On the Lyapunov Matrix of Linear Delay Difference Equations in Continuous Time

The fundamental matrix and the delay Lyapunov matrix of linear delay difference equations are introduced. Some properties of the Lyapunov matrix, and the jump discontinuities of its derivative are proven, leading to its construction in the case of single delay or commensurate delays. An approximation is proposed for the non-commensurate case

Meteorological applications of fractal analysis

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric and Planetary Sciences, 1984.Microfiche copy available in Archives and Science.Bibliography: leaves 48-49.by Michael E. Rocha.M.S

HIF-1β Positively Regulates NF-κB Activity via Direct Control of TRAF6

NF-B signalling is crucial for cellular responses to inflammation but has also been associated with the hypoxia response. NF-B and HIF transcription factors possess an intense molecular crosstalk. Although it is known that HIF-1beta modulates NF-kappaB transcriptional response, very little is understood regarding how HIF-1beta contributes to NF-kappaB signalling. Here, we demonstrate that HIF-1beta is required for full NF-kappaB activation in cells following canonical and non-canonical stimuli. We found that HIF-1beta specifically controls TRAF6 expression in human cells but also in Drosophila melanogaster. HIF-1beta binds to the TRAF6 gene and controls its expression independently of HIF-1alpha. Furthermore, exogenous TRAF6 expression is able to rescue all of the cellular phenotypes observed in the absence of HIF-1beta. These results indicate that HIF-1beta is an important regulator of NF-kappaB with consequences for homeostasis and human disease.</jats:p

Can Feedback Solve the Too Big to Fail Problem?

The observed central densities of Milky Way dwarf spheroidal galaxies (dSphs) are significantly lower than the densities of the largest (Vmax about 35 km/s) subhalos found in dissipationless simulations of Galaxy-size dark matter hosts. One possible explanation is that gas removal from feedback can lower core densities enough to match observations. We model the dynamical effects of supernova feedback through the use of a time-varying central potential in high resolution, idealized numerical simulations and explore the resulting impact on the mass distributions of dwarf dark matter halos. We find that in order to match the observed central masses of M_star about 10^6 M_sun dSphs, the energy equivalent of more than 40,000 supernovae must be delivered with 100% efficiency directly to the dark matter. This energy requirement exceeds the number of supernovae that have ever exploded in most dSphs for typical initial mass functions. We also find that, per unit energy delivered and per cumulative mass removed from the galaxy, single blow-out events are more effective than repeated small bursts in reducing central dark matter densities. We conclude that it is unlikely that supernova feedback alone can solve the "Too Big to Fail" problem for Milky Way subhalos.Comment: 9 pages, 6 figures; v2 -- accepted to MNRA

Opportunity for All: How the American Public Benefits From Internet Access at U.S. Libraries

Examines the use of free computer and Internet access in public libraries, by income level, age, race/ethnicity, and online activity. Explores libraries' role as a community resource for social media, education, employment, e-government, and other areas

A Linear Classifier Based on Entity Recognition Tools and a Statistical Approach to Method Extraction in the Protein-Protein Interaction Literature

We participated, in the Article Classification and the Interaction Method subtasks (ACT and IMT, respectively) of the Protein-Protein Interaction task of the BioCreative III Challenge. For the ACT, we pursued an extensive testing of available Named Entity Recognition and dictionary tools, and used the most promising ones to extend our Variable Trigonometric Threshold linear classifier. For the IMT, we experimented with a primarily statistical approach, as opposed to employing a deeper natural language processing strategy. Finally, we also studied the benefits of integrating the method extraction approach that we have used for the IMT into the ACT pipeline. For the ACT, our linear article classifier leads to a ranking and classification performance significantly higher than all the reported submissions. For the IMT, our results are comparable to those of other systems, which took very different approaches. For the ACT, we show that the use of named entity recognition tools leads to a substantial improvement in the ranking and classification of articles relevant to protein-protein interaction. Thus, we show that our substantially expanded linear classifier is a very competitive classifier in this domain. Moreover, this classifier produces interpretable surfaces that can be understood as "rules" for human understanding of the classification. In terms of the IMT task, in contrast to other participants, our approach focused on identifying sentences that are likely to bear evidence for the application of a PPI detection method, rather than on classifying a document as relevant to a method. As BioCreative III did not perform an evaluation of the evidence provided by the system, we have conducted a separate assessment; the evaluators agree that our tool is indeed effective in detecting relevant evidence for PPI detection methods.Comment: BMC Bioinformatics. In Pres

TNFSF14/LIGHT, a Non-Canonical NF-κB Stimulus, Induces the HIF Pathway

Non-canonical NF-&kappa;B signalling plays important roles in the development and function of the immune system but it also is deregulated in a number of inflammatory diseases. Although, NF-&kappa;B and HIF crosstalk has been documented, this has only been described following canonical NF-&kappa;B stimulation, involving RelA/p50 and the HIF-1 dimer. Here, we report that the non-canonical inducer TNFSF14/LIGHT leads to HIF induction and activation in cancer cells. We demonstrate that only HIF-2&alpha; is induced at the transcriptional level following non-canonical NF-&kappa;B activation, via a mechanism that is dependent on the p52 subunit. Furthermore, we demonstrate that p52 can bind to the HIF-2&alpha; promoter in cells. These results indicate that non-canonical NF-&kappa;B can lead to HIF signalling implicating HIF-2&alpha; as one of the downstream effectors of this pathway in cells

Peer-selected "best papers" - are they really that "good"?

Background Peer evaluation is the cornerstone of science evaluation. In this paper, we analyze whether or not a form of peer evaluation, the pre-publication selection of the best papers in Computer Science (CS) conferences, is better than random, when considering future citations received by the papers. Methods Considering 12 conferences (for several years), we collected the citation counts from Scopus for both the best papers and the non-best papers. For a different set of 17 conferences, we collected the data from Google Scholar. For each data set, we computed the proportion of cases whereby the best paper has more citations. We also compare this proportion for years before 2010 and after to evaluate if there is a propaganda effect. Finally, we count the proportion of best papers that are in the top 10% and 20% most cited for each conference instance. Results The probability that a best paper will receive more citations than a non best paper is 0.72 (95% CI = 0.66, 0.77) for the Scopus data, and 0.78 (95% CI = 0.74, 0.81) for the Scholar data. There are no significant changes in the probabilities for different years. Also, 51% of the best papers are among the top 10% most cited papers in each conference/year, and 64% of them are among the top 20% most cited. Discussion There is strong evidence that the selection of best papers in Computer Science conferences is better than a random selection, and that a significant number of the best papers are among the top cited papers in the conference.Peer evaluation is the cornerstone of science evaluation. In this paper, we analyze whether or not a form of peer evaluation, the pre-publication selection of the best papers in Computer Science (CS) conferences, is better than random, when considering fu103112sem informaçãosem informaçã