Professionalisation of sport federations - a multi-level framework for analysing forms, causes and consequences

Research question: International and national sport federations as well as their member organisations are key actors within the sport system and have a wide range of relationships outside the sport system (e.g. with the state, sponsors, and the media). They are currently facing major challenges such as growing competition in top-level sports, democratisation of sports with 'sports for all' and sports as the answer to social problems. In this context, professionalising sport organisations seems to be an appropriate strategy to face these challenges and current problems. We define the professionalisation of sport organisations as an organisational process of transformation leading towards organisational rationalisation, efficiency and business-like management. This has led to a profound organisational change, particularly within sport federations, characterised by the strengthening of institutional management (managerialism) and the implementation of efficiency-based management instruments and paid staff. Research methods: The goal of this article is to review the current international literature and establish a global understanding of and theoretical framework for analysing why and how sport organisations professionalise and what consequences this may have. Results and findings: Our multi-level approach based on the social theory of action integrates the current concepts for analysing professionalisation in sport federations. We specify the framework for the following research perspectives: (1) forms, (2) causes and (3) consequences, and discuss the reciprocal relations between sport federations and their member organisations in this context. Implications: Finally, we work out a research agenda and derive general methodological consequences for the investigation of professionalisation processes in sport organisations.

The occurrence of intra-operative hypotension varies between hospitals: observational analysis of more than 147,000 anaesthesia.

BACKGROUND: Hypotension, a common intra-operative incident, bears an important potential for morbidity. It is most often manageable and sometimes preventable, which renders its study important. Therefore, we aimed at examining hospital variations in the occurrence of intra-operative hypotension and its predictors. As secondary endpoints, we determined to what extent hypotension relates to the risk of post-operative incidents and death. METHODS: We used the Anaesthesia Databank Switzerland, built on routinely and prospectively collected data on all anaesthesias in 21 hospitals. The three outcomes were assessed using multi-level logistic regression models. RESULTS: Among 147,573 anaesthesias, hypotension ranged from 0.6% to 5.2% in participating hospitals, and from 0.3% up to 12% in different surgical specialties. Most (73.4%) were minor single events. Age, ASA status, combined general and regional anaesthesia techniques, duration of surgery and hospitalization were significantly associated with hypotension. Although significantly associated, the emergency status of the surgery had a weaker effect. Hospitals' odds ratios for hypotension varied between 0.12 and 2.50 (P < or = 0.001), even after adjusting for patient and anaesthesia factors, and for type of surgery. At least one post-operative incident occurred in 9.7% of the procedures, including 0.03% deaths. Intra-operative hypotension was associated with a higher risk of post-operative incidents and death. CONCLUSION: Wide variations remain in the occurrence of hypotension among hospitals after adjustment for risk factors. Although differential reporting from hospitals may exist, variations in anaesthesia techniques and blood pressure maintenance may also have contributed. Intra-operative hypotension is associated with morbidities and sometimes death, and constant vigilance must thus be advocated.

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

The occurrence of intra-operative hypotension varies between hospitals: observational analysis of over 147000 anaesthesia

Background: Hypotension, a common intra-operative incident, bears an important potential for morbidity. It is most often manageable and sometimes preventable, which renders its study important. Therefore, we aimed at examining hospital variations in the occurrence of intraoperative hypotension and its predictors. As secondary endpoints, we determined to what extent hypotension relates to the risk of postoperative incidents and death. Methods: We used the Anaesthesia Databank Switzerland, built on routinely and prospectively collected data on all anaesthesias in 21 hospitals. The three outcomes were assessed using multi-level logistic regression models. Results: Among 147573 anaesthesia, hypotension ranged from 0.6 to 5.2% in participating hospitals, and from 0.3 up to 12% in different surgical specialties. Most (73.4%) were minor single events. Age, ASA status, combined general and regional anaesthesia techniques, duration of surgery, and hospitalization were significantly associated to hypotension. Although significantly associated, the emergency status of the surgery had a weaker effect. Hospitals' Odds Ratios for hypotension varied between 0.12 to 2.50 (p ≤0.001) with respect to the mean prevalence of 3.1%, even after adjusting for patient and anaesthesia factors, and for type of surgery. At least one postoperative incident occurred in 9.7% of the interventions, including 0.03% deaths. Intra-operative hypotension was associated with higher risk of post-operative incidents and death. Conclusions: Wide variations in the occurrence of hypotension amongst hospitals remain after adjustment for risk factors. Although differential reporting from hospitals may exist, variations in anesthesia techniques and blood pressure maintenance could have also contributed. Intra-operative hypotension is associated with morbidities and sometimes death, and constant vigilance must thus be advocated.

The attractiveness of nations in global competition : an empirical assessment of the effects of country attractiveness on the success of strategy for hosting international sports events, 1990-2012

This dissertation aims to investigate empirical evidence on the importance and influence of attractiveness of nations in global competition. The notion of country attractiveness, which has been widely developed in the research areas of international business, tourism and migration, is a multi-dimensional construct to measure a country's characteristics with regard to its market or destination that attract international investors, tourists and migrants. This analytical concept provides an account of the mechanism as to how potential stakeholders evaluate more attractive countries based on certain criteria. Thus, in the field of international sport-event bidding, do international sport event owners also have specific country attractiveness for their sport event hosts? The dissertation attempts to address this research question by statistically assessing the effects of country attractiveness on the success of strategy for hosting international sports events. Based on theories of signaling and soft power, country attractiveness is defined and measured as the three dimensions of sustainable development: economic, social, and environmental attractiveness. This thesis proceeds to examine the concept of sport-event-hosting strategy and explore multi-level factors affecting the success in international sport-event bidding. By exploring past history of the Olympic Movement from theoretical perspectives, the thesis proposes and tests the hypotheses that economic, social and environmental attractiveness of a country may be correlated with its bid wins or the success of sport-event-hosting strategy. Quantitative analytical methods with various robustness checks are employed with using collected data on bidding results of major events in Olympic sports during the period from 1990 to 2012. The analysis results reveal that event owners of international Olympic sports are likely to prefer countries that have higher economic, social, and environmental attractiveness. The empirical assessment of this thesis suggests that high country attractiveness can be an essential element of prerequisites for a city/country to secure in order to bid with an increased chance of success.

How Answers on Political Attitudes are Shaped by Interviewers: Evidence from a Panel Survey

We analyze whether the interviewers' political opinions have an influence on those of the respondents. The research uses data from a panel survey in which interviewers are randomly assigned to respondents. The results show that the respondents express significantly similar opinions to those of the interviewers in all questions considered. Multilevel models show that more educated respondents are affected to a slightly higher extent and that the interviewer's experience is also a factor. There is no difference between different respondent subgroups or when both interviewers and respondents share the same socio-demographic characteristics. While there is no evidence for respondents wanting to please the interviewers, the hypothesis of socially desirable behavior can indeed be confirmed.

Monitoring the effects of adult psychotherapy in routine practice in Switzerland: A feasibility trial

Background: Several studies have been published on the effects of psychotherapy in routine practice. Complementing traditional views summarised as 'dose-effect models', Stiles et al. put forward data consistent with the responsive regulation model underlining the importance of the client's active participant role in defining length of treatment. One may ask what level of change reached by a patient is considered to be the 'good enough level' (GEL) and if it is related to the duration of psychotherapy. Aims: The main objective of the present feasibility trial was to monitor the patient's session-by-session evolution using a self-report questionnaire in order to define the GEL, i.e. the number of sessions necessary for the patient to reach significant change. Method: A total of N=13 patients undergoing psychotherapy in routine practice participated in the study, completing the Outcome Questionnaire - 45.2 (OQ-45), which assesses the symptom level, interpersonal relationships and social role after every psychotherapy session. The data was analysed using multi-level analyses (HLMs). Results: High feasibility of fine-grained assessment of effects of psychotherapy in routine practice in Switzerland was shown; response rates being acceptable; however, detailed analysis of the GEL was not feasible within the short study time-frame. Conclusions: Reflections on the political context of monitoring in the specific case of routine psychiatric practice in Switzerland are discussed.

Housewife or working mum--each to her own? The relevance of societal factors in the association between social roles and alcohol use among mothers in 16 industrialized countries.

Aims To investigate whether differences in gender-income equity at country level explain national differences in the links between alcohol use, and the combination of motherhood and paid labour. Design Cross-sectional data in 16 established market economies participating in the Gender, Alcohol and Culture: An International Study (GenACIS) study. Setting Population surveys. Participants A total of 12 454 mothers (aged 25-49 years). Measurements Alcohol use was assessed as the quantity per drinking day. Paid labour, having a partner, gender-income ratio at country level and the interaction between individual and country characteristics were regressed on alcohol consumed per drinking day using multi-level modelling. Findings Mothers with a partner who were in paid labour reported consuming more alcohol on drinking days than partnered housewives. In countries with high gender-income equity, mothers with a partner who were in paid labour drank less alcohol per occasion, while alcohol use was higher among working partnered mothers living in countries with lower income equity. Conclusion In countries which facilitate working mothers, daily alcohol use decreases as female social roles increase; in contrast, in countries where there are fewer incentives for mothers to remain in work, the protective effect of being a working mother (with partner) on alcohol use is weaker. These data suggest that a country's investment in measures to improve the compatibility of motherhood and paid labour may reduce women's alcohol use.

Incidents occuring during anesthesia for total hip arthroplasty: a comparison of general versus regional anaesthesia

Background: The type of anesthesia to be used for total hip arthroplasty (THA) is still a matter of debate. We compared the occurrence of per- and post-anesthesia incidents in patients receiving either general (GA) or regional anesthesia (RA). Methods: We used data from 29 hospitals, routinely collected in the Anaesthesia Databank Switzerland register between January 2001 and December 2003. We used multi-level logistic regression models. Results: There were more per- and post-anesthesia incidents under GA compared to RA (35.1% vs 32.7 %, n = 3191, and 23.1% vs 19.4%, n = 3258, respectively). In multi-level logistic regression analysis, RA was significantly associated with a lower incidence of per-anesthetic problems, especially hypertension, compared with GA. During the post-anesthetic period, RA was also less associated with pain. Conversely, RA was more associated with post-anesthetic hypotension, especially for epidural technique. In addition, age and ASA were more associated with incidents under GA compared to RA. Men were more associated with per-anesthetic problems under RA compared to GA. Whereas increased age (>67), gender (male), and ASA were linked with the choice of RA, we noticed that this choice depended also on hospital practices after we adjusted for the other variables. Conclusions: Compared to RA, GA was associated with an increased proportion of per- and post-anesthesia incidents. Although this study is only observational, it is rooted in daily practice. Whereas RA might be routinely proposed, GA might be indicated because of contraindications to RA, patients' preferences or other surgical or anaesthesiology related reasons. Finally, the choice of a type of anesthesia seems to depend on local practices that may differ between hospitals.

Incidents occurring during anesthesia for total hip arthroplasty: a comparison of general versus regional anaesthesia

Background: The type of anesthesia to be used for total hip arthroplasty (THA) is still a matter of debate. We compared the occurrence of per- and post-anesthesia incidents in patients receiving either general (GA) or regional anesthesia (RA). Methods: We used data from 29 hospitals, routinely collected in the Anaesthesia Databank Switzerland register between January 2001 and December 2003. We used multi-level logistic regression models. Results: There were more per- and post-anesthesia incidents under GA compared to RA (35.1% vs 32.7 %, n = 3191, and 23.1% vs 19.4%, n = 3258, respectively). In multi-level logistic regression analysis, RA was significantly associated with a lower incidence of per-anesthetic problems, especially hypertension, compared with GA. During the post-anesthetic period, RA was also less associated with pain. Conversely, RA was more associated with post-anesthetic hypotension, especially for epidural technique. In addition, age and ASA were more associated with incidents under GA compared to RA. Men were more associated with per-anesthetic problems under RA compared to GA. Whereas increased age (>67), gender (male), and ASA were linked with the choice of RA, we noticed that this choice depended also on hospital practices after we adjusted for the other variables. Conclusions: Compared to RA, GA was associated with an increased proportion of per- and post-anesthesia incidents. Although this study is only observational, it is rooted in daily practice. Whereas RA might be routinely proposed, GA might be indicated because of contraindications to RA, patients' preferences or other surgical or anaesthesiology related reasons. Finally, the choice of a type of anesthesia seems to depend on local practices that may differ between hospitals.

Outcome evaluation of ankle osteoarthritis treatments using spatio-temporal gait parameters and plantar pressure during unconstrained long distance walking : P25

Introduction: Ankle arthrodesis (AD) and total ankle replacement (TAR) are typical treatments for ankle osteoarthritis (AO). Despite clinical interest, there is a lack of their outcome evaluation using objective criteria. Gait analysis and plantar pressure assessment are appropriate to detect pathologies in orthopaedics but they are mostly used in lab with few gait cycles. In this study, we propose an ambulatory device based on inertial and plantar pressure sensors to compare the gait during long-distance trials between healthy subjects (H) and patients with AO or treated by AD and TAR. Methods: Our study included four groups: 11 patients with AO, 9 treated by TAR, 7 treated by AD and 6 control subjects. An ambulatory system (Physilog®, CH) was used for gait analysis; plantar pressure measurements were done using a portable insole (Pedar®-X, DE). The subjects were asked to walk 50 meters in two trials. Mean value and coefficient of variation of spatio-temporal gait parameters were calculated for each trial. Pressure distribution was analyzed in ten subregions of foot. All parameters were compared among the four groups using multi-level model-based statistical analysis. Results: Significant difference (p <0.05) with control was noticed for AO patients in maximum force in medial hindfoot and forefoot and in central forefoot. These differences were no longer significant in TAR and AD groups. Cadence and speed of all pathologic groups showed significant difference with control. Both treatments showed a significant improvement in double support and stance. TAR decreased variability in speed, stride length and knee ROM. Conclusions: In spite of a small sample size, this study showed that ankle function after AO treatments can be evaluated objectively based on plantar pressure and spatio-temporal gait parameters measured during unconstrained walking outside the lab. The combination of these two ambulatory techniques provides a promising way to evaluate foot function in clinics.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Trasporti e sviluppo territoriale negli spazi intermedi : l'esempio della regione transfrontaliera Insubrica

Avec cette thèse de doctorat nous proposons une réflexion transversale concernant les relations entre infrastructures de transport et développement territorial dans des espaces dits « intermédiaires ». Le concept d'espace intermédiaire, relativement nouveau en géographie, est conçu en fonction d'une double approche : celle des infrastructures où les espaces intermédiaires constituent des zones de transit obligées entre des pôles urbains hiérarchiquement supérieurs (par rapport une échelle horizontale) et celle des frontières où les espaces intermédiaires constituent des territoires de coopération entre différents niveaux politico-institutionnels (par rapport à une échelle verticale). Cette problématique de recherche est traitée aussi bien du point de vue théorique qu'avec des études de cas portant sur les effets des nouvelles infrastructures de transports dans la région transfrontalière insubrique (entre le Canton du Tessin et la Lombardie). L'objectif visé est de défendre un scénario d'organisation spatiale polycentrique à plusieurs niveaux comme solution pour le développement durable et cohérent de ces espaces intermédiaires. Ainsi, pour le « niveau macro », nous proposons une analyse des changements d'accessibilité spatiale et des potentiels de développement territorial pour les agglomérations concernées par la mise en service du nouveau tunnel ferroviaire de base du Monte Ceneri (TBC) et de la nouvelle ligne Lugano/Como-Mendrisio-Varese-Malpensa (FMV) à l'horizon 2020. Pour le « niveau meso », nous analysons les effets de la nouvelle ligne FMV en termes de potentiel de densification polycentrique autours des gares ferroviaires. Pour le « niveau micro », nous proposons une analyse sur les comportements de mobilité ainsi que des améliorations ciblées du système de transport pour la ville de Mendrisio visant à promouvoir le développement polycentrique de cette commune. De plus, un système d'analyse permettant de mettre en lien les divers facteurs explicatifs dans l'analyse des relations entre les nouvelles infrastructures de transport et les effets sur la mobilité et le développement territorial est également élaboré et testé dans notre recherche. -- With this Ph.D. thesis we investigate the relationship between transport infrastructures and territory development inside the so called "in-between spaces". The idea of "in-between space", relatively novel in geography, is the formal outcome of a double approach: the one of the infrastructures, saying that these spaces can be described as areas of constrained transit between urban centres of superior hierarchical level (on a horizontal scale), and the one of the borders, stating that in-between spaces are areas of cooperation between various political-institutional levels. The above mentioned research issues are deepened both at theoretical and empirical level, being the latter based on field studies of the cross-boundary Western-Lombard area (between the Swiss canton of Ticino and the Italian region of Lombardy). This research pursues the goal of defending the argument that a multi-level polycentric spatial scenario can be a possible solution fora sustainable development of the above described in- between areas. From a "macro" perspective, what we submit here is an analysis on the expected changes in spatial accessibility and on the potential territorial development for the built-up areas influenced by the construction of the new train tunnel of the Monte Ceneri (TBC) and of the new railway line Lugano/Como-Mendrisio-Varese-Malpensa (FMV). At a "meso" level we analyse the effects exerted by the new FMV line taking into account the potential densification of the areas surrounding the railway stations. Finally, at a "micro" level, we analyse the mobility behaviours in the town of Mendrisio and we propose some possible improvements to the local public transport system, with the scope to promote a polycentric development of this municipality. Moreover, we developed and tested an analytic system able to define the existing links between the various explaining factors characterizing the relationship between new transport infrastructures and effects on mobility. -- With this Ph.D. thesis we investigate the relationship between transport infrastructures and territory development inside the so called "in-between spaces". The idea of "in-between space", relatively novel in geography, is the formal outcome of a double approach: the one of the infrastructures, saying that these spaces can be described as areas of constrained transit between urban centres of superior hierarchical level (on a horizontal scale), and the one of the borders, stating that in-between spaces are areas of cooperation between various political-institutional levels. The above mentioned research issues are deepened both at theoretical and empirical level, being the latter based on field studies of the cross-boundary Western-Lombard area (between the Swiss canton of Ticino and the Italian region of Lombardy). This research pursues the goal of defending the argument that a multi-level polycentric spatial scenario can be a possible solution for a sustainable development of the above described in- between areas. From a "macro" perspective, what we submit here is an analysis on the expected changes in spatial accessibility and on the potential territorial development for the built-up areas influenced by the construction of the new train tunnel of the Monte Ceneri (TBC) and of the new railway line Lugano/Como-Mendrisio-Varese-Malpensa (FMV). At a "meso" level we analyse the effects exerted by the new FMV line taking into account the potential densification of the areas surrounding the railway stations. Finally, at a "micro" level, we analyse the mobility behaviours in the town of Mendrisio and we propose some possible improvements to the local public transport system, with the scope to promote a polycentric development of this municipality. Moreover, we developed and tested an analytic system able to define the existing links between the various explaining factors characterizing the relationship between new transport infrastructures and effects on mobility.

Large multi-gene phylogenetic trees of the grasses (Poaceae): progress towards complete tribal and generic level sampling.

In this paper we included a very broad representation of grass family diversity (84% of tribes and 42% of genera). Phylogenetic inference was based on three plastid DNA regions rbcL, matK and trnL-F, using maximum parsimony and Bayesian methods. Our results resolved most of the subfamily relationships within the major clades (BEP and PACCMAD), which had previously been unclear, such as, among others the: (i) BEP and PACCMAD sister relationship, (ii) composition of clades and the sister-relationship of Ehrhartoideae and Bambusoideae + Pooideae, (iii) paraphyly of tribe Bambuseae, (iv) position of Gynerium as sister to Panicoideae, (v) phylogenetic position of Micrairoideae. With the presence of a relatively large amount of missing data, we were able to increase taxon sampling substantially in our analyses from 107 to 295 taxa. However, bootstrap support and to a lesser extent Bayesian inference posterior probabilities were generally lower in analyses involving missing data than those not including them. We produced a fully resolved phylogenetic summary tree for the grass family at subfamily level and indicated the most likely relationships of all included tribes in our analysis.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.