Asynchronous design of a multi-dimensional logarithmic number system processor for digital hearing instruments.

This thesis presents an asynchronous Multi-Dimensional Logarithmic Number System (MDLNS) processor that exhibits very low power dissipation. The target application is for a hearing instrument DSP. The MDLNS is a newly developed number system that has the advantage of reducing hardware complexity compared to the classical Logarithmic Number System (LNS). A synchronous implementation of a 2-digit 2DLNS filterbank, using the MDLNS to construct a FIR filterbank, has successfully proved that this novel number representation can benefit this digital hearing instrument application in the requirement of small size and low power. In this thesis we demonstrate that the combination of using the MDLNS, along with an asynchronous design methodology, produces impressive power savings compared to the previous synchronous design. A 4-phase bundled-data full-handshaking protocol is applied to the asynchronous control design. We adopt the Differential Cascade Voltage Switch Logic (DCVSL) circuit family for the design of the computation cells in this asynchronous MDLNS processor. Besides the asynchronous design methodology, we also use finite ring calculations to reduce adder bit-width to provide improvements compared to the previous MDLNS filterbank architecture. Spectre power simulation results from simulations of this asynchronous MDLNS processor demonstrate that over 70 percent power savings have been achieved compared to the synchronous design. This full-custom asynchronous MDLNS processor has been submitted for fabrication in the TSMC 0.18mum CMOS technology. A further contribution in this thesis is the development of a novel synchronizing method of design for testability (DfT), which is offered as a possible solution for asynchronous DfT methods.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .W85. Source: Masters Abstracts International, Volume: 43-01, page: 0288. Advisers: G. A. Jullien; W. C. Miller. Thesis (M.A.Sc.)--University of Windsor (Canada), 2004

Impact of climate variability and change on crime rates in Tangshan, China

Studies examining the relation between climate and human conflict often focus on the role of temperature and have diverging views on the significance of other climatic variables. Using a 6-year (from 2009 to 2014) dataset of crime statistics collected in a medium size city of Tangshan in China, we find strong, positive correlations between temperature and both violent and property crimes. In addition, relative humidity is also positively correlated with Rape and Minimal Violent Robbery (MVR). The seasonal cycle is a significant factor that induces good correlations between crime rates and climatic variables, which can be reasonably explained by the Routine Activity theory. We also show that the combined impacts of temperature and relative humidity on crime rates can be reasonably captured by traditional heat stress indices. Using an ensemble of CMIP5 global climate change simulations, we estimate that at the end of the 21st century the rates of Rape (violent crime) and MVR (property crime) in Tangshan will increase by 9.5 ± 5.3% and 2.6 ± 2.1%, respectively, under the highest emission scenario (Representative Concentration Pathway 8.5). The gross domestic product (GDP) is also shown to be significantly correlated with MVR rates and the regression results are strongly impacted by whether GDP is considered or not

mTreeIllustrator: A Mixed-Initiative Framework for Visual Exploratory Analysis of Multidimensional Hierarchical Data

Multidimensional hierarchical (mTree) data are very common in daily life and scientific research. However, mTree data exploration is a laborious and time-consuming process due to its structural complexity and large dimension combination space. To address this problem, we present mTreeIllustrator, a mixed-initiative framework for exploratory analysis of multidimensional hierarchical data with faceted visualizations. First, we propose a recommendation pipeline for the automatic selection and visual representation of important subspaces of mTree data. Furthermore, we design a visual framework and an interaction schema to couple automatic recommendations with human specifications to facilitate progressive exploratory analysis. Comparative experiments and user studies demonstrate the usability and effectiveness of our framework

Adaptive mesh refinement for finite element analysis of the free vibration disturbance of cylindrical shells due to circumferential micro-crack damage

Purpose Moderately thick circular cylindrical shells are widely used as supporting structures or storage cavities in structural engineering, rock engineering, and aerospace engineering. In practical engineering, shells often work with micro-cracks or defects. The existence of micro-crack damage may result in the disturbance of dynamic behaviours and even induce accidental dynamic disasters. The free vibration frequency and mode are important parameters for the dynamic performance and damage identification analysis. In particular, stiffness weakening of the local damage region leads to significant changes in the vibration mode, which makes it difficult for the mesh generated in the conventional finite element method to capture a high-precision solution of the local oscillation. Design/methodology/approach In response to the above problems, this study developed an adaptive finite element method and a crack damage characterisation method for moderately thick circular cylindrical shells. By introducing the inverse power iteration method, error estimation, and mesh subdivision refinement technique for the analysis of finite element eigenvalue problems, an adaptive computation scheme was constructed for the free vibration problem of moderately thick circular cylindrical shells with circumferential crack damage. Findings Based on typical numerical examples, the established adaptive finite element solution for the free vibration of moderately thick circular cylindrical shells demonstrated its suitability for solving the high-precision free vibration frequency and mode of cylindrical shell structures. The any order frequency and mode shape of cracked cylindrical shells under the conditions of different ring wave numbers, crack locations, crack depths, and multiple cracks were successfully solved. The influences of the location, depth, and number of cracks on the disturbance of dynamic behaviours were analysed. Originality/value This study can be used as a reference for the adaptive finite element solution of free vibration of moderately thick circular cylindrical shells with cracks and lays the foundation for further development of a high-performance computation method suitable for the dynamic disturbance and damage identification analysis of general cracked structures

In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine

Backgrounds and AimsRecently, a growing number of hepatotoxicity cases aroused by Traditional Chinese Medicine (TCM) have been reported, causing increasing concern. To date, the reported predictive models for drug induced liver injury show low prediction accuracy and there are still no related reports for hepatotoxicity evaluation of TCM systematically. Additionally, the mechanism of herb induced liver injury (HILI) still remains unknown. The aim of the study was to identify potential hepatotoxic ingredients in TCM and explore the molecular mechanism of TCM against HILI.Materials and MethodsIn this study, we developed consensus models for HILI prediction by integrating the best single classifiers. The consensus model with best performance was applied to identify the potential hepatotoxic ingredients from the Traditional Chinese Medicine Systems Pharmacology database (TCMSP). Systems pharmacology analyses, including multiple network construction and KEGG pathway enrichment, were performed to further explore the hepatotoxicity mechanism of TCM.Results16 single classifiers were built by combining four machine learning methods with four different sets of fingerprints. After systematic evaluation, the best four single classifiers were selected, which achieved a Matthews correlation coefficient (MCC) value of 0.702, 0.691, 0.659, and 0.717, respectively. To improve the predictive capacity of single models, consensus prediction method was used to integrate the best four single classifiers. Results showed that the consensus model C-3 (MCC = 0.78) outperformed the four single classifiers and other consensus models. Subsequently, 5,666 potential hepatotoxic compounds were identified by C-3 model. We integrated the top 10 hepatotoxic herbs and discussed the hepatotoxicity mechanism of TCM via systems pharmacology approach. Finally, Chaihu was selected as the case study for exploring the molecular mechanism of hepatotoxicity.ConclusionOverall, this study provides a high accurate approach to predict HILI and an in silico perspective into understanding the hepatotoxicity mechanism of TCM, which might facilitate the discovery and development of new drugs

Uric acid predicts recovery of left ventricular function and adverse events in heart failure with reduced ejection fraction: Potential mechanistic insight from network analyses

Background and Aims: Heart failure with reduced ejection fraction (HFrEF) still carries a high risk for a sustained decrease in left ventricular ejection fraction (LVEF) even with the optimal medical therapy. Currently, there is no effective tool to stratify these patients according to their recovery potential. We tested the hypothesis that uric acid (UA) could predict recovery of LVEF and prognosis of HFrEF patients and attempted to explore mechanistic relationship between hyperuricemia and HFrEF. Methods: HFrEF patients with hyperuricemia were selected from the National Inpatient Sample (NIS) 2016-2018 database and our Xianyang prospective cohort study. Demographics, cardiac risk factors, and cardiovascular events were identified. Network-based analysis was utilized to examine the relationship between recovery of LVEF and hyperuricemia, and we further elucidated the underlying mechanisms for the impact of hyperuricemia on HFrEF. Results: After adjusting confounding factors by propensity score matching, hyperuricemia was a determinant of HFrEF [OR 1.247 (1.172-1.328); Conclusion: Lower baseline UA value predicted the LVEF recovery and less long-term adverse events in HFrEF patients. Our results provide new insights into underlying mechanistic relationship between hyperuricemia and HFrEF