Processos enunciativos e gramática operatória: o espaço semântico-enunciativo dos marcadores er e estar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Motociclistas vítimas de acidentes em Paranavaí, 2011

Pós-graduação em Saúde Coletiva - FMB

Estudo da distribuição das tensões internas, pelo método dos elementos finitos, em uma raiz com um retentor intra-radicular pré-fabricado, rosqueado e com fenda apical

Pós-graduação em Odontologia Restauradora - ICT

Análise da influência da adoção de práticas de Green Supply Chain Management no desempenho ambiental e operacional: estudo de caso

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Phenotypic and genetic variability for body weight of ostriches (Struthio camelus)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

O processo de liderança na perspectiva de enfermeiros da estratégia de saúde da família de Botucatu: uma pesquisa-ação

Pós-graduação em Enfermagem - FMB

Long-Term Prospective Study of the Influence of Estrone Levels on Events in Postmenopausal Women with or at High Risk for Coronary Artery Disease

Background. The link between endogenous estrogen, coronary artery disease (CAD), and death in postmenopausal women is uncertain. We analyzed the association between death and blood levels of estrone in postmenopausal women with known coronary artery disease (CAD) or with a high-risk factor score for CAD. Methods. 251 postmenopausal women age 50-90 years not on estrogen therapy. Fasting blood for estrone and heart disease risk factors were collected at baseline. Women were grouped according to their estrone levels (<15 and >= 15 pg/mL). Fatal events were recorded after 5.8 perpendicular to 1.4 years of followup. Results. The Kaplan-Meier survival curve showed a significant trend (P = 0.039) of greater all-cause mortality in women with low estrone levels (< 15 pg/mL). Cox multivariate regression analysis model adjusted for body mass index, diabetes, dyslipidemia, family history, and estrone showed estrone (OR = 0.45; P = 0.038) as the only independent variable for all-cause mortality. Multivariate regression model adjusted for age, body mass index, hypertension, diabetes, dyslipidemia, family history, and estrone showed that only age (OR = 1.06; P = 0.017) was an independent predictor of all-cause mortality. Conclusions. Postmenopausal women with known CAD or with a high-risk factor score for CAD and low estrone levels (< 15 pg/mL) had increased all-cause mortality.

A study of two Languages for Active Objects with Futures

In computer systems, specifically in multithread, parallel and distributed systems, a deadlock is both a very subtle problem - because difficult to pre- vent during the system coding - and a very dangerous one: a deadlocked system is easily completely stuck, with consequences ranging from simple annoyances to life-threatening circumstances, being also in between the not negligible scenario of economical losses. Then, how to avoid this problem? A lot of possible solutions has been studied, proposed and implemented. In this thesis we focus on detection of deadlocks with a static program analysis technique, i.e. an analysis per- formed without actually executing the program. To begin, we briefly present the static Deadlock Analysis Model devel- oped for coreABS−− in chapter 1, then we proceed by detailing the Class- based coreABS−− language in chapter 2. Then, in Chapter 3 we lay the foundation for further discussions by ana- lyzing the differences between coreABS−− and ASP, an untyped Object-based calculi, so as to show how it can be possible to extend the Deadlock Analysis to Object-based languages in general. In this regard, we explicit some hypotheses in chapter 4 first by present- ing a possible, unproven type system for ASP, modeled after the Deadlock Analysis Model developed for coreABS−−. Then, we conclude our discussion by presenting a simpler hypothesis, which may allow to circumvent the difficulties that arises from the definition of the ”ad-hoc” type system discussed in the aforegoing chapter.

Fattori eziologici della Sindrome del Tunnel Carpale: una revisione sistematica con meta-analisi degli studi analitici

OBIETTIVO: sintetizzare le evidenze disponibili sulla relazione tra i fattori di rischio (personali e lavorativi) e l’insorgenza della Sindrome del Tunnel Carpale (STC). METODI: è stata condotta una revisione sistematica della letteratura su database elettronici considerando gli studi caso-controllo e di coorte. Abbiamo valutato la qualità del reporting degli studi con la checklist STROBE. Le stime studio-specifiche sono state espresse come OR (IC95%) e combinate con una meta-analisi condotta con un modello a effetti casuali. La presenza di eventuali bias di pubblicazione è stata valutata osservando l’asimmetria del funnel plot e con il test di Egger. RISULTATI: Sono stati selezionati 29 studi di cui 19 inseriti nella meta-analisi: 13 studi caso-controllo e 6 di coorte. La meta-analisi ha mostrato un aumento significativo di casi di STC tra i soggetti obesi sia negli studi caso-controllo [OR 2,4 (1,9-3,1); I(2)=70,7%] che in quelli di coorte [OR 2,0 (1,6-2,7); I(2)=0%]. L'eterogeneità totale era significativa (I(2)=59,6%). Risultati simili si sono ottenuti per i diabetici e soggetti affetti da malattie della tiroide. L’esposizione al fumo non era associata alla STC sia negli studi caso-controllo [OR 0,7 (0,4-1,1); I(2)=83,2%] che di coorte [OR 0,8 (0,6-1,2); I(2)=45,8%]. A causa delle molteplici modalità di valutazione non è stato possibile calcolare una stima combinata delle esposizioni professionali con tecniche meta-analitiche. Dalla revisione, è risultato che STC è associata con: esposizione a vibrazioni, movimenti ripetitivi e posture incongrue di mano-polso. CONCLUSIONI: I risultati della revisione sistematica confermano le evidenze dell'esistenza di un'associazione tra fattori di rischio personali e STC. Nonostante la diversa qualità dei dati sull'esposizione e le differenze degli effetti dei disegni di studio, i nostri risultati indicano elementi di prova sufficienti di un legame tra fattori di rischio professionali e STC. La misurazione dell'esposizione soprattutto per i fattori di rischio professionali, è un obiettivo necessario per studi futuri.

Using sulfur isotope fractionation to understand the atmospheric oxidation of SO 2

Sulfate aerosol plays an important but uncertain role in cloud formation and radiative forcing of the climate, and is also important for acid deposition and human health. The oxidation of SO2 to sulfate is a key reaction in determining the impact of sulfate in the environment through its effect on aerosol size distribution and composition. This thesis presents a laboratory investigation of sulfur isotope fractionation during SO2 oxidation by the most important gas-phase and heterogeneous pathways occurring in the atmosphere. The fractionation factors are then used to examine the role of sulfate formation in cloud processing of aerosol particles during the HCCT campaign in Thuringia, central Germany. The fractionation factor for the oxidation of SO2 by ·OH radicals was measured by reacting SO2 gas, with a known initial isotopic composition, with ·OH radicals generated from the photolysis of water at -25, 0, 19 and 40°C (Chapter 2). The product sulfate and the residual SO2 were collected as BaSO4 and the sulfur isotopic compositions measured with the Cameca NanoSIMS 50. The measured fractionation factor for 34S/32S during gas phase oxidation is αOH = (1.0089 ± 0.0007) − ((4 ± 5) × 10−5 )T (°C). Fractionation during oxidation by major aqueous pathways was measured by bubbling the SO2 gas through a solution of H2 O2

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

The MIRELA framework: modeling and analyzing mixed reality applications using timed automata

Mixed Reality (MR) aims to link virtual entities with the real world and has many applications such as military and medical domains [JBL+00, NFB07]. In many MR systems and more precisely in augmented scenes, one needs the application to render the virtual part accurately at the right time. To achieve this, such systems acquire data related to the real world from a set of sensors before rendering virtual entities. A suitable system architecture should minimize the delays to keep the overall system delay (also called end-to-end latency) within the requirements for real-time performance. In this context, we propose a compositional modeling framework for MR software architectures in order to specify, simulate and validate formally the time constraints of such systems. Our approach is first based on a functional decomposition of such systems into generic components. The obtained elements as well as their typical interactions give rise to generic representations in terms of timed automata. A whole system is then obtained as a composition of such defined components. To write specifications, a textual language named MIRELA (MIxed REality LAnguage) is proposed along with the corresponding compilation tools. The generated output contains timed automata in UPPAAL format for simulation and verification of time constraints. These automata may also be used to generate source code skeletons for an implementation on a MR platform. The approach is illustrated first on a small example. A realistic case study is also developed. It is modeled by several timed automata synchronizing through channels and including a large number of time constraints. Both systems have been simulated in UPPAAL and checked against the required behavioral properties.

Cost-effectiveness of universal prophylaxis in pregnancy with prior group B streptococci colonization.

OBJECTIVE: To estimate the costs and outcomes of rescreening for group B streptococci (GBS) compared to universal treatment of term women with history of GBS colonization in a previous pregnancy. STUDY DESIGN: A decision analysis model was used to compare costs and outcomes. Total cost included the costs of screening, intrapartum antibiotic prophylaxis (IAP), treatment for maternal anaphylaxis and death, evaluation of well infants whose mothers received IAP, and total costs for treatment of term neonatal early onset GBS sepsis. RESULTS: When compared to screening and treating, universal treatment results in more women treated per GBS case prevented (155 versus 67) and prevents more cases of early onset GBS (1732 versus 1700) and neonatal deaths (52 versus 51) at a lower cost per case prevented ($8,805 versus $12,710). CONCLUSION: Universal treatment of term pregnancies with a history of previous GBS colonization is more cost-effective than the strategy of screening and treating based on positive culture results.

First continuous ground-based observations of long period oscillations in strato-/mesospheric wind profiles

Direct measurements of middle-atmospheric wind oscillations with periods between 5 and 50 days in the altitude range between mid-stratosphere (5 hPa) and upper mesosphere (0.02 hPa) have been made using a novel ground-based Doppler wind radiometer. The oscillations were not inferred from measurements of tracers, as the radiometer offers the unique capability of near-continuous horizontal wind profile measurements. Observations from four campaigns at high, mid and low latitudes with an average duration of 10 months have been analyzed. The dominant oscillation has mostly been found to lie in the extra-long period range (20–40 days), while the well-known atmospheric normal modes around 5, 10 and 16 days have also been observed. Comparisons of our results with ECMWF operational analysis model data revealed remarkably good agreement below 0.3 hPa but discrepancies above.

Shallow Dialogue Processing Using Machine Learning Algorithms (or not)

This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and several machine learning techniques are used to extract features from dialogue transcripts: maximum entropy classifiers for dialogue acts, latent semantic analysis for topic segmentation, or decision tree classifiers for discourse markers. A rule-based approach is proposed for solving cross-modal references to meeting documents. The methods are trained and evaluated thanks to a common data set and annotation format. The integration of the components into an automated shallow dialogue parser opens the way to multimodal meeting processing and retrieval applications.