ライフサイエンスコーパス: Bernoulli

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1 Bernoulli's equation relates differences between P(IA) (

2 e data with predictions of two models: (1) a Bernoulli Model in which bases are assumed equally likel

3 h the figure predicted by modelling DNA as a Bernoulli stream or as a Markov chain, using windows of

4 stributed (i.i.d.) random variables, i.e., a Bernoulli sequence.

5 We introduce a Bernoulli-lognormal mixture model for clustering DNA met

6 Combining this measurement model with a Bernoulli prior over binary spike trains yields a poster

7 ine, random forest, Gaussian naive Bayes and Bernoulli naive Bayes for separating infectious from non

8 the standard elastic rod theory of Euler and Bernoulli, or even the more general Cosserat theory of r

9 s: multinomial, Poisson, hypergeometric, and Bernoulli product.

10 An idealized adaptive case--the two-armed Bernoulli bandit problem--can be exactly optimized for a

11 hese components (spaces) inferred via a beta-Bernoulli process.

12 probability of identifying a protein at each Bernoulli event is determined from relative length of th

13 robability of protein identification at each Bernoulli event.

14 myloid fibrils, suggesting that simple Euler-Bernoulli beam models fail to describe the mechanics of

15 similar to the ratio predicted by the Euler-Bernoulli theorem for linear cantilevers.

16 that each analyte represents an independent Bernoulli random variable, which is then used to predict

17 e MRF prior to a situation where independent Bernoulli priors are chosen for the individual predictor

18 ound on the information lost when spiking is Bernoulli in discrete time bins.

19 ents were estimated by means of the modified Bernoulli equation, and VTIs were calculated to estimate

20 e PASP was calculated by use of the modified Bernoulli equation, with right atrial pressure assumed t

21 In this article, we apply the multivariate Bernoulli (MVB) distribution to model haplotype data.

22 nalysis allowing for normally distributed or Bernoulli distributed exposures, outcomes, mediators, me

23 , commonly taken to be 4.0 in the simplified Bernoulli equation delta P = KV2, was a function of sten

24 sumption that the target is strand-symmetric Bernoulli text (i.e. nucleotides are independently, iden

25 ming the continuum hypothesis, we prove that Bernoulli function(H) has a pure state whose restriction

26 The Bernoulli event has two outcomes: a protein is either id

27 The Bernoulli-lognormal mixture assigns observations to subg

28 erent models: (1) the Poisson model, (2) the Bernoulli model and (3) the zero-truncated Poisson model

29 From the calculated loading, and the Bernoulli-Euler curvature and moment equation, we find t

30 However, the Bernoulli formulation demonstrated a consistent overesti

31 However, the Bernoulli principle relies on several approximations tha

32 ribution using the unsteady flow form of the Bernoulli equation and was compared to the catheter meas

33 Neither (1) simplification of the Bernoulli equation nor (2) pressure recovery effects can

34 The application of the Bernoulli formulation results in a clinically significan

35 METHODS AND We assessed the accuracy of the Bernoulli principle to estimate the peak pressure drop a

36 noninvasively by echocardiography using the Bernoulli principle.

37 ed into a cantilever-in-mass model using the Bernoulli-Euler beam theory.

38 gths </= 3 are in general agreement with the Bernoulli Model.

39 uld then be integrated to yield the unsteady Bernoulli equation and estimate noninvasively both the c

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