QUARTER-WISE COMPARATIVE PREVALENCE OF MASTITIS IN BUFFALOES AND CROSSBRED COWS

The present study was designed to determine the quarter-wise comparative prevalence of mastitis in buffaloes and crossbred cows. Milk samples collected from 50 dairy buffaloes and 50 crossbred cows were tested for subclinical mastitis by Surf Field Mastitis Test. In addition, all milk samples were processed for isolation and identification of pathogens. In buffaloes, overall prevalence of subclinical mastitis was 27%, clinical mastitis 4% and blind quarters 10%. In crossbred cows, subclinical mastitis was observed in 36%, clinical mastitis in 5.5% and blind quarters in 8% quarters. Prevalence was higher (32%) in hindquarters of crossbred cows than those of buffaloes (29%). Among the isolates, Staphylococcus aureus showed the highest (45%) frequency, followed by Streptococcus agalactiae (23%), E. coli (18%) and Bacillus spp. (14%) in buffaloes. In case of crossbred cows, Staphylococcus aureus , Streptococcus agalactiae , E. coli and Bacillus spp. were isolated from 48, 30, 13 and 8% milk samples respectively

Experimental assessment of multiple contact wear using airborne noise under dry and lubricated conditions

The generation of wear and airborne noise is inevitable in the mechanical contacts of the machine components. This paper addresses the effectiveness of the airborne noise data in estimating the wear on a disc under multi-contact conditions. A pin-on-disc rig was employed to study the role of noise parameters on the evolution of the wear area. When a pin slides on the disc, the airborne noise is generated and subsequently a sound signal is obtained. These signals, for various sets of experiments, were recorded using a digital microphone. A Matlab code was developed and employed to estimate the noise parameters from the recorded sound. Noise parameters including values of voltage RMS, noise counts and amplitudes of dominant frequencies were used to analyse the variation in the disc wear at different time intervals. These parameters were found to be effective in the determination of the wear damage evaluation under different loads without lubrication

Incidence and medical management of bisphosphonate-associated atypical femoral fractures in a major trauma centre: a retrospective observational study

BACKGROUND: Atypical femoral fractures (AFFs) are rare events associated with increased duration of bisphosphonate exposure. Recommended management of AFFs include cessation of bisphosphonates and imaging of the contralateral femur. The aims of this study were to identify the local incidence of AFFs in bisphosphonate users and to audit the medical management of AFFs against published recommendations. METHODS: A retrospective analysis of the admissions database for a major trauma centre identified all femoral fractures (3150) in a five-year period (July 2009 to June 2014). Electronic health records and radiographs were reviewed using the 2013 American Society for Bone and Mineral Research (ASBMR) diagnostic criteria for AFF to establish the number of cases. To estimate incidence, the total number of bisphosphonate users was derived from primary care prescription and secondary care day-case records. Medical management of cases with AFF on bisphosphonates was audited against guidance from ASBMR and Medicines & Healthcare Products Regulatory Agency. RESULTS: 10 out of 3150 femoral fractures met criteria for AFF; 7 of these patients had a history of exposure to bisphosphonates (6 oral, 1 intravenous). There were 19.1 AFFs per 100,000 years of bisphosphonate use in our region. Bisphosphonates were stopped and the contralateral femur imaged in only 2 of the 7 patients treated with bisphosphonates. CONCLUSION: Our local incidence is in line with published figures; however, this is the first published evidence suggesting that medical management and identification of AFF may be suboptimal. Managing these patients remains challenging due to their rarity and possible lack of awareness

Preserving Privacy of High-Dimensional Data by l-Diverse Constrained Slicing

In the modern world of digitalization, data growth, aggregation and sharing have escalated drastically. Users share huge amounts of data due to the widespread adoption of Internet-of-things (IoT) and cloud-based smart devices. Such data could have confidential attributes about various individuals. Therefore, privacy preservation has become an important concern. Many privacy-preserving data publication models have been proposed to ensure data sharing without privacy disclosures. However, publishing high-dimensional data with sufficient privacy is still a challenging task and very little focus has been given to propound optimal privacy solutions for high-dimensional data. In this paper, we propose a novel privacy-preserving model to anonymize high-dimensional data (prone to various privacy attacks including probabilistic, skewness, and gender-specific). Our proposed model is a combination of l-diversity along with constrained slicing and vertical division. The proposed model can protect the above-stated attacks with minimal information loss. The extensive experiments on real-world datasets advocate the outperformance of our proposed model among its counterparts

Adverse Events among HIV/MDR-TB Co-Infected Patients Receiving Antiretroviral and Second Line Anti-TB Treatment in Mumbai, India.

Significant adverse events (AE) have been reported in patients receiving medications for multidrug- and extensively-drug-resistant tuberculosis (MDR-TB & XDR-TB). However, there is little prospective data on AE in MDR- or XDR-TB/HIV co-infected patients on antituberculosis and antiretroviral therapy (ART) in programmatic settings