Numerical Verification of an Analytical Model for Phase Noise in MEMS Oscillators.

A new analytical formulation for phase noise in MEMS oscillators was recently presented encompassing the role of essential nonlinearities in the electrical and mechanical domains. In this paper, we validate the effectiveness of the proposed analytical formulation with respect to the unified theory developed by Demir et al. describing phase noise in oscillators. In particular, it is shown that, over a range of the second-order mechanical nonlinear stiffness of the MEMS resonator, both models exhibit an excellent match in the phase diffusion coefficient calculation for a square-wave MEMS oscillator.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/TUFFC.2016.257536

Measurement of extravascular lung water to diagnose severe reperfusion lung injury following pulmonary endarterectomy: a prospective cohort clinical validation study

The measurement of extravascular lung water is a relatively new technology which has not yet been well validated as a clinically useful tool. We studied its utility in patients undergoing pulmonary endarterectomy as they frequently suffer reperfusion lung injury and associated oedematous lungs. Such patients are therefore ideal for evaluating this new monitor. We performed a prospective observational cohort study during which extravascular lung water index measurements were taken before and immediately after surgery and postoperatively in intensive care. Data were analysed for 57 patients; 21 patients (37%) experienced severe reperfusion lung injury. The first extravascular lung water index measurement after cardiopulmonary bypass failed to predict severe reperfusion lung injury, area under the receiver operating characteristic curve 0.59 (95%CI 0.44–0.74). On intensive care, extravascular lung water index correlated most strongly at 36 h, area under the receiver operating characteristic curve 0.90 (95%CI 0.80–1.00). Peri‐operative extravascular lung water index is not a useful measure to predict severe reperfusion lung injury after pulmonary endarterectomy, however, it does allow monitoring and measurement during the postoperative period. This study implies that extravascular lung water index can be used to directly assess pulmonary fluid overload and that monitoring patients by measuring extravascular lung water index during their intensive care stay is useful and correlates with their clinical course. This may allow directed, pre‐empted therapy to attenuate the effects and improve patient outcomes and should prompt further studies

Evolutionary and ecological insights from herbicide‐resistant weeds: what have we learned about plant adaptation, and what is left to uncover?

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149516/1/nph15723_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149516/2/nph15723.pd

Multi-locus approaches for the measurement of selection on correlated genetic loci

The study of ecological speciation is inherently linked to the study of selection. Methods for estimating phenotypic selection within a generation based on associations between trait values and fitness (e.g., survival) of individuals are established. These methods attempt to disentangle selection acting directly on a trait from indirect selection caused by correlations with other traits via multivariate statistical approaches (i.e., inference of selection gradients). The estimation of selection on genotypic or genomic variation could also benefit from disentangling direct and indirect selection on genetic loci. However, achieving this goal is difficult with genomic data because the number of potentially correlated genetic loci (p) is very large relative to the number of individuals sampled (n). In other words, the number of model parameters exceeds the number of observations (p ≫ n). We present simulations examining the utility of whole genome regression approaches (i.e., Bayesian sparse linear mixed models) for quantifying direct selection in cases where p ≫ n. Such models have been used for genome-wide association mapping and are common in artificial breeding. Our results show they hold promise for studies of natural selection in the wild, and thus of ecological speciation. But we also demonstrate important limitations to the approach and discuss study designs required for more robust inferences

Multi-modal signal evolution in birds: re-examining a standard proxy for sexual selection

Sexual selection is proposed to be an important driver of speciation and phenotypic diversification in animal systems. However, previous phylogenetic tests have produced conflicting results, perhaps because they have focused on a single signalling modality (visual ornaments), whereas sexual selection may act on alternative signalling modalities (e.g. acoustic ornaments). Here, we compile phenotypic data from 259 avian sister species pairs to assess the relationship between visible plumage dichromatism-a standard index of sexual selection in birds-and macroevolutionary divergence in the other major avian signalling modality: song. We find evidence for a strong negative relationship between the degree of plumage dichromatism and divergence in song traits, which remains significant even when accounting for other key factors, including habitat type, ecological divergence and interspecific interactions. This negative relationship is opposite to the pattern expected by a straightforward interpretation of the sexual selection-diversification hypothesis, whereby higher levels of dichromatism indicating strong sexual selection should be related to greater levels of mating signal divergence regardless of signalling modality. Our findings imply a 'trade-off' between the elaboration of visual ornaments and the diversification of acoustic mating signals, and suggest that the effects of sexual selection on diversification can only be determined by considering multiple alternative signalling modalities

Approximate probabilistic verification of hybrid systems

Hybrid systems whose mode dynamics are governed by non-linear ordinary differential equations (ODEs) are often a natural model for biological processes. However such models are difficult to analyze. To address this, we develop a probabilistic analysis method by approximating the mode transitions as stochastic events. We assume that the probability of making a mode transition is proportional to the measure of the set of pairs of time points and value states at which the mode transition is enabled. To ensure a sound mathematical basis, we impose a natural continuity property on the non-linear ODEs. We also assume that the states of the system are observed at discrete time points but that the mode transitions may take place at any time between two successive discrete time points. This leads to a discrete time Markov chain as a probabilistic approximation of the hybrid system. We then show that for BLTL (bounded linear time temporal logic) specifications the hybrid system meets a specification iff its Markov chain approximation meets the same specification with probability $1$. Based on this, we formulate a sequential hypothesis testing procedure for verifying -approximately- that the Markov chain meets a BLTL specification with high probability. Our case studies on cardiac cell dynamics and the circadian rhythm indicate that our scheme can be applied in a number of realistic settings

Fractional Euler-Lagrange differential equations via Caputo derivatives

We review some recent results of the fractional variational calculus. Necessary optimality conditions of Euler-Lagrange type for functionals with a Lagrangian containing left and right Caputo derivatives are given. Several problems are considered: with fixed or free boundary conditions, and in presence of integral constraints that also depend on Caputo derivatives.Comment: This is a preprint of a paper whose final and definite form will appear as Chapter 9 of the book Fractional Dynamics and Control, D. Baleanu et al. (eds.), Springer New York, 2012, DOI:10.1007/978-1-4614-0457-6_9, in pres

A database of microRNA expression patterns in Xenopus laevis

MicroRNAs (miRNAs) are short, non-coding RNAs around 22 nucleotides long. They inhibit gene expression either by translational repression or by causing the degradation of the mRNAs they bind to. Many are highly conserved amongst diverse organisms and have restricted spatio-temporal expression patterns during embryonic development where they are thought to be involved in generating accuracy of developmental timing and in supporting cell fate decisions and tissue identity. We determined the expression patterns of 180 miRNAs in Xenopus laevis embryos using LNA oligonucleotides. In addition we carried out small RNA-seq on different stages of early Xenopus development, identified 44 miRNAs belonging to 29 new families and characterized the expression of 5 of these. Our analyses identified miRNA expression in many organs of the developing embryo. In particular a large number were expressed in neural tissue and in the somites. Surprisingly none of the miRNAs we have looked at show expression in the heart. Our results have been made freely available as a resource in both XenMARK and Xenbase

Pairwise statistical significance of local sequence alignment using multiple parameter sets and empirical justification of parameter set change penalty

Background: Accurate estimation of statistical significance of a pairwise alignment is an important problem in sequence comparison. Recently, a comparative study of pairwise statistical significance with database statistical significance was conducted. In this paper, we extend the earlier work on pairwise statistical significance by incorporating with it the use of multiple parameter sets. Results: Results for a knowledge discovery application of homology detection reveal that using multiple parameter sets for pairwise statistical significance estimates gives better coverage than using a single parameter set, at least at some error levels. Further, the results of pairwise statistical significance using multiple parameter sets are shown to be significantly better than database statistical significance estimates reported by BLAST and PSI-BLAST, and comparable and at times significantly better than SSEARCH. Using non-zero parameter set change penalty values give better performance than zero penalty. Conclusion: The fact that the homology detection performance does not degrade when using multiple parameter sets is a strong evidence for the validity of the assumption that the alignment score distribution follows an extreme value distribution even when using multiple parameter sets. Parameter set change penalty is a useful parameter for alignment using multiple parameter sets. Pairwise statistical significance using multiple parameter sets can be effectively used to determine the relatedness of a (or a few) pair(s) of sequences without performing a time-consuming database search