Miracle-dz/UniFAR-FTUs huggingface dataset:
Pericarditis ay-Hospital Treatment of Acute Pericarditis Management Program for Outpatient Therapy

OBJECTIVES We sought to investigate the safety and efficacy of a protocol for acute pericarditis triage and outpatient management of low-risk cases. BACKGROUND Acute pericarditis has generally a brief and benign course after empiric treatment by non-steroidal anti-inflammatory drugs, and routine hospitalization of most patients may be unnecessary. METHODS From January 1996 to December 2001, all consecutive cases of acute pericarditis were evaluated on a day-hospital basis. Patients without clinical poor prognostic predictors (fever 38°C, subacute onset, immunodepression, trauma, oral anticoagulant therapy, myopericarditis, severe pericardial effusion, cardiac tamponade) were considered low-risk cases and assigned to outpatient treatment with high-dose oral aspirin. Patients with poor prognostic predictors or aspirin failure were hospitalized for etiology search and treatment. A clinical and echocardiographic follow-up was performed at 48 to 72 h, 7 to 10 days, 1 month, 6 months, and 1 year. RESULTS Two hundred fifty-four out of 300 (84.7%) patients were selected as low-risk cases. Outpatient treatment was efficacious in 221 out of 254 (87%) cases. Thirty-three out of 254 patients were hospitalized because of aspirin failure. Patients treated on an out-of-hospital basis had no serious complications after a mean follow-up of 38 months (no cases of cardiac tamponade). A higher frequency of recurrences and constriction was recorded in aspirinresistant cases than in aspirin responders (60.6% vs. 10.4% for recurrences and 9.1% vs. 0.5% for constriction, respectively; all p 0.01). CONCLUSIONS A protocol for acute pericarditis triage and outpatient therapy of low-risk cases is safe and efficacious and may reduce management costs. (J Am Coll Cardiol 2004;43:1042–6) © 2004 by the American College of Cardiology Foundation
Chocolate consumption and cardiometabolic disorders: systematic review and meta-analysis

Objective To evaluate the association of chocolate consumption with the risk of developing cardiometabolic disorders. Design Systematic review and meta-analysis of randomised controlled trials and observational studies. Data sources Medline, Embase, Cochrane Library, PubMed, CINAHL, IPA, Web of Science, Scopus, Pascal, reference lists of relevant studies to October 2010, and email contact with authors. Study selection Randomised trials and cohort, case-control, and cross sectional studies carried out in human adults, in which the association between chocolate consumption and the risk of outcomes related to cardiometabolic disorders were reported. Data extraction Data were extracted by two independent investigators, and a consensus was reached with the involvement of a third. The primary outcome was cardiometabolic disorders, including cardiovascular disease (coronary heart disease and stroke), diabetes, and metabolic syndrome. A meta-analysis assessed the risk of developing cardiometabolic disorders by comparing the highest and lowest level of chocolate consumption. Results From 4576 references seven studies met the inclusion criteria (including 114 009 participants). None of the studies was a randomised trial, six were cohort studies, and one a cross sectional study. Large variation was observed between these seven studies for measurement of chocolate consumption, methods, and outcomes evaluated. Five of the seven studies reported a beneficial association between higher levels of chocolate consumption and the risk of cardiometabolic disorders. The highest levels of chocolate consumption were associated with a 37% reduction in cardiovascular disease (relative risk 0.63 (95% confidence interval 0.44 to 0.90)) and a 29% reduction in stroke compared with the lowest levels. Conclusions Based on observational evidence, levels of chocolate consumption seem to be associated with a substantial reduction in the risk of cardiometabolic disorders. Further experimental studies are required to confirm a potentially beneficial effect of chocolate consumption.
The public health relevance of air pollution abatement

Assuming a causal relationship between current levels of air pollution and morbidity/mortality, it is crucial to estimate the public health relevance of the problem. The derivation of air pollution attributable cases faces inherent uncertainties and requires influential assumptions. Based on the results of the trinational impact assessment study of Austria, France, and Switzerland, where prudent estimates of the air pollution attributable cases (mortality, chronic bronchitis incidence, hospital admissions, acute bronchitis among children, restricted activity days, asthma attacks) have been made, influential uncertainties are quantified in this review. The public health impact of smoking, environmental tobacco smoke, and air pollution on the prevalence of chronic cough/phlegm are outlined. Despite all methodological caveats, impact assessment studies clearly suggest that public health largely benefits from better air quality. The studies are selective underestimates as they are strongly driven by mortality, but do not include full quantification of the impact on morbidity and their consequences on quality of life among the diseased and the caregivers. Air pollution abatement strategies are usually political in nature, targeting at policies, regulation and technology in mobile or stationary sources rather than at individuals. It is of note that key clean air strategies converge into abatement of climate change. In general, energy consumption is very closely related to both air pollution and greenhouse gases. The dominant causes of both problems are the excessive and inefficient combustion of fossil fuel. Thus, for many policy options, the benefit of air pollution abatement will go far beyond what prudent health-impact assessments may derive. From a climate change and air pollution perspective, improved energy efficiency and a strong and decisive departure from the “fossil fuel” combustion society is a science-based must. Health professionals must raise their voices in the political decision process to give strong support for clean air policies, both on a national and international level.
Understanding the Impact of Weights Constraints in Portfolio Theory

In this article, we analyze the impact of weights constraints in portfolio theory using the seminal work of Jagannathan and Ma (2003). They show that solving the global minimum variance portfolio problem with some constraints on weights is equivalent to use a shrinkage estimate of the covariance matrix. These results may be easily extended to mean variance and tangency portfolios. From a financial point of view, the shrinkage estimate of the covariance matrix may be interpreted as an implied covariance matrix of the portfolio manager. Using the universe of the DJ Eurostoxx 50, we study the impact of weights constraints on the global minimum variance portfolio and the tangency portfolio. We illustrate how imposing lower and upper bounds on weights modify some properties of the empirical covariance matrix. Finally, we draw some conclusions in the light of recent developments in the asset management industry.
First case of rabbit haemorrhagic disease in Canada: contaminated flying insect, vs. long‐term infection hypothesis

Following the announcement of the first case of rabbit haemorrhagic disease (RHD) in a pet rabbit, housed indoors in Canada for more than 1 year, I submitted an evidence‐based explanation to ProMed explaining how RHD might have caused the death of ‘one’ of the three pet rabbits. I suggested with supporting evidence, that it may have been persistently infected with rabbit haemorrhagic disease virus (RHDV) which may have reactivated to cause the fatal disease. However, in this issue, Peacock et al. have proposed an alternative ‘hypothesis’ for the appearance of RHD in the pet rabbit. They hypothesise that a non‐identified insect or fomite might have become contaminated by a Chinese strain of RHDV somewhere in the US. This insect/fomite then flew or was windborne, from the US to Canada where it entered the house containing three pet rabbits and infected one of them. RHD is non‐endemic and is rarely reported in the US, where it has only been observed in domestic European rabbits, held in rabbitries. My proposal was based on the details provided by ProMed, the veterinary report from Canada, where RHDV has never previously been identified and the epidemiological, ecological and evolutionary history of RHDV which includes serological and phylogenetic evidence that ancestral RHDV lineages circulated before 1984. The flying insect hypothesis of Peacock et al. is based on circumstantial evidence and, I believe, has a lower probability of being correct than my evidence‐based long‐term infection proposal.
A RecB-Like Helicase in Helicobacter pylori Is Important for DNA Repair and Host Colonization

ABSTRACT The human gastric pathogen Helicobacter pylori encounters frequent oxidative and acid stress in its specific niche, and this causes bacterial DNA damage. H. pylori exhibits a very high degree of DNA recombination, which is required for repairing both DNA double-stranded (ds) breaks and blocked replication forks. Nevertheless, few genes encoding components of DNA recombinational repair processes have been identified in H. pylori. An H. pylori mutant defective in a putative helicase gene (HP1553) was constructed and characterized herein. The HP1553 mutant strain was much more sensitive to mitomycin C than the WT strain, indicating that HP1553 is required for repair of DNA ds breaks. Disruption of HP1553 resulted in a significant decrease in the DNA recombination frequency, suggesting that HP1553 is involved in DNA recombination processes, probably functioning as a RecB-like helicase. HP1553 was shown to be important for H. pylori protection against oxidative stress-induced DNA damage, as the exposure of the HP1553 mutant cells to air for 6 h caused significant fragmentation of genomic DNA and led to cell death. In a mouse infection model, the HP1553 mutant strain displayed a greatly reduced ability to colonize the host stomachs, indicating that HP1553 plays a significant role in H. pylori survival/colonization in the host.
Temperature dependence of the emission and capture times of SiON individual traps after positive bias temperature stress

The authors study the statistical properties of individual defects in n-type metal-oxide-semiconductor field-effect transistors (nMOSFETs) using time dependent defect spectroscopy. This technique is based on the analysis of quantized threshold voltage transients observed on nanoscaled p-type metal-oxide-semiconductor field-effect transistors (pMOSFETs) after negative stress and provides the characteristic emission and capture times of individual traps. To complement to previous studies, the authors apply the methodology to SiON nMOSFETs and positive bias temperature stress. The authors demonstrate that the relaxation transients are due to the collective behavior of individual traps. Furthermore, a strong temperature dependence is observed for both emission and capture times. This is incompatible with elastic tunneling theory which is used in trap characterization techniques such as charge pumping, and also in simulations of erase and program transients of nonvolatile memories. The calculated thermal activ.
Structurally-Constrained Relationships between Cognitive States in the Human Brain

The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which such patterns of correlated activity systematically vary across cognitive states. Anatomical white matter connectivity is compared with functional correlations in neural activity measured via blood oxygen level dependent (BOLD) signals. Functional connectivity is separately measured at rest, during an attention task, and during a memory task. We assess these structural and functional measures within previously-identified resting-state functional networks, denoted task-positive and task-negative networks, that have been independently shown to be strongly anticorrelated at rest but also involve regions of the brain that routinely increase and decrease in activity during task-driven processes. We find that the density of anatomical connections within and between task-positive and task-negative networks is differentially related to strong, task-dependent correlations in neural activity. The space mapped out by the observed structure-function relationships is used to define a quantitative measure of separation between resting, attention, and memory states. We find that the degree of separation between states is related to both general measures of behavioral performance and relative differences in task-specific measures of attention versus memory performance. These findings suggest that the observed separation between cognitive states reflects underlying organizational principles of human brain structure and function.
Computing subsets of equivalence classes for large FSMs

Computing equivalence classes for FSMs has several applications to synthesis and verification problems. Symbolic traversal techniques are applicable to medium-small circuits. This paper extends their use to large FSMs by means of cofactor-based enhancements to the state-of-the-art approaches and of underestimations of equivalence classes. The key to success is pruning the search space by constraining it. Experimental results on some of the larger ISCAS'89 and MCNC circuits show its applicability.
A Joint Optimization Model for Image Summarization Based on Image Content and Tags

As an effective technology for navigating a large number of images, image summarization is becoming a promising task with the rapid development of image sharing sites and social networks. Most existing summarization approaches use the visual-based features for image representation without considering tag information.In this paper, we propose a novel framework, named JOINT, which employs both image content and tag information to summarize images. Our model generates the summary images which can best reconstruct the original collection. Based on the assumption that an image with representative content should also have typical tags, we introduce a similarity-inducing regularizer to our model. Furthermore, we impose the lasso penalty on the objective function to yield a concise summary set. Extensive experiments demonstrate our model outperforms the state-of-the-art approaches.
Functional diversity within the simple gut microbiota of the honey bee

Animals living in social communities typically harbor a characteristic gut microbiota important for nutrition and pathogen defense. Accordingly, in the gut of the honey bee, Apis mellifera, a distinctive microbial community, composed of a taxonomically restricted set of species specific to social bees, has been identified. Despite the ecological and economical importance of honey bees and the increasing concern about population declines, the role of their gut symbionts for colony health and nutrition is unknown. Here, we sequenced the metagenome of the gut microbiota of honey bees. Unexpectedly, we found a remarkable degree of genetic diversity within the few bacterial species colonizing the bee gut. Comparative analysis of gene contents suggests that different species harbor distinct functional capabilities linked to host interaction, biofilm formation, and carbohydrate breakdown. Whereas the former two functions could be critical for pathogen defense and immunity, the latter one might assist nutrient utilization. In a γ-proteobacterial species, we identified genes encoding pectin-degrading enzymes likely involved in the breakdown of pollen walls. Experimental investigation showed that this activity is restricted to a subset of strains of this species providing evidence for niche specialization. Long-standing association of these gut symbionts with their hosts, favored by the eusocial lifestyle of honey bees, might have promoted the genetic and functional diversification of these bee-specific bacteria. Besides revealing insights into mutualistic functions governed by the microbiota of this important pollinator, our findings indicate that the honey bee can serve as a model for understanding more complex gut-associated microbial communities.
Load Characterization and Low-Order Approximation for Smart Metering Data in the Spectral Domain

Smart metering data are providing new opportunities for various energy analyses at household level. However, traditional load analyses based on time-series techniques are challenged due to the irregular patterns and large volume from smart metering data. This paper proposes a promising alternative to decompose smart metering data in the spectral domain, where 1) the irregular load profiles can be characterized by the underlying spectral components, and 2) massive amount of load data can be represented by a small number of coefficients extracted from spectral components. This paper assesses the performances of load characterization at different aggregated levels by two spectral analysis techniques, using the discrete Fourier transform (DFT) and discrete wavelet transform (DWT). Results show that DWT significantly outperforms DFT for individual smart metering data, while DFT could be effective at a highly aggregated level.
A single-chip MPEG-2 codec based on customizable media embedded processor

A single-chip MPEG-2 MP@ML codec, integrating 3.8M gates on a 72-mm/sup 2/ die, is described. The codec employs a heterogeneous multiprocessor architecture in which six microprocessors with the same instruction set but different customization execute specific tasks such as video and audio concurrently. The microprocessor, developed for digital media processing, provides various extensions such as a very-long-instruction-word coprocessor, digital signal processor instructions, and hardware engines. Making full use of the extensions and optimizing the architecture of each microprocessor based upon the nature of specific tasks, the chip can execute not only MPEG-2 MP@ML video/audio/system encoding and decoding concurrently, but also MPEG-2 MP@HL decoding in real time.
Population size effects in evolutionary dynamics on neutral networks and toy landscapes

We study the dynamics of a population subject to selective pressures, evolving either on RNA neutral networks or on toy fitness landscapes. We discuss the spread and the neutrality of the population in the steady state. Different limits arise depending on whether selection or random drift is dominant. In the presence of strong drift we show that the observables depend mainly on Mμ, M being the population size and μ the mutation rate, while corrections to this scaling go as 1/M: such corrections can be quite large in the presence of selection if there are barriers in the fitness landscape. Also we find that the convergence to the large-Mμ limit is linear in 1/Mμ. Finally we introduce a protocol that minimizes drift; then observables scale like 1/M rather than 1/(Mμ), allowing one to determine the large-M limit more quickly when μ is small; furthermore the genotypic diversity increases from O(lnM) to O(M).
Consumer-Friendly Shopping Assistance by Personal Behavior Log Analysis on Ubiquitous Shop Space

This paper has proposed a shopping assistance service. We provide consumer-friendly services which based on personal behavior log data. The consumer-friendly services are information service which display through a monitor, robot, sound and music that can attract new consumer. In this paper, we study personal behavior from a log file that has been recorded by RFID and camera sensors in the ubiquitous environment. Utilizing ubiquitous sensors, we apply three types of observation scopes to model each user's preference. They are microscopic, mezzoscopic, and macroscopic observation scopes. We have proposed the behavior analysis, algorithms and collaborative filtering to retrieve information. Finally, we will also propose a ubiquitous shop space experiment.
Maternal Prenatal Positive Affect, Depressive and Anxiety Symptoms and Birth Outcomes: The PREDO Study

Background We investigated whether maternal prenatal emotions are associated with gestational length and birth weight in the large PREDO Study with multiple measurement points of emotions during gestation. Methods Altogether 3376 pregnant women self-assessed their positive affect (PA, Positive and Negative Affect Schedule) and depressive (Center for Epidemiologic Studies Depression Scale, CES-D) and anxiety (Spielberger State Anxiety Scale, STAI) symptoms up to 14 times during gestation. Birth characteristics were derived from the National Birth Register and from medical records. Results One standard deviation (SD) unit higher PA during the third pregnancy trimester was associated with a 0.05 SD unit longer gestational length, whereas one SD unit higher CES-D and STAI scores during the third trimester were associated with 0.04–0.05 SD unit shorter gestational lengths (P-values ≤ 0.02), corresponding to only 0.1–0.2% of the variation in gestational length. Higher PA during the third trimester was associated with a significantly decreased risk for preterm (< 37 weeks) delivery (for each SD unit higher positive affect, odds ratio was 0.8-fold (P = 0.02). Mothers with preterm delivery showed a decline in PA and an increase in CES-D and STAI during eight weeks prior to delivery. Post-term birth (≥ 42 weeks), birth weight and fetal growth were not associated with maternal prenatal emotions. Conclusions This study with 14 measurements of maternal emotions during pregnancy show modest effects of prenatal emotions during the third pregnancy trimester, particularly in the weeks close to delivery, on gestational length. From the clinical perspective, the effects were negligible. No associations were detected between prenatal emotions and birth weight.
Multidimensional Markov Models for the Cross-Layer Design of Multi-Rate Wireless Systems Using the Effective Capacity Function

In this paper, a novel framework for the cross-layer design of wireless networks combining adaptive modulation and coding (AMC) at the physical layer with an automatic repeat request (ARQ) protocol at the data-link layer is proposed. In order to achieve this goal, the physical-layer service process is first modeled as a multidimensional finite-state Markov chain. Then, based on this multidimensional Markov model, the QoS performance at the data-link layer is characterized using the effective capacity approach. Queueing analysis using this effective capacity function is finally used in a cross-layer design approach aiming to satisfy the required average packet loss probability constraint by maximizing the average throughput of the system. Numerical examples are provided to show the advantages of our approach compared to other approaches using first-order amplitude-based finite state Markov models.