Epidemiology of Bovine Mastitis and Its Diagnosis, Prevention, and Control

Mastitis is an inflammation of mammary glands that is prevalent in dairy bovines. It causes a significant proportion of economic losses to the dairy farmers in India. Cattle and buffalo farming contribute significantly to the economy of the state. Various infectious agents such as bacteria, fungi, and algae may cause mastitis. Hence, it is essential to understand the etiological agents and predisposing factors that lead to mastitis in susceptible bovine populations in Madhya Pradesh state so that appropriate prevention and control strategies can be implemented. In this chapter, epidemiology, diagnosis, prevention, and control measures of mastitis in general and in India, the state of Madhya Pradesh, in particular, will be presented

A population-based nested case control study on recurrent pneumonias in children with severe generalized cerebral palsy: ethical considerations of the design and representativeness of the study sample

BACKGROUND: In children with severe generalized cerebral palsy, pneumonias are a major health issue. Malnutrition, dysphagia, gastro-oesophageal reflux, impaired respiratory function and constipation are hypothesized risk factors. Still, no data are available on the relative contribution of these possible risk factors in the described population. This paper describes the initiation of a study in 194 children with severe generalized cerebral palsy, on the prevalence and on the impact of these hypothesized risk factors of recurrent pneumonias. METHODS/DESIGN: A nested case-control design with 18 months follow-up was chosen. Dysphagia, respiratory function and constipation will be assessed at baseline, malnutrition and gastro-oesophageal reflux at the end of the follow-up. The study population consists of a representative population sample of children with severe generalized cerebral palsy. Inclusion was done through care-centres in a predefined geographical area and not through hospitals. All measurements will be done on-site which sets high demands on all measurements. If these demands were not met in "gold standard" methods, other methods were chosen. Although the inclusion period was prolonged, the desired sample size of 300 children was not met. With a consent rate of 33%, nearly 10% of all eligible children in The Netherlands are included (n = 194). The study population is subtly different from the non-participants with regard to severity of dysphagia and prevalence rates of pneumonias and gastro-oesophageal reflux. DISCUSSION: Ethical issues complicated the study design. Assessment of malnutrition and gastro-oesophageal reflux at baseline was considered unethical, since these conditions can be easily treated. Therefore, we postponed these diagnostics until the end of the follow-up. In order to include a representative sample, all eligible children in a predefined geographical area had to be contacted. To increase the consent rate, on-site measurements are of first choice, but timely inclusion is jeopardized. The initiation of this first study among children with severe neurological impairment led to specific, unexpected problems. Despite small differences between participants and non-participating children, our sample is as representative as can be expected from any population-based study and will provide important, new information to bring us further towards effective interventions to prevent pneumonias in this population

Analysis of diabetes mellitus for early prediction using optimal features selection

Abstract Diabetes is a chronic disease or group of metabolic disease where a person suffers from an extended level of blood glucose in the body, which is either the insulin production is inadequate, or because the body’s cells do not respond properly to insulin. The constant hyperglycemia of diabetes is related to long-haul harm, brokenness, and failure of various organs, particularly the eyes, kidneys, nerves, heart, and veins. The objective of this research is to make use of significant features, design a prediction algorithm using Machine learning and find the optimal classifier to give the closest result comparing to clinical outcomes. The proposed method aims to focus on selecting the attributes that ail in early detection of Diabetes Miletus using Predictive analysis. The result shows the decision tree algorithm and the Random forest has the highest specificity of 98.20% and 98.00%, respectively holds best for the analysis of diabetic data. Naïve Bayesian outcome states the best accuracy of 82.30%. The research also generalizes the selection of optimal features from dataset to improve the classification accuracy

Bacteriological evaluation of packaged bottled water sold at Jaipur city and its public health significance

Aim: The study was carried out to investigate the microbiological quality of packaged drinking water marketed in Jaipur city. Material and Methods: In the present study 'twenty' drinking water samples (15 water bottles and 5 sachets) of different brands purchased randomly, were evaluated to access the water quality on the basis of different bacteriological parameters. Result: Out of twenty, 50% samples were found unsatisfactory in standard plate count. Psychrophillic, coliforms, E. coli and staphylococcal counts revealed that 25%, 45%, 20%, and 5% samples respectively were found unfit for human consumption as per Bureau of Indian Standards (BIS) of drinking water. On the basis of results of overall microbiological assessment 55% of samples proved to be unfit for consumption. All brands of water sachet (100%) had high coliforms count which indicates faecal contamination. Amongst those sachets two brands (40%) had presence of E. coli and all the sachet water brands fell below drinking water standards while out of fifteen brands of bottled water 6 samples contained higher microbiological value hence unfit for human consumption. Conclusion: Local brands of packaged drinking water were found unfit for human condumption. So it is suggested that government should intensify the efforts in the monitoring of activities in this rapidly expanding industry with a view to supply potable and wholesome water to the public. [Vet World 2013; 6(1.000): 27-30

State of the Art of Ex-Situ Aluminium Matrix Composite Fabrication through Friction Stir Processing

Aluminium metal matrix composites (AMMCs) are the fastest developing materials for structural applications. Friction Stir Processing (FSP) has evolved as a promising surface composite fabrication technique mainly because it is an eco-friendly and solid-state process. A spurt in the interest of research community and a resulting huge research output makes it difficult to find relevant information to further the research with objectivity. To facilitate this, the present article addresses the current state of the art and development in surface metal matrix fabrication through FSP with a specific focus on ex-situ routes. The available literature has been carefully read and categorized to present effects of particle size, morphology and elemental composition. The effect of various reinforcements on development of different functional characteristics is also discussed. Effect of main FSP parameters on various responses is presented with objectivity. Based on the studied literature concluding summary is presented in a manner in which the literature becomes useful to the researchers working on this important technology