946 resultados para Particle-antiparticle correlation


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High-energy charged particles in the van Allen radiation belts and in solar energetic particle events can damage satellites on orbit leading to malfunctions and loss of satellite service. Here we describe some recent results from the SPACECAST project on modelling and forecasting the radiation belts, and modelling solar energetic particle events. We describe the SPACECAST forecasting system that uses physical models that include wave-particle interactions to forecast the electron radiation belts up to 3 h ahead. We show that the forecasts were able to reproduce the >2 MeV electron flux at GOES 13 during the moderate storm of 7-8 October 2012, and the period following a fast solar wind stream on 25-26 October 2012 to within a factor of 5 or so. At lower energies of 10- a few 100 keV we show that the electron flux at geostationary orbit depends sensitively on the high-energy tail of the source distribution near 10 RE on the nightside of the Earth, and that the source is best represented by a kappa distribution. We present a new model of whistler mode chorus determined from multiple satellite measurements which shows that the effects of wave-particle interactions beyond geostationary orbit are likely to be very significant. We also present radial diffusion coefficients calculated from satellite data at geostationary orbit which vary with Kp by over four orders of magnitude. We describe a new automated method to determine the position at the shock that is magnetically connected to the Earth for modelling solar energetic particle events and which takes into account entropy, and predict the form of the mean free path in the foreshock, and particle injection efficiency at the shock from analytical theory which can be tested in simulations.

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The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

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Purpose: To assess the visibility and the features of ECUATS on 3.0-T MRI studies, and evaluate their correlation with tendinosis. Methods and materials: Our retrospective study was approved by IRB, with waiver of informed consent. Fifty wrist MRI and 48 MR arthrographies from 98 patients (55 males, 43 females, mean age 42.3 years) performed between January and November 2009 on 3.0-T units were reviewed. Images (transverse T1, T2, FS Gd T1 and VIBE) were independently analyzed by two radiologists, and a consensus reached with a third reader in case of disagreement. The visibility of ECUATS was assessed on each available transverse sequence. When present, ECUATS' origins, diameters and insertions were noted. ECU tendinosis was also evaluated. Inter-rater agreement was assessed using Cohen's Kappa coefficient. Results: ECUATS observed prevalence was 23.5% (23/98). ECUATS were more frequently noted on the VIBE sequence, with a good inter-rater agreement (Kappa = 0.72). Origins were noted in 95.7% of cases: 3 were at the level of, and 20 distal to ECU subsheath. Insertions were seen in 43.5%: 2 were on 5th metacarpal bone, 8 on extensor apparatus of 5th finger. ECUATS mean shortest and longest diameters were 0.54 and 0.85 mm respectively. ECU tendinosis was statistically more frequently noted in patients with ECUATS (p <0.05). Conclusion: ECUATS are readily visible on 3.0-T MRI studies, especially on transverse GRE VIBE images. ECU tendinosis is more frequently noted in patients bearing ECUATS.

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Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

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Staphylococcus aureus infections involve numerous adhesins and toxins, which expression depends on complex regulatory networks. Adhesins include a family of surface proteins covalently attached to the peptidoglycan via a conserved LPXTG motif. Here we determined the protein and mRNA expression of LPXTG-proteins of S. aureus Newman in time-course experiments, and their relation to fibrinogen adherence in vitro. Experiments were performed with mutants in the global accessory-gene regulator (agr), surface protein A (Spa), and fibrinogen-binding protein A (ClfA), as well as during growth in iron-rich or iron-poor media. Surface proteins were recovered by trypsin-shaving of live bacteria. Released peptides were analyzed by liquid chromatography coupled to tandem mass-spectrometry. To unambiguously identify peptides unique to LPXTG-proteins, the analytical conditions were refined using a reference library of S. aureus LPXTG-proteins heterogeneously expressed in surrogate Lactococcus lactis. Transcriptomes were determined by microarrays. Sixteen of the 18 LPXTG-proteins present in S. aureus Newman were detected by proteomics. Nine LPXTG-proteins showed a bell-shape agr-like expression that was abrogated in agr-negative mutants including Spa, fibronectin-binding protein A (FnBPA), ClfA, iron-binding IsdA, and IsdB, immunomodulator SasH, functionally uncharacterized SasD, biofilm-related SasG and methicillin resistance-related FmtB. However, only Spa and SasH modified their proteomic and mRNA profiles in parallel in the parent and its agr- mutant, whereas all other LPXTG-proteins modified their proteomic profiles independently of their mRNA. Moreover, ClfA became highly transcribed and active in fibrinogen-adherence tests during late growth (24 h), whereas it remained poorly detected by proteomics. On the other hand, iron-regulated IsdA-B-C increased their protein expression by >10-times in iron-poor conditions. Thus, proteomic, transcriptomic, and adherence-phenotype demonstrated differential profiles in S. aureus. Moreover, trypsin peptide signatures suggested differential protein domain exposures in various environments, which might be relevant for anti-adhesin vaccines. A comprehensive understanding of the S. aureus physiology should integrate all three approaches.

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This project was undertaken to study the relationships between the performance of locally available asphalts and their physicochemical properties under Iowa conditions with the ultimate objective of development of a locally and performance-based asphalt specification for durable pavements. Physical and physicochemical tests were performed on three sets of asphalt samples including: (a) twelve samples from local asphalt suppliers and their TFOT residues, (b) six core samples of known service records, and (c) a total of 79 asphalts from 10 pavement projects including original, lab aged and recovered asphalts from field mixes, as well as from lab aged mixes. Tests included standard rheological tests, HP-GPC and TMA. Some specific viscoelastic tests (at 5 deg C) were run on b samples and on some a samples. DSC and X-ray diffraction studies were performed on a and b samples. Furthermore, NMR techniques were applied to some a, b and c samples. Efforts were made to identify physicochemical properties which are correlated to physical properties known to affect field performance. The significant physicochemical parameters were used as a basis for an improved performance-based trial specification for Iowa to ensure more durable pavements.

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The objective of this work was to evaluate the correlation between sugarcane yield and some physical and chemical attributes of soil. For this, a 42‑ha test area in Araras, SP, Brazil, was used. Soil properties were determined from samples collected at the beginning of the 2003/2004 harvest season, using a regular 100x100 m grid. Yield assessment was done with a yield monitor (Simprocana). Correlation analyses were performed between sugarcane yield and the following soil properties: pH, pH CaCl2, N, C, cone index, clay content, soil organic matter, P, K, Ca, Mg, H+AL, cation exchange capacity, and base saturation. Correlation coefficients were respectively ‑0.05, ‑0.29, 0.33, 0.41, ‑0.27, 0.22, 0.44, ‑0.24, trace, ‑0.06, 0.01, 0.32, 0.14, and 0.04. Correlations of chemical and physical attributes of soil with sugarcane yield are weak, and, per se, they are not able to explain sugarcane yield variation, which suggests that other variables, besides soil attributes, should be analysed.

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High-energy charged particles in the van Allen radiation belts and in solar energetic particle events can damage satellites on orbit leading to malfunctions and loss of satellite service. Here we describe some recent results from the SPACECAST project on modelling and forecasting the radiation belts, and modelling solar energetic particle events. We describe the SPACECAST forecasting system that uses physical models that include wave-particle interactions to forecast the electron radiation belts up to 3 h ahead. We show that the forecasts were able to reproduce the >2 MeV electron flux at GOES 13 during the moderate storm of 7-8 October 2012, and the period following a fast solar wind stream on 25-26 October 2012 to within a factor of 5 or so. At lower energies of 10- a few 100 keV we show that the electron flux at geostationary orbit depends sensitively on the high-energy tail of the source distribution near 10 RE on the nightside of the Earth, and that the source is best represented by a kappa distribution. We present a new model of whistler mode chorus determined from multiple satellite measurements which shows that the effects of wave-particle interactions beyond geostationary orbit are likely to be very significant. We also present radial diffusion coefficients calculated from satellite data at geostationary orbit which vary with Kp by over four orders of magnitude. We describe a new automated method to determine the position at the shock that is magnetically connected to the Earth for modelling solar energetic particle events and which takes into account entropy, and predict the form of the mean free path in the foreshock, and particle injection efficiency at the shock from analytical theory which can be tested in simulations.

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Background: Urine is still the matrix of choice to fight against doping, because it can be collected non-invasively during anti-doping tests. Most of the World Anti-Doping Agency's accredited laboratories have more than 20 years experience in analyzing this biological fluid and the majority of the compounds listed in the 2010 Prohibited List - International Standard are eliminated through the urinary apparatus. Storing and transporting urine samples for doping analyses does not include a specific protocol to prevent microbial and thermal degradation. The use of a rapid and reliable screening method could enable determine reference intervals for urine specimens in doping control samples and evaluate notably the prevalence of microbial contamination known to be responsible for the degradation of chemical substances in urine.Methods: The Sysmex(R) UF-500i is a recent urine flow cytometer analyzer capable of quantifying BACT and other urinary particles such as RBC, WBC, EC, DEBRIS, CAST, PATH. CAST, YLC, SRC as well as measuring urine conductivity. To determine urine anti-doping reference intervals, 501 samples received in our laboratory over a period of two months were submitted to an immediate examination. All samples were collected and then transported at room temperature. Analysis of variance was performed to test the effects of factors such as gender, test type [in-competition, out-of-competition] and delivery time.Results: The data obtained showed that most of the urine samples were highly contaminated with bacteria. The other urine particles were also very different according to the factors.Conclusions: The Sysmex(R) UF-500i was capable of providing a snapshot of urine particles present in the samples at the time of the delivery to the laboratory. These particles, BACT in particular, gave a good idea of the possible microbial degradation which had and/or could have occurred in the sample. This information could be used as the first quality control set up in WADA (World Anti-Doping Agency) accredited laboratories to determine if steroid profiles, endogenous and prohibited substances have possibly been altered. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

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The objective of this work was to propose a way of using the Tocher's method of clustering to obtain a matrix similar to the cophenetic one obtained for hierarchical methods, which would allow the calculation of a cophenetic correlation. To illustrate the obtention of the proposed cophenetic matrix, we used two dissimilarity matrices - one obtained with the generalized squared Mahalanobis distance and the other with the Euclidean distance - between 17 garlic cultivars, based on six morphological characters. Basically, the proposal for obtaining the cophenetic matrix was to use the average distances within and between clusters, after performing the clustering. A function in R language was proposed to compute the cophenetic matrix for Tocher's method. The empirical distribution of this correlation coefficient was briefly studied. For both dissimilarity measures, the values of cophenetic correlation obtained for the Tocher's method were higher than those obtained with the hierarchical methods (Ward's algorithm and average linkage - UPGMA). Comparisons between the clustering made with the agglomerative hierarchical methods and with the Tocher's method can be performed using a criterion in common: the correlation between matrices of original and cophenetic distances.

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While scientific realism generally assumes that successful scientific explanations yield information about reality, realists also have to admit that not all information acquired in this way is equally well warranted. Some versions of scientific realism do this by saying that explanatory posits with which we have established some kind of causal contact are better warranted than those that merely appear in theoretical hypotheses. I first explicate this distinction by considering some general criteria that permit us to distinguish causal warrant from theoretical warrant. I then apply these criteria to a specific case from particle physics, claiming that scientific realism has to incorporate the distinction between causal and theoretical warrant if it is to be an adequate stance in the philosophy of particle physics.