Quality of life and satisfaction of patients wearing implant-supported fixed partial denture: a cross-sectional survey of patients from Aracatuba city, Brazil

ObjectivesThe aim of this study was to evaluate the quality of life and satisfaction of patients wearing implant-supported fixed partial dentures.Materials &methodsA total of 106 patients were selected and submitted to clinical examination and collection of the demographic data for evaluation of the implant-supported fixed dentures conditions. All participants agreed to answer to the Oral Health Impact Profile (OHIP-EDENT) questionnaire and another questionnaire about satisfaction with the implant-supported prostheses. The patients were classified into the following three groups for statistical analysis: patients wearing splinted implant-supported prosthesis (E), patients wearing single implant-supported prosthesis (U), and patients wearing single implant-supported prosthesis associated with splinted prosthesis (E+U). Kruskal-Wallis test was used to compare the answers between the groups, and a logistic regression model was measured to verify the relation between variables of the patients and the questionaries'items.ResultsThere were significant differences among groups (P=0.006) for discomfort during surgery itself of the satisfaction questionnaire. The marital status, groups, and hygiene condition were significant mainly for physical pain item.ConclusionsIt was concluded that the patients presented high level of satisfaction and quality of life for the most of the items evaluated as well as the groups showed similar results.

Thomas Belue Collection - Accession 35 - M11 (21)

The Thomas Belue Collection consists of the diary of Thomas Belue of Union County, South Carolina. He enrolled as a private in the Confederate Army in Co. F, Captain C.W. Boyd’s , 15th SCV. The diary covers August, 1861 to September, 1863, and May 1864. Belue describes battles fought in South Carolina, Georgia,Tennessee, and Virginia, mileage covered, camp life and events that occurred during his time in the army. The collection also includes biographical information, genealogical information, a partial transcript of the diary, and copies of Belue’s military records. In addition there is a tintype in a case of Belue in his uniform, two copies of the tintype, and photographs of his gravestone at Gilead Baptist Church Cemetery in Union County, South Carolina.

Classification Using Generalized Partial Least Squares

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in the context of generalized linear regression based on a previous approach, Iteratively ReWeighted Partial Least Squares, i.e. IRWPLS (Marx, 1996). We compare our results with two-stage PLS (Nguyen and Rocke, 2002A; Nguyen and Rocke, 2002B) and other classifiers. We show that by phrasing the problem in a generalized linear model setting and by applying bias correction to the likelihood to avoid (quasi)separation, we often get lower classification error rates.

Marginal Structural Models for Partial Exposure Regimes

Intensive care unit (ICU) patients are ell known to be highly susceptible for nosocomial (i.e. hospital-acquired) infections due to their poor health and many invasive therapeutic treatments. The effects of acquiring such infections in ICU on mortality are however ill understood. Our goal is to quantify these effects using data from the National Surveillance Study of Nosocomial Infections in Intensive Care Units (Belgium). This is a challenging problem because of the presence of time-dependent confounders (such as exposure to mechanical ventilation)which lie on the causal path from infection to mortality. Standard statistical analyses may be severely misleading in such settings and have shown contradicting results. While inverse probability weighting for marginal structural models can be used to accommodate time-dependent confounders, inference for the effect of ?ICU acquired infections on mortality under such models is further complicated (a) by the fact that marginal structural models infer the effect of acquiring infection on a given, fixed day ?in ICU?, which is not well defined when ICU discharge comes prior to that day; (b) by informative censoring of the survival time due to hospital discharge; and (c) by the instability of the inverse weighting estimation procedure. We accommodate these problems by developing inference under a new class of marginal structural models which describe the hazard of death for patients if, possibly contrary to fact, they stayed in the ICU for at least a given number of days s and acquired infection or not on that day. Using these models we estimate that, if patients stayed in the ICU for at least s days, the effect of acquiring infection on day s would be to multiply the subsequent hazard of death by 2.74 (95 per cent conservative CI 1.48; 5.09).

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Michigan bibliography. A partial catalogue of books, maps, manuscripts and miscellaneous materials relating to the resources, development and history of Michigan from earliest times to July 1, 1917; together with citation of libraries in which the materials may be consulted, and a complete analytical index by subject and author.

Lettered on cover: Michigan bibliography. Streeter ... Michigan historical publications, 1921.

Sugarcane moth borers (Lepidoptera: Noctuidae and Pyraloidea): phylogenetics constructed using COII and 16S mitochondrial partial gene sequences

Sugarcane moth borers are a diverse group of species occurring in several genera, but predominately within the Noctuidae and Pyraloidea. They cause economic loss in sugarcane and other crops through damage to stems and stalks by larval boring. Partial sequence data from two mitochondrial genes, COII and 16S, were used to construct a molecular phylogeny based on 26 species from ten genera and six tribes. The Noctuidae were found to be monophyletic, providing molecular support for the taxonomy within this subfamily. However, the Pyraloidea are paraphyletic, with the noctuids splitting Galleriinae and Schoenobiinae from the Crambinae. This supports the separation of the Pyralidae and Crambinae, but does not support the concept of the incorporation of the Schoenobiinae in the Crambidae. Of the three crambine genera examined, Diatraea was monophyletic, Chilo paraphyletic, and Eoreuma was basal to the other two genera. Within the Noctuidae, Sesamia and Bathytricha were monophyletic, with Busseola basal to Bathytricha. Many species in this study (both noctuids and pyraloids) had different biotypes within collection localities and across their distribution; however the individual biotypes were not phylogenetically informative. These data highlight the need for taxonomic revisions at all taxon levels and provide a basis for the development of DNA-based diagnostics for rapidly identifying many species at any developmental stage. This ability is vital, as the species are an incursion threat to Australia and have the potential to cause significant losses to the sugar industry.

Prediction of Klason lignin and lignin thermal degradation products by Py-GC/MS in a collection of Lolium and Festuca grasses

A rapid method for the analysis of biomass feedstocks was established to identify the quality of the pyrolysis products likely to impact on bio-oil production. A total of 15 Lolium and Festuca grasses known to exhibit a range of Klason lignin contents were analysed by pyroprobe-GC/MS (Py-GC/MS) to determine the composition of the thermal degradation products of lignin. The identification of key marker compounds which are the derivatives of the three major lignin subunits (G, H, and S) allowed pyroprobe-GC/MS to be statistically correlated to the Klason lignin content of the biomass using the partial least-square method to produce a calibration model. Data from this multivariate modelling procedure was then applied to identify likely "key marker" ions representative of the lignin subunits from the mass spectral data. The combined total abundance of the identified key markers for the lignin subunits exhibited a linear relationship with the Klason lignin content. In addition the effect of alkali metal concentration on optimum pyrolysis characteristics was also examined. Washing of the grass samples removed approximately 70% of the metals and changed the characteristics of the thermal degradation process and products. Overall the data indicate that both the organic and inorganic specification of the biofuel impacts on the pyrolysis process and that pyroprobe-GC/MS is a suitable analytical technique to asses lignin composition. © 2007 Elsevier B.V. All rights reserved.

On the efficiency of impingers with fritted nozzle tip for collection of ultrafine particles

The aim of this study was to determine the collection efficiency of ultrafine particles into an impinger fitted with a fritted nozzle tip as a means to increase contact surface area between the aerosol and the liquid. The influence of liquid sampling volume, frit porosity and the nature of the sampling liquid was explored and it was shown that all impact on the collection efficiency of particles smaller than 220 nm. Obtained values for overall collection efficiency were substantially higher (~30–95%) than have been previously reported, mainly due to the high deposition of particles in the fritted nozzle tip, especially in case of finer porosity frits and smaller particles. Values for the capture efficiency of the solvent alone ranged from 20 to 45%, depending on the type and the volume of solvent. Additionally, our results show that airstream dispersion into bubbles improves particle trapping by the liquid and that there is a difference in collection efficiencies based on the nature and volume of the solvent used.