25 research outputs found
TINITALY/01: a new Triangular Irregular Network of Italy
A new Digital Elevation Model (DEM) of the natural landforms of Italy is presented. A methodology is discussed to
build a DEM over wide areas where elevation data from non-homogeneous (in density and accuracy) input sources
are available. The input elevation data include contour lines and spot heights derived from the Italian Regional topographic
maps, satellite-based global positioning system points, ground based and radar altimetry data. Owing to the
great heterogeneity of the input data density, the DEM format that better preserves the original accuracy is a Triangular
Irregular Network (TIN). A Delaunay-based TIN structure is improved by using the DEST algorithm that enhances
input data by evaluating inferred break-lines. Accordingly to this approach, biased distributions in slopes and
elevations are absent. To prevent discontinuities at the boundary between regions characterized by data with different
resolution a cubic Hermite blending weight S-shaped function is adopted. The TIN of Italy consists of 1.39×109
triangles. The average triangle area ranges from 12 to about 13000 m2 accordingly to different morphologies and different
sources. About 50% of the model has a local average triangle area <500 m2. The vertical accuracy of the obtained
DEM is evaluated by more than 200000 sparse control points. The overall Root Mean Square Error (RMSE)
is less than 3.5 m. The obtained national-scale DEM constitutes an useful support to carry out accurate geomorphological
and geological investigations over large areas. The problem of choosing the best step size in deriving a grid
from a TIN is then discussed and a method to quantify the loss of vertical information is presented as a function of
the grid step. Some examples of DEM application are outlined. Under request, an high resolution stereo image database
of the whole Italian territory (derived from the presented DEM) is available to browse via internet
MOESM3 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 3: Table S2. Posterior mean number of SNPs in each distribution [0, 0.0001, 0.001 or 0.01 of the pedigree estimated genetic variance], data from Kemper et al. [1]
MOESM5 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 5: Table S4. This file contains highly significant SNPs (P < 1 × 10−6) from the mixed model analysis of the milk minerals and proteins
MOESM1 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 1: Table S1. Phenotypic and genetic correlation between milk yield traits, with trait heritability from the pedigree-based multi-trait model
MOESM2 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 2: Figure S1. Mean power and false-discovery rate for QTL discovery in simulated data for a single trait
MOESM6 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 6: Figure S2. Mean posterior probability for BayesMV and BayesR, and the âlog10(P) association test statistic between SNP and potassium concentration on bovine chromosome 19 near KCNJ2
MOESM8 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 8: Figure S3. Genetic relationship between nine dairy and beef cattle breeds
MOESM4 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 4: Table S3. Top 100 SNPs with the highest mean posterior probability (PP) for inclusion in the model from the Holstein/Jersey reference population using BayesMV [39â41]
MOESM7 of A multi-trait Bayesian method for mapping QTL and genomic prediction
Additional file 7: Table S5. Genomic prediction accuracy and bias from the univariate GBLUP model, data from Kemper et al. [1]
Between Prague and Vienna. Hermann Bahr and J.S. Machar and the spaces of (Central) European Modernism
This thesis deals with the relations between Czech and Viennese literary modernism during the 1890s, key amongst which were the contacts between Hermann Bahr and J. S. Machar. The contextual underpinnings, nature and significance of these relations are analysed in two monograph chapters. Chapter One focuses on the formation and transformation of Bahr's modernist programme as it moved between Berlin, Paris and Vienna, and an analysis is made of the programme keywords (Nervenkunst, Nervenromantik, Überwindung des Naturalismus, die Moderne, das gute Europäertum, Entdeckung der Provinz), which from the early 1890s found a response among Czech critics (e. g. F. Zákrejs, J. S. Machar and F. V. Krejčí). Bahr's conception of Viennese modernism and Austrian culture and the programme of the Die Zeit review were substantially influenced by Parisian experiences of the plurality of artistic production. Chapter Two follows developments in the work of J. S. Machar after he moved from Prague to Vienna in 1889. Machar's experience in Vienna is analysed in texts of various genres (lyric poetry, correspondence, autobiography, polemics and essay writing) and on the basis of his varying literary and intellectual contacts, while attention is paid in particular to his relationship with Jaroslav Vrchlický and T. G. Masaryk. A..