Accelerated Neural Network Training through Dimensionality Reduction for High-Throughput Screening of Topological Materials

Machine Learning facilitates building a large variety of models, starting from elementary linear regression models to very complex neural networks. Neural networks are currently limited by the size of data provided and the huge computational cost of training a model. This is especially problematic when dealing with a large set of features without much prior knowledge of how good or bad each individual feature is. We try tackling the problem using dimensionality reduction algorithms to construct more meaningful features. We also compare the accuracy and training times of raw data and data transformed after dimensionality reduction to deduce a sufficient number of dimensions without sacrificing accuracy. The indicated estimation is done using a lighter decision tree-based algorithm, AdaBoost, as it trains faster than neural networks. We have chosen the data from an online database of topological materials, Materiae. Our final goal is to construct a model to predict the topological properties of new materials from elementary properties

Bilateral sacroiliitis: a rare cause for a common presentation

Fever and osteoarticular involvement of axial skeleton are hallmark clinical manifestations of brucellosis but other diseases like ankylosing spondylitis, tuberculosis, Paget’s disease of bone, sarcoidosis should also be considered as differential diagnosis. Brucellosis is an uncommon infectious disease in India. Signs and symptoms of the disease are highly variable, with musculoskeletal complaints occurring frequently. Authors hereby reported a case of brucellosis presenting with fever, polyathralgia, bilateral sacroiliitis and enthesitis. Knowledge of geographical distribution, evidence of exposure to the cattle and a high degree of clinical suspicion of brucellosis are very important for early differentiation from other diseases to prevent lethal complications and institute early treatment and a prompt recovery

Design and development of an additive manufactured force transducer

This paper discusses the design and development of an additive manufactured force transducer for force measurement applications. The force transducer is of square ring shape and dimensions have been evaluated in accordance to available literature. Fused filament fabrication technique has been adopted for fabrication of the force transducer and strain gauges have been applied at defined location in form of a Wheatstone bride. Efforts regarding metrological characterization are underway and successful demonstration of the force transducer will define a new development in the direction of force transducers

Design and development of an additive manufactured force transducer

897-900This paper discusses the design and development of an additive manufactured force transducer for force measurement applications. The force transducer is of square ring shape and dimensions have been evaluated in accordance to available literature. Fused filament fabrication technique has been adopted for fabrication of the force transducer and strain gauges have been applied at defined location in form of a Wheatstone bride. Efforts regarding metrological characterization are underway and successful demonstration of the force transducer will define a new development in the direction of force transducers

Prevalence of gestational diabetes mellitus and its relationship with various risk factors in a tertiary care hospital in West Bengal with special reference to tribal population, India

Background: Gestational diabetes mellitus (GDM) is the most common medical complication and metabolic disorder of pregnancy. The aim and objective of this study was to determine the prevalence of GDM and its relationship with various risk factors with special reference to tribal population.Methods: The study was done in 200 patients between 24 and 28 weeks of gestation, attending antenatal outdoor in a tertiary care hospital of West Bengal.  These patients were given 75gm oral glucose irrespective of the last meal and their plasma glucose was estimated at 2hours. Patients with plasma glucose values ≥140 mg/dl were labelled as GDM. Patients who were diabetic before pregnancy or whose pre pregnancy body mass index was not known or was in labour or had chronic disease, were not included in the study.Results: Prevalence of GDM was 11% in whole population while it was 14.63% and 10.06% in tribal and non-tribal population respectively.  Prevalence of GDM and its correlation with most of risk factors in previous pregnancies was found to be significant in both non-tribal and tribal population. Family history of diabetes mellitus was the most prevalent risk factor in both non-tribal (9.4%) and tribal population (14.63%). There was no single most common risk factor among GDM patients found as there were multiple risk factors present with same frequency in both tribal and non-tribal population.Conclusions: The prevalence of GDM is 14.63% in the tribal population and 10.06% in non-tribal population which is not statically significant (P<0.407). The relation between the prevalence of GDM and risk factors was found to be significant for most of the risk factors