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

Gata4 Is Required for Formation of the Genital Ridge in Mice

In mammals, both testis and ovary arise from a sexually undifferentiated precursor, the genital ridge, which first appears during mid-gestation as a thickening of the coelomic epithelium on the ventromedial surface of the mesonephros. At least four genes (Lhx9, Sf1, Wt1, and Emx2) have been demonstrated to be required for subsequent growth and maintenance of the genital ridge. However, no gene has been shown to be required for the initial thickening of the coelomic epithelium during genital ridge formation. We report that the transcription factor GATA4 is expressed in the coelomic epithelium of the genital ridge, progressing in an anterior-to-posterior (A-P) direction, immediately preceding an A-P wave of epithelial thickening. Mouse embryos conditionally deficient in Gata4 show no signs of gonadal initiation, as their coelomic epithelium remains a morphologically undifferentiated monolayer. The failure of genital ridge formation in Gata4-deficient embryos is corroborated by the absence of the early gonadal markers LHX9 and SF1. Our data indicate that GATA4 is required to initiate formation of the genital ridge in both XX and XY fetuses, prior to its previously reported role in testicular differentiation of the XY gonadHoward Hughes Medical Institut