Political institutions and debt crises

This paper shows that political institutions matter in explaining defaults on external and domestic debt obligations. We explore a large number of political and macroeconomic variables using a non-parametric technique to predict safety from default. The advantage of this technique is that it is able to identify patterns in the data that are not captured in standard probit analysis. We find that political factors matter, and do so in different ways for democratic and non-democratic regimes, and for domestic and external debt. In democracies, a parliamentary system or sufficient checks and balances almost guarantee the absence of default on external debt when economic fundamentals or liquidity are sufficiently strong. In dictatorships, high stability and tenure play a similar role for default on domestic debt

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulation–optimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America

Meta-learning of Sequential Strategies

In this report we review memory-based meta-learning as a tool for building sample-efficient strategies that learn from past experience to adapt to any task within a target class. Our goal is to equip the reader with the conceptual foundations of this tool for building new, scalable agents that operate on broad domains. To do so, we present basic algorithmic templates for building near-optimal predictors and reinforcement learners which behave as if they had a probabilistic model that allowed them to efficiently exploit task structure. Furthermore, we recast memory-based meta-learning within a Bayesian framework, showing that the meta-learned strategies are near-optimal because they amortize Bayes-filtered data, where the adaptation is implemented in the memory dynamics as a state-machine of sufficient statistics. Essentially, memory-based meta-learning translates the hard problem of probabilistic sequential inference into a regression problem.Comment: DeepMind Technical Report (15 pages, 6 figures

Cimetidine modulates the antigen presenting capacity of dendritic cells from colorectal cancer patients

Cimetidine, a H2 receptor antagonist, has been reported to improve survival in gastrointestinal cancer patients. These effects have largely been attributed to the enhancing effects of cimetidine on the host's antitumour cell-mediated immune response, such as inhibition of suppressor T lymphocyte activity, stimulation of natural killer cell activity and increase of interleukin-2 production from helper T lymphocytes. We conducted an in vitro study on the effects of cimetidine on differentiation and antigen presenting capacity of monocyte-derived dendritic cells from advanced colorectal cancer patients and normal controls. As a result, an investigation of expression of surface molecules associated with dendritic cells by flow cytometric analyses showed that cimetidine had no enhancing effect on differentiation of dendritic cells from cancer patients and normal controls. An investigation of [3H]thymidine incorporation by allogeneic mixed lymphocyte reactions revealed that cimetidine increased the antigen presenting capacity of dendritic cells from both materials. Moreover, a higher antigen presenting capacity was observed in advanced cancer patients compared to normal controls. These effects might be mediated via specific action of cimetidine and not via H2 receptors because famotidine did not show similar effects. Our results suggest that cimetidine may enhance the host's antitumour cell-mediated immunity by improving the suppressed dendritic cells function of advanced cancer patients

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure.</p> <p>Results and Discussion</p> <p>ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems</p> <p>Conclusion</p> <p>A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.</p

Architectural Paint Research and the Archaeology of Buildings

Architectural Paint Research (APR) is the archaeological study of interior and exterior applied decoration. Over time, applied layers of paint and other decorative finishes build-up on the surface of a built structure, encapsulating microscopic deposits of material evidence. This evidence can be used to inform the phase dating of a structure, or illuminate the historic function of a space. It can challenge preconceived ideas of how specific areas were decorated, and track the changes in aesthetics over time. It can identify when architects’ ideologies have been balanced by practical considerations. It can provide an insight into the intangible and ephemeral atmosphere that decoration gives to a room. Finally, it can examine the dirt trapped between layers of decoration and thus categorize the physical environmental conditions that surrounded a building at varying points in its history. Although used in the commercial heritage and conservation sectors, Architectural Paint Research is almost completely unknown to building archaeologists. This article aims to introduce APR to a new audience, and argues that is an invaluable tool in the archaeological interpretation of buildings

Langerhans cell histiocytosis (histiocytosis X)

There has been a renewed interest in Langerhans cell histiocytosis in recent years due both to advances in basic research and to improvements in diagnostic and treatment approaches. In this article, we review the various aspects of the disease and the potential implications of these recent scientific researches for our understanding and management of the disorder.published_or_final_versio