All That Sprawl, Y’all: An Analysis of Development on Steinwehr Avenue and York Street in Gettysburg, Pennsylvania, from 1971 to 2014

The advent of the automobile transformed the American landscape in the 20th century. In conjunction with the increasing importance of the automobile, numerous post-WW II government programs such as the Interstate Highway System encouraged suburban sprawl. Towns and cities adjacent to tourist attractions, known as gateway communities, face unique problems caused by sprawl. Gettysburg, Pennsylvania, is an example of a gateway community as it includes the Gettysburg National Military Park. Two study sites, portions of Steinwehr Avenue and York Street, were studied to analyze the effects of sprawl in Gettysburg. The sites were analyzed using ArcGIS, data compiled from historic phonebooks, and discussions with local business owners. Development along York Street exemplifies an auto-centric culture with many regional and national chain establishments set back from the road. Steinwehr Avenue represents a walkable community comprising on-street parking, sidewalks, and local “mom-and-pop” establishments. Trends associated with categories of businesses varied between the two sites and revealed different development patterns. We predict that that York Street will continue to sprawl while Steinwehr Avenue development will be limited due to its close proximity to the battlefield

A Discriminant Analysis Model of Alaskan Biomes Based on Spatial Climatic and Environmental Data

Classification of high-latitude landscapes into their appropriate biomes is important for many climate and global change-related issues. Unfortunately, large-scale, high-spatial-resolution observations of plant assemblages associated with these regions are generally unavailable, so accurate modeling of plant assemblages and biome boundaries is often needed. We built different discriminant analysis models and used them to “convert” various combinations of spatial climatic data (surface temperature and precipitation) and spatial environmental data (topography, soil, permafrost) into a biome-level map of Alaska. Five biomes (alpine tundra and ice fi elds, Arctic tundra, shrublands, boreal forest, and coastal rainforest) and one biome transition zone are modeled. Mean annual values of climatic variables were less useful than their annual extrema in this context. A quadratic discriminant analysis, combined with climate, topography, permafrost, and soil information, produced the most accurate Alaskan biome classification (skill = 74% when compared to independent data). The multivariate alteration detection transformation was used to identify Climatic Transition Zones (CTZs) with large interannual variability, and hence, less climatic consistency than other parts of Alaska. Biome classification was the least accurate in the CTZs, leading to the conclusion that large interannual climatic variability does not favor a unique biome. We interpret the CTZs as “transition biome areas” or ecotones between the five “core biomes” cited above. Both disturbance events (e.g., fires and subsequent plant succession sequences) and the partial intersection of the environmental variables used to characterize Alaskan biomes further complicate biome classification. Alaskan results obtained from the data-driven quadratic discriminant model compare favorably (based on Kappa statistics) with those produced by an equilibrium-based biome model for regions of Canada ecologically similar to the biomes we studied in Alaska. Climatic statistics are provided for each biome studied. Le classement des paysages de hautes latitudes dans les biomes adéquats revêt de l'importance dans le cadre de nombreux enjeux relatifs aux changements climatiques et à d'autres changements d'envergure mondiale. Malheureusement et en règle générale, il n'existe pas d'observations spatiales de haute résolution et à grande échelle pour ce qui est des assemblages de végétaux pour ces régions. C'est pourquoi il faut souvent procéder à la modélisation des assemblages de végétaux et des limites des biomes. Nous avons élaboré différents modèles d'analyses discriminantes dont nous nous sommes servis pour « transformer » divers ensembles de données climatiques spatiales (température de la surface et précipitation) et diverses données sur l'environnement spatial (topographie, sol, pergélisol) en carte des biomes de l'Alaska. La modélisation porte sur cinq biomes (toundra alpine et champs de glace, toundra arctique, arbustaie, forêt boréale et forêt pluviale côtière) et sur une zone de transition de biome. Les valeurs moyennes annuelles des variables climatiques ont été moins utiles que leurs extremas annuels dans ce contexte. Une analyse discriminante quadratique, combinée aux données relatives au climat, à la topographie, au pergélisol et au sol, a permis d'aboutir au classement de biomes alaskiens le plus précis (habileté = 74 % lorsque comparé aux données indépendantes). Nous avons recouru à la transformation de la détection de l'altération à variables multiples (multivariate alteration detection transformation) pour identifi er les zones de transition climatique (ZTC) ayant une importante variabilité interannuelle et, par conséquent, une moins grande uniformité climatique que d'autres parties de l'Alaska. Le classement des biomes était moins précis dans les ZTC, ce qui nous a amenés à conclure que l'importante variabilité climatique interannuelle ne favorise pas un biome unique. Nous interprétons les ZTC comme des « régions de biomes de transition » ou des écotones entre les cinq « biomes principaux » dont il est question ci-dessus. Les deux perturbations (c'est-à-dire les incendies et les séquences subséquentes des végétaux) et l'intersection partielle des variables environnementales utilisées pour caractériser les biomes alaskiens compliquent davantage le classement des biomes. Les résultats alaskiens obtenus à partir du modèle discriminant quadratique dérivant des données se comparent favorablement (en fonction des statistiques kappa) à ceux obtenus par un modèle de biome en équilibre pour des régions du Canada similaires du point de vue écologique aux biomes que nous avons étudiés en Alaska. Des statistiques climatiques sont fournies pour chaque biome étudié

Model-independent determination of the cosmic expansion rate. I. Application to type-Ia supernovae

Aims: In view of the substantial uncertainties regarding the possible dynamics of the dark energy, we aim at constraining the expansion rate of the universe without reference to a specific Friedmann model and its parameters. Methods: We show that cosmological observables integrating over the cosmic expansion rate can be converted into a Volterra integral equation which is known to have a unique solution in terms of a Neumann series. Expanding observables such as the luminosity distances to type-Ia supernovae into a series of orthonormal functions, the integral equation can be solved and the cosmic expansion rate recovered within the limits allowed by the accuracy of the data. Results: We demonstrate the performance of the method applying it to synthetic data sets of increasing complexity, and to the first-year SNLS data. In particular, we show that the method is capable of reproducing a hypothetical expansion function containing a sudden transition.Comment: 9 pages, 8 figures; accepted by A&A; subsection 3.6 added, new references and minor change

The evaluation of tuyere coke probing data at Bluescope Steel Port Kembla Works

Tuyere coke probings have been conducted at Port Kembla over the past decade. This period of operation spans significant change in coking coal preparation as well as the introduction of pulverised coal injection

Measures that can be used to teach critical thinking skills in nurse prescribers

Critical thinking is a pervasive skill that involves scrutinizing, differentiating, and appraising information and reflecting on the information gained in order to make judgements and inform clinical decisions. Studies inform us of the need for agreement on the approaches used to teach and measure critical thinking. Nurse prescribers undertake an advanced role that encompass the need to be able to make clinically based decisions about the appropriateness of a specific medication. This requires critical thinking attributes. A variety of teaching and learning approaches are offered which can be used by nurse educators to develop critical thinking skills in nurse prescribers

Comparing Maps of Mean Monthly Surface Temperature and Precipitation for Alaska and Adjacent Areas of Canada Produced by Two Different Methods

Maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada, produced by Oregon State University’s Spatial Climate Analysis Service (SCAS) and the Alaska Geospatial Data Clearinghouse (AGDC), were analyzed. Because both sets of maps are generally available and in use by the community, there is a need to document differences between the processes and input data sets used by the two groups to produce their respective set of maps and to identify similarities and differences between the two sets of maps and possible reasons for the differences. These differences do not affect the observed large-scale patterns of seasonal and annual variability. Alaska is divided into interior and coastal zones, with consistent but different variability, separated by a transition region. The transition region has high interannual variability but low long-term mean variability. Both data sets support the four major ecosystems and ecosystem transition zone identified in our earlier work. Differences between the two sets of maps do occur, however, on the regional scale; they reflect differences in physiographic domains and in the treatment of these domains by the two groups (AGDC, SCAS). These differences also provide guidance for an improved observational network for Alaska. On the basis of validation with independent in situ data, we conclude that the data set produced by SCAS provides the best spatial coverage of Alaskan long-term mean monthly surface temperature and precipitation currently available.On a analysé des cartes représentant les moyennes mensuelles des précipitations et des températures de l’air en surface pour l’Alaska et les zones contiguës du Canada. Ces cartes avaient été établies par le service d’analyse du climat spatial (SCAS) de l’université de l’Oregon et le centre d’échange de données géospatiales de l’Alaska (AGDC). Vu qu’en général le public peut se procurer les deux ensembles de cartes et qu’il les utilise, il est nécessaire de documenter les différences entre les processus et les jeux de données d’entrée utilisés par les deux groupes pour créer leur propre ensemble de cartes, ainsi que de dégager les similarités et les différences entre les deux ensembles de cartes et les raisons possibles de ces différences. Ces dernières n’affectent pas les schémas de variabilité saisonnière et annuelle observés à grande échelle. L’Alaska est divisé en zones intérieures et zones côtières, possédant une variabilité constante mais différente, séparées par une région de transition. Celle-ci possède une grande variabilité interannuelle mais une faible variabilité à long terme de la moyenne. Les deux jeux de données sont compatibles avec les quatre grands écosystèmes et leurs zones de transition que nous avions identifiés dans nos travaux antérieurs. Il y a cependant des différences à l’échelle régionale entre les deux ensembles de cartes; elles témoignent de différences dans les domaines physiographiques et dans le traitement que font les deux groupes (AGDC et SCAS) de ces domaines. Ces différences offrent également une piste pour l’établissement d’un réseau d’observation amélioré pour l’Alaska. En nous basant sur une validation fondée sur des données indépendantes recueillies in situ, nous concluons que le jeu de données produit par SCAS représente actuellement la meilleure couverture spatiale disponible pour les moyennes mensuelles à long terme des précipitations et des températures de l’air en surface en Alaska

Breaking parameter degeneracy in interacting dark energy models from observations

We study the interacting dark energy model with time varying dark energy equation of state. We examine the stability in the perturbation formalism and the degeneracy among the coupling between dark sectors, the time-dependent dark energy equation of state and dark matter abundance in the cosmic microwave background radiation. Further we discuss the possible ways to break such degeneracy by doing global fitting using the latest observational data and we get a tight constraint on the interaction between dark sectors.Comment: 8 pages, 6 figures, accepted for publication in Phys.Lett.

Diversity and impact of rare variants in genes encoding the platelet G protein-coupled receptors

Platelet responses to activating agonists are influenced by common population variants within or near G protein-coupled receptor (GPCR) genes that affect receptor activity. However, the impact of rare GPCR gene variants is unknown. We describe the rare single nucleotide variants (SNVs) in the coding and splice regions of 18 GPCR genes in 7,595 exomes from the 1,000-genomes and Exome Sequencing Project databases and in 31 cases with inherited platelet function disorders (IPFDs). In the population databases, the GPCR gene target regions contained 740 SNVs (318 synonymous, 410 missense, 7 stop gain and 6 splice region) of which 70 % had global minor allele frequency (MAF) < 0.05 %. Functional annotation using six computational algorithms, experimental evidence and structural data identified 156/740 (21 %) SNVs as potentially damaging to GPCR function, most commonly in regions encoding the transmembrane and C-terminal intracellular receptor domains. In 31 index cases with IPFDs (Gi-pathway defect n=15; secretion defect n=11; thromboxane pathway defect n=3 and complex defect n=2) there were 256 SNVs in the target regions of 15 stimulatory platelet GPCRs (34 unique; 12 with MAF< 1 % and 22 with MAF≥ 1 %). These included rare variants predicting R122H, P258T and V207A substitutions in the P2Y12 receptor that were annotated as potentially damaging, but only partially explained the platelet function defects in each case. Our data highlight that potentially damaging variants in platelet GPCR genes have low individual frequencies, but are collectively abundant in the population. Potentially damaging variants are also present in pedigrees with IPFDs and may contribute to complex laboratory phenotypes

Young stars and non-stellar emission in the aligned radio galaxy 3C 256

We present ground-based images of the z=1.824 radio galaxy 3C 256 in the standard BVRIJHK filters and an interference filter centered at 8800A, a Hubble Space Telescope image in a filter dominated by Ly-alpha emission (F336W), and spectra covering rest-frame wavelengths from Ly-alpha to [O III] 5007. Together with published polarimetry observations, we use these to decompose the overall spectral energy distribution into nebular continuum emission, scattered quasar light, and stellar emission. The nebular continuum and scattered light together comprise half (one third) of the V-band (K-band) light within a 4-arcsec aperture, and are responsible for the strong alignment between the optical/near-infrared light and the radio emission. The stellar emission is dominated by a population estimated to be 100-200 Myr old (assuming a Salpeter IMF), and formed in a short burst with a peak star formation rate of 1-4x10^3 Msun/yr. The total stellar mass is estimated to be no more than 2x10^{11} Msun, which is far less than other luminous radio galaxies at similar redshifts, and suggests that 3C 256 will undergo further star formation or mergers.Comment: 35 pages including 10 figures; to appear in Nov 10 Ap

Longitudinal flow evolution and turbulence structure of dynamically similar, sustained, saline density and turbidity currents

Experimental results are presented concerning flow evolution and turbulence structure of sustained saline and turbidity flows generated on 0°, 3°, 6°, and 9° sloping ramps that terminate abruptly onto a horizontal floor. Two-component velocity and current density were measured with an ultrasonic Doppler velocity profiler and siphon sampler on the slope, just beyond the slope break and downstream on the horizontal floor. Three main factors influence longitudinal flow evolution and turbulence structure: sediment transport and sedimentation, slope angle, and the presence of a slope break. These controls interact differently depending on flow type. Sediment transport is accompanied by an inertial fluid reaction that enhances Reynolds stresses in turbidity flows. Thus turbidity flows mix more vigorously than equivalent saline density flows. For saline flows, turbulent kinetic energy is dependent on slope, and rapid deceleration occurs on the horizontal floor. For turbidity flows, normalized turbulent kinetic energy increases downstream, and mean streamwise deceleration is reduced compared with saline flows. The slope break causes mean bed-normal velocity of turbidity flows to become negative and have a gentler gradient compared with other locations. A reduction of peak Reynolds normal stress in the bed-normal direction is accompanied by an increase in turbulent accelerations across the rest of the flow thickness. Thus the presence of particles acts to increase Reynolds normal stresses independently of gradients of mean velocity, and sediment transport increases across the break in slope. The experiments illustrate that saline density currents may not be good dynamic analogues for natural turbidity currents