Marquette University Slavic Institute Paper NO. 12

https://epublications.marquette.edu/mupress-book/1005/thumbnail.jp

Assessing the phylogeographic history of the montane caddisfly Thremma gallicum using mitochondrial and restriction-site-associated DNA (RAD) mar

Repeated Quaternary glaciations have significantly shaped the present distribution and diversity of several European species in aquatic and terrestrial habitats. To study the phylogeography of freshwater invertebrates, patterns of intraspecific variation have been examined primarily using mitochondrial DNA markers that may yield results unrepresentative of the true species history. Here, population genetic parameters were inferred for a montane aquatic caddisfly, Thremma gallicum, by sequencing a 658-bp fragment of the mitochondrial CO1 gene, and 12,514 nuclear RAD loci. T. gallicum has a highly disjunct distribution in southern and central Europe, with known populations in the Cantabrian Mountains, Pyrenees, Massif Central, and Black Forest. Both datasets represented rangewide sampling of T. gallicum. For the CO1 dataset, this included 352 specimens from 26 populations, and for the RAD dataset, 17 specimens from eight populations. We tested 20 competing phylogeographic scenarios using approximate Bayesian computation (ABC) and estimated genetic diversity patterns. Support for phylogeographic scenarios and diversity estimates differed between datasets with the RAD data favouring a southern origin of extant populations and indicating the Cantabrian Mountains and Massif Central populations to represent highly diverse populations as compared with the Pyrenees and Black Forest populations. The CO1 data supported a vicariance scenario (north–south) and yielded inconsistent diversity estimates. Permutation tests suggest that a few hundred polymorphic RAD SNPs are necessary for reliable parameter estimates. Our results highlight the potential of RAD and ABC-based hypothesis testing to complement phylogeographic studies on non-model species

Constraining Disk Parameters of Be Stars using Narrowband H-alpha Interferometry with the NPOI

Interferometric observations of two well-known Be stars, gamma Cas and phi Per, were collected and analyzed to determine the spatial characteristics of their circumstellar regions. The observations were obtained using the Navy Prototype Optical Interferometer equipped with custom-made narrowband filters. The filters isolate the H-alpha emission line from the nearby continuum radiation, which results in an increased contrast between the interferometric signature due to the H-alpha-emitting circumstellar region and the central star. Because the narrowband filters do not significantly attenuate the continuum radiation at wavelengths 50 nm or more away from the line, the interferometric signal in the H-alpha channel is calibrated with respect to the continuum channels. The observations used in this study represent the highest spatial resolution measurements of the H-alpha-emitting regions of Be stars obtained to date. These observations allow us to demonstrate for the first time that the intensity distribution in the circumstellar region of a Be star cannot be represented by uniform disk or ring-like structures, whereas a Gaussian intensity distribution appears to be fully consistent with our observations.Comment: 23 pages, 14 figures, accepted for publication in A

Disentangling the Cosmic Web I: Morphology of Isodensity Contours

We apply Minkowski functionals and various derived measures to decipher the morphological properties of large-scale structure seen in simulations of gravitational evolution. Minkowski functionals of isodensity contours serve as tools to test global properties of the density field. Furthermore, we identify coherent objects at various threshold levels and calculate their partial Minkowski functionals. We propose a set of two derived dimensionless quantities, planarity and filamentarity, which reduce the morphological information in a simple and intuitive way. Several simulations of the gravitational evolution of initial power-law spectra provide a framework for systematic tests of our method.Comment: 26 pages including 12 figures. Accepted for publication in Ap

The Ellipticity and Orientation of Clusters of Galaxies from N-Body Experiments

In this study we use simulations of 128$^3$ particles to study the ellipticity and orientation of clusters of galaxies in N-body simulations of differing power-law initial spectra (P(k) \propto k^n ,n = +1, 0, -1, -2$), and density parameters ($\Omega_0 = 0.2$to 1.0). Furthermore, unlike most theoretical studies we mimic most observers by removing all particles which lie at distances greater than 2 1/h Mpc from the cluster center of mass. We computed the axial ratio and the principal axes using the inertia tensor of each cluster. The mean ellipticity of clusters increases strongly with increasing$n$. We also find that clusters tend to become more spherical at smaller radii. We compared the orientation of a cluster to the orientation of neighboring clusters as a function of distance (correlation). In addition, we considered whether a cluster's major axis tends to lie along the line connecting it to a neighboring cluster, as a function of distance (alignment). Both alignments and correlations were computed in three dimensions and in projection to mimic observational surveys. Our results show that significant alignments exist for all spectra at small separations ($D < 15 h^{-1}$Mpc) but drops off at larger distance in a strongly$n-$dependent way.Comment: 22 pages, requires aaspp4.sty, flushrt.sty, and epsf.sty Revised manuscript, accepted for publication in Ap

The Role of Dopamine in Drosophila Larval Classical Olfactory Conditioning

Learning and memory is not an attribute of higher animals. Even Drosophila larvae are able to form and recall an association of a given odor with an aversive or appetitive gustatory reinforcer. As the Drosophila larva has turned into a particularly simple model for studying odor processing, a detailed neuronal and functional map of the olfactory pathway is available up to the third order neurons in the mushroom bodies. At this point, a convergence of olfactory processing and gustatory reinforcement is suggested to underlie associative memory formation. The dopaminergic system was shown to be involved in mammalian and insect olfactory conditioning. To analyze the anatomy and function of the larval dopaminergic system, we first characterize dopaminergic neurons immunohistochemically up to the single cell level and subsequent test for the effects of distortions in the dopamine system upon aversive (odor-salt) as well as appetitive (odor-sugar) associative learning. Single cell analysis suggests that dopaminergic neurons do not directly connect gustatory input in the larval suboesophageal ganglion to olfactory information in the mushroom bodies. However, a number of dopaminergic neurons innervate different regions of the brain, including protocerebra, mushroom bodies and suboesophageal ganglion. We found that dopamine receptors are highly enriched in the mushroom bodies and that aversive and appetitive olfactory learning is strongly impaired in dopamine receptor mutants. Genetically interfering with dopaminergic signaling supports this finding, although our data do not exclude on naïve odor and sugar preferences of the larvae. Our data suggest that dopaminergic neurons provide input to different brain regions including protocerebra, suboesophageal ganglion and mushroom bodies by more than one route. We therefore propose that different types of dopaminergic neurons might be involved in different types of signaling necessary for aversive and appetitive olfactory memory formation respectively, or for the retrieval of these memory traces. Future studies of the dopaminergic system need to take into account such cellular dissociations in function in order to be meaningful

Image reconstruction in optical interferometry: Benchmarking the regularization

With the advent of infrared long-baseline interferometers with more than two telescopes, both the size and the completeness of interferometric data sets have significantly increased, allowing images based on models with no a priori assumptions to be reconstructed. Our main objective is to analyze the multiple parameters of the image reconstruction process with particular attention to the regularization term and the study of their behavior in different situations. The secondary goal is to derive practical rules for the users. Using the Multi-aperture image Reconstruction Algorithm (MiRA), we performed multiple systematic tests, analyzing 11 regularization terms commonly used. The tests are made on different astrophysical objects, different (u,v) plane coverages and several signal-to-noise ratios to determine the minimal configuration needed to reconstruct an image. We establish a methodology and we introduce the mean-square errors (MSE) to discuss the results. From the ~24000 simulations performed for the benchmarking of image reconstruction with MiRA, we are able to classify the different regularizations in the context of the observations. We find typical values of the regularization weight. A minimal (u,v) coverage is required to reconstruct an acceptable image, whereas no limits are found for the studied values of the signal-to-noise ratio. We also show that super-resolution can be achieved with increasing performance with the (u,v) coverage filling. Using image reconstruction with a sufficient (u,v) coverage is shown to be reliable. The choice of the main parameters of the reconstruction is tightly constrained. We recommend that efforts to develop interferometric infrastructures should first concentrate on the number of telescopes to combine, and secondly on improving the accuracy and sensitivity of the arrays.Comment: 15 pages, 16 figures; accepted in A&

Electric Shock-Induced Associative Olfactory Learning in Drosophila Larvae

Associative plasticity is a basic essential attribute of nervous systems. As shown by numerous reports, Drosophila is able to establish simple forms of appetitive and aversive olfactory associations at both larval and adult stages. Whereas most adult studies on aversive learning employed electric shock as a negative reinforcer, larval paradigms essentially utilized gustatory stimuli to create negative associations, a discrepancy that limits the comparison of data. To overcome this drawback, we critically revisited larval odor-electric shock conditioning. First, we show that lithium chloride (LiCl), which was used in all previous larval electric shock paradigms, is not required per se in larval odor-electric shock learning. This is of considerable practical advantage because beside its peculiar effects LiCl is attractive to larvae at low concentration that renders comparative learning studies on genetically manipulated larvae complicated. Second, we confirm that in both a 2-odor reciprocal and a 1-odor nonreciprocal conditioning regimen, larvae are able to associate an odor with electric shock. In the latter experiments, initial learning scores reach an asymptote after 5 training trials, and aversive memory is still detectable after 60 min. Our experiments provide a comprehensive basis for future comparisons of larval olfactory conditioning reinforced by different modalities, for studies aimed at analyzing odor-electric shock learning in the larva and the adult, and for investigations of the cellular and molecular substrate of aversive olfactory learning in the simple Drosophila mode

CT imaging of ascaris lumbricoides

A 37-year-old man was referred to the department of internal medicine for chronic fever, asthenia and loss of weight. He had no relevant medical history but reported frequent travels to Africa. Abdominal-CT study with contrast agent injection and oral digestive opacification was performed and revealed pleuroperitoneal and pericardial effusions with multiple mediastinal and mesenteric lymphadenopathies. Bronchoalveolar lavage and sputum expectoration analyses demonstrated systemic tuberculosis

A measure of centrality based on the spectrum of the Laplacian

We introduce a family of new centralities, the k-spectral centralities. k-Spectral centrality is a measurement of importance with respect to the deformation of the graph Laplacian associated with the graph. Due to this connection, k-spectral centralities have various interpretations in terms of spectrally determined information. We explore this centrality in the context of several examples. While for sparse unweighted networks 1-spectral centrality behaves similarly to other standard centralities, for dense weighted networks they show different properties. In summary, the k-spectral centralities provide a novel and useful measurement of relevance (for single network elements as well as whole subnetworks) distinct from other known measures.Comment: 12 pages, 6 figures, 2 table