1,833 research outputs found
Upscaling of dislocation walls in finite domains
We wish to understand the macroscopic plastic behaviour of metals by
upscaling the micro-mechanics of dislocations. We consider a highly simplified
dislocation network, which allows our microscopic model to be a one dimensional
particle system, in which the interactions between the particles (dislocation
walls) are singular and non-local.
As a first step towards treating realistic geometries, we focus on
finite-size effects rather than considering an infinite domain as typically
discussed in the literature. We derive effective equations for the dislocation
density by means of \Gamma-convergence on the space of probability measures.
Our analysis yields a classification of macroscopic models, in which the size
of the domain plays a key role
Dynamics of screw dislocations: a generalised minimising-movements scheme approach
The gradient flow structure of the model introduced in [CG99] for the
dynamics of screw dislocations is investigated by means of a generalised
minimising-movements scheme approach. The assumption of a finite number of
available glide directions, together with the "maximal dissipation criterion"
that governs the equations of motion, results into solving a differential
inclusion rather than an ODE. This paper addresses how the model in [CG99] is
connected to a time-discrete evolution scheme which explicitly confines
dislocations to move each time step along a single glide direction. It is
proved that the time-continuous model in [CG99] is the limit of these
time-discrete minimising-movement schemes when the time step converges to 0.
The study presented here is a first step towards a generalisation of the
setting in [AGS08, Chap. 2 and 3] that allows for dissipations which cannot be
described by a metric.Comment: 17 pages, 2 figures http://cvgmt.sns.it/paper/2781
Discrete-to-continuum convergence of charged particles in 1D with annihilation
We consider a system of charged particles moving on the real line driven by
electrostatic interactions. Since we consider charges of both signs, collisions
might occur in finite time. Upon collision, some of the colliding particles are
effectively removed from the system (annihilation). The two applications we
have in mind are vortices and dislocations in metals.
In this paper we reach two goals. First, we develop a rigorous solution
concept for the interacting particle system with annihilation. The main
innovation here is to provide a careful management of the annihilation of
groups of more than two particles, and we show that the definition is
consistent by proving existence, uniqueness, and continuous dependence on
initial data. The proof relies on a detailed analysis of ODE trajectories close
to collision, and a reparametrization of vectors in terms of the moments of
their elements.
Secondly, we pass to the many-particle limit (discrete-to-continuum), and
recover the expected limiting equation for the particle density. Due to the
singular interactions and the annihilation rule, standard proof techniques of
discrete-to-continuum limits do not apply. In particular, the framework of
measures seems unfit. Instead, we use the one-dimensional feature that both the
particle system and the limiting PDE can be characterized in terms of
Hamilton--Jacobi equations. While our proof follows a standard limit procedure
for such equations, the novelty with respect to existing results lies in
allowing for stronger singularities in the particle system by exploiting the
freedom of choice in the definition of viscosity solutions.Comment: 51 page
Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data
Knee osteoarthritis (OA) is the most common musculoskeletal disease without a
cure, and current treatment options are limited to symptomatic relief.
Prediction of OA progression is a very challenging and timely issue, and it
could, if resolved, accelerate the disease modifying drug development and
ultimately help to prevent millions of total joint replacement surgeries
performed annually. Here, we present a multi-modal machine learning-based OA
progression prediction model that utilizes raw radiographic data, clinical
examination results and previous medical history of the patient. We validated
this approach on an independent test set of 3,918 knee images from 2,129
subjects. Our method yielded area under the ROC curve (AUC) of 0.79 (0.78-0.81)
and Average Precision (AP) of 0.68 (0.66-0.70). In contrast, a reference
approach, based on logistic regression, yielded AUC of 0.75 (0.74-0.77) and AP
of 0.62 (0.60-0.64). The proposed method could significantly improve the
subject selection process for OA drug-development trials and help the
development of personalized therapeutic plans
Stabilizing Fluid-Fluid Displacements in Porous Media Through Wettability Alteration
We study experimentally how wettability impacts fluid-fluid-displacement patterns in granular media. We inject a low-viscosity fluid (air) into a thin bed of glass beads initially saturated with a more-viscous fluid (a water-glycerol mixture). Chemical treatment of glass surfaces allows us to control the wetting properties of the medium and modify the contact angle θ from 5° (drainage) to 120° (imbibition). We demonstrate that wettability exerts a powerful influence on the invasion morphology of unfavorable mobility displacements: increasing θ stabilizes fluid invasion into the granular pack at all capillary numbers. In particular, we report the striking observation of a stable radial displacement at low capillary numbers, whose origin lies on the cooperative nature of fluid invasion at the pore scale.Eni S.p.A. (Firm)ARCO Chair in Energy Studie
Renal microvascular endothelial cell responses in sepsis-induced acute kidney injury
Endothelial cells in the kidney microvasculature have an intrinsic molecular and phenotypic heterogeneity and respond to sepsis-induced acute kidney injury conditions in a segment-specific manner. This Review discusses the roles of these cells and the molecular systems that control endothelial functions in the development of sepsis-induced acute kidney injury. Microvascular endothelial cells in the kidney have been a neglected cell type in sepsis-induced acute kidney injury (sepsis-AKI) research; yet, they offer tremendous potential as pharmacological targets. As endothelial cells in distinct cortical microvascular segments are highly heterogeneous, this Review focuses on endothelial cells in their anatomical niche. In animal models of sepsis-AKI, reduced glomerular blood flow has been attributed to inhibition of endothelial nitric oxide synthase activation in arterioles and glomeruli, whereas decreased cortex peritubular capillary perfusion is associated with epithelial redox stress. Elevated systemic levels of vascular endothelial growth factor, reduced levels of circulating sphingosine 1-phosphate and loss of components of the glycocalyx from glomerular endothelial cells lead to increased microvascular permeability. Although coagulation disbalance occurs in all microvascular segments, the molecules involved differ between segments. Induction of the expression of adhesion molecules and leukocyte recruitment also occurs in a heterogeneous manner. Evidence of similar endothelial cell responses has been found in kidney and blood samples from patients with sepsis. Comprehensive studies are needed to investigate the relationships between segment-specific changes in the microvasculature and kidney function loss in sepsis-AKI. The application of omics technologies to kidney tissues from animals and patients will be key in identifying these relationships and in developing novel therapeutics for sepsis
The role of charge-matching in nanoporous materials formation
Unravelling the molecular-level mechanisms that lead to the formation of mesoscale-ordered porous materials is a crucial step towards the goal of computational material design. For silica templated by alkylamine surfactants, a mechanism based on hydrogen-bond interactions between neutral amines and neutral silicates in solution has been widely accepted by the materials science community, despite the lack of conclusive evidence to support it. We demonstrate, through a combination of experimental measurements and multi-scale modelling, that the so-called “neutral templating route” does not represent a viable description of the synthesis mechanism of hexagonal mesoporous silica (HMS), the earliest example of amine-templated porous silica. Instead, the mesoscale structure of the material is defined by charge-matching of ionic interactions between amines and silicates. This has profound implications for the synthesis of a wide range of templated porous materials, and may shed new light on developing sustainable and economical routes to high value porous materials
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