797 research outputs found
Dynamics of history-dependent perceptual judgment
Identical physical inputs do not always evoke identical percepts. To investigate the role of stimulus history in tactile perception, we designed a task in which rats had to judge each vibrissal vibration, in a long series, as strong or weak depending on its mean speed. After a low-speed stimulus (trial n − 1), rats were more likely to report the next stimulus (trial n) as strong, and after a high-speed stimulus, they were more likely to report the next stimulus as weak, a repulsive effect that did not depend on choice or reward on trial n − 1. This effect could be tracked over several preceding trials (i.e., n − 2 and earlier) and was characterized by an exponential decay function, reflecting a trial-by-trial incorporation of sensory history. Surprisingly, the influence of trial n − 1 strengthened as the time interval between n − 1 and n grew. Human subjects receiving fingertip vibrations showed these same key findings. We are able to account for the repulsive stimulus history effect, and its detailed time scale, through a single-parameter model, wherein each new stimulus gradually updates the subject’s decision criterion. This model points to mechanisms underlying how the past affects the ongoing subjective experience
Oscillation Effects On Neutrinos From The Early Phase Of a Nearby Supernova
Neutrinos emitted during stellar core collapse leading to a supernova are
primarily of the electron neutrino type at source which may undergo oscillation
between flavor eigenstates during propagation to an earth-bound detector.
Although the number of neutrinos emitted during the pre-bounce collapse phase
is much smaller than that emitted in the post-bounce phase (in which all
flavors of neutrinos are emitted), a nearby supernova event may nevertheless
register a substantial number of detections from the pre-bounce phase at
SuperKamiokande (SK) and the Sudbury Neutrino Observatory (SNO). The
calorimetric measurement of the supernova neutrino fluence from this stage via
the charge current and neutral current detection channels in SNO and the
corresponding distortion of detected spectrum in SK over the no-oscillation
spectrum, can probe information about neutrino mass difference and mixing which
are illustrated here in terms of two- and three-flavor oscillation models
Ensembles of probability estimation trees for customer churn prediction
Customer churn prediction is one of the most, important elements tents of a company's Customer Relationship Management, (CRM) strategy In tins study, two strategies are investigated to increase the lift. performance of ensemble classification models, i.e (1) using probability estimation trees (PETs) instead of standard decision trees as base classifiers; and (n) implementing alternative fusion rules based on lift weights lot the combination of ensemble member's outputs Experiments ale conducted lot font popular ensemble strategics on five real-life chin n data sets In general, the results demonstrate how lift performance can be substantially improved by using alternative base classifiers and fusion tides However: the effect vanes lot the (Idol cut ensemble strategies lit particular, the results indicate an increase of lift performance of (1) Bagging by implementing C4 4 base classifiets. (n) the Random Subspace Method (RSM) by using lift-weighted fusion rules, and (in) AdaBoost, by implementing both
Driver behaviour with adaptive cruise control
This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts
Modeling of Wnt-mediated tissue patterning in vertebrate embryogenesis
During embryogenesis, morphogens form a concentration gradient in responsive tissue, which is then translated into a spatial cellular pattern. The mechanisms by which morphogens spread through a tissue to establish such a morphogenetic field remain elusive. Here, we investigate by mutually complementary simulations and in vivo experiments how Wnt morphogen transport by cytonemes differs from typically assumed diffusion-based transport for patterning of highly dynamic tissue such as the neural plate in zebrafish. Stochasticity strongly influences fate acquisition at the single cell level and results in fluctuating boundaries between pattern regions. Stable patterning can be achieved by sorting through concentration dependent cell migration and apoptosis, independent of the morphogen transport mechanism. We show that Wnt transport by cytonemes achieves distinct Wnt thresholds for the brain primordia earlier compared with diffusion-based transport. We conclude that a cytoneme-mediated morphogen transport together with directed cell sorting is a potentially favored mechanism to establish morphogen gradients in rapidly expanding developmental systems
VEHICLE OCCLUSION REMOVAL FROM SINGLE AERIAL IMAGES USING GENERATIVE ADVERSARIAL NETWORKS
Removing occluding objects such as vehicles from drivable areas allows precise extraction of road boundaries and related semantic objects such as lane-markings, which is crucial for several applications such as generating high-definition maps for autonomous driving. Conventionally, multiple images of the same area taken at different times or from various perspectives are used to remove occlusions and to reconstruct the occluded areas. Nevertheless, these approaches require large amounts of data, which are not always available. Furthermore, they do not work for static occlusions caused by, among others, parked vehicles. In this paper, we address occlusion removal based on single aerial images using generative adversarial networks (GANs), which are able to deal with the mentioned challenges. To this end, we adapt several state-of-the-art GAN-based image inpainting algorithms to reconstruct the missing information. Results indicate that the StructureFlow algorithm outperforms the competitors and the restorations obtained are robust, with high visual fidelity in real-world applications. Furthermore, due to the lack of annotated aerial vehicle removal datasets, we generate a new dataset for training and validating the algorithms, the Aerial Vehicle Occlusion Removal (AVOR) dataset. To the best of our knowledge, our work is the first to address vehicle removal using deep learning algorithms to enhance maps
The impact of customer-specific marketing expenses on customer retention and customer profitability
We study the effects of customer-specific marketing expenses on customer retention and customer profitability in a business-to-business setting. Using data from a company providing hygiene services, we look at the impact of a hitherto unstudied type of expense targeted at individual customer relationships: the offering of free equipment to customers. The data allow tracking the activities performed in more than 4,500 customer relationships over a period of 4 years. Retention rates are higher for customers targeted with free equipment, but this effect results from an interaction with customer size. First-order dynamic panel data analyses show that the impact of targeted marketing expenses on customer dollar profit is positive for large customers, but there is no effect for smaller customers. Thus, targeted marketing expenses seem to be a tool for relationship maintenance rather than customer development: they help in retaining large customers that generate more profit, but they do not seem to work in developing new customers into larger, more profitable ones
Simulation of FRET dyes allows quantitative comparison against experimental data
Fully understanding biomolecular function requires detailed insight into the systems’ structural dynamics. Powerful experimental techniques such as single molecule Förster Resonance Energy Transfer (FRET) provide access to such dynamic information yet have to be carefully interpreted. Molecular simulations can complement these experiments but typically face limits in accessing slow time scales and large or unstructured systems. Here, we introduce a coarse-grained simulation technique that tackles these challenges. While requiring only few parameters, we maintain full protein flexibility and include all heavy atoms of proteins, linkers, and dyes. We are able to sufficiently reduce computational demands to simulate large or heterogeneous structural dynamics and ensembles on slow time scales found in, e.g., protein folding. The simulations allow for calculating FRET efficiencies which quantitatively agree with experimentally determined values. By providing atomically resolved trajectories, this work supports the planning and microscopic interpretation of experiments. Overall, these results highlight how simulations and experiments can complement each other leading to new insights into biomolecular dynamics and function
Towards automatic near real-time traffic monitoring with an airborne wide angle camera system
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