Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved visualization of non‐transmural scar using slice‐selective inversion‐recovery delayed contrast‐enhanced MRI: a preliminary report

Delayed contrast‐enhanced MRI (ce‐MRI) pulse sequence is a promising modality for the assessment of myocardial viability. However, conventional ce‐MRI using a non‐selective inversion recovery (IR) pulse can often yield poor edge definition or contrast‐to‐noise ratio (CNR) between the non‐transmural scar and blood (i.e. the blood and scar appear isointense). Subtraction and multicontrast ce‐MRI methods can be used to improve the CNR between the non‐transmural scar and blood, but they require two image acquisitions. The authors have developed a single‐acquisition ce‐MRI pulse sequence that utilizes a slice‐selective IR pulse to generate bright‐blood contrast using inflow effects for an improved edge definition between the non‐transmural scar and blood. Six patients with myocardial infarction were imaged at 1.5 T using both non‐selective and slice‐selective IR ce‐MRI acquisitions with identical imaging parameters. The CNR between the non‐transmural scar and normal myocardium was not different between the two acquisitions. The CNR between the blood and non‐transmural scar (16.9 ± 12.3 versus 3.2 ± 7.9; p < 0.001) was significantly higher for the slice‐selective IR acquisition than for the non‐selective IR acquisition. This study demonstrates the feasibility of using a slice‐selective IR pulse to improve the visualization of a non‐transmural scar in ce‐MRI, without increasing the acquisition time. Copyright © 2006 John Wiley & Sons, Ltd.
Eye movements and the detection of sleep onset.

The convergence of behavioral, EEG, and respiratory measures has been shown to increase the accurate detection of sleep onset (SO) (Ogilvie, 1985; Ogilvie & Wilkinson, 1984). The present investigation used a behavioral response (BR) measure and standard EEG indices to examine slow eye movement (SEM) activity during the transition from wakefulness to sleep. Several methods of scoring and assessing slow eye movements were employed in order to determine their usefulness as an index in the detection of sleep onset. Correlations between SEM activity and behavioral and EEG sleep stages were low to moderate. In multiple regression analyses, slow eye movements were shown to be a fairly stable but less powerful predictor of sleep onset than either behavioral or EEG measures. The data confirmed earlier observations linking the appearance of slow rolling eye movements with drowsiness and the disappearance of them with the beginning of behaviorally defined sleep. In most people this pattern is consistent enough to be useful in studying sleep onset. The applicability of this measure as a co-indicator of sleep onset was discussed.
Statistical modeling of low-frequency noise in MOSFETs

The low-frequency noise in deep sub-micron MOSFETs is studied, with emphasis on statistical modeling. A simple and compact modeling approach, based on the error propagation formulation is presented. The physics-related parameters which cause statistical fluctuations in noise performance between devices are detailed. The model is compared to experimental data, and the limitations of the modeling approach are discussed.
Application of high-throughput computing in bioinformatics

We describe the challenges faced when developing a Linux/PC–based cluster to apply bioinformatics algorithms to the rapidly increasing raw genomics data available. The calculations, which take around two months to complete, result in a powerful resource that can be used for data mining–most obviously for the human genome. Our current infrastructure consists of a 1314 node cluster with 1734 processors supporting both production and research. This paper highlights the problems in achieving high data throughput with such systems and shows that raw computer power is only one component of a complex problem.
Music sparse decomposition onto a MIDI dictionary of musical words and its application to music mood classification

Most of the automated music analysis methods available in the literature rely on the representation of the music through a set of low-level audio features related to temporal and frequential properties. Identifying high-level concepts, such as music mood, from this "black-box" representation is particularly challenging. Therefore we present in this paper a novel music representation that allows gaining an in-depth understanding of the music structure. Its principle is to decompose sparsely the music into a basis of elementary audio elements, called musical words, which represent the notes played by various instruments generated through a MIDI synthesizer. From this representation, a music feature is also proposed to allow automatic music classification. Experiments driven on two music datasets have shown the effectiveness of this approach to represent accurately music signals and to allow efficient classification for the complex problem of music mood classification.
Nonlinear Modeling of Switched Reluctance Motor Based on BP Neural Network

Due to highly nonlinear characteristics of switched reluctance motor (SRM), an accurate nonlinear model is the key to minimize torque ripple by optimum phase current profiling. After static torque characteristics of SRM having been measured by DSP, the inverse model of torque is developed based on BP neural network The networks are trained with several improved algorithm. It is found that for the nonlinear model of SRM, the Levenberg-Marquardt (LM) algorithm has faster convergence and more accuracy than the other techniques on BP neural network Compared with experimental dado, accuracy of the inverse model of torque for SRM based on BP neural network with LM algorithm is proved With this model, the torque ripple minimization can be achieved by optimum profiling of the phase current based on instantaneous torque control. Simulation results verify the feasibility of this torque ripple minimization technique.
The impact of protest responses in choice experiments: an application to a Biosphere Reserve Management Program

Aim of study: To identify protest responses and compute welfare estimates with and without the inclusion of such responses using follow-up statements in a choice experiment exercise. To our knowledge, this is one of the first empirical applications that, following the conventional treatment used in contingent valuation methodology, explicitly deals with the treatment and identification of protest responses in choice experiments. Area of study: the Eo, Oscos y Terras de Buron Biosphere Reserve sited between the regions of Galicia and Asturias. We are interested in the influence of such responses on preference elicitation for alternative management actions in this Reserve. Materials and methods: A face-to-face survey conducted in a sample of residents and non-residents of this Reserve. In total, more than 450 surveys were collected. Main results show that protest responses are fairly common in choice experiments, and their analysis affects the statistical performance of the empirical models as well as the valuation estimates. In fact, when the sample is corrected by protest responses, its size decreases to 303 individuals. Furthermore, we can observe that protest responses are triggered by a less positive attitude towards the wolf. Research highlight: Protest responses are a common issue in choice experiments and, therefore, future exercises should consider them explicitly, as earlier contingent valuation studies have. Key words: Biosphere Reserve; choice experiments; protest responses; willingness to pay.
Endogenous Mediator Selection: A Source of Inefficiency in Bargaining

Mediation can reduce the risk of conict in situations where the bargaining failure is due to asymmetric information. But if the parties can choose a mediator, will they choose the mediator who seeks to minimize the probability of conict? In this paper, I consider the endogenous selection of a mediator in a two-person bargaining problem
Turning Assault into a “Harmless Prank”—Teenage Perspectives on Happy Slapping

The article describes the ways in which 41 adolescents from three large English cities discussed the phenomenon of happy slapping, which is typically defined as recording a physical assault on an unsuspecting victim on a camera-enabled phone for Internet upload. Using discourse analysis, the construal of motivations for its creation and watching is explored, elaborating on social, cultural, and legal implications. The identified repertoires (creation of comedy, denial of grievous bodily harm, accomplice-witness ambiguity, and reflection of postmodern culture) caution against attributing happy slapping just to boredom, as the mainstream British press does and puts spotlight on other factors, like seeking originality and keeping “pranks” under control. Concluding with the apparent similarities between the discursive worlds inhabited by unconvicted adolescents and convicted offenders, this study provides a theoretical platform for further research on the subtle and intriguing overlap.
Climate Change, Energy and Social Preferences on Policies: Exploratory Evidence for Spain

Spain faces a complex situation regarding its climate change policies. On the one hand, greenhouse gas emissions have shown an important increase since 1990, being far from the Kyoto commitments. On the other hand, Spain is likely to suffer important impacts from climate change. However, there has been a rather limited application of corrective policies, particularly in the field of energy prices. Indeed, although Spanish citizens generally show a large concern towards climate change, price increases in energy goods have been traditionally opposed. In this paper we try to offer an explanation to this phenomenon, and a possible hint for future policies in the field, by showing how Spanish households strongly favour the application of a green electricity program that makes electricity more expensive to reduce carbon dioxide emissions. In particular, with data from a phone survey representative of the Spanish population, the mean willingness to pay per month and household is 29.91€ over the current electric bill. Our results also show that younger individuals who live in the Mediterranean area are more likely to pay for this green electricity program.
Robotic-Assisted Gait Training and Restoration

ABSTRACTThe past two decades have seen the introduction of and a strong growth in the availability of rehabilitation interventions that are based on the use of robotics. A major driving factor has been the advancement of technology, with faster, more powerful computers, new computational approaches, as well as increased sophistication of motors and other electro mechanical components. These advancements in technology have not been the only factor propelling these new rehabilitation interventions. During the same period, a strong growth in the understanding of neuroplasticity and motor learning has also been witnessed. Although there is still much to learn, comprehension of how new skills are acquired, or old ones are relearned, is evolving at a fast pace. Much of this improved understanding can be linked to the advancement of central nervous system imaging as well as techniques for studying changes at the cellular or molecular level. In this review, the authors present the notion that an ever-advancing understanding of neuroplasticity and motor learning can provide a theoretical basis for the clinical use of rehabilitation robotics as applied to enhancing mobility. Specifically focusing on locomotor training after injury to the central nervous system, these principles can provide guidance to clinicians on how to structure their interventions to potentially promote or accelerate functional recovery in their patients. Several types of existing robotic devices to assist walking that are currently available for use in the clinic, as well as their advantages and limitations, will be discussed.
Speech Recognition at 1-Year Follow-Up in the Childhood Development after Cochlear Implantation Study: Methods and Preliminary Findings

The Childhood Development after Cochlear Implantation (CDaCI) study is a longitudinal multicenter investigation designed to identify factors influencing spoken language in young deaf children with cochlear implants. Normal-hearing peers serve as controls. As part of a comprehensive evaluation battery, a speech recognition hierarchy was designed to assess how well these children recognize speech stimuli across developmental stages. Data were analyzed for the earliest measures in 42 pairs of children reaching 1 year of follow-up. A number of children in the cochlear implant group who met criteria for testing approached levels of performance similar to the normal-hearing controls, and some could identify sentences in competition. These results demonstrate the responsiveness of the speech recognition hierarchy in tracking emergent skills from a sample of the CDaCI cohort.
Prevalence of Glaucoma in Treated Multibacillary Hansen Disease

PurposeTo determine the prevalence of glaucoma in a population of patients with multibacillary Hansen disease who had completed treatment. Patients and MethodsThe authors examined 386 of 446 patients with treated multibacillary Hansen disease residing in a geographically limited area. A complete ophthalmic examination including slit-lamp, applanation tonometry, gonioscopy, ophthalmoscopy, and stereobiomicroscopic examination of the optic disc was performed in all subjects. Glaucoma suspects were invited to the base hospital for further examination including automated perimetry. ResultsThe overall prevalence of glaucoma was 3.6% (CI 1.9–5.3); 1.3% had primary open-angle glaucoma, 7% were primary angle-closure suspects (occludable angles), 1.8% had primary angle-closure glaucoma, and 0.5% had secondary glaucoma. ConclusionThe prevalence of primary glaucoma in patients with treated multibacillary Hansen disease was similar to that in the general population, and secondary glaucoma was rare.
Delay-dependent dynamic output feedback control for uncertain stochastic systems with time-varying delay

In this paper a dynamic output feedback control approach is presented for uncertain stochastic systems with time-varying delays. By employing a new Lyapunov functional, Lyapunov variable and some slack matrices, a convex LMI based delay-dependent sufficient condition was presented such that asymptotical stability condition in the mean square sense for the closed-loop system and so-called NP hard problem is dealt. A numerical example has demonstrated the effectiveness of the proposed approach.
Are Optimistic Repatriates More Hardy and Resilient

Abstract : Previous research conducted by the RE Mitchell Center for Prisoner of War Studies (REMC) has concluded that optimism proved to be the strongest predictor of health and resilience in a group of Vietnam era Repatriated Prisoners of War (RPWs). Optimism is associated with increased positive psychological health in those afflicted by extreme trauma or illness (Segovia et. al, 2012). In the follow-up study (Segovia et. al, 2015), optimism measured at repatriation was again an excellent predictor of a composite measure of psychological (9 component measures) and physical (9 component measures) health. Further studies measured psychological resilience and individual components of hardiness as a mediating factor, but did not study the relationship of optimism or pessimism on resilience and hardiness. The aim of this study is to exploit whether optimists are more hardy and resilient as compared to a pessimist.
Forecasting Realized Volatility with Linear and Nonlinear Models

In this paper we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 indexes. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high frequency intra-day returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analyzed in the paper.
Non-linear Force-free Modeling Of Coronal Magnetic Fields

We compare a variety of nonlinear force-free field (NLFFF) extrapolation algorithms, including optimization, magneto-frictional, and Grad-Rubin-like codes, applied to a solar-like reference model. The model used to test the algorithms includes realistic photospheric Lorentz forces and a complex field including a weakly twisted, right helical flux bundle. The codes were applied to both forced “photospheric” and more force-free “chromospheric” vector magnetic field boundary data derived from the model. When applied to the chromospheric boundary data, the codes are able to recover the presence of the flux bundle and the field’s free energy, though some details of the field connectivity are lost. When the codes are applied to the forced photospheric boundary data, the reference model field is not well recovered, indicating that the combination of Lorentz forces and small spatial scale structure at the photosphere severely impact the extrapolation of the field. Preprocessing of the forced photospheric boundary does improve the extrapolations considerably for the layers above the chromosphere, but the extrapolations are sensitive to the details of the numerical codes and neither the field connectivity nor the free magnetic energy in the full volume are well recovered. The magnetic virial theorem gives a rapid measure of the total magnetic energy without extrapolation, though, like the NLFFF codes, it is sensitive to the Lorentz forces in the coronal volume. Both the magnetic virial theorem and the Wiegelmann extrapolation, when applied to the preprocessed photospheric boundary, give a magnetic energy which is nearly equivalent to the value derived from the chromospheric boundary, but both underestimate the free energy above the photosphere by at least a factor of two. We discuss the interpretation of the preprocessed field in this context. When applying the NLFFF codes to solar data, the problems associated with Lorentz forces present in the low solar atmosphere must be recognized: the various codes will not necessarily converge to the correct, or even the same, solution. † On 2007/07/07, the NLFFF team was saddened by the news that Tom Metcalf had died as the result of an accident; we remain grateful for having had the opportunity to benefit from his unwavering dedication to the problems encountered in attempting to understand the Sun’s magnetic field; Tom had completed this paper several months before his death, leading the team through the many steps described above. c © 2007 Springer Science + Business Media. Printed in the USA. paper.tex; 3/12/2007; 8:28; p.1
Canadian Institutes of Health Research-Institute of Aging: Profi le Harmonizing Data for Collaborative Research on Aging: Why Should We Foster Such an Agenda?

99 (2012) doi:10.1017/S0714980811000729 95 Introduction Despite longstanding awareness that the aging process is inextricably linked to the multifaceted changes occurring throughout an individual’s lifetime (from the level of the cell, to individual psychological and behavioral factors, and to broad social contexts), a clear picture of all relevant interactions and their combined effects has not yet emerged. Furthermore, impacts of the complex interactions between biological, psychological, environmental, and social factors can take years to manifest, bringing additional challenges to the development of studies investigating this multifaceted picture. Despite these challenges, recent advances in science and technology (e.g., capacity to generate genotypes at very low cost, and the development of specialist measures adapted to elderly populations) now let us look forward to promising new avenues for research. However, to advance our understanding of the causal pathways leading to both adverse events and favorable outcomes for today’s and tomorrow’s seniors, it is essential to invest in infrastructures that enable the ongoing collection of a wide range of information and are constructed to support the next generation of research potentials and requirements. The Canadian Longitudinal Study on Aging (CLSA) (Raina et al., 2009 ) is an example of a study that will provide such infrastructure in Canada.
Nomenclature of Major Antimicrobial-Resistant Clones of Streptococcus pneumoniae Defined by the Pneumococcal Molecular Epidemiology Network

ABSTRACT The emergence of disease caused by penicillin-resistant and multidrug-resistant pneumococci has become a global concern, necessitating the identification of the epidemiological spread of such strains. The Pneumococcal Molecular Epidemiology Network was established in 1997 under the auspices of the International Union of Microbiological Societies with the aim of characterizing, standardizing, naming, and classifying antimicrobial agent-resistant pneumococcal clones. Here we describe the nomenclature for 16 pneumococcal clones that have contributed to the increase in antimicrobial resistance worldwide. Guidelines for the recognition of these clones using molecular typing procedures (pulsed-field gel electrophoresis, BOX-PCR, and multilocus sequence typing) are presented, as are the penicillin-binding profiles and macrolide resistance determinants for the 16 clones. This network can serve as a prototype for the collaboration of scientists in identifying clones of important human pathogens and as a model for the development of other networks.
Unhealthy Weight Gain During Treatment for Alcohol and Drug Use in Four Residential Programs for Latina and African American Women

Weight gain in women (n = 52) in four alcohol and drug user residential treatment programs in Boston, Massachusetts, was studied in 2004 through focus groups (n = 52) and weekly weights (n = 10). Focus group theme analyses revealed that weight gain was primarily attributed to availability of food and lack of exercise. Participants were very interested in improving nutrition, diet, and exercise in the programs. Weight gain (mean = 6.4 pounds) occurred in nine women (n = 10) in the first 12 weeks of treatment. The two-dimensional Food Model Chart and the Yale Physical Activity Survey were used. Limitations are noted and future research is suggested.
Automatic quality control of seam puckers based on shadow detection

A novel method performing automatic seam quality control based on visual information is introduced. More specifically, oblique illumination is applied and greyscale images of seam specimens are acquired. The amount of shadowing present in each image is being estimated through dynamic thresholding and first order statistics and is used by a simple linear classifier to estimate the seam quality by means of ordinary least squares (OLS) regression. The proposed method has been evaluated in the case of 112 seam specimens classified by human experts into five discrete quality grades and a correct classification rate of 84.82% has been produced exceeding the experts' average performance. Moreover, in case one grade disagreement is acceptable, the classification results become error free.
Structures of the Bacterial Ribosome in Classical and Hybrid States of tRNA Binding

Two crystal structures indicate how conformational changes in the ribosome assist protein synthesis. During protein synthesis, the ribosome controls the movement of tRNA and mRNA by means of large-scale structural rearrangements. We describe structures of the intact bacterial ribosome from Escherichia coli that reveal how the ribosome binds tRNA in two functionally distinct states, determined to a resolution of ~3.2 angstroms by means of x-ray crystallography. One state positions tRNA in the peptidyl-tRNA binding site. The second, a fully rotated state, is stabilized by ribosome recycling factor and binds tRNA in a highly bent conformation in a hybrid peptidyl/exit site. The structures help to explain how the ratchet-like motion of the two ribosomal subunits contributes to the mechanisms of translocation, termination, and ribosome recycling.