Identifying the urban communities of New York City using bikeshare data from NYC citibike

This study identifies a measure of the cultural importance of an area within a city. It does so by making use of origindestination trip data and the bike stations of the bike share system in New York City as a proxy to study the city. Rarely is movement in the city studied at such a small scale. The change in strength of the similarity of movement between each station is studied. It is the first study to provide this measure of importance for every point in the system. This measure is then related to the characteristics which make for vibrant city communities, namely highly mixed land use types. It reveals that the spatial pattern of important areas remains constant over differing time periods. Communities are then characterised by the land uses surrounding these stations with high measures of importance. Finally it identifies the areas of global cultural importance alongside the areas of local importance to the city.

Distribution of extended-spectrum β-lactamase types in a Brazilian tertiary hospital

INTRODUCTION: Epidemiological data on the prevalence of extended-spectrum β-lactamases (ESBLs) are scarce in Brazil despite the fact that these data are essential for empirical treatment and control measures. The objective of this study was to evaluate the prevalence of different ESBLs by type and distribution in a tertiary hospital in southern Brazil. METHODS: We evaluated 1,827 enterobacterial isolates between August 2003 and March 2008 isolated from patients at a tertiary hospital. Samples were identified using a Vitek automated system and were confirmed by biochemical testing. The identified ESBL strains were characterized by phenotypic methods, polymerase chain reaction (PCR), and sequencing. Genetic similarities were evaluated by pulsed-field gel electrophoresis. RESULTS: It was 390 (21.3%) ESBL-producing strains, which expressed the ESBLs CTX-M (292), SHV (84), CTX and SHV (10), TEM (2), and PER (2). CONCLUSIONS: The prevalence of ESBL-expressing strains was high, especially in Klebsiella pneumoniae and Enterobacter spp. CTX-M was the predominant type of ESBL observed, and its genetic variability indicates a polyclonal distribution.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

The residual effect of deltametrine in the control of Malaria as observed on fifferent types Of walls In the Brazilian Amazon 1

The residual power of deltametrine FW (25 mg 1 .a/m2) was evaluated and compared to that of DDT (2 g i.a./m2) by means of biological tests. The different kinds of material used in constructing houses in Amazonia, such as: masonry, wood, and wattle and daub, were used. Data from logistic regression showed that the drop in mortality, the inclination of the curve in relation to time, was similar for the two insecticides in the first samples. The negative coeficient for the variable, months after application, confirmed a reduction in the activity of both insecticides. Wooden and wattle walls showed positive and negative coeficiencies respectively from the beginning. The wooden walls retained a residual effect but the wattle walls were shown to be the least indicated for the application of insecticides The experiments demonstrated a more prolonged residual effect for deltametrine as compared to DDT, and that insecticides work better on brick and cement and wooden walls than they do on wattle and daub constructions. For these reasons, it would be necessary to spray brick and cement walls every 8 months, wooden ones every 9 months and wattle constructions every 7 months to control the vectors of malaria.

Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Forecasting human entrances at a commercial store using facial recognition data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

A survey of distributed data aggregation algorithms

Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.

Estimation of statistical cure from cancer using population-based data

Dissertação de mestrado em Estatística

Modeling usage of medical care services: the medical expenditure panel survey data, 1996-2000

We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required.

Currency Forecast Errors at Times of Low Interest Rates: Evidence from Survey Data on the Yen/Dollar Exchange Rate

Using survey expectations data and Markov-switching models, this paper evaluates the characteristics and evolution of investors' forecast errors about the yen/dollar exchange rate. Since our model is derived from the uncovered interest rate parity (UIRP) condition and our data cover a period of low interest rates, this study is also related to the forward premium puzzle and the currency carry trade strategy. We obtain the following results. First, with the same forecast horizon, exchange rate forecasts are homogeneous among different industry types, but within the same industry, exchange rate forecasts differ if the forecast time horizon is different. In particular, investors tend to undervalue the future exchange rate for long term forecast horizons; however, in the short run they tend to overvalue the future exchange rate. Second, while forecast errors are found to be partly driven by interest rate spreads, evidence against the UIRP is provided regardless of the forecasting time horizon; the forward premium puzzle becomes more significant in shorter term forecasting errors. Consistent with this finding, our coefficients on interest rate spreads provide indirect evidence of the yen carry trade over only a short term forecast horizon. Furthermore, the carry trade seems to be active when there is a clear indication that the interest rate will be low in the future.

Bacillus subtilis contains two small c-type cytochromes with homologous heme domains but different types of membrane anchors.

We demonstrate that the cccB gene, identified in the Bacillus subtilis genome sequence project, is the structural gene for a 10-kDa membrane-bound cytochrome c(551) lipoprotein described for the first time in B. subtilis. Apparently, CccB corresponds to cytochrome c(551) of the thermophilic bacterium Bacillus PS3. The heme domain of B. subtilis cytochrome c(551) is very similar to that of cytochrome c(550), a protein encoded by the cccA gene and anchored to the membrane by a single transmembrane polypeptide segment. Thus, B. subtilis contains two small, very similar, c-type cytochromes with different types of membrane anchors. The cccB gene is cotranscribed with the yvjA gene, and transcription is repressed by glucose. Mutants deleted for cccB or yvjA-cccB show no apparent growth, sporulation, or germination defect. YvjA is not required for the synthesis of cytochrome c(551), and its function remains unknown.

Data bases for the assessment of medical technologies: examples from Europe.

The assessment of medical technologies has to answer several questions ranging from safety and effectiveness to complex economical, social, and health policy issues. The type of data needed to carry out such evaluation depends on the specific questions to be answered, as well as on the stage of development of a technology. Basically two types of data may be distinguished: (a) general demographic, administrative, or financial data which has been collected not specifically for technology assessment; (b) the data collected with respect either to a specific technology or to a disease or medical problem. On the basis of a pilot inquiry in Europe and bibliographic research, the following categories of type (b) data bases have been identified: registries, clinical data bases, banks of factual and bibliographic knowledge, and expert systems. Examples of each category are discussed briefly. The following aims for further research and practical goals are proposed: criteria for the minimal data set required, improvement to the registries and clinical data banks, and development of an international clearinghouse to enhance information diffusion on both existing data bases and available reports on medical technology assessments.

Adult human adipose tissue contains several types of multipotent cells.

Multipotent mesenchymal stromal cells (MSCs) are a type of adult stem cells that can be easily isolated from various tissues and expanded in vitro. Many reports on their pluripotency and possible clinical applications have raised hopes and interest in MSCs. In an attempt to unify the terminology and the criteria to label a cell as MSC, in 2006 the International Society for Cellular Therapy (ISCT) proposed a standard set of rules to define the identity of these cells. However, MSCs are still extracted from different tissues, by diverse isolation protocols, are cultured and expanded in different media and conditions. All these variables may have profound effects on the selection of cell types and the composition of heterogeneous subpopulations, on the selective expansion of specific cell populations with totally different potentials and ergo, on the long-term fate of the cells upon in vitro culture. Therefore, specific molecular and cellular markers that identify MSCs subsets as well as standardization of expansion protocols for these cells are urgently needed. Here, we briefly discuss new useful markers and recent data supporting the rapidly emerging concept that many different types of progenitor cells are found in close association with blood vessels. This knowledge may promote the necessary technical improvements required to reduce variability and promote higher efficacy and safety when isolating and expanding these cells for therapeutic use. In the light of the discussed data, particularly the identification of new markers, and advances in the understanding of fundamental MSC biology, we also suggest a revision of the 2006 ISCT criteria.

Uncovering hidden duplicated content in public transcriptomics data.

As part of the development of the database Bgee (a dataBase for Gene Expression Evolution), we annotate and analyse expression data from different types and different sources, notably Affymetrix data from GEO and ArrayExpress, and RNA-Seq data from SRA. During our quality control procedure, we have identified duplicated content in GEO and ArrayExpress, affecting ∼14% of our data: fully or partially duplicated experiments from independent data submissions, Affymetrix chips reused in several experiments, or reused within an experiment. We present here the procedure that we have established to filter such duplicates from Affymetrix data, and our procedure to identify future potential duplicates in RNA-Seq data. Database URL: http://bgee.unil.ch/