A Neural-Symbolic Cognitive Agent for Online Learning and Reasoning

In real-world applications, the effective integration of learning and reasoning in a cognitive agent model is a difficult task. However, such integration may lead to a better understanding, use and construction of more realistic models. Unfortunately, existing models are either oversimplified or require much processing time, which is unsuitable for online learning and reasoning. Currently, controlled environments like training simulators do not effectively integrate learning and reasoning. In particular, higher-order concepts and cognitive abilities have many unknown temporal relations with the data, making it impossible to represent such relationships by hand. We introduce a novel cognitive agent model and architecture for online learning and reasoning that seeks to effectively represent, learn and reason in complex training environments. The agent architecture of the model combines neural learning with symbolic knowledge representation. It is capable of learning new hypotheses from observed data, and infer new beliefs based on these hypotheses. Furthermore, it deals with uncertainty and errors in the data using a Bayesian inference model. The validation of the model on real-time simulations and the results presented here indicate the promise of the approach when performing online learning and reasoning in real-world scenarios, with possible applications in a range of areas

In-flight degradation correction of SCIAMACHY UV reflectances and Absorbing Aerosol Index

In this paper we study the close relationship between the radiometric calibration of a satellite instrument and the Absorbing Aerosol Index (AAI) derived from the observed Earth reflectance. Instrument degradation of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument in the ultraviolet wavelength range is examined by analyzing time series of global means of the AAI, making use of the experience that the global mean should be more or less constant when instrument degradation is absent. The analysis reveals the magnitude of the (scan angle dependent) instrument degradation of SCIAMACHY and also shows that currently available correction techniques are not able to correct the instrument degradation in a sufficient manner. We therefore develop and introduce a new method for degradation correction, which is based on the analysis of the time evolution of the global mean reflectance. Seasonal variations in the global mean reflectance, which mainly result from seasonal variations in scattering geometry and global cloud coverage, are separated from the time series in order to isolate the instrument degradation. Finally, we apply the derived reflectance correction factors to the SCIAMACHY reflectances and calculate the AAI to find that the effects of instrument degradation are reduced to within the 0.1 index point level. The derived AAI is also compared with the AAI based on other correction techniques. The proposed in-flight reflectance degradation correction method performs best in all aspects. © 2012 by the American Geophysical Union

Modelling diverse root density dynamics and deep nitrogen uptake — a simple approach

We present a 2-D model for simulation of root density and plant nitrogen (N) uptake for crops grown in agricultural systems, based on a modification of the root density equation originally proposed by Gerwitz and Page in J Appl Ecol 11:773–781, (1974). A root system form parameter was introduced to describe the distribution of root length vertically and horizontally in the soil profile. The form parameter can vary from 0 where root density is evenly distributed through the soil profile, to 8 where practically all roots are found near the surface. The root model has other components describing root features, such as specific root length and plant N uptake kinetics. The same approach is used to distribute root length horizontally, allowing simulation of root growth and plant N uptake in row crops. The rooting depth penetration rate and depth distribution of root density were found to be the most important parameters controlling crop N uptake from deeper soil layers. The validity of the root distribution model was tested with field data for white cabbage, red beet, and leek. The model was able to simulate very different root distributions, but it was not able to simulate increasing root density with depth as seen in the experimental results for white cabbage. The model was able to simulate N depletion in different soil layers in two field studies. One included vegetable crops with very different rooting depths and the other compared effects of spring wheat and winter wheat. In both experiments variation in spring soil N availability and depth distribution was varied by the use of cover crops. This shows the model sensitivity to the form parameter value and the ability of the model to reproduce N depletion in soil layers. This work shows that the relatively simple root model developed, driven by degree days and simulated crop growth, can be used to simulate crop soil N uptake and depletion appropriately in low N input crop production systems, with a requirement of few measured parameters

Quantifying measures to limit wind driven resuspension of sediments for improvement of the ecological quality in some shallow Dutch lakes

Although phosphorus loadings are considered the main pressure for most shallow lakes, wind-driven resuspension can cause additional problems for these aquatic ecosystems. We quantified the potential effectiveness of measures to reduce the contribution of resuspended sediments, resulting from wind action, to the overall light attenuation for three comparable shallow peat lakes with poor ecological status in the Netherlands: Loosdrecht, Nieuwkoop, and Reeuwijk (1.8–2.7 m depth, 1.6–2.5 km fetch). These measures are: 1. wave reducing barriers, 2. water level fluctuations, 3. capping of the sediment with sand, and 4. combinations of above. Critical shear stress of the sediments for resuspension (Vcrit), size distribution, and optical properties of the suspended material were quantified in the field (June 2009) and laboratory. Water quality monitoring data (2002–2009) showed that light attenuation by organic suspended matter in all lakes is high. Spatial modeling of the impact of these measures showed that in Lake Loosdrecht limiting wave action can have significant effects (reductions from 6% exceedance to 2% exceedance of Vcrit), whereas in Lake Nieuwkoop and Lake Reeuwijk this is less effective. The depth distribution and shape of Lake Nieuwkoop and Lake Reeuwijk limit the role of wind-driven resuspension in the total suspended matter concentration. Although the lakes are similar in general appearance (origin, size, and depth range) measures suitable to improve their ecological status differ. This calls for care when defining the programme of measures to improve the ecological status of a specific lake based on experience from other lakes.

microRNA-132 regulates gene expression programs involved in microglial homeostasis

microRNA-132 (miR-132), a known neuronal regulator, is one of the most robustly downregulated microRNAs (miRNAs) in the brain of Alzheimer's disease (AD) patients. Increasing miR-132 in AD mouse brain ameliorates amyloid and Tau pathologies, and also restores adult hippocampal neurogenesis and memory deficits. However, the functional pleiotropy of miRNAs requires in-depth analysis of the effects of miR-132 supplementation before it can be moved forward for AD therapy. We employ here miR-132 loss- and gain-of-function approaches using single-cell transcriptomics, proteomics, and in silico AGO-CLIP datasets to identify molecular pathways targeted by miR-132 in mouse hippocampus. We find that miR-132 modulation significantly affects the transition of microglia from a disease-associated to a homeostatic cell state. We confirm the regulatory role of miR-132 in shifting microglial cell states using human microglial cultures derived from induced pluripotent stem cells

Avaliação visual para o monitoramento da qualidade estrutural do solo: VESS e VSA.

bitstream/item/125514/1/Documento-390.pd

Journal Staff

We present the first measurements of the differential cross section d sigma/dp(T)(gamma) for the production of an isolated photon in association with at least two b-quark jets. The measurements consider photons with rapidities vertical bar y(gamma)vertical bar < 1.0 and transverse momenta 30 < p(T)(gamma) < 200 GeV. The b-quark jets are required to have p(T)(jet) > 15 GeVand vertical bar y(jet)vertical bar < 1.5. The ratio of differential production cross sections for gamma + 2 b-jets to gamma + b-jet as a function of p(T)(gamma) is also presented. The results are based on the proton-antiproton collision data at root s = 1.96 TeV collected with the D0 detector at the Fermilab Tevatron Collider. The measured cross sections and their ratios are compared to the next- to- leading order perturbative QCD calculations as well as predictions based on the k(T)- factorization approach and those from the sherpa and pythia Monte Carlo event generators

Precise measurement of the top quark mass in the dilepton channel at D0

We measure the top quark mass (mt) in ppbar collisions at a center of mass energy of 1.96 TeV using dilepton ttbar->W+bW-bbar->l+nubl-nubarbbar events, where l denotes an electron, a muon, or a tau that decays leptonically. The data correspond to an integrated luminosity of 5.4 fb-1 collected with the D0 detector at the Fermilab Tevatron Collider. We obtain mt = 174.0 +- 1.8(stat) +- 2.4(syst) GeV, which is in agreement with the current world average mt = 173.3 +- 1.1 GeV. This is currently the most precise measurement of mt in the dilepton channel.Comment: 7 pages, 4 figure