Inequality, Transfers and Growth: New Evidence from the Economic Transition in Poland

This paper challenges the conventional wisdom that inequality in Poland increased markedly during the economic transition that began in 1989-90. Using micro data from the Household Budget Surveys, we find that, after a brief spike in 1989, income and consumption inequality actually declined to below pre-transition levels during 1990-92 and then increased gradually, rising only moderately above pre-transition levels by 1997. In sharp contrast, inequality in labor earnings increased markedly and consistently throughout the 1990-97 period. We find that social transfer mechanisms, including pensions, played an important role in mitigating increases in both overall inequality and poverty. We argue that, from a political economy perspective, transfer mechanisms were well-designed to reduce political resistance to market-oriented reforms in the early years of transition, paving the way for rapid growth. Finally, we provide cross-country evidence from the transition economies that is consistent with our interpretation of the Polish experience and is also consistent with recent work in growth theory which suggests that redistribution that reduces inequality can enhance growth.

A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units

The management of invasive mechanical ventilation, and the regulation of sedation and analgesia during ventilation, constitutes a major part of the care of patients admitted to intensive care units. Both prolonged dependence on mechanical ventilation and premature extubation are associated with increased risk of complications and higher hospital costs, but clinical opinion on the best protocol for weaning patients off of a ventilator varies. This work aims to develop a decision support tool that uses available patient information to predict time-to-extubation readiness and to recommend a personalized regime of sedation dosage and ventilator support. To this end, we use off-policy reinforcement learning algorithms to determine the best action at a given patient state from sub-optimal historical ICU data. We compare treatment policies from fitted Q-iteration with extremely randomized trees and with feedforward neural networks, and demonstrate that the policies learnt show promise in recommending weaning protocols with improved outcomes, in terms of minimizing rates of reintubation and regulating physiological stability

Amplitude death in coupled chaotic oscillators

Amplitude death can occur in chaotic dynamical systems with time-delay coupling, similar to the case of coupled limit cycles. The coupling leads to stabilization of fixed points of the subsystems. This phenomenon is quite general, and occurs for identical as well as nonidentical coupled chaotic systems. Using the Lorenz and R\"ossler chaotic oscillators to construct representative systems, various possible transitions from chaotic dynamics to fixed points are discussed.Comment: To be published in PR

Challenges in video based object detection in maritime scenario using computer vision

This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here