OPTN/SRTR 2018 Annual Data Report: Heart

The new adult heart allocation policy was approved in 2016 and implemented in October 2018, so its effect was not yet evident in 2018 data. However, the more granular data being collected are anticipated to allow for improved analyses. In 2018, new listings continued to increase; 3883 new adult and 685 new pediatric candidates were added. In 2018, 3440 heart transplants were performed, an increase of 167 over 2017; 473 transplants occurred in pediatric recipients and 2967 in adult recipients. Short‐term and long‐term posttransplant mortality improved. Overall 1‐year survival for adults who underwent heart transplant in 2011‐2013 was 90.3%, 3‐year survival was 84.7%, and 5‐year survival was 79.6%. Mortality rates for pediatric recipients were 4.5% at 6 months and in 5.9% at 1 year posttransplant, 12.5% at 3 years for transplants in 2014‐2015, 14.8% at 5 years for transplants in 2012‐2013, and 29.8% at 10 years for transplants performed in 2008‐2009.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153233/1/ajt15676.pd

Leveraging analytics to produce compelling and profitable film content

Producing compelling film content profitably is a top priority to the long-term prosperity of the film industry. Advances in digital technologies, increasing availabilities of granular big data, rapid diffusion of analytic techniques, and intensified competition from user generated content and original content produced by Subscription Video on Demand (SVOD) platforms have created unparalleled needs and opportunities for film producers to leverage analytics in content production. Built upon the theories of value creation and film production, this article proposes a conceptual framework of key analytic techniques that film producers may engage throughout the production process, such as script analytics, talent analytics, and audience analytics. The article further synthesizes the state-of-the-art research on and applications of these analytics, discuss the prospect of leveraging analytics in film production, and suggest fruitful avenues for future research with important managerial implications

Technologies of sleep research

Sleep is investigated in many different ways, many different species and under many different circumstances. Modern sleep research is a multidisciplinary venture. Therefore, this review cannot give a complete overview of all techniques used in sleep research and sleep medicine. What it will try to do is to give an overview of widely applied techniques and exciting new developments. Electroencephalography has been the backbone of sleep research and sleep medicine since its first application in the 1930s. The electroencephalogram is still used but now combined with many different techniques monitoring body and brain temperature, changes in brain and blood chemistry, or changes in brain functioning. Animal research has been very important for progress in sleep research and sleep medicine. It provides opportunities to investigate the sleeping brain in ways not possible in healthy volunteers. Progress in genomics has brought new insights in sleep regulation, the best example being the discovery of hypocretin/orexin deficiency as the cause of narcolepsy. Gene manipulation holds great promise for the future since it is possible not only to investigate the functions of different genes under normal conditions, but also to mimic human pathology in much greater detail

Evaluation of the relationship of tibiofemoralkinematics before and after total knee replacement in an in vitro model of cranial cruciate deficiency in the dog

OBJECTIVE: To investigate the relationship between tibiofemoral kinematics before and after total knee replacement (TKR) in vitro. ANIMALS: Eight canine hemipelves. METHODS: A modified Oxford Knee Rig was used to place cadaveric limbs through a range of passive motion allowing the kinematics of the stifle to be evaluated. Four measurements were performed: a control stage, followed by a cranial cruciate transection stage, then following TKR with the musculature intact stage, and finally TKR with removal of limb musculature stage. Joint angles and translations of the femur relative to the tibia, including flexion-extension versus adduction-abduction, flexion-extension versus internal-external rotation, as well as flexion-extension versus each translation (cranial-caudal and lateral-medial) were calculated. RESULTS: Significant differences were identified in kinematic data from limbs following TKR implantation as compared to the unaltered stifle. The TKR resulted in significant decreases in external rotation of the stifle during flexion-extension compared to the limb prior to any intervention, as well as increasing the abduction. The TKR significantly increased the caudal translation of the femur relative to the tibia compared to the unaltered limb. When compared with the cranial cruciate ligament-transection stage, TKR significantly decreased the ratio of the external rotation to flexion. DISCUSSION: All three test periods showed significant differences from the unaltered stifle. The TKR did not completely restore the normal kinematics of the stifle

Sequential Estimation of Dynamic Discrete Games

This paper studies the estimation of dynamic discrete games of incomplete information. Two main econometric issues appear in the estimation of these models: the indeterminacy problem associated with the existence of multiple equilibria and the computational burden in the solution of the game. We propose a class of pseudo maximum likelihood (PML) estimators that deals with these problems, and we study the asymptotic and finite sample properties of several estimators in this class. We first focus on two-step PML estimators, which, although they are attractive for their computational simplicity, have some important limitations: they are seriously biased in small samples; they require consistent nonparametric estimators of players' choice probabilities in the first step, which are not always available; and they are asymptotically inefficient. Second, we show that a recursive extension of the two-step PML, which we call nested pseudo likelihood (NPL), addresses those drawbacks at a relatively small additional computational cost. The NPL estimator is particularly useful in applications where consistent nonparametric estimates of choice probabilities either are not available or are very imprecise, e.g., models with permanent unobserved heterogeneity. Finally, we illustrate these methods in Monte Carlo experiments and in an empirical application to a model of firm entry and exit in oligopoly markets using Chilean data from several retail industries. Copyright The Econometric Society 2007.