Exploring the Influence of Patient-Professional Partnerships on the Self-Management of Chronic Back Pain: A Qualitative Study

Patients are encouraged to take an active role in self-managing their chronic back pain and functional problems. However, research suggests that patients do not self-manage, and they expect health professionals to fulfill a comprehensive role in managing pain. A partnership between patients and health professionals is called for, and self-management works best when they share knowledge and work together toward optimal goals. To explore how patients' partnerships with health professionals may influence their ability to self-manage pain by exploring patients' experiences. A grounded theory approach with in-depth, semistructured interviews was undertaken. Each interview was analyzed using constant comparative analysis. This study was nested within a larger study on patient-professional partnerships and the self-management of chronic back pain. Twenty-six patients with chronic back pain were recruited in a community-based pain management service in Northern England, United Kingdom. Three themes emerged: building partnerships with health professionals; being supported by health professionals to self-manage the pain; and experiencing a change in self-management. Five approaches that underpinned health professionals' self-management support were identified. Facilitators of and barriers to a good partnership were reported. This study suggests that a good patient-professional partnership has a positive effect on patients’ self-management ability. A theoretical model explaining how such partnership may influence self-management was developed. It is necessary for both patients and health professionals to be aware of their partnerships, which may enhance the effect of pain management services

A path-oriented encoding evolutionary algorithm for network coding resource minimization

Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, very likely at the cost of huge amount of computational overhead, due to the packet recombination performed (ie coding operations). Hence, it is of practical importance to reduce coding operations while retaining the benefits that network coding brings to us. In this paper, we propose a novel evolutionary algorithm (EA) to minimize the amount of coding operations involved. Different from the state-of-the-art EAs which all use binary encodings for the problem, our EA is based on path-oriented encoding. In this new encoding scheme, each chromosome is represented by a union of paths originating from the source and terminating at one of the receivers. Employing path-oriented encoding leads to a search space where all solutions are feasible, which fundamentally facilitates more efficient search of EAs. Based on the new encoding, we develop three basic operators, that is, initialization, crossover and mutation. In addition, we design a local search operator to improve the solution quality and hence the performance of our EA. The simulation results demonstrate that our EA significantly outperforms the state-of-the-art algorithms in terms of global exploration and computational time

The universal Glivenko-Cantelli property

Let F be a separable uniformly bounded family of measurable functions on a standard measurable space, and let N_{[]}(F,\epsilon,\mu) be the smallest number of \epsilon-brackets in L^1(\mu) needed to cover F. The following are equivalent: 1. F is a universal Glivenko-Cantelli class. 2. N_{[]}(F,\epsilon,\mu)0 and every probability measure \mu. 3. F is totally bounded in L^1(\mu) for every probability measure \mu. 4. F does not contain a Boolean \sigma-independent sequence. It follows that universal Glivenko-Cantelli classes are uniformity classes for general sequences of almost surely convergent random measures.Comment: 26 page

Some new directions in infinite-combinatorial topology

We give a light introduction to selection principles in topology, a young subfield of infinite-combinatorial topology. Emphasis is put on the modern approach to the problems it deals with. Recent results are described, and open problems are stated. Some results which do not appear elsewhere are also included, with proofs.Comment: Small update

The novel gene Ny-1 on potato chromosome IX confers hypersensitive resistance to Potato virus Y and is an alternative to Ry genes in potato breeding for PVY resistance

Hypersensitive resistance (HR) is an efficient defense strategy in plants that restricts pathogen growth and can be activated during host as well as non-host interactions. HR involves programmed cell death and manifests itself in tissue collapse at the site of pathogen attack. A novel hypersensitivity gene, Ny-1, for resistance to Potato virus Y (PVY) was revealed in potato cultivar Rywal. This is the first gene that confers HR in potato plants both to common and necrotic strains of PVY. The locus Ny-1 mapped on the short arm of potato chromosome IX, where various resistance genes are clustered in Solanaceous genomes. Expression of HR was temperature-dependent in cv. Rywal. Strains PVYO and PVYN, including subgroups PVYNW and PVYNTN, were effectively localized when plants were grown at 20°C. At 28°C, plants were systemically infected but no symptoms were observed. In field trials, PVY was restricted to the inoculated leaves and PVY-free tubers were produced. Therefore, the gene Ny-1 can be useful for potato breeding as an alternative donor of PVY resistance, because it is efficacious in practice-like resistance conferred by Ry genes