Milieuverliezen Aver Heino binnen de perken

Het project 'Echt Overijssel!' streeft naar een grote rijkdom aan planten- en diersoorten op en rond landbouwgronden, regionaal gesloten grondstofkringlopen en nieuwe economische dragers voor het landelijk gebied. Voor Aver Heino, het proefbedrijf voor biologische melkveehouderij, wordt berekend wat de milieueffecten zijn van het betrekken van meer grondstoffen uit de eigen regio

Can false memories be created through nonconscious processes?

Presentation times of study words presented in the Deese/Roediger and McDermott (DRM) paradigm varied from 20 ms to 2000 ms per word in an attempt to replicate the false memory effect following extremely short presentations reported by J.G. Seamon, C.R. Luo and D.A. Gallo (1998). Both in a within-subjects design (Experiment 1) and in a between-subjects design (Experiment 2) subjects showed memory for studied words as well as a false memory effect for related critical lures in the 2000-ms condition. However, in the

Surface melting of methane and methane film on magnesium oxide

Experiments on surface melting of several organic materials have shown contradictory results. We study the Van der Waals interactions between interfaces in surface melting of the bulk CH_4 and interfacial melting of the CH_4 film on the MgO substrate. This analysis is based on the theory of Dzyaloshinskii, Lifshitz, and Pitaevskii for dispersion forces in materials characterized by the frequency dependent dielectric functions. These functions for magnesium oxide and methane are obtained from optical data using an oscillator model of the dielectric response. The results show that a repulsive interaction between the solid-liquid and liquid-vapor interfaces exists for the bulk methane. We also found that the van der Waals forces between two solid-liquid interfaces are attractive for the CH_4 film on the MgO substrate. This implies that the van der Waals forces induce the presence of complete surface melting for the bulk methane and the absence of interfacial melting for CH_4 on the MgO substrate.Comment: 11 pages, 4 ps figure

Time-varying effective EEG source connectivity: the optimization of model parameters*

Adaptive estimation methods based on general Kalman filter are powerful tools to investigate brain networks dynamics given the non-stationary nature of neural signals. These methods rely on two parameters, the model order p and adaptation constant c, which determine the resolution and smoothness of the time-varying multivariate autoregressive estimates. A sub-optimal filtering may present consistent biases in the frequency domain and temporal distortions, leading to fallacious interpretations. Thus, the performance of these methods heavily depends on the accurate choice of these two parameters in the filter design. In this work, we sought to define an objective criterion for the optimal choice of these parameters. Since residual- and information-based criteria are not guaranteed to reach an absolute minimum, we propose to study the partial derivatives of these functions to guide the choice of p and c. To validate the performance of our method, we used a dataset of human visual evoked potentials during face perception where the generation and propagation of information in the brain is well understood and a set of simulated data where the ground truth is available

Quantitative Neutron Dark-field Imaging through Spin-Echo Interferometry

Neutron dark field imaging constitutes a seminal progress in the field of neutron imaging as it combines real space resolution capability with information provided by one of the most significant neutron scattering techniques, namely small angle scattering. The success of structural characterizations bridging the gap between macroscopic and microscopic features has been enabled by the introduction of grating interferometers so far. The induced interference pattern, a spatial beam modulation, allows for mapping of small angle scattering signals and hence addressing microstructures beyond direct spatial resolution of the imaging system with high efficiency. However, to date the quantification in the small angle scattering regime is severely limited by the monochromatic approach. To overcome such drawback we here introduce an alternative and more flexible method of interferometric beam modulation utilizing a spin echo technique. This novel method facilitates straightforward quantitative dark field neutron imaging, i.e. the required quantitative microstructural characterization combined with real space image resolution. For the first time quantitative microstructural reciprocal space information from small angle neutron scattering becomes available together with macroscopic image information creating the potential to quantify several orders of magnitude in structure sizes simultaneousl

Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis.

In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singular-value decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~ 80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth

Hoog eiwitgehalte grasklaver in nazomer vraagt om actie

Eiwitarme bijvoeding is voor een goede eiwitbenutting in de nazomer onontbeerlijk

Reductie ammoniakemissie bij maximalisatie weidegang op biologische melkveebedrijven

The calculated effect of grazing on ammonia emission based on nine organic dairy farms was 3.3 grams per hour per cow grazing on annual basis. Those results were comparable to the results from a previous survey for a common model farm. Mainly due to the supply and discharge of manure, the variation in outcomes of the organic farms was bigger, since manure application affects ammonia emission significantly. Grazing only can serve as a mitigation measure if assurance is guaranteed, but here is no single solution to provide

Nonlinear Dynamics of the Perceived Pitch of Complex Sounds

We apply results from nonlinear dynamics to an old problem in acoustical physics: the mechanism of the perception of the pitch of sounds, especially the sounds known as complex tones that are important for music and speech intelligibility