Calculo de los Parámetros Orbitales del Asteroide 2003QO104

El objetivo central del presente trabajo es el estudio del 2003 QO104 cuyo diámetro está comprendido entre 2.5 y 4 kilómetros. Este masivo asteroide tiene aproximadamente un tercio del tamaño del im-pactor K-T que probablemente hizo desaparecer a los dinosaurios 65 millones de años atrás. Fue des-cubierto el 31 de Agosto del 2003 por el sistema NEAT-Haleakala-AMOS y gira alrededor del Sol en 1139.73 días. Estuvo el 9 de junio del 2009 a 36.8 distancias lunares. Estudiamos al asteroide 2003 QO104 durante varios días del mes de junio del 2009 y realizamos astrometría de precisión. Con esos datos calculamos su órbita

Social Exclusion Modifies Climate and Deforestation Impacts on a Vector-Borne Disease

American Cutaneous Leishmaniasis emergence has been associated with changes in the interaction between people and forests. The association between outbreaks and forest clearance, higher risk for populations living close to forests, and the absence of this disease from urban settings has led to the proposal that it will disappear with the destruction of primary forests. This view ignores the complex nature of deforestation as a product of socioeconomic inequities. Our study shows that such inequities, as measured by a marginalization index, may ultimately determine risk within the country, with socially excluded populations most affected by the disease. Contrary to the established view, living close to the forest edge can diminish the risk provided other factors are taken into account. Additionally, differences in vulnerability to climatic variability appear to interact with forest cover to influence risk across counties where the disease has its largest burden. Incidence exacerbation associated with El Niño Southern Oscillation is observed in counties with larger proportions of deforestation. Our study calls for control efforts targeted to socially excluded populations and for more localized ecological studies of transmission in vectors and reservoirs in order to understand the role of biodiversity changes in driving the emergence of this disease

Blood feeding patterns of mosquitoes: random or structured?

<p>Abstract</p> <p>Background</p> <p>The foraging behavior of blood-sucking arthropods is the defining biological event shaping the transmission cycle of vector-borne parasites. It is also a phenomenon that pertains to the realm of community ecology, since blood-feeding patterns of vectors can occur across a community of vertebrate hosts. Although great advances in knowledge of the genetic basis for blood-feeding choices have been reported for selected vector species, little is known about the role of community composition of vertebrate hosts in determining such patterns.</p> <p>Methods & Results</p> <p>Here, we present an analysis of feeding patterns of vectors across a variety of locations, looking at foraging patterns of communities of mosquitoes, across communities of hosts primarily comprised of mammals and birds. Using null models of species co-occurrence, which do not require ancillary information about host abundance, we found that blood-feeding patterns were aggregated in studies from multiple sites, but random in studies from a single site. This combination of results supports the idea that mosquito species in a community may rely primarily on host availability in a given landscape, and that contacts with specific hosts will be influenced more by the presence/absence of hosts than by innate mosquito choices. This observation stresses the importance of blood-feeding plasticity as a key trait explaining the emergence of many zoonotic mosquito transmitted diseases.</p> <p>Discussion</p> <p>From an epidemiological perspective our observations support the idea that phenomena promoting synchronization of vectors and hosts can promote the emergence of vector-borne zoonotic diseases, as suggested by observations on the linkages between deforestation and the emergence of several human diseases.</p

The release of wastewater contaminants in the Arctic : a case study from Cambridge Bay, Nunavut, Canada

The treatment of municipal wastewater in the Arctic is challenging due to a variety of financial, operational, climatic and technical issues. To better understand the efficacy of current wastewater treatment in this region and the hazard posed to receiving waters, we assessed the occurrence of contaminants (i.e., pharmaceuticals, antibiotic resistance genes and nutrients) as they moved through a lagoon-based treatment system in Cambridge Bay in Nunavut, Canada. Wastewater treatment in this community is performed by the use of a lagoon-tundra wetland system that is discharged into the marine environment and is representative of current common practices throughout the region. In 2014, samples were collected before and during lagoon discharge from two locations in the main lagoon, one location downstream from the lagoon effluent and three locations offshore. Grab samples were collected to measure nutrients (e.g. total nitrogen and phosphorus) and the presence of antibiotic resistance gene-bearing microbes, and Polar Organic Chemical Integrative Samplers (POCIS) were deployed to collect passively organic contaminants in all locations. A total of six pharmaceuticals were detected from a screen of twenty-eight analytes during the study: atenolol, carbamazepine, clarithromycin, metoprolol, sulfamethoxazole and trimethoprim. The greatest concentrations of nutrients, antibiotic resistance genes (ARGs) and pharmaceuticals were found in sampling locations within the treatment lagoon. Offshore of the release point, we observed limited to no detection of pharmaceuticals and ARGs and no change in total nitrogen and phosphorus from pre-release. We conclude that the current concentrations of monitored pharmaceuticals do not pose a significant hazard at this time to aquatic organisms in Cambridge Bay

Serum levels of S100B and NSE proteins in Alzheimer's disease patients

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease is the most common dementia in the elderly, and the potential of peripheral biochemical markers as complementary tools in the neuropsychiatric evaluation of these patients has claimed further attention.</p> <p>Methods</p> <p>We evaluated serum levels of S100B and neuron-specific enolase (NSE) in 54 mild, moderate and severe Alzheimer's disease (AD) patients and in 66 community-dwelling elderly. AD patients met the probable NINCDS-ADRDA criteria. Severity of dementia was ascertained by the Clinical Dementia Rating (CDR) scale, cognitive function by the Mini Mental State Examination (MMSE), and neuroimage findings with magnetic resonance imaging. Serum was obtained from all individuals and frozen at -70°C until analysis.</p> <p>Results</p> <p>By comparing both groups, serum S100B levels were lower in AD group, while serum NSE levels were the same both groups. In AD patients, S100B levels were positively correlated with CDR scores (rho = 0.269; p = 0.049) and negatively correlated with MMSE scores (rho = -0.33; <it>P </it>= 0.048). NSE levels decreased in AD patients with higher levels of brain atrophy.</p> <p>Conclusions</p> <p>The findings suggest that serum levels of S100B may be a marker for brain functional condition and serum NSE levels may be a marker for morphological status in AD.</p

Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA

<p>Abstract</p> <p>Background</p> <p>Models of the effects of environmental factors on West Nile virus disease risk have yielded conflicting outcomes. The role of precipitation has been especially difficult to discern from existing studies, due in part to habitat and behavior characteristics of specific vector species and because of differences in the temporal and spatial scales of the published studies. We used spatial and statistical modeling techniques to analyze and forecast fine scale spatial (2000 m grid) and temporal (weekly) patterns of West Nile virus mosquito infection relative to changing weather conditions in the urban landscape of the greater Chicago, Illinois, region for the years from 2004 to 2008.</p> <p>Results</p> <p>Increased air temperature was the strongest temporal predictor of increased infection in <it>Culex pipiens </it>and <it>Culex restuans </it>mosquitoes, with cumulative high temperature differences being a key factor distinguishing years with higher mosquito infection and higher human illness rates from those with lower rates. Drier conditions in the spring followed by wetter conditions just prior to an increase in infection were factors in some but not all years. Overall, 80% of the weekly variation in mosquito infection was explained by prior weather conditions. Spatially, lower precipitation was the most important variable predicting stronger mosquito infection; precipitation and temperature alone could explain the pattern of spatial variability better than could other environmental variables (79% explained in the best model). Variables related to impervious surfaces and elevation differences were of modest importance in the spatial model.</p> <p>Conclusion</p> <p>Finely grained temporal and spatial patterns of precipitation and air temperature have a consistent and significant impact on the timing and location of increased mosquito infection in the northeastern Illinois study area. The use of local weather data at multiple monitoring locations and the integration of mosquito infection data from numerous sources across several years are important to the strength of the models presented. The other spatial environmental factors that tended to be important, including impervious surfaces and elevation measures, would mediate the effect of rainfall on soils and in urban catch basins. Changes in weather patterns with global climate change make it especially important to improve our ability to predict how inter-related local weather and environmental factors affect vectors and vector-borne disease risk.</p> <p>Local impact of temperature and precipitation on West Nile virus infection in <it>Culex </it>species mosquitoes in northeast Illinois, USA.</p

Predicting West Nile Virus Infection Risk From the Synergistic Effects of Rainfall and Temperature

Mosquito-based surveillance is a practical way to estimate the risk of transmission of West Nile virus (WNV) to people. Variations in temperature and precipitation play a role in driving mosquito infection rates and transmission of WNV, motivating efforts to predict infection rates based on prior weather conditions. Weather conditionsand sequential patterns of meteorological events can have particularly important, but regionally distinctive, consequences for WNV transmission, with high temperatures and low precipitation often increasing WNV mosquitoinfection. Predictive models that incorporate weather can thus be used to provide early indications of the risk of WNV infection. The purpose of this study was first, to assess the ability of a previously published model of WNV mosquito infection to predict infection for an area within the region for which it was developed, and second, to improve the predictive ability of this model by incorporating new weather factors that may affect mosquito development. The legacy model captured the primary trends in mosquito infection, but it was improved considerably when calibrated with local mosquito infection rates. The use of interaction terms between precipitationand temperature improved model performance. Specifically, temperature had a stronger influence than rainfall, so that lower than average temperature greatly reduced the effect of low rainfall on increased infectionrates. When rainfall was lower, high temperature had an even stronger positive impact on infection rates. The final model is practical, stable, and operationally valid for predicting West Nile virus infection rates in future weeks when calibrated with local data

Fine-Scale Variation in Vector Host Use and Force of Infection Drive Localized Patterns of West Nile Virus Transmission

The influence of host diversity on multi-host pathogen transmission and persistence can be confounded by the large number of species and biological interactions that can characterize many transmission systems. For vector-borne pathogens, the composition of host communities has been hypothesized to affect transmission; however, the specific characteristics of host communities that affect transmission remain largely unknown. We tested the hypothesis that vector host use and force of infection (i.e., the summed number of infectious mosquitoes resulting from feeding upon each vertebrate host within a community of hosts), and not simply host diversity or richness, determine local infection rates of West Nile virus (WNV) in mosquito vectors. In suburban Chicago, Illinois, USA, we estimated community force of infection for West Nile virus using data on Culex pipiens mosquito host selection and WNV vertebrate reservoir competence for each host species in multiple residential and semi-natural study sites. We found host community force of infection interacted with avian diversity to influence WNV infection in Culex mosquitoes across the study area. Two avian species, the American robin (Turdus migratorius) and the house sparrow (Passer domesticus), produced 95.8% of the infectious Cx. pipiens mosquitoes and showed a significant positive association with WNV infection in Culex spp. mosquitoes. Therefore, indices of community structure, such as species diversity or richness, may not be reliable indicators of transmission risk at fine spatial scales in vector-borne disease systems. Rather, robust assessment of local transmission risk should incorporate heterogeneity in vector host feeding and variation in vertebrate reservoir competence at the spatial scale of vector-host interaction

Cutaneous Leishmaniasis and Sand Fly Fluctuations Are Associated with El Nino in Panama

BackgroundCutaneous Leishmaniasis (CL) is a neglected tropical vector-borne disease. Sand fly vectors (SF) and Leishmania spp parasites are sensitive to changes in weather conditions, rendering disease transmission susceptible to changes in local and global scale climatic patterns. Nevertheless, it is unclear how SF abundance is impacted by El Nino Southern Oscillation (ENSO) and how these changes might relate to changes in CL transmission.Methodology and FindingsWe studied association patterns between monthly time series, from January 2000 to December 2010, of: CL cases, rainfall and temperature from Panama, and an ENSO index. We employed autoregressive models and cross wavelet coherence, to quantify the seasonal and interannual impact of local climate and ENSO on CL dynamics. We employed Poisson Rate Generalized Linear Mixed Models to study SF abundance patterns across ENSO phases, seasons and eco-epidemiological settings, employing records from 640 night-trap sampling collections spanning 2000?2011. We found that ENSO, rainfall and temperature were associated with CL cycles at interannual scales, while seasonal patterns were mainly associated with rainfall and temperature. Sand fly (SF) vector abundance, on average, decreased during the hot and cold ENSO phases, when compared with the normal ENSO phase, yet variability in vector abundance was largest during the cold ENSO phase. Our results showed a three month lagged association between SF vector abundance and CL cases.ConclusionAssociation patterns of CL with ENSO and local climatic factors in Panama indicate that interannual CL cycles might be driven by ENSO, while the CL seasonality was mainly associated with temperature and rainfall variability. CL cases and SF abundance were associated in a fashion suggesting that sudden extraordinary changes in vector abundance might increase the potential for CL epidemic outbreaks, given that CL epidemics occur during the cold ENSO phase, a time when SF abundance shows its highest fluctuations

Influência da variação da produtividade das usinas hidroelétricas no cálculo da energia firme

In the present work, the problem associated to the firm energy evaluation is treated as a non linear optimization model, which allows the representation of the productivity variation of the hydro plants. The proposed model takes into account the individualized representation of the plants and the historical series of flows since the month of January of 1931. The proposed optimization problem will be solved using the Primal-Dual Interior Point Method. A case study will be presented including the Brazilian Interconnected National System. The results obtained show that the proposed methodology is promising, since it presents an energy market value more realistic when compared with existing methodologies.No presente trabalho, o problema associado ao cálculo da energia firme é tratado como um modelo não linear de otimização, o que permite a representação da variação da produtividade das usinas. No modelo proposto é considerada a representação individualizada das usinas bem como a série histórica de vazões desde o mês de janeiro de 1931. O problema de otimização proposto é resolvido através do método primal-dual de pontos interiores. Adicionalmente, é apresentado um estudo de caso abrangendo o Sistema Interligado Nacional Brasileiro. Os resultados obtidos mostram que a metodologia proposta é promissora, tendo em vista que apresenta um valor de mercado de energia mais realista quando comparado com outras metodologias