Regularity of the minimiser of one-dimensional interaction energies

We consider both the minimisation of a class of nonlocal interaction energies over non-negative measures with unit mass and a class of singular integral equations of the first kind of Fredholm type. Our setting covers applications to dislocation pile-ups, contact problems, fracture mechanics and random matrix theory. Our main result shows that both the minimisation problems and the related singular integral equations have the same unique solution, which provides new regularity results on the minimiser of the energy and new positivity results on the solutions to singular integral equations.Comment: 46 page

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

ICU at home, with the use of mobile IC unit services:intensive care goes that extra mile

In this report we describe a patient with a long ICU stay because of severe Guillain Barré syndrome. Treatment was patient-centred and Mobile ICU facilities were used to facilitate an ICU at home for one day. Early focus on individual needs and wishes and close communication with and within ICU treatment teams can help to improve the long-term consequences of ICU admission. Research on which interventions are effective and most cost-effective need to be performed

Inhaled Nitric Oxide Therapy for Pulmonary Disorders of the Term and Preterm Infant

The 21st century began with the FDA approval of inhaled nitric oxide therapy for the treatment of neonatal hypoxic respiratory failure associated with pulmonary hypertension in recognition of the two randomized clinical trials demostrating a significant reduction in the need for extracorporeal support in the term and near-term infant. Inhaled nitric oxide is one of only a few therapeutic agents approved for use through clinical investigations primarily in the neonate. This article provides an overview of the pertinent biology and chemistry of nitric oxide, discusses potential toxicities, and reviews the results of pertinent clinical investigations and large randomized clinical trials including neurodevelopmental follow-up in term and preterm neonates. The clinical investigations conducted by the Eunice Kennedy Shriver NICHD Neonatal Research Network will be discussed and placed in context with other pertinent clinical investigations exploring the efficacy of inhaled nitric oxide therapy in neonatal hypoxic respiratory failure

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

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