1,166 research outputs found
Bayesian modelling for semi-competing risks data in the presence of censoring
In biomedical research, challenges to working with multiple events are often observed while dealing with time-to-event data. Studies on prolonged survival duration are prone to having numerous possibilities. In studies on prolonged survival, patients might die of other causes. Sometimes in the survival studies, patients experienced some events (e.g. cancer relapse) before dying within the study period. In this context, the semi-competing risks framework was found useful. Similarly, the prolonged duration of follow-up studies is also affected by censored observation, especially interval censoring, and right censoring. Some conventional approaches work with time-to-event data, like the Cox-proportional hazard model. However, the accelerated failure time (AFT) model is more effective than the Cox model because it overcomes the proportionality hazard assumption. We also observed covariates impacting the time-to-event data measured as the categorical format. No established method currently exists for fitting an AFT model that incorporates categorical covariates, multiple events, and censored observations simultaneously. This work is dedicated to overcoming the existing challenges by the applications of R programming and data illustration. We arrived at a conclusion that the developed methods are suitable to run and easy to implement in R software. The selection of covariates in the AFT model can be evaluated using model selection criteria such as the Deviance Information Criteria (DIC) and Log-pseudo marginal likelihood (LPML). Various extensions of the AFT model, such as AFT-DPM and AFT-LN, have been demonstrated. The final model was selected based on minimum DIC values and larger LPML values.</p
Security Circumvention: To Educate or To Enforce?
Deliberate circumvention of information systems security is a common behavioral pattern among users. It not only defeats the purpose of having the security controls in place, but can also go far beyond in terms of the total damage it can cause. An organization grappling with circumvention can try to (i) train its users, or (ii) take on enforcement measures, or adopt a combination of the two. In this work, we look at the trade-off between these two very different approaches towards circumvention and try to gain some insights about how an organization might wish to tackle this menace
An Unsupervised Deep Learning Model for Aspect Retrieving Using Transformer Encoder
We introduce a deep-learning-based aspect extraction model called RATE, which stands for Retrieving of Aspects using Transformer Encoder. When doing unsupervised aspect-based sentiment analysis, the process of retrieving aspects is both critical and challenging. Most prior efforts use some kind of topic modeling to extract aspect only. Despite their efficacy, these techniques seldom provide consistent outcomes for highly coherent aspects. Even though some approaches address these issues by employing an attention-based deep neural model, their performance is hindered by their single-headed attention mechanism. Thus, RATE is designed to improve the performance of extracting coherent aspects from the text by using multi-headed attention mechanism with transformer encoder, negative samplings, and word embeddings. This model promotes the proximity in the embedding space of words that arise in similar contexts, as opposed to topic models and other techniques that often presume independently created words. To further enhance the coherence of the aspects, we use multi-headed attention technique in the encoder of the RATE architecture to downplay unimportant words during training. The RATE model outperforms the highest performing unsupervised baseline ones in terms of precision (8.34%), recall (0.94%), and f1-score (5.44%) on the ACOS-Laptop dataset. Again, on the ACOS-Restaurant dataset, RATE enhances precision, recall, and f1-score by , , and , respectively, for finding more significant and coherent aspects
Perception of prevention of Japanese Encephalitis with emphasis on its vaccination programme: a community based study in a slum of Kolkata
Introduction
Japanese Encephalitis (JE) is a mosquito borne disease with epidemic potential. There is no specific treatment available till date and apart from vector control, vaccination of individuals is considered as a safe and effective measure for prevention. Vaccination campaign among 1-15 years is being carried out with full vigour from 2015 onwards in West Bengal.
Objectives
This study was conducted to assess the knowledge of the care givers of 1-15 years old children about JE and its prevention and to find out the factors associated with vaccination status of the children.
Methods
A cross sectional, community based study was conducted from May-June 2016 in a slum of Chetla, Kolkata, which is within the service area of Urban Health Unit and Training Centre (UHU&TC), Chetla of All India Institute of Hygiene and Public Health, Kolkata, where the campaign prior to the study was completed in March 2016. Care givers of 90 children of aged 1-15 years were interviewed with a pre-designed, pre-tested, structured schedule.
Results
Mean age of the surveyed children was 6.34 years (SD 3.76) and 88% of them were vaccinated during the campaign. 56.7% of the caregivers had poor knowledge about JE and 84.95% were sensitized about the campaign by relatives/friends followed by health workers (33.7%). Low socio-economic status and good knowledge of JE had significant association with vaccination of the child after adjusting with other factors (age and sex of the child, education and occupation of parents, type of family).
Conclusions
Enhancement of knowledge and awareness about JE with appropriate health education programmes and special emphasis on sensitization campaigns for JE vaccination at both mass and individual level would prevent emergence of JE epidemics in future
Studies on permeability properties and particle capture efficiencies of porous SiC ceramics processed by oxide bonding technique
Porous SiC ceramics bonded with mullite (MBS of fractional porosity (e) of 0.29-0.56, average pore size (dpore) of 5-11 μm, flexural strength (σ) of 9-34 MPa and elastic modulus (E) of 7-28GPa) and cordierite (CBS with e of 0.33-0.72, dpore of 6-50 μm, σ of 5-54 MPa and E of 6-42 GPa) were prepared by heating in air at 1350-1500°C compacts of desired amounts of SiC, Al2O3 and MgO powders and petroleum coke dust as the pore former. Air permeation behavior of well-characterized samples was studied with fluid superficial velocity (vs) from 0.08 to 1.0 m s-1and at RT to 750°C. The Darcian (k1) and non-Darcian (k2) permeability coefficients were evaluated by fitting the Forchheimer’s equation to experimental pressure drop-superficial velocity data. Porosity dependence of permeability coefficients was explained in terms of structural characteristics. Changes in pressure drop experienced by the porous ceramics at high temperatures were explained by temperature dependence of permeability coefficients and variation of fluid properties. Collection efficiency (η) of filter ceramics operating on removal of solid NaCl nanoaerosol particles (of 7-300 nm size) was determined from particle counts before and after filtration at vs = 0.05-0.10 m s-1. Experimental results showed variation of η from 96.7 to 99.9% for change of e from 0.56 to 0.68. The size-selective fractional collection efficiency at different porosity levels was derived using the well-known single-collector efficiency model considering some boundary conditions and the model data were validated with experimental results. The test results were used to examine the applicability of the filter ceramics in nanoparticle filtration processes
Eye of the tiger sign in neurodegeneration with brain iron accumulation: a case report
Neurodegeneration with brain iron accumulation (NBIA) is a rare autosomal recessive disorder characterized by abnormal accumulation of ferritin in globus pallidus of brain. Magnetic resonance imaging (MRI) of brain demonstrates a characteristic ‘eye-of-the-tiger’ sign. We describe a case of NBIA in a child with classical clinical and MRI of brain features
EFFECT OF SiC PARTICLE SIZE ON THE MATERIAL AND MECHANICAL PROPERTIES OF MULLITE BONDED SiC CERAMICS PROCESSED BY INFILTRATION TECHNIQUE
The influence of SiC particles size on the bonding phase content, microstructure, SiC oxidation degree, flexural strength,
porosity and pore size distribution of mullitebonded porous SiC ceramics were studied and compared with oxidebonded
porous SiC ceramics. The SEM morphologies and EDS elemental analysis results showed the presence of needle shaped
crystals of mullite and fish scaled cristobalite in the bond phase. It was found that increase of SiC particle size effectively
enhanced the porosity and decreased the strength. The porosity decreased as the size of SiC particles decreased from 36 vol. %
at 99 μm to 25 vol. % at 4.47 μm. The oxidation degree of SiC was found to be reduced by infiltration of mullite precursor
sol and enhanced with sintering temperature. Bimodal pore size distributions were obtained for mullite-bonded porous SiC
ceramics and the average pore diameter varied in the range of 2 - 30 μm with variation of particle size
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