Uniformly convergent finite element methods for singularly perturbed parabolic partial differential equations

This thesis is concerned with uniformly convergent finite element methods for numerically solving singularly perturbed parabolic partial differential equations in one space variable. First, we use Petrov-Galerkin finite element methods to generate three schemes for such problems, each of these schemes uses exponentially fitted elements in space. Two of them are lumped and the other is non-lumped. On meshes which are either arbitrary or slightly restricted, we derive global energy norm and L2 norm error bounds, uniformly in the diffusion parameter. Under some reasonable global assumptions together with realistic local assumptions on the solution and its derivatives, we prove that these exponentially fitted schemes are locally uniformly convergent, with order one, in a discrete L∞norm both outside and inside the boundary layer. We next analyse a streamline diffusion scheme on a Shishkin mesh for a model singularly perturbed parabolic partial differential equation. The method with piecewise linear space-time elements is shown, under reasonable assumptions on the solution, to be convergent, independently of the diffusion parameter, with a pointwise accuracy of almost order 5/4 outside layers and almost order 3/4 inside the boundary layer. Numerical results for the above schemes are presented. Finally, we examine a cell vertex finite volume method which is applied to a model time-dependent convection-diffusion problem. Local errors away from all layers are obtained in the l2 seminorm by using techniques from finite element analysis.

A qualitative study of trends in patient preferences for the management of partial dentition

Objective: To identify factors influencing attitudes of partially dentate adults towards dental treatment in Ireland. Background: People are retaining more teeth later in life than ever before. Management of partially dentate older adults will be a major requirement for the future and it is important to determine factors which may influence patients’ attitudes to care. Methods: Subjects: A purposive sample of 22 partially dentate patients was recruited; 12 women and 12 men, ranging in age from 45 to 75 years. Data Collection: Semi-structured individual interviews. Results: Dental patients have increasing expectations in relation to (i) a more sophisticated approach to the management of missing teeth and (ii) their right to actively participate in decision making regarding the management of their tooth loss. There is some evidence of a cohort effect with younger patients (45–64 years) having higher expectations. Conclusions: The evidence of a cohort effect within this study in relation to higher patient expectations indicates that both contemporary and future patients are likely to seek a service based on conservation and restoration of missing teeth by fixed prostheses.

Sorting under partial information (without the ellipsoid algorithm)

We revisit the well-known problem of sorting under partial information: sort a finite set given the outcomes of comparisons between some pairs of elements. The input is a partially ordered set P, and solving the problem amounts to discovering an unknown linear extension of P, using pairwise comparisons. The information-theoretic lower bound on the number of comparisons needed in the worst case is log e(P), the binary logarithm of the number of linear extensions of P. In a breakthrough paper, Jeff Kahn and Jeong Han Kim (STOC 1992) showed that there exists a polynomial-time algorithm for the problem achieving this bound up to a constant factor. Their algorithm invokes the ellipsoid algorithm at each iteration for determining the next comparison, making it impractical. We develop efficient algorithms for sorting under partial information. Like Kahn and Kim, our approach relies on graph entropy. However, our algorithms differ in essential ways from theirs. Rather than resorting to convex programming for computing the entropy, we approximate the entropy, or make sure it is computed only once in a restricted class of graphs, permitting the use of a simpler algorithm. Specifically, we present: an O(n2) algorithm performing O(log n·log e(P)) comparisons; an O(n2.5) algorithm performing at most (1+ε) log e(P) + Oε(n) comparisons; an O(n2.5) algorithm performing O(log e(P)) comparisons. All our algorithms are simple to implement. © 2010 ACM.

Intrastereomic proteins from the asteroid Asterias rubens. separation, partial characterization ,and interactions with growing calcite crystals

info:eu-repo/semantics/published

Clinical practice guidelines for the management of cryptococcal disease: 2010 update by the infectious diseases society of america.

Cryptococcosis is a global invasive mycosis associated with significant morbidity and mortality. These guidelines for its management have been built on the previous Infectious Diseases Society of America guidelines from 2000 and include new sections. There is a discussion of the management of cryptococcal meningoencephalitis in 3 risk groups: (1) human immunodeficiency virus (HIV)-infected individuals, (2) organ transplant recipients, and (3) non-HIV-infected and nontransplant hosts. There are specific recommendations for other unique risk populations, such as children, pregnant women, persons in resource-limited environments, and those with Cryptococcus gattii infection. Recommendations for management also include other sites of infection, including strategies for pulmonary cryptococcosis. Emphasis has been placed on potential complications in management of cryptococcal infection, including increased intracranial pressure, immune reconstitution inflammatory syndrome (IRIS), drug resistance, and cryptococcomas. Three key management principles have been articulated: (1) induction therapy for meningoencephalitis using fungicidal regimens, such as a polyene and flucytosine, followed by suppressive regimens using fluconazole; (2) importance of early recognition and treatment of increased intracranial pressure and/or IRIS; and (3) the use of lipid formulations of amphotericin B regimens in patients with renal impairment. Cryptococcosis remains a challenging management issue, with little new drug development or recent definitive studies. However, if the diagnosis is made early, if clinicians adhere to the basic principles of these guidelines, and if the underlying disease is controlled, then cryptococcosis can be managed successfully in the vast majority of patients.

Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.

Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging.

In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T2(∗) -weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed.

Diagnosis of tuberculosis: update of interferon gamma release tests in clinical practice

info:eu-repo/semantics/nonPublished

Covering Partial Cubes with Zones

http://www.combinatorics.org/ojs/index.php/eljc/article/view/v22i3p31

Deriving explanations from partial temporal information

The representation and manipulation of natural human understanding of temporal phenomena is a fundamental field of study in Computer Science, which aims both to emulate human thinking, and to use the methods of human intelligence to underpin engineering solutions. In particular, in the domain of Artificial Intelligence, temporal knowledge may be uncertain and incomplete due to the unavailability of complete and absolute temporal information. This paper introduces an inferential framework for deriving logical explanations from partial temporal information. Based on a graphical representation which allows expression of both absolute and relative temporal knowledge in incomplete forms, the system can deliver a verdict to the question if a given set of statements is temporally consistent or not, and provide understandable logical explanation of analysis by simplified contradiction and rule based reasoning.

Radio propagation modeling for capacity optimization in wireless relay MIMO systems with partial CSI

The enormous growth of wireless communication systems makes it important to evaluate the capacity of such channels. Multiple Input Multiple Output (MIMO) wireless communication systems are shown to yield significant performance improvement to data rates when compared to the traditional Single Input Single Output (SISO) wireless systems. The benefits of multiple antenna elements at the transmitter and receiver have become necessary to the research and the development of the next generation of mobile communication systems. In this paper we propose the use of Relaying MIMO wireless communication systems for use over long throughput. We investigate how Relays can be used in a "demodulate-and-forward" operation when the transmitter is equipped with spatially correlated multiple antenna elements and the receiver has only partial knowledge of the statistics of the channel. We show that Relays between the source and destination nodes of a wireless communication system in MIMO configuration improve the throughput of the system when compared to the typical MIMO systems, or achieve the desired channel capacity with significantly lower power resources needed.