bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of the catchment land use on some factors of lakes trophic status: a GIS approach
Authors: Sługocki Łukasz , Czerniawski Robert
Published: January 2018

Background. Artificial enrichment of lakes has posed serious management problems for water supply. In results many European lakes had already undergone significant eutrophication. It seems that a good tool to determine the influence of catchment use on the trophic changes in lakes is Geographic Information System (GIS) and its databases.

Methods. The study covered 31 stratified lakes located in northwestern Poland. These lakes were chosen on account of their considerable recreation value and economic importance. The parameters chosen as dependent variables were Secchi depth and electrical conductivity. Local catchments and network catchment of studied lakes as independent variables were prepared using QGIS Wien (2.8.7). The land use variables were prepared with Corine Land Cover, 2006 (CLC2006).

Results. According to Carlson index the studied lakes ranged from mesotrophic to eutrophic. Both dependent variables Secchi depth and conductivity values were significantly correlated with independent land use variables (P < 0.05).

Discussion. Our survey revealed that percentage use of the catchment (developed in the Geographic Information System) can be a useful tool in the assessment of the lakes risks. With the GIS tools we also confirmed a significant impact of land use on changes transparency and conductivity values in North West lakes in Poland.
Hotspot analysis: a first prototype Python plugin enabling exploratory spatial data analysis into QGIS
Authors: Oxoli Daniele , Zurbarán Mayra A , Shaji Stanly , Muthusamy Arun K
Published: January 2018

The growing popularity of Free and Open Source (FOSS) GIS software is without doubts due to the possibility to build and customize geospatial applications to meet specific requirements for any users. From this point of view, QGIS is one of the most flexible as well as fashionable GIS software environment which enables users to develop powerful geospatial applications using Python. Exploiting this feature, we present here a first prototype plugin for QGIS dedicated to Hotspot analysis, one of the techniques included in the Exploratory Spatial Data Analysis (ESDA). These statistics aim to perform analysis of geospatial data when spatial autocorrelation is not neglectable and they are available inside different Python libraries, but still not integrated within the QGIS core functionalities. The main plugin features, including installation requirements and computational procedures, are described together with an example of the possible applications of the Hotspot analysis.
Evaluation of the parallel performance of the TRIGRS v2.1 model for rainfall-induced landslides
Authors: Alvioli Massimiliano , Spiga Daniele , Baum Rex L
Published: January 2018

The widespread availability of high resolution digital elevation models (DEM) opens the possibility of applying physically based models of landslide initiation to large areas. With increasing size of the study area and resolution of the DEM, the required computing time for each run of such models increases proportionally to the number of grid cells in the study area. The aim of this work is to present a new parallel implementation of TRIGRS (Alvioli and Baum, 2016), an open-source FORTRAN program designed for modeling the timing and distribution of shallow, rainfall-induced landslides, and to discuss its parallel performance. We investigated the parallel performance by evaluating running time, speedup and efficiency of the code on a commonly available multi-core machine, on a high-end multi-node machine and on a cloud computing environment, showing the advantages and limitations of each case and discussing the possible weak points of using a general-purpose cloud environment
An integrated multi-level comparison highlights common aspects and specific features between distantly-related species: Tomato and Grapevine
Authors: Ambrosino Luca , Bostan Hamed , Ruggieri Valentino , Chiusano Maria Luisa
Published: January 2018

Motivation. Even after years from the first completion of genomes by sequencing, comparative genomics still remains a challenge, also enhanced by the availability of numerous draft genomes with still poor annotation quality. The detection of ortholog genes between different species is a key approach for comparative genomics. For example, ortholog gene detection may support investigations on mechanisms that shaped the organization of the genomes, highlighting on gain or loss of function and on gene annotation. On the other hand, the detection of paralog genes is fundamental for understanding the evolutionary mechanisms that drove gene function innovation and support gene families analyses. Here we report on the gene comparison between two distantly related plants, Solanum lycopersicum (Tomato) (The Tomato Genome Consortium 2012) and Vitis vinifera (Grapevine) (Jaillon et al. 2007), considered as economically important species from asterids and rosids clades, respectively. The strategy was accompanied by integration of multilevel analyses, from domain investigations to expression profiling, to get to the most reliable results and to offer powerful resources, in order to understand different useful aspects of plant evolution and physiology and to dissect traits and molecular aspects that could provide novel tools for agriculture applications and biotechnologies.

Methods. In order to predict best putative orthologs and paralogs between Tomato and Grapevine, and to overcome possible annotation issues, all-against-all sequence similarity searches between genes, mRNAs and proteins collections of both species were performed. A Bidirectional Best Hit approach was implemented to detect the best orthologs between the two species. Moreover we developed a dedicated algorithm in Python programming language able to define more extended alignments between mRNA sequences. NetworkX package (Hagberg et al. 2008) was used to define networks of paralogs and orthologs. Proteins domain prediction was carried out on the entire Tomato and Grapevine protein collection by using InterProScan program (Jones et al. 2014). The enzyme classification was obtained by sequence similarity searches between Tomato and Grapevine mRNA collections and the entire UniProt reviewed protein collection (UniProt consortium 2015). The metabolic pathways associated to the detected enzymes were identified exploiting the KEGG Database (Kanehisa and Goto 2000). Expression level of three developmental stages of Tomato (2 cm fruit, breaker and mature red) and the corresponding stages of Grapevine (post-setting, veraison, mature berry) was defined on the basis of the iTAG loci (Shearer et al. 2014) and v1 vitis loci, respectively. The expression was normalized by Reads Per Kilobases per Million (RPKM) for each tissue/stage.

Abstract truncated at 3,000 characters - the full version is available in the pdf file
Open Source for Water Management: including capabilities of MODFLOW-OWHM in the FREEWAT GIS modelling environment
Authors: Borsi Iacopo , Rossetto Rudy , Cannata Massimiliano , De Filippis Giovanna , Ghetta Matteo
Published: January 2018

FREEWAT is an ongoing GIS environment to serve as pre- and post-processor for running simulations of surface-/groundwater interaction, with the possibility to activate several features accounting for the different water stresses. This paper reports the capability related to address water resource management problems, by activating management tools available in the MODFLOW-OWHM code. The latter is integrated in FREEWAT, which appears as composite plugin of the well-know QGIS software (QGIS, 2016). Therefore, all the necessary pre- and post-process procedures can be run effectively within QGIS, also in conjunction with the several tools for GIS analysis already included in QGIS. It turns out a simple and intuitive user interface to manage the simulation of complex problem in which the mutual interaction among surface waters, groundwaters and anthropic water demand/supply terms can be handled. The development phase of such tools is already at an advanced stage, while next work will be focused on producing real-world applications to serve as tutorial for interest Users.
BioPaxCOMP: an efficient system for integrating, compressing, and querying BioPAX
Authors: Agapito Giuseppe , Greco Andrea , Cannataro Mario
Published: January 2018

Abstract truncated at 3,000 characters - the full version is available in the pdf file.

Biological networks and, in particular, biological pathways are composed of thousands of nodes and edges, posing several challenge regarding analysis and storage. The primary format used to represent pathways data is BioPAX (http://biopax.org.) BioPAX is a standard language that aims to enable integration, exchange, visualization and analysis of biological pathway data. BioPAX is an open and collaborative effort made by the community of researchers, software developers, and institutions and it specifically supports data exchange between pathway data groups. BioPAX is defined in OWL and is represented in the RDF/XML format. OWL (Web Ontology Language) is a W3C standard and is designed for use by applications that need to process the content of information instead of just presenting information to humans. RDF is a standard model for data interchange on the Web. Although OWL allows a standard representation of pathways, since it is based on XML, it is a verbose and redundant language, so the storage of pathways may be very huge, preventing an efficient transmission and sharing of this data. The typical size of a pathway is related to the organism, for example, the size of Homo Sapiens pathways (from Reactome database) is near to 200 MB on disk. Moreover, integrating pathways data coming from different data sources may require GBytes of space. A second problem with pathways is related to the possibility to integrate information coming from different data sources to have updated information in a centralized way. There exist several different databases for pathways data that emphasizes different aspect of the same pathway, thus, it could be useful to integrate and annotate together pathways coming from different databases to obtain a centralized and more informative pathway data. The principal obstacle for integrating, storing and exchanging such data is the extreme size growth when several pathways data are merged together, posing several challenges from the computational and archiving point of view. Pathways data can be easily classified as big data, because they meet all the 5V (Volume, Velocity, Variety, Veracity, Value) characteristics typical of Big Data, thus, the necessity to efficiently integrate and compress pathways data arises. The methodology for pathways data integration is based on the following steps: i) aggregation and validation locally of data coming from several pathway databases, ii) identification and normalization of compounds and reactions identifier and iii) integration. Integration occurs at the level of physical entities, such as proteins and small molecules. This is accomplished by linking interaction and pathway records together if they use the same physical entities (such as from UniProt for proteins) and by adding annotation data from UniProt or GeneOntology.
The diversity weighted Living Planet Index: controlling for taxonomic bias in a global biodiversity index
Authors: McRae Louise , Deinet Stefanie , Freeman Robin
Published: January 2018

As threats to species continue to increase, we urgently need precise and unbiased measures of the impact these pressures are having on global biodiversity. Some existing indicators of the status and trends of biodiversity largely rely on publicly available data from the scientific and grey literature, and are therefore prone to biases introduced through overrepresentation of well-studied groups and regions in monitoring schemes. This can give misleading estimates of biodiversity trends. Here, we report on an approach to tackle taxonomic and geographic bias in once such indicator (Living Planet Index) by accounting for the estimated number of species within biogeographical realms, and the relative diversity of species within them. Based on a proportionally weighted index, we estimate a global population decline in vertebrate species between 1970 and 2010 of 55% rather than 22% from an index with no proportional weighting. From this dataset, comprising 10,380 populations of 3,038 species from 2,337 data sources, we also find that freshwater populations have declined by 76%, marine populations by 41%, and terrestrial populations by 39% when using proportional weighting (compared to declines of 45%, 2% and 30% respectively). This not only shows starker declines than previously estimated, but suggests that those species for which we have poorer data coverage may be declining more rapidly.
Ten simple rules for writing a comparative software review
Authors: Beeston Amy , Blazic Larisa , Chue Hong Neil , Domander Richard , Mounce Ross , Wilson Robin T
Published: January 2018

We provide the following set of rules as a framework for researchers in any domain to undertake a comparative software review and determine the best software for their task.

Rule 1: State your credentials and motivation

Rule 2: Define and justify your scope

Rule 3: Perform a comprehensive search

Rule 4: Make your longlist data available to others

Rule 5: Summarise your software shortlist

Rule 6: Define the software quality criteria

Rule 7: Define the task suitability criteria

Rule 8: Mind the gaps

Rule 9: Summarise the findings as clearly as possible

Rule 10: Involve your community
Spatial interpolation techniques for a near real-time mapping of Pressure and Temperature data
Authors: Ferrando Ilaria , De Rosa Pierluigi , Federici Bianca , Sguerso Domenico
Published: January 2018

Among the different techniques for atmosphere monitoring, the GNSS (Global Navigation Satellite System) can provide an innovative contribution (Bevis et al.,1992; Crespi et al., 2004; Sguerso et al., 2013, 2015). The Laboratory of Geomatics, Geodesy and GIS of the University of Genoa has identified a GIS procedure and a simplified physical model to monitor the Precipitable Water Vapour (PWV) content, using data measured by existing infrastructures. The starting points are local estimations of Zenith Total Delay (ZTD) from a GNSS Permanent Stations (PSs) network, a Digital Terrain Model (DTM) and local Pressure (P) and Temperature (T) measurements (Sguerso et al., 2014; Ferrando et al., 2016). The present paper shows the study of the most appropriate interpolation technique for P and T data to create PWV maps in a quick, stable and automatic way, to support the monitoring of intense meteorological events for both a posteriori and near real-time applications. The resulting P and T maps were compared to meteorological re-analysis, to check the reliability of the simplified physical model. Additionally, the Regression Kriging (RK) was employed to evaluate the data correlation with elevation and to study the applicability of the technique.
Spatial interpolation techniques for a near real-time mapping of pressure and temperature data
Authors: Ferrando Ilaria , De Rosa Pierluigi , Federici Bianca , Sguerso Domenico
Published: January 2018

Among the different techniques for atmosphere monitoring, the GNSS (Global Navigation Satellite System) can provide an innovative contribution (Bevis et al.,1992; Crespi et al., 2004; Sguerso et al., 2013, 2015). The Laboratory of Geomatics, Geodesy and GIS of the University of Genoa has identified a GIS procedure and a simplified physical model to monitor the Precipitable Water Vapour (PWV) content, using data measured by existing infrastructures. The starting points are local estimations of Zenith Total Delay (ZTD) from a GNSS Permanent Stations (PSs) network, a Digital Terrain Model (DTM) and local Pressure (P) and Temperature (T) measurements (Sguerso et al., 2014; Ferrando et al., 2016). The present paper shows the study of the most appropriate interpolation technique for P and T data to create PWV maps in a quick, stable and automatic way, to support the monitoring of intense meteorological events for both a posteriori and near real-time applications. The resulting P and T maps were compared to meteorological re-analysis, to check the reliability of the simplified physical model. Additionally, the Regression Kriging (RK) was employed to evaluate the data correlation with elevation and to study the applicability of the technique.
Probabilistic graph models for landscape genetics
Authors: Milligan Brook G
Published: January 2018

Progress in landscape genetics depends on a strong conceptual foundation and the means of identifying mechanistic connections between environmental factors, landscape features, and genetic or genomic variation. Many existing approaches and much of the software commonly in use was developed for population genetics or statistics and is not entirely appropriate for landscape genetics. Probabilistic graph models provide a statistically rigorous and flexible means of constructing models directly applicable to landscape genetics. Sophisticated software also exists for the analysis of graph models. However, much of that software does not handle the types of data used for landscape genetics, model structures involving autoregressive spatial interaction between variables, or the scale of landscape genetics problems. Thus, an important priority for the field is to develop suitably flexible software tools for graph models that overcome these problems and allow landscape geneticists to explore meaningfully mechanistic and flexible models. We are developing such a library and applying it to examples in landscape genetics.
Probabilistic graph models for landscape genetics
Authors: Milligan Brook G.
Published: January 2018

Landscape genetics combines population genetics, landscape ecology, and spatial analysis to identify landscape and genetic factors that influence genetic and genomic variation. Progress in the field depends on a strong conceptual foundation and the means of identifying mechanistic connnections between environmental factors, landscape features, and genetic or genomic variation. Many existing approaches and much of the software commonly in use was developed for population genetics or statistics and is not entirely appropriate for landscape genetics. Probabilistic graph models provide a statistically rigorous and flexible means of constructing models directly applicable to landscape genetics. Probabilistic graph models also allow construction of mechanistic models, which are crucial elements in testing hypotheses. Sophisticated software exists for the analysis of graph models; however, much of it does not handle the types of data used for landscape genetics, model structures involving autoregressive spatial interaction between variables, or the scale of landscape genetics problems. Thus, an important priority for the field is to develop suitably flexible software tools for graph models that overcome these problems and allow landscape geneticists to explore meaningfully mechanistic and flexible models. We are developing such a library and applying it to examples in landscape genetics.
Simulation of marine activities by coupling Geographical Information System and Agent Based Model: improvements and technical achievements
Authors: Minelli Annalisa , Tissot Cyril , Rouan Mathias , Le Tixerant Matthieu
Published: January 2018

This short paper presents an example of integration between open source Geographical Information System (GIS) and Agent Based Model (ABM) in order to better simulate fishing activities on Iroise Sea (Brittany, France). This work makes part of the SIMARIS project: a simulation prototype that integrate multi-source and multi-scale spatiotemporal constraints as forcing variable in order to assess the intensity and the variability of marine activities. A pre-processing step, executed in batch in GRASS GIS, aims to calculate data for initialization and simulation step, then the Agent Based simulation is launched (in batch) on GAMA platform. All these operations are scheduled in a Python script to perform pre-processing and simulation. The work presents an example of integration from a geographical point of view. The technical improvements are detailed and the potentials of such integrated solution are discussed.
CREGIS-Q: a GIS tool to support decision making in case of aquifer contamination emergency
Authors: Petrangeli Anna Bruna , Preziosi Elisabetta , Campopiano Francesco , Corazza Angelo , Duro Andrea
Published: January 2018

GIS technology has been used for many years in environmental risk analysis due to its capability to focus on the management and analysis of geographic and alphanumeric data to support spatial decision-making (Vairavamoorthy et al, 2007). Especially in emergency management, a DSS (Decision Support System) constitutes an important task to provide quick responses, though not completely exhaustive, to immediately handle a critical scenario and limit the possible damage. In the framework of a collaboration between the Water Research Institute and the National Civil Protection Department, a customized tool called CREGIS (ContaminazioneRisorseEvento-GIS) has been developed in order to facilitate the emergency management of accidental contamination of aquifers and support decision making (Preziosi et al, 2013). The tool is aimed at both national and local authorities in order to improve response capability for a better emergency management. Originally, the tool has been developed programming Python in an ArcGIS environment; but due to the great development and dissemination of open source software, our aim is to replicate the same structure programming Python in a GIS open source environment (QGIS). The review of the tool's code is still in progress. The goal is to make the tool (now named CREGIS-Q) free and accessible to a greater number of people and stakeholders.
Why respiratory viruses or bacteria have the highest probability to be deposited in the respiratory tract in flu seasons
Authors: Ishmatov Aleksandr N
Published: January 2018

Objective:

The main aspects of influenza transmission via fine and ultrafine bioaerosols were considered. Here, we aimed to estimate the impact of the different environment conditions on the processes of heat and mass transfer in the upper respiratory tract and its role in the deposition rate of the infectious bioaerosols in the lungs.

Background:

The latest researches show the infected people generate the fine and ultrafine infectious bioaerosols with submicron particles/droplets (size below 1 µm). The airborne transmission of these particles/droplets is effective. It is considered the deposition of submicron particles in the respiratory tract (RT) has very low probability. But most studies examined the deposition of the particles in the lungs under normal environmental conditions and did not paid attention to the different environmental factors.

Methods:

We review the problems of epidemiology of respiratory infections and aspects of airborne transmission/spread of infectious agents. We contrast these approaches with known data from next area: inhalation toxicology, respiratory drug delivery and physics of heat and mass transfer in the airways.

Results:

On the basis of these analyses, we propose the next main concepts:

1 Breathing cool air leads to the supersaturation of air in RT;

2 the air supersaturation leads to the intensive condensational growth(CG) of inhaled viruses or bacteria in RT;

3 CG leads to the intensive and dramatically growth of deposition rate of viruses or bacteria in RT.

We have shown:

a) Under normal conditions of inhaled air (T>20˚C; Relatively Humidity (RH)=60%) there is no transition in supersaturated condition in RT and CG is insignificant and probability of virus deposition on epithelium of RT is low – no more than 20%.

b) Breathing cool/cold air of T<+15˚C and RH of [30..60]% leads to the supersaturation in the airways and it can dramatically increase the deposition rate of inhaled bioaresols in the lungs (up to 97%).

c) With an increase in RH of inhaled air the supersaturation in RT occurs even at warm temperature of inhaled air (for inhaled air of T<20°C and RH>70% ; T<25°C and RH>90%). It also indicates the high deposition rate of bioaerosols in the lungs.

Conclusion:

Under specific environmental conditions (when flu seasons) the processes of supersaturation in the RT can be observed. These results indicate the high probability of virus deposition on epithelium of RT and correspond to influenza and seasonal respiratory infections in temperate and tropical climates.

We believe the effect of supersaturation in the lungs can be the key to understanding of ‘the age-old epidemiologic mystery of influenza seasonality in the different climatic conditions’.
Why respiratory viruses or bacteria have the highest probability to be deposited in the respiratory tract in flu seasons
Authors: Ishmatov Aleksandr N
Published: January 2018

Objective:

In this study the main aspects of influenza transmission via fine and ultrafine bioaerosols were considered. Here, we aimed to estimate the impact of the different environment conditions on the deposition rate of the infectious bioaerosols in the respiratory tract.

Background:

The latest researches show the infected people generate the fine and ultrafine infectious bioaerosols with submicron particles/droplets (size below 1 µm). The airborne transmission of these particles/droplets in the environment is effective. It is considered the deposition of submicron particles in the respiratory tract (RT) has very low probability. But most studies examined the aerosol deposition in RT under normal environmental conditions and did not paid attention to the affecting the different environmental factors.

Methods:

We review the problems of epidemiology of respiratory infections and aspects of airborne transmission/spread of infectious agents. We contrast these approaches with known data from next areas: inhalation toxicology, respiratory drug delivery and physics of heat and mass transfer in the airways.

Results:

Based on the conducted analysis, we propose the next main concepts:

1 Breathing cool air leads to the supersaturation of air in RT;

2 the air supersaturation leads to the intensive condensational growth(CG) of inhaled viruses or bacteria in RT;

3 CG leads to the intensive and dramatically growth of deposition rate of viruses or bacteria in RT.

We have shown:

a) Under normal conditions of inhaled air (T>20˚C; Relatively Humidity, RH=60%) there is no transition in supersaturated condition in RT and CG is insignificant and probability of virus deposition on epithelium of RT is low – no more than 20%.

b) Breathing cool/cold air of T<+15˚C and RH of [30..60]% leads to the supersaturation in the airways and it can dramatically increase the deposition rate of inhaled bioaerosols in RT(up to 96%).

c) With an increase in RH of inhaled air the supersaturation in RT occurs even at warm temperature of inhaled air (for inhaled air of T<20°C and RH>70% ; T<25°C and RH>90%). Which also indicates the deposition rate of bioaerosols in RT under these conditions is high.

Conclusion:

Under specific environmental conditions (when flu seasons) the processes of supersaturation in the RT can be observed. These results indicate the high probability of virus deposition on epithelium of RT and correspond to influenza and seasonal respiratory infections in temperate and tropical climates.

We believe the effect of supersaturation in the airways can be the key to understanding of ‘the age-old epidemiologic mystery of influenza seasonality in the different climatic conditions’.
Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures
Authors: Corti Paolo , Lewis Benjamin G , Kralidis Tom , Mwenda Jude
Published: January 2018

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software components of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information.

A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others.

The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogues and search engines).

Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalogue, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.
Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures
Authors: Corti Paolo , Lewis Benjamin G , Kralidis Tom , Mwenda Jude
Published: January 2018

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide an efficient and flexible way to use spatial information. One of the key software components of an SDI is the catalogue service which is needed to discover, query, and manage the metadata. Catalogue services in an SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard which defines common interfaces for accessing the metadata information.

A search engine is a software system capable of supporting fast and reliable search, which may use “any means necessary” to get users to the resources they need quickly and efficiently. These techniques may include features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations, feedback mechanisms based on log mining, usage statistic gathering, and many others. In this paper we will be focusing on improving geospatial search with a search engine platform that uses Lucene, a Java-based search library, at its core.

In work funded by the National Endowment for the Humanities, the Centre for Geographic Analysis (CGA) at Harvard University is in the process of re-engineering the search component of its public domain SDI (WorldMap http://worldmap.harvard.edu ) which is based on the GeoNode platform. In the process the CGA has developed Harvard Hypermap (HHypermap), a map services registry and search platform independent from WorldMap.

The goal of HHypermap is to provide a framework for building and maintaining a comprehensive registry of web map services, and because such a registry is expected to be large, the system supports the development of clients with modern search capabilities such as spatial and temporal faceting and instant previews via an open API. Behind the scenes HHypermap scalably harvests OGC and Esri service metadata from distributed servers, organizes that information, and pushes it to a search engine. The system monitors services for reliability and uses that to improve search. End users will be able to search the SDI metadata using standard interfaces provided by the internal CSW catalogue, and will benefit from the enhanced search possibilities provided by an advanced search engine. HHypermap is built on an open source software source stack.
Open source tools to support Integrated Coastal Management and Maritime Spatial Planning
Authors: Menegon Stefano , Sarretta Alessandro , Barbanti Andrea , Gissi Elena , Venier Chiara
Published: January 2018

This paper describes an open source suite of libraries and tools to support research activities on marine and coastal environment. The suite was initially implemented for the ADRIPLAN portal, an integrated web platform aimed at supporting Maritime Spatial Planning (MSP) activities and other activities concerning the managing of marine environment for the Adriatic-Ionian region. The main elements of the implemented solutions are: i) a GeoNode implementation for sharing geospatial datasets and maps; ii) a new python library (RectifiedGrid) that facilitates the work with geographical grid data; iii) a new python library (MSPTools) to perform spatial analysis and assessment of human uses, pressures and the potential impact of maritime and coastal activities on the environment; iv) a new GeoNode plugin (called GeoNodeMSPTools) that provides interactive widgets to set up the analyses and to visualize and explore the results. The MSP Tools and the developed software have been released as FOSS under the GPL3 license and are currently under further development.
The Open Data GeoPortal of the Lamma Consortium
Authors: Corongiu Manuela , Mari Riccardo , Ferrari Raffaella , Bottai Lorenzo , Grasso Valentina , Zabini Federica , Fibbi Luca , Grifoni Daniele , Tei Claudio , Pasi Franceso , Gozzini Bernardo , Giannecchini Simone
Published: January 2018

The new Lamma Open Data platform (http://dati.lamma.toscana.it) allows data download related to information delivered / managed by the Consortium, encouraging the reuse both at technical and legal level. The datasets, over 220, belong to the weather forecast and geospatial topics above all, but they are in continuous updating, both spatial and no spatial (such as administrative documentation). Lamma open data platform integrates in a harmonised interface, most off the spatial dataset already available through the Lamma geoportal (http://geoportale.lamma.rete.toscana.it/MapStore/public/), now available for download as open data. The particularity of meteorological information is their organization in models, archives and formats according to the type of information, source of acquisition and level of elaboration. These formats are not all functional or directly manageable in their entirety, as data to be made available and immediately accessible. The datasets therefore require a preliminary phase of evaluation and analysis of the contents to identify the most appropriate elements for publication via filters and elaborations that maintain the significance of the variables to be highlighted. A synergic and integrated infrastructure for spatial data has been carried out through open source softwares. The LaMMA Geoportal integrates, in a single simple but powerful interface, the functionalities of research, display and download of the available data. This objective is to provide a ready-to-use tool for all users who do not intend to connect directly to the services offered or to download (and therefore reutilize) the data: in this case we relied on the software Open Source MapStore. The open data platform is directly connected to the Geonetwork metadata catalogue that in turn automatically provide a real-time ingestion of datasets in geoportal. The Lamma open data infrastructure has been implemented by the use of CKAN software. All the datasets are made available according to the CC-BY license - Attribution Creative Commons. That choice will allow an easier federation with Open Tuscany (http://dati.toscana.it/), the open data portal of Tuscany Regional Government that until now has hosted, as supplementary task, some Lamma Consortium datasets. The open data infrastructure has been implemented thanks to the Life+IMAGINE European contribution and with the support of the Geosolutions company.
The opendata geoportal of the Lamma Consortium
Authors: Corongiu Manuela , Mari Riccardo , Ferrari Raffaella , Bottai Lorenzo , Grasso Valentina , Zabini Federica , Fibbi Luca , Grifoni Daniele , Tei Claudio , Pasi Franceso , Gozzini Bernardo , Giannecchini Simone
Published: January 2018

The new Lamma Open Data platform (http://dati.lamma.toscana.it) allows data download related to information delivered / managed by the Consortium, encouraging the reuse both at technical and legal level. The datasets, over 220, belong to the weather forecast and geospatial topics above all, but they are in continuous updating, both spatial and no spatial (such as administrative documentation). Lamma open data platform integrates in a harmonised interface, most off the spatial dataset already available through the Lamma geoportal (http://geoportale.lamma.rete.toscana.it/MapStore/public/), now available for download as open data. The particularity of meteorological information is their organization in models, archives and formats according to the type of information, source of acquisition and level of elaboration. These formats are not all functional or directly manageable in their entirety, as data to be made available and immediately accessible. The datasets therefore require a preliminary phase of evaluation and analysis of the contents to identify the most appropriate elements for publication via filters and elaborations that maintain the significance of the variables to be highlighted. A synergic and integrated infrastructure for spatial data has been carried out through open source softwares. The LaMMA Geoportal integrates, in a single simple but powerful interface, the functionalities of research, display and download of the available data. This objective is to provide a ready-to-use tool for all users who do not intend to connect directly to the services offered or to download (and therefore reutilize) the data: in this case we relied on the software Open Source MapStore. The open data platform is directly connected to the Geonetwork metadata catalogue that in turn automatically provide a real-time ingestion of datasets in geoportal. The Lamma open data infrastructure has been implemented by the use of CKAN software. All the datasets are made available according to the CC-BY license - Attribution Creative Commons. That choice will allow an easier federation with Open Tuscany (http://dati.toscana.it/), the open data portal of Tuscany Regional Government that until now has hosted, as supplementary task, some Lamma Consortium datasets. The open data infrastructure has been implemented thanks to the Life+IMAGINE European contribution and with the support of the Geosolutions company.
Integrating GIScience and Crop Science datasets: a study involving genetic, geographic and environmental data
Authors: Santos Roberto , Algar Adam , Field Richard , Mayes Sean
Published: January 2018

Sharing and reusing data in research is a welcome and encouraged practice since it maximises the scientific outcomes given limited financial, material and human resources. Interdisciplinary research is considered to benefit from this practice, uniting researchers and data from two or more disciplines to advance fundamental understanding or tackle problems whose solution is beyond the limit of an individual body of knowledge. Here we discuss the challenges of combining data across disciplines, focusing in particular on associating geographic location data with genetic data in the context of a project involving Crop Science and Geospatial Information Science disciplines. This project aims to improve understanding of how geographical, environmental and anthropocentric factors affect the genetic variation in a neglected and underutilised crop called Bambara groundnut.
QGIS geoprocessing model to simplify first level seismic microzonation analysis
Authors: Cosentino Giuseppe , Pennica Francesco
Published: January 2018

The seismic microzonation evaluate the seismic hazard at the local scale proposing to identify areas of territory characterized by homogeneous seismic behaviors. The first level of seismic microzoning has the purpose of defining the lithological properties and geometry of geological units that characterize these portions of territory (microzones). The scope of this work is to contribute to the creation of a geoprocessing methodology for topographical, geological, geophysical and geo-technical data aimed at level 1 seismic microzonation map drafting. A QGIS geoprocessing tool was designed to automate one of the analysis commonly performed for the creation of level 1 seismic microzonation maps, in particular to identify unstable zones as polygon features. The result is a polygon layer with areas prone to instability due to a slope value greater than 15 degrees.
From photo-geology to 3D geological models. An open source approach
Authors: Santangelo Michele , Marchesini Ivan , Mirabella Francesco , Bucci Francesco , Cardinali Mauro , Guzzetti Fausto
Published: January 2018

Three-dimensional modeling of geological bodies is a useful tool for multiple applications. Such tasks are usually accomplished starting from field-collected data, which typically suffer from intrinsic limitations such as accessibility constraints and punctuality of data collected. In this work, we explore the reliability of photo-geological analyses starting from aerial photo-interpretation in providing data useful to build up 3D geological models, and validate them using exploration wells data in a lignite rich area in Umbria, central Italy. The procedure that produces 3D models from photo-geological data is a three-step open source GIS procedure developed using python in GRASS GIS environment and GNU-Linux OS. We maintain that this procedure can have potential broad applications in Earth Sciences, including geological and structural analyses, up to the preliminary evaluation of potential reservoirs.
A workflow to integrate pre-processing, analysis and comparison of MALDI-ToF mass spectra in GeenaR
Authors: Del Prete Eugenio , Facchiano Angelo , Profumo Aldo , Angelini Claudia , Romano Paolo
Published: January 2018

Many large-scale proteomics studies have been performed in the last years, and this field of investigation is expanding up. If the analysis of any single spectrum can be performed by tools already made available along with the mass spectrometry (MS) instrumentation, comparison of spectra on a large scale represents a complex aspect of the analysis and interpretation of the study. Recently, we developed Geena 2, a tool for the automation of different steps in the MALDI/ToF MS data analysis. Integration of further tools can be performed, in order to improve some aspects of the whole workflow: the input of more data formats, the implementation of new algorithms for data cleaning, the graphical visualization and the reporting of the results, the use of advanced statistics for the comparison of mass spectra. For this motivations, we are now developing GeenaR, a new robust web tool for pre-processing, analysing, visualizing and comparing a set of MALDI-ToF mass spectra. The aim of this work is the presentation of on-going developments. The first results will be presented at the conference. GeenaR is being written in PHP, Perl (from Geena 2) and R languages. The R packages used are MALDIquant and MALDIquantForeign for mass spectra pre-processing and analysis, OrgMassSpecR for mass spectra comparison, dendextend and pvclust for clustering, and sda and crossval for variable selection. The system is being implemented in a LAMP (Linux, Apache, MySQL, PHP) environment. Proper interfaces between PHP on one side and perl and R on the other are then implemented. The aim of GeenaR is to provide to the users a wider range of statistical methods and graphical results, without making it more difficult to use for researchers with little expertise in programming. In order to achieve this goal, we have taken advantage of the availability of several packages, written in R language, for mass spectrometry statistical that are going to be integrated in the system. The complete pipeline of GeenaR includes some features already available in Geena 2 plus others under development thanks to the integration of the R environment. In fact, an original set of heuristic algorithms is already available in Geena 2. In particular, they are the identification of isotopic peaks by taking into account molecular weight of signals and the related trend of abundances; the normalization on the basis of a reference standard molecule; the peak selection by means of a threshold line, built by linearly interpolating values provided for given m/z values; the alignment, by selecting the nearest peaks, within a limited m/z difference, in the different mass spectra. By means of some R packages, GeenaR adds new statistical methods which are highly relevant for mass spectra analysis.

(Abstract truncated at 3,000 characters - the full version is available in the pdf file)
Microbial Transglutaminases investigations for selecting putative forms of industrial interest
Authors: Giordano Deborah , Facchiano Angelo
Published: January 2018

Motivation: Microbial Transglutaminase (MTGase) is an enzyme belonging to the class of transferases. Enzymes of this family (E.C. 2.3.2.13) catalyze post-translational modification in many proteins by acyl transfer reactions, deamidation and crosslinking (polymerisation) between protein intra- or inter-chain glutamine (acyl donor) and lysine (acyl acceptor) peptide residues. Even if the functions of transglutaminases in bacteria are unknown, now they are become an important tool for industry, but also for research and biotechnology fields. The interest in these enzymes is also focused on various biological processes and clinical applications as well as on their important role in the prevention of allergy and food intolerance, including celiac disease. Since the early 1990s, many MTGase-producing strains have been found, and production processes have been optimized. Nowadays the MTGase produced by Streptomyces mobaraensis is commercially available and widely used in biopolymers industry, in cosmetics, in clinical applications, in wool textiles, and in the food processing industry. We are interested to explore the existence of different MTGases that may maintain or improve the functional features of the mTGase currently in use. Methods: Databases searches have been performed in order to identify amino acid sequences of potential transglutaminases in microorganisms. NCBI databases, UniProt and specific microbial genome databases have been searched by querying the sequence from Streptomyces mobaraensis sequence and human tissue TGase, as reference to human form, by BLAST tools. Results: Microbial sequences annotated as “hypothetical transglutaminases” are largely present in databases. Searches based on the selected query sequences evidence a even more high number of MTGases. Among them, we find different characteristics in terms of length, presence of domains, position of amino acids with expectable functional roles. The results suggest a variety of forms within the microbial universe, and this encourage us for the search of novel proteins to be investigated for in vitro activity.