Testing WWγWW\gamma vertex in radiative muon decay

Large numbers of muons will be produced at facilities developed to probe lepton flavor violating process $\mu\to e\gamma$. We show that by constructing a suitable asymmetry, radiative muon decay $\mu\to e \gamma\nu_\mu\bar{\nu}_e$ can also be used to test the $WW\gamma$ vertex at such facilities. The process has two missing neutrinos in the final state and on integrating their momenta, the partial differential decay rate shows no radiation-amplitude-zero. We establish, however, that an easily separable part of the normalized differential decay rate, odd under the exchange of photon and electron energies, does have a zero in the case of standard model (SM). This "new type of zero" has hitherto not been studied in literature. A suitably constructed asymmetry using this fact, enables a sensitive probe for the $WW\gamma$ vertex beyond the SM. With a simplistic analysis, we find that the $C$ and $P$ conserving dimension four $WW\gamma$ vertex can be probed at ${\cal O}(10^{-2})$ with satisfactory significance level.Comment: 9 pages, 4 figure

Computational examination of compaction wave-boundary interaction in granular explosive

Interactions between initially planar, piston supported compaction waves in heterogeneous energetic solids and macro-scale rigid boundaries were computationally examined for a wide range of piston impact speeds (20 ≤ Up ≤ 500 m/s) and initial solid volume fractions of the material (0.73 ≤ ϕ0 ≤ 0.90). The response of the material was described by a continuum theory that accounts for both elastic and inelastic compaction in a thermodynamically consistent manner. Initial conditions were imposed by interpolating the spatial structure of one-dimensional steady compaction waves onto two-dimensional domains considered in this study. For a planar wedge boundary, the peak solid pressure (Ps), dissipative heating rate (ėc) and bulk temperature rise (ΔT) at the boundary increased when wedge angle θ was increased from 0º to a critical value (60º ≤ θc ≤ 65º) as the flow transitioned to a single Mach reflection (SMR) from a von Neumann reflection (vNR); these quantities decreased when θ was further increased due to flow transition to a regular reflection (RR) from a SMR for ϕ0 = 0.85 and Up = 500 m/s. Locations of the peak Ps, ėc and ΔT were predicted to be removed from the wedge tip for a vNR and a SMR, but near the wedge tip for a RR. Qualitatively similar predictions were obtained for 0.73 ≤ ϕ0 ≤ 0.90 and Up ≥ 150 m/s. For a semi-circular boundary, the initial RR configuration transitioned to a SMR for all cases. For 0.73 ≤ ϕ0 ≤ 0.90 and Up ≥ 150 m/s, peak values of Ps, ėc and ΔT were predicted at a location removed from the stagnation point. For both wedge and semi-circular boundaries, dissipative heating at the boundary was dominated by rate-dependent compaction. To aid in the development of a bulk-scale combustion sub-model, bulk-scale predictions were compared to locally averaged meso-scale predictions. Bulk-scale and averaged meso-scale predictions showed good agreement, provided that the averaging area size was suitably selected

An Improved Minimum Redundancy Maximum Relevance Approach for Feature Selection in Gene Expression Data

AbstractIn this article, an improved feature selection technique has been proposed. Mutual Information is taken as the basic criterion to find the feature relevance and redundancy. The mutual information between a feature and class labels defines the relevance of that feature. Again, the mutual information among different features defines the correlation i.e., the redundancy among those features. Now our objective is to find such a feature set for which the mutual information among the features and the class labels are maximized and the mutual information among the features are minimized. Therefore, the goal of the proposed method is to find the most relevant and least redundant feature set. The number of output features is provided by the user. First the most relevant feature is added to the empty final feature set. Then in each iteration a non-dominated feature set with respect to relevance and redundancy is generated and from this set of features, the most relevant and non-redundant feature is included in the final feature set. Thereafter, in an incremental way a feature is added in every iteration and this step is repeated while the size of the final feature set is equal to the user given number of features. The features contained by the final feature set have maximum relevance and least correlation. The proposed method is applied on microarray gene expression data to find the most relevant and non-redundant genes and the performance of the proposed method is compared with that of the popular mRMR (MIQ) and mRMR (MID) schemes on several real-life data sets

Is it Difficult to Treat Asthma in Children?

Asthma, the commonest chronic lung disease in childhood, is managed effectively with inhaled medications in most of the cases. But a subset of pediatric asthma patients continues to experience substantial morbidity even after higher doses of medications; they are referred to as problematic severe asthma. In many such cases, the apparent resistance to therapy is actually due to a number of remediable factors. These cases are called ‘difficult to treat asthma’. The physician dealing with a child with problematic severe asthma needs to follow a systematic step- wise approach to find any possible underlying causes of poor response to therapy. The evaluation starts with revisiting the diagnosis of asthma and goes through a checking the prescription, patient compliance, assessment for co-morbidities, environmental triggers and psychological factors. Only in a very small number of cases where no such remediable factors are identified, a diagnosis of severe therapy-resistant asthma is made and the child should be referred to a pediatric pulmonologist for further evaluation and therapy