9,672 research outputs found

    Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)

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    The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle-motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle-motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads

    Practical divergent synthesis of all possible regioisomers of myo-inositol trisphosphates

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    Correction: Splice site identification using probabilistic parameters and SVM classification

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    BACKGROUND: Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and efficient analysis methods. Identifying genes in this newly accumulated data is an important issue in bioinformatics, and it requires the prediction of the complete gene structure. Accurate identification of splice sites in DNA sequences plays one of the central roles of gene structural prediction in eukaryotes. Effective detection of splice sites requires the knowledge of characteristics, dependencies, and relationship of nucleotides in the splice site surrounding region. A higher-order Markov model is generally regarded as a useful technique for modeling higher-order dependencies. However, their implementation requires estimating a large number of parameters, which is computationally expensive. RESULTS: The proposed method for splice site detection consists of two stages: a first order Markov model (MM1) is used in the first stage and a support vector machine (SVM) with polynomial kernel is used in the second stage. The MM1 serves as a pre-processing step for the SVM and takes DNA sequences as its input. It models the compositional features and dependencies of nucleotides in terms of probabilistic parameters around splice site regions. The probabilistic parameters are then fed into the SVM, which combines them nonlinearly to predict splice sites. When the proposed MM1-SVM model is compared with other existing standard splice site detection methods, it shows a superior performance in all the cases. CONCLUSION: We proposed an effective pre-processing scheme for the SVM and applied it for the identification of splice sites. This is a simple yet effective splice site detection method, which shows a better classification accuracy and computational speed than some other more complex methods

    Electrocardiographic patch devices and contemporary wireless cardiac monitoring.

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    Cardiac electrophysiologic derangements often coexist with disorders of the circulatory system. Capturing and diagnosing arrhythmias and conduction system disease may lead to a change in diagnosis, clinical management and patient outcomes. Standard 12-lead electrocardiogram (ECG), Holter monitors and event recorders have served as useful diagnostic tools over the last few decades. However, their shortcomings are only recently being addressed by emerging technologies. With advances in device miniaturization and wireless technologies, and changing consumer expectations, wearable “on-body” ECG patch devices have evolved to meet contemporary needs. These devices are unobtrusive and easy to use, leading to increased device wear time and diagnostic yield. While becoming the standard for detecting arrhythmias and conduction system disorders in the outpatient setting where continuous ECG monitoring in the short to medium term (days to weeks) is indicated, these cardiac devices and related digital mobile health technologies are reshaping the clinician-patient interface with important implications for future healthcare delivery

    Order statistic correlation coefficient and its application to association measurement of biosignals

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    In this paper we propose a novel and fast nonlinear association measure based on order statistics and rearrangement inequality. We employ one episode of heart signal, one episode of EEG signal and 1000 white Gaussian noises in our study. Extensive statistical analysis are performed based on one linear model and one nonlinear model. Comparative studies with three other prominent methods are presented. Theoretical derivations and experimental results suggest that our new method has small biasedness, high sensitivity to changes in association, fast computational speed, and robustness under monotone nonlinear transformations. © 2006 IEEE.published_or_final_versio

    Accretion Disks Around Black Holes: Twenty Five Years Later

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    We study the progress of the theory of accretion disks around black holes in last twenty five years and explain why advective disks are the best bet in explaining varied stationary and non-stationary observations from black hole candidates. We show also that the recently proposed advection dominated flows are incorrect.Comment: 30 Latex pages including figures. Kluwer Style files included. Appearing in `Observational Evidence for Black Holes in the Universe', ed. Sandip K. Chakrabarti, Kluwer Academic Publishers (DORDRECHT: Holland

    Order statistics correlation coefficient as a novel association measurement with applications to biosignal analysis

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    In this paper, we propose a novel correlation coefficient based on order statistics and rearrangement inequality. The proposed coefficient represents a compromise between the Pearson's linear coefficient and the two rank-based coefficients, namely Spearman's rho and Kendall's tau. Theoretical derivations show that our coefficient possesses the same basic properties as the three classical coefficients. Experimental studies based on four models and six biosignals show that our coefficient performs better than the two rank-based coefficients when measuring linear associations; whereas it is well able to detect monotone nonlinear associations like the two rank-based coefficients. Extensive statistical analyses also suggest that our new coefficient has superior anti-noise robustness, small biasedness, high sensitivity to changes in association, accurate time-delay detection ability, fast computational speed, and robustness under monotone nonlinear transformations. © 2007 IEEE.published_or_final_versio

    Transient Response of a Laminated Composite Plate

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    Propagation of guided waves in a laminated plate is of interest for ultrasonic nondestructive evaluation of defects and for material characterization. There is a need for a thorough understanding of the wave propagation characteristics in such a plate in order to use ultrasonic means to determine the material properties, assess damage, and characterize defects. The problem is also of interest for study of acoustic emission

    Inactivation of hypoxia inducible factor (HIF) 1 alpha induces obesity-associated metabolic disorders through brown adipose tissue dysfunction

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    published_or_final_versionThe 14th Medical Research Conference, Hong Kong, 10 January 2009. In Hong Kong Medical Journal, 2009, v. 15, suppl. 1, p. 40, article no. 6
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