Measurement of the 20 and 90 keV resonances in the 18O(p,α)15{}^{18}{\rm O}(p,\alpha){}^{15}N reaction via THM

The $^{18}{\rm O}(p,\alpha)^{15}{\rm N}$ reaction is of primary importance in several astrophysical scenarios, including fluorine nucleosynthesis inside AGB stars as well as oxygen and nitrogen isotopic ratios in meteorite grains. Thus the indirect measurement of the low energy region of the $^{18}{\rm O}(p,\alpha)^{15}{\rm N}$ reaction has been performed to reduce the nuclear uncertainty on theoretical predictions. In particular the strength of the 20 and 90 keV resonances have been deduced and the change in the reaction rate evaluated.Comment: 4 pages, 4 figures, submitted to PR

Clinical and service implications of a cognitive analytic therapy model of psychosis

Cognitive analytic therapy (CAT) is an integrative, interpersonal model of therapy predicated on a radically social concept of self, developed over recent years in the UK by Anthony Ryle. A CAT-based model of psychotic disorder has been developed much more recently based on encouraging early experience in this area. The model describes and accounts for many psychotic experiences and symptoms in terms of distorted, amplified or muddled enactments of normal or ‘neurotic’ reciprocal role procedures (RRPs) and of damage at a meta-procedural level to the structures of the self. Reciprocal role procedures are understood in CAT to represent the outcome of the process of internalization of early, sign-mediated, interpersonal experience and to constitute the basis for all mental activity, normal or otherwise. Enactments of maladaptive RRPs generated by early interpersonal stress are seen in this model to constitute a form of ‘internal expressed emotion’. Joint description of these RRPs and their enactments (both internally and externally) and their subsequent revision is central to the practice of CAT during which they are mapped out through written and diagrammatic reformulations. This model may usefully complement and extend existing approaches, notably recent CBT-based interventions, particularly with ‘difficult’ patients, and generate meaningful and helpful understandings of these disorders for both patients and their treating teams. We suggest that use of a coherent and robust model such as CAT could have important clinical and service implications in terms of developing and researching models of these disorders as well as for the training of multidisciplinary teams in their effective treatment

Bifidobacterium canis sp. Nov., a novel member of the bifidobacterium pseudolongum phylogenetic group isolated from faeces of a dog (canis lupus f. familiaris)

A fructose-6-phosphate phosphoketolase-positive strain (GSD1FST) was isolated from a faecal sample of a 3 weeks old German Shepherd dog. The closest related taxa to isolate GSD1FST based on results from the EZBioCloud database were Bifidobacte-rium animalis subsp. animalis ATCC 25527T, Bifidobacterium animalis subsp. lactis DSM 10140T and Bifidobacterium anseris LMG 30189T, belonging to the Bifidobacterium pseudolongum phylogenetic group. The resulting 16S rRNA gene identities (compared length of 1454 nucleotides) towards these taxa were 97.30, 97.23 and 97.09 %, respectively. The pairwise similarities of strain GSD1FST using argS, atpA, fusA, hsp60, pyrG, rpsC, thrS and xfp gene fragments to all valid representatives of the B. pseudo-longum phylogenetic group were in the concatenated range of 83.08–88.34 %. Phylogenomic analysis based on whole-genome methods such as average nucleotide identity revealed that bifidobacterial strain GSD1FST exhibits close phylogenetic relatedness (88.17 %) to Bifidobacetrium cuniculi LMG 10738T. Genotypic characteristics and phylogenetic analyses based on nine molecular markers, as well as genomic and comparative phenotypic analyses, clearly proved that the evaluated strain should be considered as representing a novel species within the B. pseudolongum phylogenetic group named as Bifidobacterium canis sp. nov. (GSD1FST=DSM 105923T=LMG 30345T=CCM 8806T)

Generalized methods and solvers for noise removal from piecewise constant signals. II. New methods

Removing noise from signals which are piecewise constant (PWC) is a challenging signal processing problem that arises in many practical scientific and engineering contexts. In the first paper (part I) of this series of two, we presented background theory building on results from the image processing community to show that the majority of these algorithms, and more proposed in the wider literature, are each associated with a special case of a generalized functional, that, when minimized, solves the PWC denoising problem. It shows how the minimizer can be obtained by a range of computational solver algorithms. In this second paper (part II), using this understanding developed in part I, we introduce several novel PWC denoising methods, which, for example, combine the global behaviour of mean shift clustering with the local smoothing of total variation diffusion, and show example solver algorithms for these new methods. Comparisons between these methods are performed on synthetic and real signals, revealing that our new methods have a useful role to play. Finally, overlaps between the generalized methods of these two papers and others such as wavelet shrinkage, hidden Markov models, and piecewise smooth filtering are touched on

Automated diffeomorphic registration of anatomical structures with rigid parts: application to dynamic cervical MRI.

International audienceWe propose an iterative two-step method to compute a diffeomorphic non-rigid transformation between images of anatomical structures with rigid parts, without any user intervention or prior knowledge on the image intensities. First we compute spatially sparse, locally optimal rigid transformations between the two images using a new block matching strategy and an efficient numerical optimiser (BOBYQA). Then we derive a dense, regularised velocity field based on these local transformations using matrix logarithms and M-smoothing. These two steps are iterated until convergence and the final diffeomorphic transformation is defined as the exponential of the accumulated velocity field. We show our algorithm to outperform the state-of-the-art log-domain diffeomorphic demons method on dynamic cervical MRI data

Asymptotic normalization coefficients from the 14C(d,p)15C reaction

The {sup 14}C(n, {gamma}){sup 15}C reaction plays an important role in inhomogeneous big bang models. In Timofeyuk et al.[Phys. Rev. Lett. 96, 162501 (2006)] it was shown that the {sup 14}C(n, {gamma}){sup 15}C radiative capture at astrophysically relevant energies is a peripheral reaction, i.e., the overall normalization of its cross section is determined by the asymptotic normalization coefficient (ANC) for {sup 15}C{yields}{sup 14}C+n. Here we present new measurements of the {sup 14}C(d, p){sup 15}C differential cross sections at deuteron incident energy of 17.06 MeV and the analysis to determine the ANCs for neutron removal from the ground and first excited states of {sup 15}C. The results are compared with previous estimations