A TOOL FOR COLLECTING, QUERYING AND MINING MACROSEISMIC DATA

SEISMO-SURFER is a tool for collecting, querying and mining seismic data being developed in Java programming language using Oracle database system. The objective is to combine recent research trends and results in the fields of spatial and spatio-temporal databases, data warehouses and data mining, as well as well established visualization techniques for geographical information. The database of the tool is automatically updated from remote sources while existing possibilities allow the querying on different earthquakes parameters, the analysis of the data for extraction of useful information and the graphical representation of the results via maps, charts etc. In the present work, we extend SEISMO-SURFER to include macroseismic data collected by the Geodynamic Institute and filled in a relative database. More specifically, the seismic parameters of the strong earthquakes, stored into the SEISMO-SURFER database, are linked to the macroseismic intensities observed at different sites. Administrative information for each site, local surface geology, tectonic lines, damage photographs and detailed descriptions from newspapers are also included. University of Piraeus and Geodynamic Institute are working together to continuously update and develop SEISMO-SURFER, concerning the data included, the variety of parameters stored and the mining algorithms supported for exploiting knowledge

MAPPING OF CODA ATTENUATION AT THE EXTEND OF THE NATIONAL SEISMOLOGICAL NETWORK OF GREECE

Coda decay rates of 538 vertical components corresponding to local earthquakes which occurred in Greece during the period 1998 to 1999 were used to deduce the coda quality factor (Qc) characteristics in the Hellenic area. The seismograms have been selected from a broader sample of 776 records obtained at 8 stations of the National Seismographic Network operated by the Institute of Geodynamics of the National Observatory of Athens. Earthquake magnitudes range from 2.5 to 4.0; epicentral distances and depths are smaller than 100 km and 40 km, respectively. Using the Single Back Scattering model, the dependence of Qc on frequencies between 1 and 10 Hz has been investigated at each station and the usual Qc =Qo f relationships have been deduced. The spatial distribution of Qo has been drawn using waves that sample approximately equivalent ellipsoidal volumes with semiminor axis up to 100 km. The corresponding map shows a decreasing trend in SN direction

Clustering Sustainable Destinations: Empirical Evidence from Selected Mediterranean Countries

Within the globalized tourism market, tourism destinations have the option to turn to sustainability as a conceptual and management framework for their unique branding and identity proposition. This research highlights the importance and utility of sustainability branding that stems from clustering tourism destinations based on the similarities of their tourism performance attributes. The study builds on secondary data from 11 coastal destinations in 8 Mediterranean countries. The analysis leads to the formulation of three main sets of evaluation indicators: (a) environmental footprint; (b) destination dependency on tourism; and (c) locals’ prosperity, incorporating elements of social and psychological carrying capacity. Findings identify three to four distinct destination clusters based mainly on the attributes of destinations’ cultural and natural attributes, seasonality of supply, typology of prevailing accommodation and tourist profile. From a theoretical perspective, the research identifies key clustering attributes of sustainable destinations that could inform management interventions around destination branding and competitive sustainability performance positioning

A Test of a Strong Ground Motion Prediction Methodology for the 7 September 1999, Mw=6.0 Athens Earthquake

We test a methodology to predict the range of ground-motion hazard for a fixed magnitude earthquake along a specific fault or within a specific source volume, and we demonstrate how to incorporate this into probabilistic seismic hazard analyses (PSHA). We modeled ground motion with empirical Green's functions. We tested our methodology with the 7 September 1999, Mw=6.0 Athens earthquake, we: (1) developed constraints on rupture parameters based on prior knowledge of earthquake rupture processes and sources in the region; (2) generated impulsive point shear source empirical Green's functions by deconvolving out the source contribution of M < 4.0 aftershocks; (3) used aftershocks that occurred throughout the area and not necessarily along the fault to be modeled; (4) ran a sufficient number of scenario earthquakes to span the full variability of ground motion possible; (5) found that our distribution of synthesized ground motions span what actually occurred and their distribution is realistically narrow; (6) determined that one of our source models generates records that match observed time histories well; (7) found that certain combinations of rupture parameters produced ''extreme'' ground motions at some stations; (8) identified that the ''best fitting'' rupture models occurred in the vicinity of 38.05{sup o} N 23.60{sup o} W with center of rupture near 12 km, and near unilateral rupture towards the areas of high damage, and this is consistent with independent investigations; and (9) synthesized strong motion records in high damage areas for which records from the earthquake were not recorded. We then developed a demonstration PSHA for a source region near Athens utilizing synthesized ground motion rather that traditional attenuation. We synthesized 500 earthquakes distributed throughout the source zone likely to have Mw=6.0 earthquakes near Athens. We assumed an average return period of 1000 years for this magnitude earthquake in the particular source zone, thereby having simulated a catalog of ground motion for a period of 500,000 years. The distribution of traditional ground motion parameters of peak acceleration or spectral ordinates then becomes the synthesized record from which we develop hazard curves in the form of the annual probability of exceedance. This approach replaces the aleatory uncertainty that current PSHA studies estimate by regression of empirical parameters from the worldwide database with epistemic uncertainty on what specific sources actually do at specific sites. This is a fundamental change for PSHA and eliminates the need to extrapolate current empirical data that was gathered over about 50 years to represent values for 10{sup -3} annual probability of exceedance or less. This difference becomes especially significant for very sensitive structures that require estimates for 10{sup -5} or less exceedance

Combination of (M)DSC and surface analysis to study the phase behaviour and drug distribution of ternary solid dispersions

Purpose: Miscibility of the different compounds that make up a solid dispersion based formulation play a crucial role in the drug release profile and physical stability of the solid dispersion as it defines the phase behaviour of the dispersion. The standard technique to obtain information on phase behaviour of a sample is (modulated) differential scanning calorimetry ((M)DSC). However, for ternary mixtures (M)DSC alone is not sufficient to characterize their phase behaviour and to gain insight into the distribution of the active pharmaceutical ingredient (API) in a two-phased polymeric matrix. Methods: MDSC was combined with complementary surface analysis techniques, specifically time-of-flight secondary ion mass spectrometry (ToF-SIMS) and atomic force microscopy (AFM). Three spray-dried model formulations with varying API/PLGA/PVP ratios were analyzed. Results: The distribution of the API in the ternary solid dispersions depended on formulation parameters. The extent of API surface coverage and therefore the distribution of the API over both polymeric phases differed significantly for the three formulations. Conclusions: Combining (M)DSC and surface analysis rendered additional insights in the composition of mixed phases in complex systems, like ternary solid dispersions

Tuning the energetics and tailoring the optical properties of silver clusters confined in zeolites

The integration of metal atoms and clusters in well-defined dielectric cavities is a powerful strategy to impart new properties to them that depend on the size and geometry of the confined space as well as on metal-host electrostatic interactions. Here, we unravel the dependence of the electronic properties of metal clusters on space confinement by studying the ionization potential of silver clusters embedded in four different zeolite environments over a range of silver concentrations. Extensive characterization reveals a strong influence of silver loading and host environment on the cluster ionization potential, which is also correlated to the cluster's optical and structural properties. Through fine-tuning of the zeolite host environment, we demonstrate photoluminescence quantum yields approaching unity. This work extends our understanding of structure property relationships of small metal clusters and applies this understanding to develop highly photoluminescent materials with potential applications in optoelectronics and bioimaging

Chitosan–Starch–Keratin composites: Improving thermo-mechanical and degradation properties through chemical modification

The lysozyme test shows an improved in the degradability rate, the weight loss of the films at 21 days is reduced from 73 % for chitosan-starch matrix up to 16 % for the composites with 5wt% of quill; but all films show a biodegradable character depending on keratin type and chemical modification. The outstanding properties related to the addition of treated keratin materials show that these natural composites are a remarkable alternative to potentiat-ing chitosan–starch films with sustainable featuresChitosan–starch polymers are reinforced with different keratin materials obtained from chicken feather. Keratin materials are treated with sodium hydroxide; the modified surfaces are rougher in comparison with untreated surfaces, observed by Scanning Electron Microscopy. The results obtained by Differential Scanning Calorimetry show an increase in the endothermic peak related to water evaporation of the films from 92 °C (matrix) up to 102–114 °C (reinforced composites). Glass transition temperature increases from 126 °C in the polymer matrix up to 170–200 °C for the composites. Additionally, the storage modulus in the composites is enhanced up to 1614 % for the composites with modified ground quill, 2522 % for composites with modified long fiber and 3206 % for the composites with modified short fiber. The lysozyme test shows an improved in the degradability rate, the weight loss of the films at 21 days is reduced from 73 % for chitosan-starch matrix up to 16 % for the composites with 5wt% of quill; but all films show a biodegradable character depending on keratin type and chemical modification. The outstanding properties related to the addition of treated keratin materials show that these natural composites are a remarkable alternative to potentiat-ing chitosan–starch films with sustainable featuresUniversidad Autónoma del Estado de México Tecnológico Nacional de México, Instituto Tecnológico de Querétaro Universidad Nacional Autónoma de México Tecnológico Nacional de México, Instituto Tecnológico de Celaya Universidad Autónoma de Cd. Juáre

STAMINA: Bioinformatics Platform for Monitoring and Mitigating Pandemic Outbreaks

Data Availability Statement: All data driven applications used the our world in data COVID-19 datasets, complimented by proprietary datasets share by the STAMINA consortium.Copyright © 2022 by the authors. This paper presents the components and integrated outcome of a system that aims to achieve early detection, monitoring and mitigation of pandemic outbreaks. The architecture of the platform aims at providing a number of pandemic-response-related services, on a modular basis, that allows for the easy customization of the platform to address user’s needs per case. This customization is achieved through its ability to deploy only the necessary, loosely coupled services and tools for each case, and by providing a common authentication, data storage and data exchange infrastructure. This way, the platform can provide the necessary services without the burden of additional services that are not of use in the current deployment (e.g., predictive models for pathogens that are not endemic to the deployment area). All the decisions taken for the communication and integration of the tools that compose the platform adhere to this basic principle. The tools presented here as well as their integration is part of the project STAMINA.The paper presented is based on research undertaken as part of the European Commission-funded project STAMINA (Grant Agreement 883441)