218 resultados para point pattern


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Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.

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Background In the emergency department, portable point-of-care testing (POCT) coagulation devices may facilitate stroke patient care by providing rapid International Normalized Ratio (INR) measurement. The objective of this study was to evaluate the reliability, validity, and impact on clinical decision-making of a POCT device for INR testing in the setting of acute ischemic stroke (AIS). Methods A total of 150 patients (50 healthy volunteers, 51 anticoagulated patients, 49 AIS patients) were assessed in a tertiary care facility. The INR's were measured using the Roche Coaguchek S and the standard laboratory technique. Results The interclass correlation coefficient and 95% confidence interval between overall POCT device and standard laboratory value INRs was high (0.932 (0.69 - 0.78). In the AIS group alone, the correlation coefficient and 95% CI was also high 0.937 (0.59 - 0.74) and diagnostic accuracy of the POCT device was 94%. Conclusions When used by a trained health professional in the emergency department to assess INR in acute ischemic stroke patients, the CoaguChek S is reliable and provides rapid results. However, as concordance with laboratory INR values decreases with higher INR values, it is recommended that with CoaguChek S INRs in the > 1.5 range, a standard laboratory measurement be used to confirm the results.

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The 12.7-10.5 Ma Cougar Point Tuff in southern Idaho, USA, consists of 10 large-volume (>10²-10³ km³ each), high-temperature (800-1000 °C), rhyolitic ash-flow tuffs erupted from the Bruneau-Jarbidge volcanic center of the Yellowstone hotspot. These tuffs provide evidence for compositional and thermal zonation in pre-eruptive rhyolite magma, and suggest the presence of a long-lived reservoir that was tapped by numerous large explosive eruptions. Pyroxene compositions exhibit discrete compositional modes with respect to Fe and Mg that define a linear spectrum punctuated by conspicuous gaps. Airfall glass compositions also cluster into modes, and the presence of multiple modes indicates tapping of different magma volumes during early phases of eruption. Equilibrium assemblages of pigeonite and augite are used to reconstruct compositional and thermal gradients in the pre-eruptive reservoir. The recurrence of identical compositional modes and of mineral pairs equilibrated at high temperatures in successive eruptive units is consistent with the persistence of their respective liquids in the magma reservoir. Recurrence intervals of identical modes range from 0.3 to 0.9 Myr and suggest possible magma residence times of similar duration. Eruption ages, magma temperatures, Nd isotopes, and pyroxene and glass compositions are consistent with a long-lived, dynamically evolving magma reservoir that was chemically and thermally zoned and composed of multiple discrete magma volumes.

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Population-based brain mapping provides great insight into the trajectory of aging and dementia, as well as brain changes that normally occur over the human life span.We describe three novel brain mapping techniques, cortical thickness mapping, tensor-based morphometry (TBM), and hippocampal surface modeling, which offer enormous power for measuring disease progression in drug trials, and shed light on the neuroscience of brain degeneration in Alzheimer's disease (AD) and mild cognitive impairment (MCI).We report the first time-lapse maps of cortical atrophy spreading dynamically in the living brain, based on averaging data from populations of subjects with Alzheimer's disease and normal subjects imaged longitudinally with MRI. These dynamic sequences show a rapidly advancing wave of cortical atrophy sweeping from limbic and temporal cortices into higher-order association and ultimately primary sensorimotor areas, in a pattern that correlates with cognitive decline. A complementary technique, TBM, reveals the 3D profile of atrophic rates, at each point in the brain. A third technique, hippocampal surface modeling, plots the profile of shape alterations across the hippocampal surface. The three techniques provide moderate to highly automated analyses of images, have been validated on hundreds of scans, and are sensitive to clinically relevant changes in individual patients and groups undergoing different drug treatments. We compare time-lapse maps of AD, MCI, and other dementias, correlate these changes with cognition, and relate them to similar time-lapse maps of childhood development, schizophrenia, and HIV-associated brain degeneration. Strengths and weaknesses of these different imaging measures for basic neuroscience and drug trials are discussed.

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This study investigated a potential source of inaccuracy for diode measurements in modulated beams; the effect of diode housing asymmetry on measurement results. The possible effects of diode housing asymmetry on the measurement of steep dose gradients were evaluated by measuring 5x5 cm2 beam profiles, with three cylindrical diodes and two commonly used ionization chambers, with each dosimeter positioned in a 3D scanning water tank with its stem perpendicular to the beam axis (horizontal) and parallel to the direction of scanning. The resulting profiles were used to compare the penumbrae measured with the diode stem pointing into (equivalent to a “stem-first” setup) and out of the field (equivalent to a “stem-last” setup) in order to evaluate the effects of dosimeter alignment and thereby identify the effects of dosimeter asymmetry. The stem-first and stem-last orientations resulted in differences of up to 0.2 mm in the measured 20-80% penumbra widths and differences of up to 0.4 mm in the off axis position of the 90% isodose. These differences, which are smaller than previously reported for older model dosimeters, were apparent in the profile results for both diodes and small volume ionization chambers. As an extension to this study, the practical use of all five dosimeters was exemplified by measuring point doses in IMRT test beams. These measurements showed good agreement (within 2%) between the diodes and the small volume ionization chamber, with all of these dosimeters being able to identify a region 3% under-dosage which was not identified by a larger volume (6 mm diameter) ionization chamber. The results of this work should help to remove some of the barriers to the use of diodes for modulated radiotherapy dosimetry in the future.

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The Eating Disorder Risk Composite (EDRC) comprises the Drive for Thinness, Bulimia, and Body Dissatisfaction subscales of the Eating Disorder Inventory, Third Edition (EDI-3, Garner, 2004). Past research conducted with Latina college women (LCW) has found older versions of the EDRC subscales to be reliable, but the EDI-3's EDRC factor structure has yet to be studied among LCW. The present study investigated the pattern of responses to and the factor structure of the EDRC in LCW. It was hypothesized that eating pathology would be present and that a factor analysiswould find some discrepancies between the original factor structure of the EDRC and the factor structure from LCW. Analyses of data on a 6-point Likert scale indicate that drive for thinness and body dissatisfaction are far more prevalent than is bulimic symptomology in LCW. Principal Axis Factoring with promax rotation was used to extract three factors very similar to the original EDRC. Some discrepancies in the item loadings were observed, most notably that half of the items from the original Body Dissatisfaction subscale did not load together on one factor. Overall, the EDRC appears to be a goodmeasurement of eating- and body-related phenomena among LCW. Implications, limitations, and future directions are discussed.

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From an economic perspective, the sustainability crisis is ultimately characterized by a worsening relationship between the resources required to support the global population and the ability of the earth to supply them. Despite the ever-increasing threat of a calamity, modern society appears unable to alter its course. The very systems which underpin global human endeavor seem to actively prevent meaningful change and the one irrepressible goal to which all societies seem to strive is the very thing that makes such endeavor ultimately life threatening: that of global growth. Using the Australian experience as an exemplar, this paper explores how the concept of growth infiltrates societal reactions to the crisis at various scales – global, national and regional. Analysis includes historic studies, a critique of current misconceptions around population demographics, comparative evaluation of various interventions in the Australian context and considerations around potential ways to address the crisis.

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BACKGROUND Little is known about the spatiotemporal pattern of bacillary dysentery (BD) in China. This study assessed the geographic distribution and seasonality of BD in China over the past two decades. METHODS Data on monthly BD cases in 31 provinces of China from January 1990 to December 2009 obtained from Chinese Center for Disease Control and Prevention, and data on demographic and geographic factors, as well as climatic factors, were compiled. The spatial distributions of BD in the four periods across different provinces were mapped, and heat maps were created to present the seasonality of BD by geography. A cosinor function combined with Poisson regression was used to quantify the seasonal parameters of BD, and a regression analysis was conducted to identify the potential drivers of morbidity and seasonality of BD. RESULTS Although most regions of China have experienced considerable declines in BD morbidity over the past two decades, Beijing and Ningxia still had high BD morbidity in 2009. BD morbidity decreased more slowly in North-west China than other regions. BD in China mainly peaked from July to September, with heterogeneity in peak time between regions. Relative humidity was associated with BD morbidity and peak time, and latitude was the major predictor of BD amplitude. CONCLUSIONS The transmission of BD was heterogeneous in China. Improved sanitation and hygiene in North-west China, and better access to clean water and food in the big floating population in some metropolises could be the focus of future preventive interventions against BD. BD control efforts should put more emphasis on those dry areas in summer.

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Objective This study explores the spatiotemporal variations of suicide across Australia from 1986 to 2005, discusses the reasons for dynamic changes, and considers future suicide research and prevention strategies. Design Suicide (1986–2005) and population data were obtained from the Australian Bureau of Statistics. A series of analyses were conducted to examine the suicide pattern by sex, method and age group over time and geography. Results Differences in suicide rates across sex, age groups and suicide methods were found across geographical areas. Male suicides were mainly completed by hanging, firearms, gases and self-poisoning. Female suicides were primarily completed by hanging and self-poisoning. Suicide rates were higher in rural areas than in urban areas (capital cities and regional centres). Suicide rates by firearms were higher in rural areas than in urban areas, while the pattern for self-poisoning showed the reverse trend. Suicide rates had relatively stable trend for the total population and those aged between 15 and 54, while suicide decreased among 55 years and over during the study period. There was a decrease in suicides by firearms during the study period especially after 1996 when a new firearm control law was implemented, while suicide by hanging continued to increase. Areas with a high proportion of indigenous population (eg, northwest of Queensland and top north of the Northern Territory) had shown a substantial increase in suicide incidence after 1995. Conclusions Suicide rates varied over time and space and across sexes, age groups and suicide methods. This study provides detailed patterns of suicide to inform suicide control and prevention strategies for specific subgroups and areas of high and increased risk.

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Animal models of critical illness are vital in biomedical research. They provide possibilities for the investigation of pathophysiological processes that may not otherwise be possible in humans. In order to be clinically applicable, the model should simulate the critical care situation realistically, including anaesthesia, monitoring, sampling, utilising appropriate personnel skill mix, and therapeutic interventions. There are limited data documenting the constitution of ideal technologically advanced large animal critical care practices and all the processes of the animal model. In this paper, we describe the procedure of animal preparation, anaesthesia induction and maintenance, physiologic monitoring, data capture, point-of-care technology, and animal aftercare that has been successfully used to study several novel ovine models of critical illness. The relevant investigations are on respiratory failure due to smoke inhalation, transfusion related acute lung injury, endotoxin-induced proteogenomic alterations, haemorrhagic shock, septic shock, brain death, cerebral microcirculation, and artificial heart studies. We have demonstrated the functionality of monitoring practices during anaesthesia required to provide a platform for undertaking systematic investigations in complex ovine models of critical illness.

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Reconstructing 3D motion data is highly under-constrained due to several common sources of data loss during measurement, such as projection, occlusion, or miscorrespondence. We present a statistical model of 3D motion data, based on the Kronecker structure of the spatiotemporal covariance of natural motion, as a prior on 3D motion. This prior is expressed as a matrix normal distribution, composed of separable and compact row and column covariances. We relate the marginals of the distribution to the shape, trajectory, and shape-trajectory models of prior art. When the marginal shape distribution is not available from training data, we show how placing a hierarchical prior over shapes results in a convex MAP solution in terms of the trace-norm. The matrix normal distribution, fit to a single sequence, outperforms state-of-the-art methods at reconstructing 3D motion data in the presence of significant data loss, while providing covariance estimates of the imputed points.

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Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

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This paper reviews the innovations that have been introduced in the milling train at Rocky Point mill since 2001 and provides some operational, performance and maintenance comparisons of the technologies in use. The decision to install BHEM mills in the #2 and #3 mill positions to complement the six-roll mills in the #1 and #4 mill positions has proven a good one. Satisfactory performance is being obtained by these mills while maintenance costs are significantly less. Very good #1 mill extraction and final bagasse moisture content are being achieved. The innovation of using Hägglunds hydraulic drives at higher speed…

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The aim of this study is to investigate the blood flow pattern in carotid bifurcation with a high degree of luminal stenosis, combining in vivo magnetic resonance imaging (MRI) and computational fluid dynamics (CFD). A newly developed two-equation transitional model was employed to evaluate wall shear stress (WSS) distribution and pressure drop across the stenosis, which are closely related to plaque vulnerability. A patient with an 80% left carotid stenosis was imaged using high resolution MRI, from which a patient-specific geometry was reconstructed and flow boundary conditions were acquired for CFD simulation. A transitional model was implemented to investigate the flow velocity and WSS distribution in the patient-specific model. The peak time-averaged WSS value of approximately 73Pa was predicted by the transitional flow model, and the regions of high WSS occurred at the throat of the stenosis. High oscillatory shear index values up to 0.50 were present in a helical flow pattern from the outer wall of the internal carotid artery immediately after the throat. This study shows the potential suitability of a transitional turbulent flow model in capturing the flow phenomena in severely stenosed carotid arteries using patient-specific MRI data and provides the basis for further investigation of the links between haemodynamic variables and plaque vulnerability. It may be useful in the future for risk assessment of patients with carotid disease.