Delay-dependent stability of high-order neutral systems

summary:In this note, we are concerned with delay-dependent stability of high-order delay systems of neutral type. A bound of unstable eigenvalues of the systems is derived by the spectral radius of a nonnegative matrix. The nonnegative matrix is related to the coefficient matrices. A stability criterion is presented which is a necessary and sufficient condition for the delay-dependent stability of the systems. Based on the criterion, a numerical algorithm is provided which avoids the computation of the coefficients of the characteristic function. Under some conditions, the presented results are less conservative than those reported. A numerical example is given to illustrate the main results

Morphological Dependence of Star Formation Properties for the Galaxies in the Merging Galaxy Cluster A2255

The merging cluster of galaxies A2255 is covered by the Sloan Digital Sky Survey (SDSS) survey. In this paper we perform a morphological classification on the basis of the SDSS imaging and spectral data, and investigate the morphological dependence of the star formation rates (SFRs) for these member galaxies. As we expect, a tight correlation between the normalized SFR by stellar mass (SFR/M$_*$) and the H$\alpha$ equivalent width is found for the late-type galaxies in A2255. The correlation of SFR/M$_*$ with the continuum break strength at 4000 \AA is also confirmed. The SFR/M$_*$ - M$_*$ correlation is found for both the early- and late-type galaxies, indicating that the star formation activity tends to be suppressed when the assembled stellar mass M$_*$) increases, and this correlation is tighter and steeper for the late-type cluster galaxies. Compared with the mass range of field spiral galaxies, only two massive late-type galaxies with M$_*>10^{11}$ M$_{\odot}$ are survived in A2255, suggesting that the gas disks of massive spiral galaxies could have been tidally stripped during cluster formation. Additionally, the SFR variation with the projected radial distance are found to be heavily dependent upon galaxy morphology: the early-type galaxies have a very weak inner decrease in SFR/M$_*$, while the inner late-type galaxies tend to have higher SFR/M$_*$ values than the outer late-types. This may suggest that the galaxy-scale turbulence stimulated by the merging of subclusters might have played different roles on early- and late-type galaxies, which leads to a suppression of the star formation activity for E/S0 galaxies and a SFR enhancement for spiral and irregular galaxies.Comment: 21 pages, including 7 EPS figures and 1 tables, uses aastex.cls, Accepted by the A

Semi-Supervised Text Simplification with Back-Translation and Asymmetric Denoising Autoencoders

Text simplification (TS) rephrases long sentences into simplified variants while preserving inherent semantics. Traditional sequence-to-sequence models heavily rely on the quantity and quality of parallel sentences, which limits their applicability in different languages and domains. This work investigates how to leverage large amounts of unpaired corpora in TS task. We adopt the back-translation architecture in unsupervised machine translation (NMT), including denoising autoencoders for language modeling and automatic generation of parallel data by iterative back-translation. However, it is non-trivial to generate appropriate complex-simple pair if we directly treat the set of simple and complex corpora as two different languages, since the two types of sentences are quite similar and it is hard for the model to capture the characteristics in different types of sentences. To tackle this problem, we propose asymmetric denoising methods for sentences with separate complexity. When modeling simple and complex sentences with autoencoders, we introduce different types of noise into the training process. Such a method can significantly improve the simplification performance. Our model can be trained in both unsupervised and semi-supervised manner. Automatic and human evaluations show that our unsupervised model outperforms the previous systems, and with limited supervision, our model can perform competitively with multiple state-of-the-art simplification systems

Screening drugs for myocardial disease in vivo with zebrafish : an expert update

Introduction: Our understanding of the complexity of cardiovascular disease pathophysiology remains very incomplete and has hampered cardiovascular drug development over recent decades. The prevalence of cardiovascular diseases and their increasing global burden call for novel strategies to address disease biology and drug discovery. Areas covered: This review describes the recent history of cardiovascular drug discovery using in vivo phenotype-based screening in zebrafish. The rationale for the use of this model is highlighted and the initial efforts in the fields of disease modeling and high-throughput screening are illustrated. Finally, the advantages and limitations of in vivo zebrafish screening are discussed, highlighting newer approaches, such as genome editing technologies, to accelerate our understanding of disease biology and the development of precise disease models. Expert opinion: Full understanding and faithful modeling of specific cardiovascular disease is a rate limiting step for cardiovascular drug discovery. The resurgence of in vivo phenotype screening together with the advancement of systems biology approaches allows for the identification of lead compounds which show efficacy on integrative disease biology in the absence of validated targets. This strategy bypasses current gaps in knowledge of disease biology and paves the way for successful drug discovery and downstream molecular target identification