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The simplified Simple Biosphere model (SSiB) has been validated using observed meteorological, turbulent flux, and vegetation property data from the Anglo-Brazilian Amazonian Climate Observation Study (ABRA-COS) over a forest clearing site. The results show that SSiB is able to simulate the observed fluxes realistically. The differences between the simulated and observed latent and sensible heat fluxes are less than 10 W m-2. Compared to previous deforestation experiments, the new vegetation dataset produces significantly different latent heat fluxes and surface temperatures in off-line and general circulation model (GCM) simulations. Using the new dataset, the GCM simulated surface temperature is about 2 K higher, and the simulated latent heat flux is about 25 W m-2 lower than that generated using a previous dataset. These differences can be expected to result in substantially different responses in rainfall and atmosphere circulation. The parameters that are most significant in producing such large differences are leaf area index and soil properties. This study again demonstrates that to realistically assess the climatic impact of land surface degradation a realistic specification of the land surface conditions within GCMs is crucial.

Systematic biases in U.S. summer integrations with the Center for Ocean-Land-Atmosphere Studies (COLA) atmospheric general circulation model (GCM) have been identified and analyzed. Positive surface air temperature biases of 2°-4°K occurred over the central United States. The temperature biases were coincident with the agricultural region of the central United States, where negative precipitation biases also occurred. The biases developed in June and became very significant during July and August. The impact of the crop area vegetation and soil properties on the biases was investigated in a series of numerical experiments. The biases were largely caused by the erroneous prescription of crop vegetation phenology in the surface model of the GCM. The prescribed crop soil properties also contributed to the biases. On the basis of these results the crop model has been improved and the systematic errors in the U.S. summer simulations have been reduced. The numerical experiments also revealed that land surface effects on the atmospheric variables at and near the surface during the North American summer are very pronounced and persistent but are largely limited to the area of the anomalous land surface forcing. In this regard, the midlatitude land surface effects described here are similar to those previously found for tropical regions. Copyright 1996 by the American Geophysical Union.

In many situations where people communicate (e.g., Twitter, Facebook etc), people self-organise into ‘echo chambers’ of like-minded individuals, with different echo chambers espousing very different beliefs. Why does this occur? Previous work has demonstrated that such belief polarisation can emerge even when all agents are completely rational, as long as their initial beliefs are heterogeneous and they do not automatically know who to trust. In this work, we used agent-based simulations to further investigate the mechanisms for belief polarisation. Our work extended previous work by using a more realistic scenario. In this scenario, we found that previously proposed methods for reducing belief polarisation did not work but we were able to find a new method that did. However, this same method could be reversed by adversarial entities to increase belief polarisation. We discuss how this danger can be best mitigated and what theoretical conclusions be drawn from our findings.

How humans produce cognitively driven fine motor movements is a question of fundamental importance in how we interact with the world around us. For example, we are exposed to a constant stream of information and we must select the information that is most relevant by which to guide our actions. In the present study, we employed a well-known behavioral assay called the Simon task to better understand how humans are able to learn to filter out irrelevant information. We trained subjects for four days with a visual stimulus presented, alternately, in central and lateral locations. Subjects responded with one hand moving a joystick in either the left or right direction. They were instructed to ignore the irrelevant location information and respond based on color (e.g. red to the right and green to the left). On the fifth day, an additional testing session was conducted where the task changed and the subjects had to respond by shape (e.g. triangle to the right and rectangle to the left). They were instructed to ignore the color and location, and respond based solely on the task relevant shape. We found that the magnitude of the Simon effect decreases with training, however it returns in the first few trials after a break. Furthermore, task-defined associations between response direction and color did not significantly affect the Simon effect based on shape, and no significant associative learning from the specific stimulus-response features was found for the centrally located stimuli. We discuss how these results are consistent with a model involving route suppression/gating of the irrelevant location information. Much of the learning seems to be driven by subjects learning to suppress irrelevant location information, however, this seems to be an active inhibition process that requires a few trials of experience to engage.

This guide provides urban food producers in California with an overview of Federal and California food safety laws and regulations that may impact their operations.

Motions of molecules adsorbed to surfaces may control the rate of charge transport within monolayers in systems such as dye sensitized solar cells. We used quasi-elastic neutron scattering (QENS) to evaluate the possible dynamics of two small dye moieties, isonicotinic acid (INA) and bis-isonicotinic acid (BINA), attached to TiO₂ nanoparticles via carboxylate groups. The scattering data indicate that moieties are immobile and do not rotate around the anchoring groups on timescales between around 10 ps and a few ns (corresponding to the instrumental range). This gives an upper limit for the rate at which conformational fluctuations can assist charge transport between anchored molecules. Our observations suggest that if the conformation of larger dye molecules varies with time, it does so on longer timescales and/or in parts of the molecule which are not directly connected to the anchoring group. The QENS measurements also indicate that several layers of acetonitrile solvent molecules are immobilized at the interface with the TiO₂ on the measurement time scale, in reasonable agreement with recent classical molecular dynamics results.

Perceptual training has been shown to be an effective and rapid way of training people to make simple diagnoses using medical images. However, it appears to be less effective at training people to make more complex diagnoses that require non-binary judgements. In the present study, we investigated whether perceptual training could be augmented to make it more effective and what factors limited its effectiveness. In Experiment 1, we created artificial stimuli that were designed to simulate liver ultrasound images to assess perceptual learning for a complex task that involved judgements on a 7-point scale. Whilst performance improved somewhat with training, we found that incorporating annotations into the training provided no benefits. Additionally, contrary to our expectations, training that was structured in a stepped fashion was detrimental to learning. In Experiment 2, we found that perceptual learning in a simple task with shaded disks was most impacted by the extent to which the brightness levels of each disk were discriminable but that attending to multiple locations did not result in a significant cost to performance. Our findings show that augmenting perceptual training does not increase learning and that learning is less when the relevant features are harder to discriminate.