions. The anticipated production plans have a considerably lower expected value of perfect information (EVPI). The main conclusion of this study is that for an oil producing country with oil processing capabilities, the impact of economic uncertainties may be tolerated by an appropriate balance between crude exports and processing capacities.     

NEURO FUZZY MODEL FOR PREDICTING THE DYNAMIC CHARACTERISTICS OF BEAMS

An adaptive neuro-fuzzy inference system （ANFIS） is introduced to predict the dynamic behavior of beams. The effects of axial forces and large displacements are considered in the analysis. A database of tests for the dynamic characteristics of beams is developed from the experimental tests. The responses of nonlinear vibration force for the single and multiple-stepped beams are calculated from the finite element method （FEM）, experimental tests and neuro-fuzzy model for comparison. The neuro-fuzzy model provides a general framework for the combination of neural networks and fuzzy logic. It is more flexible with more options of incorporating the fuzzy nature of the real-world system and is an useful estimation tool for the dynamic characteristics of beams. Therefore, ANFIS can be a useful tool for dynamic behaviour analysis of multiple-stepped beams subjected to axial loads and large displacement.     

Integrating Hydrogeochemical and Geophysical Data for Testing a Finite Volume Based Numerical Model for Saltwater Intrusion

In this paper, hydrogeological and geophysical data are used to validate a numerical model developed to predict seawater intrusion into coastal aquifers. The cell-centered finite volume method is adopted here to solve the set of coupled partial differential equations describing the motion of saltwater and freshwater separated by a sharp interface. These equations are based on the Dupuit approximation and are obtained from integration of 3D flow equations for fresh and salt water zones over the vertical dimension. In order to have flexibility upon complex configurations domain, non structured grid meshing is utilized. To approximate the diffusion fluxes, Green-Gauss type reconstruction, based on diamond-cell and least squares interpolation, is performed. The model is first validated using academic test case studies with known closed form solutions. The mathematical model has been calibrated using hydrogeochemical and geophysical data. The geophysical method applied in this study has been a frequency domain electromagnetic method. In this method the apparent electrical conductivity is measured by induction using two separate hand-held transmitter and receiver coils. During the operation the transmitter coil is energized by a low frequency alternating current that radiates an electromagnetic field and the receiver coil detects the resulting field. Taking into account the relationship between the bulk conductivity of the subsoil and the conductivity of groundwater, EM soundings have been interpreted to provide complementary information to hydrogeochemical data to outline the fresh–saltwater interface. This methodology has been applied to the case of saltwater intrusion into the Llobregat delta aquifer, near Barcelona, Spain.     

A sequential injection spectrophotometric method for the determination of penicillamine in pharmaceutical products by complexation with iron(III) in acidic media

A simple, robust and sensitive sequential injection spectrophotometric method for the assay of penicillamine (PA) in pharmaceutical formulations is developed. The method was based on the complex formation when PA is reacted with iron(III) solution in hydrochloric acid media. The deep blue colored PA-iron(III) complex produced is monitored at a maximum wavelength of 600 nm. A five level orthogonal array design coupled to genetic algorithm was employed to obtain the optimum experimental conditions for the determination of PA using peak absorbance as the measure of the system's performance criterion. A linear dynamic range for the determination of PA of 25-300 ppm was obtained with a sampling frequency of 50 h⁻¹ and a relative standard deviation of less than 0.98%. The method was successfully applied to the determination of PA in pharmaceutical formulations.     

2D silver nanocrystal ordering modulated by various substrates and revealed using oxygen plasma treatment

Here, 5 nm Ag nanocrystals are deposited, using the same procedure, on various substrates differing by their rms roughness, wetting properties and nanoparticle-substrate interactions leading, consequently, to different nanocrystal orderings. Theoretical calculations are carried out to understand how these parameters influence the size of the nanocrystal organizations on the substrate surface. When these nanocrystal arrays are subjected to an oxygen plasma treatment, the nanocrystals perfectly assembled in hexagonal networks remain intact, while the nanocrystals that are not well-packed coalesce to form larger particles independently on the used substrate. This phenomenon is observed on the entire substrate surface. This procedure gives an innovative way of using oxygen plasma generated by the reactive ion etching technique, as a new method to reveal defects in 2D Ag nanocrystal self-assemblies.     

Microwave-accelerated competing domino processes: a tether-controlled dual pathway into high molecular complexity

Bicyclic unsaturated diols undergo a path selective modular domino transformation upon subjection to Pb(OAc)4, the reaction being biased to the nature of the angular substituent. The magnitude of the linking chain and the nature of the angular substituent determine the reaction course. Methylene ether linkage acts as an autoremovable directing group (ring-retained domino product 5), whereas a propylene linkage switches the path toward the ring-expanded type 21 domino product. Reaction times were substantially reduced using microwave irradiation.