Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 1: Model description and evaluation

We introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and from biomass burning aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostics include the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between the simulated biomass burning aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM(2.5)) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosondes and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained.

The role of the observed tropical convection in the generation of frost events in the southern cone of South America

Based on previous results obtained from observations and linear wave theory analysis, the hypothesis that large-scale patterns can generate extreme cold events in southeast South America through the propagation of remotely excited Rossby waves was already suggested. This work will confirm these findings and extend their analysis through a series of numerical experiments using a primitive equation model where waves are excited by a thermal forcing situated in positions chosen according to observed convection anomalies over the equatorial region. The basic state used for these experiments is a composite of austral winters with maximum and minimum frequency of occurrence of generalized frosts that can affect a large area known as the Wet Pampas located in the central and eastern part of Argentina. The results suggest that stationary Rossby waves may be one important mechanism linking anomalous tropical convection with the extreme cold events in the Wet Pampas. The combination of tropical convection and a specific basic state can generate the right environment to guide the Rossby waves trigged by the tropical forcing towards South America. Depending on the phase of the waves entering the South American continent, they can favour the advection of anomalous wind at low levels from the south carrying cold and dry air over the whole southern extreme of the continent, producing a generalized frost in the Wet Pampa region. On the other hand, when a basic state based on the composites of minimum frosts is used, an anomalous anticyclone over the southern part of the continent generates a circulation with a south-southeast wind which brings maritime air and therefore humidity over the Wet Pampas region, creating negative temperature anomalies only over the northeastern part of the region. Under these conditions even if frosts occur they would not be generalized, as observed for the other basic state with maximum frequency of occurrence of generalized frosts.

Diversification and Species Boundaries of Rhinebothrium (Cestoda; Rhinebothriidea) in South American Freshwater Stingrays (Batoidea; Potamotrygonidae)

Background: Neotropical freshwater stingrays (Batoidea: Potamotrygonidae) host a diverse parasite fauna, including cestodes. Both cestodes and their stingray hosts are marine-derived, but the taxonomy of this host/parasite system is poorly understood. Methodology: Morphological and molecular (Cytochrome oxidase I) data were used to investigate diversity in freshwater lineages of the cestode genus Rhinebothrium Linton, 1890. Results were based on a phylogenetic hypothesis for 74 COI sequences and morphological analysis of over 400 specimens. Cestodes studied were obtained from 888 individual potamotrygonids, representing 14 recognized and 18 potentially undescribed species from most river systems of South America. Results: Morphological species boundaries were based mainly on microthrix characters observed with scanning electron microscopy, and were supported by COI data. Four species were recognized, including two redescribed (Rhinebothrium copianullum and R. paratrygoni), and two newly described (R. brooksi n. sp. and R. fulbrighti n. sp.). Rhinebothrium paranaensis Menoret & Ivanov, 2009 is considered a junior synonym of R. paratrygoni because the morphological features of the two species overlap substantially. The diagnosis of Rhinebothrium Linton, 1890 is emended to accommodate the presence of marginal longitudinal septa observed in R. copianullum and R. brooksi n. sp. Patterns of host specificity and distribution ranged from use of few host species in few river basins, to use of as many as eight host species in multiple river basins. Significance: The level of intra-specific morphological variation observed in features such as total length and number of proglottids is unparalleled among other elasmobranch cestodes. This is attributed to the large representation of host and biogeographical samples. It is unclear whether the intra-specific morphological variation observed is unique to this freshwater system. Nonetheless, caution is urged when using morphological discontinuities to delimit elasmobranch cestode species because the amount of variation encountered is highly dependent on sample size and/or biogeographical representation.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 2: Model sensitivity to the biomass burning

We describe an estimation technique for biomass burning emissions in South America based on a combination of remote-sensing fire products and field observations, the Brazilian Biomass Burning Emission Model (3BEM). For each fire pixel detected by remote sensing, the mass of the emitted tracer is calculated based on field observations of fire properties related to the type of vegetation burning. The burnt area is estimated from the instantaneous fire size retrieved by remote sensing, when available, or from statistical properties of the burn scars. The sources are then spatially and temporally distributed and assimilated daily by the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) in order to perform the prognosis of related tracer concentrations. Three other biomass burning inventories, including GFEDv2 and EDGAR, are simultaneously used to compare the emission strength in terms of the resultant tracer distribution. We also assess the effect of using the daily time resolution of fire emissions by including runs with monthly-averaged emissions. We evaluate the performance of the model using the different emission estimation techniques by comparing the model results with direct measurements of carbon monoxide both near-surface and airborne, as well as remote sensing derived products. The model results obtained using the 3BEM methodology of estimation introduced in this paper show relatively good agreement with the direct measurements and MOPITT data product, suggesting the reliability of the model at local to regional scales.

The impact of the subtropical South Atlantic SST on South American precipitation

The Community Climate Model (CCM3) from the National Center for Atmospheric Research (NCAR) is used to investigate the effect of the South Atlantic sea surface temperature (SST) anomalies on interannual to decadal variability of South American precipitation. Two ensembles composed of multidecadal simulations forced with monthly SST data from the Hadley Centre for the period 1949 to 2001 are analysed. A statistical treatment based on signal-to-noise ratio and Empirical Orthogonal Functions (EOF) is applied to the ensembles in order to reduce the internal variability among the integrations. The ensemble treatment shows a spatial and temporal dependence of reproducibility. High degree of reproducibility is found in the tropics while the extratropics is apparently less reproducible. Austral autumn (MAM) and spring (SON) precipitation appears to be more reproducible over the South America-South Atlantic region than the summer (DJF) and winter (JJA) rainfall. While the Inter-tropical Convergence Zone (ITCZ) region is dominated by external variance, the South Atlantic Convergence Zone (SACZ) over South America is predominantly determined by internal variance, which makes it a difficult phenomenon to predict. Alternatively, the SACZ over western South Atlantic appears to be more sensitive to the subtropical SST anomalies than over the continent. An attempt is made to separate the atmospheric response forced by the South Atlantic SST anomalies from that associated with the El Nino - Southern Oscillation (ENSO). Results show that both the South Atlantic and Pacific SSTs modulate the intensity and position of the SACZ during DJF. Particularly, the subtropical South Atlantic SSTs are more important than ENSO in determining the position of the SACZ over the southeast Brazilian coast during DJF. On the other hand, the ENSO signal seems to influence the intensity of the SACZ not only in DJF but especially its oceanic branch during MAM. Both local and remote influences, however, are confounded by the large internal variance in the region. During MAM and JJA, the South Atlantic SST anomalies affect the magnitude and the meridional displacement of the ITCZ. In JJA, the ENSO has relatively little influence on the interannual variability of the simulated rainfall. During SON, however, the ENSO seems to counteract the effect of the subtropical South Atlantic SST variations on convection over South America.

Meiobenthic communities of seagrass beds (Zostera capricorni) and unvegetated sediments along the coast of New South Wales, Australia

Seagrass beds have higher biomass, abundance, diversity and productivity of benthic organisms than unvegetated sediments. However, to date most studies have analysed only the macrofaunal component and ignored the abundant meiofauna present in seagrass meadows. This study was designed to test if meiobenthic communities, especially the free-living nematodes, differed between seagrass beds and unvegetated sediments. Sediment samples from beds of the eelgrass Zostera capricorni and nearby unvegetated sediments were collected in three estuaries along the coast of New South Wales, Australia. Results showed that sediments below the seagrass were finer, with a higher content of organic material and were less oxygenated than sediments without seagrass. Univariate measures of the fauna (i.e. abundance, diversity and taxa richness of total meiofauna and nematode assemblages) did not differ between vegetated and unvegetated sediments. However multivariate analysis of meiofaunal higher taxa showed significant differences between the two habitats, largely due to the presence and absence of certain taxa. Amphipods, tanaidacea, ostracods, hydrozoans and isopods occurred mainly in unvegetated sediments, while kinorhyncs, polychaetes, gastrotrichs and turbellarians were more abundant in vegetated sediments. Regarding the nematode assemblages, 32.4% of the species were restricted to Z. capricorni and 25% only occurred in unvegetated sediments, this suggests that each habitat is characterized by a particular suite of species. Epistrate feeding nematodes were more abundant in seagrass beds, and it is suggested that they graze on the microphytobenthos which accumulates underneath the seagrass. Most of the genera that characterized these estuarine unvegetated sediments are also commonly found on exposed sandy beaches. This may be explained by the fact that Australian estuaries have very little input of freshwater and experience marine conditions for most of the year. This study demonstrates that the seagrass and unvegetated sediments have discrete meiofaunal communities, with little overlap in species composition. (C) 2010 Elsevier Ltd. All rights reserved.

Simulation of Soil Carbon Dynamics under Sugarcane with the CENTURY Model

Currently there is a trend for the expansion of the area cropped with sugarcane (Saccharum officinarum L.), driven by an increase in the world demand for biofuels, due to economical, environmental, and geopolitical issues. Although sugarcane is traditionally harvested by burning dried leaves and tops, the unburned, mechanized harvest has been progressively adopted. The use of process based models is useful in understanding the effects of plant litter in soil C dynamics. The objective of this work was to use the CENTURY model in evaluating the effect of sugarcane residue management in the temporal dynamics of soil C. The approach taken in this work was to parameterize the CENTURY model for the sugarcane crop, to simulate the temporal dynamics of soil C, validating the model through field experiment data, and finally to make predictions in the long term regarding soil C. The main focus of this work was the comparison of soil C stocks between the burned and unburned litter management systems, but the effect of mineral fertilizer and organic residue applications were also evaluated. The simulations were performed with data from experiments with different durations, from 1 to 60 yr, in Goiana and Timbauba, Pernambuco, and Pradopolis, Sao Paulo, all in Brazil; and Mount Edgecombe, Kwazulu-Natal, South Africa. It was possible to simulate the temporal dynamics of soil C (R(2) = 0.89). The predictions made with the model revealed that there is, in the long term, a trend for higher soil C stocks with the unburned management. This increase is conditioned by factors such as climate, soil texture, time of adoption of the unburned system, and N fertilizer management.

Land planarians (Platyhelminthes) as a model organism for fine-scale phylogeographic studies: understanding patterns of biodiversity in the Brazilian Atlantic Forest hotspot

The Brazilian Atlantic Forest is one of the richest biodiversity hotspots of the world. Paleoclimatic models have predicted two large stability regions in its northern and central parts, whereas southern regions might have suffered strong instability during Pleistocene glaciations. Molecular phylogeographic and endemism studies show, nevertheless, contradictory results: although some results validate these predictions, other data suggest that paleoclimatic models fail to predict stable rainforest areas in the south. Most studies, however, have surveyed species with relatively high dispersal rates whereas taxa with lower dispersion capabilities should be better predictors of habitat stability. Here, we have used two land planarian species as model organisms to analyse the patterns and levels of nucleotide diversity on a locality within the Southern Atlantic Forest. We find that both species harbour high levels of genetic variability without exhibiting the molecular footprint of recent colonization or population expansions, suggesting a long-term stability scenario. The results reflect, therefore, that paleoclimatic models may fail to detect refugia in the Southern Atlantic Forest, and that model organisms with low dispersal capability can improve the resolution of these models.

Regulating industrial forest concessions in Central Africa and South America

Tropical countries face special specific problems in implementing sustainable forest management (SFM). In many countries, questions are raised on whether tropical forests should be publicly, commonly or privately owned and managed in order to enhance sustainability. Other debates also focus on whether small-scale enterprises are better positioned than large-scale industrial concessions to reduce poverty and attain sustainable management. In countries where large tracts of forest are state-owned, concessions are viewed as a means of delivering services of public and collective interest through an association of private investment and public regulation. However, the success of an industrial concession model in countries with large forest resource endowment to achieve multiple goals such as sustainable forest management and local/regional development depends on two critical assumptions. First, forest functions and services should be managed and maintained as public goods. In many cases, additional uses - and corresponding rights - can take place alongside logging activities. Industrial concessions can be more efficient than other tenure models (such as community-based forest management and small-scale enterprises) in achieving SFM, add value to raw material and comply with growing environmental norms. This is especially the case in market-remote areas with low population density and poor infrastructure. Secondly, to achieve these different outcomes, any concession system needs to be monitored and regulated, especially in contexts dominated by asymmetrical information between regulating authorities and concessionaires. New institutional responses have recently been put forward in several countries, providing valuable materials to design a renewed policy mix which associates public and private incentives. This paper provides a survey of the experience of forest concessions in several Central African and South American countries. The concession system is examined in order to clarify the issues involved, the problems encountered, and what can be learned from the shared experience of these countries in the last decade. This paper argues that despite a sometimes patchy record, concessions can help promote SFM so long as they are packaged with a certain number of specific measures. (C) 2008 Elsevier B.V. All rights reserved.

A Fault-Tolerant Manipulator Robot Based on H(2), H(infinity), and Mixed H(2)/H(infinity) Markovian Controls

This paper develops a Markovian jump model to describe the fault occurrence in a manipulator robot of three joints. This model includes the changes of operation points and the probability that a fault occurs in an actuator. After a fault, the robot works as a manipulator with free joints. Based on the developed model, a comparative study among three Markovian controllers, H(2), H(infinity), and mixed H(2)/H(infinity) is presented, applied in an actual manipulator robot subject to one and two consecutive faults.

Further improvements on impedance-based fault location for power distribution systems

In this study, further improvements regarding the fault location problem for power distribution systems are presented. The proposed improvements relate to the capacitive effect consideration on impedance-based fault location methods, by considering an exact line segment model for the distribution line. The proposed developments, which consist of a new formulation for the fault location problem and a new algorithm that considers the line shunt admittance matrix, are presented. The proposed equations are developed for any fault type and result in one single equation for all ground fault types, and another equation for line-to-line faults. Results obtained with the proposed improvements are presented. Also, in order to compare the improvements performance and demonstrate how the line shunt admittance affects the state-of-the-art impedance-based fault location methodologies for distribution systems, the results obtained with two other existing methods are presented. Comparative results show that, in overhead distribution systems with laterals and intermediate loads, the line shunt admittance can significantly affect the state-of-the-art methodologies response, whereas in this case the proposed developments present great improvements by considering this effect.

On-line fault diagnostic system for proton exchange membrane fuel cells

In this paper, a supervisor system, able to diagnose different types of faults during the operation of a proton exchange membrane fuel cell is introduced. The diagnosis is developed by applying Bayesian networks, which qualify and quantify the cause-effect relationship among the variables of the process. The fault diagnosis is based on the on-line monitoring of variables easy to measure in the machine such as voltage, electric current, and temperature. The equipment is a fuel cell system which can operate even when a fault occurs. The fault effects are based on experiments on the fault tolerant fuel cell, which are reproduced in a fuel cell model. A database of fault records is constructed from the fuel cell model, improving the generation time and avoiding permanent damage to the equipment. (C) 2007 Elsevier B.V. All rights reserved.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Fault-tolerant quantum computation with cluster states

The one-way quantum computing model introduced by Raussendorf and Briegel [Phys. Rev. Lett. 86, 5188 (2001)] shows that it is possible to quantum compute using only a fixed entangled resource known as a cluster state, and adaptive single-qubit measurements. This model is the basis for several practical proposals for quantum computation, including a promising proposal for optical quantum computation based on cluster states [M. A. Nielsen, Phys. Rev. Lett. (to be published), quant-ph/0402005]. A significant open question is whether such proposals are scalable in the presence of physically realistic noise. In this paper we prove two threshold theorems which show that scalable fault-tolerant quantum computation may be achieved in implementations based on cluster states, provided the noise in the implementations is below some constant threshold value. Our first threshold theorem applies to a class of implementations in which entangling gates are applied deterministically, but with a small amount of noise. We expect this threshold to be applicable in a wide variety of physical systems. Our second threshold theorem is specifically adapted to proposals such as the optical cluster-state proposal, in which nondeterministic entangling gates are used. A critical technical component of our proofs is two powerful theorems which relate the properties of noisy unitary operations restricted to act on a subspace of state space to extensions of those operations acting on the entire state space. We expect these theorems to have a variety of applications in other areas of quantum-information science.