930 resultados para Spatial analysis of data
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Funding Sources The NNUH Stroke and TIA Register is maintained by the NNUH NHS Foundation Trust Stroke Services and data management for this study is supported by the NNUH Research and Development Department through Research Capability Funds.
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Background: Statin therapy reduces the risk of occlusive vascular events, but uncertainty remains about potential effects on cancer. We sought to provide a detailed assessment of any effects on cancer of lowering LDL cholesterol (LDL-C) with a statin using individual patient records from 175,000 patients in 27 large-scale statin trials. Methods and Findings: Individual records of 134,537 participants in 22 randomised trials of statin versus control (median duration 4.8 years) and 39,612 participants in 5 trials of more intensive versus less intensive statin therapy (median duration 5.1 years) were obtained. Reducing LDL-C with a statin for about 5 years had no effect on newly diagnosed cancer or on death from such cancers in either the trials of statin versus control (cancer incidence: 3755 [1.4% per year [py]] versus 3738 [1.4% py], RR 1.00 [95% CI 0.96-1.05]; cancer mortality: 1365 [0.5% py] versus 1358 [0.5% py], RR 1.00 [95% CI 0.93-1.08]) or in the trials of more versus less statin (cancer incidence: 1466 [1.6% py] vs 1472 [1.6% py], RR 1.00 [95% CI 0.93-1.07]; cancer mortality: 447 [0.5% py] versus 481 [0.5% py], RR 0.93 [95% CI 0.82-1.06]). Moreover, there was no evidence of any effect of reducing LDL-C with statin therapy on cancer incidence or mortality at any of 23 individual categories of sites, with increasing years of treatment, for any individual statin, or in any given subgroup. In particular, among individuals with low baseline LDL-C (<2 mmol/L), there was no evidence that further LDL-C reduction (from about 1.7 to 1.3 mmol/L) increased cancer risk (381 [1.6% py] versus 408 [1.7% py]; RR 0.92 [99% CI 0.76-1.10]). Conclusions: In 27 randomised trials, a median of five years of statin therapy had no effect on the incidence of, or mortality from, any type of cancer (or the aggregate of all cancer).
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Systematic, high-quality observations of the atmosphere, oceans and terrestrial environments are required to improve understanding of climate characteristics and the consequences of climate change. The overall aim of this report is to carry out a comparative assessment of approaches taken to addressing the state of European observations systems and related data analysis by some leading actors in the field. This research reports on approaches to climate observations and analyses in Ireland, Switzerland, Germany, The Netherlands and Austria and explores options for a more coordinated approach to national responses to climate observations in Europe. The key aspects addressed are: an assessment of approaches to develop GCOS and provision of analysis of GCOS data; an evaluation of how these countries are reporting development of GCOS; highlighting best practice in advancing GCOS implementation including analysis of Essential Climate Variables (ECVs); a comparative summary of the differences and synergies in terms of the reporting of climate observations; an overview of relevant European initiatives and recommendations on how identified gaps might be addressed in the short to medium term.
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UNLABELLED: Black patients chronically infected with genotype 1 hepatitis C virus (HCV) have historically had lower rates of response to interferon-based treatment than patients of other races. In the phase 3 ION program, the single-tablet regimen of the NS5A inhibitor ledipasvir and NS5B nucleotide polymerase inhibitor sofosbuvir was shown to be safe and highly effective in the general population. The aim of this study was to evaluate the safety and efficacy of ledipasvir/sofosbuvir in black patients using data from the three open-label ION clinical trials, which evaluated the safety and efficacy of 8, 12, and 24 weeks of ledipasvir/sofosbuvir with or without ribavirin for the treatment of treatment-naïve and treatment-experienced patients with genotype 1 HCV, including those with compensated cirrhosis. The primary endpoint was sustained virologic response at 12 weeks after the end of therapy (SVR12). For our analysis, rates of SVR12, treatment-emergent adverse events, and graded laboratory abnormalities were analyzed in black versus non-black patients. Of the 1949 patients evaluated, 308 (16%) were black. On average, black patients were older, had higher body mass index, were more likely to be IL28B non-CC, and had a lower serum alanine aminotransferase at baseline than non-black patients. Overall, 95% of black and 97% of non-black patients achieved SVR12. The rate of relapse was 3% in black patients as compared with 2% in non-black patients. The most common adverse events included fatigue, headache, nausea, and insomnia. The majority of adverse events occurred more frequently in the ribavirin-containing arms of the studies. No differences were observed in overall safety by race. CONCLUSION: A once-daily dosage of ledipasvir/sofosbuvir was similarly effective in black and non-black patients with genotype 1 HCV infection. The addition of ribavirin did not appear to increase SVR12 but was associated with higher rates of adverse events.
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In order to examine the spatial distribution of organic-walled dinoflagellate cysts (dinocysts) in recent sediments related to environmental conditions in the water column, thirty-two surface sediment samples from the NW African upwelling region (20-32°N) were investigated. Relative abundances of the dinocyst species show distinct regional differences allowing the separation of four hydrographic regimes. (1) In the area off Cape Ghir, which is characterized by most seasonal upwelling and river discharge, Lingulodinium machaerophorum strongly dominates the associations which are additionally characterized by cysts of Gymnodinium nolleri, cysts of Polykrikos kofoidii and cysts of Polykrikos schwartzii. (2) Off Cape Yubi, a region with increasing perennial upwelling, L. machaerophorum, Brigantedinium spp., species of the genus Impagidinium and cysts of Protoperidinium stellatum occur in highest relative abundances. (3) In coastal samples between Cape Ghir and Cape Yubi, Gymnodinium catenatum, species of the genus Impagidinium, Nematosphaeropsis labyrinthus, Operculodinium centrocarpum, cysts of P. stellatum and Selenopemphix nephroides determine the species composition. (4) Off Cape Blanc, where upwelling prevails perennially, and at offshore sites, heterotrophic dinocyst species show highest relative abundances. A Redundancy Analysis reveals fluvial mud, sea surface temperature and the depth of the mixed layer in boreal spring (spring) as the most important parameters relating to the dinocyst species association. Dinocyst accumulation rates were calculated for a subset of samples using well-constrained sedimentation rates. Highest accumulation rates with up to almost 80.000 cysts cm**-2 ky**-1 were found off Cape Ghir and Cape Yubi reflecting their eutrophic upwelling filaments. A Redundancy Analysis gives evidence that primary productivity and the input of fluvial mud are mostly related to the dinocyst association. By means of accumulation rate data, quantitative cyst production of individual species can be considered independently from the rest of the association, allowing autecological interpretations. We show that a combined interpretation of relative abundances and accumulation rates of dinocysts can lead to a better understanding of the productivity conditions off NW Africa.
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The terrigenous fraction of seabed sediments recovered along the north-west African continental margin illustrates spatial variability in grain size attributed to different transport mechanisms. Three subpopulations are determined from the grain-size analyses (n = 78) of the carbonate-free silt fraction applying an end-member modelling algorithm (G. J. Weltje, 1997). The two coarsest end-members are interpreted as representing aeolian dust, and the fine-grained end-member is related to fluvial supply. The end-member model thus allows aeolian fallout to be distinguished from fluvial-sourced mud in this area. The relative contributions of the end-members show distinct regional variations that can be related to different transport processes and pathways. Understanding present-day sediment dispersal and mixing is important for a better understanding of older sedimentary records and palaeoclimate reconstructions in the region.
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The first objective of this research was to develop closed-form and numerical probabilistic methods of analysis that can be applied to otherwise conventional methods of unreinforced and geosynthetic reinforced slopes and walls. These probabilistic methods explicitly include random variability of soil and reinforcement, spatial variability of the soil, and cross-correlation between soil input parameters on probability of failure. The quantitative impact of simultaneously considering the influence of random and/or spatial variability in soil properties in combination with cross-correlation in soil properties is investigated for the first time in the research literature. Depending on the magnitude of these statistical descriptors, margins of safety based on conventional notions of safety may be very different from margins of safety expressed in terms of probability of failure (or reliability index). The thesis work also shows that intuitive notions of margin of safety using conventional factor of safety and probability of failure can be brought into alignment when cross-correlation between soil properties is considered in a rigorous manner. The second objective of this thesis work was to develop a general closed-form solution to compute the true probability of failure (or reliability index) of a simple linear limit state function with one load term and one resistance term expressed first in general probabilistic terms and then migrated to a LRFD format for the purpose of LRFD calibration. The formulation considers contributions to probability of failure due to model type, uncertainty in bias values, bias dependencies, uncertainty in estimates of nominal values for correlated and uncorrelated load and resistance terms, and average margin of safety expressed as the operational factor of safety (OFS). Bias is defined as the ratio of measured to predicted value. Parametric analyses were carried out to show that ignoring possible correlations between random variables can lead to conservative (safe) values of resistance factor in some cases and in other cases to non-conservative (unsafe) values. Example LRFD calibrations were carried out using different load and resistance models for the pullout internal stability limit state of steel strip and geosynthetic reinforced soil walls together with matching bias data reported in the literature.
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Skates (Rajidae) have been commercially exploited in Europe for hundreds of years with some species’ abundances declining dramatically during the twentieth century. In 2009 it became “prohibited for EU vessels to target, retain, tranship or land” certain species in some ICES areas, including the critically endangered common skate and the endangered white skate. To examine compliance with skate bans the official UK landings data for 2011–2014 were analysed. Surprisingly, it was found that after the ban prohibited species were still reported landed in UK ports, including 9.6 t of common skate during 2011–2014. The majority of reported landings of common and white skate were from northern UK waters and landed into northern UK ports. Although past landings could not be validated as being actual prohibited species, the landings’ patterns found reflect known abundance distributions that suggest actual landings were made, rather than sporadic occurrence across ports that would be evident if landings were solely due to systematic misidentification or data entry errors. Nevertheless, misreporting and data entry errors could not be discounted as factors contributing to the recorded landings of prohibited species. These findings raise questions about the efficacy of current systems to police skate landings to ensure prohibited species remain protected. By identifying UK ports with the highest apparent landings of prohibited species and those still landing species grouped as'skates and rays’, these results may aid authorities in allocating limited resources more effectively to reduce landings, misreporting and data errors of prohibited species, and increase species-specific landing compliance.
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Skates (Rajidae) have been commercially exploited in Europe for hundreds of years with some species’ abundances declining dramatically during the twentieth century. In 2009 it became “prohibited for EU vessels to target, retain, tranship or land” certain species in some ICES areas, including the critically endangered common skate and the endangered white skate. To examine compliance with skate bans the official UK landings data for 2011–2014 were analysed. Surprisingly, it was found that after the ban prohibited species were still reported landed in UK ports, including 9.6 t of common skate during 2011–2014. The majority of reported landings of common and white skate were from northern UK waters and landed into northern UK ports. Although past landings could not be validated as being actual prohibited species, the landings’ patterns found reflect known abundance distributions that suggest actual landings were made, rather than sporadic occurrence across ports that would be evident if landings were solely due to systematic misidentification or data entry errors. Nevertheless, misreporting and data entry errors could not be discounted as factors contributing to the recorded landings of prohibited species. These findings raise questions about the efficacy of current systems to police skate landings to ensure prohibited species remain protected. By identifying UK ports with the highest apparent landings of prohibited species and those still landing species grouped as'skates and rays’, these results may aid authorities in allocating limited resources more effectively to reduce landings, misreporting and data errors of prohibited species, and increase species-specific landing compliance.
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This paper synthesizes and discusses the spatial and temporal patterns of archaeological sites in Ireland, spanning the Neolithic period and the Bronze Age transition (4300–1900 cal BC), in order to explore the timing and implications of the main changes that occurred in the archaeological record of that period. Large amounts of new data are sourced from unpublished developer-led excavations and combined with national archives, published excavations and online databases. Bayesian radiocarbon models and context- and sample-sensitive summed radiocarbon probabilities are used to examine the dataset. The study captures the scale and timing of the initial expansion of Early Neolithic settlement and the ensuing attenuation of all such activity—an apparent boom-and-bust cycle. The Late Neolithic and Chalcolithic periods are characterised by a resurgence and diversification of activity. Contextualisation and spatial analysis of radiocarbon data reveals finer-scale patterning than is usually possible with summed-probability approaches: the boom-and-bust models of prehistoric populations may, in fact, be a misinterpretation of more subtle demographic changes occurring at the same time as cultural change and attendant differences in the archaeological record.
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This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.
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Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.
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Data from the World Federation of Exchanges show that Brazil’s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariate forecasting models based on intraday data from the futures and spot markets of the BOVESPA index. The interest is to verify if there exist arbitrage opportunities in Brazilian financial market. To this end, three econometric forecasting models were built: ARFIMA, vector autoregressive (VAR), and vector error correction (VEC). Furthermore, it presents the results of a Granger causality test for the aforementioned series. This type of study shows that it is important to identify arbitrage opportunities in financial markets and, in particular, in the application of these models on data of this nature. In terms of the forecasts made with these models, VEC showed better results. The causality test shows that futures BOVESPA index Granger causes spot BOVESPA index. This result may indicate arbitrage opportunities in Brazil.
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Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik, Dissertation, 2015