Miracle-dz/UniFAR-FTUs huggingface dataset:
ACCF/AHA clinical competence statement on cardiac imaging with computed tomography and magnetic resonance: a report of the American College of Cardiology Foundation/American Heart Association/American College of Physicians Task Force on Clinical Competence and Training.

ACCF/AHA Clinical Competence Statement on Cardiac Imaging With Computed Tomography and Magnetic Resonance A Report of the American College of Cardiology Foundation/ American Heart Association/American College of Physicians Task Force on Clinical Competence and Training Developed in Collaboration With the American Society of Echocardiography, American Society of Nuclear Cardiology, Society of Atherosclerosis Imaging, and the Society for Cardiovascular Angiography & Interventions Endorsed by the Society of Cardiovascular Computed Tomography
How Do Novice Art Teachers Define and Implement Meaningful Curriculum?

Four researchers collaborated on this qualitative case study that examined 11 first-year novice art teachers’ understanding and implementation of meaningful curriculum. Participants were selected through a criterion method sampling strategy; the subjects were employed in rural, urban, and suburban public school districts. In order to conduct a cross-site analysis of the results of the study, researchers conducted three to four structured interviews during the academic year. Results indicate that the novice teachers’ definitions and implementation of meaningful curriculum emphasized connecting art lessons to students’ lives and culture. Novice teachers were concerned about the quality of artwork their students produced and were committed to building trust with their students.
A Tempo Feature via Modulation Spectrum Analysis and its Application to Music Emotion Classification

This paper proposes a tempo feature extraction method based on the long-term modulation spectrum analysis. To transform the modulation spectrum to a condensed feature vector, the log-scale modulation frequency coefficients are introduced. This idea aims at averaging the modulation frequency energy via the constant-Q filter-banks. Further it is pointed out that the feature can be extracted directly from the perceptually compressed data of digital music archives. To verify the effectiveness of the feature and its utility to music applications, the feature vector is used in a music emotion classification system. The system consisting two layers of Adaboost classifiers. In the first layer the conventional timbre features are employed. Then by adding the tempo feature in the second layer, the classification precision is improved dramatically. By this way the discriminability of the classifier based on the given features can be exploited extremely. The system obtains high classification precision on a small corpus. It proves that the proposed feature is very effective and computationally efficient to characterize the tempo information of music
Reaching in clutter with whole-arm tactile sensing

Clutter creates challenges for robot manipulation, including a lack of non-contact trajectories and reduced visibility for line-of-sight sensors. We demonstrate that robots can use whole-arm tactile sensing to perceive clutter and maneuver within it, while keeping contact forces low. We first present our approach to manipulation, which emphasizes the benefits of making contact across the entire manipulator and assumes the manipulator has low-stiffness actuation and tactile sensing across its entire surface. We then present a novel controller that exploits these assumptions. The controller only requires haptic sensing, handles multiple contacts, and does not need an explicit model of the environment prior to contact. It uses model predictive control with a time horizon of length one and a linear quasi-static mechanical model. In our experiments, the controller enabled a real robot and a simulated robot to reach goal locations in a variety of environments, including artificial foliage, a cinder block, and randomly generated clutter, while keeping contact forces low. While reaching, the robots performed maneuvers that included bending objects, compressing objects, sliding objects, and pivoting around objects. In simulation, whole-arm tactile sensing also outperformed per-link force-torque sensing in moderate clutter, with the relative benefits increasing with the amount of clutter.
Biogenic 2‐methyl‐3‐buten‐2‐ol increases regional ozone and HOx sources

We present the first regional‐scale chemistry simulation investigating the effects of biogenic 2‐methyl‐3‐buten‐2‐ol (MBO) emissions on air quality. In a central California model domain, MBO emissions have a distinctly different regional pattern than isoprene but have similar daily maxima of about 5 mg m−2 hr−1. MBO oxidation causes an increase in ozone, formaldehyde, acetone and consequently hydrogen radical production (PHOx). The addition of MBO increases the daily maximum ozone as much as 3 ppb near source regions (2–5% in rural areas) and as much as 1 ppb in the Central Valley. Formaldehyde concentrations increase by as much as 1 ppb (40%) over the Sierra Nevada Mountains, increasing the production of HOx by 10–20% and accelerating local chemistry. This indicates that inclusion of MBO and other biogenic oxygenated emissions in regional simulations in the western and southeastern United States is essential for accurate representation of ozone and HOx.
Localizing Bugs in Program Executions with Graphical Models

We devise a graphical model that supports the process of debugging software by guiding developers to code that is likely to contain defects. The model is trained using execution traces of passing test runs; it reflects the distribution over transitional patterns of code positions. Given a failing test case, the model determines the least likely transitional pattern in the execution trace. The model is designed such that Bayesian inference has a closed-form solution. We evaluate the Bernoulli graph model on data of the software projects AspectJ and Rhino.
Outage probability and BER of switch-and-stay combining in two-way relay systems with analog network coding

In this paper, switch-and-stay combining (SSC) is considered in two-way relay systems with amplify-and-forward (AF) relays, among which one is activated to assist the information exchange between two sources. We assume that the two-way relay system operates in the analog network coding (ANC) protocol where the communication can only be achieved through the active relay without the direct link. The outage probability and the average bit error rate (BER) for Rayleigh fading channels are studied. In particular, we derive closed-form lower bounds for the outage probability and the average BER, which is tight for different fading conditions. Moreover, we present asymptotic analysis for both the outage probability and the average BER at high signal-to-noise ratio (SNR) region. It is shown that SSC can achieve the full diversity order in two-way relay systems with proper switching thresholds. Numerical and simulation results are also provided to verify the theoretical study.
Framing the Game: Examining Frame Choice in Bargaining.

This article introduces the study of frame choice in negotiation. Here, the selection of a procedural frame is treated as a dependent variable-a choice that bargainers make in addition to determining their offers. The empirical focus of the article is on whether, when given a choice between two alternative versions of the ultimatum bargaining game, negotiators choose the description that maximizes their expected payoffs. For example, in one frame-choice task, negotiators assigned to the Player 1 role were asked to select between framing the game as "Player 1 proposes a division and Player 2 accepts or rejects it" or "Player 1 makes a claim from a common pool and Player 2 makes a counterclaim. " Past research has shown that the second frame leads to higher expected payoffs for Player 1 than does the first. Across four studies and three established framing effects, it is found that participants consistently fail to select the procedural frames that optimize monetary outcomes. Subsequent analyses suggest that this tendency is due to two factors: (a) nonmonetary motivations, such as fairness and respect, that influence frame-choice preferences and (b) cognitive limitations that inhibit the ability to accurately predict the effect of alternative procedural frames on opponents' responses Copyright 2000 Academic Press.
A Permutation Approach to Testing Interactions in Many Dimensions

To date, testing interactions in high dimensions has been a challenging task. Existing methods often have issues with sensitivity to modeling assumptions and heavily asymptotic nominal p-values. To help alleviate these issues, we propose a permutation-based method for testing marginal interactions with a binary response. Our method searches for pairwise correlations which differ between classes. In this manuscript, we compare our method on real and simulated data to the standard approach of running many pairwise logistic models. On simulated data our method finds more significant interactions at a lower false discovery rate (especially in the presence of main effects). On real genomic data, although there is no gold standard, our method finds apparent signal and tells a believable story, while logistic regression does not. We also give asymptotic consistency results under not too restrictive assumptions.
Access: news and blog analysis for the social sciences

The social sciences strive to understand the political, social, and cultural world around us, but have been impaired by limited access to the quantitative data sources enjoyed by the hard sciences. Careful analysis of Web document streams holds enormous potential to solve longstanding problems in a variety of social science disciplines through massive data analysis. This paper introduces the TextMap Access system, which provides ready access to a wealth of interesting statistics on millions of people, places, and things across a number of interesting web corpora. Powered by a flexible and scalable distributed statistics computation framework using Hadoop, continually updated corpora include newspapers, blogs, patent records, legal documents, and scientific abstracts; well over a terabyte of raw text and growing daily. The Lydia Textmap Access system, available through http://www.textmap. com/access, provides instant access for students and scholars through a convenient web user-interface. We describe the architecture of the TextMap Access system, and its impact on current research in political science, sociology, and business/marketing.
System-level analysis of soft error rates and mitigation trade-off explorations

This paper presents a novel system-level analysis of soft error rates (SER) based on the Transaction Level Model (TLM) of a targeted System-On-a-Chip (SoC). This analysis runs 1000x faster than the conventional SoC analysis using a gate-level model. Moreover, it allows accurate prediction in the early design phase of a SoC, when only limited application details are available. Preliminary validation results from accelerated SER tests on the physical system have shown that the analysis can predict the SER with a reasonable accuracy (within 5x of the results from tests on physical systems). This system-level analysis is particularly suitable to handle the black-box models for industrial semiconductor IP libraries. Based on this system-level analysis, we also propose a SE mitigation solution using selective protection of SRAM of a SoC. This solution provides a series of trade-offs between the system dependability and cost (in terms of silicon area).
Error Estimation Models Integrating Previous Models and Using Artificial Neural Networks for Embedded Software Development Projects

In an earlier paper, we established 9 models for estimating errors in a new project. In this paper, we integrate the 9 models into 5 by investigating similarities among the models. In addition, we establish a new model using an artificial neural network (ANN). It is becoming increasingly important for software-development corporations to ascertain how to develop software efficiently, whilst guaranteeing delivery time and quality, and keeping development costs low. Estimating the manpower required by new projects and guaranteeing the quality of software are particularly important, because the estimation relates directly to costs while the quality reflects on the reliability of the corporations. In the field of embedded software, development techniques, management techniques, tools, testing techniques, reuse techniques, real-time operating systems and so on, have already been studied. However, there is little research on the relationship between the scale of the development and the number of errors using data accumulated from past projects. Hence, we integrate the previous models and establish a new model using an artificial neural network (ANN). We also compare the accuracy of the ANN model and the regression analysis models. The results of these comparisons indicate that the ANN model is more accurate than any of the 5 integrated models.
Episodic accretion in magnetically layered protoplanetary discs

We study protoplanetary disc evolution assuming that angular momentum transport is driven by gravitational instability at large radii, and magnetohydrodynamic (MHD) turbulence in the hot inner regions. At radii of the order of 1 AU such discs develop a magnetically layered structure, with accretion occurring in an ionized surface layer overlying quiescent gas that is too cool to sustain MHD turbulence. We show that layered discs are subject to a limit cycle instability, in which accretion onto the protostar occurs in ∼ 10 4 yr bursts with u M ∼ 10 −5 M⊙yr −1 , separated by quiescent intervals lasting ∼ 10 5 yr where u M ≈ 10 −8 M⊙yr −1 . Such bursts could lead to repeated episodes of strong mass outflow in Young Stellar Objects. The transition to this episodic mode of accretion occurs at an early epoch (t ≪ 1 Myr), and the model therefore predicts that many young pre-main-sequence stars should have low rates of accretion through the inner disc. At ages of a few Myr, the discs are up to an order of magnitude more massive than the minimum mass solar nebula, with most of the mass locked up in the quiescent layer of the disc at r ∼ 1 AU. The predicted rate of low mass planetary migration is reduced at the outer edge of the layered disc, which could lead to an enhanced probability of giant planet formation at radii of 1 – 3 AU.
Modellus : Automated Modeling of Complex Data Center Applications

The rising complexity of distributed server applications in enterprise data centers has made the tasks of modeling and analyzing their behavior increasingly difficult. This paper presents Modellus, a novel system for automated modeling of complex data center applications using statistical methods from data mining and machine learning. Modellus can automatically derive models to predict the resource usage of an application and the workload it triggers; these models can be composed to capture multiple dependencies between interacting applications. Model accuracy is maintained by fast, distributed testing, automated relearning of models when they change, and methods to bound prediction errors in composite models. We have implemented a prototype of Modellus, deployed it on a data center testbed, and evaluated its efficacy for modeling and analysis of several distributed server applications. Our results show that this feature-based modeling technique is able to make predictions across several data center tiers, and maintain predictive accuracy (typically 95% or better) in the face of significant shifts in workload composition; we also demonstrate practical applications of the Modellus system to prediction and provisioning of real-world applications.
Feature Extraction on Range Images - A New Approach

Range images can provide an almost 3-dimensional description of a scene. Feature driven segmentation of range images has been primarily used for 3D object recognition, and hence the accuracy of the detected features is a prominent issue. Feature extraction on range images has proven to be a more complex problem than on intensity images due to both the irregular distribution of range image data and the nature of the features that are present in range images. Approaches to range image feature extraction are often scan line based approximations that carry a significant computational overhead and hence are not appropriate for real-time processing. This paper presents a design procedure for scalable first order derivative operators that can be used directly on irregularly distributed data. Hence the method is appropriate for direct use on range image data without the requirement of image preprocessing and could form the basis of algorithms of real-time robotic applications.
Randomly hiding secret data using dynamic programming for image steganography

Data hiding in multimedia systems is a ubiquitous practice encouraging secret communication of highly confidential information among different parties. To accomplish such a task, a steganographic system is to be realized. Adding to the plethora of algorithms designed to hide secret data in images, a new data hiding scheme based on Energy and Cost of the Image has been proposed. Energy of an image describes the relationship between adjacent pixels which is based on its potential. Offshoots of Dynamic Programming are used to estimate the cost of the image and further random traversal is employed to select the pixels in which data is to be embedded. The information in the form of bits is embedded in each of the selected pixel in a predefined manner. The mean square error and peak signal to noise ratio has also been calculated along with structural similarity index to assess the quality of the cover and the obtained stego image. The final results show a remarkable improvement over some of the existing methods in terms of payload capacity, robustness, fidelity and the metrics calculated. With minimum computational time a robust steganography scheme is achieved.
Australia and New Zealand Health Policy Evaluating Health Policy Capacity: Learning from International and Australian Experience

Background: The health sector in Australia faces major challenges that include an ageing population, spiralling health care costs, continuing poor Aboriginal health, and emerging threats to public health. At the same time, the environment for policy-making is becoming increasingly complex. In this context, strong policy capacity – broadly understood as the capacity of government to make "intelligent choices" between policy options – is essential if governments and societies are to address the continuing and emerging problems effectively.
Model-Based Approach to Measuring Quality of Experience

Quantifiable quality measures are necessary for VoIP service providers in order to offer services and be sure to keep users for their services. Existing methods used for evaluating the Quality of Experience (QoE) mostly rely on user survey and scores from the user, which are too subjective and need much processing time and cost. This paper proposes a pentagram model for measuring QoE. The model consists of five factors, including integrality, retainability, availability, usability, and instantaneousness. The experiments show that the proposed model offers better performance in terms of quality measurement than the conventional method.
Masculinity impediments: Internalized masculinity contributes to healthcare avoidance in men and women

Gender beliefs contribute to men’s healthcare avoidance, but little research examines these outcomes in women. This article models healthcare avoidance related to masculine contingencies of self-worth in men and women. Nested path modelling tested relationships between social role beliefs, masculine contingencies of self-worth, barriers to help seeking and avoidance of health care in university and non-university-student adult samples. Results indicated social role beliefs predicted masculine contingencies of self-worth in men but not in women. Regardless of gender, masculine contingencies of self-worth predicted barriers to help seeking, which predicted healthcare avoidance in both men and women. Thus, masculine contingencies of self-worth have downstream consequences for men and women through barriers to help seeking.
Genotypic Variation and Mixtures of Lyme Borrelia in Ixodes Ticks from North America and Europe

Background Lyme disease, caused by various species of Borrelia, is transmitted by Ixodes ticks in North America and Europe. Studies have shown the genotype of Borrelia burgdorferi sensu stricto (s.s.) or the species of B. burgdorferi sensu lato (s.l.) affects the ability of the bacteria to cause local or disseminated infection in humans. Methodology/Principal Findings We used a multilocus PCR electrospray mass spectrometry assay to determine the species and genotype Borrelia from ticks collected in New York, Connecticut, Indiana, Southern Germany, and California and characterized isolates from parts of the United States and Europe. These analyses identified 53 distinct genotypes of B. burgdorferi sensu stricto with higher resolution than ospC typing. Genotypes of other members of the B. burgdorferi sensu lato complex were also identified and genotyped including B. afzelii, B. garinii, B. lusitaniae, B. spielmanii, and B. valaisiana. While each site in North America had genotypes unique to that location, we found genotypes shared between individual regions and two genotypes found across the United States. Significant B. burgdorferi s.s. genotypic diversity was observed between North America and Europe: only 6.6% of US genotypes (3 of 45) were found in Europe and 27% of the European genotypes (3 of 11) were observed in the US. Interestingly, 39% of adult Ixodes scapularis ticks from North America were infected with more than one genotype of B. burgdorferi s.s. and 22.2% of Ixodes ricinus ticks from Germany were infected with more than one genotype of B. burgdorferi s.l. Conclusions/Significance The presence of multiple Borrelia genotypes in ticks increases the probability that a person will be infected with more than one genotype of B. burgdorferi, potentially increasing the risks of disseminated Lyme disease. Our study indicates that the genotypic diversity of Borrelia in ticks in both North America and Europe is higher then previously reported and can have potential clinical consequences.
An Original Approach for Quantification of Blood Vessels on the Whole Tumour Section

Relative abundance of tumour angiogenesis has been shown to be of clinical relevance in cancers of various locations such as the ovary. Nevertheless, several problems are encountered when quantifying tumour microvessels: (i) as many other tumour markers, vascularity pattern is often heterogeneous within the tumour mass and even within the same histological section. As a consequence, an adequate acquisition method must be developed for accurate field sampling. (ii) Manual microvessel counting is long, tedious and subject to poor reproducibility. Introduction in routine practice requires a fast, reproducible and reliable automatic image processing. In this study we present an original procedure combining a slide scanner image acquisition and a fully automatic image analysis sequence. The slide scanner offers the advantage of recording an image of the whole histological section for subsequent automatic blood vessel detection and hot spot area location. Microvessel density and surface fraction were measured for the whole section as well as within hot spots. Different immunostaining methods were tested in order to optimise the procedure. Moreover, the method proposed was submitted to a quality control procedure, with reference to interactive identification of microvessels at scanner level. This experiment showed that 93 to 97% of blood vessels were detected, according to the staining protocol used. Colour figures can be viewed on http://www.esacp. org/acp/2003/25‐2/kim.htm.