Training of the Ni-Mn-Fe-Ga ferromagnetic shape-memory alloys by cycling in a high magnetic field

The temperature and magnetic field dependencies of Ni-Mn-Ga polycrystals deformation are investigated. Ingots were prepared by arc-melting in argon atmosphere and further annealing. A training procedure (cycling across the martensitic transition point) for the two-way shape-memory effect was performed with Ni$_{2.16}$Fe$_{0.04}$Mn$_{0.80}$Ga samples. Changes in sample deformations were noticed with changing the magnetic field at a constant temperature. The first cycle deformation increment as compared with the initial value (in the austenitic state at zero field) in the course of the martensitic transition was 0.29%, and 0.41% and 0.48% for the second and third cycles, respectively.Comment: Presented at the Second Moscow International Symposium on Magnetism (Moscow-2002

Index insurance for managing climate-related agricultural risk: toward a strategic research agenda

In October 2011, the CGIAR program on Climate Change, Agriculture and Food Security (CCAFS) and the Index Insurance Innovation Initiative (I4) organized a joint workshop hosted by the International Food Policy Research Institute (IFPRI). The workshop was designed to identify and address issues surrounding index‐based insurance for smallholder farmers and the rural poor in the developing world. Emphasis was placed on identifying key areas of research and learning for the academic and policy community to pursue. The workshop took as its starting point the idea that there is large potential in using indices to insure smallholder farmers. However, in practice, the costs of providing and scaling up index insurance have not been insubstantial. In view of this potential and these constraints, workshop participants identified key areas of research and learning aimed at increasing the benefits of index‐based insurance to smallholder farmers and the rural poor in the developing world. This report summarizes the findings of the two‐day workshop

Long-Term Preservation of Cones and Improvement in Visual Function Following Gene Therapy in a Mouse Model of Leber Congenital Amaurosis Caused by Guanylate Cyclase-1 Deficiency

Leber congenital amaurosis (LCA) is a severe retinal dystrophy manifesting from early infancy as poor vision or blindness. Loss-of-function mutations in GUCY2D cause LCA1 and are one of the most common causes of LCA, accounting for 20% of all cases. Human GUCY2D and mouse Gucy2e genes encode guanylate cyclase-1 (GC), which is responsible for restoring the dark state in photoreceptors after light exposure. The Glicy2e(-/-) mouse shows partially diminished rod function, but an absence of cone function before degeneration. Although the cones appear morphologically normal, they exhibit mislocalization of proteins involved in phototransduction. In this study we tested the efficacy of an rAAV2/8 vector containing the human rhodopsin kinase promoter and the human GUCY2D gene. Following subretinal delivery of the vector in Glicy2e(-/-) mice, GC1 protein was detected in the rod and cone outer segments, and in transduced areas of retina cone transducin was appropriately localized to cone outer segments. Moreover, we observed a dose-dependent restoration of rod and cone function and an improvement in visual behavior of the treated mice. Most importantly, cone preservation was observed in transduced areas up to 6 months post injection. To date, this is the most effective rescue of the Glicy2e(-/-) mouse model of LCA and we propose that a vector, similar to the one used in this study, could be suitable for use in a clinical trial of gene therapy for LCA1

Dynamics of tournaments: the soccer case

A random walk-like model is considered to discuss statistical aspects of tournaments. The model is applied to soccer leagues with emphasis on the scores. This competitive system was computationally simulated and the results are compared with empirical data from the English, the German and the Spanish leagues and showed a good agreement with them. The present approach enabled us to characterize a diffusion where the scores are not normally distributed, having a short and asymmetric tail extending towards more positive values. We argue that this non-Gaussian behavior is related with the difference between the teams and with the asymmetry of the scores system. In addition, we compared two tournament systems: the all-play-all and the elimination tournaments.Comment: To appear in EPJ

Variation in centre-specific survival in patients starting renal replacement therapy in England is explained by enhanced comorbidity information from hospitalization data

Background Unadjusted survival on renal replacement therapy (RRT) varies widely from centre to centre in England. Until now, missing data on case mix have made it impossible to determine whether this variation reflects genuine differences in the quality of care. Data linkage has the capacity to reduce missing data. Methods Modelling of survival using Cox proportional hazards of data returned to the UK Renal Registry on patients starting RRT for established renal failure in England. Data on ethnicity, socioeconomic status and comorbidity were obtained by linkage to the Hospital Episode Statistics database, using data from hospitalizations prior to starting RRT. Results Patients with missing data were reduced from 61 to 4%. The prevalence of comorbid conditions was remarkably similar across centres. When centre-specific survival was compared after adjustment solely for age, survival was below the 95% limit for 6 of 46 centres. The addition of variables into the multivariable model altered the number of centres that appeared to be ‘outliers’ with worse than expected survival as follows: ethnic origin four outliers, socioeconomic status eight outliers and year of the start of RRT four outliers. The addition of a combination of 16 comorbid conditions present at the start of RRT reduced the number of centres with worse than expected survival to one. Conclusions Linked data between a national registry and hospital admission dramatically reduced missing data, and allowed us to show that nearly all the variation between English renal centres in 3-year survival on RRT was explained by demographic factors and by comorbidity

Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning

Retinopathy of prematurity (ROP) is a disease that affects premature infants, where abnormal growth of the retinal blood vessels can lead to blindness unless treated accordingly. Infants considered at risk of severe ROP are monitored for symptoms of plus disease, characterized by arterial tortuosity and venous dilation at the posterior pole, with a standard photographic definition. Disagreement among ROP experts in diagnosing plus disease has driven the development of computer-based methods that classify images based on hand-crafted features extracted from the vasculature. However, most of these approaches are semi-automated, which are time-consuming and subject to variability. In contrast, deep learning is a fully automated approach that has shown great promise in a wide variety of domains, including medical genetics, informatics and imaging. Convolutional neural networks (CNNs) are deep networks which learn rich representations of disease features that are highly robust to variations in acquisition and image quality. In this study, we utilized a U-Net architecture to perform vessel segmentation and then a GoogLeNet to perform disease classification. The classifier was trained on 3,000 retinal images and validated on an independent test set of patients with different observed progressions and treatments. We show that our fully automated algorithm can be used to monitor the progression of plus disease over multiple patient visits with results that are consistent with the experts’ consensus diagnosis. Future work will aim to further validate the method on larger cohorts of patients to assess its applicability within the clinic as a treatment monitoring tool

How Does CMB + BBN Constrain New Physics?

Recent cosmic microwave background (CMB) results from BOOMERANG, MAXIMA, and DASI provide cosmological constraints on new physics that can be competitive with those derived from Big Bang Nucleosynthesis (BBN). In particular, both CMB and BBN can be used to place limits on models involving neutrino degeneracy and additional relativistic degrees of freedom. However, for the case of the CMB, these constraints are, in general, sensitive to the assumed priors. We examine the CMB and BBN constraints on such models and study the sensitivity of ``new physics" to the assumed priors. If we add a constraint on the age of the universe (t_0 \ga 11 Gyr), then for models with a cosmological constant, the range of baryon densities and neutrino degeneracy parameters allowed by the CMB and BBN is fairly robust: $\eta_{10} = 6.0 \pm 0.6$, \deln \la 6, \xi_e \la 0.3. In the absence of new physics, models without a cosmological constant are only marginally compatible with recent CMB observations (excluded at the 93% confidence level).Comment: 6 pages, 5 figures; version to appear in Phys. Rev.

Gate-defined quantum confinement in InSe-based van der Waals heterostructures

Indium selenide, a post-transition metal chalcogenide, is a novel two-dimensional (2D) semiconductor with interesting electronic properties. Its tunable band gap and high electron mobility have already attracted considerable research interest. Here we demonstrate strong quantum confinement and manipulation of single electrons in devices made from few-layer crystals of InSe using electrostatic gating. We report on gate-controlled quantum dots in the Coulomb blockade regime as well as one-dimensional quantization in point contacts, revealing multiple plateaus. The work represents an important milestone in the development of quality devices based on 2D materials and makes InSe a prime candidate for relevant electronic and optoelectronic applications