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 $W$ 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 $\sim$7% in discovery reach of hadronic $W$ 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

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-$^{13}$C aligned in stretched polyvinyl acetate gels. This represents the first investigation of dipolar couplings as a perturbation on the indirect spin-spin $J$-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