Processing irrelevant location information: practice and transfer effects in a Simon task.

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

Weak Lensing Reconstruction and Power Spectrum Estimation: Minimum Variance Methods

Large-scale structure distorts the images of background galaxies, which allows one to measure directly the projected distribution of dark matter in the universe and determine its power spectrum. Here we address the question of how to extract this information from the observations. We derive minimum variance estimators for projected density reconstruction and its power spectrum and apply them to simulated data sets, showing that they give a good agreement with the theoretical minimum variance expectations. The same estimator can also be applied to the cluster reconstruction, where it remains a useful reconstruction technique, although it is no longer optimal for every application. The method can be generalized to include nonlinear cluster reconstruction and photometric information on redshifts of background galaxies in the analysis. We also address the question of how to obtain directly the 3-d power spectrum from the weak lensing data. We derive a minimum variance quadratic estimator, which maximizes the likelihood function for the 3-d power spectrum and can be computed either from the measurements directly or from the 2-d power spectrum. The estimator correctly propagates the errors and provides a full correlation matrix of the estimates. It can be generalized to the case where redshift distribution depends on the galaxy photometric properties, which allows one to measure both the 3-d power spectrum and its time evolution.Comment: revised version, 36 pages, AAS LateX, submitted to Ap

Behavior of heuristics and state space structure near SAT/UNSAT transition

We study the behavior of ASAT, a heuristic for solving satisfiability problems by stochastic local search near the SAT/UNSAT transition. The heuristic is focused, i.e. only variables in unsatisfied clauses are updated in each step, and is significantly simpler, while similar to, walksat or Focused Metropolis Search. We show that ASAT solves instances as large as one million variables in linear time, on average, up to 4.21 clauses per variable for random 3SAT. For K higher than 3, ASAT appears to solve instances at the ``FRSB threshold'' in linear time, up to K=7.Comment: 12 pages, 6 figures, longer version available as MSc thesis of first author at http://biophys.physics.kth.se/docs/ardelius_thesis.pd

Reconstruction methods — P‾ANDA focussing-light guide disc DIRC

The Focussing-Lightguide Disc DIRC will provide crucial Particle Identification (PID) information for the P‾ANDA experiment at FAIR, GSI. This detector presents a challenging environment for reconstruction due to the complexity of the expected hit patterns and the operating conditions of the P‾ANDA experiment. A discussion of possible methods to reconstruct PID from this detector is given here. Reconstruction software is currently under development

The GALATEA Test-Facility for High Purity Germanium Detectors

GALATEA is a test facility designed to investigate bulk and surface effects in high purity germanium detectors. A vacuum tank houses an infrared screened volume with a cooled detector inside. A system of three stages allows an almost complete scan of the detector. The main feature of GALATEA is that there is no material between source and detector. This allows the usage of alpha and beta sources as well as of a laser beam to study surface effects. A 19-fold segmented true-coaxial germanium detector was used for commissioning

Single Proton Knock-Out Reactions from 24,25,26F

The cross sections of the single proton knock-out reactions from 24F, 25F, and 26F on a 12C target were measured at energies of about 50 MeV/nucleon. Ground state populations of 6.6+-.9 mb, 3.8+-0.6 mb for the reactions 12C(24F,23O) and 12C(25F,24O) were extracted, respectively. The data were compared to calculations based on the many-body shell model and the eikonal theory. In the reaction 12C(26F,25O) the particle instability of 25O was confirmed

Влияние скорости ветра на размер противопожарных разрывов

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