Supplier selection with an integrated methodology in unknown environment

This paper proposes an integrated methodology and its solution for supplier selection problem. A two-stage stochastic programming model and fuzzy TOPSIS methods are consolidated in this methodology. After pre-research phase, in the second part of the methodology, fuzzy TOPSIS is used for ranking potential suppliers considering qualitative data under fuzzy environment. In the third part of the methodology a group of ranked potential suppliers are included in a two-stage stochastic programming model for evaluation. In the two-stage stochastic programming model demand is assumed as uncertain and different scenarios are generated for this parameter. With this methodology, supplier evaluation procedure can be done in unknown environment. Our methodology is interested with a problem in multi-product, multi-period and multi-sourcing environment.     

Capacity allocation problem in flexible manufacturing systems: branch and bound based approaches

This study considers an operation assignment and capacity allocation problem that arises in flexible manufacturing systems. The machines have limited time and tool magazine capacities and the available tools are limited. Our objective is to maximise total weight of assigned operations. We develop a branch and bound algorithm that finds the optimal solutions and a beam search algorithm that finds high quality solutions in polynomial time.     

Sulfurized Co-Mo Alloy Thin Films as Efficient Electrocatalysts for Hydrogen Evolution Reaction

Catalysis Letters - Here, we successfully fabricated sulfurized Co-Mo alloy thin film electrodes with different compositions and studied their catalytic properties for hydrogen evolution reaction...     

Modeling Alcohol Dehydrogenase Catalysis in Deep Eutectic Solvent/Water Mixtures

The use of oxidoreductases (EC1) in non-conventional reaction media has been increasingly explored. In particular, deep eutectic solvents (DESs) have emerged as a novel class of solvents. Herein, an in-depth study of bioreduction with an alcohol dehydrogenase (ADH) in the DES glyceline is presented. The activity and stability of ADH in mixtures of glyceline/water with varying water contents were measured. Furthermore, the thermodynamic water activity and viscosity of mixtures of glyceline/water have been determined. For a better understanding of the observations, molecular dynamics simulations were performed to quantify the molecular flexibility, hydration layer, and intraprotein hydrogen bonds of ADH. The behavior of the enzyme in DESs follows the classic dependence of water activity (a_W) in non-conventional media. At low a_W values (<0.2), ADH does not show any activity; at higher a_W values, the activity was still lower than that in pure water due to the high viscosities of the DES. These findings could be further explained by increased enzyme flexibility with increasing water content.     

The Correlation Between Statistically Downscaled Precipitation Data and Groundwater Level Records in North-Western Turkey

Downscaling of atmospheric climate parameters is a sophisticated tool to develop statistical relationships between large-scale atmospheric variables and local-scale meteorological variables. In this study, the variables selected from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data set were used as predictors for the downscaling of monthly precipitation in a watershed located in north-western Turkey where station records terminated two decades ago. An Artificial Neural Network (ANN) based approach was used to downscale global climate predictors that are positively correlated to the existing time frame of precipitation data in the basin. The downscaled precipitation information were used to extend the non-existing data from the meteorological station, which were later correlated with groundwater level data obtained from automatic pressure transducers that continuously record depth to groundwater. The results of the study showed that, among a large set of NCEP/NCAR parameters, surface precipitation data recorded at the meteorological station was strongly correlated with precipitation rate, air temperature and relative humidity at surface and air temperature at 850, 500, and 200 hPa pressure levels, and geopotential heights at 850 and 200 hPa pressure levels. The gaps in station data were then filled with the correlations obtained from NCEP/NCAR parameters and a complete precipitation data set was obtained that extended to current time line. This extended precipitation time series was later correlated with the existing groundwater level data from an alluvial plain in order to develop a general relationship that can be used in basin-wide water budget estimations. The proposed methodology is believed to serve the needs of engineers and basin planners who try to create a link between related hydrological variables under data-limited conditions.     

A spectral Integral method (SIM) for layered media

A spectral integral method is presented for electromagnetic scattering from dielectric and perfectly electric conducting (PEC) objects with a closed boundary embedded in a layered medium. Two-dimensional layered medium Green's functions are computed adaptively by using Gaussian quadratures. The singular terms in the Green's functions and the non-smooth terms in their derivatives are handled appropriately to achieve exponential convergence. Numerical results, compared with the ones obtained by using other methods, demonstrate the spectral accuracy and high efficiency of the proposed method. They also confirm that the spectral integral method (SIM) is applicable to concave objects.     

Mechanochemical processing and microstructural characterization of pure Fe2B nanocrystals

The results of current investigation demonstrate that mechanochemical processing can be used to synthesize high purity Fe₂B nanocrystals by selecting well-optimized milling conditions, reaction paths and proper starting materials. Microstructure, phase analyses, specific surface area, and magnetic properties of the synthesized nanocrystals were examined by using X-ray diffraction/spectroscopy, electron microscopy, nitrogen adsorption–desorption methods following Brunauer-Emmett-Teller equation and vibrating sample magnetometer techniques, respectively. Removal of MgO impurity phase by leaching the resulting powder in the acetic acid solution yielded single phase Fe₂B nanocrystals with the crystallite size and specific surface area of 12.5 nm and 29 m²/g, respectively. Magnetization results clearly indicated the ferromagnetic behavior of Fe₂B nanocrystals with saturation magnetization observed around 96.26 emu·g^?1. Electron microscope images revealed coaxial/spherical powder shape and morphology of the single-phase Fe₂B nanocrystals.