Occupational health for an ageing workforce: Do we need a geriatric perspective?

10.1186/1745-6673-1-8Journal of Occupational Medicine and Toxicology11

Stress relief as the driving force for self-assembled Bi nanolines

Stress resulting from mismatch between a substrate and an adsorbed material has often been thought to be the driving force for the self-assembly of nanoscale structures. Bi nanolines self-assemble on Si(001), and are remarkable for their straightness and length -- they are often more than 400 nm long, and a kink in a nanoline has never been observed. Through electronic structure calculations, we have found an energetically favourable structure for these nanolines that agrees with our scanning tunneling microscopy and photoemission experiments; the structure has an extremely unusual subsurface structure, comprising a double core of 7-membered rings of silicon. Our proposed structure explains all the observed features of the nanolines, and shows that surface stress resulting from the mismatch between the Bi and the Si substrate are responsible for their self-assembly. This has wider implications for the controlled growth of nanostructures on semiconductor surfaces.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Let

Evaluation of the utility of sediment data in NASQAN (National Stream Quality Accounting Network)

Monthly suspended sediment discharge measurements, made by the USGS as part of the National Stream Quality Accounting Network (NASQAN), are analysed to assess the adequacy in terms of spatial coverage, temporal sampling frequency, accuracy of measurements, as well as in determining the sediment yield in the nation's rivers. It is concluded that the spatial distribution of NASQAN stations is reasonable but necessarily judgemental. The temporal variations of sediment data contain much higher frequencies than monthly. Sampling error is found to be minor when compared with other causes of data scatter which can be substantial. The usefulness of the monthly measurements of sediment transport is enhanced when combined with the daily measurements of water discharge. Increasing the sampling frequency moderately would not materially improve the accuracy of sediment yield determinations

Manifestation Of Differences In Item-Level Characteristics In Scale-Level Measurement Invariance Tests Of Multi-Group Confirmatory Factor Analyses

If a researcher applies the conventional tests of scale-level measurement invariance through multi-group confirmatory factor analysis of a PC matrix and MLE to test hypotheses of strong and full measurement invariance when the researcher has a rating scale response format wherein the item characteristics are different for the two groups of respondents, do these scale-level analyses reflect (or ignore) differences in item threshold characteristics? Results of the current study demonstrate the inadequacy of judging the suitability of a measurement instrument across groups by only investigating the factor structure of the measure for the different groups with a PC matrix and MLE. Evidence is provided that item level bias can still be present when a CFA of the two different groups reveals an equivalent factorial structure of rating scale items using a PC matrix and MLE

Multi-Group Confirmatory Factor Analysis for Testing Measurement Invariance in Mixed Item Format Data

This simulation study investigated the empirical Type I error rates of using the maximum likelihood estimation method and Pearson covariance matrix for multi-group confirmatory factor analysis (MGCFA) of full and strong measurement invariance hypotheses with mixed item format data that are ordinal in nature. The results indicate that mixed item formats and sample size combinations do not result in inflated empirical Type I error rates for rejecting the true measurement invariance hypotheses. Therefore, although the common methods are in a sense sub-optimal, they don’t lead to researchers claiming that measures are functioning differently across groups – i.e., a lack of measurement invariance

Self-reported domain-specific and accelerometer-based physical activity and sedentary behaviour in relation to psychological distress among an urban Asian population

Background: The interpretation of previous studies on the association of physical activity and sedentary behaviour with psychological health is limited by the use of mostly self-reported physical activity and sedentary behaviour, and a focus on Western populations. We aimed to explore the association of self-reported and devise-based measures of physical activity and sedentary behaviour domains on psychological distress in an urban multi-ethnic Asian population. Methods: From a population-based cross-sectional study of adults aged 18-79 years, data were used from an overall sample (n = 2653) with complete self-reported total physical activity/sedentary behaviour and domain-specific physical activity data, and a subsample (n = 703) with self-reported domain-specific sedentary behaviour and accelerometry data. Physical activity and sedentary behaviour data were collected using the Global Physical Activity Questionnaire (GPAQ), a domain-specific sedentary behaviour questionnaire and accelerometers. The Kessler Screening Scale (K6) and General Health Questionnaire (GHQ-12) were used to assess psychological distress. Logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals, adjusted for socio-demographic and lifestyle characteristics. Results: The sample comprised 45.0% men (median age = 45.0 years). The prevalence of psychological distress based on the K6 and GHQ-12 was 8.4% and 21.7%, respectively. In the adjusted model, higher levels of self-reported moderate-to-vigorous physical activity (MVPA) were associated with significantly higher odds for K6 (OR = 1.47 [1.03-2.10]; p-trend = 0.03) but not GHQ-12 (OR = 0.97 [0.77-1.23]; p-trend = 0.79), when comparing the highest with the lowest tertile. Accelerometry-assessed MVPA was not significantly associated with K6 (p-trend = 0.50) nor GHQ-12 (p-trend = 0.74). The highest tertile of leisure-time physical activity, but not work- or transport-domain activity, was associated with less psychological distress using K6 (OR = 0.65 [0.43-0.97]; p-trend = 0.02) and GHQ-12 (OR = 0.72 [0.55-0.93]; p-trend = 0.01). Self-reported sedentary behaviour was not associated with K6 (p-trend = 0.90) and GHQ-12 (p-trend = 0.33). The highest tertile of accelerometry-assessed sedentary behaviour was associated with significantly higher odds for K6 (OR = 1.93 [1.00-3.75]; p-trend = 0.04), but not GHQ-12 (OR = 1.34 [0.86-2.08]; p-trend = 0.18). Conclusions: Higher levels of leisure-time physical activity and lower levels of accelerometer-based sedentary behaviour were associated with lower psychological distress. This study underscores the importance of assessing accelerometer-based and domain-specific activity in relation to mental health, instead of solely focusing on total volume of activity

Statistical Basis for Predicting Technological Progress

Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly tied. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation