Geospatial intelligence and visual classification of environmentally observed species in the future Internet

The rapid development of advanced smart communication tools with good quality and resolution video cameras,audio and GPS devices in the last few years shall lead to profound impacts on the way future environmentalobservations are conducted and accessed by communities. The resulting large scale interconnections of these"Future Internet Things" form a large environmental sensing network which will generate large volumes of qualityenvironmental observations and at highly localised spatial scales. This enablement in environmental sensing atlocal scales will be of great importance to contribute in the study of fauna and flora in the near future, particularlyon the effect of climate change on biodiversity in various regions of Europe and beyond. The Future Internet couldalso potentially become the de facto information space to provide participative real-time sensing by communitiesand improve our situation awarness of the effect of climate on local environments. In the ENVIROFI(2011-2013)Usage Area project in the FP7 FI-PPP programme, a set of requirements for specific (and generic) enablers isachieved with the potential establishement of participating community observatories of the future. In particular,the specific enablement of interest concerns the building of future interoperable services for the management ofenvironmental data intelligently with tagged contextual geo-spatial information generated by multiple operatorsin communities (Using smart phones). The classification of observed species in the resulting images is achievedwith structured data pre-processing, semantic enrichement using contextual geospatial information, and high levelfusion with controlled uncertainty estimations. The returned identification of species is further improved usingfuture ground truth corrections and learning by the specific enablers

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.ResultsHere, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.ConclusionWe conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.</p

The evolution of disaster early warning systems in the TRIDEC project

The TRIDEC project (Collaborative, Complex, and Critical Decision Processes in Evolving Crises) focuses on real-time intelligent information management in the Earth management domain and its long-term applications. It is funded under the European Union’s seventh Framework Programme (FP7). The TRIDEC software framework is applied in two application environments, which include industrial subsurface drilling (ISD) and natural crisis management (NCM). For each domain, three consecutive demonstrators with extended capabilities are developed and field-tested during the projects lifespan. This article focuses on the technical advances achieved by the light-, mid- and heavyweight NCM demonstrators for Tsunami Early Warning

Neuropsychiatric profiles of patients with juvenile myoclonic epilepsy treated with valproate or topiramate

In this cross-sectional study, the neuropsychiatric profiles of 42 patients with juvenile myoclonic epilepsy (JME) who were treated with valproate (VPA) or topiramate (TPM) in monotherapy were compared with the aim of verifying the relationship between cognitive dysfunction, psychiatric disorders, and factors related to epilepsy. Patients with JME taking VPA 500-1750 mg/day or TPM 50-175 mg/day were selected. for all patients, psychiatric profiles were evaluated with the Scheduled Clinical Interview, axes I and II (SCID I and SCID II), or the Brazilian version of the Schedule for Affective Disorders and Schizophrenia for School-Aged Children (K-SADS-PL). Neuropsychological measures included intellectual functions, attention, memory, executive functions, and language. Patients taking TPM exhibited worse neuropsychological performance on attention, short-term memory, processing speed, and verbal fluency functions related to frontal lobes, which may be dysfunctional in JME. Anxiety disorders were associated with lack of seizure control and having had more than 20 lifetime generalized tonic-clonic seizures. (c) 2006 Elsevier Inc. All rights reserved.UNIFESP, Escola Paulista Med, Dept Neurol, São Paulo, BrazilUNIFESP, Escola Paulista Med, Dept Neurol, São Paulo, BrazilWeb of Scienc

Novel Indicators for Identifying Critical INFRAstructure at RISK from Natural Hazards

e achievements of the European Union targets regarding energy and socio-economicsustainability are highly dependent on the way risks and vulnerabilities of European operatinginfrastructure networks and critical assets are minimised against natural extreme events. eINFRARISK project is developing reliable stress tests for European critical infrastructure usingintegrated modelling tools for decision-support. As a result it is possible to obtain higher infrastructurenetworks resilience to rare and low probability extreme events. INFRARISK advancesdecision making approaches and leads to beer protection of existing infrastructure whilst achievingmore robust strategies for the development of new ones. INFRARISK expands existing stresstest procedures and adapts them to critical land-based infrastructure, which may be exposed to orthreatened by natural hazards. Integrated risk mitigation scenarios and strategies are employed,using local, national and pan-European infrastructure risk analysis methodologies. ese take intoconsideration multiple hazards and risks with cascading impact assessments. e INFRARISK approachrobustly models spatio-temporal processes with propagated dynamic uncertainties in multiplerisk complexity scenarios. An operational framework with cascading hazards, impacts anddependent geospatial vulnerabilities is developed. is framework is a central driver to practicalsoware tools and guidelines that provide greater support to the next generation of European infrastructuremanagers to analyse and handle scenarios of extreme events. e minimisation of theimpact of such events by the supporting tools establishes optimum mitigation measures and rapidresponse. INFRARISK delivers a collaborative integrated platform where risk management professionalsaccess and share data, information and risk scenario results efficiently and intuitivel