2 resultados para 902

em Digital Commons at Florida International University


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With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.

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Miami-Dade County has approximately 27,000 people living with HIV (PLWH), and the highest HIV incidence in the nation. PLWH have reported several types of sleep disturbances. Caffeine is an anorexic and lipolytic stimulant that may adversely affect sleep patterns, dietary intakes and body composition. High caffeine consumption (>250 mg. per day or the equivalent of >4 cups of brewed coffee) may also affect general functionality, adherence to antiretroviral treatment (ART) and HIV care. This study assess the relationship of high caffeine intake with markers of disease progression, sleep quality, insomnia, anxiety, nutritional intakes and body composition. A convenience sample of 130 PLWH on stable ART were recruited from the Miami Adult Studies on HIV (MASH) cohort, and followed for three months. After consenting, questionnaires on Modified Caffeine Consumption (MCCQ), Pittsburg Insomnia Rating Scale (PIRS), Pittsburg Sleep Quality Index (PSQI), Generalized Anxiety Disorder-7 (GAD-7), socio-demographics, drug and medication use were completed. CD4 count, HIV viral load, anthropometries, and body composition measures were obtained. Mean age was 47.89±6.37 years, 60.8% were male and 75.4% were African-Americans. Mean caffeine intake at baseline was 337.63 ± 304.97 mg/day (Range: 0-1498 mg/day) and did not change significantly at 3 months. In linear regression, high caffeine consumption was associated with higher CD4 cell count (β=1.532, P=0.049), lower HIV viral load (β=-1.067, P=0.048), higher global PIRS (β=1.776, P=0.046), global PSQI (β=2.587, P=0.038), and GAD-7 scores (β=1.674, P=0.027), and with lower fat mass (β=-0.994, P=0.042), energy intakes (β=-1.643, P=0.042) and fat consumption (β=-1.902, P=0.044), adjusting for relevant socioeconomic and disease progression variables. Over three months, these associations remained significant. The association of high caffeine with lower BMI weakened when excluding users of other anorexic and stimulant drugs such as cocaine and methamphetamine, suggesting that caffeine in combination, but not alone, may worsen their action. In summary, high caffeine consumption was associated with better measures of disease progression; but was also detrimental on sleep quality, nutritional intakes, BMI and body composition and associated with insomnia and anxiety. Large scale studies for longer time are needed to elucidate the contribution of caffeine to the well-being of PLWH.