On the determination of diffusion coefficients in two-component alloys and doped semiconductors: several implications concerning the International Space Station

The accurate determination of mass diffusion coefficients is a technologically relevant problem that has implications on the modelling and control of material processes such as crystal growth and casting. It is also important in the validation of different theories of atomic diffusion. The experimental determination of these coefficients, when there is a liquid phase, is difficult due to the unavoidable presence of buoyancy driven convection currents that enhance mass transport and disturb diffusion measurements. To minimize as much as possible these problems, long capillaries are used in order to confine the fluid and reduce the intensity of the convective motions. These measurements have also been done in reduced gravity environments, but the residual gravity may still be able to induce buoyancy driven convection motions. The aim of our work is to analyze the impact of low solutal Rayleigh number environments on the accuracy of the interdiffusion coefficient measurements using long capillaries. In the present study we deal with two liquid systems; photovoltaic silicon and Al-based liquid binary alloys at high temperature. We have numerically simulated two different experimental techniques used to determine the diffusion coefficients; the shear cell and the long capillary techniques. We also consider the effect of rotating the cylindrical cell along their axis as a mechanism to reduce axial convective transport even in Earth laboratories. Finally, we use typical accelerometric signals from the International Space Station (ISS) in the quasi-steady range of frequencies. The signals concentrate on typical station reboosts because the accelerometric level of the rest of potentially dangerous disturbances - dockings, undockings and Extra Vehicular Activities, EVAs - is considerably lower.Peer ReviewedPostprint (author's final draft

Critical packing in granular shear bands

In a realistic three-dimensional setup, we simulate the slow deformation of idealized granular media composed of spheres undergoing an axisymmetric triaxial shear test. We follow the self-organization of the spontaneous strain localization process leading to a shear band and demonstrate the existence of a critical packing density inside this failure zone. The asymptotic criticality arising from the dynamic equilibrium of dilation and compaction is found to be restricted to the shear band, while the density outside of it keeps the memory of the initial packing. The critical density of the shear band depends on friction (and grain geometry) and in the limit of infinite friction it defines a specific packing state, namely the \emph{dynamic random loose packing}

Order-of-magnitude speedup for steady states and traveling waves via Stokes preconditioning in Channelflow and Openpipeflow

Steady states and traveling waves play a fundamental role in understanding hydrodynamic problems. Even when unstable, these states provide the bifurcation-theoretic explanation for the origin of the observed states. In turbulent wall-bounded shear flows, these states have been hypothesized to be saddle points organizing the trajectories within a chaotic attractor. These states must be computed with Newton's method or one of its generalizations, since time-integration cannot converge to unstable equilibria. The bottleneck is the solution of linear systems involving the Jacobian of the Navier-Stokes or Boussinesq equations. Originally such computations were carried out by constructing and directly inverting the Jacobian, but this is unfeasible for the matrices arising from three-dimensional hydrodynamic configurations in large domains. A popular method is to seek states that are invariant under numerical time integration. Surprisingly, equilibria may also be found by seeking flows that are invariant under a single very large Backwards-Euler Forwards-Euler timestep. We show that this method, called Stokes preconditioning, is 10 to 50 times faster at computing steady states in plane Couette flow and traveling waves in pipe flow. Moreover, it can be carried out using Channelflow (by Gibson) and Openpipeflow (by Willis) without any changes to these popular spectral codes. We explain the convergence rate as a function of the integration period and Reynolds number by computing the full spectra of the operators corresponding to the Jacobians of both methods.Comment: in Computational Modelling of Bifurcations and Instabilities in Fluid Dynamics, ed. Alexander Gelfgat (Springer, 2018

A new approach to comprehensively evaluate the morphological properties of the human femoral head : example of application to osteoarthritic joint

Osteoarthritis affects the morphological properties of the femoral head. The goal of this study was to develop a method to elucidate whether these changes are localised to discrete regions, or if the reported trends in microstructural changes may be identified throughout the subchondral bone of the human femoral head. Whole femoral heads extracted from osteoarthritic (n = 5) and healthy controls (n = 5) underwent microCT imaging 39 μm voxel size. The subchondral bone plate was virtually isolated to evaluate the plate thickness and plate porosity. The trabecular bone region was divided into 37 volumes of interest spatially distributed in the femoral head, and bone morphometric properties were determined in each region. The study showed how the developed approach can be used to study the heterogeneous properties of the human femoral head affected by a disease such as osteoarthritis. As example, in the superior femoral head osteoarthritic specimens exhibited a more heterogeneous micro-architecture, with trends towards thicker cortical bone plate, higher trabecular connectivity density, higher trabecular bone density and thicker structures, something that could only be observed with the newly developed approach. Bone cysts were mostly confined to the postero-lateral quadrants extending from the subchondral region into the mid trabecular region. Nevertheless, in order to generalise these findings, a larger sample size should be analysed in the future. This novel method allowed a comprehensive evaluation of the heterogeneous micro-architectural properties of the human femoral head, highlighting effects of OA in the superior subchondral cortical and trabecular bone. Further investigations on different stages of OA would be needed to identify early changes in the bone

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Reconstruction versus conservative treatment after rupture of the anterior cruciate ligament: cost effectiveness analysis

BACKGROUND: The decision whether to treat conservatively or reconstruct surgically a torn anterior cruciate ligament (ACL) is an ongoing subject of debate. The high prevalence and associated public health burden of torn ACL has led to continuous efforts to determine the best therapeutic approach. A critical evaluation of benefits and expenditures of both treatment options as in a cost effectiveness analysis seems well-suited to provide valuable information for treating physicians and healthcare policymakers. METHODS: A literature review identified four of 7410 searched articles providing sufficient outcome probabilities for the two treatment options for modeling. A transformation key based on the expert opinions of 25 orthopedic surgeons was used to derive utilities from available evidence. The cost data for both treatment strategies were based on average figures compiled by Orthopaedic University Hospital Balgrist and reinforced by Swiss national statistics. A decision tree was constructed to derive the cost-effectiveness of each strategy, which was then tested for robustness using Monte Carlo simulation. RESULTS: Decision tree analysis revealed a cost effectiveness of 16,038 USD/0.78 QALY for ACL reconstruction and 15,466 USD/0.66 QALY for conservative treatment, implying an incremental cost effectiveness of 4,890 USD/QALY for ACL reconstruction. Sensitivity analysis of utilities did not change the trend. CONCLUSION: ACL reconstruction for reestablishment of knee stability seems cost effective in the Swiss setting based on currently available evidence. This, however, should be reinforced with randomized controlled trials comparing the two treatment strategies

A new era for understanding amyloid structures and disease

The aggregation of proteins into amyloid fibrils and their deposition into plaques and intracellular inclusions is the hallmark of amyloid disease. The accumulation and deposition of amyloid fibrils, collectively known as amyloidosis, is associated with many pathological conditions that can be associated with ageing, such as Alzheimer disease, Parkinson disease, type II diabetes and dialysis-related amyloidosis. However, elucidation of the atomic structure of amyloid fibrils formed from their intact protein precursors and how fibril formation relates to disease has remained elusive. Recent advances in structural biology techniques, including cryo-electron microscopy and solid-state NMR spectroscopy, have finally broken this impasse. The first near-atomic-resolution structures of amyloid fibrils formed in vitro, seeded from plaque material and analysed directly ex vivo are now available. The results reveal cross-β structures that are far more intricate than anticipated. Here, we describe these structures, highlighting their similarities and differences, and the basis for their toxicity. We discuss how amyloid structure may affect the ability of fibrils to spread to different sites in the cell and between organisms in a prion-like manner, along with their roles in disease. These molecular insights will aid in understanding the development and spread of amyloid diseases and are inspiring new strategies for therapeutic intervention

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment. Tumor-infiltrating lymphocytes (TILs) were identified from standard pathology cancer images by a deep-learning-derived \u201ccomputational stain\u201d developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles