Physical therapy assessment tools to evaluate disease progression and phenotype variability in Golden Retriever muscular dystrophy

Dogs suffering from Golden Retriever muscular dystrophy (GRMD) present symptoms that are similar to human patients with Duchenne muscular dystrophy (DMD). Phenotypic variability is common in both cases and correlates with disease progression and response to therapy. Physical therapy assessment tools were used to study disease progression and assess phenotypic variability in dogs with GRMD. At 5 (TO), 9 (T1), 13 (T2) and 17 (T3) months of age, the physical features, joint ranges of motion (ROM), limb and thorax circumferences, weight and creatine kinase (CK) levels were assessed in 11 dogs with GRMD. Alterations of physical features were higher at 13 months, and different disease progression rates were observed. Passive ROM decreased until 1 year old, which was followed by a decline of elbow and tarsal ROM. Limb and thorax circumferences, which were corrected for body weight, decreased significantly between TO and T3. These measurements can be used to evaluate disease progression in dogs with GRMD and to help discover new therapies for DMD patients. (C) 2011 Elsevier Ltd. All rights reserved.

Outcomes and indicators, measurement tools, and databases for the National Action Plan for Promotion, Prevention and Early Intervention for Mental Health 2000

This publication is a support and resource document for the "National Action Plan for Promotion, Prevention and Early Intervention for Mental Health 2000". It includes indicators, measurement tools and databases relevant to assessing the implementation of the outcomes and strategies identified in the action plan.

Thermal/mechanical simulation and laboratory fatigue testing of an alternative yttria tetragonal zirconia polycrystal core-veneer all-ceramic layered crown design

This study evaluated the stress levels at the core layer and the veneer layer of zirconia crowns (comprising an alternative core design vs. a standard core design) under mechanical/thermal simulation, and subjected simulated models to laboratory mouth-motion fatigue. The dimensions of a mandibular first molar were imported into computer-aided design (CAD) software and a tooth preparation was modeled. A crown was designed using the space between the original tooth and the prepared tooth. The alternative core presented an additional lingual shoulder that lowered the veneer bulk of the cusps. Finite element analyses evaluated the residual maximum principal stresses fields at the core and veneer of both designs under loading and when cooled from 900 degrees C to 25 degrees C. Crowns were fabricated and mouth-motion fatigued, generating master Weibull curves and reliability data. Thermal modeling showed low residual stress fields throughout the bulk of the cusps for both groups. Mechanical simulation depicted a shift in stress levels to the core of the alternative design compared with the standard design. Significantly higher reliability was found for the alternative core. Regardless of the alternative configuration, thermal and mechanical computer simulations showed stress in the alternative core design comparable and higher to that of the standard configuration, respectively. Such a mechanical scenario probably led to the higher reliability of the alternative design under fatigue.

Step size control for efficient discrete element simulation

The step size determines the accuracy of a discrete element simulation. The position and velocity updating calculation uses a pre-calculated table and hence the control of step size can not use the integration formulas for step size control. A step size control scheme for use with the table driven velocity and position calculation uses the difference between the calculation result from one big step and that from two small steps. This variable time step size method chooses the suitable time step size for each particle at each step automatically according to the conditions. Simulation using fixed time step method is compared with that of using variable time step method. The difference in computation time for the same accuracy using a variable step size (compared to the fixed step) depends on the particular problem. For a simple test case the times are roughly similar. However, the variable step size gives the required accuracy on the first run. A fixed step size may require several runs to check the simulation accuracy or a conservative step size that results in longer run times. (C) 2001 Elsevier Science Ltd. All rights reserved.

A systematic approach to error isolation in computerized wastewater simulation models

Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them, Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally. localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM 1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.