Cue validity and object-based attention

In a previous study, Egly, Driver, and Rafal (1994) observed both space- and object-based components of visual selective attention. However, the mechanisms underlying these two components and the relationship between them are not well understood. In the present research, with a similar paradigm, these issues were addressed by manipulating cue validity. Behavioral results indicated the presence of both space- and object-based components under high cue validity, similar to the results of Egly et al.'s study. In addition, under low cue validity, the space-based component was absent, whereas the object-based component was maintained. Further event-related potential results demonstrated an object-based effect at a sensory level over the posterior areas of brain, and a space-based effect over the anterior region. The present data suggest that the space- and object-based components reflect mainly voluntary and reflexive mechanisms, respectively

MUonE sensitivity to new physics explanations of the muon anomalous magnetic moment

The MUonE experiment aims at a precision measurement of the hadronic vacuum polarization contribution to the muon $g-2$, via elastic muon-electron scattering. Since the current muon $g-2$ anomaly hints at the potential existence of new physics (NP) related to the muon, the question then arises as to whether the measurement of hadronic vacuum polarization in MUonE could be affected by the same NP as well. In this work, we address this question by investigating a variety of NP explanations of the muon $g-2$ anomaly via either vector or scalar mediators with either flavor-universal, non-universal or even flavor-violating couplings to electrons and muons. We derive the corresponding MUonE sensitivity in each case and find that the measurement of hadronic vacuum polarization at the MUonE is not vulnerable to any of these NP scenarios.Comment: 30 pages, 12 figures, minor corrections and changes, more references, version to appear in JHE

Quantum dynamics of an Ising spin-chain in a random transverse field

We consider an Ising spin-chain in a random transverse magnetic field and compute the zero temperature wave vector and frequency dependent dynamic structure factor numerically by using Jordan-Wigner transformation. Two types of distributions of magnetic fields are introduced. For a rectangular distribution, a dispersing branch is observed, and disorder tends to broaden the dispersion peak and close the excitation gap. For a binary distribution, a non-dispersing branch at almost zero energy is recovered. We discuss the relationship of our work to the neutron scattering measurement in $\mathrm{LiHoF_4}$.Comment: 4 pages and 6 eps figures; minor clarifications were made; the text was shortened to add an additional figur

On the Feature Discovery for App Usage Prediction in Smartphones

With the increasing number of mobile Apps developed, they are now closely integrated into daily life. In this paper, we develop a framework to predict mobile Apps that are most likely to be used regarding the current device status of a smartphone. Such an Apps usage prediction framework is a crucial prerequisite for fast App launching, intelligent user experience, and power management of smartphones. By analyzing real App usage log data, we discover two kinds of features: The Explicit Feature (EF) from sensing readings of built-in sensors, and the Implicit Feature (IF) from App usage relations. The IF feature is derived by constructing the proposed App Usage Graph (abbreviated as AUG) that models App usage transitions. In light of AUG, we are able to discover usage relations among Apps. Since users may have different usage behaviors on their smartphones, we further propose one personalized feature selection algorithm. We explore minimum description length (MDL) from the training data and select those features which need less length to describe the training data. The personalized feature selection can successfully reduce the log size and the prediction time. Finally, we adopt the kNN classification model to predict Apps usage. Note that through the features selected by the proposed personalized feature selection algorithm, we only need to keep these features, which in turn reduces the prediction time and avoids the curse of dimensionality when using the kNN classifier. We conduct a comprehensive experimental study based on a real mobile App usage dataset. The results demonstrate the effectiveness of the proposed framework and show the predictive capability for App usage prediction.Comment: 10 pages, 17 figures, ICDM 2013 short pape

Transforms for intra prediction residuals based on prediction inaccuracy modeling

In intra video coding and image coding, the directional intra prediction is used to reduce spatial redundancy. Intra prediction residuals are encoded with transforms. In this paper, we develop transforms for directional intra prediction residuals. Specifically, we observe that the directional intra prediction is most effective in smooth regions and edges with a particular direction. In the ideal case, edges can be predicted fairly accurately with an accurate prediction direction. In practice, an accurate prediction direction is hard to obtain. Based on the inaccuracy of prediction direction that arises in the design of many practical video coding systems, we can estimate the residual variance and propose a class of transforms based on the estimated variance function. The proposed method is evaluated by the energy compaction property. Experimental results show that with the proposed method, the same amount of energy in directional intra prediction residuals can be preserved with a significantly smaller number of transform coefficients

New interpretation of matter-antimatter asymmetry based on branes and possible observational consequences

Motivated by the AMS project, we assume that after the Big Bang or inflation epoch, antimatter was repelled onto one brane which is separated from our brane where all the observational matter resides. It is suggested that CP may be spontaneously broken, the two branes would correspond to ground states for matter and antimatter respectively. Generally a complex scalar field which is responsible for the spontaneous CP violation, exists in the space between the branes and causes a repulsive force against the gravitation. A possible potential barrier prevents the mater(antimatter) particles to enter the space between two branes. However, by the quantum tunnelling, a sizable anti-matter flux may come to our brane. In this work by considering two possible models, i.e. the naive flat space-time and Randall-Sundrum models and using the observational data on the visible matter in our universe as inputs, we derive the antimatter flux which would be observed by the AMS detector.Comment: 10 pages, 4 figures and 2 tables. Replaced by new versio

White Mold Mushrooms Show Up

Over the last 10 days the weather was favorable for the production of soybean white mold mushrooms in Iowa. Yesterday we visited fields near Clear Lake in north central Iowa with crop consultant Dan Muff and found abundant white mold mushrooms in a continuous soybean field, which had a closed canopy with wonderful growth. The density of the mushrooms was very high, 3 apothecia/square foot, and soybean plants are likely to be infected. The early showing in such a large number in this field was due to early planting, good growth and a higher number of sclerotia from last year. According to Dan, this field had very bad white mold and this year it was planted April 29