Chemometric analysis of groundwater quality data of alluvial aquifer of Gangetic plain, North India

Water quality data set from the alluvial region in the Gangetic plain in northern India, which is known for high fluoride levels in soil and groundwater, has been analysed by chemometric techniques, such as principal component analysis (PCA), discriminant analysis (DA) and partial least squares (PLS) in order to investigate the compositional differences between surface and groundwater samples, spatial variations in groundwater composition and influence of natural and anthropogenic factors. Trilinear plots of major ions showed that the groundwater in this region is mainly of Na/K-bicarbonate type. PCA performed on complete data matrix yielded six significant PCs explaining 65% of the data variance. Although, PCA rendered considerable data reduction, it could not clearly group and distinguish the sample types (dug well, hand-pump and surface water). However, a visible differentiation between the water samples pertaining to two watersheds (Khar and Loni) was obtained. DA identified six discriminating variables between surface and groundwater and also between different types of samples (dug well, hand pump and surface water). Distinct grouping of the surface and groundwater samples was achieved using the PLS technique. It further showed that the groundwater samples are dominated by variables having origin both in natural and anthropogenic sources in the region, whereas, variables of industrial origin dominate the surface water samples. It also suggested that the groundwater sources are contaminated with various industrial contaminants in the region.     

Elliptic Reconstruction and a Posteriori Error Estimates for Fully Discrete Semilinear Parabolic Optimal Control Problems

This article studies a posteriori error analysis of fully discrete finite element approximations for semilinear parabolic optimal control problems. Based on elliptic reconstruction approach introduced earlier by Makridakis and Nochetto [25], a residual based a posteriori error estimators for the state, co-state and control variables are derived. The space discretization of the state and co-state variables is done by using the piecewise linear and continuous finite elements, whereas the piecewise constant functions are employed for the control variable. The temporal discretization is based on the backward Euler method. We derive a posteriori error estimates for the state, co-state and control variables in the $L^\infty(0,T;L^2(\Omega))$-norm. Finally, a numerical experiment is performed to illustrate the performance of the derived estimators.     

Mössbauer and PAC studies of nanocrystalline Fe

High-purity Fe powder was mechanically milled under argon at ambient temperature using an SPEX 8000 mill. The local atomic and magnetic structure was studied using⁵⁷Co/Fe Mössbauer and¹¹¹In/Cd perturbed angular correlations (PAC) spectroscopies. After 32 hours of milling, X-ray diffraction revealed effective grain diameters of 18 nm and energy-dispersive X-ray analysis indicated a Cr impurity concentration of 5%, presumably introduced by mechanical attrition of steel ball bearings used for milling. In addition to a spectral component very similar to bulk iron metal, the Mössbauer spectra exhibited hyperfine field shifts attributed to the Cr impurities. PAC spectra on Fe milled for 5 h, with no contamination, exhibited two components: (1) A slightly broadened magnetic interaction attributed to interior, defect-free sites of In/Cd probes with a mean hyperfine field slightly greater than in macroscopic grains. The defect-free site fraction grew appreciably during milling, even though In is essentially insoluble in Fe. (2) An indistinct signal due to mixed magnetic and quadrupole interactions attributed to probes at surface or other defect sites.     

Evaluating the information content of a measure of plant output: An application to high-technology manufacturing

Commonly used measures of plant output have been criticized for their inability to provide information required to manage the dynamic operations of high-technology manufacturing plants. In this paper, we propose tests to evaluate the information content of a measure of plant output that is specifically directed at these issues. These tests are based on recent developments in DATA Envelopment Analysis (DEA), namely the Cone Ratio Envelopments. In this new application of DEA models, we shift the focus from Decision Making Units (DMUs) being evaluated to the DMUs that are being used to effect evaluations. The proposed tests are applied to evaluate the information contnet of a complexity adjusted measure of plant output, which we refer to as Total Net Die Equivalent (TNDE). Developed recently in the context of a high-technology manufacturing plant—a wafer fabrication plant of a merchant semiconductor manufacturing company-TNDE reflects the ongoing changes in product and process technologies, process flow characteristics, and volume of production. Evaluating the information content on joint criteria of recency and efficiency, the results of our tests, conducted over a 28-month period in the wafer fabrication plant,show that TNDE as a single aggregate (scalar) measure of plant output outperforms the two outputs from which it is synthesized. Thus, TNDE as a single measure of output can be used to provide an improved basis for planning a plant's future operations. En route to the development and application of the proposed tests, we illustrate how DEA concepts and models provide a rigorous and systematic basis for conducting ex post technology evaluation to guide continuous improvements in a plant's current operations.     

X–H rotational-echo double-resonance NMR for torsion angle determination of peptides

C–H and N–H rotational-echo double-resonance (REDOR) NMR is developed for determining torsion angles in peptides. The distance between an X spin such as ¹³C or ¹⁵N and a proton is measured by evolving the proton magnetization under REDOR-recoupled X–H dipolar interaction. The proton of interest is selected through its directly bonded heteronuclear spin Y. The sidechain torsion angle χ₁ is extracted from a ¹³Cβ-detected Hβ–N distance, while the backbone torsion angle φ is extracted from an ¹⁵N-detected H^N–C^′ distance. The approach is demonstrated on three model peptides with known crystal structures to illustrate its utility.