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

Maintaining New Markets: Determinants of Antitrust Enforcement in Central and Eastern Europe

While others have examined the implementation and/or the stringency of enforcement of antitrust laws in post-socialist economies, this paper is the first study that attempts to explain the determinants of antitrust enforcement activity across post-socialist countries using economic and political variables. Using a panel of ten European post-socialist countries over periods ranging from 4 to 11 years, we find a number of significant determinants of enforcement in these countries. For example, larger economies engage in more antitrust enforcement, and countries have tended to increase their enforcement efforts over time. Our results also suggest that countries characterized by more unionization and less corruption tend to engage in greater antitrust enforcement of all types. Countries more successful in privatizing have filed fewer cases, while more affluent or developed countries investigate fewer cases of all types, consistent with an income-shifting motivation for antitrust.Antitrust Enforcement, Central and Eastern Europe, Competition Policy JEL classification: L4, P3

Honduras: Factors Underlying Immigration to the United States

This thesis examines the relationship between out-migration from Honduras, US policy, and conditions in Honduras. More particularly, it examines the violent and repressive conditions in Honduras along with US Military Assistance from 1980 to 2017. I look at the impact of US immigration policy on migration flows into the United States. Using data from World Bank databank, the US Foreign Aid Greenbook, the World Development Report, the Migration Policy Institute (MPI), and the Political Terror Scale (PTS), I argue that violent conditions in Honduras, US military aid, and US immigration policy have significantly contributed to the ongoing exodus from Honduras to the United States between 1980 and 2017

SN contributions to GRB lightcurves

Several of the nearer GRB afterglows (up to z ∼ 1) show bumps in their lightcurves that have been interpreted as contributions from associated SNae. Thebumps arecustomarily modelled likethet ype-Ic SN 1998bw, but wein vestigate here, for several low-z GRBs, whether other SN types might offer alternatives. While several SN types are ruled out, or are unlikely, a type “II-bl” could also explain the observations

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

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