6 resultados para multi-method study

em Duke University


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BACKGROUND: Recent studies have found low-normal potassium (K) to be associated with increased diabetes risk. We sought to verify these associations in a multi-ethnic US cohort; and to determine if these associations extend to US Hispanics and Asian-Americans. METHODS: We analyzed data from Multi-Ethnic Study of Atherosclerosis (MESA) participants who were free-of-diabetes at baseline. We examined cross-sectional associations between measures of K-serum, dietary, and urine-with fasting glucose and HOMA-IR. We examined longitudinal associations between K and diabetes risk over 8 years. FINDINGS: In multivariable models, compared to those with higher serum K (≥4.5mmol/L), those with lower serum K (<4.0mmol/L) had significantly higher fasting glucose [1.3 mg/dL (95%CI 0.2, 2.4), P-value = 0.03]. Incident diabetes developed in 1281 of 5415 at-risk participants. In minimally-adjusted models, we found inverse associations between serum and dietary K and diabetes risk. Compared to those with higher serum K, those with lower serum K had an HR (95% CI) of incident diabetes of 1.23 (1.04, 1.47), P-value = 0.02. However, these associations were attenuated in fully-adjusted models. We found no significant interaction between potassium and ethnicity. CONCLUSIONS: In this multi-ethnic cohort, we found a significant inverse association between serum K and fasting glucose but no significant association with longer-term diabetes risk. This inverse association between potassium and glucose must be studied further to understand the physiology and its potential impact on chronic health.

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This research project involves a comparative, cross-national study of truth and reconciliation commissions (TRCs) in countries around the world that have used these extra-judicial institutions to pursue justice and promote national reconciliation during periods of democratic transition or following a civil conflict marked by intense violence and severe human rights abuses. An important objective of truth and reconciliation commissions involves instituting measures to address serious human rights abuses that have occurred as a result of discrimination, ethnocentrism and racism. In recent years, rather than solely utilizing traditional methods of conflict resolution and criminal prosecution, transitional governments have established truth and reconciliation commissions as part of efforts to foster psychological, social and political healing.

The primary objective of this research project is to determine why there has been a proliferation of truth and reconciliation commissions around the world in recent decades, and assess whether the perceived effectiveness of these commissions is real and substantial. In this work, using a multi-method approach that involves quantitative and qualitative analysis, I consider the institutional design and structural composition of truth and reconciliation commissions, as well as the roles that these commissions play in the democratic transformation of nations with a history of civil conflict and human rights violations.

In addition to a focus on institutional design of truth and reconciliation commissions, I use a group identity framework that is grounded in social identity theory to examine the historical background and sociopolitical context in which truth commissions have been adopted in countries around the world. This group identity framework serves as an invaluable lens through which questions related to truth and reconciliation commissions and other transitional justice mechanisms can be explored. I also present a unique theoretical framework, the reconciliatory democratization paradigm, that is especially useful for examining the complex interactions between the various political elements that directly affect the processes of democratic consolidation and reconciliation in countries in which truth and reconciliation commissions have been established. Finally, I tackle the question of whether successor regimes that institute truth and reconciliation commissions can effectively address the human rights violations that occurred in the past, and prevent the recurrence of these abuses.

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As the world population continues to grow past seven billion people and global challenges continue to persist including resource availability, biodiversity loss, climate change and human well-being, a new science is required that can address the integrated nature of these challenges and the multiple scales on which they are manifest. Sustainability science has emerged to fill this role. In the fifteen years since it was first called for in the pages of Science, it has rapidly matured, however its place in the history of science and the way it is practiced today must be continually evaluated. In Part I, two chapters address this theoretical and practical grounding. Part II transitions to the applied practice of sustainability science in addressing the urban heat island (UHI) challenge wherein the climate of urban areas are warmer than their surrounding rural environs. The UHI has become increasingly important within the study of earth sciences given the increased focus on climate change and as the balance of humans now live in urban areas.

In Chapter 2 a novel contribution to the historical context of sustainability is argued. Sustainability as a concept characterizing the relationship between humans and nature emerged in the mid to late 20th century as a response to findings used to also characterize the Anthropocene. Emerging from the human-nature relationships that came before it, evidence is provided that suggests Sustainability was enabled by technology and a reorientation of world-view and is unique in its global boundary, systematic approach and ambition for both well being and the continued availability of resources and Earth system function. Sustainability is further an ambition that has wide appeal, making it one of the first normative concepts of the Anthropocene.

Despite its widespread emergence and adoption, sustainability science continues to suffer from definitional ambiguity within the academe. In Chapter 3, a review of efforts to provide direction and structure to the science reveals a continuum of approaches anchored at either end by differing visions of how the science interfaces with practice (solutions). At one end, basic science of societally defined problems informs decisions about possible solutions and their application. At the other end, applied research directly affects the options available to decision makers. While clear from the literature, survey data further suggests that the dichotomy does not appear to be as apparent in the minds of practitioners.

In Chapter 4, the UHI is first addressed at the synoptic, mesoscale. Urban climate is the most immediate manifestation of the warming global climate for the majority of people on earth. Nearly half of those people live in small to medium sized cities, an understudied scale in urban climate research. Widespread characterization would be useful to decision makers in planning and design. Using a multi-method approach, the mesoscale UHI in the study region is characterized and the secular trend over the last sixty years evaluated. Under isolated ideal conditions the findings indicate a UHI of 5.3 ± 0.97 °C to be present in the study area, the magnitude of which is growing over time.

Although urban heat islands (UHI) are well studied, there remain no panaceas for local scale mitigation and adaptation methods, therefore continued attention to characterization of the phenomenon in urban centers of different scales around the globe is required. In Chapter 5, a local scale analysis of the canopy layer and surface UHI in a medium sized city in North Carolina, USA is conducted using multiple methods including stationary urban sensors, mobile transects and remote sensing. Focusing on the ideal conditions for UHI development during an anticyclonic summer heat event, the study observes a range of UHI intensity depending on the method of observation: 8.7 °C from the stationary urban sensors; 6.9 °C from mobile transects; and, 2.2 °C from remote sensing. Additional attention is paid to the diurnal dynamics of the UHI and its correlation with vegetation indices, dewpoint and albedo. Evapotranspiration is shown to drive dynamics in the study region.

Finally, recognizing that a bridge must be established between the physical science community studying the Urban Heat Island (UHI) effect, and the planning community and decision makers implementing urban form and development policies, Chapter 6 evaluates multiple urban form characterization methods. Methods evaluated include local climate zones (LCZ), national land cover database (NCLD) classes and urban cluster analysis (UCA) to determine their utility in describing the distribution of the UHI based on three standard observation types 1) fixed urban temperature sensors, 2) mobile transects and, 3) remote sensing. Bivariate, regression and ANOVA tests are used to conduct the analyses. Findings indicate that the NLCD classes are best correlated to the UHI intensity and distribution in the study area. Further, while the UCA method is not useful directly, the variables included in the method are predictive based on regression analysis so the potential for better model design exists. Land cover variables including albedo, impervious surface fraction and pervious surface fraction are found to dominate the distribution of the UHI in the study area regardless of observation method.

Chapter 7 provides a summary of findings, and offers a brief analysis of their implications for both the scientific discourse generally, and the study area specifically. In general, the work undertaken does not achieve the full ambition of sustainability science, additional work is required to translate findings to practice and more fully evaluate adoption. The implications for planning and development in the local region are addressed in the context of a major light-rail infrastructure project including several systems level considerations like human health and development. Finally, several avenues for future work are outlined. Within the theoretical development of sustainability science, these pathways include more robust evaluations of the theoretical and actual practice. Within the UHI context, these include development of an integrated urban form characterization model, application of study methodology in other geographic areas and at different scales, and use of novel experimental methods including distributed sensor networks and citizen science.

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We examined how individual differences in social understanding contribute to variability in early-appearing prosocial behavior. Moreover, potential sources of variability in social understanding were explored and examined as additional possible predictors of prosocial behavior. Using a multi-method approach with both observed and parent-report measures, 325 children aged 18-30 months were administered measures of social understanding (e.g., use of emotion words; self-understanding), prosocial behavior (in separate tasks measuring instrumental helping, empathic helping, and sharing, as well as parent-reported prosociality at home), temperament (fearfulness, shyness, and social fear), and parental socialization of prosocial behavior in the family. Individual differences in social understanding predicted variability in empathic helping and parent-reported prosociality, but not instrumental helping or sharing. Parental socialization of prosocial behavior was positively associated with toddlers' social understanding, prosocial behavior at home, and instrumental helping in the lab, and negatively associated with sharing (possibly reflecting parents' increased efforts to encourage children who were less likely to share). Further, socialization moderated the association between social understanding and prosocial behavior, such that social understanding was less predictive of prosocial behavior among children whose parents took a more active role in socializing their prosociality. None of the dimensions of temperament was associated with either social understanding or prosocial behavior. Parental socialization of prosocial behavior is thus an important source of variability in children's early prosociality, acting in concert with early differences in social understanding, with different patterns of influence for different subtypes of prosocial behavior.

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Prior to the Civil Rights Movement, fewer than 50 Black judges had been elected or appointed to the judiciary. As of August 2015, there are over 1,000 Black state and federal judges. As the number of black judges has increased, one question arises: have American courts been altered purely by this substantial increase? One expectation—and, at times, a prediction—behind the increased descriptive representation of Black judges is that their mere presence would alter the judiciary. It was supposed that these judges would substantively represent Black interests in the decisions they made. In other words, it was suspected, and predicted, that Blacks in the judiciary would enhance equality and justice by being aware of, responsive to, and advocating for African Americans. This theory about the likely role of Black judges derives from theoretical work on political representation and racial group consciousness, and empirical studies of Black elite behavior in other political institutions.

Despite such predictions, there is no corresponding scholarly consensus regarding whether Black judges possess a racial group consciousness and have racially distinctive judicial behavior. Therefore, the theory undergirding the demand for increased diversification, as a means to transform the judiciary, remains unsubstantiated. This is precisely where this project, “They’re There, Now What?: The Identities, Behavior, and Perceptions of Black Judges,” seeks to intervene in and explore, if not settle, the matter of whether black judges possess a racial group consciousness and exhibit racially-distinctive judicial behavior. It addresses a set of interrelated questions relevant to understanding whether we can view Black judges as representatives in ways that are similar to how we view other Black political officials. I examine these questions using a multi-method approach. For my analyses, I draw on diverse materials: the published biographies of every Black judge appointed to the federal bench, a survey experiment with a nationally-representative adult sample, and semi-structured interviews with 30 Black judges.

This research, which engages with scholarship on representation, group consciousness, judicial behavior, and candidate perceptions, offers new insights into the lives, perceptions, and behavior of Black judges, as well as the manifestations of Black substantive representation in the judiciary. My dissertation argues that, despite the general reluctance to use the term “representation” when referring to judges, we can consider Black judges as representatives. Black judges behave as substantive representatives by (1) sharing and understanding the experience, history, and perspectives of Black Americans, (2) challenging language, persons, policies, and laws they feel negatively affect, or violate the rights and liberties of, African Americans, (3) respecting African American litigants, and (4) ensuring the rights of African Americans are protected and the needs of black Americans are being met.

Only through research that considers the perspectives, identities, perceptions, and behavior of Black judges will we arrive at a more comprehensive understanding of the importance of racial diversity in the courts. As this project finds, a link between descriptive representation and substantive representation can, and frequently does exist within the judicial context. Such a link is significant given that Blacks’ liberty and justice through the American legal system continues to be subject to those who exercise judicial power. This dissertation has implications for the discourse surrounding the need for increased descriptive and substantive representation of Blacks in the judiciary, and the factors that affect representation in the justice system.

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Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.