Morphing of Triangular Meshes in Shape Space

We present a novel approach to morph between two isometric poses of the same non-rigid object given as triangular meshes. We model the morphs as linear interpolations in a suitable shape space $\mathcal{S}$. For triangulated 3D polygons, we prove that interpolating linearly in this shape space corresponds to the most isometric morph in $\mathbb{R}^3$. We then extend this shape space to arbitrary triangulations in 3D using a heuristic approach and show the practical use of the approach using experiments. Furthermore, we discuss a modified shape space that is useful for isometric skeleton morphing. All of the newly presented approaches solve the morphing problem without the need to solve a minimization problem.Comment: Improved experimental result

New tests of the pp-wave correspondence.

The pp-wave/SYM correspondence is an equivalence relation, H string = Δ-J , between the hamiltonian H string of string field theory in the pp-wave background and the dilatation operator Δ in = 4 Super Yang-Mills in the double scaling limit. We calculate matrix elements of these operators in string field theory and in gauge theory. In the string theory Hilbert space we use the natural string basis, and in the gauge theory we use the basis which is isomorphic to it. States in this basis are specific linear combinations of the original BMN operators, and were constructed previously for the case of two scalar impurities. We extend this construction to incorporate BMN operators with vector and mixed impurities. This enables us to verify from the gauge theory perspective two key properties of the three-string interaction vertex of Spradlin and Volovich: (1) the vanishing of the three-string amplitude for string states with one vector and one scalar impurity; and (2) the relative minus sign in the string amplitude involving states with two vector impurities compared to that with two scalar impurities. This implies a spontaneous breaking of the 2 symmetry of the string field theory in the pp-wave background. Furthermore, we calculate the gauge theory matrix elements of Δ-J for states with an arbitrary number of scalar impurities. In all cases we find perfect agreement with the corresponding string amplitudes derived from the three-string vertex

Targeting protein–protein interactions within the cyclic AMP signaling system as a therapeutic strategy for cardiovascular disease

The cAMP signaling system can trigger precise physiological cellular responses that depend on the fidelity of many protein–protein interactions, which act to bring together signaling intermediates at defined locations within cells. In the heart, cAMP participates in the fine control of excitation–contraction coupling, hence, any disregulation of this signaling cascade can lead to cardiac disease. Due to the ubiquitous nature of the cAMP pathway, general inhibitors of cAMP signaling proteins such as PKA, EPAC and PDEs would act non-specifically and universally, increasing the likelihood of serious ‘off target’ effects. Recent advances in the discovery of peptides and small molecules that disrupt the protein–protein interactions that underpin cellular targeting of cAMP signaling proteins are described and discussed

Data-driven identification of parametric partial differential equations

In this work we present a data-driven method for the discovery of parametric partial differential equations (PDEs), thus allowing one to disambiguate between the underlying evolution equations and their parametric dependencies. Group sparsity is used to ensure parsimonious representations of observed dynamics in the form of a parametric PDE, while also allowing the coefficients to have arbitrary time series, or spatial dependence. This work builds on previous methods for the identification of constant coefficient PDEs, expanding the field to include a new class of equations which until now have eluded machine learning based identification methods. We show that group sequentially thresholded ridge regression outperforms group LASSO in identifying the fewest terms in the PDE along with their parametric dependency. The method is demonstrated on four canonical models with and without the introduction of noise

Assessing the effects of the first 2 years of industry-led badger culling in England on the incidence of bovine tuberculosis in cattle in 2013–2015

Culling badgers to control the transmission of bovine tuberculosis (TB) between this wildlife reservoir and cattle has been widely debated. Industry-led culling began in Somerset and Gloucestershire between August and November 2013 to reduce local badger populations. Industry-led culling is not designed to be a randomised and controlled trial of the impact of culling on cattle incidence. Nevertheless, it is important to monitor the effects of the culling and, taking the study limitations into account, perform a cautious evaluation of the impacts. A standardised method for selecting areas matched to culling areas in factors found to affect cattle TB risk has been developed to evaluate the impact of badger culling on cattle TB incidence. The association between cattle TB incidence and badger culling in the first two years has been assessed. Descriptive analyses without controlling for confounding showed no association between culling and TB incidence for Somerset, or for either of the buffer areas for the first two years since culling began. A weak association was observed in Gloucestershire for Year 1 only. Multivariable analysis adjusting for confounding factors showed that reductions in TB incidence were associated with culling in the first two years in both the Somerset and Gloucestershire intervention areas when compared to areas with no culling (IRR: 0.79, 95%CI: 0.72-0.87, p<0.001 and IRR: 0.42, 95%CI: 0.34-0.51, p<0.001 respectively). An increase in incidence was associated with culling in the 2 km buffer surrounding the Somerset intervention area (IRR: 1.38, 95%CI: 1.09-1.75, p=0.008), but not in Gloucestershire (IRR: 0.91, 95%CI: 0.77-1.07, p=0.243). As only two intervention areas with two years’ of data are available for analysis, and the biological cause-effect relationship behind the statistical associations is difficult to determine, it would be unwise to use these findings to develop generalisable inferences about the effectiveness of the policy at present

Exploring the Risk Posed by Animals with An Inconclusive Reaction to the Bovine Tuberculosis Skin Test in England and Wales

The single intradermal comparative cervical tuberculin (SICCT) test is the primary test for ante-mortem diagnosis of bovine tuberculosis (TB) in England and Wales. When an animal is first classified as an inconclusive reactor (IR) using this test, it is not subject to compulsory slaughter, but it must be isolated from the rest of the herd. To understand the risk posed by these animals, a case-control study was conducted to measure the association between IR status of animals and the odds of them becoming a reactor to the SICCT at a subsequent test. The study included all animals from herds in which only IR animals were found at the first whole herd test in 2012 and used data from subsequent tests up until the end of 2016. Separate mixed-effects logistic regression models were developed to examine the relationship between IR status and subsequent reactor status for each risk area of England and for Wales, adjusting for other explanatory variables. The odds of an animal becoming a subsequent reactor during the study period were greater for IR animals than for negative animals in the high-risk area (odds ratio (OR): 6.85 (5.98–7.86)) and edge area (OR: 8.79 (5.92–13.04)) of England and in Wales (OR: 6.87 (5.75–8.22)). In the low-risk area of England, the odds were 23 times greater, although the confidence interval around this estimate was larger due to the smaller sample size (11–48, p < 0.001). These findings support the need to explore differential controls for IR animals to reduce the spread of TB, and they highlight the importance of area-specific policies

An assessment of the application of ultrasound in the processing of ready-to-eat whole brown crab (Cancer pagurus)

This study assesses the potential of incorporating ultrasound as a processing aid in the production of whole cooked brown crab (Cancer pagurus). The FDA recommended heat treatment to reduce Listeria monocytogenes by 6 log10 cycles in this product is a F70 7.5 of 2 min. An equivalent F value was applied at 75 °C in presence and absence of ultrasound in water alone or in water with 5% w/v NaCl added. Heat penetration, turbidity and conductivity of the cook water and also salt and moisture content of the crab meat (white and brown) were determined. Ultrasound assisted cooking allowed a reduction of the cooking time by up to 15% while still maintaining an F70 7.5 of 2 min. Ultrasound also enhanced the rate and total amount of compounds released from the crab, which suggests that crabs cooked in the presence of ultrasound would be expected to be cleaner. Ultrasound also proved to be effective in reducing the salt content but hardly affected the final moisture content of the crab meat

The effectiveness of community engagement in public health interventions for disadvantaged groups: a meta-analysis

BACKGROUND: Inequalities in health are acknowledged in many developed countries, whereby disadvantaged groups systematically suffer from worse health outcomes such as lower life expectancy than non-disadvantaged groups. Engaging members of disadvantaged communities in public health initiatives has been suggested as a way to reduce health inequities. This systematic review was conducted to evaluate the effectiveness of public health interventions that engage the community on a range of health outcomes across diverse health issues. METHODS: We searched the following sources for systematic reviews of public health interventions: Cochrane CDSR and CENTRAL, Campbell Library, DARE, NIHR HTA programme website, HTA database, and DoPHER. Through the identified reviews, we collated a database of primary studies that appeared to be relevant, and screened the full-text documents of those primary studies against our inclusion criteria. In parallel, we searched the NHS EED and TRoPHI databases for additional primary studies. For the purposes of these analyses, study design was limited to randomised and non-randomised controlled trials. Only interventions conducted in OECD countries and published since 1990 were included. We conducted a random effects meta-analysis of health behaviour, health consequences, self-efficacy, and social support outcomes, and a narrative summary of community outcomes. We tested a range of moderator variables, with a particular emphasis on the model of community engagement used as a potential moderator of intervention effectiveness. RESULTS: Of the 9,467 primary studies scanned, we identified 131 for inclusion in the meta-analysis. The overall effect size for health behaviour outcomes is d = .33 (95% CI .26, .40). The interventions were also effective in increasing health consequences (d = .16, 95% CI .06, .27); health behaviour self-efficacy (d = .41, 95% CI .16, .65) and perceived social support (d = .41, 95% CI .23, .65). Although the type of community engagement was not a significant moderator of effect, we identified some trends across studies. CONCLUSIONS: There is solid evidence that community engagement interventions have a positive impact on a range of health outcomes across various conditions. There is insufficient evidence to determine whether one particular model of community engagement is more effective than any other