Can market failure cause political failure?

We study how inefficiencies of market failure may be further amplified by political choices made by interest groups created in the inefficient market. We take an occupational choice framework, where agents are endowed heterogeneously with wealth and talent. In our model, market failure due to unobservability of talent endogenously creates a class structure that affects voting on institutional reform. In contrast to the world without market failure where the electorate unanimously vote in favour of surplus maximising institutional reform, we find that the preferences of these classes are often aligned in ways that creates a tension between surplus maximising and politically feasible institutional reforms

Practical approach to diastolic dysfunction in light of the new guidelines and clinical applications in the operating room and in the intensive care

There is growing evidence both in the perioperative period and in the field of intensive care (ICU) on the association between left ventricular diastolic dysfunction (LVDD) and worse outcomes in patients. The recent American Society of Echocardiography and European Association of Cardiovascular Imaging joint recommendations have tried to simplify the diagnosis and the grading of LVDD. However, both an often unknown pre-morbid LV diastolic function and the presence of several confounders—i.e., use of vasopressors, positive pressure ventilation, volume loading—make the proposed parameters difficult to interpret, especially in the ICU. Among the proposed parameters for diagnosis and grading of LVDD, the two tissue Doppler imaging-derived variables e′ and E/e′ seem most reliable. However, these are not devoid of limitations. In the present review, we aim at rationalizing the applicability of the recent recommendations to the perioperative and ICU areas, discussing the clinical meaning and echocardiographic findings of different grades of LVDD, describing the impact of LVDD on patients’ outcomes and providing some hints on the management of patients with LVDD

Can Market Failure Cause Political Failure?

We study how inefficiencies of market failure may be further amplified by political choices made by interest groups created in the inefficient market. We take an occupational choice framework, where agents are endowed heterogeneously with wealth and talent. In our model, market failure due to unobservability of talent endogenously creates a class structure that affects voting on institutional reform. In contrast to the world without market failure where the electorate unanimously vote in favour of surplus maximising institutional reform, we find that the preferences of these classes are often aligned in ways that creates a tension between surplus maximising and politically feasible institutional reforms.occupational choice, adverse selection, property rights, assetliquidation, political failure, market failure.

A Bayesian inference framework to reconstruct transmission trees using epidemiological and genetic data

The accurate identification of the route of transmission taken by an infectious agent through a host population is critical to understanding its epidemiology and informing measures for its control. However, reconstruction of transmission routes during an epidemic is often an underdetermined problem: data about the location and timings of infections can be incomplete, inaccurate, and compatible with a large number of different transmission scenarios. For fast-evolving pathogens like RNA viruses, inference can be strengthened by using genetic data, nowadays easily and affordably generated. However, significant statistical challenges remain to be overcome in the full integration of these different data types if transmission trees are to be reliably estimated. We present here a framework leading to a bayesian inference scheme that combines genetic and epidemiological data, able to reconstruct most likely transmission patterns and infection dates. After testing our approach with simulated data, we apply the method to two UK epidemics of Foot-and-Mouth Disease Virus (FMDV): the 2007 outbreak, and a subset of the large 2001 epidemic. In the first case, we are able to confirm the role of a specific premise as the link between the two phases of the epidemics, while transmissions more densely clustered in space and time remain harder to resolve. When we consider data collected from the 2001 epidemic during a time of national emergency, our inference scheme robustly infers transmission chains, and uncovers the presence of undetected premises, thus providing a useful tool for epidemiological studies in real time. The generation of genetic data is becoming routine in epidemiological investigations, but the development of analytical tools maximizing the value of these data remains a priority. Our method, while applied here in the context of FMDV, is general and with slight modification can be used in any situation where both spatiotemporal and genetic data are available

Measuring spike train synchrony

Estimating the degree of synchrony or reliability between two or more spike trains is a frequent task in both experimental and computational neuroscience. In recent years, many different methods have been proposed that typically compare the timing of spikes on a certain time scale to be fixed beforehand. Here, we propose the ISI-distance, a simple complementary approach that extracts information from the interspike intervals by evaluating the ratio of the instantaneous frequencies. The method is parameter free, time scale independent and easy to visualize as illustrated by an application to real neuronal spike trains obtained in vitro from rat slices. In a comparison with existing approaches on spike trains extracted from a simulated Hindemarsh-Rose network, the ISI-distance performs as well as the best time-scale-optimized measure based on spike timing.Comment: 11 pages, 13 figures; v2: minor modifications; v3: minor modifications, added link to webpage that includes the Matlab Source Code for the method (http://inls.ucsd.edu/~kreuz/Source-Code/Spike-Sync.html

Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results

Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models

Analysis of an intense bora event in the Adriatic area

International audienceNumerical simulations of a bora event, recently occurred in the Adriatic area, are presented. Two reference runs at different horizontal resolution (about 20km and 8km) describe the case. Initial conditions for the atmospheric model integration are obtained from ECMWF analyses. Satellite data are used for comparisons. A further run at horizontal resolution of 8km, using initial satellite sea surface temperatures, is performed to evaluate their impact on the low level wind over the Adriatic Sea. All the simulations are carried out with 50 layers in the vertical. Numerous aspects of the simulations are found to be in agreement with the understanding as well as the observational knowledge of bora distinctive characteristics. Satellite data and model results indicate that a more realistic simulation of the bora wind over the sea is achieved using the model with 8km horizontal resolution and that the low level wind in this case is sensitive, though weakly, to the difference between the used sea surface temperature fields. Simulation results also show that both wind intensity and the area around wind peaks tend to increase when relatively higher sea surface temperatures are used

Resource-Efficient High-Dimensional Entanglement Detection via Symmetric Projections

We introduce two families of criteria for detecting and quantifying the entanglement of a bipartite quantum state of arbitrary local dimension. The first is based on measurements in mutually unbiased bases and the second is based on equiangular measurements. Both criteria give a qualitative result in terms of the state's entanglement dimension and a quantitative result in terms of its fidelity with the maximally entangled state. The criteria are universally applicable since no assumptions on the state are required. Moreover, the experimenter can control the trade-off between resource-efficiency and noise-tolerance by selecting the number of measurements performed. For paradigmatic noise models, we show that only a small number of measurements are necessary to achieve nearly-optimal detection in any dimension. The number of global product projections scales only linearly in the local dimension, thus paving the way for detection and quantification of very high-dimensional entanglement