7,000 research outputs found
Pediatric Rotavirus Gastroenteritis: A 2 year Analysis to Understand Current Prevalence in Mumbai
Many studies have established the high prevalence of paediatric Rotavirus gastroenteritis in India. The importance of rapid diagnosis of rotavirus infection has also been stressed upon, to initiate prompt rehydration therapy and prevent unnecessary use of antibiotics .We undertook a retrospective analysis of 327 paediatric stool specimens to understand the current prevalence and seasonal distribution of cases in Mumbai and its surrounding areas. Overall Rotavirus positivity rate was 37.9 %, with peak positivity in winter seasons. Infections were more common upto 2 years of age. Incidence of bacterial and parasitic coinfections was low
Online Learning Models for Content Popularity Prediction In Wireless Edge Caching
Caching popular contents in advance is an important technique to achieve the
low latency requirement and to reduce the backhaul costs in future wireless
communications. Considering a network with base stations distributed as a
Poisson point process (PPP), optimal content placement caching probabilities
are derived for known popularity profile, which is unknown in practice. In this
paper, online prediction (OP) and online learning (OL) methods are presented
based on popularity prediction model (PPM) and Grassmannian prediction model
(GPM), to predict the content profile for future time slots for time-varying
popularities. In OP, the problem of finding the coefficients is modeled as a
constrained non-negative least squares (NNLS) problem which is solved with a
modified NNLS algorithm. In addition, these two models are compared with
log-request prediction model (RPM), information prediction model (IPM) and
average success probability (ASP) based model. Next, in OL methods for the
time-varying case, the cumulative mean squared error (MSE) is minimized and the
MSE regret is analyzed for each of the models. Moreover, for quasi-time varying
case where the popularity changes block-wise, KWIK (know what it knows)
learning method is modified for these models to improve the prediction MSE and
ASP performance. Simulation results show that for OP, PPM and GPM provides the
best ASP among these models, concluding that minimum mean squared error based
models do not necessarily result in optimal ASP. OL based models yield
approximately similar ASP and MSE, while for quasi-time varying case, KWIK
methods provide better performance, which has been verified with MovieLens
dataset.Comment: 9 figure, 29 page
Quantum correlations and least disturbing local measurements
We examine the evaluation of the minimum information loss due to an unread
local measurement in mixed states of bipartite systems, for a general entropic
form. Such quantity provides a measure of quantum correlations, reducing for
pure states to the generalized entanglement entropy, while in the case of mixed
states it vanishes just for classically correlated states with respect to the
measured system, as the quantum discord. General stationary conditions are
provided, together with their explicit form for general two-qubit states.
Closed expressions for the minimum information loss as measured by quadratic
and cubic entropies are also derived for general states of two-qubit systems.
As application, we analyze the case of states with maximally mixed marginals,
where a general evaluation is provided, as well as X states and the mixture of
two aligned states.Comment: 10 pages, 3 figure
DEVELOPMENT AND VALIDATION OF SPECTROPHOTOMETRIC AND ION PAIR CHROMATOGRAPHIC TECHNIQUE FOR ESTIMATION OF VALSARTAN AND HYDROCHLOROTHIAZIDE
Two new simple, sensitive, rapid, accurate and reproducible methods (UV-spectrophotometric and ion pair chromatography) have been developed for simultaneous estimation of valsartan (VAL) and hydrochlrothiazide (HCTZ) from their tablet dosage form. The first method involves multiwavelength spectrophotometric method (Method 1) in which interference of HCTZ at 245nm (wavelength for estimation of VAL) was removed by recording absorbance difference at 245nm and 301 nm whereas HCTZ was estimated directly from its absorbance at 316 nm at which VAL shows no absorbance. Linearity of the response was demonstrated by VAL in the concentration range of 5-45 g/ml with a square correlation coefficient (r2) of 0.9998. Linearity of the response was demonstrated by HCTZ in the concentration range of 2-18 g/ml with a square correlation coefficient (r2) of 0.9994. The second method utilizes ion pair chromatography (Method 2) on a HIQ sil ODS column (250 mm* 4.6 mm i.d.) using methanol: 0.0025 M orthophosphoric acid: (70:30 by volume) having pH 4.6: 0.1% hexane sulphonic acid as mobile phase with UV detection at 259nm over concentration range for VAL is 240-0 μg/ml, and for HCTZ is 75-0μg/ml. Losartan potassium was used as the internal standard. The suggested procedures were checked using laboratory prepared mixtures and were applied successfully for the analysis of their tablet dosage form. The results of analysis were statistically analysed. Both the methods were validated as per ICH Q2B guideline
Classification of Handwritten Digits using Machine Learning Techniques
ThenbspMNIST datasetnbsp(MixednbspNational Institute of Standards and Technologynbspdatabase) is a largenbspdatabasenbspof handwritten digits that is commonly used fornbsptrainingnbspvariousnbspimage processingnbspsystems. [1][2] The database is also widely used for training and testing in the field ofnbspmachine learning. The MNIST database contains 60,000 training images and 10,000 testing images. [3]
In this paper, we aim to apply classification techniques to predict labels for records in the MNIST dataset using machine learning. In total, there are 10 labels ranging from 0-9. Classification will be done using Random Forest Classification Algorithm. We also aim to implement Principle Component Analysis to reduce the dimensionality of the data while retaining its variance. To this data, we aim to apply K Nearest Neighbors Classification Algorith
Religious factors affecting death anxiety in older adults practicing Hinduism
The aim of the study was to examine the influence of religion on death anxiety in older adults (N = 105) practicing Hinduism and visiting the Kumbh pilgrimage. Standardized questionnaires and brief interviews were administered in participants' native language. Pilgrims with higher religiosity had lower death anxiety compared to pilgrims with lower religiosity. Greater belief in the cycle of rebirth, an increased presence of meaning in life, and less continued search of meaning in life were significantly associated with lower death anxiety. The findings provide support for incorporating religious and spiritual awareness for older adults in community health settings
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