Benchmarking in primary health care: An application of the stochasticd frontier analysis and the grades of membership approach to Portuguese family health units

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Towards cryogenic liquid –vapor energy storage units for space applications

Dissertation to obtain the Doctoral degree in Physics Engineering

Re-evaluation of the basic procedures involved in the storage of measles vaccine in public health units of the municipality of Niterói, state of Rio de Janeiro, Brazil

Four years after the first visit seventeen public health units were visited again and evaluated as to standards of storage recommended by the Brazilian Immunization Programme. In 100% of the units, refrigerators and proper inside location of vaccines in the refrigerator were adequatety or regularfy maintained and checked, respectively. However, when control of temperature was checked, onfy 64.7% presented adequate storage conditions. In 94.1 % of the units, health workers complained of lack of immediate technical support in emergency situations. In 55.2 % the titers vaccine samples of were under the minimal recommended potency. It is necessary that the factors concerning the cold chain be continualfy evaluated so that the quality of the vaccines that will be used is not affected.

The Edges of Areal Units: a case study in the heterogeneous effects of assessment district edges

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

Methicillin-resistant Staphylococcus aureus bloodstream infection: risk factors and clinical outcome in non-intensive-care units

INTRODUCTION: Methicillin-resistant Staphylococcus aureus (MRSA) is spread out in hospitals across different regions of the world and is regarded as the major agent of nosocomial infections, causing infections such as skin and soft tissue pneumonia and sepsis. The aim of this study was to identify risk factors for methicillin-resistance in Staphylococcus aureus bloodstream infection (BSI) and the predictive factors for death. METHODS: A retrospective cohort of fifty-one patients presenting bacteraemia due to S. aureus between September 2006 and September 2008 was analysed. Staphylococcu aureus samples were obtained from blood cultures performed by clinical hospital microbiology laboratory from the Uberlândia Federal University. Methicillinresistance was determined by growth on oxacillin screen agar and antimicrobial susceptibility by means of the disk diffusion method. RESULTS: We found similar numbers of MRSA (56.8%) and methicillin-susceptible Staphylococcus aureus (MSSA) (43.2%) infections, and the overall hospital mortality ratio was 47%, predominantly in MRSA group (70.8% vs. 29.2%) (p=0.05). Age (p=0.02) was significantly higher in MRSA patients as also was the use of central venous catheter (p=0.02). The use of two or more antimicrobial agents (p=0.03) and the length of hospital stay prior to bacteraemia superior to seven days (p=0.006) were associated with mortality. High odds ratio value was observed in cardiopathy as comorbidity. CONCLUSIONS: Despite several risk factors associated with MRSA and MSSA infection, the use of two or more antimicrobial agents was the unique independent variable associated with mortality.

Assessment of microbiological air quality in hemato-oncology units and its relationship with the occurrence of invasive fungal infections: an integrative review

Worldwide aging of the human population has promoted an increase in the incidence of neoplasia, including hematological cancers, which render patients particularly vulnerable to invasive fungal infections. For this reason, air filtration in hemato-oncology units has been recommended. However, scarce literature has assessed the impact of microbiological air quality on the occurrence of fungal infections in this population. We performed an integrative review of studies in the MEDLINE database that were published between January 1980 and October 2012, using the following combinations of keywords: air × quality × HEPA, air × quality × hematology, and airborne fungal infections. The search yielded only 13 articles, suggesting that high-efficiency filtering of the ambient air in hemato-oncology units can prevent the incidence of invasive fungal infections. However, no randomized clinical trial was found to confirm this suggestion. Currently, there is no consensus about the maximum allowable count of fungi in the air, which complicates filtration monitoring, including filter maintenance and replacement, and needs to be addressed in future studies.

Prevalence rates of infection in intensive care units of a tertiary teaching hospital

OBJECTIVE: To determine the prevalence rates of infections among intensive care unit patients, the predominant infecting organisms, and their resistance patterns. To identify the related factors for intensive care unit-acquired infection and mortality rates. DESIGN: A 1-day point-prevalence study. SETTING:A total of 19 intensive care units at the Hospital das Clínicas - University of São Paulo, School of Medicine (HC-FMUSP), a teaching and tertiary hospital, were eligible to participate in the study. PATIENTS: All patients over 16 years old occupying an intensive care unit bed over a 24-hour period. The 19 intensive care unit s provided 126 patient case reports. MAIN OUTCOME MEASURES: Rates of infection, antimicrobial use, microbiological isolates resistance patterns, potential related factors for intensive care unit-acquired infection, and death rates. RESULTS: A total of 126 patients were studied. Eighty-seven patients (69%) received antimicrobials on the day of study, 72 (57%) for treatment, and 15 (12%) for prophylaxis. Community-acquired infection occurred in 15 patients (20.8%), non- intensive care unit nosocomial infection in 24 (33.3%), and intensive care unit-acquired infection in 22 patients (30.6%). Eleven patients (15.3%) had no defined type. The most frequently reported infections were respiratory (58.5%). The most frequently isolated bacteria were Enterobacteriaceae (33.8%), Pseudomonas aeruginosa (26.4%), and Staphylococcus aureus (16.9%; [100% resistant to methicillin]). Multivariate regression analysis revealed 3 risk factors for intensive care unit-acquired infection: age > 60 years (p = 0.007), use of a nasogastric tube (p = 0.017), and postoperative status (p = 0.017). At the end of 4 weeks, overall mortality was 28.8%. Patients with infection had a mortality rate of 34.7%. There was no difference between mortality rates for infected and noninfected patients (p=0.088). CONCLUSION: The rate of nosocomial infection is high in intensive care unit patients, especially for respiratory infections. The predominant bacteria were Enterobacteriaceae, Pseudomonas aeruginosa, and Staphylococcus aureus (resistant organisms). Factors such as nasogastric intubation, postoperative status, and age ³60 years were significantly associated with infection. This study documents the clinical impression that prevalence rates of intensive care unit-acquired infections are high and suggests that preventive measures are important for reducing the occurrence of infection in critically ill patients.

Lightweight concrete masonry units based on processed granulate of corn cob as aggregate

A research work was performed in order to assess the potential application of processed granulate of corn cob (PCC) as an alternative lightweight aggregate for the manufacturing process of lightweight concrete masonry units (CMU). Therefore, CMU-PCC were prepared in a factory using a typical lightweight concrete mixture for non-structural purposes. Additionally, lightweight concrete masonry units based on a currently applied lightweight aggregate such as expanded clay (CMU-EC) were also manufactured. An experimental work allowed achieving a set of results that suggest that the proposed building product presents interesting material properties within the masonry wall context. Therefore, this unit is promising for both interior and exterior applications. This conclusion is even more relevant considering that corn cob is an agricultural waste product.

A study on the performance of technology transfer units

Universities are increasingly institutionalizing activities related to technology transfer and one of the main institutional mechanisms that has emerged is the “technology transfer unit” (TTU). Many of them are focusing their activities on the management of the university intellectual property. Studies have investigated factors that seem to affect their performance, but few have looked in detail at internal procedures and techniques that are used in their processes related to technology evaluation and licensing. The aim of this paper is to provide a comprehensive overview of some of the several steps that comprises the processes regarding technology evaluation and licensing, providing an analysis of the critical issues that affect each step of the process. A review of the literature was made, complemented with interviews to seven university TTUs, which was used as a check and a complement to the literature review and as way of perceiving from an insider perspective, the problems and issues that this paper wants to emphasize and to state clearly.

Cost-effective and lightweight mobile units for MixAR: A comparative trial among different setups

Cultural heritage has arousing the interest of the general public (e.g. tourists), resulting in the increasing number of visitations to archaeological sites. However, many buildings and monuments are severely damaged or completely destroyed, which doesn’t allow to get a full experience of “travelling in time”. Over the years, several Augmented Reality (AR) approaches were proposed to overcome these issues by providing three-dimensional visualization of reconstructed ancient structures in situ. However, most of these systems were made available through heavy and expensive technological bundles. Alternatively, MixAR intends to be a lightweight and cost-effective Mixed Reality system which aims to provide the visualization of virtual ancient buildings reconstructions in situ, properly superimposed and aligned with real-world ruins. This paper proposes and compares different AR mobile units setups to be used in the MixAR system, with low-cost and lightweight requirements in mind, providing different levels of immersion. It was propounded four different mobile units, based on: a laptop computer, a single-board computer (SBC), a tablet and a smartphone, which underwent a set of tests to evaluate their performances. The results show that mobile units based on laptop computer and SBC reached a good overall performance while mobile units based on tablet and smartphone did not meet such a satisfactory result even though they are acceptable for the intended use.

Step towards a patient timeline in intensive care units

In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.