892 resultados para Time-motion Analysis


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Objective: To examine the impact of a sudden and dramatic decrease in heroin availability, concomitant with increases in price and decreases in purity, on fatal and non-fatal drug overdoses in New South Wales, Australia. Design and setting: Time-series analysis was conducted where possible on data on overdoses collected from NSW hospital emergency departments, the NSW Ambulance Service, and all suspected drug-related deaths referred to the NSW Coroner's court. Main outcome measures: The number of suspected drug-related deaths where heroin and other drugs were mentioned; ambulance calls to suspected opioid overdoses; and emergency department admissions for overdoses on heroin and other drugs. Results: Both fatal and non-fatal heroin overdoses decreased significantly after heroin supply reduced; the reductions were greater among younger age groups than older age groups. There were no clear increases in non-fatal overdoses with cocaine, methamphetamines or benzodiazepines recorded at hospital emergency departments after the reduction in heroin supply. Data on drug-related deaths suggested that heroin use was the predominant driver of drug-related deaths in NSW, and that when heroin supply was reduced overdose deaths were more likely to involve a wider combination of drugs. Conclusion: A reduction in heroin supply reduced heroin-related deaths, and did not result in a concomitant increase, to the same degree, in deaths relating to other drugs. Younger people were more affected by the reduction in supply.

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All signals that appear to be periodic have some sort of variability from period to period regardless of how stable they appear to be in a data plot. A true sinusoidal time series is a deterministic function of time that never changes and thus has zero bandwidth around the sinusoid's frequency. A zero bandwidth is impossible in nature since all signals have some intrinsic variability over time. Deterministic sinusoids are used to model cycles as a mathematical convenience. Hinich [IEEE J. Oceanic Eng. 25 (2) (2000) 256-261] introduced a parametric statistical model, called the randomly modulated periodicity (RMP) that allows one to capture the intrinsic variability of a cycle. As with a deterministic periodic signal the RMP can have a number of harmonics. The likelihood ratio test for this model when the amplitudes and phases are known is given in [M.J. Hinich, Signal Processing 83 (2003) 1349-13521. A method for detecting a RMP whose amplitudes and phases are unknown random process plus a stationary noise process is addressed in this paper. The only assumption on the additive noise is that it has finite dependence and finite moments. Using simulations based on a simple RMP model we show a case where the new method can detect the signal when the signal is not detectable in a standard waterfall spectrograrn display. (c) 2005 Elsevier B.V. All rights reserved.

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Play is the primary occupation of childhood and provides a potentially powerful means of assessing and treating children with autistic disorder. This study utilized a cross-sectional comparison design to investigate the nature of play engagement in children with AD (n = 24), relative to typically developing children (n = 34) matched for chronological age. Play behaviours were recorded in a clinical play environment. Videotapes comprising 15 minutes of the children's spontaneous play behaviour were analysed using time-interval analysis. The particular play behaviours observed and play objects used were coded. Differences in play behaviours (p < 0.0001) and play object preferences (p < 0.0001) were identified between the groups. Findings regarding play behaviour contribute to contention in the literature surrounding functional and symbolic play. Explanations for play object preferences are postulated. Recommendations are made regarding clinical application of findings in terms of enhancing assessment and intervention by augmenting motivation.

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The rate of electronic energy transfer (EET) between a naphthalene donor and an anthracene acceptor in [ZnL3]-(ClO4)(2) and [ZnL4](ClO4)(2) was determined by time-resolved fluorescence measurements, where L 3 and L 4 are the geometrical isomers of 6-[(anthracen-9-ylmethyl)amino]-trans-6,13-dimethyl-1,4,8,11-tetraazacyclotetradecane-13-amine (L-2), substituted with either a naphthalen-1-ylmethyl or naphthalen-2-ylmethyl donor, respectively. The energy transfer rate constant, k(EET), was determined to be (0.92 +/- 0.02) x 10(9) s(-1) for the naphthalen-1-ylmethyl-substituted isomer, while that for the naphthalen-2-ylmethyl-substituted isomer is somewhat faster, with k(EET) = (1.31 +/- 0.01) x 10(9) s(-1). The solid-state structure of [(ZnLCl)-Cl-3]ClO4 has been determined, and using molecular modeling calculations, the likely distributions of solution conformations in CH3CN have been evaluated for both complexes. The calculated conformational distributions in the common trans-III N-based isomeric form gave Forster EET rate constants that account for the differences observed and are in excellent agreement with the experimental values. It is shown that the full range of conformers must be considered to accurately reproduce the observed EET kinetics.

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The authors examine the evidence on the relationship between inflation and productivity growth for nine Asian economies using causality analysis in a multivariate model with money supply as a possible effective monetary policy tool. The inflation-productivity growth relationship is found to be non-uniform, as the evidence of uni-directional, bi-directional, and no causality between the two variables is varied and significant for some countries and insignificant for others. An attempt is made to explain the inflation-productivity nexus for these countries and to discuss implications for anti-inflationary policies such as inflation targeting.

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The aim of this investigation was to test the hypothesis that testicular germ cell tumors (TGCTs) are hormone-dependent cancers. Human TGCT cells were implanted in the left testis of male severe combined immunodeficient mice receiving either no treatment or hormone manipulation treatment [blockade of gonadotropin-releasing hormone secretion and/or signaling using leuprolide or leuprolide plus exogenous testosterone]. Real-time RT-PCR analysis was used to determine the expression profiles of hormone pathway-associated genes. Tumor burden was significantly smaller in mice receiving both leuprolide and testosterone. Real-time RTPCR analysis of follicle-stimulating hormone (FSH) receptor, luteinizing hormone (LH) receptor and P450 aromatase revealed changes in expression in normal testis tissue related to presence of xenograft tumors and manipulation of hormone levels but a complete absence of expression of these genes in tumor cells themselves. This was confirmed in human specimens of TGCT. Reduced TGCT growth in vivo was associated with significant downregulation of LH receptor and P450 aromatase expression in normal testes. In conclusion, manipulation of hormone levels influenced the growth of TGCT in vivo, while the presence of xenografted tumors influenced the expression of hormone-related genes in otherwise untreated animals. Human TGCTs, both in the animal model and in clinical specimens, appear not to express receptors for FSH or LH. Similarly, expression of the P450 aromatase gene is absent in TGCTs. Impaired estrogen synthesis and/or signaling may be at least partly responsible for inhibition of TGCT growth in the animal model. (c) 2005 Wiley-Liss, Inc.

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Eddy currents induced within a magnetic resonance imaging (MRI) cryostat bore during pulsing of gradient coils can be applied constructively together with the gradient currents that generate them, to obtain good quality gradient uniformities within a specified imaging volume over time. This can be achieved by simultaneously optimizing the spatial distribution and temporal pre-emphasis of the gradient coil current, to account for the spatial and temporal variation of the secondary magnetic fields due to the induced eddy currents. This method allows the tailored design of gradient coil/magnet configurations and consequent engineering trade-offs. To compute the transient eddy currents within a realistic cryostat vessel, a low-frequency finite-difference time-domain (FDTD) method using total-field scattered-field (TFSF) scheme has been performed and validated

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In the last two decades there have been substantial developments in the mathematical theory of inverse optimization problems, and their applications have expanded greatly. In parallel, time series analysis and forecasting have become increasingly important in various fields of research such as data mining, economics, business, engineering, medicine, politics, and many others. Despite the large uses of linear programming in forecasting models there is no a single application of inverse optimization reported in the forecasting literature when the time series data is available. Thus the goal of this paper is to introduce inverse optimization into forecasting field, and to provide a streamlined approach to time series analysis and forecasting using inverse linear programming. An application has been used to demonstrate the use of inverse forecasting developed in this study. © 2007 Elsevier Ltd. All rights reserved.

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Companies under pressure from stakeholders to meet profit expectations are often tempted to cut advertising expenses, particularly in times of economic difficulties. However, firms may not fully grasp the actual impact of such drastic cuts. Indeed, the general assumption is that advertising effects are symmetric: the numerical sales impact of budget increase or decrease would be the same in absolute value. Our paper addresses this gap by developing a new model based on multivariate time-series analysis (VAR models) to capture these asymmetric dynamic relationships. Our results show that advertising models are improved by allowing the capture of these asymmetric patterns.

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We report statistical time-series analysis tools providing improvements in the rapid, precision extraction of discrete state dynamics from time traces of experimental observations of molecular machines. By building physical knowledge and statistical innovations into analysis tools, we provide techniques for estimating discrete state transitions buried in highly correlated molecular noise. We demonstrate the effectiveness of our approach on simulated and real examples of steplike rotation of the bacterial flagellar motor and the F1-ATPase enzyme. We show that our method can clearly identify molecular steps, periodicities and cascaded processes that are too weak for existing algorithms to detect, and can do so much faster than existing algorithms. Our techniques represent a step in the direction toward automated analysis of high-sample-rate, molecular-machine dynamics. Modular, open-source software that implements these techniques is provided.