2,120 research outputs found
Tagging Boosted Ws with Wavelets
We present a new technique for distinguishing the hadronic decays of boosted
heavy particles from QCD backgrounds based on wavelet transforms. As an initial
exploration, we illustrate the technique in the particular case of hadronic
boson decays, comparing it to the ``mass drop'' cut currently used by the LHC
experiments. We apply wavelet cuts, which make use of complementary
information, and in combination with the mass drop cut results in an
improvement of 7% in discovery reach of hadronic boson final states
over a wide range of transverse momenta.Comment: 14 pages, 5 figure
Evidence for a Common Representation of Decision Values for Dissimilar Goods in Human Ventromedial Prefrontal Cortex
To make economic choices between goods, the brain needs to compute representations of their values. A great deal of research has been performed to determine the neural correlates of value representations in the human brain. However, it is still unknown whether there exists a region of the brain that commonly encodes decision values for different types of goods, or if, in contrast, the values of different types of goods are represented in distinct brain regions. We addressed this question by scanning subjects with functional magnetic resonance imaging while they made real purchasing decisions among different categories of goods (food, nonfood consumables, and monetary gambles). We found activity in a key brain region previously implicated in encoding goal-values: the ventromedial prefrontal cortex (vmPFC) was correlated with the subjects' value for each category of good. Moreover, we found a single area in vmPFC to be correlated with the subjects' valuations for all categories of goods. Our results provide evidence that the brain encodes a "common currency" that allows for a shared valuation for different categories of goods
Neural Mechanisms Underlying Paradoxical Performance for Monetary Incentives Are Driven by Loss Aversion
Employers often make payment contingent on
performance in order to motivate workers. We used
fMRI with a novel incentivized skill task to examine
the neural processes underlying behavioral responses
to performance-based pay. We found that
individuals’ performance increased with increasing
incentives; however, very high incentive levels led
to the paradoxical consequence of worse performance.
Between initial incentive presentation and
task execution, striatal activity rapidly switched
between activation and deactivation in response
to increasing incentives. Critically, decrements in
performance and striatal deactivations were directly
predicted by an independent measure of behavioral
loss aversion. These results suggest that incentives
associated with successful task performance are
initially encoded as a potential gain; however, when
actually performing a task, individuals encode the
potential loss that would arise from failure
Goal Programming Approach for Selection of COTS Components in Designing a Fault Tolerant Modular Software System under Consensus Recovery Block Scheme
The application of computer systems has now crossed many different fields. Systems are becoming more software intensive. The requirements of the customer for a more reliable software led to the fact that software reliability is now an important research area. One method to improve software reliability is by the application of redundancy. A careful use of redundancy may allow the system to tolerate faults generated during software design and coding thus improving software reliability. The fault tolerant software systems are usually developed by integrating COTS (commercial off-the-shelf) software components. This paper is designed to select optimal components for a fault tolerant modular software system so as to maximize the overall reliability of the system with simultaneously minimizing the overall cost. A chance constrained goal programming model has been designed after considering the parameters corresponding to reliability and cost of the components as random variable. The random variable in this case has been considered as value which has known mean and standard deviation. A chance constraint goal programming technique is used to solve the model. The issue of compatibility among different commercial off-the shelf alternatives is also considered in the paper. Numerical illustrations are provided to demonstrate the model
Formalizing behavior-based planning for nonholonomic robots
In this paper we present a formalization of behavior-based planning for nonholonomic robotic systems. This work provides a framework that integrates features of reactive planning models with modern control-theory-based robotic approaches in the area of path-planning for nonholonomic robots. In particular, we introduce a motion description language, MDLe, that provides a formal basis for robot programming using behaviors, and at the same time permits incorporation of kinematic models of robots given in the form of differential equations. The structure of the language MDLe is such as to allow descriptions of triggers (generated by sensors) in the language. Feedback and feedforward control laws are selected and executed by the triggering events. We demonstrate the use of MDLe in the area of motion planning for nonholonomic robots. Such models impose limitations on stabilizability via smooth feedback, i.e. piecing together open loop and closed loop trajectories becomes essential in these circumstances, and MDLe enables one to describe such piecing together in a systematic manner. A reactive planner using the formalism of the paper is described. We demonstrate obstacle avoidance with limited range sensors as a test of this planner.
Measurement of Untruncated Nuclear Spin Interactions via Zero- to Ultra-Low-Field Nuclear Magnetic Resonance
Zero- to ultra-low-field nuclear magnetic resonance (ZULF NMR) provides a new
regime for the measurement of nuclear spin-spin interactions free from effects
of large magnetic fields, such as truncation of terms that do not commute with
the Zeeman Hamiltonian. One such interaction, the magnetic dipole-dipole
coupling, is a valuable source of spatial information in NMR, though many terms
are unobservable in high-field NMR, and the coupling averages to zero under
isotropic molecular tumbling. Under partial alignment, this information is
retained in the form of so-called residual dipolar couplings. We report zero-
to ultra-low-field NMR measurements of residual dipolar couplings in
acetonitrile-2-C aligned in stretched polyvinyl acetate gels. This
represents the first investigation of dipolar couplings as a perturbation on
the indirect spin-spin -coupling in the absence of an applied magnetic
field. As a consequence of working at zero magnetic field, we observe terms of
the dipole-dipole coupling Hamiltonian that are invisible in conventional
high-field NMR. This technique expands the capabilities of zero- to
ultra-low-field NMR and has potential applications in precision measurement of
subtle physical interactions, chemical analysis, and characterization of local
mesoscale structure in materials.Comment: 6 pages, 3 figure
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