Parallel plate model for trabecular bone exhibits volume fraction-dependent bias

Unbiased stereological methods were used in conjunction with microcomputed tomographic (micro-CT) scans of human and animal bone to investigate errors created when the parallel plate model was used to calculate morphometric parameters. Bone samples were obtained from the human proximal tibia, canine distal femur, rat tail, and pig spine and scanned in a micro-CT scanner. Trabecular thickness, trabecular spacing, and trabecular number were calculated using the parallel plate model. Direct thickness, and spacing and connectivity density were calculated using unbiased three-dimensional methods. Both thickness and spacing calculated using the plate model were well correlated to the direct three-dimensional measures (r(2) = 0. 77-0.92). The correlation between trabecular number and connectivity density varied greatly (r(2) = 0.41-0.94). Whereas trabecular thickness was consistently underestimated using the plate model, trabecular spacing was underestimated at low volume fractions and overestimated at high volume fractions. Use of the plate model resulted in a volume-dependent bias in measures of thickness and spacing (p < 0.001). This was a result of the fact that samples of low volume fraction were much more "rod-like" than those of the higher volume fraction. Our findings indicate that the plate model provides biased results, especially when populations with different volume fractions are compared. Therefore, we recommend direct thickness measures when three-dimensional data sets are available

Benthic foraminiferal assemblages and test accumulation in coastal microhabitats on San Salvador, Bahamas

Benthic foraminiferal populations were studied in a shallow bay of San Salvador Island, the Bahamas. Surface sediments and marine macrophytes were collected from 14 sample sites along a 500&thinsp;m transect at Grahams Harbour to investigate the foraminiferal assemblage in each microhabitat and to test the link between dead foraminiferal test accumulation patterns and living epiphytic and sedimentary foraminiferal assemblages, macrophyte distribution, and environmental gradients. The analyses include grain size measurements, macrophyte biomass quantification, and qualitative and quantitative studies of benthic foraminifera. The foraminifera found attached to macrophytes differed between macrophyte habitats. However, a correlation between these living communities and the dead assemblages in the sediments at the same sites could not be observed. Principal component analysis (PCA) and redundancy analysis (RDA) suggest that the presence of the macroalgae Halimeda explains 16&thinsp;% of the residual faunal variation in the dead foraminiferal assemblage after the effects of sorting according to fall speed are partialled out. The RDA also reflects a positive correlation between foraminifera larger than 1.0&thinsp;mm in diameter and the 0.25–0.5&thinsp;mm sediment grain size, indicating sedimentological processes as the main factor controlling the sedimentary epiphytic foraminiferal assemblages. These sedimentary processes overprint most effects of ecological features or macrophyte-specific association.</p

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method

Introducing willingness-to-pay for noise changes into transport appraisal: an application of benefit transfer.

Numerous research studies have elicited willingness-to-pay values for transport-related noise, however, in many industrialised countries including the UK, noise costs and benefits are still not incorporated into appraisals for most transport projects and policy changes (Odgaard et al, 2005; Grant-Muller et al, 2001). This paper describes the actions recently taken in the UK to address this issue, comprising: primary research based on the city of Birmingham; an international review of willingness-to-pay evidence; development of values using benefit transfers over time and locations; and integration with appraisal methods. Amongst the main findings are: that the willingness-to-pay estimates derived for the UK are broadly comparable with those used in appraisal elsewhere in Europe; that there is a case for a lower threshold at 1 45dB(A)Leq,18hr1 rather than the more conventional 55dB(A); and that values per dB(A) increase with the noise level above this threshold. There are significant issues over the valuation of rail versus road noise, the neglect of non-residential noise and the valuation of high noise levels in different countries. Conclusions are drawn regarding the feasibility of noise valuation based on benefit transfers in the UK and elsewhere, and future research needs in this field are discussed

Measurement properties of UCLA Activity Scale for hip and knee arthroplasty patients and translation and cultural adaptation into Danish

Background and purpose — The UCLA Activity Scale (UCLA) is a questionnaire assessing physical activity level from 1 (low) to 10 (high) in patients undergoing hip or knee arthroplasty (HA/KA). After translation and cultural adaptation, we evaluated the measurement properties of the Danish UCLA. Patients and methods — After dual panel translation, cognitive interviews were performed among 55 HA/KA patients. An orthopedic surgeon and a physiotherapist estimated UCLA scores for 80 KA patients based on short interviews. Measurement properties were evaluated in 130 HA and 134 KA patients preoperatively and 1-year postoperatively. Results — To suit Danish patients of today, several adaptations were required. Prior to interviews, 4 patients were excluded, and 11 misinterpreted the answer options. Examiners rated the remaining 65 patients (mean age 67 years) 0.2–1.6 UCLA levels lower than patients themselves. The 130 HA and 134 KA patients (mean age 71/68 years) changed from 4.3 (SD 1.9)/4.5 (1.8) preoperatively to 6.6 (1.8)/6.2 (1.0) at 1-year follow-up. 103 (79%) HA and 89 (66%) KA patients reported increased activity. Effect sizes were large (1.2/0.96). Knee patients reaching minimal important change (MIC, ≥ 8 Oxford Knee Score points) had higher 1-year UCLA scores than patients not reaching MIC. Interpretation — Original scale development was undocumented. Content validity was questionable, and there was discrepancy between patient and examiner estimates. UCLA appears valuable for measuring change in self-reported physical activity on a group level. 4 out of 5 HA patients and 2 out of 3 KA patients were more physically active 1 year after joint replacement surgery

Impact testing to determine the mechanical properties of articular cartilage in isolation and on bone

The original publication is available at www.springerlink.comNon peer reviewedPostprin

Control and Supervision of Wind Energy Conversion Systems

This paper is about a PhD thesis and includes the study and analysis of the performance of an onshore wind energy conversion system. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as integer-order controllers, fractional-order controllers, fuzzy logic controllers, adaptive controllers and predictive controllers and the study of a supervisor based on finite state machines is also studied. The controllers are included in the lower level of a hierarchical structure composed by two levels whose objective is to control the electric output power around the rated power. The supervisor included at the higher level is based on finite state machines whose objective is to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the wind energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. The wind energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two mass drive train, a gearbox, a doubly fed induction generator rotor and by a two level converter