Muon anomalous magnetic moment and lepton flavor violation in MSSM

We give a thorough analysis of the correlation between the muon anomalous magnetic moment and the radiative lepton flavor violating (LFV) processes within the minimal supersymmetric standard model. We find that in the case when the slepton mass eigenstates are nearly degenerate, $\delta a_\mu$, coming from SUSY contributions, hardly depends on the lepton flavor mixing and, thus, there is no direct relation between $\delta a_\mu$ and the LFV processes. On the contrary, if the first two generations' sleptons are much heavier than the 3rd one, i.e., in the effective SUSY scenario, the two quantities are closely related. In the latter scenario, the SUSY parameter space to account for the experimental $\delta a_\mu$ is quite different from the case of no lepton flavor mixing. Especially, the Higgsino mass parameter $\mu$ can be either positive or negative.Comment: 22 pages, 9 figures; Some discussions are modifie

VHE gamma ray absorption by galactic interstellar radiation field

Adopting a recent calculation of the Galactic interstellar radiation field, we calculate the attenuation of the very high energy gamma rays from the Galactic sources. The infra-red radiation background near the Galactic Center is very intense due to the new calculation and our result shows that a cutoff of high energy gamma ray spectrum begins at about 20 TeV and reaches about 10% for 50 TeV gamma rays.Comment: 6 pages, 1 figure, figure is changed, conclusion not change

An L1 image transform for edge-preserving smoothing and scene-level intrinsic decomposition

Identifying sparse salient structures from dense pixels is a longstanding problem in visual computing. Solutions to this problem can benefit both image manipulation and understanding. In this paper, we introduce an image transform based on the L1 norm for piecewise image flattening. This transform can effectively preserve and sharpen salient edges and contours while eliminating insignificant details, producing a nearly piecewise constant image with sparse structures. A variant of this image transform can perform edge-preserving smoothing more effectively than existing state-of-the-art algorithms. We further present a new method for complex scene-level intrinsic image decomposition. Our method relies on the above image transform to suppress surface shading variations, and perform probabilistic reflectance clustering on the flattened image instead of the original input image to achieve higher accuracy. Extensive testing on the Intrinsic-Images-in-the-Wild database indicates our method can perform significantly better than existing techniques both visually and numerically. The obtained intrinsic images have been successfully used in two applications, surface retexturing and 3D object compositing in photographs.postprin

Suggestions for solution space exploration in the early stage of architectural design based on a literature review

Early design decisions have higher potential to influence building performance compared with the decisions made at later design stages. Performance simulation and optimization algorithms have been integrated to assist early design in reducing carbon emissions, improving indoor thermal comfort, etc. However, early decision making within a limited time frame is still challenging due to the large number of design options, the lack of decision-making guidance, and the trade-offs among various requirements. Selecting appropriate methods to explore design space is the key to find an ideal solution. This paper reviewed the challenges and identified the key questions to access the ability of existing decision-making methods to cope with different challenges. It is concluded that the interactive exploration of design space could be more effective and efficient by (1) combining the surrogate models and the automated optimization algorithms to improve the efficiency of the building performance calculation and the optimal design space position; and by (2) extending the optimal design space to increase the solution diversity, and (3) filtering the near optimal design space with consideration of the stakeholders\u27 preferences and values. Further integration of tools for building performance simulation, diversity description and decision-making guidance is needed to support the decision -making process

Multi-Level Cross Residual Network for Lung Nodule Classification.

Computer-aided algorithm plays an important role in disease diagnosis through medical images. As one of the major cancers, lung cancer is commonly detected by computer tomography. To increase the survival rate of lung cancer patients, an early-stage diagnosis is necessary. In this paper, we propose a new structure, multi-level cross residual convolutional neural network (ML-xResNet), to classify the different types of lung nodule malignancies. ML-xResNet is constructed by three-level parallel ResNets with different convolution kernel sizes to extract multi-scale features of the inputs. Moreover, the residuals are connected not only with the current level but also with other levels in a crossover manner. To illustrate the performance of ML-xResNet, we apply the model to process ternary classification (benign, indeterminate, and malignant lung nodules) and binary classification (benign and malignant lung nodules) of lung nodules, respectively. Based on the experiment results, the proposed ML-xResNet achieves the best results of 85.88% accuracy for ternary classification and 92.19% accuracy for binary classification, without any additional handcrafted preprocessing algorithm

CP Asymmetry in Charged Higgs Decays in MSSM

We discuss and compare the charge-parity (CP) asymmetry in the charged Higgs boson decays H -> \bar{u}_i d_j for the second and third generation quarks in the minimal supersymmetric standard model. As part of the analysis, we derive some general analytical formulas for the imaginary parts of two-point and three-point scalar one-loop integrals and use them for calculating vectorial and tensorial type integrals needed for the problem under consideration. We find that, even though each decay mode has a potential to yield a CP asymmetry larger than 10%, further analysis based on the number of required charged Higgs events at colliders favors the \bar{t}b, \bar{c}b, and \bar{c}s channels, whose asymmetry could reach 10-15% in certain parts of the parameter space.Comment: 25 pages, 9 figures. Discussion about charged Higgs observability added, typos corrected, accepted for publication in PR