Miracle-dz/UniFAR-FTUs huggingface dataset:
High Concentrations of Measles Neutralizing Antibodies and High-Avidity Measles IgG Accurately Identify Measles Reinfection Cases

ABSTRACT In the United States, approximately 9% of the measles cases reported from 2012 to 2014 occurred in vaccinated individuals. Laboratory confirmation of measles in vaccinated individuals is challenging since IgM assays can give inconclusive results. Although a positive reverse transcription (RT)-PCR assay result from an appropriately timed specimen can provide confirmation, negative results may not rule out a highly suspicious case. Detection of high-avidity measles IgG in serum samples provides laboratory evidence of a past immunologic response to measles from natural infection or immunization. High concentrations of measles neutralizing antibody have been observed by plaque reduction neutralization (PRN) assays among confirmed measles cases with high-avidity IgG, referred to here as reinfection cases (RICs). In this study, we evaluated the utility of measuring levels of measles neutralizing antibody to distinguish RICs from noncases by receiver operating characteristic curve analysis. Single and paired serum samples with high-avidity measles IgG from suspected measles cases submitted to the CDC for routine surveillance were used for the analysis. The RICs were confirmed by a 4-fold rise in PRN titer or by RT-quantitative PCR (RT-qPCR) assay, while the noncases were negative by both assays. Discrimination accuracy was high with serum samples collected ≥3 days after rash onset (area under the curve, 0.953; 95% confidence interval [CI], 0.854 to 0.993). Measles neutralizing antibody concentrations of ≥40,000 mIU/ml identified RICs with 90% sensitivity (95% CI, 74 to 98%) and 100% specificity (95% CI, 82 to 100%). Therefore, when serological or RT-qPCR results are unavailable or inconclusive, suspected measles cases with high-avidity measles IgG can be confirmed as RICs by measles neutralizing antibody concentrations of ≥40,000 mIU/ml.
Systematic Evaluation of Design Decisions in CBR

Two important goals in the evaluation of an AI theory or model are to assess the merit of the design decisions in the performance of an implemented computer system and to analyze the impact in the performance when the system faces problem domains with diierent characteristics. This is particularly diicult in case-based reasoning systems because such systems are typically very complex, as are the tasks and domains in which they operate. We present a methodology for the evaluation of case-based reasoning systems through systematic empirical experimentation over a range of system conngurations and environmental conditions, coupled with rigorous statistical analysis of the results of the experiments. This methodology enables us to understand the behavior of the system in terms of the theory and design of the computational model, to select the best system conngu-ration for a given domain, and to predict how the system will behave in response to changing domain and problem characteristics. A case study of a mul-tistrategy case-based and reinforcement learning system which performs autonomous robotic navigation is presented as an example.
Nanotechnology and Diagnostic Imaging: New Advances in Contrast Agent Technology

Medical imaging technologies allow for the rapid diagnosis and evaluation of a wide range of pathologies. In order to increase their sensitivity and utility, many imaging technologies such as CT and MRI rely on intravenously administered contrast agents. While the current generation of contrast agents has enabled rapid diagnosis, they still suffer from many undesirable drawbacks including a lack of tissue specificity and systemic toxicity issues. Through advances made in nanotechnology and materials science, researchers are now creating a new generation of contrast agents that overcome many of these challenges, and are capable of providing more sensitive and specific information. In this review, we summarize the main classes of nanotechnology-based contrast agents for each of the major imaging technologies, and highlight progress in their development as well as the challenges to be addressed. We also review the relevant biological interactions that determine the in vivo fate of these contrast agents, and describe major themes in medical nanotechnology including stealth and targeting.
Real Estate Prices in Production Economies

The aim of this study is to develop a general equilibrium framework linking real estate prices to the real economy. The model is evaluated in terms of its ability to explain: (i) the high volatility of residential real estate prices, (ii) the fact that commercial real estate prices are more volatile than residential real estate prices, (iii) the low volatility of residential rents. This study finds that a production economy model, allowing prices and quantities to be endogenously determined, is able to explain the puzzling volatility of real estate prices while capturing the main empirical regularities of the business cycle. • House Prices, Production Economies, Asset Pricing, General Equilibrium, Real Estate • JEL: G1, E3, R31 Visiting postdoctoral fellow, Wharton School of Finance. Financial support by the National Center of Competence in Research "Financial Valuation and Risk Management" (NCCR Finrisk) is gratefully acknowledged. NCCR Finrisk is a research instrument of the Swiss National Foundation. This project has benefited from the comments and suggestions of Pascal St-Amour, Urban Jermann, Jean-Pierre Danthine, Jean Imbs and the participants of the reading group of the Wharton School. Any remaining errors are my own responsibility. http://assets.wharton.upenn.edu/~ijaccard/, email: ijaccard@wharton.upenn.edu Contact information: Wharton School of Finance, University of Pennsylvania, 3620 Locust Walk, 19104 Philadelphia, USA. Tel. : 215-898-90-23.
Studies in Robotic Vision, Optical Illusions and Nonlinear Diffusion Filtering

This thesis is divided into three parts, which all deal with computational analysis and processing of images. However, the settings are quite diverse.They range from robotic camera sensors, over human perception, to physical measurement setups. In spite of this diversity, common theoretical ideas and computational aspects are applied which ties the three different parts closer together. The first part of the thesis deals with calibration methods for robotic vision. Both the estimation of the intrinsic parameters of the applied camera model, intrinsic camera calibration, and the estimation of the orientation and position of the camera in relation to the end-effector of the robot, hand-eye calibration, are discussed. Two different methods are presented. The first one explores the constraints that arise when calibrating a single camera or a stereo head configuration using a planar calibration object, while performing translational or general motions. The other one uses estimations of the spatial and temporal intensity derivatives in an image sequence for direct computation of the unknown parameters. The second part of the thesis discusses a new framework for explaining a number of geometrical optical illusions. It is proposed that noise, that enters into the visual process at different stages, causes the estimation of different features in the observed image to be biased. Different types of error models are discussed and illusions that are best explained by each particular model are presented. The discussion is not restricted to the human visual system and highlights the importance of analyzing the influence of noise and uncertainty in any visual process. The third and final part of the thesis propose the use of nonlinear diffusion filtering to process images obtained by planar laser-induced fluorescence (PLIF) spectroscopy. In particular, the images in the present application are PLIF images of turbulent flames in combustion processes. Solving a nonlinear diffusion equation using an image of this type as initial value, makes succeeding extraction of interesting quantities, such as the length of the flame boundary, an easy task. An analysis of the properties of nonlinear diffusion filtering in general, and for the present application in particular, is given.
Fisher's Paradox and the Theory of Interest

Irving Fisher's Theory of Interest has proved to be a most durable and influential contribution to economic theory. A central element of Fisher's contribution is the Fisher hypothesis that, over the longer term, the real rate of interest is approximately constant, being determined largely by time preference, with movements in the nominal interest rate reflecting movements in the rate of inflation one-for-one. The paradox of the Fisher hypothesis is that, despite its wide acceptance as the cornerstone of interest rate theory, most empirical evidence appears to be inconsistent with the hypothesis, at least in its strictest form. This empirical anomaly was noted by Fisher himself, who attributed it to money illusion. In the fifty years following the publication of the Theory of Interest, a considerable literature has evolved around this paradox. ' The unifying theme of this literature is a common acceptance of the essence of Fisher's hypothesis. Most of the energy in this literature has been devoted to explaining systematic movements in the real rate of interest, and to providing reasons why the relationship between the nominal interest rate and inflation may only be approximate in
INDEPENDÊNCIA DO JUDICIÁRIO: MENSURANDO O VIÉS POLÍTICO DAS CORTES BRASILEIRAS

The degree of judicial independence has broad implications on economic development. For the executive’s non-expropriation commitment to be credible, it is necessary that the judiciary should be free to impartially mediate disputes between the State and its citizens. The prolific literature on de facto judicial independence misses a key-variable to explain political bias: the government’s discretion in appointing Supreme Court members. In this paper we explore a distinct feature of Brazilian judiciary to assess political bias due to government appointment discretion. As there are two courts, the Supremo Tribunal Federal (STF) and the Superior Tribunal de Justica (STJ), which deal with similar matters and have different restrictions on the appointment of its members, it is possible to compare the degree of political influence to which they are subject. We test (1) if there is a political appointment effect on the decisions of the justices of the two courts, (2) if there are differences on the degree of political influence in accordance to the restrictions on presidential nomination in place in each court; and (3) if the justices of both courts make strategic use of their positions, that is, actively benefit the party that has appointed them. We find evidence of the second and, partially, of the third effect.
The Sharpey-Schafer lecture. Ion channels and signal processing in the outer retina.

Q J Exp Physiol David Attwell OUTER RETINA CHANNELS AND SIGNAL PROCESSING IN THE THE SHARPEY-SCHAFER LECTURE: ION This information is current as of April 11, 2008 http://ep.physoc. org at: This is the final published version of this article; it is available JournalsRights@oxon.blackwellpublishing. com Blackwell Publishing: No part of this article may be reproduced without the permission of articles are free 12 months after publication. Experimental Physiology . http://ep.physoc. org/subscriptions go to Experimental Physiology to Society. It has been published continuously since 1908. To subscribe is a publication of The Physiological Experimental Physiology
Optimization of MPI collective communication on BlueGene/L systems

BlueGene/L is currently the world's fastest supercomputer. It consists of a large number of low power dual-processor compute nodes interconnected by high speed torus and collective networks, Because compute nodes do not have shared memory, MPI is the the natural programming model for this machine. The BlueGene/L MPI library is a port of MPICH2.In this paper we discuss the implementation of MPI collectives on BlueGene/L. The MPICH2 implementation of MPI collectives is based on point-to-point communication primitives. This turns out to be suboptimal for a number of reasons. Machine-optimized MPI collectives are necessary to harness the performance of BlueGene/L. We discuss these optimized MPI collectives, describing the algorithms and presenting performance results measured with targeted micro-benchmarks on real BlueGene/L hardware with up to 4096 compute nodes.
Risk factors for prolonged mechanical ventilation after surgical repair of congenital heart disease.

OBJECTIVE The purpose of this study was to determine factors contributing to prolonged mechanical ventilation in children following surgery for congenital heart defects. DESIGN Prospective cohort trial. SETTING Critical Care Unit. "Ignacio Chávez" National Heart Institute, México; from January to December 2000. PATIENTS A total of 318 consecutive patients < 18 years old who underwent cardiovascular surgical procedures for congenital heart defects were enrolled in this study. Of these, 297 patients were admitted to the intensive care unit with respiratory support and 2.8% required prolonged mechanical ventilation (MV) > 120 hours. MEASUREMENTS AND MAIN RESULTS Patients with cardiac failure had MV time of 214 +/- 200 hours, whereas those without it had MV time of 33 +/- 73 hours (p > 0.001). Patients with severe pulmonary hypertension had MV time of 160 +/- 176 hours, while those who did not had MV time of 47 +/- 105 hours (p < 0.001). Twenty-four patients (8.5%) had extubation failure, in 79% them due to hemodynamic alteration during the respiratory support time of 277 +/- 188 hours versus the rest of the group with MV time of 41 +/- 92 hours (p < 0.001). Factors associated with prolonged MV (> 120 hours) were: patients ages of < 1 year, pulmonary hypertension, and cardiac failure, and represented the greatest risk (90%, CI 58 to 99) of prolonging MV. Mortality rate was 34% for patients with prolonged MV. Times of aortic clamping and cardiopulmonary bypass were not significant risk factors for prolonged respiratory support. CONCLUSION Patients ages of < 1 year old, pulmonary hypertension, and cardiac failure were significant risk factors for prolonged respiratory support.
Intravenous thrombolysis in acute ischemic stroke after dabigatran reversal with idarucizumab – a case report

Much excitement has been generated with the approval of idarucizumab, a humanized monoclonal antigen‐binding antibody fragment that is capable of reversing the anticoagulant activity of dabigatran. Here, we describe our initial experience of using tissue plasminogen activator (tPA) in an acute posterior circulation ischemic stroke after dabigatran reversal with idarucizumab. Both treatments were well tolerated and no hemorrhagic or procoagulatory complications were observed. We propose that the option of dabigatran reversal needs to be considered for contemporary treatment concepts of acute ischemic stroke.
Control of a quadruped walking robot based on biologically inspired approach

In this paper, a new biomimetic control method for a quadruped walking robot is proposed. The method is derived by the observation of the gravity load receptor and stimulus- reaction mechanism of quadrupeds' locomotion, and the study of the stances on walking and energy efficiency. Though the controller is simple, it provides a useful framework for controlling a quadruped walking robot. In particular, by introducing a new rhythmic pattern generator the heavy computational burden to be paid on solving kinematics is relieved. The effectiveness of the proposed method is validated via a dynamic simulation and experimental works in a quadruped walking robot, called AiDIN(Artiflcial Digitigrade for Natural Environment).
Sustainable development and international distribution: Theory and application to rainforests as carbon sinks

A situation is analysed in which two countries negotiate the financing of the incremental costs which accrue if one of them switches from a non-sustainable onto a sustainable development path. The other country's incentive to pay arises as it benefits from the developing country's environmental resources, but at an ever declining rate as long as development remains non-sustainable. The paper shows that such negotiations induce a redistribution of income in favour of the developing country which in general will exceed incremental costs. The paper also derives conditions under which the developing country has an incentive to get on a less sustainable path in the pre-agreement phase. In an application to the protection of tropical rainforests as carbon sinks it is shown that North to South redistribution of welfare would indeed be substantial. However, despite these transfer payments in excess of incremental costs the North would still gain enormously in efficiency terms from the use of the carbon sink option.
On the Distribution of Roots of Polynomials

1. We start by explaining two groups of theorems and we shall derive both from a common source. P. Bloch and G. P6lya' investigated first the question of giving an upper estimation of the number R of real roots of (1.1) f(z) = UIJ + Olc? T +. They proved that the number of real roots is* <-41G, $1 n log log n log n * A few years later Erhardt Schmidt3 proved the sharper inequality and the still sharper one RZ 6 A& /. ~'>n log F (1.2)
Edge Detection Method Based on Multi-Expert Information Fusion

This article presents an information fusion method for edge detection based on multi-expert. There are many methods of edge detection. Each of the methods is regarded as an expert, and every expert has its different detection result because of the different ideas and approaches. It is difficult to determine which result we should choose, because there is no objective standard of choice. PCA is applied to these results. Some components are chosen according to the actual situation. We fuse the information of these chosen components, and derive the single detection result based on multi-expert. This method solves the inconsistency of different experts response. The experiments show the results obtained with this method, both noiseless image and noisy image, and these results are very satisfactory. Keywords-edge detection; expert; information fusion; principle component analysis
Beyond Feeling: Chronic Pain Hurts the Brain, Disrupting the Default-Mode Network Dynamics

Chronic pain patients suffer from more than just pain; depression and anxiety, sleep disturbances, and decision-making abnormalities (Apkarian et al., 2004a) also significantly diminish their quality of life. Recent studies have demonstrated that chronic pain harms cortical areas unrelated to pain (Apkarian et al., 2004b; Acerra and Moseley, 2005), but whether these structural impairments and behavioral deficits are connected by a single mechanism is as of yet unknown. Here we propose that long-term pain alters the functional connectivity of cortical regions known to be active at rest, i.e., the components of the “default mode network” (DMN). This DMN (Raichle et al., 2001; Greicius et al., 2003; Vincent et al., 2007) is marked by balanced positive and negative correlations between activity in component brain regions. In several disorders, however this balance is disrupted (Fox and Raichle, 2007). Using well validated functional magnetic resonance imaging (fMRI) paradigms to study the DMN (Fox et al., 2005), we investigated whether the impairments of chronic pain patients could be rooted in disturbed DMN dynamics. Studying with fMRI a group of chronic back pain (CBP) patients and healthy controls while executing a simple visual attention task, we discovered that CBP patients, despite performing the task equally well as controls, displayed reduced deactivation in several key DMN regions. These findings demonstrate that chronic pain has a widespread impact on overall brain function, and suggest that disruptions of the DMN may underlie the cognitive and behavioral impairments accompanying chronic pain.
Aspects Influencing Trustworthiness In Service Oriented Environments

Transactions have moved away from faceto- face encounters to more being on the Internet. The infrastructure for the business and information exchange activities could be client-server, peer-to-peer (P2P), or mobile networks. In this paper we refer to ‘peer’ as an entity involved in a transaction. Trust between two interacting peers involved in an electronic transaction is a major issue that needs to be addressed in order to make the internet a safe medium for carrying out transactions. In this paper, we propose the aspects that can influence the trustworthiness assigned to the trusted peer. Furthermore we catalogue these factors into three classes and discuss the relationship between these factors.
A Passive-Aggressive Algorithm for Semi-supervised Learning

In this paper, we proposed a novel semi-supervised learning algorithm, named passive-aggressive semi-supervised learner, which consists of the concepts of passive-aggressive, down-weighting, and multi-view scheme. Our approach performs the labeling and training procedures iteratively. In labeling procedure, we use two views, known as teacher's classifiers for consensus training to obtain a set of guessed labeled points. In training procedure, we use the idea of down-weighting to retrain the third view, i.e., student's classifier by the given initial labeled and guessed labeled points. Based on the idea of passive-aggressive algorithm, we would also like the new retrained classifier to be held as near as possible to the original classifier produced by the initial labeled data. The experiment results showed that our method only uses a small portion of the labeled training data points, but its test accuracy is comparable to the pure supervised learning scheme that uses all the labeled data points for training.
Deep Observations with the Parkes 21-cm Multibeam System

Abstract We report on a preliminary analysis of a 5600 sec per point survey of 32 square degrees in Centaurus, carried out with the Parkes 13-beam system. The signal-to-noise ratio is found to improve as for the whole integration. We have detected 102 HI sources between +250 and +12,700 km s−1 either by eye or by using the new galaxy-finding algorithm PICASSO. Over half of these are new HI detections. Around a dozen of these are not associated with catalogued galaxies and, in two of these cases, we have not identified an optical counterpart on the Digitized Sky Survey. Arguments are put forward to explain why deep integrations are needed to find low surface brightness objects.
Adaptive Energy-Bounding Approach for Robustly Stable Interaction Control of Impedance-Controlled Industrial Robot With Uncertain Environments

Even though impedance control approaches are useful for robot interaction control, they can guarantee stability only for the assumed range of the environments. This paper presents a new adaptive energy-bounding approach (EBA) that can maintain a desired contact force at steady state while guaranteeing robust contact stability for impedance-controlled industrial robots that are contacting with very uncertain environments beyond the assumed range of the environments. The proposed adaptive EBA that is applied to impedance-controlled industrial robots interacting with incompletely specified real environments is an extension of the haptic EBA, which was previously developed for stable haptic interaction with virtual environments. Moreover, the adaptive EBA estimates online control parameters to improve performance while assuring stability for the system. Theoretical analyses on the performance and experimental results demonstrate the effectiveness of the proposed approach.