938 resultados para Currency forecast errors
Resumo:
Clinic simulation as a training and knowledge method allows people experiment a real event representation with the aim of acquiring knowledge, abilities and aptitudes. The filming of the staging represents a useful tool to review the decisions taken and the actions they did, with the purpose to highlight the strengths, weaknesses and the areas for improvement. The article describes a study carried out by a group of students in second course of nursing, and it tries to evaluate if there is any influence if somebody is filming you during the clinic simulation, does it make you do more errors or not?
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We present a detailed evaluation of the seasonal performance of the Community Multiscale Air Quality (CMAQ) modelling system and the PSU/NCAR meteorological model coupled to a new Numerical Emission Model for Air Quality (MNEQA). The combined system simulates air quality at a fine resolution (3 km as horizontal resolution and 1 h as temporal resolution) in north-eastern Spain, where problems of ozone pollution are frequent. An extensive database compiled over two periods, from May to September 2009 and 2010, is used to evaluate meteorological simulations and chemical outputs. Our results indicate that the model accurately reproduces hourly and 1-h and 8-h maximum ozone surface concentrations measured at the air quality stations, as statistical values fall within the EPA and EU recommendations. However, to further improve forecast accuracy, three simple bias-adjustment techniques mean subtraction (MS), ratio adjustment (RA), and hybrid forecast (HF) based on 10 days of available comparisons are applied. The results show that the MS technique performed better than RA or HF, although all the bias-adjustment techniques significantly reduce the systematic errors in ozone forecasts.
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Les erreurs innées du métabolisme (EIM) sont dues à des mutations de gènes codant pour des enzymes du métabolisme et sont classées selon trois grands groupes de maladies: 1) intoxications; 2) déficit énergétique et 3) déficit de synthèse ou catabolisme des maladies complexes. Le progrès thérapeutique des vingt dernières années a permis d'améliorer le pronostic des enfants atteints d'EIM. Ces enfants grandissent et doivent être pris en charge à l'adolescence et à l'âge adulte par des équipes spécialisées. Cette médecine métabolique pour adultes est une discipline relativement nouvelle avec une information limitée chez l'adulte. Les recommandations pédiatriques sont extrapolées à la prise en charge des adultes tout en intégrant les différentes étapes de vie (indépendance sociale, grossesse, vieillissement et éventuelles complications tardives). Inborn errors of metabolism (IEM) are due to mutations of genes coding for enzymes of intermediary metabolism and are classified into 3 broad categories: 1) intoxication, 2) energy defect and 3) cellular organelles synthesis or catabolism defect. Improvements of therapy over these last 20 years has improved prognosis of children with IEM. These children grow up and should have their transition to specialized adult care. Adult patients with IEM are a relatively new phenomenon with currently only limited knowledge. Extrapolated pediatric guidelines are applied to the adult population taking into account adult life stages (social independence, pregnancy, aging process and potential long-term complications).
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In humans, action errors and perceptual novelty elicit activity in a shared frontostriatal brain network, allowing them to adapt their ongoing behavior to such unexpected action outcomes. Healthy and pathologic aging reduces the integrity of white matter pathways that connect individual hubs of such networks and can impair the associated cognitive functions. Here, we investigated whether structural disconnection within this network because of small-vessel disease impairs the neural processes that subserve motor slowing after errors and novelty (post-error slowing, PES; post-novel slowing, PNS). Participants with intact frontostriatal circuitry showed increased right-lateralized beta-band (12-24 Hz) synchrony between frontocentral and frontolateral electrode sites in the electroencephalogram after errors and novelty, indexing increased neural communication. Importantly, this synchrony correlated with PES and PNS across participants. Furthermore, such synchrony was reduced in participants with frontostriatal white matter damage, in line with reduced PES and PNS. The results demonstrate that behavioral change after errors and novelty result from coordinated neural activity across a frontostriatal brain network and that such cognitive control is impaired by reduced white matter integrity.
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Abstract Objective: To evaluate three-dimensional translational setup errors and residual errors in image-guided radiosurgery, comparing frameless and frame-based techniques, using an anthropomorphic phantom. Materials and Methods: We initially used specific phantoms for the calibration and quality control of the image-guided system. For the hidden target test, we used an Alderson Radiation Therapy (ART)-210 anthropomorphic head phantom, into which we inserted four 5mm metal balls to simulate target treatment volumes. Computed tomography images were the taken with the head phantom properly positioned for frameless and frame-based radiosurgery. Results: For the frameless technique, the mean error magnitude was 0.22 ± 0.04 mm for setup errors and 0.14 ± 0.02 mm for residual errors, the combined uncertainty being 0.28 mm and 0.16 mm, respectively. For the frame-based technique, the mean error magnitude was 0.73 ± 0.14 mm for setup errors and 0.31 ± 0.04 mm for residual errors, the combined uncertainty being 1.15 mm and 0.63 mm, respectively. Conclusion: The mean values, standard deviations, and combined uncertainties showed no evidence of a significant differences between the two techniques when the head phantom ART-210 was used.
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Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.
Resumo:
Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.
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The presence of illicit drugs such as cocaine and marijuana in US paper currency is very well demonstrated. However, there is no published study describing the presence of cocaine and/or other illicit drugs in Brazilian paper currency. In this study, Brazilian banknotes were collected from nine cities, extracted and analyzed by capillary gas chromatography/mass spectrometry, in order to investigate the presence of cocaine. Bills were extracted with deionized water followed by ethyl acetate. Results showed that 93% of the bills presented cocaine in a concentration range of 2.38-275.10 µg/bill.
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Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.
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The aim of this study was to determine the minimum conditions of wetness duration and mean temperature required for Fusarium head blight infection in wheat. The weather model developed by Zoldan (2008) was tested in field experiments for two wheat cultivars grown in 2005 (five sowing dates) and 2006 (six sowing dates) in 10 m² plots with three replicates. The disease was assessed according to head incidence (HI), spikelet incidence (SI), and the interaction between these two methods was called head blight severity (HBS). Starting at the beginning of anthesis, air temperature and head wetness duration were daily recorded with an automatic weather station. With the combination of these two factors, a weather favorability table was built for the disease occurrence. Starting on the day of flowering beginning (1 - 5% fully exserted anthers), the sum of daily values for infection favorability (SDVIF) was calculated by means of a computer program, according to Zoldan (2008) table. The initial symptoms of the disease were observed at 3.7% spikelet incidence, corresponding to 2.6 SVDFI. The infection occurs in wheat due to rainfall which results in spike wetting of > 61.4 h duration. Rainfall events forecast can help time fungicide application to control FHB. The name of this alert system is proposed as UPF-scab alert.
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Thermal and air conditions inside animal facilities change during the day due to the influence of the external environment. For statistical and geostatistical analyses to be representative, a large number of points spatially distributed in the facility area must be monitored. This work suggests that the time variation of environmental variables of interest for animal production, monitored within animal facility, can be modeled accurately from discrete-time records. The aim of this study was to develop a numerical method to correct the temporal variations of these environmental variables, transforming the data so that such observations are independent of the time spent during the measurement. The proposed method approached values recorded with time delays to those expected at the exact moment of interest, if the data were measured simultaneously at the moment at all points distributed spatially. The correction model for numerical environmental variables was validated for environmental air temperature parameter, and the values corrected by the method did not differ by Tukey's test at 5% significance of real values recorded by data loggers.
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The existence of a minimum storage capacity of grains as a condition for the maintenance of regulator physical stocks has been used as a strategic factor in the agribusiness expansion. However, in Brazil the storage infrastructure has not followed the growth of the agricultural sector. This fact is evident in the case of soybeans that currently represent 49% of grain production in the country, whose volume production has been increasing significantly over the years. This study aimed to predict the futureï needs of static storage capacity of soybeans from historical data to estimate the investment needed to install storage units in Brazil for the next five years. A statistic analysis of collected data allowed a forecast and identification of the number of storage units that should be installed to meet the storage needs of soybeans in the next five years. It was concluded that by 2015 the soybean storage capacity should be 87 million tons, and to store 49% of soybeans produced, 1,104 storage units should be installed at a cost of R$ 442 million.