Access to this document was granted through an Emerald subscription provided by emerald-srm:451335 [] For AuthorsIf you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. AbstractPurpose -The purpose of this paper is to evaluate the contribution of location (geographical concentration) and firm structure (age and subsector) to the risk of business failure. Design/methodology/approach -The Markov's regression analysis was made for a sample of over 11,700 Spanish textile-clothing firms. Findings -The results obtained from the analysis suggest that the risk of business failure is increased by some risk factors relative to the structural characteristics of the firms (younger firms and specialization in low-tech activities), and under determined locational circumstances. Research limitations/implications -Our conclusions have been obtained starting from a sample of manufacturing firms in the Spanish textile sector. An extension of this work would be to test its robustness in other countries (for example, Italy or Portugal) and/or for other industries such as footwear and furniture. Practical implications -Explaining the different levels of risk business failure shown by firms in an industry. Originality/value -Work that has studied the failure of the textile firms within this locationsubsector relationship is still scarce. Given that the viability of clusters and of European textile have been put into question, our work evidences that the risk of failure related to the firm's location and structure needs to be tested jointly, so that the way in which the firm addresses environmental changes can be appraised.

No abstract

each pipe we approximated the time until the failure of each pipe by means of an interval and we apply a model developed by Farrington for intervalcensored data. This method is based on a nonlinear model for binary data and uses standard statistical packages with interpretation analogous to Cox's. In order to check the consistency of Farrington's model we do an exhaustive validation of this method and we compare it with some well established models: Cox's model and the Generalized Linear model. Results: This study shows that network characteristics aect the risk of pipe failure: an increase in the length and pressure, a small diameter, the material used and to make the pipes and a heavy trac conditions of the street. So we propose a clear framework for decision support in the diagnosis and rehabilitation of water supply systems in that company. In order to compare the models, we have used the ROC curves and the Concordance Index to decide which models provide better discrimination in order to predict service breakdown: the Farrington model had the best discrimination and the Cox model the worst.

No abstract

By means of flowmotion analysis, it is mainly accepted that, in normal conditions, insulin specifically increases the activity of microvascular smooth muscle. The objective of this study was to compare this effect in severely obese and normalweight adolescents. Laser Doppler measurements were used to assess cutaneous blood flux (CBF) and flowmotion in response to transdermal iontophoresis of insulin in 20 severely obese adolescents (SOA) aged 12-17 years (BMI = 33.34 ± 1.07 kg/m 2 ), and 16 normal-weight adolescents (BMI = 18.85 ± 0.50 kg/m 2 ). Fasting insulin levels were higher in SOA than in normal-weight adolescents (6.25 ± 1.03 vs. 3.11 ± 0.28 U/ml, P = 0.007). Net insulin-induced increase of CBF did not significantly differ between SOA and normal-weight adolescents (422.41 ± 146.09 vs. 232.36 ± 80.98 %, P = 0.265). A significant impairment of myogenic flowmotion was detected in SOA compared to normal-weight adolescents in response to insulin delivery (5.91 ± 0.35 vs. 8.12 ± 0.63 %, P = 0.003). Severely obese adolescents exhibit decreased myogenic activity in response to insulin, which may be an early step in the development of insulin resistance.