Mechanisms of Spontaneous Current Generation in an Inhomogeneous d-Wave Superconductor

A boundary between two d-wave superconductors or an s-wave and a d-wave superconductor generally breaks time-reversal symmetry and can generate spontaneous currents due to proximity effect. On the other hand, surfaces and interfaces in d-wave superconductors can produce localized current-carrying states by supporting the T-breaking combination of dominant and subdominant order parameters. We investigate spontaneous currents in the presence of both mechanisms and show that at low temperature, counter-intuitively, the subdominant coupling decreases the amplitude of the spontaneous current due to proximity effect. Superscreening of spontaneous currents is demonstrated to be present in any d-d (but not s-d) junction and surface with d+id' order parameter symmetry. We show that this supercreening is the result of contributions from the local magnetic moment of the condensate to the spontaneous current.Comment: 4 pages, 5 figures, RevTe

The Analysis of the Prevalence of Diabetes in the Third Age in a Northeast State Between the Years From 2002 To 2013

Diabetes potentiates when the body can not control the amount of glucose (sugar) in the blood. This disease develops when the body does not produce enough amounts of the hormone called insulin. The elderly are more fragile in not producing adequate insulin for their proper functioning, since the prevalence is related to aging, sedentary lifestyle and obesity, and these last two factors, in turn, intensify with the advancing age. The decompensated glycemia accentuates frequent difficulties in this phase of life. It can incapacitate the elderly because it increases the risk of dementias such as Alzheimer’s, in addition to diabetic neuropathy, which causes the elderly to lose firmness on the floor, the use of many medications and other problems that impact the quality of life and increase the risk of death

Project Proof: Internet Enabled Process Reengineering at J.D. Edwards & Company

J.D. Edwards is a provider of the new generation of ERP and collaborative commerce solutions. This case study describes the challenges faced internally by the company to upgrade to the latest enterprise software it would sell to the world. Dubbed Project PROOF, the project started in June 2001 and was completed in November 2002. The perspectives of the CIO, the program manager, and other key personnel are presented. The case study highlights the issues that arise in an enterprise software implementation project. In addition, the case touches upon issues of project management, process redesign, and marketing. The case study uses a multimedia format to add richness and detail. Although J.D. Edwards was acquired in 2003, the issues discussed are relevant to current business practices

Unifying inflation with dark energy in modified F(R) Horava-Lifshitz gravity

We study FRW cosmology for a non-linear modified F(R) Horava-Lifshitz gravity which has a viable convenient counterpart. A unified description of early-time inflation and late-time acceleration is possible in this theory, but the cosmological dynamic details are generically different from the ones of the convenient viable F(R) model. Remarkably, for some specific choice of parameters they do coincide. The emergence of finite-time future singularities is investigated in detail. It is shown that these singularities can be cured by adding an extra, higher-derivative term, which turns out to be qualitatively different when compared with the corresponding one of the convenient F(R) theory.Comment: LaTeX 12 pages, typos are correcte

The COMPASS Experiment at CERN

The COMPASS experiment makes use of the CERN SPS high-intensitymuon and hadron beams for the investigation of the nucleon spin structure and the spectroscopy of hadrons. One or more outgoing particles are detected in coincidence with the incoming muon or hadron. A large polarized target inside a superconducting solenoid is used for the measurements with the muon beam. Outgoing particles are detected by a two-stage, large angle and large momentum range spectrometer. The setup is built using several types of tracking detectors, according to the expected incident rate, required space resolution and the solid angle to be covered. Particle identification is achieved using a RICH counter and both hadron and electromagnetic calorimeters. The setup has been successfully operated from 2002 onwards using a muon beam. Data with a hadron beam were also collected in 2004. This article describes the main features and performances of the spectrometer in 2004; a short summary of the 2006 upgrade is also given.Comment: 84 papes, 74 figure

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function