Processes Mapping in Cotton Culture to Traceability Creation

Traceability is a concept that arose from the need for monitoring of production processes, this concept is usually used in sectors related to food production or activities involving some kind of direct risk to people. Agribusiness in the cotton industry does not have a comprehensive infrastructure for all stages of the processes involved in production. Map and define the data to enable traceability of products is synonymous to delegate responsibilities for all involved in the production, the collection of aggregate data on cotton production is done in stages and specific pre-defined since the choice of the variety through the processing, the scope of this article specifically addresses the production of lint cotton. The paper presents a proposal based on service oriented architecture (SOA) for data integration processes in the cotton industry, this proposal provide support for the implementation of platform independent solutions.

A UML profile for the OBO relation ontology

Background: Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain. Results: We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO). Conclusions: The use of an established and well-known graphical language in the development of biomedical ontologies provides a more intuitive form of capturing and representing knowledge than using only text-based notations. The use of the profile requires the domain expert to reason about the underlying semantics of the concepts and relationships being modeled, which helps preventing the introduction of inconsistencies in an ontology under development and facilitates the identification and correction of errors in an already defined ontology.

Web Scale Discovery Systems – How to assess the best solution

The University of São Paulo has been experiencing the increase in contents in electronic and digital formats, distributed by different suppliers and hosted remotely or in clouds, and is faced with the also increasing difficulties related to facilitating access to this digital collection by its users besides coexisting with the traditional world of physical collections. A possible solution was identified in the new generation of systems called Web Scale Discovery, which allow better management, data integration and agility of search. Aiming to identify if and how such a system would meet the USP demand and expectation and, in case it does, to identify what the analysis criteria of such a tool would be, an analytical study with an essentially documental base was structured, as from a revision of the literature and from data available in official websites and of libraries using this kind of resources. The conceptual base of the study was defined after the identification of software assessment methods already available, generating a standard with 40 analysis criteria, from details on the unique access interface to information contents, web 2.0 characteristics, intuitive interface, facet navigation, among others. The details of the studies conducted into four of the major systems currently available in this software category are presented, providing subsidies for the decision-making of other libraries interested in such systems.

Circulating FABP4 Is a Prognostic Biomarker in Patients With Acute Coronary Syndrome but Not in Asymptomatic Individuals.

OBJECTIVE Blood-borne biomarkers reflecting atherosclerotic plaque burden have great potential to improve clinical management of atherosclerotic coronary artery disease and acute coronary syndrome (ACS). APPROACH AND RESULTS Using data integration from gene expression profiling of coronary thrombi versus peripheral blood mononuclear cells and proteomic analysis of atherosclerotic plaque-derived secretomes versus healthy tissue secretomes, we identified fatty acid-binding protein 4 (FABP4) as a biomarker candidate for coronary artery disease. Its diagnostic and prognostic performance was validated in 3 different clinical settings: (1) in a cross-sectional cohort of patients with stable coronary artery disease, ACS, and healthy individuals (n=820), (2) in a nested case-control cohort of patients with ACS with 30-day follow-up (n=200), and (3) in a population-based nested case-control cohort of asymptomatic individuals with 5-year follow-up (n=414). Circulating FABP4 was marginally higher in patients with ST-segment-elevation myocardial infarction (24.9 ng/mL) compared with controls (23.4 ng/mL; P=0.01). However, elevated FABP4 was associated with adverse secondary cerebrovascular or cardiovascular events during 30-day follow-up after index ACS, independent of age, sex, renal function, and body mass index (odds ratio, 1.7; 95% confidence interval, 1.1-2.5; P=0.02). Circulating FABP4 predicted adverse events with similar prognostic performance as the GRACE in-hospital risk score or N-terminal pro-brain natriuretic peptide. Finally, no significant difference between baseline FABP4 was found in asymptomatic individuals with or without coronary events during 5-year follow-up. CONCLUSIONS Circulating FABP4 may prove useful as a prognostic biomarker in risk stratification of patients with ACS.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

Assembling models of embryo development: Image analysis and the construction of digital atlases

Digital atlases of animal development provide a quantitative description of morphogenesis, opening the path toward processes modeling. Prototypic atlases offer a data integration framework where to gather information from cohorts of individuals with phenotypic variability. Relevant information for further theoretical reconstruction includes measurements in time and space for cell behaviors and gene expression. The latter as well as data integration in a prototypic model, rely on image processing strategies. Developing the tools to integrate and analyze biological multidimensional data are highly relevant for assessing chemical toxicity or performing drugs preclinical testing. This article surveys some of the most prominent efforts to assemble these prototypes, categorizes them according to salient criteria and discusses the key questions in the field and the future challenges toward the reconstruction of multiscale dynamics in model organisms.

INFOBIOMED: European Network of Excellence on Biomedical Informatics to support individualised healthcare

INFOBIOMED is an European Network of Excellence (NoE) funded by the Information Society Directorate-General of the European Commission (EC). A consortium of European organizations from ten different countries is involved within the network. Four pilots, all related to linking clinical and genomic information, are being carried out. From an informatics perspective, various challenges, related to data integration and mining, are included.

A novel motion tracking system for evaluation of functional rehabilitation of the upper limbs

Upper limb function impairment is one of the most common sequelae of central nervous system injury, especially in stroke patients and when spinal cord injury produces tetraplegia. Conventional assessment methods cannot provide objective evaluation of patient performance and the tiveness of therapies. The most common assessment tools are based on rating scales, which are inefficient when measuring small changes and can yield subjective bias. In this study, we designed an inertial sensor-based monitoring system composed of five sensors to measure and analyze the complex movements of the upper limbs, which are common in activities of daily living. We developed a kinematic model with nine degrees of freedom to analyze upper limb and head movements in three dimensions. This system was then validated using a commercial optoelectronic system. These findings suggest that an inertial sensor-based motion tracking system can be used in patients who have upper limb impairment through data integration with a virtual reality-based neuroretation system.

Sistema para integrar automáticamente datos públicos del NCBI en la plataforma de medicina personalizada p-medicine

En los últimos años ha habido un gran aumento de fuentes de datos biomédicos. La aparición de nuevas técnicas de extracción de datos genómicos y generación de bases de datos que contienen esta información ha creado la necesidad de guardarla para poder acceder a ella y trabajar con los datos que esta contiene. La información contenida en las investigaciones del campo biomédico se guarda en bases de datos. Esto se debe a que las bases de datos permiten almacenar y manejar datos de una manera simple y rápida. Dentro de las bases de datos existen una gran variedad de formatos, como pueden ser bases de datos en Excel, CSV o RDF entre otros. Actualmente, estas investigaciones se basan en el análisis de datos, para a partir de ellos, buscar correlaciones que permitan inferir, por ejemplo, tratamientos nuevos o terapias más efectivas para una determinada enfermedad o dolencia. El volumen de datos que se maneja en ellas es muy grande y dispar, lo que hace que sea necesario el desarrollo de métodos automáticos de integración y homogeneización de los datos heterogéneos. El proyecto europeo p-medicine (FP7-ICT-2009-270089) tiene como objetivo asistir a los investigadores médicos, en este caso de investigaciones relacionadas con el cáncer, proveyéndoles con nuevas herramientas para el manejo de datos y generación de nuevo conocimiento a partir del análisis de los datos gestionados. La ingestión de datos en la plataforma de p-medicine, y el procesamiento de los mismos con los métodos proporcionados, buscan generar nuevos modelos para la toma de decisiones clínicas. Dentro de este proyecto existen diversas herramientas para integración de datos heterogéneos, diseño y gestión de ensayos clínicos, simulación y visualización de tumores y análisis estadístico de datos. Precisamente en el ámbito de la integración de datos heterogéneos surge la necesidad de añadir información externa al sistema proveniente de bases de datos públicas, así como relacionarla con la ya existente mediante técnicas de integración semántica. Para resolver esta necesidad se ha creado una herramienta, llamada Term Searcher, que permite hacer este proceso de una manera semiautomática. En el trabajo aquí expuesto se describe el desarrollo y los algoritmos creados para su correcto funcionamiento. Esta herramienta ofrece nuevas funcionalidades que no existían dentro del proyecto para la adición de nuevos datos provenientes de fuentes públicas y su integración semántica con datos privados.---ABSTRACT---Over the last few years, there has been a huge growth of biomedical data sources. The emergence of new techniques of genomic data generation and data base generation that contain this information, has created the need of storing it in order to access and work with its data. The information employed in the biomedical research field is stored in databases. This is due to the capability of databases to allow storing and managing data in a quick and simple way. Within databases there is a variety of formats, such as Excel, CSV or RDF. Currently, these biomedical investigations are based on data analysis, which lead to the discovery of correlations that allow inferring, for example, new treatments or more effective therapies for a specific disease or ailment. The volume of data handled in them is very large and dissimilar, which leads to the need of developing new methods for automatically integrating and homogenizing the heterogeneous data. The p-medicine (FP7-ICT-2009-270089) European project aims to assist medical researchers, in this case related to cancer research, providing them with new tools for managing and creating new knowledge from the analysis of the managed data. The ingestion of data into the platform and its subsequent processing with the provided tools aims to enable the generation of new models to assist in clinical decision support processes. Inside this project, there exist different tools related to areas such as the integration of heterogeneous data, the design and management of clinical trials, simulation and visualization of tumors and statistical data analysis. Particularly in the field of heterogeneous data integration, there is a need to add external information from public databases, and relate it to the existing ones through semantic integration methods. To solve this need a tool has been created: the term Searcher. This tool aims to make this process in a semiautomatic way. This work describes the development of this tool and the algorithms employed in its operation. This new tool provides new functionalities that did not exist inside the p-medicine project for adding new data from public databases and semantically integrate them with private data.

Studio Integrato Geomorfologico-Geofisico dell'Area Epicentrale del Terremoto del 20 Maggio 2012 (Mw 5.9) in Emilia-Romagna

La Sequenza Sismica Emiliana del 2012 ha colpito la zona compresa tra Mirandola e Ferrara con notevoli manifestazioni cosismiche e post-sismiche secondarie, soprattutto legate al fenomeno della liquefazione delle sabbie e alla formazione di fratturazioni superficiali del terreno. A fronte del fatto che la deformazione principale, osservata tramite tecniche di remote-sensing, ha permesso di individuare la posizione della struttura generatrice, ci si è interrogati sul rapporto tra strutture profonde e manifestazioni secondarie superficiali. In questa tesi è stato svolto un lavoro di integrazione di dati a varia scala, dalla superficie al sottosuolo, fino profondità di alcuni chilometri, per analizzare il legame tra le strutture geologiche che hanno generato il sisma e gli effetti superficiali percepiti dagli osservatori. Questo, non solo in riferimento allo specifico del sisma emiliano del 2012, ma al fine di trarre utili informazioni in una prospettiva storica e geologica sugli effetti di un terremoto “tipico”, in una regione dove le strutture generatrici non affiorano in superficie. Gli elementi analizzati comprendono nuove acquisizioni e rielaborazioni di dati pregressi, e includono cartografie geomorfologiche, telerilevamenti, profili sismici a riflessione superficiale e profonda, stratigrafie e informazioni sulla caratterizzazione dell’area rispetto al rischio sismico. Parte dei dati di nuova acquisizione è il risultato dello sviluppo e la sperimentazione di metodologie innovative di prospezione sismica in corsi e specchi d’acqua continentali, che sono state utilizzate con successo lungo il Cavo Napoleonico, un canale artificiale che taglia ortogonalmente la zona di massima deformazione del sisma del 20 Maggio. Lo sviluppo della nuova metodologia di indagine geofisica, applicata ad un caso concreto, ha permesso di migliorare le tecniche di imaging del sottosuolo, oltre a segnalare nuove evidenze co-sismiche che rimanevano nascoste sotto le acque del canale, e a fornire elementi utili alla stratigrafia del terreno. Il confronto tra dati geofisici e dati geomorfologici ha permesso di cartografare con maggiore dettaglio i corpi e le forme sedimentarie superficiali legati alla divagazione fluviale dall’VIII sec a.C.. I dati geofisici, superficiali e profondi, hanno evidenziato il legame tra le strutture sismogeniche e le manifestazioni superficiali seguite al sisma emiliano. L’integrazione dei dati disponibili, sia nuovi che da letteratura, ha evidenziato il rapporto tra strutture profonde e sedimentazione, e ha permesso di calcolare i tassi geologici di sollevamento della struttura generatrice del sisma del 20 Maggio. I risultati di questo lavoro hanno implicazioni in vari ambiti, tra i quali la valutazione del rischio sismico e la microzonazione sismica, basata su una caratterizzazione geomorfologico-geologico-geofisica dettagliata dei primi 20 metri al di sotto della superficie topografica. Il sisma emiliano del 2012 ha infatti permesso di riconoscere l’importanza del substrato per lo sviluppo di fenomeni co- e post-sismici secondari, in un territorio fortemente eterogeneo come la Pianura Padana.

The use of future Internet technologies in the agriculture and food sectors:integrating the supply chain

The Future Internet is expected to greatly influence how the food and agriculture sector is currently operating. In this paper, we present the specific characteristics of the agri-food sector focusing on how information management in this area will take place under a highly heterogeneous group of actors and services, based on the EU SmartAgriFood project. We also discuss how a new dynamic marketplace will be realized based on the adoption of a number of specialized software modules, called “Generic Enablers” that are currently developed in the context of the EU FI-WARE project. Thus, the paper presents the overall vision for data integration along the supply chain as well as the development and federation of Future Internet services that are expected to revolutionize the agriculture sector.

Enhancing visibility in EPCIS governing agri-food supply chains via linked pedigrees

Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services (EPCIS) is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code (EPC). In this paper, the authors propose a framework that utilises events and EPCs in the generation of "linked pedigrees" - linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.

Supporting and Enhancing Research on Cultural Heritage in France: the PATRIMA Project

In this paper, we first overview the French project on heritage called PATRIMA, launched in 2011 as one of the Projets d'investissement pour l'avenir, a French funding program meant to last for the next ten years. The overall purpose of the PATRIMA project is to promote and fund research on various aspects of heritage presentation and preservation. Such research being interdisciplinary, research groups in history, physics, chemistry, biology and computer science are involved in this project. The PATRIMA consortium involves research groups from universities and from the main museums or cultural heritage institutions in Paris and surroundings. More specifically, the main members of the consortium are the two universities of Cergy-Pontoise and Versailles Saint-Quentin and the following famous museums or cultural institutions: Musée du Louvre, Château de Versailles, Bibliothèque nationale de France, Musée du Quai Branly, Musée Rodin. In the second part of the paper, we focus on two projects funded by PATRIMA named EDOP and Parcours and dealing with data integration. The goal of the EDOP project is to provide users with a data space for the integration of heterogeneous information about heritage; Linked Open Data are considered for an effective access to the corresponding data sources. On the other hand, the Parcours project aims at building an ontology on the terminology about the techniques dealing with restoration and/or conservation. Such an ontology is meant to provide a common terminology to researchers using different databases and different vocabularies.