Shell-model description of monopole shift in neutron-rich Cu

Variations in the nuclear mean-field, in neutron-rich nuclei, are investigated within the framework of the nuclear shell model. The change is identified to originate mainly from the monopole part of the effective two-body proton-neutron interaction. Applications for the low-lying states in odd-$A$ Cu nuclei are presented. We compare the results using both schematic and realistic forces. We also compare the monopole shifts with the results obtained from large-scale shell-model calculations, using the same realistic interaction, in order to study two-body correlations beyond the proton mean-field variations.Comment: Phys. Rev. C (in press

Comparison of distance measures in spatial analytical modeling for health service planning

<p>Abstract</p> <p>Background</p> <p>Several methodological approaches have been used to estimate distance in health service research. In this study, focusing on cardiac catheterization services, Euclidean, Manhattan, and the less widely known Minkowski distance metrics are used to estimate distances from patient residence to hospital. Distance metrics typically produce less accurate estimates than actual measurements, but each metric provides a single model of travel over a given network. Therefore, distance metrics, unlike actual measurements, can be directly used in spatial analytical modeling. Euclidean distance is most often used, but unlikely the most appropriate metric. Minkowski distance is a more promising method. Distances estimated with each metric are contrasted with road distance and travel time measurements, and an optimized Minkowski distance is implemented in spatial analytical modeling.</p> <p>Methods</p> <p>Road distance and travel time are calculated from the postal code of residence of each patient undergoing cardiac catheterization to the pertinent hospital. The Minkowski metric is optimized, to approximate travel time and road distance, respectively. Distance estimates and distance measurements are then compared using descriptive statistics and visual mapping methods. The optimized Minkowski metric is implemented, via the spatial weight matrix, in a spatial regression model identifying socio-economic factors significantly associated with cardiac catheterization.</p> <p>Results</p> <p>The Minkowski coefficient that best approximates road distance is 1.54; 1.31 best approximates travel time. The latter is also a good predictor of road distance, thus providing the best single model of travel from patient's residence to hospital. The Euclidean metric and the optimal Minkowski metric are alternatively implemented in the regression model, and the results compared. The Minkowski method produces more reliable results than the traditional Euclidean metric.</p> <p>Conclusion</p> <p>Road distance and travel time measurements are the most accurate estimates, but cannot be directly implemented in spatial analytical modeling. Euclidean distance tends to underestimate road distance and travel time; Manhattan distance tends to overestimate both. The optimized Minkowski distance partially overcomes their shortcomings; it provides a single model of travel over the network. The method is flexible, suitable for analytical modeling, and more accurate than the traditional metrics; its use ultimately increases the reliability of spatial analytical models.</p

Performance issues in optical burst/packet switching

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-01524-3_8This chapter summarises the activities on optical packet switching (OPS) and optical burst switching (OBS) carried out by the COST 291 partners in the last 4 years. It consists of an introduction, five sections with contributions on five different specific topics, and a final section dedicated to the conclusions. Each section contains an introductive state-of-the-art description of the specific topic and at least one contribution on that topic. The conclusions give some points on the current situation of the OPS/OBS paradigms

Expiratory flow rate, breath hold and anatomic dead space influence electronic nose ability to detect lung cancer

BACKGROUND: Electronic noses are composites of nanosensor arrays. Numerous studies showed their potential to detect lung cancer from breath samples by analysing exhaled volatile compound pattern ("breathprint"). Expiratory flow rate, breath hold and inclusion of anatomic dead space may influence the exhaled levels of some volatile compounds; however it has not been fully addressed how these factors affect electronic nose data. Therefore, the aim of the study was to investigate these effects. METHODS: 37 healthy subjects (44 +/- 14 years) and 27 patients with lung cancer (60 +/- 10 years) participated in the study. After deep inhalation through a volatile organic compound filter, subjects exhaled at two different flow rates (50 ml/sec and 75 ml/sec) into Teflon-coated bags. The effect of breath hold was analysed after 10 seconds of deep inhalation. We also studied the effect of anatomic dead space by excluding this fraction and comparing alveolar air to mixed (alveolar + anatomic dead space) air samples. Exhaled air samples were processed with Cyranose 320 electronic nose. RESULTS: Expiratory flow rate, breath hold and the inclusion of anatomic dead space significantly altered "breathprints" in healthy individuals (p 0.05). These factors also influenced the discrimination ability of the electronic nose to detect lung cancer significantly. CONCLUSIONS: We have shown that expiratory flow, breath hold and dead space influence exhaled volatile compound pattern assessed with electronic nose. These findings suggest critical methodological recommendations to standardise sample collections for electronic nose measurements