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Computational statistics & data analysis
| Computational statistics & data analysis |
| Pubbl/distr/stampa | [Amsterdam?], : North-Holland |
| Soggetto topico |
Statistics
Mathematical statistics Data Interpretation, Statistical Statistics as Topic Statistiques - Périodiques Statistique mathématique - Périodiques Méthodes statistiques Publications périodiques Econométrie Statistiek Dataprocessing Data-analyse |
| Soggetto genere / forma | Periodicals. |
| ISSN | 1872-7352 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Computational statistics and data analysis |
| Record Nr. | UNINA-9910146583803321 |
| [Amsterdam?], : North-Holland | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data-driven healthcare [[electronic resource] ] : how analytics and BI are transforming the industry
| Data-driven healthcare [[electronic resource] ] : how analytics and BI are transforming the industry |
| Autore | Madsen Laura B. <1973-> |
| Pubbl/distr/stampa | Hoboken, : Wiley, 2014 |
| Descrizione fisica | 1 online resource (219 p.) |
| Disciplina | 362.1068/4 |
| Collana | Wiley and SAS Business Series |
| Soggetto topico |
Health services administration - Data processing
Medical informatics Big data Health Care Sector Confidentiality Data Interpretation, Statistical Forms and Records Control Medical Records Health insurance - Finance - United States Business intelligence - United States |
| ISBN |
1-119-20501-8
1-118-97388-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910132160203321 |
Madsen Laura B. <1973->
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| Hoboken, : Wiley, 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data-driven healthcare : how analytics and BI are transforming the industry
| Data-driven healthcare : how analytics and BI are transforming the industry |
| Autore | Madsen Laura B. <1973-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, : Wiley, 2014 |
| Descrizione fisica | 1 online resource (219 p.) |
| Disciplina | 362.1068/4 |
| Collana | Wiley and SAS Business Series |
| Soggetto topico |
Health services administration - Data processing
Medical informatics Big data Health Care Sector Confidentiality Data Interpretation, Statistical Forms and Records Control Medical Records Health insurance - United States - Finance Business intelligence - United States |
| ISBN |
1-119-20501-8
1-118-97388-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Data-Driven Healthcare -- Contents -- Foreword -- For the Skimmers -- Acknowledgments -- Chapter 1 What Does Data Mean to You? -- The Gap -- Data Is a Four-Letter Word -- Strengths -- Weaknesses -- Opportunities -- Threats -- Setting the Stage -- Is This Book for You? -- References -- Chapter 2 What Happens When You Use Data to Transform an Industry? -- The History of Change -- On the Brink -- What Is "Data Driven," and Why Does It Matter? -- Management and Measurement -- Planning the Approach -- RISE -- Reduce the Unknowns -- Identify the Alternatives -- Streamline the Standards -- Evaluate the Activities -- Change Mechanisms of RISE -- Revolution -- References -- Chapter 3 How the Lack of Data Standardization Impedes Data-Driven Healthcare -- Healthcare Data Complexity -- Moving Data -- Data Is Your Asset-Manage It That Way -- Standards . . . Because Everyone Else Has Them -- Pareto's Principle -- The Great Wall of Data -- References -- Note -- Chapter 4 Adopting Your Data Warehouse for the Next Step in BI Maturity -- Go Boldly -- Disruptive Technologies -- Hadoop, the Cloud, and Modern Data Platforms -- The New Way Forward -- Reduce the Unknowns -- Identify the Alternatives -- Standardize -- Evaluate and Improve -- The Future Is Now -- Chapter 5 Creating a Data-Driven Healthcare Organization -- IT or the Business? -- Training -- What and How Should We Teach? -- Governing Data for Our New MDP -- Chapter 6 Applying "Big Data" to Change Healthcare -- The Call of Big Data -- Evolve or Die -- Let's Organize This and Take All the Fun Out of It -- Dipping Your Big Toe into Big Data -- References -- Chapter 7 Making Data Consumable -- How We Present Information Matters -- When We Present the Information Matters, Too -- Why Do We Want to Visually Represent Our Data? -- Learning a New Language -- A Multimedia Approach to Consumable Data.
References -- Chapter 8 Data Privacy and Confidentiality: A Brave New World -- Who Owns the Data? -- Barriers Are Everywhere -- Process and Technology -- Reference -- Chapter 9 A Call to Action -- Applying RISE to Your Efforts -- Some Distinctions about Being New -- Getting Started -- You Know What They Say about Assuming -- What Does Data Mean to You? -- Transforming an Industry -- Data Standardization -- The Next Step in BI Maturity -- Creating the DDHO -- "Big Data" -- Make Your Data Consumable -- Privacy and Confidentiality -- Final Thoughts on Data-Driven Healthcare -- Appendix A Readiness for Change -- Appendix B Tenets of Healthcare BI -- Appendix C Estimating the Efforts -- Appendix D Business Metrics -- Appendix E Agenda | Company Name | JAD Session -- Appendix F Data Visualization Guide -- Afterword -- About the Author -- Index -- EULA. |
| Record Nr. | UNINA-9910814457903321 |
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Madsen Laura B. <1973->
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| Hoboken, : Wiley, 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
| Développer et interpréter une échelle de mesure : applications du modèle de Rasch |
| Autore | Penta Massimo |
| Pubbl/distr/stampa | [Place of publication not identified], : Mardaga, 2005 |
| Soggetto topico |
Statistics as Topic
Decision Support Techniques Models, Theoretical Medical Informatics Applications Investigative Techniques Health Care Evaluation Mechanisms Epidemiologic Methods Quality of Health Care Analytical, Diagnostic and Therapeutic Techniques and Equipment Medical Informatics Public Health Health Care Quality, Access, and Evaluation Information Science Environment and Public Health Health Care Data Interpretation, Statistical Models, Statistical |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNINA-9910159401003321 |
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Penta Massimo
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| [Place of publication not identified], : Mardaga, 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
| Développer et interpréter une échelle de mesure : applications du modèle de Rasch |
| Autore | Penta Massimo |
| Pubbl/distr/stampa | [Place of publication not identified], : Mardaga, 2005 |
| Soggetto topico |
Statistics as Topic
Decision Support Techniques Models, Theoretical Medical Informatics Applications Investigative Techniques Health Care Evaluation Mechanisms Epidemiologic Methods Quality of Health Care Medical Informatics Public Health Health Care Quality, Access, and Evaluation Information Science Environment and Public Health Health Care Data Interpretation, Statistical Models, Statistical |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNINA-9910788249203321 |
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Penta Massimo
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| [Place of publication not identified], : Mardaga, 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Développer et interpréter une échelle de mesure : applications du modèle de Rasch
| Développer et interpréter une échelle de mesure : applications du modèle de Rasch |
| Autore | Penta Massimo |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | [Place of publication not identified], : Mardaga, 2005 |
| Descrizione fisica | 1 online resource (175 pages) |
| Soggetto topico |
Statistics as Topic
Decision Support Techniques Models, Theoretical Medical Informatics Applications Investigative Techniques Health Care Evaluation Mechanisms Epidemiologic Methods Quality of Health Care Medical Informatics Public Health Health Care Quality, Access, and Evaluation Information Science Environment and Public Health Delivery of Health Care Data Interpretation, Statistical Models, Statistical |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Nota di contenuto |
Page de couverture -- Page de titre -- Préface -- Introduction -- 1. Les premières étapes vers une échelle de mesure : l'identification, l'observation et l'évaluation de la variable -- 1.1. L'identification de la variable et la sélection des items -- 1.2. L'observation des personnes -- 1.3. L'évaluation de la variable -- Le format dichotomique -- Le format polytomique -- L'évaluation par le score -- 1.4. Résumé -- 1.5. Exercices -- 1.6. Solutions -- 2. Le modèle de mesure Rasch -- 2.1. Toutes les mesures sont des nombres, mais tous les nombres ne sont pas des mesures -- Une mesure linéaire -- Une mesure continue -- Une mesure objective -- 2.2. Le modèle dichotomique -- La formulation du modèle dichotomique -- La Courbe Caractéristique de l'Item (CCI) ou la probabilité de réussite -- L'unité de mesure : le logit -- 2.3. Les modèles polytomiques -- Les Courbes de Probabilité des Catégories (CPC) -- La Courbe Caractéristique de l'Item (CCI) -- Les seuils centralisés et décentralisés -- La formulation des modèles polytomiques -- Les modèles rating scale et partial credit -- La formulation logistique des modèles polytomiques -- 2.4. La mesure à l'aide du modèle de Rasch -- 2.5. Résumé -- 2.6. Exercices -- 2.7. Solutions -- 3. Les critères d'une mesure objective -- 3.1. L'ordre -- 3.2. L'unidimensionnalité -- 3.3. L'indépendance locale -- 3.4. La linéarité de l'échelle -- 3.5. L'objectivité spécifique -- 3.6. Exercices -- 3.7. Solutions -- 4. L'estimation des paramètres -- 4.1. La préparation de la matrice des réponses -- Le pattern «diagonal» -- Des statistiques suffisantes -- Les scores extrêmes -- 4.2. La procédure pairée (PAIR) -- 4.3. La procédure inconditionnelle (UCON) -- 4.4. Les erreurs associées aux estimations des paramètres -- 4.5. La représentation des paramètres -- 4.6. Résumé -- 4.7. Exercices -- 4.8. Solutions.
5. La vérification des critères d'une mesure objective -- 5.1. La vérification de l'ajustement des données aux prescriptions du modèle -- 5.1.1. Les réponses observées et les scores attendus -- 5.1.2. Les résidus -- 5.1.3. Les types de mauvais ajustement : overfit et underfit -- 5.1.4. Les indices d'ajustement -- L' Infit et l' Outfit -- Le Chi-Carré (χ2) -- 5.1.5. L'interprétation des indices d'ajustement -- L' Infit et l' Outfit -- Le Chi-Carré (χ2) -- 5.2. La vérification de l'ordre des catégories -- 5.2.1. L'ordre des catégories -- 5.2.2. Les critères de vérification de l'ordre des catégories -- 5.2.3. L'interprétation de l'ordre des catégories -- 5.3. Exercices -- 5.4. Solutions -- 6. Les qualités psychométriques de l'échelle -- 6.1. La validité -- 6.2. La fiabilité -- 6.3. La plus petite différence mesurable -- 6.4. Le fonctionnement différentiel des items -- 6.5. L'analyse en composantes principales des résidus -- 6.6. Exercices -- 6.7. Solutions -- 7. Le développement d'une échelle d'habileté manuelle à l'aide du modèle de Rasch -- 7.1. La conception et le développement de l'échelle -- 7.1.1. L'identification de la variable et la sélection des items -- 7.1.2. L'observation des personnes -- 7.1.3. L'évaluation de la variable -- 7.2. Le protocole d'évaluation des patients -- 7.2.1. Les critères de sélection de l'échantillon -- 7.2.2. Les procédures d'évaluation -- 7.3. L'analyse préliminaire des réponses -- 7.3.1. Le choix d'un modèle d'analyse des réponses -- 7.3.2. L'analyse des réponses manquantes -- 7.3.3. La vérification de l'ordre des catégories -- 7.3.4. La vérification du ciblage du test par rapport aux patients -- 7.3.5. L'analyse en composantes principales des résidus -- 7.4. L'échelle d'habileté manuelle pour adultes hémiplégiques chroniques -- 7.4.1. L'ordre des catégories de réponse. 7.4.2. Les propriétés métriques de l'échelle ABILHAND -- L'étendue de mesure -- L'ajustement des réponses aux prescriptions du modèle -- La fiabilité de séparation -- 7.4.3. La structure d'ABILHAND -- 7.4.4. L'invariance d'ABILHAND -- 7.5. La validité d'ABILHAND -- 7.5.1. La validité de contenu d'ABILHAND -- 7.5.2. La validité conceptuelle d'ABILHAND -- 8. Conclusion -- Bibliographie -- Glossaire des principaux symboles -- Lexique Français-Anglais -- Lexique Anglais-Français -- Catalogue des éditions Mardaga -- Copyright. |
| Record Nr. | UNINA-9910967719703321 |
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Penta Massimo
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| [Place of publication not identified], : Mardaga, 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Empirical evaluation of the association between methodological shortcomings and estimates of adverse events
| Empirical evaluation of the association between methodological shortcomings and estimates of adverse events |
| Pubbl/distr/stampa | [Place of publication not identified], : U S Dept of Health and Human Services Agency for Healthcare Research and Quality, 2006 |
| Descrizione fisica | 1 online resource |
| Collana |
Technical Reviews
AHRQ publication |
| Soggetto topico |
Outcome Assessment, Health Care
Data Interpretation, Statistical |
| Soggetto genere / forma | Review |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910698400803321 |
| [Place of publication not identified], : U S Dept of Health and Human Services Agency for Healthcare Research and Quality, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fatality and injury rates for two types of rotorcraft accidents [[electronic resource] ] : final report / / David Palmerton
| Fatality and injury rates for two types of rotorcraft accidents [[electronic resource] ] : final report / / David Palmerton |
| Autore | Palmerton David |
| Pubbl/distr/stampa | Washington, DC : , : Federal Aviation Administration, Office of Aerospace Medicine, , [2005] |
| Descrizione fisica | 1 volume : digital, PDF file |
| Soggetto topico |
Accidents, Aviation - mortality
Aircraft Data Interpretation, Statistical Wounds and Injuries - mortality Helicopters - Accidents - Investigation Aircraft accidents - Research |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Fatality and injury rates for two types of rotorcraft accidents |
| Record Nr. | UNINA-9910694623603321 |
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Palmerton David
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| Washington, DC : , : Federal Aviation Administration, Office of Aerospace Medicine, , [2005] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters
| How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters |
| Autore | Campbell Michael J. <1950-> |
| Pubbl/distr/stampa | Chichester, England : , : Wiley, , 2014 |
| Descrizione fisica | 1 online resource (268 p.) |
| Disciplina | 610.72/4 |
| Collana | Statistics in Practice |
| Soggetto topico |
Randomized Controlled Trials as Topic
Data Interpretation, Statistical Health Services Research - method Research Design |
| ISBN |
1-118-76360-2
1-118-76345-9 1-118-76359-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Copyright; Contents; Preface; Acronyms and abbreviations; Chapter 1 Introduction; 1.1 Randomised controlled trials; 1.1.1 A-Allocation at random; 1.1.2 B-Blindness; 1.1.3 C-Control; 1.2 Complex interventions; 1.3 History of cluster randomised trials; 1.4 Cohort and field trials; 1.5 The field/community trial; 1.5.1 The REACT trial; 1.5.2 The Informed Choice leaflets trial; 1.5.3 The Mwanza trial; 1.5.4 The paramedics practitioner trial; 1.6 The cohort trial; 1.6.1 The PoNDER trial; 1.6.2 The DESMOND trial; 1.6.3 The Diabetes Care from Diagnosis trial; 1.6.4 The REPOSE trial
1.6.5 Other examples of cohort cluster trials 1.7 Field versus cohort designs; 1.8 Reasons for cluster trials; 1.9 Between- and within-cluster variation; 1.10 Random-effects models for continuous outcomes; 1.10.1 The model; 1.10.2 The intracluster correlation coefficient; 1.10.3 Estimating the intracluster correlation (ICC) coefficient; 1.10.4 Link between the Pearson correlation coefficient and the intraclass correlation coefficient; 1.11 Random-effects models for binary outcomes; 1.11.1 The model; 1.11.2 The ICC for binary data; 1.11.3 The coefficient of variation 1.11.4 Relationship between cvc and ρ for binary data 1.12 The design effect; 1.13 Commonly asked questions; 1.14 Websources; Exercise; Appendix 1.A; Chapter 2 Design issues; 2.1 Introduction; 2.2 Issues for a simple intervention; 2.2.1 Phases of a trial; 2.2.1.1 Preclinical; 2.2.1.2 Sequence of phases; 2.2.2 'Pragmatic' and 'explanatory' trials; 2.2.3 Intention-to-treat and per-protocol analyses; 2.2.4 Non-inferiority and equivalence trials; 2.3 Complex interventions; 2.3.1 Design of complex interventions; 2.3.1.1 Theory (preclinical); 2.3.2 Phase I modelling/qualitative designs 2.3.3 Pilot or feasibility studies 2.3.4 Example of pilot/feasibility studies in cluster trials; 2.4 Recruitment bias; 2.5 Matched-pair trials; 2.5.1 Design of matched-pair studies; 2.5.2 Limitations of matched-pairs designs; 2.5.3 Example of matched-pair design: The Family Heart Study; 2.6 Other types of designs; 2.6.1 Cluster factorial designs; 2.6.2 Example cluster factorial trial; 2.6.3 Cluster crossover trials; 2.6.4 Example of a cluster crossover trial; 2.6.5 Stepped wedge; 2.6.6 Pseudorandomised trials; 2.7 Other design issues; 2.8 Strategies for improving precision; 2.9 Randomisation 2.9.1 Reasons for randomisation 2.9.2 Simple randomisation; 2.9.3 Stratified randomisation; 2.9.4 Restricted randomisation; 2.9.5 Minimisation; Exercise; Appendix 2.A; Chapter 3 Sample size: How many subjects/clusters do I need for my cluster randomised controlled trial?; 3.1 Introduction; 3.1.1 Justification of the requirement for a sample size; 3.1.2 Significance tests, P-values and power; 3.1.3 Sample size and cluster trials; 3.2 Sample size for continuous data-comparing two means; 3.2.1 Basic formulae; 3.2.2 The design effect (DE) in cluster RCTs; 3.2.3 Example from general practice 3.3 Sample size for binary data-comparing two proportions |
| Record Nr. | UNINA-9910139141103321 |
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Campbell Michael J. <1950->
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||
| Chichester, England : , : Wiley, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters
| How to design, analyse and report cluster randomised trials in medicine and health related research / / Michael J. Campbell and Stephen J. Walters |
| Autore | Campbell Michael J. <1950-> |
| Pubbl/distr/stampa | Chichester, England : , : Wiley, , 2014 |
| Descrizione fisica | 1 online resource (268 p.) |
| Disciplina | 610.72/4 |
| Collana | Statistics in Practice |
| Soggetto topico |
Randomized Controlled Trials as Topic
Data Interpretation, Statistical Health Services Research - method Research Design |
| ISBN |
1-118-76360-2
1-118-76345-9 1-118-76359-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Copyright; Contents; Preface; Acronyms and abbreviations; Chapter 1 Introduction; 1.1 Randomised controlled trials; 1.1.1 A-Allocation at random; 1.1.2 B-Blindness; 1.1.3 C-Control; 1.2 Complex interventions; 1.3 History of cluster randomised trials; 1.4 Cohort and field trials; 1.5 The field/community trial; 1.5.1 The REACT trial; 1.5.2 The Informed Choice leaflets trial; 1.5.3 The Mwanza trial; 1.5.4 The paramedics practitioner trial; 1.6 The cohort trial; 1.6.1 The PoNDER trial; 1.6.2 The DESMOND trial; 1.6.3 The Diabetes Care from Diagnosis trial; 1.6.4 The REPOSE trial
1.6.5 Other examples of cohort cluster trials 1.7 Field versus cohort designs; 1.8 Reasons for cluster trials; 1.9 Between- and within-cluster variation; 1.10 Random-effects models for continuous outcomes; 1.10.1 The model; 1.10.2 The intracluster correlation coefficient; 1.10.3 Estimating the intracluster correlation (ICC) coefficient; 1.10.4 Link between the Pearson correlation coefficient and the intraclass correlation coefficient; 1.11 Random-effects models for binary outcomes; 1.11.1 The model; 1.11.2 The ICC for binary data; 1.11.3 The coefficient of variation 1.11.4 Relationship between cvc and ρ for binary data 1.12 The design effect; 1.13 Commonly asked questions; 1.14 Websources; Exercise; Appendix 1.A; Chapter 2 Design issues; 2.1 Introduction; 2.2 Issues for a simple intervention; 2.2.1 Phases of a trial; 2.2.1.1 Preclinical; 2.2.1.2 Sequence of phases; 2.2.2 'Pragmatic' and 'explanatory' trials; 2.2.3 Intention-to-treat and per-protocol analyses; 2.2.4 Non-inferiority and equivalence trials; 2.3 Complex interventions; 2.3.1 Design of complex interventions; 2.3.1.1 Theory (preclinical); 2.3.2 Phase I modelling/qualitative designs 2.3.3 Pilot or feasibility studies 2.3.4 Example of pilot/feasibility studies in cluster trials; 2.4 Recruitment bias; 2.5 Matched-pair trials; 2.5.1 Design of matched-pair studies; 2.5.2 Limitations of matched-pairs designs; 2.5.3 Example of matched-pair design: The Family Heart Study; 2.6 Other types of designs; 2.6.1 Cluster factorial designs; 2.6.2 Example cluster factorial trial; 2.6.3 Cluster crossover trials; 2.6.4 Example of a cluster crossover trial; 2.6.5 Stepped wedge; 2.6.6 Pseudorandomised trials; 2.7 Other design issues; 2.8 Strategies for improving precision; 2.9 Randomisation 2.9.1 Reasons for randomisation 2.9.2 Simple randomisation; 2.9.3 Stratified randomisation; 2.9.4 Restricted randomisation; 2.9.5 Minimisation; Exercise; Appendix 2.A; Chapter 3 Sample size: How many subjects/clusters do I need for my cluster randomised controlled trial?; 3.1 Introduction; 3.1.1 Justification of the requirement for a sample size; 3.1.2 Significance tests, P-values and power; 3.1.3 Sample size and cluster trials; 3.2 Sample size for continuous data-comparing two means; 3.2.1 Basic formulae; 3.2.2 The design effect (DE) in cluster RCTs; 3.2.3 Example from general practice 3.3 Sample size for binary data-comparing two proportions |
| Record Nr. | UNINA-9910828428003321 |
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Campbell Michael J. <1950->
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| Chichester, England : , : Wiley, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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