Identification and evaluation of linear damping models in beam vibrations

Sensitive method, identifying effective damping mechanisms, involves comparing experimentally determined ratio of first to second mode magnification factors related to common point on beam. Cluster size has little effect on frequencies of elements, magnification factor decreases with cluster size, and viscous and stress damping are dominant damping mechanisms

Haze in the Klang Valley of Malaysia

Continuous measurements of dry aerosol light scattering (Bsp) were made at two sites in the Klang Valley of Malaysia between December 1998 and December 2000. In addition 24-h PM2.5 samples were collected on a one-day-in-six cycle and the chemical composition of the aerosol was determined. Periods of excessive haze were defined as 24-h average Bsp values greater than 150 Mm-1 and these occurred on a number of occasions, between May and September 1999, during May 2000, and between July and September 2000. The evidence for smoke being a significant contributor to aerosol during periods of excessive haze is discussed and includes features of the aerosol chemistry, the diurnal cycle of Bsp, and the coincidence of forest fires on Sumatra during the southwest (SW) monsoon period, as well as transport modelling for one week of the southwest Monsoon of 2000. The study highlights that whilst transboundary smoke is a major contributor to poor visibility in the Klang Valley, smoke from fires on Peninsular Malaysia is also a contributor, and at all times, the domestic source of secondary particle production is present

Shigellosis and AIDS : Report of a case and brief review of the literature

Contains fulltext : 4491.pdf (publisher's version ) (Open Access

Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning

CT Perfusion (CTP) imaging has gained importance in the diagnosis of acute stroke. Conventional perfusion analysis performs a deconvolution of the measurements and thresholds the perfusion parameters to determine the tissue status. We pursue a data-driven and deconvolution-free approach, where a deep neural network learns to predict the final infarct volume directly from the native CTP images and metadata such as the time parameters and treatment. This would allow clinicians to simulate various treatments and gain insight into predicted tissue status over time. We demonstrate on a multicenter dataset that our approach is able to predict the final infarct and effectively uses the metadata. An ablation study shows that using the native CTP measurements instead of the deconvolved measurements improves the prediction.Comment: Accepted for publication in Medical Image Analysi

Safety of low dose glucocorticoid treatment in rheumatoid arthritis: published evidence and prospective trial data

Adverse effects of glucocorticoids have been abundantly reported. Published reports on low dose glucocorticoid treatment show that few of the commonly held beliefs about their incidence, prevalence, and impact are supported by clear scientific evidence. Safety data from recent randomised controlled clinical trials of low dose glucocorticoid treatment in RA suggest that adverse effects associated with this drug are modest, and often not statistically different from those of placebo