Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.

Decompression scenarios in a new underground transportation system

BACKGROUND: The risks of a public exposure to a sudden decompression, until now, have been related to civil aviation and, at a lesser extent, to diving activities. However, engineers are currently planning the use of low pressure environments for underground transportation. This method has been proposed for the future Swissmetro, a high-speed underground train designed for inter-urban linking in Switzerland. HYPOTHESIS: The use of a low pressure environment in an underground public transportation system must be considered carefully regarding the decompression risks. Indeed, due to the enclosed environment, both decompression kinetics and safety measures may differ from aviation decompression cases. METHOD: A theoretical study of decompression risks has been conducted at an early stage of the Swissmetro project. A three-compartment theoretical model, based on the physics of fluids, has been implemented with flow processing software (Ithink 5.0). Simulations have been conducted in order to analyze "decompression scenarios" for a wide range of parameters, relevant in the context of the Swissmetro main study. RESULTS: Simulation results cover a wide range from slow to explosive decompression, depending on the simulation parameters. Not surprisingly, the leaking orifice area has a tremendous impact on barotraumatic effects, while the tunnel pressure may significantly affect both hypoxic and barotraumatic effects. Calculations have also shown that reducing the free space around the vehicle may mitigate significantly an accidental decompression. CONCLUSION: Numeric simulations are relevant to assess decompression risks in the future Swissmetro system. The decompression model has proven to be useful in assisting both design choices and safety management.

T1-weighted MRI as a substitute to CT for refocusing planning in MR-guided focused ultrasound.

Precise focusing is essential for transcranial MRI-guided focused ultrasound (TcMRgFUS) to minimize collateral damage to non-diseased tissues and to achieve temperatures capable of inducing coagulative necrosis at acceptable power deposition levels. CT is usually used for this refocusing but requires a separate study (CT) ahead of the TcMRgFUS procedure. The goal of this study was to determine whether MRI using an appropriate sequence would be a viable alternative to CT for planning ultrasound refocusing in TcMRgFUS. We tested three MRI pulse sequences (3D T1 weighted 3D volume interpolated breath hold examination (VIBE), proton density weighted 3D sampling perfection with applications optimized contrasts using different flip angle evolution and 3D true fast imaging with steady state precision T2-weighted imaging) on patients who have already had a CT scan performed. We made detailed measurements of the calvarial structure based on the MRI data and compared those so-called 'virtual CT' to detailed measurements of the calvarial structure based on the CT data, used as a reference standard. We then loaded both standard and virtual CT in a TcMRgFUS device and compared the calculated phase correction values, as well as the temperature elevation in a phantom. A series of Bland-Altman measurement agreement analyses showed T1 3D VIBE as the optimal MRI sequence, with respect to minimizing the measurement discrepancy between the MRI derived total skull thickness measurement and the CT derived total skull thickness measurement (mean measurement discrepancy: 0.025; 95% CL (-0.22-0.27); p = 0.825). The T1-weighted sequence was also optimal in estimating skull CT density and skull layer thickness. The mean difference between the phase shifts calculated with the standard CT and the virtual CT reconstructed from the T1 dataset was 0.08 ± 1.2 rad on patients and 0.1 ± 0.9 rad on phantom. Compared to the real CT, the MR-based correction showed a 1 °C drop on the maximum temperature elevation in the phantom (7% relative drop). Without any correction, the maximum temperature was down 6 °C (43% relative drop). We have developed an approach that allows for a reconstruction of a virtual CT dataset from MRI to perform phase correction in TcMRgFUS.

Are virtual planning and guided surgery for head and neck reconstruction economically viable?

PURPOSE: Virtual planning and guided surgery with or without prebent or milled plates are becoming more and more common for mandibular reconstruction with fibular free flaps (FFFs). Although this excellent surgical option is being used more widely, the question of the additional cost of planning and cutting-guide production has to be discussed. In capped payment systems such additional costs have to be offset by other savings if there are no special provisions for extra funding. Our study was designed to determine whether using virtual planning and guided surgery resulted in time saved during surgery and whether this time gain resulted in self-funding of such planning through the time saved. MATERIALS AND METHODS: All consecutive cases of FFF surgery were evaluated during a 2-year period. Institutional data were used to determine the price of 1 minute of operative time. The time for fibula molding, plate adaptation, and insetting was recorded. RESULTS: During the defined period, we performed 20 mandibular reconstructions using FFFs, 9 with virtual planning and guided surgery and 11 freehand cases. One minute of operative time was calculated to cost US $47.50. Multiplying this number by the time saved, we found that the additional cost of virtual planning was reduced from US $5,098 to US $1,231.50 with a prebent plate and from US $6,980 to US $3,113.50 for a milled plate. CONCLUSIONS: Even in capped health care systems, virtual planning and guided surgery including prebent or milled plates are financially viable.

Planning and conducting focus group research with nurses.

Focus groups are increasingly popular in nursing research. However, proper care and attention are critical to their planning and conduct, particularly those involving nursing staff. This article uses data gleaned from prior research to address the complexities present in clinical settings when conducting focus groups with nurses. Applying their combined experiences of conducting studies with nursing staff, the authors present a data-derived approach to thorough preparation and successful implementation of focus group research, offering a unique contribution to the literature regarding this research strategy.

Map of ecological networks for landscape planning

This paper presents a method based on a geographical information system (GIS) to model ecological networks in a fragmented landscape. The ecological networks are generated with the help of a landscape model (which integrate human activities) and with a wildlife dispersal model. The main results are maps which permit the analysis and the understanding of the impact of human activities on wildlife dispersal. Three applications in a study area are presented: ecological networks at the landscape scale, conflicting areas at the farmstead scale and ecological distance between biotopes. These applications show the flexibility of the model and its potential to give information on ecological networks at different planning scales.