A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.

Impact of an intervention on the availability and consumption of fruits and vegetables in the workplace

Objective: To evaluate the impact of an educational and environmental intervention on the availability and consumption of fruits and vegetables in workplace cafeterias. Design: This was a randomized intervention study involving a sample of companies that were divided into intervention and control groups. The intervention, which focused on change in the work environment, was based on an ecological model for health promotion. It involved several different aspects including menu planning, food presentation and motivational strategies to encourage the consumption of fruits and vegetables. The impact of the intervention was measured by changes (between baseline and follow-up) in the availability of fruits and vegetables that were eaten per consumer in meals and the consumption of fruits and vegetables in the workplace by workers. We also evaluated the availability of energy, macronutrients and fibre. Settings: Companies of Sao Paulo, Brazil. Subjects: Twenty-nine companies and 2510 workers. Results: After the intervention we found an average increase in the availability of fruits and vegetables of 49 g in the intervention group, an increase of approximately 15 %, whereas the results for the control group remained practically equal to baseline levels. During the follow-up period, the intervention group also showed reduced total fat and an increase in fibre in the meals offered. The results showed a slight but still positive increase in the workers` consumption of fruits and vegetables (about 11 g) in the meals offered by the companies. Conclusions: Interventions focused on the work environment can be effective in promoting the consumption of healthy foods.

Effect of fires on soil nutrient availability in an open savanna in Central Brazil

Fire is common in savannas but its effects on soil are poorly understood. We analyzed long-term effects of fire on surface soil of an open Brazilian savanna (campo sujo) in plots submitted to different fire regimes during 18 years. The five fire regimes were: unburned, quadrennial fires in middle dry season, and biennial fires in early, middle or late dry season. Soil was collected during the wet and the middle dry season of 2008, and analyzed for pH, organic matter, total N, potential acidity, exchangeable cations and available P, S, Mn, Cu, Zn and Fe. We applied multivariate analysis to search for patterns related to fire regimes, and to local climate, fuel, and fire behavior. Spearman test was used to establish correlations between soil variables and the multivariate analysis gradient structure. Seasonal differences were tested using t-test. We found evidence of long-term fire effects: the unburned plot was segregated mainly by lower soil pH; the quadrennial plot was also segregated by lower soil pH and higher amount of exchangeable cations; the time of burning during the dry season in biennial plots did not significantly affect soil availability of nutrients. Differences in elements amounts due to the season of soil sampling (wet or dry) were higher than due to the effect of fires. Higher availability of nutrients in the soil during the wet season was probably related to higher nutrient inputs via rainfall and higher microbial activity.

Metal location and thickness in a multilayered sheet by measuring K alpha/K beta, L alpha/L beta and L alpha/L gamma X-ray ratios

When a multilayered material is analyzed by means of energy-dispersive X-ray fluorescence analysis, then the X-ray ratios of K alpha/K beta, or L alpha/L beta and L alpha/L gamma, for an element in the multilayered material, depend on the composition and thickness of the layer in which the element is situated, and on the composition and thickness of the superimposed layer (or layers). Multilayered samples are common in archaeometry, for example, in the case of pigment layers in paintings, or in the case of gilded or silvered alloys. The latter situation is examined in detail in the present paper, with a specific reference to pre-Columbian alloys from various museums in the north of Peru. (C) 2009 Elsevier B.V. All rights reserved.

Measuring time series predictability using support vector regression

Most studies involving statistical time series analysis rely on assumptions of linearity, which by its simplicity facilitates parameter interpretation and estimation. However, the linearity assumption may be too restrictive for many practical applications. The implementation of nonlinear models in time series analysis involves the estimation of a large set of parameters, frequently leading to overfitting problems. In this article, a predictability coefficient is estimated using a combination of nonlinear autoregressive models and the use of support vector regression in this model is explored. We illustrate the usefulness and interpretability of results by using electroencephalographic records of an epileptic patient.

Measuring CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

Measuring CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

Measuring Ultrasonic Communication Between Mouse Pups and Adult Mother Mice

Measuring ultrasonic communication provides us with a way to study parental influence on animals. In this study I measured the ultrasonic communication between mouse pups and two maternal females, one of which who had given birth to the pups and the other had raised them. I found that there was no significant difference between the amount of noise expressed by pups in response to each the biological mother and foster mother test groups. Mouse pups call to maternal females regardless of genetic relatedness. Communication in mice may be a more complicated model because of their communal nature.

Investigation of Iron (III) desferrioxamine B oxalate ligand exchange by UV-vis spectroscopy: the next step in developing a quantitative analytical method for measuring bioavailable iron in marine ecosystems

To date there are no analytical techniques designed to exclusively measure bioavailable iron in marine environments. The goal of this research is to develop such a technique by isolating the bioavailable iron using the terrestrial siderophore desferrioxamine B (DFB). This project contained many challenging aspects, but the specific goal of this study was to develop a robust analytical technique for quantification of Fe(III)-DFB complexes at nanomolar concentrations. Past work showed that oxalate (Ox) promotes photodissociation of Fe(III)-DFB to Fe(Il), and we are specifically interested in the mechanism of this process. A model was developed using known thermodynamic constants for Fe(III)-DFB and Fe(III) oxalato complexes and adjusting for ionic strength. The model was confirmed by monitoring the UV-VIS absorbance of the system at a variety of oxalate concentrations and pH. The model did not include ternary complexes. Next., the rate of Fe(1I) production during UV irradiation was examined. The results showed that the rate of Fe(II) production was based entirely on the [Fe(Ox)?]3- speciation, and that reoxidation of Fe(II) occurred via reactive oxygen intermediates. This reoxidation could be avoided by either decreasing the oxygen concentration or by adding a Fe(II) stabilizing reagent, such as ferrozine. Further studies need to be done to confirm that these results apply at sub nanomolar concentrations, and the issue of Fe(II) reoxidation at lower Fe concentrations needs to be addressed.

Housing development in Latin America and the Caribean, its measuring and its determinants

This text briejly describes the Housing Development lndex (HDI). Following a concise introduction on the reasons for this research, HDI's methodology, characteristics, properties and databases supporting its calculation are discussed. Next, the third part presents, analyzes and compares the HDI's figures for Brazil and some other Latin American countries. The part that follows shows HDI figures for all states in Brazil and points out the regional differences and the indicator 's recent growth. Then, this paper analyses the injluence of some social and economic variables on the HDI and, finally, it makes some considerations on HDI.

Measuring core inflation as the common trend of prices

In recent years, many central banks have adopted inflation targeting policies starting an intense debate about which measure of inflation to adopt. The literature on core inflation has tried to develop indicators of inflation which would respond only to "significant" changes in inflation. This paper defines a measure of core inflation as the common trend of prices in a multivariate dynamic model, that has, by construction, three properties: it filters idiosyncratic and transitory macro noises, and it leads the future leveI of headline inflation. We also show that the popular trimmed mean estimator of core inflation could be regarded as a proxy for the ideal GLS estimator for heteroskedastic data. We employ an asymmetric trimmed mean estimator to take account of possible skewness of the distribution, and we obtain an unconditional measure of core inflation.