Ultrafast processing of pixel detector data with machine learning frameworks

Modern photon science performed at high repetition rate free-electron laser (FEL) facilities and beyond relies on 2D pixel detectors operating at increasing frequencies (towards 100 kHz at LCLS-II) and producing rapidly increasing amounts of data (towards TB/s). This data must be rapidly stored for offline analysis and summarized in real time. While at LCLS all raw data has been stored, at LCLS-II this would lead to a prohibitive cost; instead, enabling real time processing of pixel detector raw data allows reducing the size and cost of online processing, offline processing and storage by orders of magnitude while preserving full photon information, by taking advantage of the compressibility of sparse data typical for LCLS-II applications. We investigated if recent developments in machine learning are useful in data processing for high speed pixel detectors and found that typical deep learning models and autoencoder architectures failed to yield useful noise reduction while preserving full photon information, presumably because of the very different statistics and feature sets between computer vision and radiation imaging. However, we redesigned in Tensorflow mathematically equivalent versions of the state-of-the-art, "classical" algorithms used at LCLS. The novel Tensorflow models resulted in elegant, compact and hardware agnostic code, gaining 1 to 2 orders of magnitude faster processing on an inexpensive consumer GPU, reducing by 3 orders of magnitude the projected cost of online analysis at LCLS-II. Computer vision a decade ago was dominated by hand-crafted filters; their structure inspired the deep learning revolution resulting in modern deep convolutional networks; similarly, our novel Tensorflow filters provide inspiration for designing future deep learning architectures for ultrafast and efficient processing and classification of pixel detector images at FEL facilities.Comment: 9 pages, 9 figure

Indwelling Pleural Catheters in Hepatic Hydrothorax: A Single-Center Series of Outcomes and Complications

Background Treatment of hepatic hydrothorax (HH) generally involves sodium restriction, diuretics, and serial thoracentesis. In more advanced cases, transjugular intrahepatic portosystemic shunt and liver transplantation may be required. Previously, indwelling tube drainage has been avoided due to concerns regarding high complication rates and overall poor outcomes. Recently, indwelling pleural catheters (IPCs) have been proposed as a novel treatment option for HH. Methods This study was a retrospective review of patients who had undergone IPC placement for HH over a 10-year period at a large liver transplant referral center. We tracked outcomes, including complication rates and liver transplantation, as well as biomarkers of nutritional status. Results Sixty-two patients underwent IPC placement between 2007 and 2017, with 33 IPCs (53%) placed as a bridge to liver transplantation. Complications were recorded in 22 patients (36%); empyema was the most common, diagnosed in 10 patients (16.1%). Ten patients evaluated for liver transplantation underwent successful transplantation following IPC placement. There were statistically significant decreases in both BMI and serum albumin levels following IPC placement. Conclusions IPCs represent a potential treatment for refractory HH and should be used with caution in patients eligible for liver transplantation. Ideally, IPC use for these patients would be evaluated by a multidisciplinary team. IPC use may lead to small decreases in BMI and serum albumin levels in patients over time

How forward-looking is the Fed? Direct estimates from a `Calvo-type' rule

We estimate an alternative type of monetary policy rule, termed Calvo rule, according to which the central bank is assumed to target a discounted in?nite sum of future expected in?ation. Compared to conventional in?ation forecast-based rules, which are typically of the Taylor-type with discrete forward looking horizons, this class of rule is less prone to the problem of indeterminacy. Parameter estimates obtained from GMM estimation provide support for Calvo-type rules, suggesting that the Federal Reserve targeted a mean forward horizon of between 4 and 8 quarters.Calvo-type interest rules; In?ation Forecast Based rules; GMM; Indeterminacy.

How forward-looking is the Fed? Direct estimates from a ‘Calvo-type’ rule

We estimate an alternative type of monetary policy rule, termed Calvo rule, according to which the central bank is assumed to target a discounted infinite sum of future expected inflation. Compared to conventional inflation forecast-based rules, which are typically of the Taylor-type with discrete forward looking horizons, this class of rule is less prone to the problem of indeterminacy. Parameter estimates obtained from GMM estimation provide support for Calvo-type rules, suggesting that the Federal Reserve targeted a mean forward horizon of between 4 and 8 quarters.Calvo-type interest rules, Inflation Forecast Based rules, GMM, indeterminacy.

Religion and Attitudes toward Same-Sex Marriage among U.S. Latinos

Objectives. This study examines links between multiple aspects of religious involvement and attitudes toward same-sex marriage among U.S. Latinos. The primary focus is on variations by affiliation and participation, but the possible mediating roles of biblical beliefs, clergy cues, and the role of religion in shaping political views are also considered. Methods. We use binary logistic regression models to analyze data from a large nationwide sample of U.S. Latinos conducted by the Pew Hispanic Forum in late 2006. Results. Findings highlight the strong opposition to same-sex marriage among Latino evangelical (or conservative) Protestants and members of sectarian groups (e.g., LDS), even compared with devout Catholics. Although each of the hypothesized mediators is significantly linked with attitudes toward same-sex marriage, for the most part controlling for them does not alter the massive affiliation/attendance differences in attitudes toward same-sex marriage. Conclusions. This study illustrates the importance of religious cleavages in public opinion on social issues within the diverse U.S. Latino population. The significance of religious variations in Hispanic civic life is likely to increase with the growth of the Latino population and the rising numbers of Protestants and sectarians among Latinos

Determination of the most appropriate method for extrapolating overall survival data from a placebo-controlled clinical trial of lenvatinib for progressive, radioiodine-refractory differentiated thyroid cancer

Background: Cost-effectiveness models for the treatment of long-term conditions often require information on survival beyond the period of available data. Objectives: This paper aims to identify a robust and reliable method for the extrapolation of overall survival (OS) in patients with radioiodine-refractory differentiated thyroid cancer receiving lenvatinib or placebo. Methods: Data from 392 patients (lenvatinib: 261, placebo: 131) from the SELECT trial are used over a 34-month period of follow-up. A previously published criterion-based approach is employed to ascertain credible estimates of OS beyond the trial data. Parametric models with and without a treatment covariate and piecewise models are used to extrapolate OS, and a holistic approach, where a series of statistical and visual tests are considered collectively, is taken in determining the most appropriate extrapolation model. Results: A piecewise model, in which the Kaplan–Meier survivor function is used over the trial period and an extrapolated tail is based on the Exponential distribution, is identified as the optimal model. Conclusion: In the absence of long-term survival estimates from clinical trials, survival estimates often need to be extrapolated from the available data. The use of a systematic method based on a priori determined selection criteria provides a transparent approach and reduces the risk of bias. The extrapolated OS estimates will be used to investigate the potential long-term benefits of lenvatinib in the treatment of radioiodine-refractory differentiated thyroid cancer patients and populate future cost-effectiveness analyses

Planning for Decentralized Control of Multiple Robots Under Uncertainty

We describe a probabilistic framework for synthesizing control policies for general multi-robot systems, given environment and sensor models and a cost function. Decentralized, partially observable Markov decision processes (Dec-POMDPs) are a general model of decision processes where a team of agents must cooperate to optimize some objective (specified by a shared reward or cost function) in the presence of uncertainty, but where communication limitations mean that the agents cannot share their state, so execution must proceed in a decentralized fashion. While Dec-POMDPs are typically intractable to solve for real-world problems, recent research on the use of macro-actions in Dec-POMDPs has significantly increased the size of problem that can be practically solved as a Dec-POMDP. We describe this general model, and show how, in contrast to most existing methods that are specialized to a particular problem class, it can synthesize control policies that use whatever opportunities for coordination are present in the problem, while balancing off uncertainty in outcomes, sensor information, and information about other agents. We use three variations on a warehouse task to show that a single planner of this type can generate cooperative behavior using task allocation, direct communication, and signaling, as appropriate

On the (ir)relevance of direct supply-side effects of monetary policy

The relevance of direct supply-side effects of monetary policy in a New Keynesian DSGE model is studied. We extend a model with several nominal and real frictions by introducing a cost channel of monetary transmission and allowing for non-separability of money and consumption in the utility of the representative household. These fea- tures have important theoretical consequences for the output-inflation trade-off and indeterminacy of interest rate rules. The empirical evidence for these effects are then examined using a Bayesian maximum likelihood framework complemented with GMM single-equation estimation. Both estimation strategies point to weak evidence for the cost channel and non-separable utility.New Keynesian model, Bayesian maximum likelihood estimation, GMM, non-separable utility, cost channel.