Discrete modeling of sculptured surface machining for robust automatic feedrate selection

Traditional feedrate selection techniques currently used in three and five-axis CNC machining reduces milling efficiency. Manually estimated feedrates tend to be conservative and constant, greatly increasing mill time. The goal of this research is to develop robust techniques and software tools for automatically generating optimized feedrates for use on three and five-axis CNC mills, to both simplify the feed selection process and to increase the safety and efficiency of the milling operation through milling process simulation. The simulation software estimates milling force vectors for each tool move, and identifies a feedrate that maintains a desired peak force. The desired cutting force value may be selected to prevent cutter breakage, maintain part tolerance, or meet some other criteria. Other conditions are also considered, such as maximum allowable chip thickness and machine constraints. This allows for the generation of variable feedrates that are optimized for each tool move. The software consists of three distinct portions: a discrete mechanistic model, a discrete geometric model, and a CNC machine model. The mechanistic model estimates cutting forces as a function of cut geometry, cutter/stock relative velocity, and material constants. The geometric model keeps track of the changing in-process stock geometry and provides the cut geometry parameters required by the mechanistic model. The CNC machine model calculates the cutter/stock relative velocity based on feed inputs, machine kinematics, and controller behavior. A feed value is calculated in an iterative manner for each tool move based on the force estimates. The results of this research have produced accurate force estimates during sculptured surface machining, and have also demonstrated that this approach at automatic feedrate selection is feasible. Testing of feedrate selection has included the five-axis milling of production turbomachinery in an industrial environment. An average improvement in efficiency of 20% has resulted from the use of the optimized feeds

Abnormal task driven neural oscillations in multiple sclerosis: a visuomotor MEG study

Multiple sclerosis (MS) is a debilitating disease commonly attributed to degradation of white matter myelin. Symptoms include fatigue, as well as problems associated with vision and movement. Although areas of demyelination in white matter are observed routinely in patients undergoing MRI scans, such measures are often a poor predictor of disease severity. For this reason, it is instructive to measure associated changes in brain function. Widespread white-matter demyelination may lead to delays of propagation of neuronal activity, and with its excellent temporal resolution, magnetoencephalography can be used to probe such delays in controlled conditions (e.g., during a task). In healthy subjects, responses to visuomotor tasks are well documented: in motor cortex, movement elicits a localised decrease in the power of beta band oscillations (event-related beta desynchronisation) followed by an increase above baseline on movement cessation (post-movement beta rebound (PMBR)). In visual cortex, visual stimulation generates increased gamma oscillations. In this study, we use a visuomotor paradigm to measure these responses in MS patients and compare them to age- and gender-matched healthy controls. We show a significant increase in the time-to-peak of the PMBR in patients which correlates significantly with the symbol digit modalities test: a measure of information processing speed. A significant decrease in the amplitude of visual gamma oscillations in patients is also seen. These findings highlight the potential value of electrophysiological imaging in generating a new understanding of visual disturbances and abnormal motor control in MS patients

How People with Multiple Sclerosis Rate Their Quality of Life: An EQ-5D Survey via the UK MS Register

The EQ-5D is a widely-used, standardised, quality of life measure producing health profiles, indices and states. The aims of this study were to assess the role of various factors in how people with Multiple Sclerosis rate their quality of life, based on responses to the EQ-5D received via the web portal of the UK MS Register.The 4516 responses to the EQ-5D (between May 2011 and April 2012) were collated with basic demographic and descriptive MS data and the resulting dataset was analysed in SPSS (v.20).The mean health state for people with MS was 59.73 (SD 22.4, median 61), compared to the UK population mean of 82.48 (which is approximately 1SD above the cohort mean). The characteristics of respondents with high health states (at or above +1SD) were: better health profiles (most predictive dimension: Usual Activities), higher health indices, younger age, shorter durations of MS, female gender, relapsing-remitting MS, higher educational attainment and being in paid employment (all p-values<0.001). Conversely, the characteristics of respondents with low health states (at or below -1SD) were: poorer health profiles (most predictive dimension: Mobility), lower health indices, older age, longer durations of MS, male gender, progressive MS, lower educational attainment and having an employment status of sick/disabled (p = 0.0014 for age, all other p-values<0.001). Particular living arrangements were not associated with either the high or low health status groups.This large-scale study has enabled in-depth analyses on how people with MS rate their quality of life, and it provides new knowledge on the various factors that contribute to their self-assessed health status. These findings demonstrate the impact of MS on quality of life, and they can be used to inform care provision and further research, to work towards enhancing the quality of life of people with MS

The cost-effectiveness of human papillomavirus screening for cervical cancer

Screening strategies, Human papillomavirus testing, Cost-effectiveness ratio, Cost per quality-adjusted life-year, Life years saved,