MICROORGANISMS VARIANTS FOR HEALTHCARE-ASSOCIATED INFECTIONS IN A SELECTED TERTIARY CARE HOSPITAL

Objective: Microorganisms are minute and can be only in microscope and these are not visible to naked eyes. Various types of microbe include bacteria, virus, fungi, and protozoa. These microorganisms are subclassified and these are disease causing leading to mortality and morbidity. Healthcare-associated infections (HAIs) arise from different variants of microbes and knowing the category of microbes for treating the diseases with specific antibiotics is important for better patient outcome. Methods: Using secondary data, all the patients who had HAI for 3 years were taken into consideration by considering the different variants of microorganisms. Results: Retrospective data collected for the period of 3 years the inpatients who got admitted for more than 48 h of duration, the data collected included the parameters for various microorganisms such as Bacilli, cocci, Klebsiella, Acinetobacter, and Aures, other micro-organisms such as Escherichia coli, Citrobacter, and Pseudomonas microorganisms. Bacilli group of microorganisms was more common for urinary tract infection, blood stream infection, and ventilator-associated pneumonia. Aures was more common among surgical site infection infections. Conclusions: Most of the patients who had an HAI had two or more different kind of microorganisms which are responsible for spreading infection. There is a need to control microbial flora in the hospital set up as the rate of HAI increases with microbial flora

Modeling charge transport in Swept Charge Devices for X-ray spectroscopy

We present the formulation of an analytical model which simulates charge transport in Swept Charge Devices (SCDs) to understand the nature of the spectral redistribution function (SRF). We attempt to construct the energy-dependent and position dependent SRF by modeling the photon interaction, charge cloud generation and various loss mechanisms viz., recombination, partial charge collection and split events. The model will help in optimizing event selection, maximize event recovery and improve spectral modeling for Chandrayaan-2 (slated for launch in 2014). A proto-type physical model is developed and the algorithm along with its results are discussed in this paper.Comment: 9 pages, 7 figures, Proc. SPIE 8453, High Energy, Optical, and Infrared Detectors for Astronomy

The Chandrayaan-2 Large Area Soft X-ray Spectrometer (CLASS)

The CLASS experiment on Chandrayaan-2, the second Indian lunar mission, aims tomap the abundance of the major rock forming elements on the lunar surface using the technique of X-ray fluorescence during solar flare events. CLASS is a continuation of the successful C1XS [1] XRF experiment on Chandrayaan-1. CLASS is designed to provide lunar mapping of elemental abundances with a nominal spatial resolution of 25 km (FWHM) from a 200 km polar, circular orbit of Chandrayaan-2

Real-time Thermal Error Compensation Module for Intelligent Ultra Precision Turning Machine (iUPTM)

AbstractAccuracy & precision are 1he main requirements for ultra precision machine tools. Many factors affect 1he performance of 1he system 1hat in turns affect 1he product quality. Among all sources of errors, the thermo mechanical deformation errors are the main contributor for 1he overall geometrical errors. This paper mainly aims at establislunent of methodology to compensate thermal deformation errors in real-time for ultra precision machine tools. The real-time thermal error compensation module has been developed and integrated to intelligent Ultra Precision Turning machine. The module includes temperatures as inputs, neural network algorithm for computing the thermal deformations errors, ‘C’ programming for real-time calculations and integration with open architecture CNC controller. The module runs in silent mode which avoids human intervention for correction of thermal deformation errors

Diversity of lactic acid bacteria of the bioethanol process

<p>Abstract</p> <p>Background</p> <p>Bacteria may compete with yeast for nutrients during bioethanol production process, potentially causing economic losses. This is the first study aiming at the quantification and identification of Lactic Acid Bacteria (LAB) present in the bioethanol industrial processes in different distilleries of Brazil.</p> <p>Results</p> <p>A total of 489 LAB isolates were obtained from four distilleries in 2007 and 2008. The abundance of LAB in the fermentation tanks varied between 6.0 × 10⁵and 8.9 × 10⁸CFUs/mL. Crude sugar cane juice contained 7.4 × 10⁷to 6.0 × 10⁸LAB CFUs. Most of the LAB isolates belonged to the genus <it>Lactobacillus </it>according to rRNA operon enzyme restriction profiles. A variety of <it>Lactobacillus </it>species occurred throughout the bioethanol process, but the most frequently found species towards the end of the harvest season were <it>L. fermentum </it>and <it>L. vini</it>. The different rep-PCR patterns indicate the co-occurrence of distinct populations of the species <it>L. fermentum </it>and <it>L. vini</it>, suggesting a great intraspecific diversity. Representative isolates of both species had the ability to grow in medium containing up to 10% ethanol, suggesting selection of ethanol tolerant bacteria throughout the process.</p> <p>Conclusions</p> <p>This study served as a first survey of the LAB diversity in the bioethanol process in Brazil. The abundance and diversity of LAB suggest that they have a significant impact in the bioethanol process.</p