Total-body digital X-ray in trauma. An experience report on the first operational full body scanner in Europe and its possible role in ATLS

When patients enter our emergency room with suspected multiple injuries, Statscan provides a full body anterior and lateral image for initial diagnosis, and then zooms in on specific smaller areas for a more detailed evaluation. In order to examine the possible role of Statscan in the management of multiply injured patients we implemented a modified ATLS((R)) algorithm, where X-ray of C-spine, chest and pelvis have been replaced by single-total a.p./lat. body radiograph. Between 15 October 2006 and 1 February 2007 143 trauma patients (mean ISS 15+/-14 (3-75)) were included. We compared the time in resuscitation room to 650 patients (mean ISS 14+/-14 (3-75)) which were treated between 1 January 2002 and 1 January 2004 according to conventional ATLS protocol. The total-body scanning time was 3.5 min (3-6 min) compared to 25.7 (8-48 min) for conventional X-rays, The total ER time was unchanged 28.7 min (13-58 min) compared to 29.1 min (15-65 min) using conventional plain radiography. In 116/143 patients additional CT scans were necessary. In 98/116 full body trauma CT scans were performed. In 18/116 patients selective CT scans were ordered based on Statscan findings. In 43/143 additional conventional X-rays had to be performed, mainly due to inadequate a.p. views of fractured bones. All radiographs were transmitted over the hospital network (Picture Archiving and Communication System, PACS) for immediate simultaneous viewing at different places. The rapid availability of images for interpretation because of their digital nature and the reduced need for repeat exposures because of faulty radiography are also felt to be strengths.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.

Comparing satellite and ground-based observations of paroxysmal degassing events at Etna volcano, Italy

Mount Etna, Italy, is one of the most active volcanoes in the world, and is also regarded as one of the strongest volcanic sources of sulfur dioxide (SO2) emissions to the atmosphere. Since October 2004, an automated ultraviolet (UV) spectrometer network (FLAME) has provided ground-based SO2 measurements with high temporal resolution, providing an opportunity to validate satellite SO2 measurements at Etna. The Ozone Monitoring Instrument (OMI) on the NASA Aura satellite, which makes global daily measurements of trace gases in the atmosphere, was used to compare SO2 amount released by the volcano during paroxysmal lava-fountaining events from 2004 to present. We present the first comparison between SO2 emission rates and SO2 burdens obtained by the OMI transect technique and OMI Normalized Cloud-Mass (NCM) technique and the ground-based FLAME Mini-DOAS measurements. In spite of a good data set from the FLAME network, finding coincident OMI and FLAME measurements proved challenging and only one paroxysmal event provided a good validation for OMI. Another goal of this work was to assess the efficacy of the FLAME network in capturing paroxysmal SO2 emissions from Etna, given that the FLAME network is only operational during daylight hours and some paroxysms occur at night. OMI measurements are advantageous since SO2 emissions from nighttime paroxysms can often be quantified on the following day, providing improved constraints on Etna’s SO2 budget.