349 research outputs found

    Wide-Band, High-Quantum-Efficiency Photodetector

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    A design has been proposed for a photodetector that would exhibit a high quantum efficiency (as much as 90 percent) over a wide wavelength band, which would typically be centered at a wavelength of 1.55 m. This and similar photodetectors would afford a capability for detecting single photons - a capability that is needed for research in quantum optics as well as for the practical development of secure optical communication systems for distribution of quantum cryptographic keys. The proposed photodetector would be of the hot-electron, phonon-cooled, thin-film superconductor type. The superconducting film in this device would be a meandering strip of niobium nitride. In the proposed photodetector, the quantum efficiency would be increased through incorporation of optiA design has been proposed for a photodetector that would exhibit a high quantum efficiency (as much as 90 percent) over a wide wavelength band, which would typically be centered at a wavelength of 1.55 m. This and similar photodetectors would afford a capability for detecting single photons - a capability that is needed for research in quantum optics as well as for the practical development of secure optical communication systems for distribution of quantum cryptographic keys. The proposed photodetector would be of the hot-electron, phonon-cooled, thin-film superconductor type. The superconducting film in this device would be a meandering strip of niobium nitride. In the proposed photodetector, the quantum efficiency would be increased through incorporation of opti

    The Relation of Patient Dependence to Home Health Aide Use in Alzheimer's Disease

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    BACKGROUND: Although there has been much research devoted to understanding the predictors of nursing home placement (NHP) in Alzheimer's disease (AD) patients, there is currently a lack of research concerning the predictors of home health care. The objective of this study was to examine whether the Dependence Scale can predict home health aide (HHA) use. METHODS: The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed annually for up to 7 years in three university-based AD centers in the United States. Markov analyses (n=75) were used to calculate annual transition probabilities for the "new onset" of HHA use (instances where an HHA was absent at the previous visit, but present at the next visit) as a function of HHA presence at the preceding year's visit and dependence level at that preceding year's visit. RESULTS: The dependence level at the previous year's visit was a significant predictor of HHA use at the next year's visit. Three specific items of the Dependence Scale (needing household chores done for oneself, needing to be watched or kept company when awake, and needing to be escorted when outside) were significant predictors of the presence of an HHA. CONCLUSION: The Dependence Scale is a valuable tool for predicting HHA use in AD patients. Obtaining a better understanding of home health care in AD patients may help delay NHP and have a positive impact on the health and well-being of both the caregiver and the patient

    Change in Body Mass Index before and after Alzheimer's Disease Onset

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    OBJECTIVES: A high body mass index (BMI) in middle-age or a decrease in BMI at late-age has been considered a predictor for the development of Alzheimer's disease (AD). However, little is known about the BMI change close to or after AD onset. METHODS: BMI of participants from three cohorts, the Washington Heights and Inwood Columbia Aging Project (WHICAP; population-based) and the Predictors Study (clinic-based), and National Alzheimer's Coordinating Center (NACC; clinic-based) were analyzed longitudinally. We used generalized estimating equations to test whether there were significant changes of BMI over time, adjusting for age, sex, education, race, and research center. Stratification analyses were run to determine whether BMI changes depended on baseline BMI status. RESULTS: BMI declined over time up to AD clinical onset, with an annual decrease of 0.21 (p=0.02) in WHICAP and 0.18 (p=0.04) kg/m2 in NACC. After clinical onset of AD, there was no significant decrease of BMI. BMI even increased (b=0.11, p=0.004) among prevalent AD participants in NACC. During the prodromal period, BMI decreased over time in overweight (BMI>/=25 and /=30) NACC participants. After AD onset, BMI tended to increase in underweight/normal weight (BMI<25) patients and decrease in obese patients in all three cohorts, although the results were significant in NACC study only. CONCLUSIONS: Our study suggests that while BMI declines before the clinical AD onset, it levels off after clinical AD onset, and might even increase in prevalent AD. The pattern of BMI change may also depend on the initial BMI
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