This paper presents experiences and lessons from the structural health monitoring practice on the Tamar Bridge in Plymouth, UK, a 335m span suspension bridge opened in 1961. After 40 years of operations the bridge was strengthened and widened in 2001 to meet a European Union requirement to carry heavy goods vehicles up to 40 tonnes weight, a process in which additional stay cables and cantilever decks were added and the composite deck was replaced with a lightweight orthotropic steel deck. At that time a structural monitoring system comprising wind, temperature, cable tension and deck level sensors was installed to monitor the bridge behaviour during and after the upgrading. In 2006 and 2009 respectively, a dynamic response monitoring system with real time modal parameter identification and a three-dimensional total positioning system were added to provide a more complete picture of the bridge behavior, and in 2006 a one day ambient vibration survey of the bridge was carried out to characterize low frequency vibration modes of the suspended structure. Practical aspects of the instrumentation and data processing & management are discussed and some key response observations are presented. The bridge is a surprisingly complex structure with a number of inter-linked load-response mechanisms evident, all of which have to be characterized as part of a long term structural health monitoring exercise. Structural temperature leading to thermal expansion of the deck, main cables and additional stays is a major factor on global deformation, while vehicle loading and wind are apparently secondary factors. Dynamic response levels and modal parameters show apparently complex relationships among themselves and with the quasi-static load and response. As well as the challenges of fusing and managing data from three distinct but parallel monitoring systems, there is a significant challenge in interpreting the load and response data firstly to diagnose the normal service behavior and secondly to identify performance anomalies.

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Summary. To examine the temporal relationship between Hb Aic values and various indices of blood glucose control, 38 diabetic and 28 nondiabetic youth counsellors employed at two summer camps for diabetic children took part in an eight-week study. Each week fasting determinations were made of Hb AI, Hb Al~ , serum cholesterol, triglyceride and growth hormone and plasma glucose. Total daily urine glucose excretion was measured approximately two times per week, capillary glucose values were measured fasting and at 11 a. m. and 3 p. m. on two days per week, and urine glucose was measured semiquantitatively four times per day. As Hb AI was correlated highly with Hb AI0 (r = 0.997), it was used as the primary index of glycosylated haemoglobin. The mean values of Hb AI, serum cholesterol and triglycerides and fasting plasma glucose were all significantly elevated in the diabetic group but only Hb AI values provided total separation of the two groups. Within the diabetic group the Week 8 Hb A I values showed a significant correlation with the Week 8 mean capillary glucose concentrations, the proportion of urine tests showing 2% and 0% glycosuria, and mean serum triglycerides. Correlations of Week 8 Hb A~ with the mean values of these glycaemic parameters for each week of the study demonstrated low order correlations with the glycaemie measures of Week 1, and a progressive increase in the degree of correlation reaching a plateau with the glycaernic measures of Week 4 to 8. Similar correlation analysis using the Hb Ai values from Week 4 confirmed these findings. Therefore, while Hb AI provides an index of the control of diabetes, it appears to be more acutely responsive to blood glucose alteration than generally recognized.