The Founders Go On-Line: An Original Intent Solution to a Jurisdictional Dilemma

The Internet has created a blossoming cyber-economy and a new way of conducting business. Unfortunately for those looking for jurisdictional certainty, however, cyberspace also effectively eliminates geographic boundaries. The unprecedented circumstances set by this new frontier have put federal courts in the unenviable position of deciding whether Internet-based cases meet diversity jurisdiction requirements. Examining the constitutional history and recent use of diversity, this Note argues that the Founders did not foresee an era where every contract or sales case would end up in federal court; rather, they intended diversity jurisdiction to be a rare and perhaps temporary proposition. The author argues that the potential of Internet-based contacts to throw a large number of cases into federal court could overburden the federal system. This Note suggests that the solution to this problem lies in courts following the Founder\u27s intent

Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks

Purpose: We developed a method to automatically locate and quantify graft detachment after Descemet's Membrane Endothelial Keratoplasty (DMEK) in Anterior Segment Optical Coherence Tomography (AS-OCT) scans. Methods: 1280 AS-OCT B-scans were annotated by a DMEK expert. Using the annotations, a deep learning pipeline was developed to localize scleral spur, center the AS-OCT B-scans and segment the detached graft sections. Detachment segmentation model performance was evaluated per B-scan by comparing (1) length of detachment and (2) horizontal projection of the detached sections with the expert annotations. Horizontal projections were used to construct graft detachment maps. All final evaluations were done on a test set that was set apart during training of the models. A second DMEK expert annotated the test set to determine inter-rater performance. Results: Mean scleral spur localization error was 0.155 mm, whereas the inter-rater difference was 0.090 mm. The estimated graft detachment lengths were in 69% of the cases within a 10-pixel (~150{\mu}m) difference from the ground truth (77% for the second DMEK expert). Dice scores for the horizontal projections of all B-scans with detachments were 0.896 and 0.880 for our model and the second DMEK expert respectively. Conclusion: Our deep learning model can be used to automatically and instantly localize graft detachment in AS-OCT B-scans. Horizontal detachment projections can be determined with the same accuracy as a human DMEK expert, allowing for the construction of accurate graft detachment maps. Translational Relevance: Automated localization and quantification of graft detachment can support DMEK research and standardize clinical decision making.Comment: To be published in Translational Vision Science & Technolog

Giant Josephson current through a single bound state in a superconducting tunnel junction

We study the microscopic structure of the Josephson current in a single-mode tunnel junction with a wide quasiclassical tunnel barrier. In such a junction each Andreev bound state carries a current of magnitude proportional to the {\em amplitude} of the normal electron transmission through the junction. Tremendous enhancement of the bound state current is caused by the resonance coupling of superconducting bound states at both superconductor-insulator interfaces of the junction. The possibility of experimental observation of the single bound state current is discussed.Comment: 11 pages, [aps,preprint]{revtex

Corneal Pachymetry by AS-OCT after Descemet's Membrane Endothelial Keratoplasty

Corneal thickness (pachymetry) maps can be used to monitor restoration of corneal endothelial function, for example after Descemet's membrane endothelial keratoplasty (DMEK). Automated delineation of the corneal interfaces in anterior segment optical coherence tomography (AS-OCT) can be challenging for corneas that are irregularly shaped due to pathology, or as a consequence of surgery, leading to incorrect thickness measurements. In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans. Three different deep learning strategies were developed based on 960 B-scans from 50 patients. On an independent test set of 320 B-scans, corneal thickness could be measured with an error of 13.98 to 15.50 micrometer for the central 9 mm range, which is less than 3% of the average corneal thickness. The accurate thickness measurements were used to construct detailed pachymetry maps. Moreover, follow-up scans could be registered based on anatomical landmarks to obtain differential pachymetry maps. These maps may enable a more comprehensive understanding of the restoration of the endothelial function after DMEK, where thickness often varies throughout different regions of the cornea, and subsequently contribute to a standardized postoperative regime.Comment: Fixed typo in abstract: The development set consists of 960 B-scans from 50 patients (instead of 68). The B-scans from the other 18 patients were used for testing onl

Spin-Imbalance and Magnetoresistance in Ferromagnet/Superconductor/Ferromagnet Double Tunnel Junctions

We theoretically study the spin-dependent transport in a ferromagnet/super- conductor/ferromagnet double tunnel junction. The tunneling current in the antiferromagnetic alignment of the magnetizations gives rise to a spin imbalance in the superconductor. The resulting nonequilibrium spin density strongly suppresses the superconductivity with increase of bias voltage and destroys it at a critical voltage Vc. The results provide a new method not only for measuring the spin polarization of ferromagnets but also for controlling superconductivity and tunnel magnetoresistance (TMR) by applying the bias voltage.Comment: 4pages, to be published in Phys. Rev. Let

Current and Spin-Torque in Double Tunnel Barrier Ferromagnet - Superconductor - Ferromagnet Systems

We calculate the current and the spin-torque in small symmetric double tunnel barrier ferromagnet - superconductor - ferromagnet (F-S-F) systems. Spin-accumulation on the superconductor governs the transport properties when the spin-flip relaxation time is longer than the transport dwell time. In the elastic transport regime, it is demonstrated that the relative change in the current (spin-torque) for F-S-F systems equals the relative change in the current (spin-torque) for F-N-F systems upon changing the relative magnetization direction of the two ferromagnets. This differs from the results in the inelastic transport regime where spin-accumulation suppresses the superconducting gap and dramatically changes the magnetoresistance [S. Takahashi, H. Imamura, and S. Maekawa, Phys. Rev. Lett. 82, 3911 (1999)]. The experimental relevance of the elastic and inelastic transport regimes, respectively, as well as the reasons for the change in the transport properties are discussed.Comment: 7 page

Self-consistent scattering description of transport in normal-superconductor structures

We present a scattering description of transport in several normal-superconductor structures. We show that the related requirements of self-consistency and current conservation introduce qualitative changes in the transport behavior when the current in the superconductor is not negligible. The energy thresholds for quasiparticle propagation in the superconductor are sensitive to the existence of condensate flow ($v_s\neq 0$). This dependence is responsible for a rich variety of transport regimes, including a voltage range in which only Andreev transmission is possible at the interfaces, and a state of gapless superconductivity which may survive up to high voltages if temperature is low. The two main effects of current conservation are a shift towards lower voltages of the first peak in the differential conductance and an enhancement of current caused by the greater availability of charge transmitting scattering channels.Comment: 31 pages, 10 PS figures, Latex file, psfig.sty file is added. To appear in Phys. Rev. B (Jan 97

First-principles study of nucleation, growth, and interface structure of Fe/GaAs

We use density-functional theory to describe the initial stages of Fe film growth on GaAs(001), focusing on the interplay between chemistry and magnetism at the interface. Four features appear to be generic: (1) At submonolayer coverages, a strong chemical interaction between Fe and substrate atoms leads to substitutional adsorption and intermixing. (2) For films of several monolayers and more, atomically abrupt interfaces are energetically favored. (3) For Fe films over a range of thicknesses, both Ga- and As-adlayers dramatically reduce the formation energies of the films, suggesting a surfactant-like action. (4) During the first few monolayers of growth, Ga or As atoms are likely to be liberated from the interface and diffuse to the Fe film surface. Magnetism plays an important auxiliary role for these processes, even in the dilute limit of atomic adsorption. Most of the films exhibit ferromagnetic order even at half-monolayer coverage, while certain adlayer-capped films show a slight preference for antiferromagnetic order.Comment: 11 two-column pages, 12 figures, to appear in Phys. Rev.

Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study

Type 2 Diabetes (T2D) is a chronic metabolic disorder that can lead to blindness and cardiovascular disease. Information about early stage T2D might be present in retinal fundus images, but to what extent these images can be used for a screening setting is still unknown. In this study, deep neural networks were employed to differentiate between fundus images from individuals with and without T2D. We investigated three methods to achieve high classification performance, measured by the area under the receiver operating curve (ROC-AUC). A multi-target learning approach to simultaneously output retinal biomarkers as well as T2D works best (AUC = 0.746 [$\pm$0.001]). Furthermore, the classification performance can be improved when images with high prediction uncertainty are referred to a specialist. We also show that the combination of images of the left and right eye per individual can further improve the classification performance (AUC = 0.758 [$\pm$0.003]), using a simple averaging approach. The results are promising, suggesting the feasibility of screening for T2D from retinal fundus images.Comment: to be published in the proceeding of SPIE - Medical Imaging 2020, 6 pages, 1 figur