Gravid uterus in post caesarean incisional hernia: a rare occurrence

Incisional hernia following section caesarean is a not so uncommon a complication following sepsis in the postoperative period. An ever rising primary caesarean rates in many developed countries like USA and emerging economies like China is leading to rising trend of incisional hernia following c-section. The contents of hernial sac in these cases are usually small gut loops or omentum. Only about a dozen cases having gravid uterus as hernial content have been recorded in literature. Paucity of cases has meant that there are no established guidelines for its management, which is totally individualized. We report here a very rare case of protrusion of gravid uterus in post caesarean incisional ventral hernia and its successful management resulting in delivery of a healthy baby

Hybrid subtractive clustering technique for estimation of ground water table

70-76Groundwater scarcity and groundwater table decline at alarming rate create many problems for managers and planners. This problem will be worsening in future as demand for water would rise tremendously due to steady rise in human population. Optimal-exploitation of groundwater ‘in all the areas that are getting fast depleted’ is required to estimate the groundwater table. Keeping this in view, different models have been developed for an Indian catchment located in North – East region of India. Groundwater studies have not been conducted much by researchers for the problematic area of Budaun district where the water table is continuously declining at a faster rate. The present study is taken up to study the groundwater availability in the district. Models have been developed for prediction of water table behaviour and a proper groundwater recharge plan for the problematic areas can be suggested. Over the last decade, soft computing techniques like Fuzzy logic and Artificial Neural Networks (ANN) are increasingly used in hydrological studies. Furthermore, their computational speed in simulating and forecasting is very welcomed in real time operations. It is robust and flexible in managing real world complex systems involving uncertainty and imprecise data. Fuzzy Logic Controller (FLC) provides a means of converting a linguistic control strategy based on operators’ knowledge into an automatic control strategy. An important feature of fuzzy set theory is the symmetry between the objective function and constraints. During this study, a Neuro-Fuzzy approach such as ANFIS (Adaptive Neuro Fuzzy Inference System) subtractive cluster method (SCM) and ANN techniques have been used for monsoon (M) and non-monsoon (NM) periods in order to estimate the ground water tables. Input data of the network are composed by past measurements of nearby inflow and rainfall, and the quantity of water which has been pumped out from ground during that specific period. Input data are fuzzified with different degrees of membership. The models are developed and applied for Budaun district in Uttar Pradesh to get the optimum output during monsoon and non-monsoon period. Models developed by SCM technique give better results than ANN technique

Empirical analysis of change metrics for software fault prediction

A quality assurance activity, known as software fault prediction, can reduce development costs and improve software quality. The objective of this study is to investigate change metrics in conjunction with code metrics to improve the performance of fault prediction models. Experimental studies are performed on different versions of Eclipse projects and change metrics are extracted from the GIT repositories. In addition to the existing change metrics, several new change metrics are defined and collected from the Eclipse project repository. Machine learning algorithms are applied in conjunction with the change and source code metrics to build fault prediction models. The classification model with new change metrics performs better than the models using existing change metrics. In this work, the experimental results demonstrate that change metrics have a positive impact on the performance of fault prediction models, and high-performance models can be built with several change metrics

Evaluation of the safety, immunogenicity and efficacy of a new live-attenuated lumpy skin disease vaccine in India

ABSTRACTLumpy skin disease (LSD) was reported for the first time in India in 2019 and since then, it has become endemic. Since a homologous (LSD-virus based) vaccine was not available in the country, goatpox virus (GPV)-based heterologous vaccine was authorized for mass immunization to induce protection against LSD in cattle. This study describes the evaluation of safety, immunogenicity and efficacy of a new live-attenuated LSD vaccine developed by using an Indian field strain, isolated in 2019 from cattle. The virus was attenuated by continuous passage (P = 50) in Vero cells. The vaccine (50th LSDV passage in Vero cells, named as Lumpi-ProVacInd) did not induce any local or systemic reaction upon its experimental inoculation in calves (n = 10). At day 30 post-vaccination (pv), the vaccinated animals were shown to develop antibody- and cell-mediated immune responses and exhibited complete protection upon virulent LSDV challenge. A minimum Neethling response (0.018% animals; 5 out of 26,940 animals) of the vaccine was observed in the field trials conducted in 26,940 animals. There was no significant reduction in the milk yield in lactating animals (n = 10108), besides there was no abortion or any other reproductive disorder in the pregnant animals (n = 2889). Sero-conversion was observed in 85.18% animals in the field by day 30 pv