Learning Equations for Extrapolation and Control

We present an approach to identify concise equations from data using a shallow neural network approach. In contrast to ordinary black-box regression, this approach allows understanding functional relations and generalizing them from observed data to unseen parts of the parameter space. We show how to extend the class of learnable equations for a recently proposed equation learning network to include divisions, and we improve the learning and model selection strategy to be useful for challenging real-world data. For systems governed by analytical expressions, our method can in many cases identify the true underlying equation and extrapolate to unseen domains. We demonstrate its effectiveness by experiments on a cart-pendulum system, where only 2 random rollouts are required to learn the forward dynamics and successfully achieve the swing-up task.Comment: 9 pages, 9 figures, ICML 201

Soil fauna and litter decomposition in primary and secondary forests and a mixed culture system in Amazonia.

Este relatório representa um relato das atividades efetuadas no segundo ano do projeto como também dos resultados obtidos dos dados de 1997-1998 e da primeira serie de experimentos de decomposição com sacos de liteira (serrapilheira). Baseado nos resultados ainda preliminares, as áreas de estudo podem ser organizadas numa série, começando da área de floresta primária FLO via um dos locais de plantação, POC, até o local de floresta secundária, SEC, e o segundo local de plantação, POA.bitstream/item/201401/1/Soil-Fauna-And-Litter-Decomposition-in-Primary...-1998.pdfSHIFT ENV 52. Annual Report 1998

Litter production, litter stocks and decomposition coefficients in a central Amazonian rain forest, a secondary forest and agroforestry systems.

Fine litter fall and stocks were determined from July 1997 to March 1999 in an area of primary rain forest (FLO), a 13-year old secondary forest (SEC), and two polyculture systems (agroforestry; POA and POC) in central Amazonia Brazil.Final Report 1996-1999

Microclimate 1997-1999 in primary forest, secondary forest and agroforestry systems in central Amazonia.

Rainfall, average maximum and minimum air temperature, and relative air humidity as measured at the Embrapa weather station all show that 1997 was a strong El Nino (ENSO) year.bitstream/item/181106/1/ID-5199-34-49.pdfFinal Report 1996-1999

Object-based analysis of simulated thunderstorms in Switzerland: application and validation of automated thunderstorm tracking with simulation data

We present a feasibility study for an object-based method to characterise thunderstorm properties in simulation data from convection-permitting weather models. An existing thunderstorm tracker, the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) algorithm, was applied to thunderstorms simulated by the Advanced Research Weather Research and Forecasting (AR-WRF) weather model at convection-permitting resolution for a domain centred on Switzerland. Three WRF microphysics parameterisations were tested. The results are compared to independent radar-based observations of thunderstorms derived using the MeteoSwiss Thunderstorms Radar Tracking (TRT) algorithm. TRT was specifically designed to track thunderstorms over the complex Alpine topography of Switzerland. The object-based approach produces statistics on the simulated thunderstorms that can be compared to object-based observation data. The results indicate that the simulations underestimated the occurrence of severe and very large hail compared to the observations. Other properties, including the number of storm cells per day, geographical storm hotspots, thunderstorm diurnal cycles, and storm movement directions and velocities, provide a reasonable match to the observations, which shows the feasibility of the technique for characterisation of simulated thunderstorms over complex terrain

Magnetodielectric detection of magnetic quadrupole order in Ba(TiO)Cu4_4(PO4_4)4_4 with Cu4_4O12_{12} square cupolas

In vortex-like spin arrangements, multiple spins can combine into emergent multipole moments. Such multipole moments have broken space-inversion and time-reversal symmetries, and can therefore exhibit linear magnetoelectric (ME) activity. Three types of such multipole moments are known: toroidal, monopole, and quadrupole moments. So far, however, the ME-activity of these multipole moments has only been established experimentally for the toroidal moment. Here, we propose a magnetic square cupola cluster, in which four corner-sharing square-coordinated metal-ligand fragments form a noncoplanar buckled structure, as a promising structural unit that carries an ME-active multipole moment. We substantiate this idea by observing clear magnetodielectric signals associated with an antiferroic ME-active magnetic quadrupole order in the real material Ba(TiO)Cu$_4$(PO$_4$)$_4$. The present result serves as a useful guide for exploring and designing new ME-active materials based on vortex-like spin arrangements.Comment: 4 figure

Structure and function of soil fauna communities in Amazonian anthropogenic and natural ecosystems.

The aim of our study was to judge the soil biological conditions in the plantations with regard to the aspired sustainability of agricultural and forestry systems

A quantitative model of the role of soil fauna in decomposition as affected by different forested cropping systems in central Amazonia.

The basic idea this study was the improvement of the traditional fallow system with slash burning for land preparation and differs in this respect from attenpts to develop completely new land-use systems, in the Manaus-AM (Brasil)

Independent data for transparent monitoring of greenhouse gas emissions from the land use sector – What do stakeholders think and need?

The agriculture, forestry and other land use (AFOLU) sectors contribute substantially to the net global anthropogenic greenhouse gas (GHG) emissions. To reduce these emissions under the Paris Agreement, effective mitigation actions are needed that require engagement of multiple stakeholders. Emission reduction also requires that accurate, consistent and comparable datasets are available for transparent reference and progress monitoring. Availability of free and open datasets and portals (referred to as independent data) increases, offering opportunities for improving and reconciling estimates of GHG emissions and mitigation options. Through an online survey, we investigated stakeholders’ data needs for estimating forest area and change, forest biomass and emission factors, and AFOLU GHG emissions. The survey was completed by 359 respondents from governmental, intergovernmental and non-governmental organizations, research institutes and universities, and public and private companies. These can be grouped into data users and data providers. Our results show that current open and freely available datasets and portals are only able to fulfil stakeholder needs to a certain degree. Users require a) detailed documentation regarding the scope and usability of the data, b) comparability between alternative data sources, c) uncertainty estimates for evaluating mitigation options, d) more region-specific and detailed data with higher accuracy for sub-national application, e) regular updates and continuity for establishing consistent time series. These requirements are found to be key elements for increasing overall transparency of data sources, definitions, methodologies and assumptions, which is required under the Paris Agreement. Raising awareness and improving data availability through centralized platforms are important for increasing engagement of data users. In countries with low capacities, independent data can support countries’ mitigation planning and implementation, and related GHG reporting. However, there is a strong need for further guidance and capacity development (i.e. ‘readiness support’) on how to make proper use of independent datasets. Continued investments will be needed to sustain programmes and keep improving datasets to serve the objectives of the many stakeholders involved in climate change mitigation and should focus on increased accessibility and transparency of data to encourage stakeholder involvement