938 research outputs found
Internationale concurrentiepositie van de Nederlandse vollegrondsgroenteteelt
Onderzoek naar de internationale concurrentiepositie van de Nederlandse vollegronds-groenteteelt. De vijf strategische thema's voor de toekomst van de Nederlandse vollegrondsgroentesector zijn: ketensamenwerking, kwaliteit, productinnovatie, arbeid en gewasbescherming. Deze conclusie volgt uit een SWOT-analyse op basis van een studie van de belangrijkste afzetmarkten én concurrenten Duitsland en het Verenigd Koninkrijk. Het onderzoek sluit af met een beschrijving van vier mogelijke marktstrategieën voor indi-viduele producenten en een aantal aanbevelingen voor de Nederlandse vollegrondsgroenteketen als geheel ter verbetering van de concurrentiekrach
Stresses in isostatic granular systems and emergence of force chains
Progress is reported on several questions that bedevil understanding of
granular systems: (i) are the stress equations elliptic, parabolic or
hyperbolic? (ii) how can the often-observed force chains be predicted from a
first-principles continuous theory? (iii) How to relate insight from isostatic
systems to general packings? Explicit equations are derived for the stress
components in two dimensions including the dependence on the local structure.
The equations are shown to be hyperbolic and their general solutions, as well
as the Green function, are found. It is shown that the solutions give rise to
force chains and the explicit dependence of the force chains trajectories and
magnitudes on the local geometry is predicted. Direct experimental tests of the
predictions are proposed. Finally, a framework is proposed to relate the
analysis to non-isostatic and more realistic granular assemblies.Comment: 4 pages, 2 figures, Corrected typos and clkearer text, submitted to
Phys. Rev. Let
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Ein neues Verfahren fĂŒr namensbasierte Zufallsstichproben von Migranten
The set of best methods for sampling mi- grant populations includes name-based sampling. So far this is done using either ad-hoc lists or onomastic dictionaries for the classi cation of names. This paper pro- poses a new name-based procedure, which uses a Bayes-classi er for the n-grams of the name. The new procedure is fault-tol- erant of alternate spellings, and also allows the classi cation of names that are not found in dictionaries. It was tested using the names of about 1.600 foreigners in the PASS panel. Finally, a CATI survey based on the new method in Hesse is described
A practical framework for tracing sources of Salmonella in a pig slaughter plant
Salmonella causes around 30 000 cases of human illness per year in The Netherlands, of which an estimated 25% is caused by pork. Salmonella carrying pigs and resident flora on slaughter equipment are relevant sources of carcass contamination. Although recognized, these sources from which and the routes through which Salmonella is transmitted to the pig carcasses during slaughter are not well understood in a quantitative way
Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases
BACKGROUND: Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL).
METHODS: We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients.
RESULTS: Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei.
CONCLUSION: The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls
Assessment and treatment of distorted schemas in sexual offenders
The aim of this review is to examine the literature related to the assessment and treatment of sex offendersâ distorted schemas. Where appropriate, the review draws upon current insights from the field of social cognition to aid in the critical evaluation of the findings. First, the review considers the various different methodologies for assessing distorted schemas, discussing their strengths and limitations. Second, the review examines the work related to the treatment of sex offendersâ schemas. Suggestions for future research, and the implications for clinical practice, are highlighted in the article
Static avalanches and Giant stress fluctuations in Silos
We propose a simple model for arch formation in silos. We show that small
pertubations (such as the thermal expansion of the beads) may lead to giant
stress fluctuations on the bottom plate of the silo. The relative amplitude
of these fluctuations are found to be power-law distributed, as
, . These fluctuations are related to large
scale `static avalanches', which correspond to long-range redistributions of
stress paths within the silo.Comment: 10 pages, 4 figures.p
Stress in frictionless granular material: Adaptive Network Simulations
We present a minimalistic approach to simulations of force transmission
through granular systems. We start from a configuration containing cohesive
(tensile) contact forces and use an adaptive procedure to find the stable
configuration with no tensile contact forces. The procedure works by
sequentially removing and adding individual contacts between adjacent beads,
while the bead positions are not modified. In a series of two-dimensional
realizations, the resulting force networks are shown to satisfy a linear
constraint among the three components of average stress, as anticipated by
recent theories. The coefficients in the linear constraint remain nearly
constant for a range of shear loadings up to about .6 of the normal loading.
The spatial distribution of contact forces shows strong concentration along
``force chains". The probability of contact forces of magnitude f shows an
exponential falloff with f. The response to a local perturbing force is
concentrated along two characteristic rays directed downward and laterally.Comment: 8 pages, 8 figure
Neurocognitive basis of model-based decision making and its metacontrol in childhood
Human behavior is supported by both goal-directed (model-based) and habitual (model-free) decision-making, each differing in its flexibility, accuracy, and computational cost. The arbitration between habitual and goal-directed systems is thought to be regulated by a process known as metacontrol. However, how these systems emerge and develop remains poorly understood. Recently, we found that while children between 5 and 11 years displayed robust signatures of model-based decision-making, which increased during this developmental period, there were substantial individual differences in the display of metacontrol. Here, we inspect the neurocognitive basis of model-based decision-making and metacontrol in childhood and focus this investigation on executive functions, fluid reasoning, and brain structure. A total of 69 participants between the ages of 6-13 completed a two-step decision-making task and an extensive behavioral test battery. A subset of 44 participants also completed a structural magnetic resonance imaging scan. We find that individual differences in metacontrol are specifically associated with performance on an inhibition task and individual differences in thickness of dorsolateral prefrontal, temporal, and superior-parietal cortices. These brain regions likely reflect the involvement of cognitive processes crucial to metacontrol, such as cognitive control and contextual processing
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