3,142 research outputs found
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-κB 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-κB and HIF crosstalk has been documented, this has only been described following canonical NF-κB 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-2α is induced at the transcriptional level following non-canonical NF-κB activation, via a mechanism that is dependent on the p52 subunit. Furthermore, we demonstrate that p52 can bind to the HIF-2α promoter in cells. These results indicate that non-canonical NF-κB can lead to HIF signalling implicating HIF-2α 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
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