Self -management factors, influences, and conditions for type 2 diabetes among Black ethnic groups in Miami, Florida and Abidjan, Cote d'Ivoire

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.^

Energy-efficient self -organization of wireless acoustic sensor networks for ground target tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Fabrication of Dense Non-Circular Nanomagnetic Device Arrays Using Self-Limiting Low-Energy Glow-Discharge Processing

We describe a low-energy glow-discharge process using reactive ion etching system that enables non-circular device patterns, such as squares or hexagons, to be formed from a precursor array of uniform circular openings in polymethyl methacrylate, PMMA, defined by electron beam lithography. This technique is of a particular interest for bit-patterned magnetic recording medium fabrication, where close packed square magnetic bits may improve its recording performance. The process and results of generating close packed square patterns by self-limiting low-energy glow-discharge are investigated. Dense magnetic arrays formed by electrochemical deposition of nickel over self-limiting formed molds are demonstrated.

The Role of Family/Friend Social Support in Diabetes Self-Management for Minorities with Type 2 Diabetes

This study investigated how ethnicity, perceived family/friend social support (FSS), and health behaviors are associated with diabetes self-management (DSM) in minorities. The participants were recruited by community outreach methods and included 174 Cuban-, 121 Haitian- and 110 African-Americans with type 2 diabetes. The results indicated that ethnicity and FSS were associated with DSM. Higher FSS scores were associated with higher DSM scores, independent of ethnicity. There were ethnic differences in several elements of FSS. DSM was highest in Haitian- as compared to African-Americans; yet Haitian Americans had poorer glycemic control. The findings suggest FSS together with ethnicity may influence critical health practices. Studies are needed that further investigate the relationships among minorities with diabetes, their intimate network (family and friends) and the diabetes care process.

Medical Advice and Diabetes Self-Management Reported by Mexican-American, Black- and White-Non-Hispanic Adults Across the United States

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.

Self-tuning algorithm for dsp-based motion control in cnc applications

This thesis describes the development of an adaptive control algorithm for Computerized Numerical Control (CNC) machines implemented in a multi-axis motion control board based on the TMS320C31 DSP chip. The adaptive process involves two stages: Plant Modeling and Inverse Control Application. The first stage builds a non-recursive model of the CNC system (plant) using the Least-Mean-Square (LMS) algorithm. The second stage consists of the definition of a recursive structure (the controller) that implements an inverse model of the plant by using the coefficients of the model in an algorithm called Forward-Time Calculation (FTC). In this way, when the inverse controller is implemented in series with the plant, it will pre-compensate for the modification that the original plant introduces in the input signal. The performance of this solution was verified at three different levels: Software simulation, implementation in a set of isolated motor-encoder pairs and implementation in a real CNC machine. The use of the adaptive inverse controller effectively improved the step response of the system in all three levels. In the simulation, an ideal response was obtained. In the motor-encoder test, the rise time was reduced by as much as 80%, without overshoot, in some cases. Even with the larger mass of the actual CNC machine, decrease of the rise time and elimination of the overshoot were obtained in most cases. These results lead to the conclusion that the adaptive inverse controller is a viable approach to position control in CNC machinery.

Exploring therapy process and outcome in interventions that target at risk adolescents

The purpose of this study was to conduct a larger scale replication and extension study on the use of a Session Impact Measure the Session Evaluation Form. Ninety-one public high school students in Miami Florida were obtained through self or counselor referrals and placed in one or two of five counseling groups for one or two school semesters. To investigate differences in therapy processes across counseling groups, participants were administered a Session Evaluation Form at the end of each therapy session. This assessed group members' perception of four therapy process domains, Group, Facilitator, Skills and Exploration Impacts. The pattern significant results for the MANOVAs provided strong evidence for the greater impact of the group on therapy process relative to the impact of facilitator. Further research is needed to identify more specifically, ways, group process differences interact with other treatment variables.

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

The Impact of Social Comparison Processes on Hoped-For Possible Selves, Self-Regulatory Processes, and Mental Health Outcomes in Young Adults

In exploring the role of social influences in the development of the self, the current study evaluated whether young adults use social comparisons in developing their hoped-for possible selves and, if so, whether their developmental process correlates with self-regulatory processes and positive mental health outcomes. The current study found the following: (1) the domains of hoped-for possible selves among young adults were related to the gender of the social comparison target, (2) the direction of young adults’ social comparison processes (upward or downward) did not significantly influence self-regulatory processes (self-efficacy and outcome expectancy) toward achieving their hoped-for possible selves, (3) strong masculine gender identification related to greater outcome expectancy, while strong feminine gender identification related to both greater self-efficacy and outcome expectancy, and (4) self-efficacy related to less state anxiety, trait anxiety, and depression, while outcome expectancy related only to less trait anxiety. Males and females were found to use traditional gender role identification in forming their hoped-for possible selves.