Global scale water stages from SAR imagery (GlosSARi) to support global flood forecasting

Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

Efficient and cost-effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the efficiency and cost-effectiveness by reducing the necessary amount of experiments and data points measured. (C) 2003 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Semantic-associative visual content labelling and retrieval: A multimodal approach

A novel framework referred to as collaterally confirmed labelling (CCL) is proposed, aiming at localising the visual semantics to regions of interest in images with textual keywords. Both the primary image and collateral textual modalities are exploited in a mutually co-referencing and complementary fashion. The collateral content and context-based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix of the visual keywords. A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. We introduce a novel high-level visual content descriptor that is devised for performing semantic-based image classification and retrieval. The proposed image feature vector model is fundamentally underpinned by the CCL framework. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval, respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicate that the proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models. (C) 2007 Elsevier B.V. All rights reserved.

Generalized beta generated distributions

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets.

Estimation of wind storm impacts over Western Germany under future climate conditions using a statistical-dynamical downscaling approach

A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses. Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.

Autoeficácia, características sociodemográficas e capacitação profissional: um estudo com servidores de uma Universidade Federal

Self-efficacy, the construct developed by Albert Bandura in 1977 and widely studied around the world, means the individual's belief in his own capacity to successfully perform a certain activity. This study aims to determine the degree of association between sociodemographic characteristics and professional training to the levels of Self-Efficacy at Work (SEW) of the Administrative Assistants in a federal university. This is a descriptive research submitted to and approved by the Ethics Committee of UFRN. The method of data analysis, in quantitative nature, was accomplished with the aid of the statistical programs R and Minitab. The instrument used in research was a sociodemographic data questionnaire, variables of professional training and the General Perception of Self-efficacy Scale (GPSES), applied to the sample by 289 Assistants in Administration. Statistical techniques for data analysis were descriptive statistics, cluster analysis, reliability test (Cronbach's alpha), and test of significance (Pearson). Results show a sociodemographic profile of Assistants in Administration of UFRN with well-distributed characteristics, with 48.4% men and 51.6% female; 59.9% of them were aged over 40 years, married (49.3%), color or race white (58%) and Catholics (67.8%); families are composed of up to four people (75.8%) with children (59.4%) of all age groups; the occupation of the mothers of these professionals is mostly housewives (51.6%) with high school education up to parents (72%) and mothers (75.8%). Assistants in Administration have high levels of professional training, most of them composed two groups of servers: the former, recently hired public servants (30.7%) and another with long service (59%), the majority enter young in career and it stays until retirement, 72.4% of these professionals have training above the minimum requirement for the job. The analysis of SEW levels shows medium to high levels for 72% of assistants in administration; low SEWclassified people have shown a high average of 2.7, considered close to the overall mean presented in other studies, which is 2.9. The cluster analysis has allowed us to say that the characteristics of the three groups (Low, Medium and High SEW) are similar and can be found in the three levels of SEW representatives with all the characteristics investigated. The results indicate no association between the sociodemographic variables and professional training to the levels of self-efficacy at work of Assistants in Administration of UFRN, except for the variable color or race. However, due to the small number of people who declared themselves in color or black race (4% of the sample), this result can be interpreted as mere coincidence or the black people addressed in this study have provided a sense of efficacy higher than white and brown ones. The study has corroborated other studies and highlighted the subjectivity of the self-efficacy construct. They are needed more researches, especially with public servants for the continuity and expansion of studies on the subject, making it possible to compare and confirm the results

Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Signal transduction-related responses to phytohormones and environmental challenges in sugarcane

Background: Sugarcane is an increasingly economically and environmentally important C4 grass, used for the production of sugar and bioethanol, a low-carbon emission fuel. Sugarcane originated from crosses of Saccharum species and is noted for its unique capacity to accumulate high amounts of sucrose in its stems. Environmental stresses limit enormously sugarcane productivity worldwide. To investigate transcriptome changes in response to environmental inputs that alter yield we used cDNA microarrays to profile expression of 1,545 genes in plants submitted to drought, phosphate starvation, herbivory and N-2-fixing endophytic bacteria. We also investigated the response to phytohormones (abscisic acid and methyl jasmonate). The arrayed elements correspond mostly to genes involved in signal transduction, hormone biosynthesis, transcription factors, novel genes and genes corresponding to unknown proteins.Results: Adopting an outliers searching method 179 genes with strikingly different expression levels were identified as differentially expressed in at least one of the treatments analysed. Self Organizing Maps were used to cluster the expression profiles of 695 genes that showed a highly correlated expression pattern among replicates. The expression data for 22 genes was evaluated for 36 experimental data points by quantitative RT-PCR indicating a validation rate of 80.5% using three biological experimental replicates. The SUCAST Database was created that provides public access to the data described in this work, linked to tissue expression profiling and the SUCAST gene category and sequence analysis. The SUCAST database also includes a categorization of the sugarcane kinome based on a phylogenetic grouping that included 182 undefined kinases.Conclusion: An extensive study on the sugarcane transcriptome was performed. Sugarcane genes responsive to phytohormones and to challenges sugarcane commonly deals with in the field were identified. Additionally, the protein kinases were annotated based on a phylogenetic approach. The experimental design and statistical analysis applied proved robust to unravel genes associated with a diverse array of conditions attributing novel functions to previously unknown or undefined genes. The data consolidated in the SUCAST database resource can guide further studies and be useful for the development of improved sugarcane varieties.

Uma Aplicação do Algoritmo QT Clustering para Marcação Colaborativa de Pontos Perigosos em Vias Públicas

This work proposes a collaborative system for marking dangerous points in the transport routes and generation of alerts to drivers. It consisted of a proximity warning system for a danger point that is fed by the driver via a mobile device equipped with GPS. The system will consolidate data provided by several different drivers and generate a set of points common to be used in the warning system. Although the application is designed to protect drivers, the data generated by it can serve as inputs for the responsible to improve signage and recovery of public roads

Aplicação do Sensoriamento Remoto e do Sistema de Informações Geográficas na Detecção de Manchas de Óleo na Região do Pólo de Exploração de Guamaré, R.N.

Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamaré, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamaré for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamaré. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier

Atitudes e conhecimentos de agentes comunitários de saúde e suas relações com idosos

OBJETIVO: Analisar as relações entre agentes comunitários de saúde e os cuidados prestados a idosos. MÉTODOS: Estudo transversal descritivo, com 213 agentes comunitários das 12 unidades básicas de saúde e das 29 unidades de saúde da família de Marília em 2010. Os dados foram coletados por meio de um questionário sociodemográfico, um instrumento de escala de atitudes em relação à velhice (Escala de Neri) e um questionário para avaliar conhecimentos gerontológicos (Questionário Palmore-Neri-Cachioni). Para a análise dos dados, foi utilizado o programa Statistical Package for the Social Sciences versão 16.0 para Windows. RESULTADOS: Predominaram no quadro dos agentes comunitários os adultos jovens, do sexo feminino, casados, escolaridade > 12 anos e inseridos na atividade há mais de seis anos. A maioria dos agentes relatou experiência com grupo de idosos e convivência intradomiciliar com pessoas dessa faixa etária, porém menos da metade referiu capacitação no tema envelhecimento. As avaliações positivas dos agentes quanto às atitudes perante a velhice ocorreram principalmente em aspectos como a sabedoria e generosidade dos idosos, porém foram marcantes as atitudes negativas para lentidão e rigidez. O número de acertos sobre gerontologia foi baixo e esteve diretamente associado às capacitações recebidas pelos agentes. Foram observados estereótipos em relação ao idoso, na medida em que muitos agentes os consideravam insatisfeitos e dependentes. CONCLUSIONES: Mudar as atitudes e melhorar o conhecimento que se tem acerca do envelhecimento é essencial no enfrentamento das demandas advindas dessa fase da vida. Qualificar a formação do agente comunitário de saúde é fundamental no cuidado ao idoso na atenção primária.

Diversity of ectoparasites in sheep flocks in São Paulo, Brazil

The occurrence of ectoparasites in sheep flocks is frequently reported but seldom quantified. Sheep production used to be a predominantly family activity in the state of São Paulo (Brazil), but it began to become a commercial activity in the past decade. Thus, information about the ectoparasites existing in sheep flocks has become necessary. The present data were obtained by means of questionnaires sent to all sheep breeders belonging to the 'Associação Paulista de Criadores de Ovinos' (ASPACO; São Paulo State Association of Sheep Breeders). Response reliability was tested by means of random visits paid to 10.6% of the respondents. Most of the properties (89.5%) reported the presence of one or more ectoparasites. Screw-worm (Cochliomyia hominivorax) was the most frequent ectoparasite (72.5%), followed by bot fly larvae (Dermatobia hominis, 45.0%), ticks (Amblyomma cajennense) and Boophilus microplus, 31.3%) and finally lice (Damalinia ovis, 13.8%). Combined infestations also occurred, the most common one being screw-worm with bot fly larvae (36.0%) followed by bot fly larvae with ticks (13.9%), screw-worm with ticks (9.3%), bot fly larvae with lice (6.9%), and ticks with lice (5.0%). The most common triple combination was screw-worm, bot fly larvae and ticks (12.8%). Breeds raised for meat or wool were attacked by bot fly larvae and ticks more often than other breeds. Lice were only absent from animals of indigenous breeds. The relationships among these ectoparasites are discussed in terms of sheep breeds, flock size, seasonality and the ectoparasitic combinations on the host.

The CMS experiment at the CERN LHC

The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 10(34)cm(-2)s(-1) (10(27)cm(-2)s(-1)). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4 pi solid angle. Forward sampling calorimeters extend the pseudo-rapidity coverage to high values (vertical bar eta vertical bar <= 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.