266 research outputs found
Experimental methodology for characterizing flame emissivity of small scale forest fires using infrared thermography techniques
An experimental methodology based on thermography techniques has been developed
and implemented with the aim of finding emissivity values of forest fuel flames. In this paper, previous works by different authors are discussed and theoretical fundamentals of heat transfer by radiation and of infrared thermography on which experimental method relies are briefly
described. Then, designed methodology, equipments, devices and experimental tests are detailed in depth. Finally, analysis procedure is pointed out and some conclusions from the study of theresults are announced.Postprint (published version
The formation of physician patient sharing networks in medicare: Exploring the effect of hospital affiliation
This study explores the forces that drive the formation of physician patient sharing networks. In particular, I examine the degree to which hospital affiliation drives physicians\u27 sharing of Medicare patients. Using a revealed preference framework where observed network links are taken to be pairwise stable, I estimate the physicians\u27 pair‐specific values using a tetrad maximum score estimator that is robust to the presence of unobserved physician specific characteristics. I also control for a number of potentially confounding patient sharing channels, such as (a) common physician group or hospital system affiliation, (b) physician homophily, (c) knowledge complementarity, (d) patient side considerations related to both geographic proximity and insurance network participation, and (e) spillover from other collaborations. Focusing on the Chicago hospital referral region, I find that shared hospital affiliation accounts for 36.5% of the average pair‐specific utility from a link. Implications for reducing care fragmentation are discussed
Tailored graph ensembles as proxies or null models for real networks I: tools for quantifying structure
We study the tailoring of structured random graph ensembles to real networks,
with the objective of generating precise and practical mathematical tools for
quantifying and comparing network topologies macroscopically, beyond the level
of degree statistics. Our family of ensembles can produce graphs with any
prescribed degree distribution and any degree-degree correlation function, its
control parameters can be calculated fully analytically, and as a result we can
calculate (asymptotically) formulae for entropies and complexities, and for
information-theoretic distances between networks, expressed directly and
explicitly in terms of their measured degree distribution and degree
correlations.Comment: 25 pages, 3 figure
Efficient and exact sampling of simple graphs with given arbitrary degree sequence
Uniform sampling from graphical realizations of a given degree sequence is a
fundamental component in simulation-based measurements of network observables,
with applications ranging from epidemics, through social networks to Internet
modeling. Existing graph sampling methods are either link-swap based
(Markov-Chain Monte Carlo algorithms) or stub-matching based (the Configuration
Model). Both types are ill-controlled, with typically unknown mixing times for
link-swap methods and uncontrolled rejections for the Configuration Model. Here
we propose an efficient, polynomial time algorithm that generates statistically
independent graph samples with a given, arbitrary, degree sequence. The
algorithm provides a weight associated with each sample, allowing the
observable to be measured either uniformly over the graph ensemble, or,
alternatively, with a desired distribution. Unlike other algorithms, this
method always produces a sample, without back-tracking or rejections. Using a
central limit theorem-based reasoning, we argue, that for large N, and for
degree sequences admitting many realizations, the sample weights are expected
to have a lognormal distribution. As examples, we apply our algorithm to
generate networks with degree sequences drawn from power-law distributions and
from binomial distributions.Comment: 8 pages, 3 figure
Constrained Markovian dynamics of random graphs
We introduce a statistical mechanics formalism for the study of constrained
graph evolution as a Markovian stochastic process, in analogy with that
available for spin systems, deriving its basic properties and highlighting the
role of the `mobility' (the number of allowed moves for any given graph). As an
application of the general theory we analyze the properties of
degree-preserving Markov chains based on elementary edge switchings. We give an
exact yet simple formula for the mobility in terms of the graph's adjacency
matrix and its spectrum. This formula allows us to define acceptance
probabilities for edge switchings, such that the Markov chains become
controlled Glauber-type detailed balance processes, designed to evolve to any
required invariant measure (representing the asymptotic frequencies with which
the allowed graphs are visited during the process). As a corollary we also
derive a condition in terms of simple degree statistics, sufficient to
guarantee that, in the limit where the number of nodes diverges, even for
state-independent acceptance probabilities of proposed moves the invariant
measure of the process will be uniform. We test our theory on synthetic graphs
and on realistic larger graphs as studied in cellular biology.Comment: 28 pages, 6 figure
Design and Synthesis of Heterocyclic Cations for Specific DNA Recognition: From AT-Rich to Mixed-Base-Pair DNA Sequences
The compounds synthesized in this research were designed with the goal of establishing a new paradigm for mixed-base-pair DNA sequence-specific recognition. The design scheme starts with a cell-permeable heterocyclic cation that binds to AT base pair sites in the DNA minor groove. Modifications were introduced in the original compound to include an Hbond accepting group to specifically recognize the G-NH that projects into the minor groove. Therefore, a series of heterocyclic cations substituted with an azabenzimidazole ring has been designed and synthesized for mixed-base-pair DNA recognition. The most successful compound, 12a, had an azabenzimidazole to recognize G and additional modifications for general minor groove interactions. It binds to the DNA site −AAAGTTT− more strongly than the −AAATTT− site without GC and indicates the design success. Structural modifications of 12a generally weakened binding. The interactions of the new compound with a variety of DNA sequences with and without GC base pairs were evaluated by thermal melting analysis, circular dichroism, fluorescence emission spectroscopy, surface plasmon resonance, and molecular modeling
Using Transcription Modules to Identify Expression Clusters Perturbed in Williams-Beuren Syndrome
The genetic dissection of the phenotypes associated with Williams-Beuren Syndrome (WBS) is advancing thanks to the study of individuals carrying typical or atypical structural rearrangements, as well as in vitro and animal studies. However, little is known about the global dysregulations caused by the WBS deletion. We profiled the transcriptomes of skin fibroblasts from WBS patients and compared them to matched controls. We identified 868 differentially expressed genes that were significantly enriched in extracellular matrix genes, major histocompatibility complex (MHC) genes, as well as genes in which the products localize to the postsynaptic membrane. We then used public expression datasets from human fibroblasts to establish transcription modules, sets of genes coexpressed in this cell type. We identified those sets in which the average gene expression was altered in WBS samples. Dysregulated modules are often interconnected and share multiple common genes, suggesting that intricate regulatory networks connected by a few central genes are disturbed in WBS. This modular approach increases the power to identify pathways dysregulated in WBS patients, thus providing a testable set of additional candidates for genes and their interactions that modulate the WBS phenotypes
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