Core pinning by intragranular nanoprecipitates in polycrystalline MgCNi_3

The nanostructure and magnetic properties of polycrystalline MgCNi_3 were studied by x-ray diffraction, electron microscopy, and vibrating sample magnetometry. While the bulk flux-pinning force curve F_p(H) indicates the expected grain-boundary pinning mechanism just below T_c = 7.2 K, a systematic change to pinning by a nanometer-scale distribution of core pinning sites is indicated by a shift of F_p(H) with decreasing temperature. The lack of scaling of F_p(H) suggests the presence of 10 to 20% of nonsuperconducting regions inside the grains, which are smaller than the diameter of fluxon cores 2xi at high temperature and become effective with decreasing temperature when xi(T) approaches the nanostructural scale. Transmission electron microscopy revealed cubic and graphite nanoprecipitates with 2 to 5 nm size, consistent with the above hypothesis since xi(0) = 6 nm. High critical current densities, more than 10^6 A/cm^2 at 1 T and 4.2 K, were obtained for grain colonies separated by carbon. Dirty-limit behavior seen in previous studies may be tied to electron scattering by the precipitates, indicating the possibility that strong core pinning might be combined with a technologically useful upper critical field if versions of MgCNi_3 with higher T_c can be found.Comment: 5 pages, 6 figures, submitted to PR

A Novel Approach for Ellipsoidal Outer-Approximation of the Intersection Region of Ellipses in the Plane

In this paper, a novel technique for tight outer-approximation of the intersection region of a finite number of ellipses in 2-dimensional (2D) space is proposed. First, the vertices of a tight polygon that contains the convex intersection of the ellipses are found in an efficient manner. To do so, the intersection points of the ellipses that fall on the boundary of the intersection region are determined, and a set of points is generated on the elliptic arcs connecting every two neighbouring intersection points. By finding the tangent lines to the ellipses at the extended set of points, a set of half-planes is obtained, whose intersection forms a polygon. To find the polygon more efficiently, the points are given an order and the intersection of the half-planes corresponding to every two neighbouring points is calculated. If the polygon is convex and bounded, these calculated points together with the initially obtained intersection points will form its vertices. If the polygon is non-convex or unbounded, we can detect this situation and then generate additional discrete points only on the elliptical arc segment causing the issue, and restart the algorithm to obtain a bounded and convex polygon. Finally, the smallest area ellipse that contains the vertices of the polygon is obtained by solving a convex optimization problem. Through numerical experiments, it is illustrated that the proposed technique returns a tighter outer-approximation of the intersection of multiple ellipses, compared to conventional techniques, with only slightly higher computational cost

Brief of Corporate Law Professors as Amici Curie in Support of Respondents

The Supreme Court has looked to the rights of corporate shareholders in determining the rights of union members and non-members to control political spending, and vice versa. The Court sometimes assumes that if shareholders disapprove of corporate political expression, they can easily sell their shares or exercise control over corporate spending. This assumption is mistaken. Because of how capital is saved and invested, most individual shareholders cannot obtain full information about corporate political activities, even after the fact, nor can they prevent their savings from being used to speak in ways with which they disagree. Individual shareholders have no “opt out” rights or practical ability to avoid subsidizing corporate political expression with which they disagree. Nor do individuals have the practical option to refrain from putting their savings into equity investments, as doing so would impose damaging economic penalties and ignore conventional financial guidance for individual investors

The effect of tumour necrosis factor-α (TNF-α) muteins on human neutrophils in vitro

Tumour necrosis factor-α (TNF-α) has been implicated as an important inflammatory mediator. In vitro, TNF-α is reported to activate human polymorphonuclear neutrophils (PMN), inducing responses such as phagocytic activity, degranulation and oxidative metabolism. Biological responses to TNF-α are initiated by its binding to specific cell surface receptors, and various studies have shown that the major TNF receptor species on PMN is the 75 kDa receptor. To verify the suggestion that the receptor binding domain includes the region close to the N-terminus of the TNF-α molecule, four TNF-α derivatives termed muteins were constructed, using a synthetic cDNA fragment substituting the N-terminal 3–7 selected hydrophilic or hydrophobic amino acids in the original TNF-α genomic DNA. Binding of muteins to PMN was assessed using monoclonal antibodies recognizing either the 55 kDa (p55) or the 75 kDa (p75) TNF receptor subtypes. Blocking by muteins of anti-p75 antibody binding to PMN was as expected from their N-terminal amino acid composition and hydrophilic properties. Hydrophilic muteins competed well with anti-TNF receptor antibodies for binding to the p75 receptor. In contrast, hydrophobic muteins were unable to block anti-p75 binding. Similarly, degranulation, chemiluminescence or enhancement of the PMN response to specific stimuli by the muteins correlated with the hydrophilic properties of the muteins. The significance of these observations in relation to the molecular structure of TNF-α is discussed

Future aspects of renal transplantation

New and exciting advances in renal transplantation are continuously being made, and the horizons for organ transplantation are bright and open. This article reviews only a few of the newer advances that will allow renal transplantation to become even more widespread and successful. The important and exciting implications for extrarenal organ transplantation are immediately evident. © 1988 Springer-Verlag

On the construction of high-order force gradient algorithms for integration of motion in classical and quantum systems

A consequent approach is proposed to construct symplectic force-gradient algorithms of arbitrarily high orders in the time step for precise integration of motion in classical and quantum mechanics simulations. Within this approach the basic algorithms are first derived up to the eighth order by direct decompositions of exponential propagators and further collected using an advanced composition scheme to obtain the algorithms of higher orders. Contrary to the scheme by Chin and Kidwell [Phys. Rev. E 62, 8746 (2000)], where high-order algorithms are introduced by standard iterations of a force-gradient integrator of order four, the present method allows to reduce the total number of expensive force and its gradient evaluations to a minimum. At the same time, the precision of the integration increases significantly, especially with increasing the order of the generated schemes. The algorithms are tested in molecular dynamics and celestial mechanics simulations. It is shown, in particular, that the efficiency of the new fourth-order-based algorithms is better approximately in factors 5 to 1000 for orders 4 to 12, respectively. The results corresponding to sixth- and eighth-order-based composition schemes are also presented up to the sixteenth order. For orders 14 and 16, such highly precise schemes, at considerably smaller computational costs, allow to reduce unphysical deviations in the total energy up in 100 000 times with respect to those of the standard fourth-order-based iteration approach.Comment: 23 pages, 2 figures; submitted to Phys. Rev.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective