Solid solution GaSe1−xSx single crystals for THz generation

A table top source of coherent Terahertz (30-1000 µm) radiation, which is high power, narrow bandwidth, and broadly tunable, is high desired for applications in imaging, non-destructive testing (NDT), quantum, security and biomedical technologies. In spite of intensive research over many decades such a device remains elusive. Sulpher doped Gallium Selenide (GaSex−1Sx) solid solution ε-polytype crystals are an outstanding candidate for the efficient generation of radiation and tunability throughout the majority of the Terahertz (THz) regime; thanks to the prodigious linear and nonlinear optical properties of the Gallium Selenide (GaSe) parent crystal. Close control of doping and the crystal growth process enable the manufacture of superior quality nonlinear crystals, where the optical properties may be engineered and the mechanical properties vastly improved. Thus overcoming many of the physical issues that, despite its exceptional optical properties, have frustrated the widespread adoption of GaSe for laser frequency down conversion to the THz regime. In order to fully exploit the potential of GaSex−1Sx crystals and successfully design efficient sources for THz generation the optical properties of these crystals must be accurately determined and their transformation with doping well understood. The work in this thesis aims to accurately determine the optical properties of GaSe, Gallium Sulphide (GaS) and GaSex−1Sx crystals in the Far-Infrared and THz regimes to enable this exploitation. In the first phase of investigation we determine the linear refractive index (n) and absorption (α) coefficient for both the o and e waves in the THz regime (0.14.5 THz) using Terahertz - Time Domain Spectroscopy (THz-TDS) for GaSe, and a dense set of GaSex−1Sx crystals (x = 0.05 0.11 0.22 0.29 0.44). Measurements of THz dispersion and absorption properties of GaS crystals are performed for the first time. The transformation of the optical properties of the crystals and their phonon structure is studied. We examine the sources of inaccuracy in the THzTDs measurements of high refractive index birefringent crystals and propose a set of criteria for the selection of adequate data. The nonlinear Figure of Merit (FOM) of available high quality GaSex−1Sx crystals is found to be an order of magnitude less than that predicted in the literature, with FOM = 19.8 for GaSe, FOM = 17 for GaSex−1Sx, on the other hand estimates for double doping with Sulphur and Aluminium predict significant enhanced of these FOM values, up to 5-10 times. In the second phase of investigation we examine the phonon band of the GaSe, GaS and GaSex−1Sx by FTIR and Raman spectroscopy. For the first time we determine the absorption coefficients of the main phonon peak in the set of GaSex−1Sx crystals. The transformation of the phonon band with doping is studied. In the third phase of investigation we attempt to determine the nonlinear optical properties deff and n2 of GaSe and GaSex−1Sx in the Far Infra-Red (FIR) and THz regimes using the Maker fringe and Z-scan methods on the FELIX free electron laser

Griffithsia schousboei (Ceramiaceae, Rhodophyceae), a species new to South Africa

A species of Griffithsia from southern Natal has been isolated into unialgal culture. Its vegetative and reproductive characters align it with G. schousboei, a species previously known only to occur in Portugal, the Mediterranean and Caribbean Seas, and south to Brazil and Ghana. This report extends the known range of this alga to Natal. Closely related species are discussed and synonymies recommended

Exercise and the microbiota

The authors are supported in part by research grants from Science Foundation Ireland including a centre grant (Alimentary Pharmabiotic Centre; Grant Numbers SFI/12/RC/2273 and 12/RC/2273). Dr. Orla O’Sullivan is funded by a Starting Investigator Research Grant from Science Foundation Ireland (Grant number 13/SIRG/2160). Dr. Paul Cotter is funded by a Principal Investigator Award from Science Foundation Ireland P.D.C are supported by a SFI PI award (Grant number 11/PI/1137).peer-reviewedSedentary lifestyle is linked with poor health, most commonly obesity and associated disorders, the corollary being that exercise offers a preventive strategy. However, the scope of exercise biology extends well beyond energy expenditure and has emerged as a great ‘polypill’, which is safe, reliable and cost-effective not only in disease prevention but also treatment. Biological mechanisms by which exercise influences homeostasis are becoming clearer and involve multi-organ systemic adaptations. Most of the elements of a modern lifestyle influence the indigenous microbiota but few studies have explored the effect of increased physical activity. While dietary responses to exercise obscure the influence of exercise alone on gut microbiota, professional athletes operating at the extremes of performance provide informative data. We assessed the relationship between extreme levels of exercise, associated dietary habits and gut microbiota composition, and discuss potential mechanisms by which exercise may exert a direct or indirect influence on gut microbiota.The authors are supported in part by research grants from Science Foundation Ireland including a centre grant (Alimentary Pharmabiotic Centre; Grant Numbers SFI/12/RC/2273 and 12/RC/2273). Dr. Orla O’Sullivan is funded by a Starting Investigator Research Grant from Science Foundation Ireland (Grant number 13/SIRG/2160). Dr. Paul Cotter is funded by a Principal Investigator Award from Science Foundation Ireland P.D.C are supported by a SFI PI award (Grant number 11/PI/1137)

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A novel configuration model for random graphs with given degree sequence

Recently, random graphs in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices have attracted much attention. Here, we present a specific realization of a class of random network models in which the connection probability between two vertices (i,j) is a specific function of degrees ki and kj. In the framework of the configuration model of random graphs, we find analytical expressions for the degree correlation and clustering as a function of the variance of the desired degree distribution. The expressions obtained are checked by means of numerical simulations. Possible applications of our model are discussed.Comment: 7 pages, 3 figure

Percolation in invariant Poisson graphs with i.i.d. degrees

Let each point of a homogeneous Poisson process in R^d independently be equipped with a random number of stubs (half-edges) according to a given probability distribution mu on the positive integers. We consider translation-invariant schemes for perfectly matching the stubs to obtain a simple graph with degree distribution mu. Leaving aside degenerate cases, we prove that for any mu there exist schemes that give only finite components as well as schemes that give infinite components. For a particular matching scheme that is a natural extension of Gale-Shapley stable marriage, we give sufficient conditions on mu for the absence and presence of infinite components

Giant strongly connected component of directed networks

We describe how to calculate the sizes of all giant connected components of a directed graph, including the {\em strongly} connected one. Just to the class of directed networks, in particular, belongs the World Wide Web. The results are obtained for graphs with statistically uncorrelated vertices and an arbitrary joint in,out-degree distribution $P(k_i,k_o)$. We show that if $P(k_i,k_o)$ does not factorize, the relative size of the giant strongly connected component deviates from the product of the relative sizes of the giant in- and out-components. The calculations of the relative sizes of all the giant components are demonstrated using the simplest examples. We explain that the giant strongly connected component may be less resilient to random damage than the giant weakly connected one.Comment: 4 pages revtex, 4 figure

Dynamical Scaling Behavior of Percolation Clusters in Scale-free Networks

In this work we investigate the spectra of Laplacian matrices that determine many dynamic properties of scale-free networks below and at the percolation threshold. We use a replica formalism to develop analytically, based on an integral equation, a systematic way to determine the ensemble averaged eigenvalue spectrum for a general type of tree-like networks. Close to the percolation threshold we find characteristic scaling functions for the density of states rho(lambda) of scale-free networks. rho(lambda) shows characteristic power laws rho(lambda) ~ lambda^alpha_1 or rho(lambda) ~ lambda^alpha_2 for small lambda, where alpha_1 holds below and alpha_2 at the percolation threshold. In the range where the spectra are accessible from a numerical diagonalization procedure the two methods lead to very similar results.Comment: 9 pages, 6 figure

Random Networks Tossing Biased Coins

In statistical mechanical investigations on complex networks, it is useful to employ random graphs ensembles as null models, to compare with experimental realizations. Motivated by transcription networks, we present here a simple way to generate an ensemble of random directed graphs with, asymptotically, scale-free outdegree and compact indegree. Entries in each row of the adjacency matrix are set to be zero or one according to the toss of a biased coin, with a chosen probability distribution for the biases. This defines a quick and simple algorithm, which yields good results already for graphs of size n ~ 100. Perhaps more importantly, many of the relevant observables are accessible analytically, improving upon previous estimates for similar graphs

Great South Bay, Long Island, New York Summer Phytoplankton Identification & Monitoring Program

Phytoplankton Collection Methodologies: 80 micron Plankton Tow Net with sample bottle attachment Phytoplankton Protocol: 1.Gather Samples 2.Make one slide per sample 3.View slides using microscope connected with computer 4. Record findings using “ Row # “ and “ Colum letter “ 5. Record using “ Tally’s “ per species found within sample 6. Capture anything interesting “ Take Picture “ 7.Duplicate pictures taken 8.Make sure measurement of species found is take