Indication for Large Rescatterings in Charmless Rare B Decays

The current wealth of charmless B decay data may suggest the presence of final state rescattering. In a factorized amplitude approach, better fits are found by incorporating two SU(3) rescattering phase differences, giving delta ~ 65 degree and sigma ~ 90 - 100 degree. Fitting with unitarity phase phi_3 as a fit parameter gives phi_3 ~ 96 degree, the CP asymmetries A_{pi pi}, S_{pi pi} agree better with BaBar, and the sigma phase is slightly lower. Keeping phi_3 = 60 degree fixed in fit gives S_{pi pi} ~-0.9, which agrees better with Belle. With the sizable delta, sigma rescattering phases as fitted, many direct CP asymmetries flip sign, and B0 --> pi0 pi0, K- K+ rates are of order 10^{-6}, which can be tested soon.Comment: 6 pages, 4 figures, updated, references adde

Average-case optimized technology mapping of one-hot domino circuits*

Journal ArticleThis paper presents a technology mapping technique for optimizing the average-case delay of asynchronous combinational circuits implemented using domino logic and one-hot encoded outputs. The technique minimizes the critical path for common input patterns at the possible expense of making less common critical paths longer. To demonstrate the application of this technique, we present a case study of a combinational length decoding block, an integral component of an Asynchronous Instruction Length Decoder (AILD) which can be used in PentiumR processors. The experimental results demonstrate that the average-case delay of our mapped circuits can be dramatically lower than the worst-case delay of the circuits obtained using conventional worst-case mapping techniques

Understanding Software-as-a-Service Performance - A Dynamic Capability Perspective

How to increase a client’s capability through outsourcing remains a problem. This papers draws on strategic management literature and the relational view to develop a theoretical model that explains the relationships between collaboration, agility, and outsourcing performance in software-as-a-service (SaaS) context. Collaboration are characterized as knowledge sharing and process alignment between a supplier and its client, agility as a supplier’s sensing agility and responding agility. This study also investigates the moderating effect of environmental turbulence on the relationships between agility and performance. The proposed hypotheses are largely supported by the empirical data from 215 firms. The results show that SaaS performance is affected by both sensing agility and responding ability, which, in turn, are impacted by collaboration between a supplier and its client. Finally, we discuss the implications of our results

Visual gene-network analysis reveals the cancer gene co-expression in human endometrial cancer

Abstract Background Endometrial cancers (ECs) are the most common form of gynecologic malignancy. Recent studies have reported that ECs reveal distinct markers for molecular pathogenesis, which in turn is linked to the various histological types of ECs. To understand further the molecular events contributing to ECs and endometrial tumorigenesis in general, a more precise identification of cancer-associated molecules and signaling networks would be useful for the detection and monitoring of malignancy, improving clinical cancer therapy, and personalization of treatments. Results ECs-specific gene co-expression networks were constructed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Important pathways and putative cancer hub genes contribution to tumorigenesis of ECs were identified. An elastic-net regularized classification model was built using the cancer hub gene signatures to predict the phenotypic characteristics of ECs. The 19 cancer hub gene signatures had high predictive power to distinguish among three key principal features of ECs: grade, type, and stage. Intriguingly, these hub gene networks seem to contribute to ECs progression and malignancy via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle. Conclusions The results of this study provide a powerful biomarker discovery platform to better understand the progression of ECs and to uncover potential therapeutic targets in the treatment of ECs. This information might lead to improved monitoring of ECs and resulting improvement of treatment of ECs, the 4th most common of cancer in women.Peer Reviewe

From Real to Complex: Enhancing Radio-based Activity Recognition Using Complex-Valued CSI

Activity recognition is an important component of many pervasive computing applications. Radio-based activity recognition has the advantage that it does not have the privacy concern and the subjects do not have to carry a device on them. Recently, it has been shown channel state information (CSI) can be used for activity recognition in a device-free setting. With the proliferation of wireless devices, it is important to understand how radio frequency interference (RFI) can impact on pervasive computing applications. In this paper, we investigate the impact of RFI on device-free CSI-based location-oriented activity recognition. We present data to show that RFI can have a significant impact on the CSI vectors. In the absence of RFI, different activities give rise to different CSI vectors that can be differentiated visually. However, in the presence of RFI, the CSI vectors become much noisier and activity recognition also becomes harder. Our extensive experiments show that the performance of state-of-the-art classification methods may degrade significantly with RFI. We then propose a number of counter measures to mitigate the impact of RFI and improve the location-oriented activity recognition performance. We are also the first to use complex-valued CSI to improve the performance in the environment with RFI

Understanding Outsourcing Commitment—An Integrated Model Combining The Resoruce-Based View And Knowledge Management

The understanding on how a service provider’s (SP) process capabilities, in terms of aligning and adapting resources to deliver value to its service recipient (SR) in business process outsourcing (BPO), affect its commitment is limited. To address this, building on a strategic perspective and related theories such as the resource-based view and knowledge management, we develop a theoretical model and test it empirically. Specifically, we posit that a SP’s process capabilities, in terms of process alignment, offering flexibility, and partnering flexibility, positively affect its SR’s commitment and the above relationships is negatively moderated by the SR’s behavior control. Besides, we also examine the influence of interaction effect between antecedents of process capabilities on commitment, such as how does process alignment interact with its partnering flexibility and offering flexibility to affect commitment. Finally, we assess whether process capabilities are influenced by the SR’s absorptive capacity and the SP’s task-knowledge coordination. We test our model using survey data collected from 183 firms, supporting most proposed hypotheses. We discuss the theoretical and practical implications of how to increase the value offered to a SR by levering resources, in terms of process capabilities and knowledge management

EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks

For training fully-connected neural networks (FCNNs), we propose a practical approximate second-order method including: 1) an approximation of the Hessian matrix and 2) a conjugate gradient (CG) based method. Our proposed approximate Hessian matrix is memory-efficient and can be applied to any FCNNs where the activation and criterion functions are twice differentiable. We devise a CG-based method incorporating one-rank approximation to derive Newton directions for training FCNNs, which significantly reduces both space and time complexity. This CG-based method can be employed to solve any linear equation where the coefficient matrix is Kronecker-factored, symmetric and positive definite. Empirical studies show the efficacy and efficiency of our proposed method.Comment: Change to AAAI-19 Versio

Liquid biopsy genotyping in lung cancer: ready for clinical utility?

Liquid biopsy is a blood test that detects evidence of cancer cells or tumor DNA in the circulation. Despite complicated collection methods and the requirement for technique-dependent platforms, it has generated substantial interest due, in part, to its potential to detect driver oncogenes such as epidermal growth factor receptor (EGFR) mutants in lung cancer. This technology is advancing rapidly and is being incorporated into numerous EGFR tyrosine kinase inhibitor (EGFR-TKI) development programs. It appears ready for integration into clinical care. Recent studies have demonstrated that biological fluids such as saliva and urine can also be used for detecting EGFR mutant DNA through application other user-friendly techniques. This review focuses on the clinical application of liquid biopsies to lung cancer genotyping, including EGFR and other targets of genotype-directed therapy and compares multiple platforms used for liquid biopsy