Leadership power bases related to satisfaction, compliance, and program quality

The dissertation examined prekindergarten teachers' perceptions of their supervisory relationship with their educational specialist, and the effect of the prekindergarten teachers' perceptions on the quality of the High/Scope prekindergarten program. The High/Scope educational specialists use their leader power bases (reward, coercive, legitimate, referent, expert and informational) to influence teachers' perceptions of satisfaction and compliance, as well as teachers' actual compliance with the High/Scope prekindergarten program standards. The correlational relationships between the variables were examined using Analysis of Variance and Multivariate Analysis of Variance. Path Analysis was utilized to analyze variables to determine the validity of the correlational model. Expert, legitimate, referent, and informational power bases of the High/Scope educational specialist were found to be the most influential on attitudinal and behavioral compliance of teachers. ^

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Natural ventilation and indoor air quality in educational buildings: experimental assessment and improvement strategies

Indoor environmental conditions in classrooms, in particular temperature and indoor air quality, influence students’ health, attitude and performance. In recent years, several studies regarding indoor environmental quality of classrooms were published and natural ventilation proved to have great potential, particularly in southern European climate. This research aimed to evaluate indoor environmental conditions in eight schools and to assess their improvement potential by simple natural ventilation strategies. Temperature, relative humidity and carbon dioxide concentration were measured in 32 classrooms. Ventilation performance of the classrooms was characterized using two techniques, first by fan pressurization measurements of the envelope airtightness and later by tracer gas measurements of the air change rate assuming different envelope conditions. A total of 110 tracer gas measurements were made and the results validated ventilation protocols that were tested afterward. The results of the ventilation protocol implementation were encouraging and, overall, a decrease on the CO2 concentration was observed without modifying the comfort conditions. Nevertheless, additional measurements must be performed for winter conditions.

Crescimento e desempenho motor em pre-escolares de Itapira SP : um enfoque bio-social-cultural

Universidade Estadual de Campinas. Faculdade de Educação Física

Da formação e desenvolvimento profissional do professor de educação fisica a inovação educativa

Universidade Estadual de Campinas . Faculdade de Educação Física

Genetic trend estimates of meat quality traits in a male broiler line

The present research was conducted to estimate the genetic trends for meat quality traits in a male broiler line. The traits analyzed were initial pH, pH at 6 h after slaughter, final pH, initial range of falling pH, final range of falling pH, lightness, redness, yellowness, weep loss, drip loss, shrink loss, and shear force. The number of observations varied between 618 and 2125 for each trait. Genetic values were obtained by restricted maximum likelihood, and the numerator relationship matrix had 107,154 animals. The genetic trends were estimated by regression of the broiler average genetic values with respect to unit of time (generations), and the average genetic trend was estimated by regression coefficients. Generally, for the traits analyzed, small genetic trends were obtained, except for drip loss and shear force, which were higher. The small magnitude of the trends found could be a consequence of the absence of selection for meat quality traits in the line analyzed. The estimates of genetic trends obtained were an indication of an improvement in the meat quality traits in the line analyzed, except for drip loss.

Fermentation of cacao (Theobroma cacao L.) seeds with a hybrid Kluyveromyces marxianus strain improved product quality attributes

Fermentation of Theobroma cacao (cacao) seeds is an absolute requirement for the full development of chocolate flavor precursors. An adequate aeration of the fermenting cacao seed mass is a fundamental prerequisite for a satisfactory fermentation. Here, we evaluated whether a controlled inoculation of cacao seed fermentation using a Kluyveromyces marxianus hybrid yeast strain, with an increased pectinolytic activity, would improve an earlier liquid drainage (`sweatings`) from the fermentation mass, developing a superior final product quality. Inoculation with K. marxianus increased by one third the volume of drained liquid and affected the microorganism population structure during fermentation, which was detectable up to the end of the process. Introduction of the hybrid yeast affected the profile of total seed protein degradation evaluated by polyacrylamide gel electrophoresis, with improved seed protein degradation, and reduction of titrable acidity. Sensorial evaluation of the chocolate obtained from beans fermented with the K. marxianus inoculation was more accepted by analysts in comparison with the one from cocoa obtained through natural fermentation. The increase in mass aeration during the first 24 h seemed to be fundamental for the improvement of fermentation quality, demonstrating the potential application of this improved hybrid yeast strain with superior exogenous pectinolytic activity.

Improvement of radiology services based on the process management approach

The health sector requires continuous investments to ensure the improvement of products and services from a technological standpoint, the use of new materials, equipment and tools, and the application of process management methods. Methods associated with the process management approach, such as the development of reference models of business processes, can provide significant innovations in the health sector and respond to the current market trend for modern management in this sector (Gunderman et al. (2008) [4]). This article proposes a process model for diagnostic medical X-ray imaging, from which it derives a primary reference model and describes how this information leads to gains in quality and improvements. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Risk-based decision making method for maintenance policy selection of thermal power plant equipment

This study presents a decision-making method for maintenance policy selection of power plants equipment. The method is based on risk analysis concepts. The method first step consists in identifying critical equipment both for power plant operational performance and availability based on risk concepts. The second step involves the proposal of a potential maintenance policy that could be applied to critical equipment in order to increase its availability. The costs associated with each potential maintenance policy must be estimated, including the maintenance costs and the cost of failure that measures the critical equipment failure consequences for the power plant operation. Once the failure probabilities and the costs of failures are estimated, a decision-making procedure is applied to select the best maintenance policy. The decision criterion is to minimize the equipment cost of failure, considering the costs and likelihood of occurrence of failure scenarios. The method is applied to the analysis of a lubrication oil system used in gas turbines journal bearings. The turbine has more than 150 MW nominal output, installed in an open cycle thermoelectric power plant. A design modification with the installation of a redundant oil pump is proposed for lubricating oil system availability improvement. (C) 2009 Elsevier Ltd. All rights reserved.

Availability analysis of heat recovery steam generators used in thermal power plants

The combined-cycle gas and steam turbine power plant presents three main pieces of equipment: gas turbines, steam turbines and heat recovery steam generator (HRSG). In case of HRSG failure the steam cycle is shut down, reducing the power plant output. Considering that the technology for design, construction and operation of high capacity HRSGs is quite recent its availability should be carefully evaluated in order to foresee the performance of the power plant. This study presents a method for reliability and availability evaluation of HRSGs installed in combined-cycle power plant. The method`s first step consists in the elaboration of the steam generator functional tree and development of failure mode and effects analysis. The next step involves a reliability and availability analysis based on the time to failure and time to repair data recorded during the steam generator operation. The third step, aiming at availability improvement, recommends the fault-tree analysis development to identify components the failure (or combination of failures) of which can cause the HRSG shutdown. Those components maintenance policy can be improved through the use of reliability centered maintenance (RCM) concepts. The method is applied on the analysis of two HRSGs installed in a 500 MW combined-cycle power plant. (C) 2010 Elsevier Ltd. All rights reserved.

Improved effective charge density in MOS capacitors with PECVD SiOxNy dielectric layer obtained at low RF power

In this work SiOxNy films are produced and characterized. Series of samples were deposited by the plasma enhanced chemical vapor deposition (PECVD) technique at low temperatures from silane (SiH4), nitrous oxide (N2O) and helium (He) precursor gaseous mixtures, at different deposition power in order to analyze the effect of this parameter on the films structural properties, on the SiOxNy/Si interface quality and on the SiOxNy effective charge density. In order to compare the film structural properties with the interface (SiOxNy/Si) quality and effective charge density, MOS capacitors were fabricated using these films as dielectric layer. X-ray absorption near-edge spectroscopy (XANES), at the Si-K edge, was utilized to investigate the structure of the films and the material bonding characteristics were analyzed through Fourier transform infrared spectroscopy (FTIR). The MOS capacitors were characterized by low and high frequency capacitance (C-V) measurements, in order to obtain the interface state density (D-it) and the effective charge density (N-ss). An effective charge density linear reduction for decreasing deposition power was observed, result that is attributed to the smaller amount of ions present in the plasma for low RF power. (C) 2008 Elsevier B.V. All rights reserved.

Thermodynamic information system for diagnosis and prognosis of power plant operation condition

A thermodynamic information system for diagnosis and prognosis of an existing power plant was developed. The system is based on an analytic approach that informs the current thermodynamic condition of all cycle components, as well as the improvement that can be obtained in the cycle performance by the elimination of the discovered anomalies. The effects induced by components anomalies and repairs in other components efficiency, which have proven to be one of the main drawbacks in the diagnosis and prognosis analyses, are taken into consideration owing to the use of performance curves and corrected performance curves together with the thermodynamic data collected from the distributed control system. The approach used to develop the system is explained, the system implementation in a real gas turbine cogeneration combined cycle is described and the results are discussed. (C) 2011 Elsevier Ltd. All rights reserved.

WINE GRAPE QUALITY OF GRAPEVINES GROWN IN THE CERRADO ECOREGION OF BRAZIL

Aims: Geographical indication plays an important role in the improvement of wine quality. In this context, the search for new grape growing areas has been constant. The Sao Francisco River Valley in the cerrado of Minas Gerais State (Brazil) has been pointed out in the Geoviticulture Multicriteria Climatic Classification System (MCC System) as a potentially winegrowing region, especially considering the autumn-winter period when night temperatures are favorable to grape ripening. In this work, we studied the maturation curves and fruit composition of four wine grape varieties (Syrah, Merlot, Cabernet-Sauvignon and Cabernet Franc) in two growing seasons in order to validate the state of Minas Gerais as a new winegrowing region in Brazil. Methods and results: Quality parameters (berry weight, pH, titratable acidity and total soluble solids) were measured weekly from veraison to harvest, and sugar, organic acid, anthocyanin and phenolic concentrations were determined in must and berry skins and seeds at harvest. Syrah berries showed the highest weight throughout maturation which contributed to higher yield (8.92 ton ha(-1)), followed closely by Merlot (8.07 ton ha(-1)). Bern, sugar concentrations were higher and malic acid levels were lower than the values usually observed in wine grapes harvested during summer in traditional winegrowing regions in Brazil. Cabernet Franc showed lower levels of anthocyanins and skin phenolics per kg berries and the highest values of seed phenolics, which were not affected by growing season. Conclusion: Weather conditions of the cerrado of Minas Gerais State in Brazil during winter allowed complete maturation of Cabernet-Sauvignon, Cabernet Franc, Merlot and Syrah cultivars as revealed by the satisfactory sugar, anthocyanin and skin phenolic accumulation. Significance and impact of the study: This study revealed the potential of the cerrado ecoregion in the northeast of Minas Gerais to become a new winemaking region in Brazil.