Liquefaction Potential Determination and Hazard Mapping Based on Standard Penetration Tests in Long Beach and Tuzla Regions of Cyprus

This study proposes an improved and precise liquefaction risk index for the evaluation and translation of outcomes into maps to establish susceptible liquefiable areas. Cyprus is the third largest and populated island in the Mediterranean Sea, which is rapidly expanding in every way. Significant infrastructures, such as hotels, educational institutions, and large residential complexes are being built. Historically, two major earthquakes with magnitudes of 6.5 Mw struck the island in 1953 and 1996. Potential liquefaction areas have been detected on the island's east coast as a result of these significant earthquakes. In this case study, the liquefaction potential of Tuzla and Long Beach in the northern part of Cyprus is estimated using the standard penetration test (SPT) data from more than 200 boreholes at different locations at the sites. The overall results are presented in a liquefaction risk index obtained from the factor of safety (FS) coefficient. It is clear that both study areas are susceptible to liquefaction. Thus, risk index maps are prepared to identify susceptible liquefiable areas. In addition, the average factor of the safety line was introduced for both sites to create a correlation between the liquefaction risk area and FS values of every borehole. It is clear that the adopted approach precisely provides the suspected depth of the liquefiable soil layer when compared with the risk index maps. Additionally, the results prove that the liquefaction potential must be considered during the design stage of new infrastructure in these areas.

Prediction of Cracking Susceptibility of Commercial Aluminum Alloys during Solidification

Cracking during solidification is a complex phenomenon which has been investigated from various angles for decades using both experimental and theoretical methods. In this paper, cracking susceptibility was investigated by a simulation method for three series of aluminum alloys: AA2xxx, AA6xxx, and AA7xxx alloys. The simulation tool was developed using the CALPHAD method and is readily applicable to multicomponent alloy systems. For each series of alloys, cracking susceptible index values were calculated for more than 1000 alloy compositions by high-throughput calculation. Cracking susceptible maps were then constructed for these three series of aluminum alloys using the simulated results. The effects of major and minor alloying elements were clearly demonstrated by these index maps. The cooling rate effect was also studied, and it was concluded that back diffusion in the solid can significantly improve the cracking susceptibility.

Narrow-Line Seyfert 1 Galaxies With Absorbed Jets–Insights From Radio Spectral Index Maps

Narrow-line Seyfert 1 (NLS1) galaxies are active galactic nuclei (AGN) believed to be in the early stages of their evolution. A fraction of them have been found to host relativistic jets. Due to the lack of large-scale diffuse radio emission they are believed to be experiencing one of their first activity cycles, and can offer us an opportunity to study the early evolution of more powerful AGN, such as radio galaxies and flat-spectrum radio quasars. Recently, a group of intriguing jetted NLS1s was discovered: based on high radio frequency data they host relativistic jets, but in the JVLA observations they all showed steep radio spectra at least up to 9.0 GHz, indicating very strong absorption at these frequencies. In this paper we study a subset of these sources in detail by employing spatially resolved radio spectral index maps at central frequencies of 1.6, 5.2, and 9.0 GHz. With spectral index maps we can disentangle the different radio emission components over the radio-emitting region, and get insights into the production mechanisms of radio emission. In addition, we study their host galaxies in relation to the radio emission to investigate if the host can provide us additional information regarding the origin of the radio emission, or the launching mechanism of the jets. It is fascinating how different the sources studied are, and certainly more, especially wide frequency-range, and high-resolution observations will be needed to understand their history and current properties, such as the reason behind the extraordinary radio spectra.

Simplified intravoxel incoherent motion diffusion-weighted MRI of liver lesions: feasibility of combined two-colour index maps

Background To evaluate the feasibility of two-colour index maps containing combined diffusion and perfusion information from simplified intravoxel incoherent motion (IVIM) for liver lesion malignancy assessment. Methods Diffusion-weighted data from a respiratory-gated 1.5-T magnetic resonance sequence were analysed in 109 patients with liver lesions. With three b values (0, 50, 800 s/mm2) estimated diffusion coefficient D′, perfusion fraction f′, and apparent diffusion coefficient (ADC) maps were calculated and analysed for regions of interest (ROIs). D′ and f′ cutoff values were determined by differentiating haemangiomas from other lesions and focal nodular hyperplasias from other lesions, respectively. Combined IDf index maps were generated with a voxel value set to 100, if both D′ and f′ voxel values were lower than their cutoff values (1,529.4 × 10-6 mm2/s and 114.4 × 10-3, respectively), otherwise to 0. Moreover, IADC index maps were generated from ADC cutoff value (1,338.5 × 10-6 mm2/s) obtained by differentiating benign from malignant lesions. Discriminatory power was assessed for both IDf and IADC. Index maps were displayed as two-colour overlays to b-800 images and visually assessed within the translucent hyperintense areas. Results For IDf, the same diagnostic accuracy was achieved as for the combined use of parameters D′ and f′ (93.6%). Compared to IADC, IDf showed a higher diagnostic accuracy. Visual judgment of IDf yielded an accuracy (95.4%) similar to that of quantitative analysis (93.6%). Conclusion Voxel-wise combined two-colour index maps IDf provide similar diagnostic accuracy as ROI-based combination of estimated IVIM parameters D′ and f′ and are suitable for visual assessment of liver lesion malignancy.

Prognostic Ozone for ICON: Enabling UV Forecasts

<p>Stratospheric Ozone (O<sub>3</sub>) absorbs biologically harmful solar ultraviolet radiation (most of the UV‑B radiation) and keeps it from reaching the surface. Such UV radiation is destructive of genetic cellular material in plants and animals, as well as human beings. Without the ozone layer, life on the surface of the Earth would not be possible as we know it.</p><p>As part of its work the German Weather Service (DWD) provides UV index maps to warn the population in Germany of excessive UV exposure <sup>[[1]]</sup>. For this purpose, global ICON data, external ozone data and an external UV model is used.</p><p>This study aims to create a self-consistent framework to generate UV index maps entirely from the non-hydrostatic global modelling system ICON <sup>[[2]]</sup>. For this purpose, a linearized ozone scheme (LINOZ) <sup>[[3]] </sup>will be optimized and the forecast functionality of ICON-ART <sup>[[4]][[5]]</sup> (ICOsahedral Non-hydrostatic – Aerosols and Reactive Trace gases) will be extended. For the derivation of UV radiation fluxes and indices a radiative transfer model for solar radiation (Cloud-J) <sup>[[6]]</sup> shall be implemented and extended. Since the entire framework is to be used at the DWD during ongoing operations, a functionality with very low computational effort is required.  </p><p>Here we present the first results of the UV radiation flux through the atmosphere and its diurnal variation. Furthermore, the influence of clouds on the UV radiation flux is considered.</p><div><br><div> <p><sup>[[1]]</sup> https://kunden.dwd.de/uvi/index.jsp</p> </div> <div> <p><sup>[[2]]</sup> Zängl, G., et al. (2014), The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD MPI-M: Description of the non-hydrostatic dynamical core. Q.J.R. Meteorol. Soc., doi:10.1002/qj.2378</p> </div> <div> <p><sup>[[3]]</sup> McLinden, C. A., et al. (2000), Stratospheric ozone in 3-D models: A simple chemistry and the cross-tropopause flux, Journal of Geophysical Research: Atmospheres, doi:10.1029/2000JD900124</p> </div> <div> <p><sup>[[4]]</sup> Rieger, D., et al. (2015), ICON-ART - A new online-coupled model system from the global to regional scale, Geosci. Model Dev., doi:10.5194/gmd-8-1659-2015</p> </div> <div> <p><sup>[[5]]</sup> Schröter, et al. (2018), ICON-ART 2.1: a flexible tracer framework and its application for composition studies in numerical weather forecasting and climate simulations. Geosci. Model Dev., doi:10.5194/gmd-11-4043-2018</p> </div> <div> <p><sup>[[6]]</sup> Prather, M.J. (2015), Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c. Geosci. Model Dev., doi:10.5194/gmd-8-2587-2015</p> </div> </div>

Spread of SARS-CoV-2 Genomes on Genomic Index Maps of Hierarchy - Compared with B.1.1.7 Lineage on BLAST

COVID-19 patients worldwide are conveniently described by position information to collect samples, and modern GIS maps are useful to show influenced flows and numbers of patients on various regions of a pendamic. From an analysis viewpoint, it is more interesting to organize genomic information into a phylogenic tree with multiple branches and leaves in representations. Clusters of genomes are organized as phylogenic trees to represent intrinsic information of genomes. However, there are structural difficulties in projecting phylogenetic information into 2D distributions as GIS maps naturally.Considering advanced generating schemes of phylogenetic trees, information entropy provides ultra optimal properties in the minimum computational complexity, superior flexibility, better stability, improved reliability and higher quality on global constructions.In this paper, a novel projection is proposed to arrange SARS-CoV-2 genomes by genomic indexes to make a structural organization as 2D GIS maps. For any genome, there is a unique invariant under certain conditions to provide an absolute position on a specific region. In this hierarchical framework, it is possible to use a visual tool to represent any selected region for clustering genomes on refined effects. Applied diversity measure to a given set of genomes, equivalent clusters and complementary visual effects are provided between genomic index maps and phylogenetic trees. Sample genomes of three UK new lineages are aligned by BLAST as a basis on both RNA-dependent RNA polymerase RDRP segments and whole genomes. Selected regions and various projections show spread effects of five thousand SARS-CoV-2 genomes in 72 countries on both RDRP and whole genomes, and six special countries/regions are selected on genomic index maps.Based on genomic index maps, one SNV of two genomes on B.1.1.7 lineage can be identified from a unit of 10^4 probability measure to a unit of 10^6 difference for genomic indexes on a special ‘G’ projection to extract the finest variation.Further exploration on optimal classification and phylogenetic analysis of genomic index maps and phylogenetic trees on SARS-CoV-2 genomes worldwide are discussed.

Reducing the Uncertainty of Radiata Pine Site Index Maps Using an Spatial Ensemble of Machine Learning Models

Site Index has been widely used as an age normalised metric in order to account for variation in forest height at a range of spatial scales. Although previous research has used a range of modelling methods to describe the regional variation in Site Index, little research has examined gains that can be achieved through the use of regression kriging or spatial ensemble methods. In this study, an extensive set of environmental surfaces were used as covariates to predict Site Index measurements covering the environmental range of Pinus radiata D. Don plantations in Chile. Using this dataset, the objectives of this research were to (i) compare predictive precision of a range of geostatistical, parametric, and non-parametric models, (ii) determine whether significant gains in precision can be attained through use of regression kriging, (iii) evaluate the precision of a spatial ensemble model that utilises predictions from the five most precise models, through using the model prediction with lowest error for a given pixel, and (iv) produce a map of Site Index across the study area. The five most precise models were all geostatistical and they included ordinary kriging and four regression kriging models that were based on partial least squares or random forests. A spatial ensemble model that was constructed from these five models was the most precise of those developed (RMSE = 1.851 m, RMSE% = 6.38%) and it had relatively little bias. Climatic and edaphic variables were the strongest determinants of Site Index and, in particular, variables that are related to soil water balance were well represented within the most precise predictive models. These results highlight the utility of predicting Site Index using a range of approaches, as these can be used to construct a spatial ensemble that may be more precise than predictions from the constituent models.