949 resultados para Quantitative methodology


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This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

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Background. Cardiovascular disease (CVD) remains the most serious threat to life and health in industrialized countries. Atherosclerosis is the main underlying pathology associated with CVD, in particular coronary artery disease (CAD), ischaemic stroke, and peripheral arterial disease. Risk factors play an important role in initiating and accelerating the complex process of atherosclerosis. Most studies of risk factors have focused on the presence or absence of clinically defined CVD. Less is known about the determinants of the severity and extent of atherosclerosis in symptomatic patients. Aims. To clarify the association between coronary and carotid artery atherosclerosis, and to study the determinants associated with these abnormalities with special regard to novel cardiovascular risk factors. Subjects and methods. Quantitative coronary angiography (QCA) and B-mode ultrasound were used to assess coronary and carotid artery atherosclerosis in 108 patients with clinically suspected CAD referred for elective coronary angiography. To evaluate anatomic severity and extent of CAD, several QCA parameters were incorporated into indexes. These measurements reflected CAD severity, extent, and overall atheroma burden and were calculated for the entire coronary tree and separately for different coronary segments (i.e., left main, proximal, mid, and distal segments). Maximum and mean intima-media thickness (IMT) values of carotid arteries were measured and expressed as mean aggregate values. Furthermore, the study design included extensive fasting blood samples, oral glucose tolerance test, and an oral fat-load test to be performed in each participant. Results. Maximum and mean IMT values were significantly correlated with CAD severity, extent, and atheroma burden. There was heterogeneity in associations between IMT and CAD indexes according to anatomical location of CAD. Maximum and mean IMT values, respectively, were correlated with QCA indexes for mid and distal segments but not with the proximal segments of coronary vessels. The values of paraoxonase-1 (PON1) activity and concentration, respectively, were lower in subjects with significant CAD and there was a significant relationship between PON1 activity and concentration and coronary atherosclerosis assessed by QCA. PON1 activity was a significant determinant of severity of CAD independently of HDL cholesterol. Neither PON1 activity nor concentration was associated with carotid IMT. The concentration of triglycerides (TGs), triglyceride-rich lipoproteins (TRLs), oxidized LDL (oxLDL), and the cholesterol content of remnant lipoprotein particle (RLP-C) were significantly increased at 6 hours after intake of an oral fatty meal as compared with fasting values. The mean peak size of LDL remained unchanged 6 hours after the test meal. The correlations between total TGs, TRLs, and RLP-C in fasting and postprandial state were highly significant. RLP-C correlated with oxLDL both in fasting and in fed state and inversely with LDL size. In multivariate analysis oxLDL was a determinant of severity and extent of CAD. Neither total TGs, TRLs, oxLDL, nor LDL size were linked to carotid atherosclerosis. Insulin resistance (IR) was associated with an increased severity and extent of coronary atherosclerosis and seemed to be a stronger predictor of coronary atherosclerosis in the distal parts of the coronary tree than in the proximal and mid parts. In the multivariate analysis IR was a significant predictor of the severity of CAD. IR did not correlate with carotid IMT. Maximum and mean carotid IMT were higher in patients with the apoE4 phenotype compared with subjects with the apoE3 phenotype. Likewise, patients with the apoE4 phenotype had a more severe and extensive CAD than individuals with the apoE3 phenotype. Conclusions. 1) There is an association between carotid IMT and the severity and extent of CAD. Carotid IMT seems to be a weaker predictor of coronary atherosclerosis in the proximal parts of the coronary tree than in the mid and distal parts. 2) PON1 activity has an important role in the pathogenesis of coronary atherosclerosis. More importantly, the study illustrates how the protective role of HDL could be modulated by its components such that equivalent serum concentrations of HDL cholesterol may not equate with an equivalent, potential protective capacity. 3) RLP-C in the fasting state is a good marker of postprandial TRLs. Circulating oxLDL increases in CAD patients postprandially. The highly significant positive correlation between postprandial TRLs and postprandial oxLDL suggests that the postprandial state creates oxidative stress. Our findings emphasize the fundamental role of LDL oxidation in the development of atherosclerosis even after inclusion of conventional CAD risk factors. 4) Disturbances in glucose metabolism are crucial in the pathogenesis of coronary atherosclerosis. In fact, subjects with IR are comparable with diabetic subjects in terms of severity and extent of CAD. 5) ApoE polymorphism is involved in the susceptibility to both carotid and coronary atherosclerosis.

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This paper addresses the problem of detecting and resolving conflicts due to timing constraints imposed by features in real-time systems. We consider systems composed of a base system with multiple features or controllers, each of which independently advise the system on how to react to input events so as to conform to their individual specifications. We propose a methodology for developing such systems in a modular manner based on the notion of conflict tolerant features that are designed to continue offering advice even when their advice has been overridden in the past. We give a simple priority based scheme for composing such features. This guarantees the maximal use of each feature. We provide a formal framework for specifying such features, and a compositional technique for verifying systems developed in this framework.

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Purpose of review: Cancer-related fatigue (CRF) is the most common psychosomatic distress experienced by cancer patients before, during and after chemotherapy. Its impact on functional status and Health Related Quality of Life is a great concern among patients, healthcare professionals and researchers. The primary objective of this systematic review is to determine whether the different chemotherapies affect the association of CRF with individual pro- and anti-inflammatory cytokines. The PRISMA statement guideline has been followed to systematically search and screen article from PubMed and Embase. Recent findings: This review has examined 14 studies which included a total of 1312 patients. These studies assayed 20 different kinds of cytokines. The cytokines interleukin-6, interleukin-1RA, TGF-[beta] and sTNF-R2 were associated with CRF in patients receiving anthracycline-based chemotherapy. However, only interleukin-13 was identified in the taxane-based chemotherapy. Similarly, different sets of cytokines were linked with CRF in patients with chemotherapy regimens containing platinum, cyclophosphamides, topotecan or bleomycin. Summary: This review has identified that cytokines are differentially linked with CRF according to the various types of chemotherapy regimens.

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We describe a noniterative method for recovering optical absorption coefficient distribution from the absorbed energy map reconstructed using simulated and noisy boundary pressure measurements. The source reconstruction problem is first solved for the absorbed energy map corresponding to single- and multiple-source illuminations from the side of the imaging plane. It is shown that the absorbed energy map and the absorption coefficient distribution, recovered from the single-source illumination with a large variation in photon flux distribution, have signal-to-noise ratios comparable to those of the reconstructed parameters from a more uniform photon density distribution corresponding to multiple-source illuminations. The absorbed energy map is input as absorption coefficient times photon flux in the time-independent diffusion equation (DE) governing photon transport to recover the photon flux in a single step. The recovered photon flux is used to compute the optical absorption coefficient distribution from the absorbed energy map. In the absence of experimental data, we obtain the boundary measurements through Monte Carlo simulations, and we attempt to address the possible limitations of the DE model in the overall reconstruction procedure.

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Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

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Marja Heinonen s dissertation Verkkomedian käyttö ja tutkiminen. Iltalehti Online 1995-2001 describes the usage of new internet based news service Iltalehti Online during its first years of existence, 1995-2001. The study focuses on the content of the service and users attitudes towards the new media and its contents. Heinonen has also analyzed and described the research methods that can be used in the research of any new media phenomenon when there is no historical perspective to do the research. Heinonen has created a process model for the research of net medium, which is based on a multidimensional approach. She has chosen an iterative research method inspired by Sudweeks and Simoff s CEDA-methodology in which qualitative and quantitative methods take turns both creating results and new research questions. The dissertation discusses and describes the possibilities of combining several research methods in the study of online news media. On general level it discusses the methodological possibilities of researching a completely new media form when there is no historical perspective. The result of these discussions is in favour for the multidimensional methods. The empiric research was built around three cases of Iltalehti Online among its users: log analysis 1996-1999, interviews 1999 and clustering 2000-2001. Even though the results of different cases were somewhat conflicting here are the central results from the analysis of Iltalehti Online 1995-2001: - Reading was strongly determined by the gender. - The structure of Iltalehti Online guided the reading strongly. - People did not make a clear distinction in content between news and entertainment. - Users created new habits in their everyday life during the first years of using Iltalehti Online. These habits were categorized as follows: - break between everyday routines - established habit - new practice within the rhythm of the day - In the clustering of the users sports, culture and celebrities were the most distinguishing contents. Users did not move across these borders as much as within them. The dissertation gives contribution to the development of multidimensional research methods in the field of emerging phenomena in media field. It is also a unique description of a phase of development in media history through an unique research material. There is no such information (logs + demographics) available of any other Finnish online news media. Either from the first years or today.

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Hole-doped perovskites such as La1-xCaxMnO3 present special magnetic and magnetotransport properties, and it is commonly accepted that the local atomic structure around Mn ions plays a crucial role in determining these peculiar features. Therefore experimental techniques directly probing the local atomic structure, like x-ray absorption spectroscopy (XAS), have been widely exploited to deeply understand the physics of these compounds. Quantitative XAS analysis usually concerns the extended region [extended x-ray absorption fine structure (EXAFS)] of the absorption spectra. The near-edge region [x-ray absorption near-edge spectroscopy (XANES)] of XAS spectra can provide detailed complementary information on the electronic structure and local atomic topology around the absorber. However, the complexity of the XANES analysis usually prevents a quantitative understanding of the data. This work exploits the recently developed MXAN code to achieve a quantitative structural refinement of the Mn K-edge XANES of LaMnO3 and CaMnO3 compounds; they are the end compounds of the doped manganite series LaxCa1-xMnO3. The results derived from the EXAFS and XANES analyses are in good agreement, demonstrating that a quantitative picture of the local structure can be obtained from XANES in these crystalline compounds. Moreover, the quantitative XANES analysis provides topological information not directly achievable from EXAFS data analysis. This work demonstrates that combining the analysis of extended and near-edge regions of Mn K-edge XAS spectra could provide a complete and accurate description of Mn local atomic environment in these compounds.

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Design research informs and supports practice by developing knowledge to improve the chances of producing successful products.Training in design research has been poorly supported. Design research uses human and natural/technical sciences, embracing all facets of design; its methods and tools are adapted from both these traditions. However, design researchers are rarely trained in methods from both the traditions. Research in traditional sciences focuses primarily on understanding phenomena related to human, natural, or technical systems. Design research focuses on supporting improvement of such systems, using understanding as a necessary but not sufficient step, and it must embrace methods for both understanding reality and developing support for its improvement. A one-semester, postgraduate-level, credited course that has been offered since 2002, entitled Methodology for Design Research, is described that teaches a methodology for carrying out research into design. Its steps are to clarify research success; to understand relevant phenomena of design and how these influence success; to use this to envision design improvement and develop proposals for supporting improvement; to evaluate support for its influence on success; and, if unacceptable, to modify, support, or improve the understanding of success and its links to the phenomena of design. This paper highlights some major issues about the status of design research and describes how design research methodology addresses these. The teaching material, model of delivery, and evaluation of the course on methodology for design research are discussed.

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Fish farming introduces nutrients, microbes and a wide variety of chemicals such as heavy metals, antifoulants and antibiotics to the surrounding environment. Introduction of antibiotics has been linked with the increased incidence of antibiotic resistant pathogenic bacteria in the farm vicinities. In this thesis molecular methods such as quantitative PCR and DNA sequencing were applied to analyze bacterial communities in sediments from fish farms and pristine locations. Altogether four farms and four pristine sites were sampled in the Baltic Sea. Two farm and two pristine locations were sampled over a surveillance period of four years. Furthermore, a new methodology was developed as a part of the study that permits amplifying single microbial genomes and capturing them according to any genetic traits, including antibiotic resistance genes. The study revealed that several resistance genes for tetracycline were found at the sediment underneath the aquaculture farms. The copy number of these genes remained elevated even at a farm that had not used any antibiotics since year 2000, six years before this study started. Similarly, an increase in the amount of mercury resistance gene merA was observed at the aquaculture sediment. The persistence of the resistance genes in absence of any selection pressure from antibiotics or heavy metals suggests that the genes may be introduced to the sediment by the farming process. This is also supported by the diversity pattern of the merA gene between farm and pristine sediments. The bacterial community-level changes in response to fish farming were very complex and no single phylogenetic groups were found that would be typical to fish farm sediments. However, the community structures had some correlation with the exposure to fish farming. Our studies suggest that the established approaches to deal with antibiotic resistance at the aquaculture, such as antibiotic cycling, are fundamentally flawed because they cannot prevent the introduction of the resistance genes and resistant bacteria to the farm area by the farming process. Further studies are required to study the entire fish farming process to identify the sources of the resistance genes and the resistant bacteria. The results also suggest that in order to prevent major microbiological changes in the surrounding aquatic environment, the farms should not be founded in shallow water where currents do not transport sedimenting matter from the farms. Finally, the technique to amplify and select microbial genomes will potentially have a considerable impact in microbial ecology and genomics.

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Regional impacts of climate change remain subject to large uncertainties accumulating from various sources, including those due to choice of general circulation models (GCMs), scenarios, and downscaling methods. Objective constraints to reduce the uncertainty in regional predictions have proven elusive. In most studies to date the nature of the downscaling relationship (DSR) used for such regional predictions has been assumed to remain unchanged in a future climate. However,studies have shown that climate change may manifest in terms of changes in frequencies of occurrence of the leading modes of variability, and hence, stationarity of DSRs is not really a valid assumption in regional climate impact assessment. This work presents an uncertainty modeling framework where, in addition to GCM and scenario uncertainty, uncertainty in the nature of the DSR is explored by linking downscaling with changes in frequencies of such modes of natural variability. Future projections of the regional hydrologic variable obtained by training a conditional random field (CRF) model on each natural cluster are combined using the weighted Dempster-Shafer (D-S) theory of evidence combination. Each projection is weighted with the future projected frequency of occurrence of that cluster (''cluster linking'') and scaled by the GCM performance with respect to the associated cluster for the present period (''frequency scaling''). The D-S theory was chosen for its ability to express beliefs in some hypotheses, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The methodology is tested for predicting monsoon streamflow of the Mahanadi River at Hirakud Reservoir in Orissa, India. The results show an increasing probability of extreme, severe, and moderate droughts due to limate change. Significantly improved agreement between GCM predictions owing to cluster linking and frequency scaling is seen, suggesting that by linking regional impacts to natural regime frequencies, uncertainty in regional predictions can be realistically quantified. Additionally, by using a measure of GCM performance in simulating natural regimes, this uncertainty can be effectively constrained.

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The special magnetotransport properties of hole doped manganese perovskites originate from a complex interplay among structural, magnetic and electronic degree of freedom. In this picture the local atomic structure around Mn ions plays a special role and this is the reason why short range order techniques like X-ray absorption spectroscopy (XAS) have been deeply exploited for studying these compounds. The analysis of near edge region features (XANES) of XAS spectra can provide very fine details of the local structure around Mn, complementary to the EXAFS, so contributing to the full understanding of the peculiar physical properties of these materials. Nevertheless the XANES analysis is complicated by the large amount of structural and electronic details involved making difficult the quantitative interpretation.This work exploits the recently developed MXAN code to achieve a full structural refinement of the Mn K edge XANES of LaMnO3 and CaMnO3 compounds; they are the end compounds of the doped manganite series LaxCa1-xMnO3, in which the Mn ions are present only in one charge state as Mn3+ and Mn4+ respectively. The good agreement between the results derived from the analysis of near edge and extended region of the XAS spectra demonstrates that a quantitative picture of the local structure call be obtained from structural refinement of Mn K edge XANES data in these crystalline compounds. The XANES analysis offers, in addition.. the possibility to directly achieve information on the topology of local atomic structure around the absorber not directly achievable from EXAFS.