Galactic R Coronae Borealis Stars: The C-2 Swan Bands, The Carbon Problem, And The C-12/C-13 Ratio

Observed spectra of R Coronae Borealis (RCB) and hydrogen-deficient carbon (HdC) stars are analyzed by synthesizing the C-2 Swan bands (1, 0), (0, 0), and (0, 1) using our detailed line list and the Uppsala model atmospheres. The (0, 1) and (0, 0) C-2 bands are used to derive the C-12 abundance, and the (1, 0) (CC)-C-12-C-13 band to determine the C-12/C-13 ratios. The carbon abundance derived from the C-2 Swan bands is about the same for the adopted models constructed with different carbon abundances over the range 8.5 (C/He = 0.1%) to 10.5 (C/He = 10%). Carbon abundances derived from C I lines are about a factor of four lower than the carbon abundance of the adopted model atmosphere over the same C/He interval, as reported by Asplund et al., who dubbed the mismatch between adopted and derived C abundance as the "carbon problem." In principle, the carbon abundances obtained from C-2 Swan bands and that assumed for the model atmosphere can be equated for a particular choice of C/He that varies from star to star. Then, the carbon problem for C-2 bands is eliminated. However, such C/He ratios are in general less than those of the extreme helium stars, the seemingly natural relatives to the RCB and HdC stars. A more likely solution to the C-2 carbon problem may lie in a modification of the model atmosphere's temperature structure. The derived carbon abundances and the C-12/C-13 ratios are discussed in light of the double degenerate and the final flash scenarios.Robert A. Welch Foundation of Houston, TX F-634McDonald Observator

Predicting Software Reliability Using Ant Colony Optimization Technique with Travelling Salesman Problem for Software Process – A Literature Survey

Computer software has become an essential and important foundation in several versatile domains including medicine, engineering, etc. Consequently, with such widespread application of software, there is a need of ensuring software reliability and quality. In order to measure such software reliability and quality, one must wait until the software is implemented, tested and put for usage for a certain time period. Several software metrics have been proposed in the literature to avoid this lengthy and costly process, and they proved to be a good means of estimating software reliability. For this purpose, software reliability prediction models are built. Software reliability is one of the important software quality features. Software reliability is defined as the probability with which the software will operate without any failure for a specific period of time in a specified environment. Software reliability, when estimated in early phases of software development life cycle, saves lot of money and time as it prevents spending huge amount of money on fixing of defects in the software after it has been deployed to the client. Software reliability prediction is very challenging in starting phases of life cycle model. Software reliability estimation has thus become an important research area as every organization aims to produce reliable software, with good quality and error or defect free software. There are many software reliability growth models that are used to assess or predict the reliability of the software. These models help in developing robust and fault tolerant systems. In the past few years many software reliability models have been proposed for assessing reliability of software but developing accurate reliability prediction models is difficult due to the recurrent or frequent changes in data in the domain of software engineering. As a result, the software reliability prediction models built on one dataset show a significant decrease in their accuracy when they are used with new data. The main aim of this paper is to introduce a new approach that optimizes the accuracy of software reliability predictive models when used with raw data. Ant Colony Optimization Technique (ACOT) is proposed to predict software reliability based on data collected from literature. An ant colony system by combining with Travelling Sales Problem (TSP) algorithm has been used, which has been changed by implementing different algorithms and extra functionality, in an attempt to achieve better software reliability results with new data for software process. The intellectual behavior of the ant colony framework by means of a colony of cooperating artificial ants are resulting in very promising results. Keywords: Software Reliability, Reliability predictive Models, Bio-inspired Computing, Ant Colony Optimization technique, Ant Colon

One step procedure for screening and diagnosis of gestational diabetes mellitus by diabetes in pregnancy study group of India

Background: In the Indian context, screening for Diabetes is essential in all pregnant women, as the Indian women have an eleven-fold increased risk of developing glucose intolerance during pregnancy. For this, we need a simple procedure which is economical and feasible. Hence this study was undertaken as a screening as it is acceptable, economical and feasible to perform. Aim of this study was to assess the feasibility of one step procedure for screening and diagnosis of Gestational Diabetes Mellitus by Diabetes in Pregnancy Study Group of India (DIPSI).aim of the study was to study the occurrence of Gestational Diabetes mellitus, Tumkur, to assess the sensitivity and specificity of glucose challenge test, to assess the need for universal screening and to study the maternal and perinatal outcomes in patient with Gestational Diabetes Mellitus.Method: Type of study was prospective study. this study included 200 pregnant women attending the antenatal OPD in Sri Siddhartha Medical College, Tumkur. Data collection was in a predesigned proforma. Pregnant women with 24-28 weeks of gestation were given 75 grams of oral glucose load, irrespective of their meal and venous blood sample drawn after 2 hours. If blood glucose value was ≥140mg/dl, the screening was considered as DIPSI positive. These patients underwent OGTT.Results: Incidence of GDM was found to be 3.5% in the patients studied. 40% of cases did not have risk factors, hencethere is a need for universal screening. DIPSI was positive in 10 cases, of which 7 were OGTT positive. Patients were managed with diet and insulin. The maternal and perinatal outcome of pregnancy was good.Conclusion: For universal screening, DIPSI performed irrespective of last meal timing with 75g glucose load is a patient friendly approach. This method recommended by WHO serves both as a one-step screening and diagnostic procedure & is easy to perform besides being economical