99,372 research outputs found
Critical congenital heart disease screening by pulse oximetry in a neonatal intensive care unit.
ObjectiveCritical congenital heart disease (CCHD) screening is effective in asymptomatic late preterm and term newborn infants with a low false-positive rate (0.035%). (1) To compare 2817 neonatal intensive care unit (NICU) discharges before and after implementation of CCHD screening; and (2) to evaluate CCHD screening at <35 weeks gestation.Study designCollection of results of CCHD screening including pre- and postductal pulse oximetry oxygen saturation (SpO2) values.ResultDuring the pre-CCHD screen period, 1247 infants were discharged from the NICU and one case of CCHD was missed. After 1 March 2012, 1508 CCHD screens were performed among 1570 discharges and no CCHDs were missed. The pre- and postductal SpO2 values were 98.8 ± 1.4% and 99 ± 1.3%, respectively, in preterm and 98.9 ± 1.3% and 98.9 ± 1.4%, respectively, in term infants. Ten infants had false-positive screens (10/1508 = 0.66%).ConclusionPerforming universal screening in the NICU is feasible but is associated with a higher false-positive rate compared with asymptomatic newborn infants
ELIMINATION OF CADMIUM AND LEAD MIXTURE IN SOLUTION BY PRETREATED RICE STRAW AND HUSK
An experiment on the activity of pretreated rice straw and husk in eliminating heavy metals from solution has been conducted. The rice straw and husk were soaked in 3% NaOH solution, drained and then washed with demineralised water until the washing became neutral (the results were referred to as straw and husk). The pretreated rice straw and husk (straw and husk) were mixed (stirring and without stirring) separately with Cd and Pb solution in time series. It was
found that Cd was adsorbed more than Pb and straw was more active than husk. On the other hand, the stirring process and time series did not give much effect on straw, while the activity of husk increased with the increase of time period
Empirical and Simulated Adjustments of Composite Likelihood Ratio Statistics
Composite likelihood inference has gained much popularity thanks to its
computational manageability and its theoretical properties. Unfortunately,
performing composite likelihood ratio tests is inconvenient because of their
awkward asymptotic distribution. There are many proposals for adjusting
composite likelihood ratio tests in order to recover an asymptotic chi square
distribution, but they all depend on the sensitivity and variability matrices.
The same is true for Wald-type and score-type counterparts. In realistic
applications sensitivity and variability matrices usually need to be estimated,
but there are no comparisons of the performance of composite likelihood based
statistics in such an instance. A comparison of the accuracy of inference based
on the statistics considering two methods typically employed for estimation of
sensitivity and variability matrices, namely an empirical method that exploits
independent observations, and Monte Carlo simulation, is performed. The results
in two examples involving the pairwise likelihood show that a very large number
of independent observations should be available in order to obtain accurate
coverages using empirical estimation, while limited simulation from the full
model provides accurate results regardless of the availability of independent
observations.Comment: 15 page
Loss Functions for Top-k Error: Analysis and Insights
In order to push the performance on realistic computer vision tasks, the
number of classes in modern benchmark datasets has significantly increased in
recent years. This increase in the number of classes comes along with increased
ambiguity between the class labels, raising the question if top-1 error is the
right performance measure. In this paper, we provide an extensive comparison
and evaluation of established multiclass methods comparing their top-k
performance both from a practical as well as from a theoretical perspective.
Moreover, we introduce novel top-k loss functions as modifications of the
softmax and the multiclass SVM losses and provide efficient optimization
schemes for them. In the experiments, we compare on various datasets all of the
proposed and established methods for top-k error optimization. An interesting
insight of this paper is that the softmax loss yields competitive top-k
performance for all k simultaneously. For a specific top-k error, our new top-k
losses lead typically to further improvements while being faster to train than
the softmax.Comment: In Computer Vision and Pattern Recognition (CVPR), 201
Extending the Higgs sector: an extra singlet
An extension of the Standard Model with an additional Higgs singlet is
analyzed. Bounds on singlet admixture in 125 GeV h boson from electroweak
radiative corrections and data on h production and decays are obtained.
Possibility of double h production enhancement at 14 TeV LHC due to heavy higgs
contribution is considered.Comment: 18 pages, 7 figures. v2: one equation added; references received
after the publication of v1 are adde
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