bluuebunny/crossref_metadata_2025 huggingface dataset:
Transferability of the Assessment of Positive Occupation 15 in elderly people with physical disabilities
Authors: Noguchi Takuya , Kyougoku Makoto
Published: January 2018

Purpose

The present study aimed to verify the reliability and validity of the Assessment of Positive Occupation 15 (APO-15) in elderly individuals with physical disabilities in health science.

Methods

The study sample comprised 761 elderly individuals with physical disabilities residing in community dwellings, hospitals, and group homes. They completed the APO-15 and Kessler Psychological Distress Scale (K6) evaluations. We analyzed the psychometric properties of the APO-15, polyserial correlation coefficient, and average extracted variance, which included a confirmatory factor analysis (CFA), entropy, Cronbach’s α coefficient, Pearson’s product–moment correlation coefficient, item response theory (IRT), cut-off point, and latent rank values.

Results

The study outcome supported the APO-15, a 15-item, 4-factor model incorporating positive relationships, achievement, meaning, and engagement. The validity of this model was supported by various results; for example, each item score of polyserial correlation coefficient and entropy of APO-15 was the reference value was confirmed as being higher. The structural validity of APO-15 was assessed by CFA, which indicated a good model fit. Hypothesis testing revealed good values for the convergent and discriminant validity of the APO-15, and Cronbach’s α coefficient analysis revealed acceptable internal consistency. These results showed that the 4-factor structure of APO-15, which assumes has been established. Cut-off points for APO-15 of 51-point sensitivity (0.512) and specificity (0.704) yielded good results. The latent rank theory of APO-15 exhibited a good fit in all four rank values. The item reference profile suggested that an effective occupation promotes well-being.

Conclusion

The APO-15 exhibited good psychometric properties with respect to measuring positive occupations in individuals, including elderly individuals, with physical disabilities. This important tool will facilitate participation in occupations that promote daily well-being.
Object recognition using hybrid boosting method
Authors: Ashfaq Osama
Published: January 2018

Li (ICCV, 2005) proposed a novel generative/discriminative way to combine features with different types and use them to learn labels in the images. However, the mixture of Gaussian used in Li’s paper suffers greatly from the curse of dimensionality. Here I propose an alternative approach to generate local region descriptor. I treat GMM with diagonal covariance matrix and PCA as separate features, and combine them as the local descriptor. In this way, we could reduce the computational time for mixture model greatly while score greater 90% accuracies for caltech-4 image sets.
r.avaflow & r.randomwalk: two complementary and comprehensive open source GIS simulation tools for the propagation of rapid geophysical mass flows
Authors: Mergili Martin , Benedikt Matthias , Krenn Julia , Fischer Jan-Thomas , Pudasaini Shiva P
Published: January 2018

We present two GIS model applications for simulating the propagation of rapid geophysical mass flows: r.avaflow employs an advanced physically-based two phase flow model intended for in-detail case studies, r.randomwalk a conceptual model suitable for studies at various scales. Both tools are implemented in open source software environments serving for the needs of both research and practice. They offer a range of visualization, validation, parameter sensitivity analysis and parameter optimization functions. Some of the key functionalities of both tools are demonstrated for the Acheron rock avalanche in New Zealand.
A GRASS tool for the Sediment Delivery Ratio mapping
Authors: De Rosa Pierluigi , Cencetti Corrado , Fredduzzi Andrea
Published: January 2018

This work involves a tool implementation for evaluating Sediment Delivery Ratio (SDR) in a river basin, through GRASS GIS software. The definition of a spatially distributed value of SDR is a very important task as the sediment routing can affects solid transport in stream channels, water quality degradation, and frequency increase of natural disasters such as debris flows and mudflows. For such reason the SDR evaluation, coupled with GIS approach, has been extensively used in scientific literature. Geographic information systems provide a fundamental support for a better prediction of SDR, since it can consider the space variability of factors influencing the sediment routing processes. Actually a specific GIS module to estimate the spatial variability of SDR does not exist. We implemented a GRASS GIS module (in python language) called r.sdr where the sediment delivery ratio is evaluated by GIS procedure using several SDR equations available in literature. We applied the tool to the Feo Creek watershed, located in the Apennines area of northeastern Umbria (Italy).
City Focus: A web-based interactive 2D and 3D GIS application to find the best place in a city, using open data and open source software
Authors: Arias Muñoz Carolina , Corti Simone , Molinari Monia , Oxoli Daniele , prestifilippo Gabriele
Published: January 2018

City Focus is a web-based interactive 2D and 3D GIS application to find the best place in a city to live as well as to pass shorter staying. The user can select among different criteria and decide their importance by assigning weights to each of them. The application provides thematic maps displaying insights on the places which better fit the user’s preferences. The resulting map is computed through map algebra by means of Web Coverage Processing Service WCPS provided by RASDAMAN Database Management System. Data visualization is mainly based on NASA Web WorldWind open-source virtual globe. The app exploits exclusively open data as well as Free and Open Source Software (FOSS) for its implementation by enabling continuous improvements while minimizing development costs.
Exploiting observations and measurement data standard for distributed LTER-Italy freshwater sites. Water quality issues
Authors: Lanucara Simone , Carrara Paola , Oggioni Alessandro , Rogora Michela , Kamburska Lyudmila , Rossetti Giampaolo
Published: January 2018

Water quality is a multi-source, multi-purpose problem that needs exploiting observations, often taken by a number of heterogeneous bodies. This problem has been tackled within the Italian Long Term Ecological research network (LTER-Italy) in an experiment aimed at testing how ecological observations of mountain lakes water can be shared by OGC (Open Geospatial Consortium) standard services of the Sensor Web Enablement (SWE) initiative. A friendly and easy implementation of these services is fostered by the usage of the open source software Geoinformation Enabling Toolkit StarterKit ® (GET-IT). It has been used in the experiment to create SOS services, upload observations and create SensorML metadata of the involved sensors. This contribution describes the experiment and presents its results.
Summer Heat Risk Index: how to integrate recent climatic changes and soil consumption component
Authors: Crisci Alfonso , Congedo Luca , Morabito Marco , Munafò Michele
Published: January 2018

Face to the urban resiliency two major environmental threats are widely recognized: the increasing summer air temperatures and the soil consumption that affects a large number of city in Italy. The work have the goal to present preliminary the actual Heat Summer Risk defined by using Crichton's Risk Triangle (Crichton, 1999) on the second Italian level of administration (ADM2 - Province). For each administrative unit we have considered as hazard layer the most recent trend of summer air temperature assessed (1980-2014); the exposure layer is individuated by the amount of population living in each province and finally as vulnerable layer the mean degree of soil consumption expressed in percentage was considered. Thanks to these information Crichton's methodology are able to give a quantitative risk value index further classified in five risk class. Data sources was provided by several authoritative institutions : (i) ISPRA ( Italian National Institute for Environmental Protection and Research) that provide data about density of soil consumption for 2015 as reported in the Soil Consumption Report 2016; (ii) ECAD (European Climate Assessment \& Dataset) that gives detailed historical daily climatic layers (E-OBS 1950-2015 v 13.0); (iii) ISTAT ( Italian National Institute of Statistics) that provides the last updates on Italian population data (2016). The results was mapped and presented. All computations was carried out in R-STAT environment by using different library available for Spatial and Trend Analysis. Data and code are released in public repository.
Statistical methods for identifying sequence motifs affecting point mutations
Authors: Zhu Yicheng , Neeman Teresa M , Yap Von Bing , Huttley Gavin A
Published: January 2018

Mutation processes differ between types of point mutation, genomic locations, cells, and biological species. For some point mutations, specific neighbouring bases are known to be mechanistically influential. Beyond these cases, numerous questions remain unresolved including: what are the sequence motifs that affect point mutations? how large are the motifs? and, do they vary between samples? We present new log-linear models that allow explicit examination of these questions along with sequence logo style visualisation to enable identifying specific motifs. We demonstrate the utility of these methods by analysing human germline and malignant melanoma mutations. We recapitulate the known CpG effect and identify numerous novel motifs, including a highly significant motif associated with A→G mutations. We show that major effects of neighbourhood on germline mutation lie within ±2 of the mutating base. Models are also presented for contrasting the entire mutation spectra (the distribution of the different point mutations) and applied to the data. We show the spectra vary significantly between autosomes and X-chromosome, with a difference in T→C transition dominating. Analyses of malignant melanoma confirmed reported characteristic features of this cancer including strand asymmetry and markedly different neighbouring influences. The methods reported are made freely available as a Python library https://bitbucket.org/gavin.huttley/mutationmotif.
Statistical methods for identifying sequence motifs affecting point mutations
Authors: Zhu Yicheng , Neeman Teresa M , Yap Von Bing , Huttley Gavin A
Published: January 2018

Mutation processes differ between types of point mutation, genomic locations, cells, and biological species. For some point mutations, specific neighbouring bases are known to be mechanistically influential. Beyond these cases, numerous questions remain unresolved including: what are the sequence motifs that affect point mutations? how large are the motifs? and, do they vary between samples? We present new log-linear models that allow explicit examination of these questions along with sequence logo style visualisation to enable identifying specific motifs. We demonstrate the utility of these methods by analysing human germline and malignant melanoma mutations. We recapitulate the known CpG effect and identify numerous novel motifs, including a highly significant motif associated with A→G mutations. We show that major effects of neighbourhood on germline mutation lie within ±2 of the mutating base. Models are also presented for contrasting the entire mutation spectra (the distribution of the different point mutations) and applied to the data. We show the spectra vary significantly between autosomes and X-chromosome, with a difference in T→C transition dominating. Analyses of malignant melanoma confirmed reported characteristic features of this cancer including strand asymmetry and markedly different neighbouring influences. The methods reported are made freely available as a Python libraryhttps://bitbucket.org/pycogent3/mutationmotif.
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 Database 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 component 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 catalogs 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 catalog, 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, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. In this paper we will be focusing on the Lucene, a powerful Javabased search library.

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

Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, built on an open source stack. The system implements an OGC catalogue based on pycsw, to provide access to metadata in a standard way, and uses a search engine based on Solr/Lucene, to provide 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 Athanasios Tom , Mwenda Ntabathia 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.
Mapping and analysis of pressures on water resources from agriculture to target water and agriculture policies
Authors: Ferrigno Marianna , Martello Marco , Giannerini Gianfranco , Manganiello Veronica , Quarato Daniela , Antinoro Chiara , Capone Simona , Pepe Antonio , Zucaro Raffaella
Published: January 2018

A recent work carried out by CREA (ex INEA) compared spatial analysis of the main problems concerning the use of water resources for irrigation in Italian River basin districts (RBD) with the policy measures for water resources and agriculture, in order to verify the relevance of planning to address specific regional sensitivities. The bases for the policy analysis was River basin management plans (RBMPs), in updating, and proposal of Regulation for rural development, not yet approved at the time. The spatial and statistical analysis was done, for each Italian RBD, through cluster analysis method using specific indicators, calculated using quantifiable and comparable public database (ISTAT, ISPRA, SIGRIAN) and representing qualitative and quantitative pressures on waters and environmental constraint. The aim of this work is the updating of spatial analysis, with reference to recently approved RBMPs and new regional RDPs 2014-2020, based on the Regulation for rural development 1305/2013. The update of the work involves the use of additional indicators through the analysis of new data made available by the updating of RBMPs such as, for example, the qualitative and quantitative status of water bodies. Moreover, it is now possible to know the real measures put in place by each RDP, instead of possible measures to activate, and so to verify the real match between policies. Finally, the cluster analysis was conducted at national level instead of at RBD level, so that the magnitude of indicators is the same for all RBD and, then, comparable. The preliminary results of the updating, show a different variability of clusters trough national territory, with lower variability in Central and Southern Italy and higher variability in Northern Italy.
Integrated method for cities air temperature estimation
Authors: Bernard Jérémy , Musy Marjorie , Calmet Isabelle , Bocher Erwan , Kéravec Pascal
Published: January 2018

Urban Heat Island (UHI) is defined as the air temperature difference between the city and its surrounding areas. This phenomenon varies spatially (depending on the type of urban fabric constituting each neighborhood) and temporally (depending on the time of the day, on the season and on the weather conditions). This contribution proposes a methodology to model the UHI spatially and temporally using simple models built with free and open sources softwares (orbisGIS and python language). Ten air temperature sensors have been implemented in several neighborhoods of the Nantes urban area (a west coast french conurbation). The difference of UHI is observed and modeled for each of those sites. Spatial differences are modeled according to geographical indicators characterizing the urban surroundings of each temperature station. Temporal variations are modeled according to weather conditions (such as wind speed, solar radiations, etc.) for different time scales : diurnal and nocturnal differences, daily variations and seasonal variations. The objective is to create a method which may be applied for any city in France. Geographical indicators are then calculated with OrbisGIS software from geographical data which are homogeneous and available at the french territory scale. Wheather conditions are recorded by MeteoFrance stations, which follow the same standard for the measurement of climatic parameters all around France. Climatic data analysis and modeling are performed with Python language using libraries such as Pandas and StatsModels. Modeled established according to the Nantes temperature dataset are verificated according to new air temperature networks implemented in the city of Nantes as well as other cities of west France (Angers, La Roche-sur-Yon).
Weather events identification in social media streams: tools to detect their evidence in Twitter
Authors: Grasso Valentina , Zaza Imad , Zabini Federica , Pantaleo Gianni , Nesi Paolo , Crisci Alfonso
Published: January 2018

Severe weather impact identification and monitoring through social media data is a good challenge for data science. In last years we assisted to an increase of natural disasters, also due to climate change. Many works showed that during such events people tend to share specific messages by of mean of social media platforms, especially Twitter. Not only they contribute to"situational" awareness also improving the dissemination of information during emergency but can be used to assess social impact of crisis events. We present in this work preliminary findings concerning how temporal distribution of weather related messages may help the identification of severe events that impacted a community. Severe weather events are recognizable by observing the synchronization of twitter streams volumes concerning extractions by using different but semantically graduate terms and hash-tags including the specific containing geo-content names. Impacting events seems immediately recognizable by graphical representation of weather streams and when the time-line show a specific parallel-wise pattern that we named "Half Onion Shape". Different but weather semantically linked twitter streams could exhibits different magnitude, in order to their term popularity, but they show, when a weather event occurs, the same temporal relative maximum. In reason of to these interesting indications, that needs to be confirmed through more deeper analysis, and of the great use of social media, as Twitter, during crisis events it's becoming fundamental to have a suite of suitable tools to monitor social media data. For Twitter data a comprehensive suite of tools is presented: the DISIT-Twitter Vigilance Platform for twitter data retrieve,management and visualization.
QGIS plugin or web app? Lessons learned in the development of a 3D georeferencer
Authors: Produit Timothee , Ingensand Jens , Milani Gillian
Published: January 2018

Collections of historical images are currently being scanned to stop their degradation and to enable a numeric exploitation. These collections have a high cultural, artistic and scientific value. However, they are not fully exploited because the photographs do not have a georeference (geographic information cannot be extracted from the picture) and are poorly labeled (makes searching in a database inefficient). During the last years, we developed a QGIS plugin and a web app dedicated to the georeferencing of photographs and the linking of images with spatial data. In this paper, we discuss the technologies involved and compare both implementations. The results suggest that both approaches are valuable but provide different advantages in term of target users and development effort.
Oscillation of water table due to rainfall: an experience of modeling in GIS
Authors: Federici Bianca , Bovolenta Rossella , Balestrero Dario , Passalacqua Roberto V
Published: January 2018

A physically-based Integrated Hydrological-Geotechnical model (IHG) able to assess the rainfall-induced landslide susceptibility was developed, refined and applied in GIS environment along the past years (Passalacqua 2002; Federici et al. 2014; Bovolenta et al. 2016), showing its reliability. It is a useful instrument to landslide susceptibility evaluations and land-use planning over wide areas. The present paper focuses on the modeling of water table oscillation due to rainfall, comparing different hydrological models.
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. At the moment the Database is a main collection of more than 200 weather forecast layers, together with other basic geospatial layers (NDVI, LandCoverChangeFlows, Landslides, Natural Risk Zones), that are in continuous updating. LaMMA open data platform integrates in a harmonised interface, most of the spatial dataset already available through the LaMMA geoportal (http://geoportale.lamma.rete.toscana.it/MapStore/public/), making them available for a direct download with a specific licence of use.
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 anthropogenic factors affect the genetic variation in a neglected and underutilised crop called Bambara groundnut.
Are controversies in science driven by randomness and misbeliefs?
Authors: Siwiak Marlena , Wyszomirski Tomasz , Zielenkiewicz Piotr
Published: January 2018

Recent years have brought about the realisation of an irreproducibility crisis in science, which may have numerous causes, including common standards of statistical analysis. For decades, the methodological paradigm of null hypothesis significance testing (NHST) has remained under harsh, yet rather ineffective criticism. Here, we show that the vast majority of contradictions between the results of distinct studies may be fictitious, resulting from misbeliefs about NHST. To exemplify how they appear, we provide extensive reanalyses of results from high-profile literature and reveal statistical uncertainties that customarily remained obscured by the NHST paradigm. Widespread awareness of these uncertainties accompanied with quantitative interpretation of the results is the first step in assessing the actual scale of the irreproducibility problem and eradicating it.
Demonstration of an open source platform for reproducible comparison of predictive models
Authors: Bokde Neeraj , Kulat Kishore
Published: January 2018

This paper discusses about a tool PredictTestbench, which is an R package which provides a testbench to do comparison of prediction methods. This package compares a proposed time series prediction method with other default methods like Autoregressive integrated moving average (ARIMA) and Pattern Sequence based Forecasting (PSF). The testbench is not limited to these methods. It allows user to add or remove multiple numbers of methods in the existing methods in the study. By default, testbench compares different imputation methods considering different error metrics RMSE, MAE or MAPE. Along with this, it facilitates user to add new error metrics as per requirements. The simplicity of the package usage and significant reduction in efforts and time consumption in state of art procedure, adds valuable advantage to it. The aim of the testbench is reduce the efforts for coding, experiments on output visualization and time for different steps involved in such study. This paper explains the use of all functions in PredictTestbench package with the demonstration of examples.
Beliefs propagation in log domain: a neural inspired algorithm for machine learning
Authors: Ashfaq Osama
Published: January 2018

In this paper, we consider a variant of belief propagation algorithm in a tree graphical model where computations are carried out in the negative log-likelihood domain. Unlike the min-product algorithm, our goal is not limited to estimating the mode of the marginal distribution. We would like to obtain the entire marginal distribution as the sum-product algorithm does. We applied the algorithm to learn effective users features for A/B testing. We discussed scalable extension to the proposed algorithm for processing large amount of data.The primary goal of a parallel program is to reduce running time comparing to the sequential program by taking full advantage of computing power of multiprocessors. Threads are widely used in the implementation of parallelism in shared memory multiprocessor architectures. For UNIX/LINUX systems, pthread is the POSIX standard threading interface, which provides support a standardized way for creating and synchronizing threads. Here we presents how pthreads can be used successfully in parallelizing real scientific problems. We will illustrate it by implementing the shared memory parallel version of Jacobi iteration algorithm. Results of performance tests showed that the speedups can be up to p where p is the number of processors.
Molecular effects of microcystin-LA toxicity in Tilapia (Oreochromis niloticus)
Authors: Moreira Daniel A , Soares Raquel , Valente Richard H , Bebianno Maria João A , de Freitas Rebelo Mauro
Published: January 2018

A comprehensive understanding of microcystin (MC) effects and mode(s) of action(s) on aquatic biota has not been achieved yet. In the present study, Nile tilapia (Oreochromis niloticus) were sub-lethally exposed to the microcystin analogue MC-LA for 12, 24, 48 and 96 hours, and gene expression of PP1, PP2A, GST and actin were analyzed by quantitative PCR. Moreover, PP2A protein abundance profile was established by immunoblotting, while its biological function integrity was checked by a phosphatase enzymatic assay. PP2A activity was significantly reduced by MC-LA, indicating that MC acts as a PP2A inhibitor, similarly to what occurs in mammals. However, the positive (9.1-fold after 12h) feedback mechanism induced by PP2A gene, after exposure to sub-lethal MC-LA dose (1,000 µg.kg-1), did not counteract the complete PP2A catalytic activity inhibition that occurred concomitantly. A weaker inflammatory response in fish compared to mammals may be the reason why O. niloticus is able to tolerate such high concentrations of MC-LA when compared to mice.
Open source GIS for geological field mapping: research and teaching experience
Authors: De Donatis Mauro , Alberti Mauro , Cesarini Carlo , Menichetti Marco , Susini Sara
Published: January 2018

The journey to digital field mapping in the geosciences academic world is far from ending. When it started some years ago, many geoscientists were skeptical about the use of digital tools in the field. Nowadays, the work done in this decade shows clearly that this will be the way of working in the future. The traditional way of mapping can be incorporated and improved in the digital survey. Many of the previously existing limitations have been overcome. Part of this process is possible thanks to the choice of open source tools.
Using ontologies and semantic similarity measures for prioritization of gene regulatory networks
Authors: Milano Marianna , Guzzi Pietro , Cannataro Mario
Published: January 2018

Omics sciences are widely used to analyze diseases at a molecular level. Usually, results of omics experiments are sets of candidate genes potentially involved in different diseases. The interpretation of results and the filtering of candidate genes or proteins selected in an experiment is a challenge in some scenarios. This problem is particularly evident in clinical environments in which researchers are interested in the behavior of few molecules related to some specific disease while results may contains thousands of data and have very relevant dimensions. The filtering requires the use of domain-specific knowledge that is usually encoded into ontologies. Consequently, to filter out false positive genes, different approaches for selecting genes have been introduced. Such approaches are often referred to as Gene prioritization methods. They aim to identify the most related genes to a disease among a larger set of candidates genes, through the use of computational methods. We implemented GoD (Gene ranking based On Diseases), an algorithm that ranks a given set of genes based on ontology annotations. The algorithm orders genes by the semantic similarity computed with respect to a disease among the annotations of each gene and those describing the selected disease.The current version of GoD enables the prioritization of a list of input genes for a selected disease. It uses HPO (Human Phenotype Ontology), GO (Gene Ontology), and DO (Disease Ontology) ontologies for the calculation of the ranking. It takes as input a list of genes or gene products annotated with GO Terms, HPO Terms, DO Terms and a selected disease described regarding annotation of GO, HPO or DO (user may also provide novel annotations). It produces as output the ranking of those genes with respect of the input disease. Package consists of three main functions: hpoGoD (for HPO based prioritization), goGoD (for GO based prioritization), and doGoD (for DO based prioritization). We tested GoD on Gene Regulatory Networks (GRNs). Biological network inference aims to reconstruct network of interactions (or associations) among biological genes starting from experimental observations. We selected three expression datasets: Dataset 1 (GDS3285) , related to breast cancer disease; Dataset 2 (GDS5072), related to prostate cancer disease; and Dataset 3 (GDS5093), related to Dengue virus (DENV) infection. Initially, experimental data are given as input to five GRN inference algorithms, i.e. ARACNE, CLR, MRNET, GENIE3 and GGM, to produce 5 inferred GRN networks. For each inferred GRN, GoD receives as input the list of top genes and produces for each gene a semantic similarity value on a selected disease considering one of the previous ontologies (e.g. Disease Ontology). For each GRN, the genes are ranked and reordered on the basis of the computed semantic similarity and are compared allowing to rank each GRN inference method with respect to the initially selected disease.
Building size modelization
Authors: Antoni Arlette , Dhorne Thierry
Published: January 2018

New challenges in the efficient management of cities depend on a deep knowledge of their inner structures. It is therefore very important to have access to reliable models of cities characteristics and organization. This paper aims at providing and validating a stochastic modelization based on statistical data of buildings parameters which can be useful as an entry for many other models considered in a wide range of fields where buildings structure is a main factor of a thorough modelization of cities.
Multi-scale ecological filters shape the crayfish microbiome
Authors: Skelton James , Geyer Kevin M , Lennon Jay T , Creed Robert P , Brown Bryan L
Published: January 2018

Communities of symbiotic microbes obtained from the environment are an integral component of animal fitness and ecology. Thus a general and practical understanding of the processes that drive microbiome assembly and structure are paramount to understanding animal ecology, health, and evolution. We conceptualized a series of ecological filters that operate at the environment, host, and host tissue levels during microbiome assembly and discuss key ecological processes that structure animal microbiomes at each level. We conducted a survey of crayfish across four sites within the contiguous range of the of stream-inhabiting crayfish Cambarus sciotensis in western Virginia, USA, to characterize multiscale variation in the crayfish microbiome. We also conducted an in situ experiment to assess local drivers of microbial diversity on the closely related Cambarus chasmodactylus. We used a combination of DNA fingerprinting and next-generation sequencing to characterize microbiome diversity and composition from crayfish carapaces and gills to identify key filters affecting microbiome structure. Field survey showed that local environment and host tissues interact to create patterns of microbial diversity and composition, but the strongest effects on microbial community structure were observed at the level of host tissue. Our field experiment confirmed strong effects of host tissue, and also showed that a metazoan ectosymbiont which feeds on biofilms (Annelida; Branchiobdellida) had significant effects on microbial composition of the host carapace. Crayfish carapaces were colonized by diverse and taxonomically even microbial communities that were similar to, and correlated with, microbial communities of the ambient environment. Conversely, crayfish gills were colonized by less diverse communities and dominated by two families of bacteria with potentially significant functional roles: Comamonadaceae and Chitinophagaceae. Our results suggest that microbial assembly of the carapace is driven by external biotic and abiotic processes, whereas assembly on the gills appears to be coupled to host biology that favors interactions with few specific taxa. Our work shows how multi-scale studies of symbiont community assembly provide valuable insights into how the animal microbiome is structured under conditions of natural complexity and help identify other symbiont taxa, i.e., the branchiobdellidans, that may further influence microbiome assembly and structure.
OnoM@p : a Spatial Data Infrastructure dedicated to noise monitoring based on volunteers measurements
Authors: Bocher Erwan , Petit Gwendall , Fortin Nicolas , Picaut Judicaël , Guillaume Gwenaël , Palominos Sylvain
Published: January 2018

The present paper proposes an ideal Spatial Data Infrastructure (SDI) dedicated to noise monitoring based on volunteers measurements. Called OnoM@P, it takes advantage of the geospatial standards and open source tools to build an integrated platform to manage the whole knowledge about a territory and to observe its dynamics. It intends also to diffuse good practices to organize, collect, represent and process geospatial data in field of acoustic researches. OnoM@p falls within the framework of the Environmental Noise Directive (END) 2002/49/CE. The system relies on the NoiseCapture Android application developed for allowing each citizen to estimate its own noise exposure with its smartphone.
The individual and social drivers of primate innovation
Authors: Hopper Lydia M
Published: January 2018

How does nonhuman primate innovation compare to our own? Many primates innovate, for example to get otherwise inaccessible food or to increase their social standing, and nonhuman primate innovation can be broken into three component steps. It begins with the initial invention, which is then transmitted to other members of the inventor’s group, and is then adopted by other individuals and maintained within the society. These three steps – invention, transmission, and maintenance – are all required for innovation and in this review, I discuss the factors (social, environmental, and cognitive) that influence each step. I also highlight the comparable and contrasting features between human and nonhuman primate innovation. In contrast to human innovations, primate innovations are relatively simple and are typically self-serving. Nonhuman primates do not invent new products explicitly for the use of others (although group members certainly copy others' innovations) and nor are their inventions artistic or abstract in nature. Intriguingly, although chimpanzees and other nonhuman primates appear to be expert at copying others’ inventions, there is far less evidence of their ability to build upon others’ inventions (i.e., to show cumulative culture). At the core of our complex cultural world is the fidelity with which we copy others and our specialism at building upon the ideas of others. Thus, it is the cumulative nature of our innovative process that has created our complex material cultural world and is a key difference between how we innovate, learn and transmit knowledge, and how our chimpanzee cousins copy one another. Another difference is our ability to work collaboratively in teams to innovate and develop new technologies, as well as our potential to cooperate in an altruistic way that allows for planning for future generations. In conclusion, perhaps primate innovation can be most usefully likened to human ‘user innovators’ who typically innovate products or techniques to fill a personal need, rather than by being driven to create a product to go to market.
What is done and what has to be done in Lamiaceae, a review of phylogenetics
Authors: Zahra Nadia B , Shinwari Zabta K
Published: January 2018

The most recent classification proposed by Harley et al. in 2004 recognized seven subfamilies within the family Lamiaceae (Symphorematoideae, Viticoideae, Ajugoideae, Prostantheroideae, Scutellarioideae, Lamioideae and Nepetoideae). Symphorematoideae (formerly as part of Verbenaceae) is recognized as a subfamily of Lamiaceae for the first. Recognition of Viticoideae is one of the major modifications introduced in Harley’s treatment but yet it is the least satisfactory circumscribed subfamily which appeared to be clearly non-monophyletic. Subsequent studies based on molecular analysis also reported the non-monophyly of Viticoideae. New combinations are proposed in later studies at the generic level in subfamily Ajugoideae and Prostantheroideae. Suprageneric relationships among the Lamioideae remained poorly understood providing no tribal ranks in the Harley’s classification. Therefore, new tribes have been erected in the recent investigations to reflect improved phylogenetic undersanding of the Lamioideae. Subtribal delimitation of Mentheae (Nepetoideae) according to recent studies is not congruent with the Harley’s and new subtribes are recommended to establish the monophyly of Mentheae. Although the clade structure is relatively well established in the Lamiaceae, but tribal compositions remain unclear and needs to be further investigated to transform their taxonomy into a more ‘natural’ classification.
MetaCRAST: Reference-guided extraction of CRISPR spacers from unassembled metagenomes
Authors: Moller Abraham G , Liang Chun
Published: January 2018

Summary: Clustered regularly interspaced palindromic repeat (CRISPR) systems are prokaryotic adaptive immune systems against phage infection. CRISPR spacer sequences can provide valuable ecological insights by linking environmental viruses to their microbial hosts. Despite this importance, metagenomic CRISPR detection remains a major challenge. Here we present a reference-guided CRISPR detection tool (Metagenomic CRISPR Reference-Aided Search Tool - MetaCRAST) that constrains searches based on user-specified direct repeats. These DRs could be expected from assembly or taxonomic profiles of metagenomic sequence data. Our evaluation shows MetaCRAST improves CRISPR spacer detection in real metagenomes compared to de novo detection methods. Simulations show it performs better than comparable tools when analyzing Illumina metagenomes.

Availability and implementation: MetaCRAST is implemented in Perl and takes metagenomic sequence reads and direct repeat queries in FASTA format as input. It is freely available for download at https://github.com/molleraj/MetaCRAST .
MetaCRAST: Reference-guided extraction of CRISPR spacers from unassembled metagenomes
Authors: Moller Abraham G , Liang Chun
Published: January 2018

Clustered regularly interspaced short palindromic repeat (CRISPR) systems are the adaptive immune systems of bacteria and archaea against viral infection. While CRISPRs have been exploited as a tool for genetic engineering, their spacer sequences can also provide valuable insights into microbial ecology by linking environmental viruses to their microbial hosts. Despite this importance, metagenomic CRISPR detection remains a major challenge. Here we present a reference-guided CRISPR spacer detection tool (Metagenomic CRISPR Reference-Aided Search Tool - MetaCRAST) that constrains searches based on user-specified direct repeats (DRs). These DRs could be expected from assembly or taxonomic profiles of metagenomes. We compared the performance of MetaCRAST to those of two existing metagenomic CRISPR detection tools – Crass and MinCED – using both real and simulated acid mine drainage (AMD) and enhanced biological phosphorus removal (EBPR) metagenomes. Our evaluation shows MetaCRAST improves CRISPR spacer detection in real metagenomes compared to the de novo CRISPR detection methods Crass and MinCED. Evaluation on simulated metagenomes show it performs better than de novo tools for Illumina metagenomes and comparably for 454 metagenomes. It also has comparable performance dependence on read length and community composition, run time, and accuracy to these tools MetaCRAST is implemented in Perl, parallelizable through the Many Core Engine (MCE), and takes metagenomic sequence reads and direct repeat queries (FASTA or FASTQ) as input. It is freely available for download at https://github.com/molleraj/MetaCRAST.
EvoPER -- An R package for applying evolutionary computation methods in the parameter estimation of individual-based models implemented in Repast
Authors: Prestes García Antonio , Rodríguez-Patón Alfonso
Published: January 2018

Individual-based models are complex and they normally have an elevated number of input parameters which must be tuned in order to reproduce the experimental or observed data as accurately as possible. Hence one of the weakest points of such kind of models is the fact that rarely the modeler has the enough information about the correct values or even the acceptable range for the input parameters. Therefore, several parameter combinations must be checked to find an acceptable set of input factors minimizing the deviations of simulated and observed data. In practice, most of times, is computationally unfeasible to traverse the complete search space to check all parameter combination in order to find the best of them. That is precisely the kind of combinatorial problem suitable for evolutionary computation techniques. In this work we present the EvoPER, an R package for simplifying the parameter estimation using evolutionary computation techniques. The current version of EvoPER includes implementations of PSO, SA and ACO algorithms for parameter estimation of Repast models.