Bandits in the Lab

We test Keller, Rady, Cripps’ (2005) game of strategic experimentation with exponential bandits in the laboratory. We find strong support for the prediction of free-riding because of strategic concerns. We also find strong evidence for behavior that is characteristic of Markov perfect equilibrium: non-cutoff behavior, lonely pioneers and frequent switches of action

Improving Deep Learning for HAR with shallow LSTMs

Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning methods are able to outperform classical Machine Learning algorithms. One popular Deep Learning architecture in HAR is the DeepConvLSTM. In this paper we propose to alter the DeepConvLSTM architecture to employ a 1-layered instead of a 2-layered LSTM. We validate our architecture change on 5 publicly available HAR datasets by comparing the predictive performance with and without the change employing varying hidden units within the LSTM layer(s). Results show that across all datasets, our architecture consistently improves on the original one: Recognition performance increases up to 11.7% for the F1-score, and our architecture significantly decreases the amount of learnable parameters. This improvement over DeepConvLSTM decreases training time by as much as 48%. Our results stand in contrast to the belief that one needs at least a 2-layered LSTM when dealing with sequential data. Based on our results we argue that said claim might not be applicable to sensor-based HAR.Comment: 6 pages, 2 figures, accepted at ISWC 21: International Symposium on Wearable Computer, Sept, 202

Estimativa de Emissão de Monóxido de Carbono e de Metano para o Nordeste do Brasil

O entendimento das emissões provenientes da queima dos resíduos agrícolas é de grande importância para a modelagem química atmosférica, economia, saúde, e para a compreensão do comportamento das espécies químicas emitidas na atmosfera, que tem um efeito no meio ambiente e no clima.Segundo o IPCC (2007) o metano (CH4) é cerca 21 vezes mais eficiente na retenção de calor do que o CO2. O objetivo desse trabalho foi estimar as emissões de monóxido de carbono e de metano a partir da produção de cana-de-açúcar para o Nordeste Brasileiro (NEB), para contribuir para a quantificação de emissões da regiã

Emissions of primary aerosol and precursor gases in the year 2000 and 1750 prescribed data-sets for AeroCom.

Inventories for global aerosol and aerosol precursor emissions have been collected (based on published inventories and published simulations), assessed and prepared for the year 2000 (present-day conditions) and for the year 1750 (pre-industrial conditions). These global datasets establish a comprehensive source for emission input to global modeling, when simulating the aerosol impact on climate with state-of-the-art aerosol component modules. As these modules stratify aerosol into dust, sea-salt, sulfate, organic matter and soot, for all these aerosol types global fields on emission strength and recommendations for injection altitude and particulate size are provided. Temporal resolution varies between daily (dust and sea-salt), monthly (wild-land fires) and annual (all other emissions). These datasets benchmark aerosol emissions according to the knowledge in the year 2004. They are intended to serve as systematic constraints in sensitivity studies of the AeroCom initiative, which seeks to quantify (actual) uncertainties in aerosol global modeling

Evaluation of atmospheric aerosols in the metropolitan area of São Paulo simulated by the regional EURAD-IM model on high-resolution

We present a high-resolution air quality study over São Paulo, Brazil with the EURopean Air Pollution Dispersion - Inverse Model (EURAD-IM) used for the first time over South America simulating detailed features of aerosols. Modeled data are evaluated with observational surface data and a Lidar. Two case studies in 2016 with distinct meteorological conditions and pollution plume features show transport (i) from central South America, associated to biomass burning activities, (ii) from the rural part of the state of São Paulo, (iii) between the metropolitan areas of Rio de Janeiro and São Paulo (MASP) either through the Paraíba Valley or via the ocean, connecting Brazil's two largest cities, (iv) from the port-city Santos to MASP and also from MASP to the city Campinas, and vice versa. A Pearson coefficient of 0.7 was found for PM10 at MASP CENTER and EURAD-IM simulations vary within the observational standard deviation, with a Mean Percentual Error (MPE) of 10%. The model's vertical distributions of aerosol layers agree with the Lidar profiles that show either characteristics of long-range transported biomass burning plumes, or of local pollution. The distinct transport patterns that agree with satellite Aerosol Optical Death and fire spot images as well as with the ground-based observations within the standard deviations, allows us exploring patterns of air pollution in a detailed manner and to understand the complex interactions between local to long-range transport sources.This study was financed in part by the Coordenaç ̃ao de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001, Brazil, for the doctoral scholarship granted. This article and the research behind it are a direct contribution to the research themes of the Klimapolis Laboratory (klimapolis.net

Improving global estimates of atmospheric emissions from biomass burning

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94770/1/jgrd11567.pd

Global burned area and biomass burning emissions from small fires

[1] In several biomes, including croplands, wooded savannas, and tropical forests, many small fires occur each year that are well below the detection limit of the current generation of global burned area products derived from moderate resolution surface reflectance imagery. Although these fires often generate thermal anomalies that can be detected by satellites, their contributions to burned area and carbon fluxes have not been systematically quantified across different regions and continents. Here we developed a preliminary method for combining 1-km thermal anomalies (active fires) and 500 m burned area observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the influence of these fires. In our approach, we calculated the number of active fires inside and outside of 500 m burn scars derived from reflectance data. We estimated small fire burned area by computing the difference normalized burn ratio (dNBR) for these two sets of active fires and then combining these observations with other information. In a final step, we used the Global Fire Emissions Database version 3 (GFED3) biogeochemical model to estimate the impact of these fires on biomass burning emissions. We found that the spatial distribution of active fires and 500 m burned areas were in close agreement in ecosystems that experience large fires, including savannas across southern Africa and Australia and boreal forests in North America and Eurasia. In other areas, however, we observed many active fires outside of burned area perimeters. Fire radiative power was lower for this class of active fires. Small fires substantially increased burned area in several continental-scale regions, including Equatorial Asia (157%), Central America (143%), and Southeast Asia (90%) during 2001–2010. Globally, accounting for small fires increased total burned area by approximately by 35%, from 345 Mha/yr to 464 Mha/yr. A formal quantification of uncertainties was not possible, but sensitivity analyses of key model parameters caused estimates of global burned area increases from small fires to vary between 24% and 54%. Biomass burning carbon emissions increased by 35% at a global scale when small fires were included in GFED3, from 1.9 Pg C/yr to 2.5 Pg C/yr. The contribution of tropical forest fires to year-to-year variability in carbon fluxes increased because small fires amplified emissions from Central America, South America and Southeast Asia—regions where drought stress and burned area varied considerably from year to year in response to El Nino-Southern Oscillation and other climate modes