27 resultados para management characteristics


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Background Diabetes has reached epidemic proportions in the United States, particularly among minorities, and if improperly managed can lead to medical complications and death. Healthcare providers play vital roles in communicating standards of care, which include guidance on diabetes self-management. The background of the client may play a role in the patient-provider communication process. The aim of this study was to determine the association between medical advice and diabetes self care management behaviors for a nationally representative sample of adults with diabetes. Moreover, we sought to establish whether or not race/ethnicity was a modifier for reported medical advice received and diabetes self-management behaviors. Methods We analyzed data from 654 adults aged 21 years and over with diagnosed diabetes [130 Mexican-Americans; 224 Black non-Hispanics; and, 300 White non-Hispanics] and an additional 161 with 'undiagnosed diabetes' [N = 815(171 MA, 281 BNH and 364 WNH)] who participated in the National Health and Nutrition Examination Survey (NHANES) 2007-2008. Logistic regression models were used to evaluate whether medical advice to engage in particular self-management behaviors (reduce fat or calories, increase physical activity or exercise, and control or lose weight) predicted actually engaging in the particular behavior and whether the impact of medical advice on engaging in the behavior differed by race/ethnicity. Additional analyses examined whether these relationships were maintained when other factors potentially related to engaging in diabetes self management such as participants' diabetes education, sociodemographics and physical characteristics were controlled. Sample weights were used to account for the complex sample design. Results Although medical advice to the patient is considered a standard of care for diabetes, approximately one-third of the sample reported not receiving dietary, weight management, or physical activity self-management advice. Participants who reported being given medical advice for each specific diabetes self-management behaviors were 4-8 times more likely to report performing the corresponding behaviors, independent of race. These results supported the ecological model with certain caveats. Conclusions Providing standard medical advice appears to lead to diabetes self-management behaviors as reported by adults across the United States. Moreover, it does not appear that race/ethnicity influenced reporting performance of the standard diabetes self-management behavior. Longitudinal studies evaluating patient-provider communication, medical advice and diabetes self-management behaviors are needed to clarify our findings.

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The Dahlgren and Whitehead ecological theory provides the framework for a cross-sectional design to compare socio-demographic characteristics, living and working conditions, and lifestyle daily habits as well as cultural and ecological factors among six diabetic multiethnic Black groups in Miami and Abidjan. Approximately 180 Black Americans (African-, Caribbean-, and Haitian-) and 180 Black Africans (Akan, Malinke, and Krou) aged 20 years and older were surveyed. During the preliminary of this study participants' attitudes and behaviors were qualitatively assessed (N=60) and a tool was developed to describe, in the main study (N=360), differences in participants' strength of commitment to diabetes lifestyle self-management. Despite similarities found in terms of age and gender, statistically significant differences were also found within and among groups in terms of living and working conditions, education level, and religion. African American groups were more likely to participate in more diabetes classes than Haitian Americans and Caribbean Americans. However, African Americans were less likely to adhere to daily dietary and weight control regimens. Although, Black African groups reported limited access to equipment, facilities, and financial support they were more likely to follow dietary and weight control recommendations than Black American groups. Overall, African American participants showed the poorest attitudes towards recommended foods, Caribbean American respondents reported the best attitudes and behaviors towards weight control regimens, and the Malinke group had significantly more strength of commitment to successful weight control. Furthermore, Black African groups had significantly more strength of commitment to successful dietary adherence and significantly less support for weight control than Black American groups. ^ Significant differences found within Black groups suggest that understanding each patient's conditions may help healthcare professionals in initiating individualized appropriate counseling before goal setting, and in developing culturally relevant type 2 diabetes management programs. Moreover, significant differences exist in strength of commitment to lifestyle adherence among Black groups in Miami and Abidjan. Cultural, socio-demographic factors and self-management habits may explain differences in participants' outcomes. At the policy level, Black groups should not be approached as a homogenous group and assessment of the vulnerability of each ethnic group may be necessary in the decision-making process.^

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Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

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In this paper, a heterogeneous network composed of femtocells deployed within a macrocell network is considered, and a quality-of-service (QoS)-oriented fairness metric which captures important characteristics of tiered network architectures is proposed. Using homogeneous Poisson processes, the sum capacities in such networks are expressed in closed form for co-channel, dedicated channel, and hybrid resource allocation methods. Then a resource splitting strategy that simultaneously considers capacity maximization, fairness constraints, and QoS constraints is proposed. Detailed computer simulations utilizing 3GPP simulation assumptions show that a hybrid allocation strategy with a well-designed resource split ratio enjoys the best cell-edge user performance, with minimal degradation in the sum throughput of macrocell users when compared with that of co-channel operation.

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A pivotal component of hydrological restoration of the Florida Everglades is the improvement of water conveyance to Everglades National Park by the degradation of the current network of canals, roadways and levees. The Tamiami Trail (L29) road/canal complex represents a major barrier to natural water flows into the park and a variety of modification options for flow improvement are currently being explored, including the installation of spreader swales immediately downstream of culverts conveying water under Tamiami Trail from the L29 canal into Everglades National Park. In this study, we evaluated water column chemistry and wet-season diatom community structure to provide baseline information for use in future monitoring activities related to the proposed Tamiami Trail modifications. Water chemistry showed pronounced fluctuations in response to precipitation and anthropogenically mediated hydrological events. Differences in water quality variables among sites were dampened during periods of inundation, and became more pronounced during periods of low canal stage, suggesting the importance of small-scale mechanisms related to isolation of habitat patches. Diatom assemblages were unexpectedly speciose (127 taxa in 40 samples) compared to typical Everglades assemblages, and spatially heterogeneous in sites associated with concentric areas of dense vegetation immediately downstream of culverts. We also observed significant compositional dissimilarities among transects, indicating that culvert pool and north transect assemblages were substantially influenced by propagule input from the canal and areas to the north, while south transect sites were compositionally similar to typical sawgrass prairie diatom communities. Central transect sites were compositionally intermediate to their north and south counterparts. We propose that the position and spatial extent of this “transitional assemblage” is a sensitive indicator of subtle environmental change related to Tamiami Trail modifications.

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Ecosystem management practices that modify the major drivers and stressors of an ecosystem often lead to changes in plant community composition. This paper examines how closely the trajectory of vegetation change in seasonally-flooded wetlands tracks management-induced alterations in hydrology and soil characteristics. We used trajectory analysis, a multivariate method designed to test hypotheses about rates and directions of community change, to examine vegetation shifts in response to changes in water management practices within the Taylor Slough basin of Everglades National Park. We summarized vegetation data by non-metric multidimensional scaling ordination, and examined the time trajectory of each site along environmental vectors representing hydrology and soil phosphorus gradients. In the Taylor Slough basin, vegetation change trajectories closely followed the hydrologic changes caused by the operation of water pumps and detention ponds adjacent to the canals. We also observed a shift in vegetation composition along a vector of increasing soil phosphorus, which suggests the need for implementing measures to avoid P-enrichment in southern Everglades marl prairies. This study indicates that shifts in vegetation composition in response to changes in hydrologic conditions and associated parameters may be detected through trajectory analysis, thereby providing feedback for adaptive management of wetland ecosystems.

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Background: Diabetes has reached epidemic proportions in the United States, particularly among minorities, and if improperly managed can lead to medical complications and death. Healthcare providers play vital roles in communicating standards of care, which include guidance on diabetes self-management. The background of the client may play a role in the patient-provider communication process. The aim of this study was to determine the association between medical advice and diabetes self care management behaviors for a nationally representative sample of adults with diabetes. Moreover, we sought to establish whether or not race/ethnicity was a modifier for reported medical advice received and diabetes self-management behaviors. Methods: We analyzed data from 654 adults aged 21 years and over with diagnosed diabetes [130 MexicanAmericans; 224 Black non-Hispanics; and, 300 White non-Hispanics] and an additional 161 with ‘undiagnosed diabetes’ [N = 815(171 MA, 281 BNH and 364 WNH)] who participated in the National Health and Nutrition Examination Survey (NHANES) 2007-2008. Logistic regression models were used to evaluate whether medical advice to engage in particular self-management behaviors (reduce fat or calories, increase physical activity or exercise, and control or lose weight) predicted actually engaging in the particular behavior and whether the impact of medical advice on engaging in the behavior differed by race/ethnicity. Additional analyses examined whether these relationships were maintained when other factors potentially related to engaging in diabetes self management such as participants’ diabetes education, sociodemographics and physical characteristics were controlled. Sample weights were used to account for the complex sample design. Results: Although medical advice to the patient is considered a standard of care for diabetes, approximately onethird of the sample reported not receiving dietary, weight management, or physical activity self-management advice. Participants who reported being given medical advice for each specific diabetes self-management behaviors were 4-8 times more likely to report performing the corresponding behaviors, independent of race. These results supported the ecological model with certain caveats. Conclusions: Providing standard medical advice appears to lead to diabetes self-management behaviors as reported by adults across the United States. Moreover, it does not appear that race/ethnicity influenced reporting performance of the standard diabetes self-management behavior. Longitudinal studies evaluating patient-provider communication, medical advice and diabetes self-management behaviors are needed to clarify our findings.

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Objectives: We investigated the relationship among factors predicting inadequate glucose control among 182 Cuban-American adults (Females=110, Males=72) with type 2 diabetes mellitus (CAA). Study Design: Cross-sectional study of CAA from a randomized mailing list in two counties of South Florida Methods: Fasted blood parameters and anthropometric measures were collected during the study. BMI was calculated (kg/ m2). Characteristics and diabetes care of CAA were self-reported Participants were screened by trained interviewers for heritage and diabetes status (inclusion criteria: self-reported having type 2 diabetes; age  35 years, male and female; not pregnant or lactating; no thyroid disorders; no major psychiatric disorders). Participants signed informed consent form. Statistical analyses used SPSS and included descriptive statistic, multiple logistic and ordinal logistic regression models, where all CI 95%. Results: Eighty-eight percent of CAA had BMI of ≥ 25 kg/ m2. Only 54% reported having a diet prescribed/told to schedule meals. We found CAA told to schedule meals were 3.62 more likely to plan meals (1.81, 7.26), p<0.001) and given a prescribed diet, controlling for age, corresponded with following a meal plan OR 4.43 (2.52, 7.79, p<0.001). The overall relationship for HbA1c < 8.5 to following a meal plan was OR 9.34 (2.84, 30.7. p<0.001). Conclusions: The advantage of having a medical professional prescribe a diet seems to be an important environmental support factor in this sample’s diabetes care, since obesity rates are well above the national average. Nearly half CAA are not given dietary guidance, yet our results indicate CAA may improve glycemic control by receiving dietary instructions.

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The aim of this work is to present a methodology to develop cost-effective thermal management solutions for microelectronic devices, capable of removing maximum amount of heat and delivering maximally uniform temperature distributions. The topological and geometrical characteristics of multiple-story three-dimensional branching networks of microchannels were developed using multi-objective optimization. A conjugate heat transfer analysis software package and an automatic 3D microchannel network generator were developed and coupled with a modified version of a particle-swarm optimization algorithm with a goal of creating a design tool for 3D networks of optimized coolant flow passages. Numerical algorithms in the conjugate heat transfer solution package include a quasi-ID thermo-fluid solver and a steady heat diffusion solver, which were validated against results from high-fidelity Navier-Stokes equations solver and analytical solutions for basic fluid dynamics test cases. Pareto-optimal solutions demonstrate that thermal loads of up to 500 W/cm2 can be managed with 3D microchannel networks, with pumping power requirements up to 50% lower with respect to currently used high-performance cooling technologies.

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Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

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Urban inequality has emerged as one of the dominant themes of modern life and globalization. More than three million people experienced homelessness in the United States last year; in Miami-Dade, more than 15,000 individuals were homeless. Surviving extreme poverty, and exiting or avoiding homelessness, involves negotiating a complex mix of public and private assistance. However, a range of factors influence what types of help are available and how they can be accessed. Frequently, larger social structures determine which resource are available, leaving many choices entirely out of the individual’s control. For single men, who are ineligible for many benefits, homelessness can be difficult to avoid and even harder to exit. My study seeks to better understand how adult, minority men living in extreme poverty in Miami-Dade negotiate their daily survival. Specific research questions address: Do black and Hispanic men who are homeless or at risk of homelessness have different personal characteristics and different experiences in avoiding or exiting homelessness? How does Miami’s response to extreme poverty/homelessness, including availability of public benefits and public and private service organizations, either maximize or constrain the choices available to this population? And, what is the actual experience of single, adult men who are homeless or at risk of homelessness, in negotiating their daily survival? A mixed methods approach combines quantitative survey data from 7,605 homeless men, with qualitative data from 54 semi-structured interviews incorporating the visual ethnography techniques of Photo Elicitation Interviewing. Results show the differences experienced by black and Hispanic men who are poor and homeless in Miami. Findings also highlight how the community’s official and unofficial responses to homelessness intersect with the actual experiences of the persons targeted by the policies and programs, challenging preconceived notions regarding the lives of persons living in extreme poverty. It adds to the existing body of literature by focusing on the urban Miami context, emphasizing disparities amongst racial and ethnic groups. Findings are intended to provide an empirically grounded thesis that humanizes the subjects and illuminates their personal experiences, helping to inform public policy around the needs of extremely poor populations.

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Florida is the second leading horticulture state in the United States with a total annual industry sale of over $12 Billion. Due to its competitive nature, agricultural plant production represents an extremely intensive practice with large amounts of water and fertilizer usage. Agrochemical and water management are vital for efficient functioning of any agricultural enterprise, and the subsequent nutrient loading from such agricultural practices has been a concern for environmentalists. A thorough understanding of the agrochemical and the soil amendments used in these agricultural systems is of special interest as contamination of soils can cause surface and groundwater pollution leading to ecosystem toxicity. The presence of fragile ecosystems such as the Everglades, Biscayne Bay and Big Cypress near enterprises that use such agricultural systems makes the whole issue even more imminent. Although significant research has been conducted with soils and soil mix, there is no acceptable method for determining the hydraulic properties of mixtures that have been subjected to organic and inorganic soil amendments. Hydro-physical characterization of such mixtures can facilitate the understanding of water retention and permeation characteristics of the commonly used mix which can further allow modeling of soil water interactions. The objective of this study was to characterize some of the locally and commercially available plant growth mixtures for their hydro-physical properties and develop mathematical models to correlate these acquired basic properties to the hydraulic conductivity of the mixture. The objective was also to model the response patterns of soil amendments present in those mixtures to different water and fertilizer use scenarios using the characterized hydro-physical properties with the help of Everglades-Agro-Hydrology Model. The presence of organic amendments helps the mixtures retain more water while the inorganic amendments tend to adsorb more nutrients due to their high surface area. The results of these types of characterization can provide a scientific basis for understanding the non-point source water pollution from horticulture production systems and assist in the development of the best management practices for the operation of environmentally sustainable agricultural enterprise