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Background: Studies have demonstrated women to have a higher prevalence of dementia compared to men. However, sex differences in dementia incidence are controversial with conflicting reports showing women with higher, lower, or similar incidence. Source of difference may be due to clinical setting and lack of consideration of competing risk of death. We examined dementia incidence in a sample of the national Veteran population to determine differences by sex.Methods: We examined data from the Veterans Health Administration (VHA), the largest integrated health care system in the United States. We studied 947 797 Veterans aged ≥55 years (mean age: 69.9 ± 8.4, 3% female) evaluated in the VHA from October 1, 1999 to September 30, 2019. We estimated age-adjusted incidence rates of dementia (International Classification of Diseases, 9th and 10th Edition codes) by sex, and used Fine-Gray proportional hazards models with age as time scale to examine time to diagnosis, accounting for competing risk of death.Results: During the follow-up (mean 8.4 years), 11.3% (n = 106 977, 11.4% men and 8.0% women) of Veterans developed dementia. Age-adjusted incidence was 12.6/1 000 person-years for men and 12.7/1 000 person-years for women. Compared to male Veterans, risk dementia was slightly higher among females (hazard ratio = 1.15; 95% confidence interval: 1.10-1.20), and on average, female Veterans developed dementia 0.2 years earlier than male Veterans. After additional adjustment for race, education, medical, and psychiatric conditions, results were similar.Conclusions: Among older Veterans in a national cohort, women had a slightly increased risk for developing dementia compared to men after accounting for competing risk of death. [ABSTRACT FROM AUTHOR]

In many radio-frequency identification (RFID) applications, one of the essential systematic functionalities is to quickly detect missing-tag event in case of misplacement or other incorrect operations. In this paper, we focus on probabilistically detecting the missing tags for the anonymous multicategory RFID systems without revealing the tag privacy. The main objective is to minimize the detection time while satisfying the required detection reliability of each category. First, we propose to use a multihash technique to sequentially detect the missing tags category-by-category, called segmented sequential detection approach, in which the frame segmentation is adopted to reduce the detection time. Then, we propose an enhanced segmented sequential detection approach to further improve the detection efficiency by deactivating the identified existing tags. We conduct extensive simulations to illustrate the effectiveness of our proposed two missing tag detection approaches. [ABSTRACT FROM AUTHOR]