Cost-effectiveness of physical fitness training for stroke survivors

Background Physical fitness is impaired after stroke, yet fitness training after stroke reduces disability. Several international guidelines recommend that fitness training be incorporated as part of stroke rehabilitation. However, information about cost-effectiveness is limited. Methods A decision tree model was used to estimate the cost-effectiveness of a fitness programme for stroke survivors vs. relaxation (control group). This was based on a published randomised controlled trial, from which evidence about quality of life was used to estimate Quality Adjusted Life Years. Costs were based on the cost of the provision of group fitness classes within local community centres and a cost per Quality Adjusted Life Year was calculated. Results The results of the base case analysis found an incremental cost per Quality Adjusted Life Year of £2,343. Conclusions Physical fitness sessions after stroke are a cost-effective intervention for stroke survivors. This information will help make the case for the development of new services

Effect of seeding rate and row spacing on the agronomic performance of winter wheat

Non-Peer ReviewedThe effect of row spacings and seed rates on the agronomic performance of "stubbled in" winter wheat (Triticum aestivum L.) were studied over a period of two years at locations in central, northeast, and southeast Saskatchewan. In both years of the study there was a highly significant relationship between row spacing and yield with increased yields at narrower row spacings. The yield response to seeding rate indicated different trends in each of the two years of the study. In 1985/86 there was a highly significant relationship between seed rate and yield with increased yields at higher seed rates. In 1986/87 the relationship between seeding rate and yield was not significant. In 1985/86 higher head counts/m2 at higher seeding rates resulted in the higher yields. In 1986/87 the head counts/m2 were also higher at higher seeding rates however a reduction in seeds/head and/or 1000k weight counteracted the effects of the higher head populations resulting in non-significant yield differences

The effect of hoe-opener design on draft forces of a minimum tillage hoe drill

Non-Peer Reviewe

Using the Regular Chains Library to build cylindrical algebraic decompositions by projecting and lifting

Cylindrical algebraic decomposition (CAD) is an important tool, both for quantifier elimination over the reals and a range of other applications. Traditionally, a CAD is built through a process of projection and lifting to move the problem within Euclidean spaces of changing dimension. Recently, an alternative approach which first decomposes complex space using triangular decomposition before refining to real space has been introduced and implemented within the RegularChains Library of Maple. We here describe a freely available package ProjectionCAD which utilises the routines within the RegularChains Library to build CADs by projection and lifting. We detail how the projection and lifting algorithms were modified to allow this, discuss the motivation and survey the functionality of the package

Effect of seeding depth on the performance of winter wheat

Non-Peer Reviewe

Speeding up Cylindrical Algebraic Decomposition by Gr\"obner Bases

Gr\"obner Bases and Cylindrical Algebraic Decomposition are generally thought of as two, rather different, methods of looking at systems of equations and, in the case of Cylindrical Algebraic Decomposition, inequalities. However, even for a mixed system of equalities and inequalities, it is possible to apply Gr\"obner bases to the (conjoined) equalities before invoking CAD. We see that this is, quite often but not always, a beneficial preconditioning of the CAD problem. It is also possible to precondition the (conjoined) inequalities with respect to the equalities, and this can also be useful in many cases.Comment: To appear in Proc. CICM 2012, LNCS 736

Adapting Real Quantifier Elimination Methods for Conflict Set Computation

The satisfiability problem in real closed fields is decidable. In the context of satisfiability modulo theories, the problem restricted to conjunctive sets of literals, that is, sets of polynomial constraints, is of particular importance. One of the central problems is the computation of good explanations of the unsatisfiability of such sets, i.e.\ obtaining a small subset of the input constraints whose conjunction is already unsatisfiable. We adapt two commonly used real quantifier elimination methods, cylindrical algebraic decomposition and virtual substitution, to provide such conflict sets and demonstrate the performance of our method in practice

Renormalization Group Analysis of \rho-Meson Properties at Finite Density

We calculate the density dependence of the $\rho$-meson mass and coupling constant($g_{\rho NN}$) for $\rho$-nucleon-nucleon vertex at one loop using the lagrangian where the $\rho$-meson is included as a dynamical gauge boson of a hidden local symmetry. From the condition that thermodynamic potential should not depend on the arbitrary energy scale, renormalization scale, one can construct a renormalization group equation for the thermodynamic potential and argue that the various renormalization group coefficients are functions of the density or temperature. We calculate the $\beta$-function for $\rho$-nucleon-nucleon coupling constant ($g_{\rho NN}$) and $\gamma$-function for $\rho$-meson mass ($\gamma_{m_\rho}$). We found that the $\rho$-meson mass and the coupling constant for $g_{\rho NN}$ drop as density increases in the low energy limit.Comment: 24 pages, 10 figures, revised versio

Dynamic noise estimation: a generalized method for modeling noise fluctuations in decision-making

Computational cognitive modeling is an important tool for understanding the processes supporting human and animal decision-making. Choice data in decision-making tasks are inherently noisy, and separating noise from signal can improve the quality of computational modeling. Common approaches to model decision noise often assume constant levels of noise or exploration throughout learning (e.g., the ϵ-softmax policy). However, this assumption is not guaranteed to hold – for example, a subject might disengage and lapse into an inattentive phase for a series of trials in the middle of otherwise low-noise performance. Here, we introduce a new, computationally inexpensive method to dynamically estimate the levels of noise fluctuations in choice behavior, under a model assumption that the agent can transition between two discrete latent states (e.g., fully engaged and random). Using simulations, we show that modeling noise levels dynamically instead of statically can substantially improve model fit and parameter estimation, especially in the presence of long periods of noisy behavior, such as prolonged lapses of attention. We further demonstrate the empirical benefits of dynamic noise estimation at the individual and group levels by validating it on four published datasets featuring diverse populations, tasks, and models. Based on the theoretical and empirical evaluation of the method reported in the current work, we expect that dynamic noise estimation will improve modeling in many decision-making paradigms over the static noise estimation method currently used in the modeling literature, while keeping additional model complexity and assumptions minimal

Synthesis for Polynomial Lasso Programs

We present a method for the synthesis of polynomial lasso programs. These programs consist of a program stem, a set of transitions, and an exit condition, all in the form of algebraic assertions (conjunctions of polynomial equalities). Central to this approach is the discovery of non-linear (algebraic) loop invariants. We extend Sankaranarayanan, Sipma, and Manna's template-based approach and prove a completeness criterion. We perform program synthesis by generating a constraint whose solution is a synthesized program together with a loop invariant that proves the program's correctness. This constraint is non-linear and is passed to an SMT solver. Moreover, we can enforce the termination of the synthesized program with the support of test cases.Comment: Paper at VMCAI'14, including appendi