886 resultados para Discrete Gaussian Sampling


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An assessment of sewage workers' exposure to airborne cultivable bacteria, fungi and inhaled endotoxins was performed at 11 sewage treatment plants. We sampled the enclosed and unenclosed treatment areas in each plant and evaluated the influence of seasons (summer and winter) on bioaerosol levels. We also measured personal exposure to endotoxins of workers during special operation where a higher risk of bioaerosol inhalation was assumed. Results show that only fungi are present in significantly higher concentrations in summer than in winter (2331 +/- 858 versus 329 +/- 95 CFU m(-3)). We also found that there are significantly more bacteria in the enclosed area, near the particle grids for incoming water, than in the unenclosed area near the aeration basins (9455 +/- 2661 versus 2435 +/- 985 CFU m(-3) in summer and 11 081 +/- 2299 versus 2002 +/- 839 CFU m(-3) in winter). All bioaerosols were frequently above the recommended values of occupational exposure. Workers carrying out special tasks such as cleaning tanks were exposed to very high levels of endotoxins (up to 500 EU m(-3)) compared to routine work. The species composition and concentration of airborne Gram-negative bacteria were also studied. A broad spectrum of different species within the Pseudomonadaceae and the Enterobacteriaceae families were predominant in nearly all plants investigated. [Authors]

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Introduction/objectives: Multipatient use of a single-patient CBSD occurred inan outpatient clinic during 4 to 16 months before itsnotification. We looked for transmission of blood-bornepathogens among exposed patients.Methods: Exposed patients underwent serology testing for HBV,HCV and HIV. Patients with isolated anti-HBc receivedone dose of hepatitis B vaccine to look for a memoryimmune response. Possible transmissions were investigatedby mapping visits and sequencing of the viral genomeif needed.Results: Of 280 exposed patients, 9 had died without suspicionof blood-borne infection, 3 could not be tested, and 5declined investigations. Among the 263 (93%) testedpatients, 218 (83%) had negative results. We confirmeda known history of HCV infection in 6 patients (1 coinfectedby HIV), and also identified resolved HBVinfection in 37 patients, of whom 18 were alreadyknown. 2 patients were found to have a previouslyunknown HCV infection. According to the time elapsedfrom the closest previous visit of a HCV-infected potentialsource patient, we could rule out nosocomial transmissionin one case (14 weeks) but not in the other (1day). In the latter, however, transmission was deemedvery unlikely by 2 reference centers based on thesequences of the E1 and HVR1 regions of the virus.Conclusion: We did not identify any transmission of blood-bornepathogens in 263 patients exposed to a single-patientCBSD, despite the presence of potential source cases.Change of needle and disinfection of the device betweenpatients may have contributed to this outcome.Although we cannot exclude transmission of HBV, previousacquisition in endemic countries is a more likelyexplanation in this multi-national population.

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The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

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The paper considers the use of artificial regression in calculating different types of score test when the log

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A study on lead pollution was carried out on a sample of ca. 300 city children. This paper presents the errors producing bias in the sample. It is emphasized that, in Switzerland, the difference between the Swiss and the migrant population (the latter being mainly Italian and Spanish) must be taken into account.

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Staphylococcal enterotoxins are bacterial products that display superantigen activity in vitro as well as in vivo. For instance, staphylococcal enterotoxin B (SEB) polyclonally activates T cells that bear the Vbeta8 gene segment of the TCR. SEB-activated T cells undergo a burst of proliferation that is followed by apoptosis. Using an in vivo adaptation of a fluorescent cell division monitoring technique, we show here that SEB-activated T cells divide asynchronously, and that apoptosis of superantigen-activated T cells is preferentially restricted to cells which have undergone a discrete number of cell divisions. Collectively, our data suggest that superantigen-activated T cells are programmed to undergo a fixed number of cell divisions before undergoing apoptosis. A delayed death program may provide a mechanistic compromise between effector functions and homeostasis of activated T cells.

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We present a new a-priori estimate for discrete coagulation fragmentation systems with size-dependent diffusion within a bounded, regular domain confined by homogeneous Neumann boundary conditions. Following from a duality argument, this a-priori estimate provides a global L2 bound on the mass density and was previously used, for instance, in the context of reaction-diffusion equations. In this paper we demonstrate two lines of applications for such an estimate: On the one hand, it enables to simplify parts of the known existence theory and allows to show existence of solutions for generalised models involving collision-induced, quadratic fragmentation terms for which the previous existence theory seems difficult to apply. On the other hand and most prominently, it proves mass conservation (and thus the absence of gelation) for almost all the coagulation coefficients for which mass conservation is known to hold true in the space homogeneous case.

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The objective of this paper is to re-examine the risk-and effort attitude in the context of strategic dynamic interactions stated as a discrete-time finite-horizon Nash game. The analysis is based on the assumption that players are endogenously risk-and effort-averse. Each player is characterized by distinct risk-and effort-aversion types that are unknown to his opponent. The goal of the game is the optimal risk-and effort-sharing between the players. It generally depends on the individual strategies adopted and, implicitly, on the the players' types or characteristics.

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Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (Bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker - typically a client of a forensic examination or a scientist acting on behalf of a client - ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and Bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and Bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing Bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper.

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In this paper we included a very broad representation of grass family diversity (84% of tribes and 42% of genera). Phylogenetic inference was based on three plastid DNA regions rbcL, matK and trnL-F, using maximum parsimony and Bayesian methods. Our results resolved most of the subfamily relationships within the major clades (BEP and PACCMAD), which had previously been unclear, such as, among others the: (i) BEP and PACCMAD sister relationship, (ii) composition of clades and the sister-relationship of Ehrhartoideae and Bambusoideae + Pooideae, (iii) paraphyly of tribe Bambuseae, (iv) position of Gynerium as sister to Panicoideae, (v) phylogenetic position of Micrairoideae. With the presence of a relatively large amount of missing data, we were able to increase taxon sampling substantially in our analyses from 107 to 295 taxa. However, bootstrap support and to a lesser extent Bayesian inference posterior probabilities were generally lower in analyses involving missing data than those not including them. We produced a fully resolved phylogenetic summary tree for the grass family at subfamily level and indicated the most likely relationships of all included tribes in our analysis.

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In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise which is white in time with some spatially homogeneous covariance. These estimates are obtained using tools of the Malliavin calculus. The most challenging part is the lower bound, which is obtained by adapting a general method developed by Kohatsu-Higa to the underlying spatially homogeneous Gaussian setting. Both lower and upper estimates have the same form: a Gaussian density with a variance which is equal to that of the mild solution of the corresponding linear equation with additive noise.