947 resultados para Dynamic data analysis


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The purpose of this study was to document and critically analyze the lived experience of selected nursing staff developers in the process of moving toward a new model for hospital nursing education. Eleven respondents were drawn from a nation-wide population of about two hundred individuals involved in nursing staff development. These subjects were responsible for the implementation of the Performance Based Development System (PBDS) in their institutions.^ A purposive, criterion-based sampling technique was used with respondents being selected according to size of hospital, primary responsibility for orchestration of the change, influence over budgetary factors and managerial responsibility for PBDS. Data were gathered by the researcher through both in-person and telephone interviews. A semi-structured interview guide, designed by the researcher was used, and respondents were encouraged to amplify on their recollections as desired. Audiotapes were transcribed and resulting computer files were analyzed using the program "Martin". Answers to interview questions were compiled and reported across cases. The data was then reviewed a second time and interpreted for emerging themes and patterns.^ Two types of verification were used in the study. Internal verification was done through interview transcript review and feedback by respondents. External verification was done through review and feedback on data analysis by readers who were experienced in management of staff development departments.^ All respondents were female, so Gilligan's concept of the "ethic of care" was examined as a decision making strategy. Three levels of caring which influenced decision making were found. They were caring: (a) for the organization, (b) for the employee, and (c) for the patient. The four existentials of the lived experience, relationality, corporeality, temporality and spatiality were also examined to reveal the everydayness of making change. ^

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This study investigated the nature and impact of the sexual abuse of children ages birth through 6 years. The purpose was to enhance knowledge about this understudied population through examination of: (1) characteristics of the abuse; (2) socioemotional developmental outcomes of young victims; and (3) potential moderating effects of family dynamics. An ecological-developmental theoretical framework was applied. Secondary data analysis was conducted using data collected from the consortium Longitudinal Studies of Child Abuse and Neglect (LONGSCAN). A sample of 250 children was drawn from LONGSCAN data, including children who were sexually abused (n=125) and their nonabused counterparts (n=125), matched on demographic variables. Results revealed that young victims of sexual abuse were disproportionately female (91 girls; 73%). The sexual abuse committed against these youngsters was severe in nature, with 111 children (89%) experiencing contact offenses ranging from fondling to forcible rape. Sixty-two percent of child victims demonstrated borderline, clinical, or less than adequate functioning on normative, expected socioemotional outcomes. Child victims reported low degrees of perceived competence and satisfaction in the social environment. When compared with their nonabused counterparts, child victims demonstrated significantly poorer socioemotional functioning, as evidenced by aggressive behaviors, attention and thought problems. Sexually abused youngsters also reported lower self-perceptions of cognitive and physical competence and maternal acceptance. Family dynamic factors did not significantly moderate the relationships between abuse and socioemotional outcomes, with one exception. The caregivers’ degree of empathy for their children had a significant moderating effect on the children’s social problems. This study contributes to an otherwise scant body of literature on the sexual abuse of preschoolers. Findings provide implications for social work practice, especially in the development of assessment and prevention strategies.

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The necessity of elemental analysis techniques to solve forensic problems continues to expand as the samples collected from crime scenes grow in complexity. Laser ablation ICP-MS (LA-ICP-MS) has been shown to provide a high degree of discrimination between samples that originate from different sources. In the first part of this research, two laser ablation ICP-MS systems were compared, one using a nanosecond laser and another a femtosecond laser source for the forensic analysis of glass. The results showed that femtosecond LA-ICP-MS did not provide significant improvements in terms of accuracy, precision and discrimination, however femtosecond LA-ICP-MS did provide lower detection limits. In addition, it was determined that even for femtosecond LA-ICP-MS an internal standard should be utilized to obtain accurate analytical results for glass analyses. In the second part, a method using laser induced breakdown spectroscopy (LIBS) for the forensic analysis of glass was shown to provide excellent discrimination for a glass set consisting of 41 automotive fragments. The discrimination power was compared to two of the leading elemental analysis techniques, μXRF and LA-ICP-MS, and the results were similar; all methods generated >99% discrimination and the pairs found indistinguishable were similar. An extensive data analysis approach for LIBS glass analyses was developed to minimize Type I and II errors en route to a recommendation of 10 ratios to be used for glass comparisons. Finally, a LA-ICP-MS method for the qualitative analysis and discrimination of gel ink sources was developed and tested for a set of ink samples. In the first discrimination study, qualitative analysis was used to obtain 95.6% discrimination for a blind study consisting of 45 black gel ink samples provided by the United States Secret Service. A 0.4% false exclusion (Type I) error rate and a 3.9% false inclusion (Type II) error rate was obtained for this discrimination study. In the second discrimination study, 99% discrimination power was achieved for a black gel ink pen set consisting of 24 self collected samples. The two pairs found to be indistinguishable came from the same source of origin (the same manufacturer and type of pen purchased in different locations). It was also found that gel ink from the same pen, regardless of the age, was indistinguishable as were gel ink pens (four pens) originating from the same pack.

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Housing Partnerships (HPs) are collaborative arrangements that assist communities in the delivery of affordable housing by combining the strengths of the public and private sectors. They emerged in several states, counties, and cities in the eighties as innovative solutions to the challenges in affordable housing resulting from changing dynamics of delivery and production. ^ My study examines HPs with particular emphasis upon the identification of those factors associated with the successful performance of their mission of affordable housing. I will use the Balanced Scorecard (BSC) framework in this study. The identification of performance factors facilitates a better understanding of how HPs can be successful in achieving their mission. The identification of performance factors is significant in the context of the current economic environment because HPs can be viewed as innovative institutional mechanisms in the provision of affordable housing. ^ The present study uses a mixed methods research approach, drawing on data from the IRS Form 990 tax returns, a survey of the chief executives of HPs, and other secondary sources. The data analysis is framed according to the four perspectives of BSC: the financial, customer, internal business, and learning and growth. Financially, revenue diversification affects the financial health of HPs and overall performance. Although HPs depend on private and government funding, they also depend on service fees to carry out their mission. From a customer perspective, the HPs mainly serve low and moderate income households, although some serve specific groups such as seniors, homeless, veterans, and victims of domestic violence. From an internal business perspective, HPs’ programs are oriented toward affordable housing needs, undertaking not only traditional activities such as construction, loan provision, etc., but also advocacy and educational programs. From an employee and learning growth perspective, the HPs are small in staff size, but undertake a range of activities with the help of volunteers. Every part of the HP is developed to maximize resources, knowledge, and skills in order to assist communities in the delivery of affordable housing and related needs. Overall, housing partnerships have played a key role in affordable housing despite the housing market downturn since 2006. Their expenses on affordable housing activities increased despite the decrease in their revenues.^

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Tall buildings are wind-sensitive structures and could experience high wind-induced effects. Aerodynamic boundary layer wind tunnel testing has been the most commonly used method for estimating wind effects on tall buildings. Design wind effects on tall buildings are estimated through analytical processing of the data obtained from aerodynamic wind tunnel tests. Even though it is widely agreed that the data obtained from wind tunnel testing is fairly reliable the post-test analytical procedures are still argued to have remarkable uncertainties. This research work attempted to assess the uncertainties occurring at different stages of the post-test analytical procedures in detail and suggest improved techniques for reducing the uncertainties. Results of the study showed that traditionally used simplifying approximations, particularly in the frequency domain approach, could cause significant uncertainties in estimating aerodynamic wind-induced responses. Based on identified shortcomings, a more accurate dual aerodynamic data analysis framework which works in the frequency and time domains was developed. The comprehensive analysis framework allows estimating modal, resultant and peak values of various wind-induced responses of a tall building more accurately. Estimating design wind effects on tall buildings also requires synthesizing the wind tunnel data with local climatological data of the study site. A novel copula based approach was developed for accurately synthesizing aerodynamic and climatological data up on investigating the causes of significant uncertainties in currently used synthesizing techniques. Improvement of the new approach over the existing techniques was also illustrated with a case study on a 50 story building. At last, a practical dynamic optimization approach was suggested for tuning structural properties of tall buildings towards attaining optimum performance against wind loads with less number of design iterations.

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Social capital, or social cohesion or group connectedness, can influence both HIV risk behavior and substance use. Because recent immigrants undergo a change in environment, one of the consequences can be a change in social capital. There may be an association among changes in social capital, and HIV risk behavior and substance use post immigration. The dissertation focused on the interface of these three variables among recent Latino immigrants (RLIs) in South Florida. The first manuscript is a systematic review of social capital and HIV risk behavior, and served as a partial background for the second and third manuscripts. Twelve papers with a measure of social capital as an independent variable and HIV risk as the dependent variable were included in the analysis. Eleven studies measured social capital at the individual level, and one study measured social capital at the group level. HIV risk was influenced by social capital, but the type of influence was dependent on the type of social capital and on the study population. Cognitive social capital, or levels of collective action, was protective against HIV in both men and women. The role of structural social capital, or levels of civic engagement/group participation, on HIV risk was dependent on the type of structural social capital and varied by gender. Microfinance programs and functional group participation were protective for women, while dysfunctional group participation and peer-level support may have increased HIV risk among men. The second manuscript was an original study assessing changes in social capital and HIV risk behavior pre to post immigration among RLIs in South Florida (n=527). HIV risk behavior was assessed through the frequency of vaginal-penile condom use, and the number of sexual partners. It was a longitudinal study using secondary data analysis to assess changes in social capital and HIV risk behavior pre immigration to two years post immigration, and to determine if there was a relationship between the two variables. There was an 8% decrease in total social capital (p < .05). Reporting of 'Never use' of condoms in the past 90 days increased in all subcategories (p < .05). Single men had a decrease in number of sexual partners (p < .05). Lower social capital measured on the dimension of 'friend and other' was marginally associated with fewer sexual partners. The third manuscript was another original study looking at the association between social capital and substance use among RLIs in South Florida (n=527). Substance use with measured by frequency of hazardous alcoholic drinking, and illicit drug use. It was a longitudinal study of social capital and substance-use from pre to two years post immigration. Post-immigration, social capital, hazardous drinking and illicit drug use decreased (p<.001). After adjusting for time, compared to males, females were less likely to engage in hazardous drinking (OR=.31, p<.001), and less likely to engage in illicit drug use (OR=.67, p=.01). Documentation status was a moderator between social capital and illicit drug use. 'Business' and 'Agency' social capital were associated with changes in illicit drug use for documented immigrants. After adjusting for gender and marital status, on average, documented immigrants with a one-unit increase in 'business' social capital were 1.2 times more likely to engage in illicit drug use (p<.01), and documented immigrants with one-unit increase in 'agency' social capital were 38% less likely to engage in illicit drug use (p<.01). 'Friend and other' social capital was associated with a decrease in illicit drug use among undocumented immigrants. After adjusting for gender and marital status, on average, undocumented immigrants with a one-unit increase in 'friend and other' social capital were 45% less likely to engage in hazardous drinking and 44% less likely to use illicit drugs (p<.01, p<.05). Studying these three domains is relevant because HIV continues to be a public health issue, particularly in Miami-Dade County, which is ranked among other U.S. regions with high rates of HIV/AIDS prevalence. Substance use is associated with HIV risk behavior; in most studies, increased substance use is associated with increased chances of HIV risk behavior. Immigration, which is the hypothesized catalyst for the change in social capital, has an impact on the dynamic of a society. Greater immigration can be burdensome on the host country's societal resources; however immigrants are also potentially a source of additional skilled labor for the workforce. Therefore, successful adaption of immigrants can have a positive influence on receiving communities. With Florida being a major receiver of immigrants to the U.S, this dissertation attempts to address an important public health issue for South Florida and the U.S. at large.

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Advanced Placement is a series of courses and tests designed to determine mastery over introductory college material. It has become part of the American educational system. The changing conception of AP was examined using critical theory to determine what led to a view of continual success. The study utilized David Armstrong's variation of Michel Foucault's critical theory to construct an analytical framework. Black and Ubbes' data gathering techniques and Braun and Clark's data analysis were utilized as the analytical framework. Data included 1135 documents: 641 journal articles, 421 newspaper articles and 82 government documents. ^ The study revealed three historical ruptures correlated to three themes containing subthemes. The first rupture was the Sputnik launch in 1958. Its correlated theme was AP leading to school reform with subthemes of AP as reform for able students and AP's gaining of acceptance from secondary schools and higher education. The second rupture was the Nation at Risk report published in 1983. Its correlated theme was AP's shift in emphasis from the exam to the course with the subthemes of AP as a course, a shift in AP's target population, using AP courses to promote equity, and AP courses modifying curricula. The passage of the No Child Left Behind Act of 2001 was the third rupture. Its correlated theme was AP as a means to narrow the achievement gap with the subthemes of AP as a college preparatory program and the shifting of AP to an open access program. ^ The themes revealed a perception that progressively integrated the program into American education. The AP program changed emphasis from tests to curriculum, and is seen as the nation's premier academic program to promote reform and prepare students for college. It has become a major source of income for the College Board. In effect, AP has become an agent of privatization, spurring other private entities into competition for government funding. The change and growth of the program over the past 57 years resulted in a deep integration into American education. As such the program remains an intrinsic part of the system and continues to evolve within American education. ^

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Women are a high-risk population for cardiovascular diseases (CVD); however relationships between CVD and subpopulations of mothers are sparse. A secondary data analysis of the 2006 Health Survey of Adults and Children in Bermuda was conducted to compare the prevalence of CVD risk factors in single (n=77) and partnered (n=241) mothers. A higher percentage of single mothers were Black (p25 kg/m2 (p=0.01) and reported high blood pressure (p=0.004) and high cholesterol (0.017). Single mothers were nearly three times (OR=2.66) more likely to experience high blood pressure and two times (OR= 2.22) more likely to have high cholesterol. Single mothers may benefit from nutrition education programs related to lowering CVD risk.

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This study investigated the nature and impact of the sexual abuse of children ages birth through 6 years. The purpose was to enhance knowledge about this understudied population through examination of: (1) characteristics of the abuse; (2) socioemotional developmental outcomes of young victims; and (3) potential moderating effects of family dynamics. An ecological-developmental theoretical framework was applied. Secondary data analysis was conducted using data collected from the consortium Longitudinal Studies of Child Abuse and Neglect (LONGSCAN). A sample of 250 children was drawn from LONGSCAN data, including children who were sexually abused (n=125) and their nonabused counterparts (n=125), matched on demographic variables. Results revealed that young victims of sexual abuse were disproportionately female (91 girls; 73%). The sexual abuse committed against these youngsters was severe in nature, with 111 children (89%) experiencing contact offenses ranging from fondling to forcible rape. Sixty-two percent of child victims demonstrated borderline, clinical, or less than adequate functioning on normative, expected socioemotional outcomes. Child victims reported low degrees of perceived competence and satisfaction in the social environment. When compared with their nonabused counterparts, child victims demonstrated significantly poorer socioemotional functioning, as evidenced by aggressive behaviors, attention and thought problems. Sexually abused youngsters also reported lower self-perceptions of cognitive and physical competence and maternal acceptance. Family dynamic factors did not significantly moderate the relationships between abuse and socioemotional outcomes, with one exception. The caregivers’ degree of empathy for their children had a significant moderating effect on the children’s social problems. This study contributes to an otherwise scant body of literature on the sexual abuse of preschoolers. Findings provide implications for social work practice, especially in the development of assessment and prevention strategies.

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This research aimed to know and analyze the pedagogical practices that have been developed in the teaching and learning of students with Intellectual Disability (DI), enrolled at common class of elementary school I. The study was conducted in a public school at Natal/RN, involving two students with DI, a multipurpose teacher, a teaching assistant, a teacher of arts and educational coordinator. As for methodological choice, we chose to develop a qualitative study, undertaking a case study. As tools for the construction of the data we use: semi-structured interviews, participant observation, field diary and document analysis. Data analysis reveals that the institution in which the research was undertaken gradually implementing changes in order to develop an inclusive practice, consistent with its assumptions. Regarding the practices developed in the teaching and learning of students with intellectual disabilities, it was possible to realize the fulfillment of certain adjustments in relation to the objectives, activities and some content, involving the use of resources and varied strategies. With regard to educational activities, we found that these had different levels of complexity, covering both basic goals as more complex objectives. From the observations, we realize that the Assistant Professor of mediations during varied activities as challenging tool in intellectual processes. We note, too, a dynamic classroom in which disabled students were under the guidance of Assistant Professor, and other students with all-round teacher who had a fairly traditional teaching methodology. It created thus an isolation situation, since there was no proposition practices to be developed with all students, and interaction among classmates, generally quite restricted. Although were highlighted developments in the social and academic learning of the surveyed students, the teachers said they did not feel prepared to work freight inclusion. The study reveals the need for teachers reviewing some actions undertaken, in order to develop more democratic pedagogical practices of education, stimulating the interactions between students, by proposing challenging activities that promote the formation and concepts. In addition, it points to the need of the education system invest and encourage the qualification of teachers with regard to education in an inclusive perspective, through actions that promote lifelong learning. It needs to be developed on the teacher a reflective attitude, resulting in a view that due diligence must be entered in practice inherent in teaching in order to use to enhance their educational experience.

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This research aimed to know and analyze the pedagogical practices that have been developed in the teaching and learning of students with Intellectual Disability (DI), enrolled at common class of elementary school I. The study was conducted in a public school at Natal/RN, involving two students with DI, a multipurpose teacher, a teaching assistant, a teacher of arts and educational coordinator. As for methodological choice, we chose to develop a qualitative study, undertaking a case study. As tools for the construction of the data we use: semi-structured interviews, participant observation, field diary and document analysis. Data analysis reveals that the institution in which the research was undertaken gradually implementing changes in order to develop an inclusive practice, consistent with its assumptions. Regarding the practices developed in the teaching and learning of students with intellectual disabilities, it was possible to realize the fulfillment of certain adjustments in relation to the objectives, activities and some content, involving the use of resources and varied strategies. With regard to educational activities, we found that these had different levels of complexity, covering both basic goals as more complex objectives. From the observations, we realize that the Assistant Professor of mediations during varied activities as challenging tool in intellectual processes. We note, too, a dynamic classroom in which disabled students were under the guidance of Assistant Professor, and other students with all-round teacher who had a fairly traditional teaching methodology. It created thus an isolation situation, since there was no proposition practices to be developed with all students, and interaction among classmates, generally quite restricted. Although were highlighted developments in the social and academic learning of the surveyed students, the teachers said they did not feel prepared to work freight inclusion. The study reveals the need for teachers reviewing some actions undertaken, in order to develop more democratic pedagogical practices of education, stimulating the interactions between students, by proposing challenging activities that promote the formation and concepts. In addition, it points to the need of the education system invest and encourage the qualification of teachers with regard to education in an inclusive perspective, through actions that promote lifelong learning. It needs to be developed on the teacher a reflective attitude, resulting in a view that due diligence must be entered in practice inherent in teaching in order to use to enhance their educational experience.

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The social media classification problems draw more and more attention in the past few years. With the rapid development of Internet and the popularity of computers, there is astronomical amount of information in the social network (social media platforms). The datasets are generally large scale and are often corrupted by noise. The presence of noise in training set has strong impact on the performance of supervised learning (classification) techniques. A budget-driven One-class SVM approach is presented in this thesis that is suitable for large scale social media data classification. Our approach is based on an existing online One-class SVM learning algorithm, referred as STOCS (Self-Tuning One-Class SVM) algorithm. To justify our choice, we first analyze the noise-resilient ability of STOCS using synthetic data. The experiments suggest that STOCS is more robust against label noise than several other existing approaches. Next, to handle big data classification problem for social media data, we introduce several budget driven features, which allow the algorithm to be trained within limited time and under limited memory requirement. Besides, the resulting algorithm can be easily adapted to changes in dynamic data with minimal computational cost. Compared with two state-of-the-art approaches, Lib-Linear and kNN, our approach is shown to be competitive with lower requirements of memory and time.

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Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

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Thermodynamic stability measurements on proteins and protein-ligand complexes can offer insights not only into the fundamental properties of protein folding reactions and protein functions, but also into the development of protein-directed therapeutic agents to combat disease. Conventional calorimetric or spectroscopic approaches for measuring protein stability typically require large amounts of purified protein. This requirement has precluded their use in proteomic applications. Stability of Proteins from Rates of Oxidation (SPROX) is a recently developed mass spectrometry-based approach for proteome-wide thermodynamic stability analysis. Since the proteomic coverage of SPROX is fundamentally limited by the detection of methionine-containing peptides, the use of tryptophan-containing peptides was investigated in this dissertation. A new SPROX-like protocol was developed that measured protein folding free energies using the denaturant dependence of the rate at which globally protected tryptophan and methionine residues are modified with dimethyl (2-hydroxyl-5-nitrobenzyl) sulfonium bromide and hydrogen peroxide, respectively. This so-called Hybrid protocol was applied to proteins in yeast and MCF-7 cell lysates and achieved a ~50% increase in proteomic coverage compared to probing only methionine-containing peptides. Subsequently, the Hybrid protocol was successfully utilized to identify and quantify both known and novel protein-ligand interactions in cell lysates. The ligands under study included the well-known Hsp90 inhibitor geldanamycin and the less well-understood omeprazole sulfide that inhibits liver-stage malaria. In addition to protein-small molecule interactions, protein-protein interactions involving Puf6 were investigated using the SPROX technique in comparative thermodynamic analyses performed on wild-type and Puf6-deletion yeast strains. A total of 39 proteins were detected as Puf6 targets and 36 of these targets were previously unknown to interact with Puf6. Finally, to facilitate the SPROX/Hybrid data analysis process and minimize human errors, a Bayesian algorithm was developed for transition midpoint assignment. In summary, the work in this dissertation expanded the scope of SPROX and evaluated the use of SPROX/Hybrid protocols for characterizing protein-ligand interactions in complex biological mixtures.

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Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.