Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

Plenária Virtual Permanente: em busca da interlocução entre os conselhos de saúde

A Plenária Virtual Permanente é um sistema de áudio e vídeo para redes digitais desenvolvido para conselhos de saúde do Brasil. O artigo aborda as discussões que subsidiaram a criação do dispositivo, a descrição do mesmo e os desafios para a inclusão digital no âmbito dessas instâncias de participação.

Virtual screening and computational optimization for the discovery of covalent prolyl oligopeptidase inhibitors with activity in human cells.

Our docking program, Fitted, implemented in our computational platform, Forecaster, has been modified to carry out automated virtual screening of covalent inhibitors. With this modified version of the program, virtual screening and further docking-based optimization of a selected hit led to the identification of potential covalent reversible inhibitors of prolyl oligopeptidase activity. After visual inspection, a virtual hit molecule together with four analogues were selected for synthesis and made in one-five chemical steps. Biological evaluations on recombinant POP and FAPα enzymes, cell extracts, and living cells demonstrated high potency and selectivity for POP over FAPα and DPPIV. Three compounds even exhibited high nanomolar inhibitory activities in intact living human cells and acceptable metabolic stability. This small set of molecules also demonstrated that covalent binding and/or geometrical constraints to the ligand/protein complex may lead to an increase in bioactivity.

Matrizes da linguagem e a organização virtual do conhecimento

Os signos e as linguagens foram investigados para a organização virtual do conhecimento por meio dos mecanismos de busca. Fundamentou-se na teoria das matrizes da linguagem-pensamento, postuladas por Santaella (2005), na qual se perscrutou as linguagens sonora, visual e verbal. O objetivo da investigação foi estabelecer uma categorização dos mecanismos de busca a partir da correspondência dessas matrizes da linguagem com a indexação virtual e o modus análogo de busca. Os resultados da investigação indicam ser adequada a categorização dos mecanismos de busca sob o critério dos paradigmas semiótico da linguagem em três matrizes, dado o seu modo de ser e sua operacionalidade, sendo eles baseados em conteúdos sonoros, visuais e verbais. Sinteticamente, a sintaxe é a representação do sonoro, a forma é a representação do visível e o discurso é a representação do conhecimento verbal.

Why microalgal biofuels won't save the internal combustion machine

Proponents of microalgae biofuel technologies often claim that the world demand of liquid fuels, about 5 trillion liters per year, could be supplied by microalgae cultivated on only a few tens of millions of hectares. This perspective reviews this subject and points out that such projections are greatly exaggerated, because (1) the pro- ductivities achieved in large-scale commercial microalgae production systems, operated year-round, do not surpass those of irrigated tropical crops; (2) cultivating, harvesting and processing microalgae solely for the production of biofuels is simply too expensive using current or prospective technology; and (3) currently available (limited) data suggest that the energy balance of algal biofuels is very poor. Thus, microalgal biofuels are no panacea for depleting oil or global warming, and are unlikely to save the internal combustion machine.

IMRT credentialing for prospective trials using institutional virtual phantoms: results of a joint European Organization for the Research and Treatment of Cancer and Radiological Physics Center project.

BACKGROUND AND PURPOSE: Intensity-modulated radiotherapy (IMRT) credentialing for a EORTC study was performed using an anthropomorphic head phantom from the Radiological Physics Center (RPC; RPCPH). Institutions were retrospectively requested to irradiate their institutional phantom (INSTPH) using the same treatment plan in the framework of a Virtual Phantom Project (VPP) for IMRT credentialing. MATERIALS AND METHODS: CT data set of the institutional phantom and measured 2D dose matrices were requested from centers and sent to a dedicated secure EORTC uploader. Data from the RPCPH and INSTPH were thereafter centrally analyzed and inter-compared by the QA team using commercially available software (RIT; ver.5.2; Colorado Springs, USA). RESULTS: Eighteen institutions participated to the VPP. The measurements of 6 (33%) institutions could not be analyzed centrally. All other centers passed both the VPP and the RPC ±7%/4 mm credentialing criteria. At the 5%/5 mm gamma criteria (90% of pixels passing), 11(92%) as compared to 12 (100%) centers pass the credentialing process with RPCPH and INSTPH (p = 0.29), respectively. The corresponding pass rate for the 3%/3 mm gamma criteria (90% of pixels passing) was 2 (17%) and 9 (75%; p = 0.01), respectively. CONCLUSIONS: IMRT dosimetry gamma evaluations in a single plane for a H&N prospective trial using the INSTPH measurements showed agreement at the gamma index criteria of ±5%/5 mm (90% of pixels passing) for a small number of VPP measurements. Using more stringent, criteria, the RPCPH and INSTPH comparison showed disagreement. More data is warranted and urgently required within the framework of prospective studies.

Insularity and the evolution of melanism, sexual dichromatism and body size in the worldwide-distributed barn owl.

Abstract Island biogeography has provided fundamental hypotheses in population genetics, ecology and evolutionary biology. Insular populations usually face different feeding conditions, predation pressure, intraspecific and interspecific competition than continental populations. This so-called island syndrome can promote the evolution of specific phenotypes like a small (or large) body size and a light (or dark) colouration as well as influence the evolution of sexual dimorphism. To examine whether insularity leads to phenotypic differentiation in a consistent way in a worldwide-distributed nonmigratory species, we compared body size, body shape and colouration between insular and continental barn owl (Tyto alba) populations by controlling indirectly for phylogeny. This species is suitable because it varies in pheomelanin-based colouration from reddish-brown to white, and it displays eumelanic black spots for which the number and size vary between individuals, populations and species. Females are on average darker pheomelanic and display more and larger eumelanic spots than males. Our results show that on islands barn owls exhibited smaller and fewer eumelanic spots and lighter pheomelanic colouration, and shorter wings than on continents. Sexual dimorphism in pheomelanin-based colouration was less pronounced on islands than continents (i.e. on islands males tended to be as pheomelanic as females), and on small islands owls were redder pheomelanic and smaller in size than owls living on larger islands. Sexual dimorphism in the size of eumelanic spots was more pronounced (i.e. females displayed much larger spots than males) in barn owls living on islands located further away from a continent. Our study indicates that insular conditions drive the evolution towards a lower degree of eumelanism, smaller body size and affects the evolution of sexual dichromatism in melanin-based colour traits. The effect of insularity was more pronounced on body size and shape than on melanic traits.

Assessment of emotional reactivity produced by exposure to virtual environments in patients with eating disorders

The aim of this study was to assess the usefulness of virtual environments representing situations that are emotionally significant to subjects with eating disorders (ED). These environments may be applied with both evaluative and therapeutic aims and in simulation procedures to carry out a range of experimental studies. This paper is part of a wider research project analyzing the influence of the situation to which subjects are exposed on their performance on body image estimation tasks. Thirty female patients with eating disorders were exposed to six virtual environments: a living-room (neutral situation), a kitchen with highcalorie food, a kitchen with low-calorie food, a restaurant with high-calorie food, a restaurant with low-calorie food, and a swimming-pool. After exposure to each environment the STAI-S (a measurement of state anxiety) and the CDB (a measurement of depression) were administered to all subjects. The results show that virtual reality instruments are particularly useful for simulating everyday situations that may provoke emotional reactions such as anxiety and depression, in patients with ED. Virtual environments in which subjects are obliged to ingest high-calorie food provoke the highest levels of state anxiety and depression.

The future of patient safety: Surgical trainees accept virtual reality as a new training tool.

BACKGROUND: The use of virtual reality (VR) has gained increasing interest to acquire laparoscopic skills outside the operating theatre and thus increasing patients' safety. The aim of this study was to evaluate trainees' acceptance of VR for assessment and training during a skills course and at their institution. METHODS: All 735 surgical trainees of the International Gastrointestinal Surgery Workshop 2006-2008, held in Davos, Switzerland, were given a minimum of 45 minutes for VR training during the course. Participants' opinion on VR was analyzed with a standardized questionnaire. RESULTS: Fivehundred-twenty-seven participants (72%) from 28 countries attended the VR sessions and answered the questionnaires. The possibility of using VR at the course was estimated as excellent or good in 68%, useful in 21%, reasonable in 9% and unsuitable or useless in 2%. If such VR simulators were available at their institution, most course participants would train at least one hour per week (46%), two or more hours (42%) and only 12% wouldn't use VR. Similarly, 63% of the participants would accept to operate on patients only after VR training and 55% to have VR as part of their assessment. CONCLUSION: Residents accept and appreciate VR simulation for surgical assessment and training. The majority of the trainees are motivated to regularly spend time for VR training if accessible.

How early can we predict Alzheimer's disease using computational anatomy?

Computational anatomy with magnetic resonance imaging (MRI) is well established as a noninvasive biomarker of Alzheimer's disease (AD); however, there is less certainty about its dependency on the staging of AD. We use classical group analyses and automated machine learning classification of standard structural MRI scans to investigate AD diagnostic accuracy from the preclinical phase to clinical dementia. Longitudinal data from the Alzheimer's Disease Neuroimaging Initiative were stratified into 4 groups according to the clinical status-(1) AD patients; (2) mild cognitive impairment (MCI) converters; (3) MCI nonconverters; and (4) healthy controls-and submitted to a support vector machine. The obtained classifier was significantly above the chance level (62%) for detecting AD already 4 years before conversion from MCI. Voxel-based univariate tests confirmed the plausibility of our findings detecting a distributed network of hippocampal-temporoparietal atrophy in AD patients. We also identified a subgroup of control subjects with brain structure and cognitive changes highly similar to those observed in AD. Our results indicate that computational anatomy can detect AD substantially earlier than suggested by current models. The demonstrated differential spatial pattern of atrophy between correctly and incorrectly classified AD patients challenges the assumption of a uniform pathophysiological process underlying clinically identified AD.

Educació virtual : Els dispositius mòbils com a eina d'ensenyament-aprenentatge

Aquest treball pretén aprofundir en com es poden aprofitar les noves eines tecnològiques per millorar l'entorn educatiu. Analitzarem de quina manera els dispositius mòbils poden ajudar a incrementar la motivació, la curiositat i la cooperació dels alumnes i, en definitiva, l'aprentatge.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.