L-H transition dynamics in fluid turbulence simulations with neoclassical force balance

Spontaneous transport barrier generation at the edge of a magnetically confined plasma is investigated. To this end, a model of electrostatic turbulence in three-dimensional geometry is extended to account for the impact of friction between trapped and passing particles on the radial electric field. Non-linear flux-driven simulations are carried out, and it is shown that considering the radial and temporal variations of the neoclassical friction coefficients allows for a transport barrier to be generated above a threshold of the input power

INNOVATION AND NATIONAL BROADBAND POLICIES: FACTS, FICTION AND UNANSWERED QUESTIONS IN THE NET NEUTRALITY DEBATE

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Distal motor latency and residuallatency as sensitive markersof anti-MAG polyneuropathy

Abstract.: There is debate whether the terminal latency index (TLI) is a sensitive marker for polyneuropathy with anti-myelinassociated-glycoprotein antibodies (anti-MAGP). We examined 6 patients with an anti-MAGP and 6 patients with a chronic inflammatory demyelinating polyneuropathy (CIDP). The electroneurographic features studied were: distal compound motor action potential (CMAP), distal motor latency (DML), motor conduction velocity (MCV) elbow to wrist (distal MCV), MCV axilla to elbow (proximal MCV), MCV distal/proximal, terminal latency index (TLI), residual latency (RL), F-wave, and modified F ratio.We found significant differences between anti-MAGP and CIDP for DML and for RL.No significant differences were found for TLI and the other measures. The TLI values were not significant probably because our patients had a longer duration of disease,which supports the hypothesis of a distal to proximal progression of conduction slowing over time. We propose that a residual latency >4.0 and a distal motor latency >7.0 are strongly suggestive for an anti- MAG

Non-substitutional single-atom defects in the Ge_(1-x)Sn_x alloy

Ge_(1-x)Sn_x alloys have proved difficult to form at large x, contrary to what happens with other group IV semiconductor combinations. However, at low x they are typical examples of well-behaved substitutional compounds, which is desirable for harnessing the electronic properties of narrow band semiconductors. In this paper, we propose the appearance of another kind of single-site defect ($\beta-Sn$), consisting of a single Sn atom in the center of a Ge divacancy, that may account for these facts. Accordingly, we examine the electronic and structural properties of these alloys by performing extensive numerical ab-initio calculations around local defects. The results show that the environment of the $\beta$ defect relaxes towards a cubic octahedral configuration, facilitating the nucleation of metallic white tin and its segregation, as found in amorphous samples. Using the information stemming from these local defect calculations, we built a simple statistical model to investigate at which concentration these $\beta$ defects can be formed in thermal equilibrium. These results agree remarkably well with experimental findings, concerning the critical concentration above which the homogeneous alloys cannot be formed at room temperature. Our model also predicts the observed fact that at lower temperature the critical concentration increases. We also performed single site effective-field calculations of the electronic structure, which further support our hypothesis.Comment: 12 pages, 1 table, 16 figure

A designed and potentially decadentate ligand for use in lanthanide(III) catalysed biomass transformations: targeting diastereoselective trans-4,5-diaminocyclopentenone derivatives

The goal of this study was to design a ligand system which can accommodate single lanthanide(III)-ions and investigate the properties of the resulting complexes. The complexes of all the accesible lanthanides and yttrium with the new ligand LH6 = N,N′-dimethyl-N,N′-ethylene-bis(5-bromo-3-(1H-benzimidazol-2-yl)hydrazineylidene)-2-hydroxybenzylamine) were obtained in high yield at room temperature under aerobic reaction conditions. The corresponding compounds were characterised using X-ray diffraction, FT-IR, elemental analysis and the optical properties of all complexes were investigated using UV-vis and fluorescence spectroscopy. The air stable complexes efficiently transform biomass furfural to trans-4,5-cyclopentenones in high yield

Comparative effectiveness of total population versus disease-specific neural network models in predicting medical costs

The objective of this research was to compare the accuracy of two types of neural networks in identifying individuals at risk for high medical costs for three chronic conditions. Two neural network models—a population model and three disease-specific models—were compared regarding effectiveness predicting high costs. Subjects included 33,908 health plan members with diabetes, 19,264 with asthma, and 2,605 with cardiac conditions. For model development/testing, only members with 24 months of continuous enrollment were included. Models were developed to predict probability of high costs in 2000 (top 15% of distribution) based on 1999 claims factors. After validation, models were applied to 2000 claims factors to predict probability of high 2001 costs. Each member received two scores—population model score applied to cohort and disease model score. Receiver Operating Characteristic (ROC) curves compared sensitivity, specificity, and total performance of population model and three disease models. Diabetes-specific model accuracy, C = 0.786 (95%CI = 0.779–0.794), was greater than that of population model applied to diabetic cohort, C = 0.767 (0.759–0.775). Asthma-specific model accuracy, C = 0.835 (0.825–0.844), was no different from that of population model applied to asthma cohort, C = 0.844 (0.835–0.853). Cardiac-specific model accuracy, C = 0.651 (0.620–0.683), was lower than that of population model applied to cardiac cohort, C = 0.726 (0.697–0.756). The population model predictive power, compared to the disease model predictive power, varied by disease; in general, the larger the cohort, the greater the advantage in predictive power of the disease model compared to the population model. Given these findings, disease management program staff should test multiple approaches before implementing predictive models. (Disease Management 2005;8:277–287