Diluted chemical bath deposition of CdZnS as prospective buffer layer in CIGS solar cell

In this study, dilute chemical bath deposition technique has been used to deposit CdZnS thin films on soda-lime glass substrates. The structural, morphological, optoelectronic properties of as-grown films have been investigated as a function of different Zn²⁺ precursor concentrations. The X-ray diffractogram of CdS thin-film reveals a peak corresponding to (002) plane with wurtzite structure, and the peak shift has been observed with the increase of the Zn²⁺ concentration upon formation of CdZnS thin film. From morphological studies, it has been revealed that the diluted chemical bath deposition technique provides homogeneous distribution of film on the substrate even at a lower concentration of Zn²⁺. Optical characterization has shown that the transparency of the film is influenced by Zn²⁺ concentration and when the Zn²⁺ concentration is varied from 0 M to 0.0256 M, bandgap values of resulting films range from 2.42 eV to 3.90 eV while. Furthermore, electrical properties have shown that with increasing zinc concentration the resistivity of the film increases. Finally, numerical simulation validates and suggests that CdZnS buffer layer with composition of 0.0032 M Zn²⁺ concentration would be a promising candidate in CIGS solar cell.     

Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...     

Purification and characterization of a fatty acid binding protein from human prostatic tissue

Epidemiological studies suggest the existence of a strong relationship between the incidence of prostatic cancer and the intake of dietary lipids in humans. However, very little information is available on intracellular fatty acid metabolism in human prostatic tissue. The objective of this study was to identify and subsequently characterize a fatty acid binding protein of human prostatic tissue. A fatty acid binding protein (FABP) was purified and characterized from human prostatic tissue. The purified FABP had an apparent molecular mass of 15.0±1.0 kDa as averaged from three different methods, sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE), gel filtration and amino acid analysis. The pI value of the protein was determined to be 6.8. Scatchard analysis of fatty acid binding to the purified FABP from malignant prostatic tissue showed a Kd value of 0.53±0.02 μM for arachidonic acid (n=5). The Kd values of FABP purified from benign prostatic tissue were 0.57±0.02 μM for oleic acid and 0.51±0.04 μM for arachidonic acid (n=5). Fatty acid analysis revealed that the level of endogenously bound arachidonic acid was about 2.5-fold higher in FABP from malignant than from benign tissue. In addition, both malignant and benign tissues contained the same concentration of FABP. The concentrations of FABP in malignant and benign tissues were 19.2±1.8 and 21.4±2.1 μg per mg of total cytosolic protein, respectively. Characterization based on amino acid composition, isoelectric point and fluorescence with dansyl undecanoic acid suggests that the FABP may not be of the heart type, but is rather more closely related to the liver type. As malignant prostatic tissue produces more PGE₂ compared to benign tissue, our data suggest that FABP may help enhancing the synthesis of the prostaglandin in malignant tissue by facilitating arachidonic acid transport. A preliminary account of this work was presented at the Biochemical Society Meeting, London, December 16–18, 1991, and published as an abstract (Ref. 1).     

Double organic modification by 3‐chloropropyl and methyl groups on pure silica MCM‐41 and Ti‐MCM‐41: efficient catalyst for epoxidation of cyclododecene

Simultaneous surface modification by 3‐chloropropyl and methyl groups on the same Si atoms resulted in hydrophobic and highly ordered mesoporous silica with a very high surface area. ¹³C and ²⁹Si MAS NMR spectra indicate homogeneous grafting of chloropropyl and methyl groups in the silica matrix and this organically modified Ti‐MCM‐41 shows outstanding catalytic performance in the epoxidation of cyclododecene using tert‐butyl hydroperoxide as oxidant. This revised version was published online in July 2006 with corrections to the Cover Date.     

Estimation of gross calorific value of coals using artificial neural networks

The gross calorific value (GCV) is an important property defining the energy content and thereby efficiency of fuels, such as coals. There exist a number of correlations for estimating the GCV of a coal sample based upon its proximate and/or ultimate analyses. These correlations are mainly linear in character although there are indications that the relationship between the GCV and a few constituents of the proximate and ultimate analyses could be nonlinear. Accordingly, in this paper a total of seven nonlinear models have been developed using the artificial neural networks (ANN) methodology for the estimation of GCV with a special focus on Indian coals. The comprehensive ANN model developed here uses all the major constituents of the proximate and ultimate analyses as inputs while the remaining six sub-models use different combinations of the constituents of the stated analyses. It has been found that the GCV prediction accuracy of all the models is excellent with the comprehensive model being the most accurate GCV predictor. Also, the performance of the ANN models has been found to be consistently better than that of their linear counterparts. Additionally, a sensitivity analysis of the comprehensive ANN model has been performed to identify the important model inputs, which significantly affect the GCV. The ANN-based modeling approach illustrated in this paper is sufficiently general and thus can be gainfully extended for estimating the GCV of a wide spectrum of solid, liquid and gaseous fuels.     

Sulphur dioxide loadings over megacity Lahore (Pakistan) and adjoining region of Indo-Gangetic Basin

This article presents spatial and temporal variations of planetary boundary layer (PBL) sulphur dioxide (SO₂) over megacity Lahore and adjoining region, a typical representative area in the Indo-Gangetic Basin (IGB) largely influenced by transported volcanic SO₂ from Africa, Middle East, and southern Europe, by using data retrieved from satellite-based Ozone Monitoring Instrument (OMI) during October 2004–September 2015. We find a positive trend of 2.4% per year (slope 0.01 ± 0.005 with y-intercept 0.35 ± 0.03 Dobson Unit (DU), correlation coefficient r = 0.55 and 2-tailed p-value at 0.1) of OMI-SO₂ column with the average value of 0.4 ± 0.05 DU. Strong seasonality of OMI-SO₂ column is observed over the region linked with local meteorology, patterns of anthropogenic emissions, crop residue burning, and vegetation cover. There exists a seasonal high value in winter 0.56 ± 0.24 DU with a peak in December 0.67 ± 0.26 DU. The seasonal lowest value is observed to be 0.29 ± 0.11 DU in wet summer with minimum value in July 0.25 ± 0.06 DU. High growth rates of OMI-SO₂ column over the study region have been observed in January, June, October, and December ranging from 5.7% to 11.6% per year. Satellite data show elevated OMI-SO₂ columns in 2007, 2008, 2011, and 2012 largely contributed by trans-boundary volcanic SO₂. A detailed analysis of volcanic SO₂ transported from Africa and Middle East (Jabal Al-Tair, Dalaffilla, and Nabro volcanoes) over the study area is presented. Air mass trajectories suggest the presence of long-range transported volcanic SO₂ at high altitude levels over Lahore and IGB region during the volcanic episodes. The SO₂ enhancements in PBL during winter season are generally due to significant vertical downdraft of high-altitude volcanic SO₂. For the first time, we present significant influence of volcanic SO₂ from southern Europe (Mt. Etna volcano) reaching over the study area. Daily mean OMI-SO₂ levels up to 21.4, 10.0, 5.6, and 2.4 DU have been noticed due to the eruptions from Dalaffilla, Mt. Etna, Nabro, and Jabal Al-Tair volcanoes, respectively.     

Target coverage in camera networks for manufacturing workplaces

In this paper, we investigate the camera network placement problem for target coverage in manufacturing workplaces. The problem is formulated to find the minimum number of cameras of different types and their best configurations to maximise the coverage of the monitored workplace such that the given set of target points of interest are each k-covered with a predefined minimum spatial resolution. Since the problem is NP-complete, and even NP-hard to approximate, a novel method based on Simulated Annealing is presented to solve the optimisation problem. A new neighbourhood generation function is proposed to handle the discrete nature of the problem. The visual coverage is modelled using realistic and coherent assumptions of camera intrinsic and extrinsic parameters making it suitable for many real world camera based applications. Task-specific quality of coverage measure is proposed to assist selecting the best among the set of camera network placements with equal coverage. A 3D CAD of the monitored space is used to examine physical occlusions of target points. The results show the accuracy, efficiency and scalability of the presented solution method; which can be applied effectively in the design of practical camera networks.