Robust Synchronization of Ambient Vibration Time Histories Based on Phase Angle Compensations and Kernel Density Function.

The output-only modal analysis is ubiquitously used for structural health monitoring of civil engineering systems. The measurements for such applications require the use of multiple data acquisition systems (DAS) to avoid complicated meshes of cables in high-rise buildings, avoid traffic constriction on a bridge during measurements, or to avoid having limited channels in a single DAS. Nevertheless, such requirements introduce time synchronization problems which potentially lead to erroneous structural dynamic characterization and hence misleading or inconclusive structural health monitoring results. This research aims at proposing a system-identification-based time synchronization algorithm for output-only modal analysis using multiple DAS. A new procedure based on the compensation of the phase angle shifts is proposed to identify and address the time synchronization issue in ambient vibration data measured through multiple DAS. To increase the robustness of the proposed algorithm to the inherent inconsistencies in these datasets, the kernel density function is applied to rank multiple time-shift estimates that are sometimes detected by the algorithm when inaccuracies exist in the data arising from low signal-to-noise ratio and/or presence of colored noise in the ambient excitations. First, the synchronized ambient vibration dataset of a full-scale bridge is artificially de-synchronized and used to present a proof of concept for the proposed algorithm. Next, the algorithm is applied to ambient vibration data of a 30-story, reinforced concrete building, where the synchronization of the data could not be achieved using two DAS despite best efforts. The application of the proposed time synchronization algorithm is shown to both detect and correct the time synchronization discrepancies in the output-only modal analysis.

Prevalence of HIV and hepatitis B virus among pregnant women in Luanda (Angola): geospatial distribution and its association with socio-demographic and clinical-obstetric determinants.

BACKGROUND: HIV and HBV infections remain responsible for high rate of morbidity and mortality in many African Countries, affecting women and newborns. This study aims to analyze the spatial pattern of HIV and HBV infections in pregnant women in Luanda, Angola, and the statistical association between HIV and HBV and socio-economic characteristics, hygiene, and health status. METHODS: Detection of anti-HIV antibodies (total anti-HIV-1, anti-HIV-2 and HIV-1 p24 antigen) and Hepatitis B antigens (HBsAg, HBeAg) and antibodies (anti-HBc Total II, HBc IgM, Anti-HBsT II) was performed by Enzyme Linked Fluorescent Assay (ELFA) in serum samples of 878 pregnant women attended at the Lucrecia Paim Maternity Hospital (LPMH). Data were collected by questionnaire after written consent, and spatial distribution was assessed through a Kernel Density Function. The potential risk factors associated with HIV HBV infection were evaluated using bivariate and multivariate binomial logistic regression analysis. RESULTS: Anti-HIV antibodies were positive in 118 samples (13.4%) and HBV infection were positive in 226 (25.7%). The seroprevalence of HIV/HBV coinfection was of 6.3%. The results showed that the seroprevalence of HBV was similar in most municipalities: 25.8% in Belas; 26.6% in Viana; 27.6% in Luanda; 19.2% in Cacuaco; and 15.6% Cazenga. For HIV, the seroprevalence was also close ranges among the municipalities: 10.0% in Belas; 14.5% in Viana 14.9% in Luanda and 12.5% in Cazenga. However, the seroprevalence in municipality of in Cacuaco was lower (5.8%) and bivariate and multivariate analysis showed a lower risk for HIV in this area (OR 0.348, CI 0.083-0.986; OR 0.359, CI 0.085-1.021). The multivariate analysis had also showed a significant increased risk for HIV in women with 2 or 3 births (OR 1.860, CI 1.054-3.372). CONCLUSIONS: Our results underlined the need to improve the screening and clinical follow-up of HIV and HBV in Angola, as well the educational campaigns to prevent not only the morbidity and mortality associated with these diseases, but also their transmission, mainly in women in reproductive age and pregnant, encouraging the pre-natal consultations in order to avoid mother-to-child transmission.

Developing a Health Risk Evaluation Method for Triple H.

The development of a health evaluation system from human-related data is an important issue in preventive medicine. Previously, most studies have focused on disease assessment and prevention in patients. However, even if certain risk factors are all within normal ranges, individuals may not necessarily be completely healthy. This study focused on healthy individuals to develop a new index to assess health risks; this index can be used for the prevention of multiple diseases in healthy people. The kernel density technique was proposed to estimate the distribution of common risk factors and to develop a health risk index. A dataset of hypertension, hyperlipidemia, and hyperglycemia (Triple H) data from the National Health Insurance Research Database in Taiwan was used to demonstrate the proposed analytical process. The results of risk factor changes after six weeks of exercise were used to calculate the health risk index. The results showed that the subjects experienced a 7.29% reduction in their health risk index after the exercise intervention. This finding demonstrates the potential impact of an important reference index on quantifying the effect of maintenance in healthy people.