Ordered Landmarks in Planning

Many known planning tasks have inherent constraints concerning the best order in which to achieve the goals. A number of research efforts have been made to detect such constraints and to use them for guiding search, in the hope of speeding up the planning process. We go beyond the previous approaches by considering ordering constraints not only over the (top-level) goals, but also over the sub-goals that will necessarily arise during planning. Landmarks are facts that must be true at some point in every valid solution plan. We extend Koehler and Hoffmann's definition of reasonable orders between top level goals to the more general case of landmarks. We show how landmarks can be found, how their reasonable orders can be approximated, and how this information can be used to decompose a given planning task into several smaller sub-tasks. Our methodology is completely domain- and planner-independent. The implementation demonstrates that the approach can yield significant runtime performance improvements when used as a control loop around state-of-the-art sub-optimal planning systems, as exemplified by FF and LPG

Anosov diffeomorphisms of flat manifolds

Let M be a compact differentiable manifold without boundary. A Riemannian structure on II is called flat if all sectional curvatures vanish at each point; then M is called a flat manifold A diffeomorphism f :→M is called an Anosov diffeomorphism. if for some (and hence any) Riemannian metric on M there exist constants c > 0, ƛ 0 and ║Tf-rw║ ≤ c ƛr║w║ for all W E Eu and all integers r > 0 (the letters s and u stand as usual, for stable and unstable; they are also used for dimensions of the spaces involved). Example if we write matrix T2 =R2/Z2 for the flat torus, then the automorphism of R2 given by the matrix (1112) induces an Anosov diffeomorphism on T2. On the Klein bottle, however, it is impossible to construct an Anosov diffeomorphism. This raises the obvious question: On which manifolds can we construct Anosov diffeomorphisms? c.f. Smale [14] p.760. Smale gives examples of Anosov diffeomorphisms on nilmanifold (p. 761). Shub [13] gives examples on a four-dimensional flat manifold which is not a torus, and on a six- dimensional infranil manifold. We give below a complete algebraic characterization of those flat manifolds whichsupport Anosov diffeomorphisms (see Theorem 2.3.1). Each flat manifold comes prepacked with its own finite group F (the linear holonomy group) and a representation T of this group into GL(n, Z), where '" n is the dimension of the manifold. In chapter 1 we find necessary and also sufficient conditions for M to support an Anosov diffeomorphism, and show that these depend only on 2. the representation T. In chapter 2 we examine those cconditions, as a problem in abstract representation theory and arrive at the surprising conclusion that the conditions are equivalent. They depend on the manner in which T decomposes as we enlarge the coefficient domain first from Z to Q and then to R. What we do is this : first we decompose T over. Q. If any pieces occur more than once in the decomposition we ignore them. We non take those pieces which occur precisely once and attempt to decompose them over R. If we are successful every time, the manifold will support an Anosov diffeomorphism, but if any of them is irreducible over R, then the manifold will not support an Anosov diffeomorphism. In chapter 3 we apply our results to specific problems, generate lots of examples and finally use one of the examples to illustrate a formula of Williams [15] on zeta functions of diffeomorphisms. To reduce the weight of the proofs in chapters 1 and 2, we have assembled those parts of the proofs which have nothing to do with Anosov diffeomorphisms into a chapter 0 which we call "Prerequisites". It is used heavily for reference, and to establish notation

The prevalence of medical reasons for non-participation in the Scottish breast and bowel cancer screening programmes

Objective: Increasing uptake of cancer screening is a priority for health systems internationally, however, some patients may not attend because they are undergoing active treatment for the cancer of interest or have other medical reasons that mean participation would be inappropriate. This study aims to quantify the proportion of non-participants who have a medical reason for not attending cancer screening.<p></p> Methods: Medical reasons for not participating in breast and bowel screening were defined a priori on the basis of a literature review and expert opinion. The notes of 700 patients at two GP practices in Scotland were reviewed, to ascertain the prevalence of medical reasons amongst non-participants. Simple proportions and confidence intervals were calculated.<p></p> Results: 17.4% of breast and 2.3% of bowel screening non-participants had a medical reason to not participate. The two most common reasons were previous breast cancer follow up (8.86%) and recent mammogram (6.57%).<p></p> Conclusion: These patients may not benefit from screening while also being distressed by receiving an invitation. This issue also makes accurate monitoring and target-setting for improving uptake difficult. Further work is needed to estimate robustly the extent to which medical reasons account for screening non-participation in a larger population.<p></p&gt

Ordered Landmarks in Planning

Many known planning tasks have inherent constraints concerning the best order in which to achieve the goals. A number of research efforts have been made to detect such constraints and to use them for guiding search, in the hope of speeding up the planning process. We go beyond the previous approaches by considering ordering constraints not only over the (top-level) goals, but also over the sub-goals that will necessarily arise during planning. Landmarks are facts that must be true at some point in every valid solution plan. We extend Koehler and Hoffmann's definition of reasonable orders between top level goals to the more general case of landmarks. We show how landmarks can be found, how their reasonable orders can be approximated, and how this information can be used to decompose a given planning task into several smaller sub-tasks. Our methodology is completely domain- and planner-independent. The implementation demonstrates that the approach can yield significant runtime performance improvements when used as a control loop around state-of-the-art sub-optimal planning systems, as exemplified by FF and LPG

'Help for hay fever', a goal-focused intervention for people with intermittent allergic rhinitis, delivered in Scottish community pharmacies: study protocol for a pilot cluster randomized controlled trial

<b>Background</b> Despite the availability of evidence-based guidelines for managing allergic rhinitis in primary care, management of the condition in the United Kingdom (UK) remains sub-optimal. Its high prevalence and negative effects on quality of life, school performance, productivity and co-morbid respiratory conditions (in particular, asthma), and high health and societal costs, make this a priority for developing novel models of care. Recent Australian research demonstrated the potential of a community pharmacy-based ‘goal-focused’ intervention to help people with intermittent allergic rhinitis to self-manage their condition better, reduce symptom severity and improve quality of life. In this pilot study we will assess the transferability of the goal-focused intervention to a UK context, the suitability of the intervention materials, procedures and outcome measures and collect data to inform a future definitive UK randomized controlled trial (RCT). <p></p> <b>Methods/design</b> A pilot cluster RCT with associated preliminary economic analysis and embedded qualitative evaluation. The pilot trial will take place in two Scottish Health Board areas: Grampian and Greater Glasgow and Clyde. Twelve community pharmacies will be randomly assigned to intervention or usual care group. Each will recruit 12 customers seeking advice or treatment for intermittent allergic rhinitis. Pharmacy staff in intervention pharmacies will support recruited customers in developing strategies for setting and achieving goals that aim to avoid/minimize triggers for, and eliminate/minimize symptoms of allergic rhinitis. Customers recruited in non-intervention pharmacies will receive usual care. The co-primary outcome measures, selected to inform a sample size calculation for a future RCT, are: community pharmacy and customer recruitment and completion rates; and effect size of change in the validated mini-Rhinoconjunctivitis Quality of Life Questionnaire between baseline, one-week and six-weeks post-intervention. Secondary outcome measures relate to changes in symptom severity, productivity, medication adherence and self-efficacy. Quantitative data about accrual, retention and economic measures, and qualitative data about participants’ experiences during the trial will be collected to inform the future RCT.<P></P> <b>Discussion</b> This work will lay the foundations for a definitive RCT of a community pharmacy-based ‘goal-focused’ self-management intervention for people with intermittent allergic rhinitis. Results of the pilot trial are expected to be available in April 2013

Speeding disease gene discovery by sequence based candidate prioritization

BACKGROUND: Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. RESULTS: We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. CONCLUSION: PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies

Topological transversals to a family of convex sets

Let $\mathcal F$ be a family of compact convex sets in $\mathbb R^d$. We say that $\mathcal F$ has a \emph{topological $\rho$-transversal of index $(m,k)$} ($\rho<m$, $0<k\leq d-m$) if there are, homologically, as many transversal $m$-planes to $\mathcal F$ as $m$-planes containing a fixed $\rho$-plane in $\mathbb R^{m+k}$. Clearly, if $\mathcal F$ has a $\rho$-transversal plane, then $\mathcal F$ has a topological $\rho$-transversal of index $(m,k),$ for $\rho<m$ and $k\leq d-m$. The converse is not true in general. We prove that for a family $\mathcal F$ of $\rho+k+1$ compact convex sets in $\mathbb R^d$ a topological $\rho$-transversal of index $(m,k)$ implies an ordinary $\rho$-transversal. We use this result, together with the multiplication formulas for Schubert cocycles, the Lusternik-Schnirelmann category of the Grassmannian, and different versions of the colorful Helly theorem by B\'ar\'any and Lov\'asz, to obtain some geometric consequences