Social capital and hygiene practices among the extreme poor in rural Bangladesh

We investigate the effect of social capital on hygiene practices pertaining to lives of the extreme poor in rural Bangladesh. Analysing a unique survey dataset for 5,600 extreme poor households, we document a significant positive effect of social capital on sanitary latrine use and wearing shoes/sandals at home for hygiene. We account for the endogeneity of social capital by instrumental variable estimation. Our findings emphasise the role of social capital in preventing common diseases through improving hygiene practices for the extreme poor, who usually lack access to medical services in the event of illness, which has important policy implications.

Adrenocortical stress responses influence an invasive vertebrate's fitness in an extreme environment

Continued range expansion into physiologically challenging environments requires invasive species to maintain adaptive phenotypic performance. The adrenocortical stress response, governed in part by glucocorticoid hormones, influences physiological and behavioural responses of vertebrates to environmental stressors. However, any adaptive role of this response in invasive populations that are expanding into extreme environments is currently unclear. We experimentally manipulated the adrenocortical stress response of invasive cane toads (Rhinella marina) to investigate its effect on phenotypic performance and fitness at the species' range front in the Tanami Desert, Australia. Here, toads are vulnerable to overheating and dehydration during the annual hot-dry season and display elevated plasma corticosterone levels indicative of severe environmental stress. By comparing unmanipulated control toads with toads whose adrenocortical stress response was manipulated to increase acute physiological stress responsiveness, we found that control toads had significantly reduced daily evaporative water loss and higher survival relative to the experimental animals. The adrenocortical stress response hence appears essential in facilitating complex phenotypic performance and setting fitness trajectories of individuals from invasive species during range expansion.

A systematic design of interval type-2 fuzzy logic system using extreme learning machine for electricity load demand forecasting

This paper presents a novel design of interval type-2 fuzzy logic systems (IT2FLS) by utilizing the theory of extreme learning machine (ELM) for electricity load demand forecasting. ELM has become a popular learning algorithm for single hidden layer feed-forward neural networks (SLFN). From the functional equivalence between the SLFN and fuzzy inference system, a hybrid of fuzzy-ELM has gained attention of the researchers. This paper extends the concept of fuzzy-ELM to an IT2FLS based on ELM (IT2FELM). In the proposed design the antecedent membership function parameters of the IT2FLS are generated randomly, whereas the consequent part parameters are determined analytically by the Moore-Penrose pseudo inverse. The ELM strategy ensures fast learning of the IT2FLS as well as optimality of the parameters. Effectiveness of the proposed design of IT2FLS is demonstrated with the application of forecasting nonlinear and chaotic data sets. Nonlinear data of electricity load from the Australian National Electricity Market for the Victoria region and from the Ontario Electricity Market are considered here. The proposed model is also applied to forecast Mackey-glass chaotic time series data. Comparative analysis of the proposed model is conducted with some traditional models such as neural networks (NN) and adaptive neuro fuzzy inference system (ANFIS). In order to verify the structure of the proposed design of IT2FLS an alternate design of IT2FLS based on Kalman filter (KF) is also utilized for the comparison purposes.

Investigating The Sources Of Fresh Water Affecting The Hydrological Balance Of Lakes Enriquillo And Azuei (Hispaniola) – Data Analysis

The Enriquillo and Azuei are saltwater lakes located in a closed water basin in the southwestern region of the island of La Hispaniola, these have been experiencing dramatic changes in total lake-surface area coverage during the period 1980-2012. The size of Lake Enriquillo presented a surface area of approximately 276 km2 in 1984, gradually decreasing to 172 km2 in 1996. The surface area of the lake reached its lowest point in the satellite observation record in 2004, at 165 km2. Then the recent growth of the lake began reaching its 1984 size by 2006. Based on surface area measurement for June and July 2013, Lake Enriquillo has a surface area of ~358 km2. Sumatra sizes at both ends of the record are 116 km2 in 1984 and 134 km2in 2013, an overall 15.8% increase in 30 years. Determining the causes of lake surface area changes is of extreme importance due to its environmental, social, and economic impacts. The overall goal of this study is to quantify the changing water balance in these lakes and their catchment area using satellite and ground observations and a regional atmospheric-hydrologic modeling approach. Data analyses of environmental variables in the region reflect a hydrological unbalance of the lakes due to changing regional hydro-climatic conditions. Historical data show precipitation, land surface temperature and humidity, and sea surface temperature (SST), increasing over region during the past decades. Salinity levels have also been decreasing by more than 30% from previously reported baseline levels. Here we present a summary of the historical data obtained, new sensors deployed in the sourrounding sierras and the lakes, and the integrated modeling exercises. As well as the challenges of gathering, storing, sharing, and analyzing this large volumen of data in a remote location from such a diverse number of sources.

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.

Regionalização das velocidades extremas e temperaturas dos ventos no centro-sul do Brasil.

Séries de dados de velocidades máximas anuais do vento, classificadas segundo o tipo de tormenta (ventos EPS ou TS) e a direção (octantes), são utilizadas para o ajuste de um modelo baseado em regressão linear múltipla, permitindo a estimativa dos ventos extremos no interior da região definida pelas estações meteorológicas disponíveis. A correlação entre as velocidades do vento e a temperatura do ar durante tormentas também é investigada, bem como o comportamento estatístico das temperaturas durante ventos fortes.

Extreme poverty and development: the role of state in the assurance of minimal existence conditions

This paper follows the idea of Amartya Sen, Nobel Prize of economic, about the role of State in the assurance of minimal existence condition, and aim to answer how countries of Latin America (specifically Brazil) and countries of Europe (specifically United Kingdom) deal with the assurance of this minimal existence conditions. According to Amartya Sen’s view, development must be seen as a process of expanding substantive freedoms, such expansion being the primary purpose of each society and the main mean of development. Substantive freedoms can be considered as basic capabilities allocated to individuals whereby they are entitled to be architects of their own lives, providing them conditions to “live as they wish”. These basic capabilities are divided by Amartya Sen in 5 (five) kinds of substantive freedoms, but for this article’s purpose, we will consider just one of this 5 (five) kinds, specifically the Protective Safety capability. Protective Safety capability may be defined as the assurance of basic means of survival for individuals who are in extreme poverty, at risk of starvation or hypothermia, or even impending famine. Among the means available that could be used to avoid such situations are the possibility of supplemental income to the needy, distributing food and clothing to the needy, supply of energy and water, among others. But how countries deal whit this protective safety? Aiming to answer this question, we selected the problem of “fuel poverty” and how Brazil and United Kingdom solve it (if they solve), in order to assess how the solution found impacts development. The analysis and the comparison between these countries will allow an answer to the question proposed.

Extreme observations and diversification in Latin American emerging equity markets

In this paper, we focus on the tails of the unconditional distribution of Latin American emerging markets stock returns. We explore their implications for portfolio diversification according to the safety tirst principIe, tirst proposed by Roy (1952). We tind that the Latin American emerging markets have signiticantly fatter tails than industrial markets. especially, the lower tail of the distrihution. We consider the implication of the safety tirst principIe for a U .S. investor who creates a diversitied portfolio using Latin American stock markets. We tind that a U.S. investor gains by adding Latin American equity markets to her purely domestic portfolio. For different parameter specitications. we finu a more realistic asset allocation than the one suggested by the Iiterature haseu on the traditional mean-variance framework.

Bayesian analysis of extreme events with threshold estimation

The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds by estimating the GPD parameters based on data beyond it, discarding all the information available be10w the threshold. We introduce a mixture model that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold inc1uded. Prior distribution for the parameters are indirectly obtained through experts quantiles elicitation. Posterior inference is available through Markov Chain Monte Carlo (MCMC) methods. Simulations are carried out in order to analyze the performance of our proposed mode1 under a wide range of scenarios. Those scenarios approximate realistic situations found in the literature. We also apply the proposed model to a real dataset, Nasdaq 100, an index of the financiai market that presents many extreme events. Important issues such as predictive analysis and model selection are considered along with possible modeling extensions.

Statistical modelling of extreme rainfall in Madeira Island

Extreme rainfall events have triggered a significant number of flash floods in Madeira Island along its past and recent history. Madeira is a volcanic island where the spatial rainfall distribution is strongly affected by its rugged topography. In this thesis, annual maximum of daily rainfall data from 25 rain gauge stations located in Madeira Island were modelled by the generalised extreme value distribution. Also, the hypothesis of a Gumbel distribution was tested by two methods and the existence of a linear trend in both distributions parameters was analysed. Estimates for the 50– and 100–year return levels were also obtained. Still in an univariate context, the assumption that a distribution function belongs to the domain of attraction of an extreme value distribution for monthly maximum rainfall data was tested for the rainy season. The available data was then analysed in order to find the most suitable domain of attraction for the sampled distribution. In a different approach, a search for thresholds was also performed for daily rainfall values through a graphical analysis. In a multivariate context, a study was made on the dependence between extreme rainfall values from the considered stations based on Kendall’s τ measure. This study suggests the influence of factors such as altitude, slope orientation, distance between stations and their proximity of the sea on the spatial distribution of extreme rainfall. Groups of three pairwise associated stations were also obtained and an adjustment was made to a family of extreme value copulas involving the Marshall–Olkin family, whose parameters can be written as a function of Kendall’s τ association measures of the obtained pairs.

Estudo estatístico sobre eventos de precipitação intensa no nordeste do Brasil

The Northeast of Brazil (NEB) shows high climate variability, ranging from semiarid regions to a rainy regions. According to the latest report of the Intergovernmental Panel on Climate Change, the NEB is highly susceptible to climate change, and also heavy rainfall events (HRE). However, few climatology studies about these episodes were performed, thus the objective main research is to compute the climatology and trend of the episodes number and the daily rainfall rate associated with HRE in the NEB and its climatologically homogeneous sub regions; relate them to the weak rainfall events and normal rainfall events. The daily rainfall data of the hydrometeorological network managed by the Agência Nacional de Águas, from 1972 to 2002. For selection of rainfall events used the technique of quantiles and the trend was identified using the Mann-Kendall test. The sub regions were obtained by cluster analysis, using as similarity measure the Euclidean distance and Ward agglomerative hierarchical method. The results show that the seasonality of the NEB is being intensified, i.e., the dry season is becoming drier and wet season getting wet. The El Niño and La Niña influence more on the amount of events regarding the intensity, but the sub-regions this influence is less noticeable. Using daily data reanalysis ERAInterim fields of anomalies of the composites of meteorological variables were calculated for the coast of the NEB, to characterize the synoptic environment. The Upper-level cyclonic vortex and the South atlantic convergene zone were identified as the main weather systems responsible for training of EPI on the coastland

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelagem e simulação da deposição de parafinas em escoamento turbulento

The flow assurance has become one of the topics of greatest interest in the oil industry, mainly due to production and transportation of oil in regions with extreme temperature and pressure. In these operations the wax deposition is a commonly problem in flow of paraffinic oils, causing the rising costs of the process, due to increased energy cost of pumping, decreased production, increased pressure on the line and risk of blockage of the pipeline. In order to describe the behavior of the wax deposition phenomena in turbulent flow of paraffinic oils, under different operations conditions, in this work we developed a simulator with easy interface. For that we divided de work in four steps: (i) properties estimation (physical, thermals, of transport and thermodynamics) of n-alkanes and paraffinic mixtures by using correlations; (ii) obtainment of the solubility curve and determination the wax appearance temperature, by calculating the solid-liquid equilibrium of parafinnic systems; (iii) modelling wax deposition process, comprising momentum, mass and heat transfer; (iv) development of graphic interface in MATLAB® environment for to allow the understanding of simulation in different flow conditions as well as understand the matter of the variables (inlet temperature, external temperature, wax appearance temperature, oil composition, and time) on the behavior of the deposition process. The results showed that the simulator developed, called DepoSim, is able to calculate the profile of temperature, thickness of the deposit, and the amount of wax deposited in a simple and fast way, and also with consistent results and applicable to the operation