Performance tests of the LCA- ECS heat exchanger duct with simulation of primary heat exchanger pressure drop

Total pressure drop in the inlet and outlet ducting of the LCA-ECS primary heat exchanger were determined corresponding to flight Mach numbers upto 0.86. A suitable screen/wire mesh was selected whose pressure loss characteristics matched with those of the primary heat exchanger being procured for use with LCA. The flow through the duct at low inlet Mach numbers was augmented using a suitable ejector. The inlet duct pressure loss was found to be nearly 60% higher than that due to the heat exchanger alone. The ram air and ejector air temperatures were simulated as per flight conditions and their effects were studied

An algorithmic approach to understand trace elemental homeostasis in serum samples of Parkinson disease

A classical problem in neurological disorders is to understand the progression of disorder and define the trace elements (metals) which play a role in deviating a sample from normal to an abnormal state, which implies the need to create a reference knowledge base (KB) employing the control samples drawn from normal/healthy set in the context of the said neurological disorder, and in sequel to analytically understand the deviations in the cases of disorders/abnormalities/unhealthy samples. Hence building up a computational model involves mining the healthy control samples to create a suitable reference KB and designing an algorithm for estimating the deviation in case of unhealthy samples. This leads to realizing an algorithmic cognition–recognition model, where the cognition stage establishes a reference model of a normal/healthy class and the recognition stage involves discriminating whether a given test sample belongs to a normal class or not. Further if the sample belongs to a specified reference base (normal) then the requirement is to understand how strong the affiliation is, and if otherwise (abnormal) how far away the sample is from the said reference base. In this paper, an exploratory data analysis based model is proposed to carry out such estimation analysis by designing distribution and parametric models for the reference base. Further, the knowledge of the reference base in case of the distribution model is expressed in terms of zones with each zone carrying a weightage factor. Different distance measures are utilized for the subsequent affiliation analysis (City block with distribution model and Doyle's with Parametric model). Results of an experimental study based on the database of trace elemental analysis in human serum samples from control and Parkinson's neurological disorder are presented to corroborate the performance of the computational algorithm

Relationship between consanguinity and depression in a south Indian population

A Pilot study was Carried out to study the association of consanguinity marriage with depression. It was observed that the consanguinity of marriage was associated with depression. The odds ratio was 5.66 (CI: 2.42-13.54). The age and sex had an association with depression. The age and sex adjusted odds ratio of consanguinity marriage was 7.66 (CI: 3.93-19.45) indicating that it is independently associated with depression