Miracle-dz/UniFAR-FTUs huggingface dataset:
Canadian Thoracic Society Asthma Management Continuum--2010 Consensus Summary for children six years of age and over, and adults.

BACKGROUND/OBJECTIVE To integrate new evidence into the Canadian Asthma Management Continuum diagram, encompassing both pediatric and adult asthma. METHODS The Canadian Thoracic Society Asthma Committee members, comprised of experts in pediatric and adult respirology, allergy and immunology, emergency medicine, general pediatrics, family medicine, pharmacoepidemiology and evidence-based medicine, updated the continuum diagram, based primarily on the 2008 Global Initiative for Asthma guidelines, and performed a focused review of literature pertaining to key aspects of asthma diagnosis and management in children six years of age and over, and adults. RESULTS In patients six years of age and over, management of asthma begins with establishing an accurate diagnosis, typically by supplementing medical history with objective measures of lung function. All patients and caregivers should receive self-management education, including a written action plan. Inhaled corticosteroids (ICS) remain the first-line controller therapy for all ages. When asthma is not controlled with a low dose of ICS, the literature supports the addition of long-acting beta2-agonists in adults, while the preferred approach in children is to increase the dose of ICS. Leukotriene receptor antagonists are acceptable as second-line monotherapy and as an alternative add-on therapy in both age groups. Antiimmunoglobulin E therapy may be of benefit in adults, and in children 12 years of age and over with difficult to control allergic asthma, despite high-dose ICS and at least one other controller. CONCLUSIONS The foundation of asthma management is establishing an accurate diagnosis based on objective measures (eg, spirometry) in individuals six years of age and over. Emphasis is placed on the similarities and differences between pediatric and adult asthma management approaches to achieve asthma control.
Eotaxin: a potent eosinophil chemoattractant cytokine detected in a guinea pig model of allergic airways inflammation

Eosinophil accumulation is a prominent feature of allergic inflammatory reactions, such as those occurring in the lung of the allergic asthmatic, but the endogenous chemoattractants involved have not been identified. We have investigated this in an established model of allergic inflammation, using in vivo systems both to generate and assay relevant activity. Bronchoalveolar lavage (BAL) fluid was taken from sensitized guinea pigs at intervals after aerosol challenge with ovalbumin. BAL fluid was injected intradermally in unsensitized assay guinea pigs and the accumulation of intravenously injected 111In- eosinophils was measured. Activity was detected at 30 min after allergen challenge, peaking from 3 to 6 h and declining to low levels by 24 h. 3-h BAL fluid was purified using high performance liquid chromatography techniques in conjunction with the skin assay. Microsequencing revealed a novel protein from the C-C branch of the platelet factor 4 superfamily of chemotactic cytokines. The protein, "eotaxin," exhibits homology of 53% with human MCP-1, 44% with guinea pig MCP-1, 31% with human MIP-1 alpha, and 26% with human RANTES. Laser desorption time of flight mass analysis gave four different signals (8.15, 8.38, 8.81, and 9.03 kD), probably reflecting differential O- glycosylation. Eotaxin was highly potent, inducing substantial 111In- eosinophil accumulation at a 1-2 pmol dose in the skin, but did not induce significant 111In-neutrophil accumulation. Eotaxin was a potent stimulator of both guinea pig and human eosinophils in vitro. Human recombinant RANTES, MIP-1 alpha, and MCP-1 were all inactive in inducing 111In-eosinophil accumulation in guinea pig skin; however, evidence was obtained that eotaxin shares a binding site with RANTES on guinea pig eosinophils. This is the first description of a potent eosinophil chemoattractant cytokine generated in vivo and suggests the possibility that similar molecules may be important in the human asthmatic lung.
NONLINEAR IDENTIFICATION USING NEURAL NETWORK COMBINED WITH TRAINING BASED ON PARTICLE SWARM OPTIMIZATION

Most processes in industry are characterized by nonlinear and time-varying behavior. In this context, the identification of mathematical models typically nonlinear systems is vital in many fields of engineering. A variety of system identification techniques are applied to the modeling of processes dynamics. Recently, the identification of nonlinear systems by artificial neural networks has been successfully applied. In this paper, an original approach based on radial basis function neural network (RBF-NN) with a training method based on particle swarm optimization (PSO) is proposed as an alternative solution. RBF-NN is considered as a good candidate for the prediction problems due to its rapid learning capacity and, therefore, has been applied successfully to nonlinear time series modeling and nonlinear identification. On the other hand, PSO was inspired by the choreography of a bird flock and can be seen as a distributed behavior algorithm that performs multidimensional search. The RBF-NN model is trained and validated based on the experimental data of a nonlinear process. Finally, simulation results from the performance analysis of RBF-NN are presented and discussed.
SPPEAR: security & privacy-preserving architecture for participatory-sensing applications

Recent advances in sensing, computing, and networking have paved the way for the emerging paradigm of participatory sensing (PS). The openness of such systems and the richness of user data they entail raise significant concerns for their security, privacy and resilience. Prior works addressed different aspects of the problem. But in order to reap the benefits of this new sensing paradigm, we need a comprehensive solution. That is, a secure and accountable PS system that preserves user privacy, and enables the provision of incentives to the participants. At the same time, we are after a PS system that is resilient to abusive users and guarantees privacy protection even against multiple misbehaving PS entities (servers). We address these seemingly contradicting requirements with our SPPEAR architecture. Our full blown implementation and experimental evaluation demonstrate that SPPEAR is efficient, practical, and scalable. Last but not least, we formally assess the achieved security and privacy properties. Overall, our system is a comprehensive solution that significantly extends the state-of-the-art and can catalyze the deployment of PS applications.
Assessing Suitability of Cloud Oriented Platforms for Application Development

The enterprise data centers and software development teams are increasingly embracing the cloud oriented and virtualized computing platforms and technologies. As a result it is no longer straight forward to choose the most suitable platform which may satisfy a given set of Non-Functional Quality Attributes (NFQA) criteria that is significant for an application. Existing methods such as Serial Evaluation and Consequential Choice [1], [2] etc. are inadequate as they fail to capture the objective measurement of various criteria that are important for evaluating the platform alternatives. In practice, these methods are applied in an ad-hoc fashion. In this paper we introduce three application development platforms: 1) Traditional non-cloud 2) Virtualized and 3) Cloud Aware. We propose a systematic method that allows the stakeholders to evaluate these platforms so as to select the optimal one by considering important criteria. We apply our evaluation method to these platforms by considering a certain (non-business) set of NFQAs. We show that the pure cloud oriented platforms fare no better than the traditional non-cloud and vanilla virtualized platforms in case of most NFQAs.
Joint reporting and linear fusion optimization in Collaborative Spectrum Sensing for cognitive radio networks

In this paper, the cooperative spectrum sensing in centralized cognitive radio networks is studied as a three-phase process, composed of local sensing, reporting, and decision/data fusion and a novel approach is proposed to optimize the linear soft combining scheme at the fusion phase jointly with two elements of the reporting phase: i) the number of bits used by each node to quantize the local sensing outcomes, and ii) the power level by which each node reports its sensing outcome to the fusion center. The proposed optimization problem is represented using the conventional false alarm and missed detection probabilities and two straightforward solutions are also provided. Finally, the performance improvement associated with the proposed joint optimization scheme is demonstrated by a set of illustrative simulation results.
Detection of a dark substructure through gravitational imaging

We report the detection of a dark substructure ‐ undetected in the HST-ACS F814W image ‐ in the gravitational lens galaxy SDSSJ0946+1006 (the “Double Einstein Ring”), through direct gravitational imaging. The lens galaxy is of particular int erest because of its relative high inferred fraction of dark matter inside the effective radius. The detection is based on a Bayesian grid reconstruction of the two-dimensional surface density of the galaxy inside an annulus around its Einstein radius. The detection of a small mass concentration in the surface density maps has a strong statistical significance. We confirm this de tection by modeling the substructure with a tidally truncated pseudo-Jaffe density profile; in that case the substructure mass is Msub = (3.51±0.15)×10 9 M⊙, located at (−0.651±0.038, 1.040±0.034)”, precisely where also   
Rotational broadening and Doppler tomography of the quiescent X-ray nova Centaurus X-4

We present high- and intermediate-resolution spectroscopy of the X-ray nova Centaurus X-4 during its quiescent phase. Our analysis of the absorption features supports a K3–K5 V spectral classification for the companion star, which contributes ≃75 per cent of the total flux at Hα. Using the high-resolution spectra we have measured the rotational broadening of the secondary star to be v sin i=43±6 km s-1 and determined a binary mass ratio of q=0.17±0.06. Combining our results for K2 and q with the published limits for the binary inclination, we constrain the mass of the compact object and the secondary star to the ranges 0.49<M1<2.49 M⊙ and 0.04<M2<0.58 M⊙. A Doppler image of the Hα line shows emission coming from the secondary star, but no hotspot is present. We discuss the possible origins of this emission.
Conflits locaux en élevage porcin : jeux d'acteurs, déterminants et enjeux pour la filière et la démocratie de proximité

Dans un contexte de renforcement de la democratie technique et de multiplication des revendications sociales adressees a l'elevage, ce memoire vise a mieux comprendre les controverses liees a l’elevage porcin, en envisageant cette question sous l'angle local d'oppositions a des projets presentes en enquetes publiques. Ce travail s'appuie sur l’etude de dix cas de conflits locaux ayant eu lieu en Bretagne au cours des dix dernieres annees, par des entretiens semi-directifs menes aupres des acteurs des conflits, completes par les rapports d'enquetes publiques et la presse quotidienne regionale. A partir de l'analyse des visions qu’ont les acteurs de l’elevage et des eleveurs porcins, de leurs registres d’argumentation ainsi que des strategies qu’ils adoptent lors des conflits, ce memoire realise une description fine des processus conflictuels, permettant alors d'en identifier des determinants plus generaux et d'elaborer des preconisations visant a favoriser la concertation lors de la conception de projets. Nous montrons que les conflits locaux peuvent finalement etre consideres comme des symptomes de la transformation du mode de decision et d’action publique, tout autant voire davantage que comme des symptomes de l’evolution de l’espace rural et de sa population.
Gender Equality in Educational Achievement: An East-West Comparison

Data on educational access show gender parity of pupils attending primary and secondary schools in transition countries. The first aim of this analysis is to examine whether the gender balance in educational access translates also into gender equality in educational achievement. There are several and very recent international surveys available measuring pupils learning achievement and functional literacy in schools. These surveys are typically analysed in isolation from each other even though they are very different in their design. The second aim of this paper is to evaluate whether we find a robust pattern on gender equality in achievement across different sources: the Trends in International Maths and Science Study (TIMSS), the Programme of International Student Assessment (PISA) and the Programme of International Reading Literacy Study (PIRLS). Besides a comparison of gender differences in mean achievement for transition and OECD countries we discuss alternatives for translating achievement scores into something easily understood. In addition, differences in boys’ and girls’ achievement distributions and determinants of gender inequality will be examined.
Managing Uncertainties in Networks a Network Approach to Problem Solving and Decision Making

Part 1: The Analysis of Uncertainties in Dealing with Complex Problems in Networks 1. Uncertainties in Dealing with Complex Problems in the Network Society 2. Uncertainty about Content: Knowledge Conflicts and Asymmetrical Debates 3. Uncertainty and Process: Problem Solving as Strategic Game 4. Uncertainty and Institutions: Patterns, Rules and Trust 5. Uncertainties and Governments: Old and New Responses 6. Summing Up: Dealing with Uncertainties in Networks Part 2: The Management of Uncertainties in Dealing with Complex Problems in Networks 7. Mapping Uncertainties in Games and Networks 8. Managing Content: Furthering Cross-Frame Reflection and the Creation of Negotiated Knowledge 9. Managing the Game 10. Managing the Network: Strategies for Institutional Design 11. Managing Uncertainties in Networks
Characterization of long-term endogenous cardiac repair in children after heart transplantation.

AIMS Circulating cells repopulate the heart at a very low rate in adult humans. The knowledge about time-dependent cardiac regeneration is very limited and the contribution of circulating cells to cardiomyocytes or vascular cells in children is unknown. This study investigates the endogenous repair capacity and the long-term incorporation of circulating cells in heart-transplanted children. METHODS AND RESULTS Cardiac and endothelial chimerism was detected in endomyocardial biopsies of nine children (age 1 months-14 years) with sex-mismatched heart transplantation by fluorescence in situ hybridization. Time from transplantation to biopsy ranged from 1 month up to 10 years. The extent of repopulating cardiomyocytes was 2.39 +/- 1.54% (range: 0-4.2%) and correlated significantly with the time from transplantation to biopsy sampling (r(2) = 0.69, P = 0.006; n = 9). The calculated contribution of male cardiomyocytes in the female heart per year was 0.36 +/- 0.09%. Consistent with the previous reports, the incorporation of vascular cells was higher compared with cardiomyocytes (14.4 +/- 4.17%), but did not correlate in a time-dependent manner. CONCLUSION Circulating cells contribute to cardiomyocytes and endothelial cells in children after heart transplantation. The incidence of repopulating cardiomyocytes continuously increases in a time-dependent manner ( approximately 4% Y-chromosome(+) cardiomyocytes/10 years) and resembles the cardiac regeneration activity observed in adults.
Visualizing a Personal Social Network of Email Archives For Re-Finding

has become an important communication medium that people routinely rely on to achieve their daily work. However, managing email accounts for life-long communication is not an easy task. Users have different strategies for archiving their messages and have varied understanding and expectations of retrieval and how to use that capability. We have designed and implemented a tool, VisPEAM that applies the benefits of visualization of social network in personal email archive management. This helps users re- find email messages by using people's name, folder and subjects as search criteria. The graphical representation helps users to find their old emails by exploring the social relationships in different folders as well as shows how frequently those people exchange email messages regarding a particular topic. Moreover, the graphic visualization helps people manage their growing collections of email messages with respect to their social relationships.
Differential dopamine receptor D4 allele association with ADHD dependent of proband season of birth

Season of birth (SOB) has been associated with attention deficit hyperactivity disorder (ADHD) in two existing studies. One further study reported an interaction between SOB and genotypes of the dopamine D4 receptor (DRD4) gene. It is important that these findings are further investigated to confirm or refute the findings. In this study, we investigated the SOB association with ADHD in four independent samples collected for molecular genetic studies of ADHD and found a small but significant increase in summer births compared to a large population control dataset. We also observed a significant association with the 7‐repeat allele of the DRD4 gene variable number tandem repeat polymorphism in exon three with probands born in the winter season, with no significant differential transmission of this allele between summer and winter seasons. Preferential transmission of the 2‐repeat allele to ADHD probands occurred in those who were born during the summer season, but did not surpass significance for association, even though the difference in transmission between the two seasons was nominally significant. However, following adjustment for multiple testing of alleles none of the SOB effects remained significant. We conclude that the DRD4 7‐repeat allele is associated with ADHD but there is no association or interaction with SOB for increased risk for ADHD. Our findings suggest that we can refute a possible effect of SOB for ADHD. © 2007 Wiley‐Liss, Inc.
Parallel iterated Runge-Kutta methods and applications

The iterated Runge Kutta IRK method is an iteration scheme for the numerical solu tion of initial value problems IVP of ordinary di erential equations ODEs that is based on a predictor corrector method with an Runge Kutta RK method as corrector Embed ded approximation formulae are used to control the stepsize We present di erent parallel algorithms of the IRK method on distributed memory multiprocessors for the solution of systems of ODEs The parallel algorithms are given in an SPMD single program multiple data programming style where data exchanges are described with appropriate communi cation primitives A theoretical performance analysis and a runtime simulation allow to value the presented algorithms The implementation on the Intel iPSC con rms the predicted runtimes The speedup values strongly depend on the particular system of ODEs to be solved The parallel IRK method is applied to a typical discretization problem the discretized Brusselator equation Application speci c modi cations of the general parallel ODE solver are developed which result in a considerable reduction of the parallel execution time
Adaptive Cloth Simulation

Cloth has traditionally been simulated on a static mesh composed of a uniform grid of nodes. Since a coarse mesh cannot generally capture fine wrinkles, realistic cloth simulation relies on a fine grid of nodes that is expensive to simulate. However, fine wrinkles are often localized to relatively small portions of a mesh. We introduce an adaptive method that locally refines cloth where wrinkles tend to appear and simplifies regions where wrinkles have disappeared. Recent work has produced adaptive methods for simple models of cloth and related simulations. This project extends to more sophisticated models of cloth. In particular, this work introduces an adaptive model supporting implicit integration.
PREVALENCE OF CHAGAS DISEASE AMONG BLOOD DONOR CANDIDATES IN TRIANGULO MINEIRO, MINAS GERAIS STATE, BRAZIL

Despite public health campaigns and epidemiological surveillance activities, Chagas disease remains a major health problem in Latin America. According to data from the World Health Organization, there are approximately 7-8 million people infected with Trypanosoma cruzi worldwide, a large percentage of which in Latin America. This study aims to examine the serological profile of blood donors in blood banks of Hemominas hematology center, in the town of Ituiutaba, Minas Gerais State, Brazil. The study sample consisted of 53,941 blood donors, which were grouped according to gender and age. Sample collections were performed from January 1991 to December 2011, and 277 donors (0.5%) were considered serologically ineligible due to Chagas disease. Analysis of data showed no significant difference between genders. As for age, the highest proportion of ineligible donors was from 40 to 49 years (30%), and there was a positive correlation between increasing age and the percentage of patients seropositive for Chagas disease. Therefore, adopting strategies that allow the safe identification of donors with positive serology for Chagas disease is essential to reduce or eliminate indeterminate serological results.
Achieving application level fairness through utility-based wireless fair scheduling

The increasing number of wireless data users and the deployment of broadband wireless networks have brought the issue of providing fair channel access to the forefront. Wireless fair scheduling algorithms must deal with unique domain-specific issues such as location-dependent and bursty channel error. In the past, a number of scheduling disciplines have been proposed for approximating fluid fair queueing in wireless channels, but using only the ARQ-based link-layer retransmit model. In this work, we generalize past work in three key ways: (a) we use the notion of "utility-based" fair scheduling, wherein the goal of the scheduler is to serve flows in a way that maximizes the aggregate utility of the system, (b) we combine the techniques of FEC and ARQ in a generalized framework in which different scheduling disciplines can be realized by mixing and matching component algorithms within the framework, and (c) we support the notion of "application level fairness" when flows see different channel error probabilities. Specifically, we explore the combination of adaptive FEC and ARQ-based schemes within the utility-based wireless fair scheduling paradigm. We show through simulation and analysis that this combination enables the scheduling disciplines to optimize the aggregate system utility and achieve application level fairness, while handling varying channel errors effectively.
Ant colony optimization using pheromone updating strategy to solve job shop scheduling

Scheduling is considered to be a major task to improve the shop-floor productivity. The job shop problem is under this category and is combinatorial in nature. Research on optimization of job shop problem is one of the most significant and promising areas of optimization. This paper presents an application of the Ant Colony Optimization metaheuristic to job shop problem. The main characteristics of this model are positive feedback and distributed computation. The inspiring source of Ant Colony Optimization is pheromone trail laying and following behavior of real ant. The methods of updating the pheromone have more influence in solving instances of job shop problem. An algorithm is introduced to improve the basic ant colony system by using a pheromone updating strategy. Experiments using well-known bench mark problems show that this approach improves on the performance obtained by the basic ant colony system.