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1. On sparsity, power-law and clustering properties of graphex processes

Author

Caron, F, Panero, F, and Rousseau, J

Subjects
Probability (math.PR), FOS: Mathematics, Mathematics - Statistics Theory, Statistics Theory (math.ST), Mathematics - Probability
Abstract

This paper investigates properties of the class of graphs based on exchangeable point processes. We provide asymptotic expressions for the number of edges, number of nodes, and degree distributions, identifying four regimes: (i) a dense regime, (ii) a sparse, almost dense regime, (iii) a sparse regime with power-law behaviour, and (iv) an almost extremely sparse regime. We show that, under mild assumptions, both the global and local clustering coefficients converge to constants which may or may not be the same. We also derive a central limit theorem for subgraph counts and for the number of nodes. Finally, we propose a class of models within this framework where one can separately control the latent structure and the global sparsity/power-law properties of the graph.

Published
2022
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2. Power-law phenomena in Bayesian nonparametrics

Author

Panero, F, Lambiotte, R, Williamson, S, Caron, F, and Rousseau, J

Subjects
Machine learning, Statistics, Spatial analysis (Statistics), Data privacy
Abstract

Bayesian methods constitute a popular approach to perform statistical inference and predict phenomena of interest. Surely, part of the popularity of the Bayesian paradigm can be linked to their intuitive core idea: to take advantage of the user's prior knowledge and integrate it in the statistical procedure. The result of this synergy is the posterior distribution, focal point of Bayesian inference and instrument to quantify the uncertainty of the estimation. This thesis collects the work done as a research student on statistical models, built with the tools of Bayesian nonparametrics, to describe power-law distributed data. The motivation of the proposed models are to be found in two different fields of application: complex networks and privacy assessment. After the introduction, in the first half of the thesis I concentrate on the proposal and analysis of models for networks, the mathematical objects that describe relations among entities by representing them as nodes connected through links. Power-laws usually appear in real-world networks as the distribution function of the degrees, namely the number of links of the nodes. The two pieces of work presented belong to the graphex process framework, a flexible generating process which allows to mimic empirically observed networks characteristics. Chapter 2 fits into this framework and extends the original proposal of Caron and Fox (2017) to provide a novel modelling approach to describe sparse networks with spatial structure or other covariates. An approximate inference strategy is provided and tested on simulated data. The paper presented in chapter 3 casts light on the asymptotic properties of networks generated under the graphex process, proving the desirable properties of sparsity, power-law degree distributions, clustering and two central limit theorems. The second half of the thesis is devoted to the development of statistical methods to quantify the risk of disclosure, which arises whenever datasets with records of individuals are published: an intruder could match the data with prior information and disclose the identity, and therefore the sensitive features, of a person. Chapter 4 develops an estimator to quantify this risk using the Pitman-Yor process, a popular prior on probability distributions that has a distinguishable power-law tail. A closed form posterior distribution of the estimator is provided in a convenient mixture representation, and experiments on both simulated and real data show the effectiveness of the method. Chapter 5 deals with the estimation of the same risk under no distributional assumptions, using a fully nonparametric method. The estimator is extremely easy to understand, fast to compute and has provable guarantees of optimality. Chapter 6 concludes the thesis with a final summary and some proposals to extend the current work towards new research directions.

Published
2022

3. Prediction of dry matter, carbon and ash contents and identification of Calycophyllum spruceanum (Benth) organs by Near-Infrared spectrophotometry

Author

CIARNOSCHI, L. D., OLIVEIRA, L. C. de, SIMEONE, M. L. F., PANERO, F. dos S., PANERO, P. dos S., RUIZ RODRIGUEZ, A., ALVES FILHO, E. G., PEREIRA, M. G., SILVA, L. M. da, LUCAS DALMOLIN CIARNOSCHI, Consultor Júnior I da STCP Engenharia de Projetos, Curitiba, Paraná, LUIS CLAUDIO DE OLIVEIRA, CPAF-AC, MARIA LUCIA FERREIRA SIMEONE, CNPMS, FRANCISCO DOS SANTOS PANERO, Professor da Universidade Federal de Roraima, PEDRO DOS SANTOS PANERO, Professor do Instituto Federal de Educação, Ciência e Tecnologia de Roraima, Boa Vista, RR, ANSELMO RUIZ RODRIGUEZ, Professor da Universidade Federal do Acre, ELENILSON G. ALVES FILHO, Professor da Universidade Federal do Ceará, MARCOS GERVASIO PEREIRA, Professor da Universidade Federal Rural do Rio de Janeiro, and LUCIELIO MANOEL DA SILVA, CPATC.

Subjects
Matéria Seca, Produção, Espectroscopia no infravermelho próximo, Acre, Analytical Chemistry, Regressão Linear, Near-infrared spectroscopy, Análisis de regresión, Carbono, Dry matter accumulation, Calycophyllum Spruceanum, Productos forestales no madereros, Acumulación de materia seca, Spectroscopy, Espectroscopía del infrarrojo cercano, Produto florestal não madeireiro (PFNM), Mulateiro, Cinza, Wood ash, Ceniza de madera, Carbon, Amazonia Occidental, Amazônia Ocidental, Western Amazon, Nontimber forest products, Regression analysis
Abstract

Calycophyllum spruceanum (Benth) is a tree of the Amazon region popularly known as 'mulateiro', whose wood has multiple uses, from energy to folk medicine. Thus, it is extremely important to evaluate desirable characteristics, through quick methods that meet the principles of green chemistry. The objective of this study was to evaluate the potential of the near-infrared (NIR) spectroscopy technique for the prediction of dry matter, carbon and ash contents and identification of parts of C. spruceanum trees. The Partial Least Squares (PLS) regression model applied within the spectral range of 400-2498 nm proved to be adequate to estimate the dry matter, carbon and ash contents in C. spruceanum sapwood and bark samples, with R2 above 0.90 in both calibration and validation. Hierarchical cluster analysis and principal component analysis techniques when applied to the spectra were able to efficiently separate bark from sapwood. The results show that the NIR technique developed can be used in the determination of dry matter, carbon and ash contents in C. spruceanum, in addition to its discriminatory power in the separation of parts of the plant. Made available in DSpace on 2022-06-22T04:00:25Z (GMT). No. of bitstreams: 1 27328.pdf: 2041971 bytes, checksum: e7951753116916d19c30a538608898d1 (MD5) Previous issue date: 2022

Published
2022
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4. Issues with Nonparametric Disclosure Risk Assessment

Author

Camerlenghi, F, Favaro, S, Naulet, Z, Panero, F, Camerlenghi, F, Favaro, S, Naulet, Z, and Panero, F

Subjects
disclosure risk assessment, microdata sample, parametric inference, nonparametric inference
Published
2019

5. Effects on the incidence of cardiovascular events of the addition of pioglitazone versus sulfonylureas in patients with type 2 diabetes inadequately controlled with metformin (TOSCA.IT): a randomised, multicentre trial

Author

Vaccaro, O, Masulli, M, Nicolucci, A, Bonora, E, Del Prato, S, Maggioni, Ap, Rivellese, Aa, Squatrito, S, Giorda, Cb, Sesti, G, Mocarelli, P, Lucisano, G, Sacco, M, Signorini, S, Cappellini, F, Perriello, G, Babini, Ac, Lapolla, A, Gregori, G, Giordano, C, Corsi, L, Buzzetti, R, Clemente, G, Di Cianni, G, Iannarelli, R, Cordera, R, La Macchia, O, Zamboni, C, Scaranna, C, Boemi, M, Iovine, C, Lauro, D, Leotta, S, Dall'Aglio, E, Cannarsa, E, Tonutti, L, Pugliese, G, Bossi, Ac, Anichini, R, Dotta, F, Di Benedetto, A, Citro, G, Antenucci, D, Ricci, L, Giorgino, F, Santini, C, Gnasso, A, De Cosmo, S, Zavaroni, D, Vedovato, M, Consoli, A, Calabrese, M, di Bartolo, P, Fornengo, P, Riccardi, G, IT) study group, Thiazolidinediones Or Sulfonylureas Cardiovascular Accidents Intervention Trial (TOSCA., Collaborators: Vaccaro O, Italian Diabetes Society., D'Angelo, F, Giansanti, R, Tanase, L, Lanari, L, Testa, I, Pancani, F, Ranchelli, A, Vagheggi, P, Scatona, A, Fontana, L, Laviola, L, Tarantino, L, Ippolito, C, Gigantelli, V, Manicone, M, Conte, E, Trevisan, R, Rota, R, Corsi, A, Dodesini, Ar, Reggiani, Gm, Montesi, L, Mazzella, N, Forlani, G, Caselli, C, Di Luzio, R, Mazzotti, A, Aiello, A, Barrea, A, Musto, A, D'Amico, F, Sinagra, T, Longhitano, S, Trowpea, V, Sparti, M, Italia, S, Lisi, E, Grasso, G, Pezzino, V, Insalaco, F, Carallo, C, Scicchitano, C, De Franceschi MS, Calbucci, G, Ripani, R, Cuneo, G, Corsi, S, Romeo, F, Lesina, A, Comoglio, M, Bonetto, C, Robusto, A, Nada, E, Asprino, V, Cetraro, R, Impieri, M, Lucchese, G, Donnarumma, G, Tizio, B, Lenza, L, Paraggio, P, Tomasi, F, Dozio, N, Scalambra, E, Mannucci, E, Lamanna, C, Cignarelli, M, Macchia, O, Fariello, S, Sorrentino, Mr, Franzetti, I, Radin, R, Annunziata, F, Bonabello, La, Durante, A, Dolcino, M, Gallo, F, Mazzucchelli, C, Aleo, A, Melga, P, Briatore, L, Maggi, D, Storace, D, Cecoli, F, D'Ugo, E, Pupillo, M, Baldassarre, Mpa, Salvati, F, Minnucci, A, De Luca, A, Zugaro, A, Santarelli, L, Bosco, A, Petrella, V, La Verghetta GG, De Gregorio, A, D'Andrea, S, Giuliani, Ae, Polidoro, Wl, Sperandio, A, Sciarretta, F, Pezzella, A, Carlone, A, Potenziani, S, Venditti, C, Foffi, C, Carbone, S, Cipolloni, L, Moretti, C, Leto, G, Serra, R, Petrachi, F, Romano, I, Lacaria, E, Russo, L, Goretti, C, Sannino, C, Dolci, M, Bruselli, L, Mori, Ml, Baccetti, F, Del Freo, M, Cucinotta, D, Giunta, L, Ruffo, Mc, Cannizzaro, D, Pintaudi, B, Perrone, G, Pata, P, Ragonese, F, Lettina, G, Mancuso, T, Coppolino, A, Piatti, Pm, Monti, L, Stuccillo, M, Lucotti, P, Setola, M, Crippa, Gv, Loi, C, Oldani, M, Bottalico, Ml, Pellegata, B, Bonomo, M, Menicatti, Lsm, Resi, V, Bertuzzi, F, Disoteo, Eo, Pizzi, G, Annuzzi, G, Capaldo, B, Nappo, R, Auciello, Sm, Turco, Aa, Costagliola, L, Corte, Gd, Vallefuoco, P, Nappi, F, Vitale, M, Cocozza, S, Ciano, O, Massimino, E, Garofalo, N, Avogaro, A, Guarneri, G, Fedele, D, Sartore, G, Chilelli, Nc, Burlina, S, Bonsembiante, B, Galluzzo, A, Torregrossa, V, Mancastroppa, G, Arsenio, L, Cioni, F, Caronna, S, Papi, M, Babini, M, Santeusanio, F, Calagreti, G, Timi, A, Tantucci, A, Marino, C, Ginestra, F, Di Biagio, R, Taraborelli, M, Miccoli, R, Bianchi, C, Garofolo, M, Politi, Ks, Penno, G, Livraga, S, Calzoni, F, Mancastroppa, Glf, Corsini, E, Tedeschi, A, Gaglianò, Ms, Ippolito, G, Salutini, E, Cervellino, F, Natale, M, Salvatore, V, Zampino, A, Sinisi, R, Arcangeli, A, Zogheri, A, Guizzotti, S, Longo, R, Di Bartolo, P, Pellicano, F, Scolozzi, P, Termine, S, Luberto, A, Ballardini, G, Trojani, C, Mazzuca, P, Bruglia, M, Ciamei, M, Genghini, S, Zannoni, C, Rangel, G, Salvi, L, Zappaterreno, A, Cordone, S, Simonelli, P, Meggiorini, M, Frasheri, A, Di Pippo, C, Maglio, C, Mazzitelli, G, Rinaldi, Me, Galli, A, Romano, M, D'Angelo, P, Suraci, C, Bacci, S, Palena, Ap, Genovese, S, Mancino, M, Rondinelli, M, Capone, F, Calabretto, E, Bulgheroni, M, Bucciarelli, L, Ceccarelli, E, Fondelli, C, Santacroce, C, Guarino, E, Nigi, L, Lalli, C, Di Vizia, G, Scarponi, M, Montani, V, Di Bernardino, P, Romagni, P, Dolcetti, K, Forte, E, Tamburo, L, Perin, Pc, Prinzis, T, Gruden, G, Bruno, G, Zucco, C, Perotta, M, Marena, S, Monsignore, S, Panero, F, Ponzi, F, Carpinteri, R, Casagrande, Ml, Coletti, Mf, Balini, A, Filopanti, M, Madaschi, S, Pulcina, A, Grimaldi, F, Venturini, G, Agus, S, Pagnutti, S, Guidotti, F, Cavarape, A, Cigolini, M, Pichiri, I, Brangani, C, Fainelli, G, Tomasetto, E, Zoppini, G, Galletti, A, Perrone, D, Capra, C, Bianchini, F, Ceseri, M, Di Nardo, B, Sasso, E, Bartolomei, B, Suliman, I, Fabbri, G, Romano, G, Maturo, N, Nunziata, G, Capobianco, G, De Simone, G, Villa, V, Rota, G, Pentangelo, C, Carbonara, O, Caiazzo, G, Cutolo, M, Sorrentino, T, Mastrilli, V, Amelia, U, Masi, S, Corigliano, G, Gaeta, I, Armentano, V, Calatola, P, Capuano, G, Angiulli, B, Auletta, P, Petraroli, E, Iodice, Ce, Agrusta, M., Vaccaro, Olga, Masulli, Maria, Nicolucci, Antonio, Bonora, Enzo, Del Prato, Stefano, Maggioni, Aldo P, Rivellese, Angela A, Squatrito, Sebastiano, Giorda, Carlo B, Sesti, Giorgio, Mocarelli, Paolo, Lucisano, Giuseppe, Sacco, Michele, Signorini, Stefano, Cappellini, Fabrizio, Perriello, Gabriele, Babini, Anna Carla, Lapolla, Annunziata, Gregori, Giovanna, Giordano, Carla, Corsi, Laura, Buzzetti, Raffaella, Clemente, Gennaro, Di Cianni, Graziano, Iannarelli, Rossella, Cordera, Renzo, La Macchia, Olga, Zamboni, Chiara, Scaranna, Cristiana, Boemi, Massimo, Iovine, Ciro, Lauro, Davide, Leotta, Sergio, Dall'Aglio, Elisabetta, Cannarsa, Emanuela, Tonutti, Laura, Pugliese, Giuseppe, Bossi, Antonio C, Anichini, Roberto, Dotta, Francesco, Di Benedetto, Antonino, Citro, Giuseppe, Antenucci, Daniela, Ricci, Lucia, Giorgino, Francesco, Santini, Costanza, Gnasso, Agostino, De Cosmo, Salvatore, Zavaroni, Donatella, Vedovato, Monica, Consoli, Agostino, Calabrese, Maria, Di Bartolo, Paolo, Fornengo, Paolo, Riccardi, Gabriele, Maggioni, Aldo Pietro, D'Angelo, Federica, Giansanti, Roberto, Tanase, Laura, Lanari, Luigi, Testa, Ivano, Pancani, Francesca, Ranchelli, Anna, Vagheggi, Paolo, Scatona, Alessia, Fontana, Lucia, Laviola, Luigi, Tarantino, Lucia, Ippolito, Claudia, Gigantelli, Vittoria, Manicone, Mariangela, Conte, Eleonora, Trevisan, Roberto, Rota, Rossella, Corsi, Anna, Dodesini, Alessandro R., Reggiani, Giulio Marchesini, Montesi, Luca, Mazzella, Natalia, Forlani, Gabriele, Caselli, Chiara, Di Luzio, Raffaella, Mazzotti, Arianna, Aiello, Antimo, Barrea, Angelina, Musto, Antonio, D'Amico, Fiorentina, Sinagra, Tiziana, Longhitano, Sara, Trowpea, Vanessa, Sparti, Maria, Italia, Salvatore, Lisi, Enrico, Grasso, Giuseppe, Pezzino, Vincenzo, Insalaco, Federica, Carallo, Claudio, Scicchitano, Caterina, De Franceschi, Maria Serena, Calbucci, Giovanni, Ripani, Raffaella, Cuneo, Giacomo, Corsi, Simona, Giorda, Carlo B., Romeo, Francesco, Lesina, Annalisa, Comoglio, Marco, Bonetto, Caterina, Robusto, Anna, Nada, Elisa, Asprino, Vincenzo, Cetraro, Rosa, Impieri, Michelina, Lucchese, Giuseppe, Donnarumma, Giovanna, Tizio, Biagio, Lenza, Lazzaro, Paraggio, Pia, Tomasi, Franco, Dozio, Nicoletta, Scalambra, Egle, Mannucci, Edoardo, Lamanna, Caterina, Cignarelli, Mauro, Macchia, Olga La, Fariello, Stefania, Sorrentino, Maria Rosaria, Franzetti, Ivano, Radin, Raffaella, Annunziata, Francesca, Bonabello, Laura Affinito, Durante, Arianna, Dolcino, Mara, Gallo, Fiorenza, Mazzucchelli, Chiara, Aleo, Anna, Melga, Pierluigi, Briatore, Lucia, Maggi, Davide, Storace, Daniela, Cecoli, Francesca, D'Ugo, Ercole, Pupillo, Mario, Baldassarre, Maria Pompea Antonia, Salvati, Filippo, Minnucci, Anita, De Luca, Angelo, Zugaro, Antonella, Santarelli, Livia, Bosco, Angela, Petrella, Vittorio, La Verghetta, Grazia Giovanna, De Gregorio, Antonella, D'Andrea, Settimio, Giuliani, Anna Elisa, Polidoro, W. Lorella, Sperandio, Alessandra, Sciarretta, Filomena, Pezzella, Alfonso, Carlone, Angela, Potenziani, Stella, Venditti, Chiara, Foffi, Chiara, Carbone, Salvatore, Cipolloni, Laura, Moretti, Chiara, Leto, Gaetano, Serra, Rosalia, Petrachi, Francesca, Romano, Isabella, Lacaria, Emilia, Russo, Laura, Goretti, Chiara, Sannino, Claudia, Dolci, Maria, Bruselli, Laura, Mori, Mary L., Baccetti, Fabio, Del Freo, Maria, Cucinotta, Domenico, Giunta, Loretta, Ruffo, Maria Concetta, Cannizzaro, Desiree, Pintaudi, Basilio, Perrone, Giovanni, Pata, Pietro, Ragonese, Francesco, Lettina, Gabriele, Mancuso, Teresa, Coppolino, Aldo, Piatti, Pier Marco, Monti, Lucilla, Stuccillo, Michela, Lucotti, Pietro, Setola, Manuela, Crippa, Giulia Valentina, Loi, Cinzia, Oldani, Matteo, Bottalico, Maria Luisa, Pellegata, Beatrice, Bonomo, Matteo, Menicatti, Laura Silvia Maria, Resi, Veronica, Bertuzzi, Federico, Disoteo, Eugenia Olga, Pizzi, Gianluigi, Rivellese, Angela Albarosa, Annuzzi, Giovanni, Capaldo, Brunella, Nappo, Rossella, Auciello, Stefania Michela, Turco, Anna Amelia, Costagliola, Lucia, Corte, Giuseppina Della, Vallefuoco, Pasquale, Nappi, Francesca, Vitale, Marilena, Cocozza, Sara, Ciano, Ornella, Massimino, Elena, Garofalo, Nadia, Avogaro, Angelo, Guarneri, Gabriella, Fedele, Domenico, Sartor, Giovanni, Chilelli, Nino Cristiano, Burlina, Silvia, Bonsembiante, Barbara, Galluzzo, Aldo, Torregrossa, Vittoria, Mancastroppa, Giovanni, Arsenio, Leone, Cioni, Federico, Caronna, Silvana, Papi, Matteo, Babini, Massimiliano, Santeusanio, Fausto, Calagreti, Gioia, Timi, Alessia, Tantucci, Alice, Marino, Cecilia, Ginestra, Federica, Di Biagio, Rosamaria, Taraborelli, Merilda, Miccoli, Roberto, Bianchi, Cristina, Garofolo, Monia, Politi, Konstantina Savina, Penno, Giuseppe, Livraga, Stefania, Calzoni, Fabio, Mancastroppa, Giovanni Luigi Francesco, Corsini, Elisa, Tedeschi, Anna, Gaglianã², Maria Sole, Ippolito, Giulio, Salutini, Elisabetta, Cervellino, Francesco, Natale, Maria, Salvatore, Vita, Zampino, Armando, Sinisi, Rosa, Arcangeli, Adolfo, Zogheri, Alessia, Guizzotti, Sandra, Longo, Rossella, Pellicano, Francesca, Scolozzi, Patrizia, Termine, Simona, Luberto, Alessandra, Ballardini, Giorgio, Trojani, Cristina, Mazzuca, Paolo, Bruglia, Matteo, Ciamei, Monica, Genghini, Silvia, Zannoni, Chiara, Vitale, Martina, Rangel, Graziela, Salvi, Laura, Zappaterreno, Alessandra, Cordone, Samantha, Simonelli, Paola, Meggiorini, Marilla, Frasheri, Aurora, Di Pippo, Clelia, Maglio, Cristina, Mazzitelli, Giulia, Rinaldi, Maria Elena, Galli, Angelica, Romano, Maria, D'Angelo, Paola, Suraci, Concetta, Bacci, Simonetta, Palena, Antonio Pio, Genovese, Stefano, Mancino, Monica, Rondinelli, Maurizio, Capone, Filippo, Calabretto, Elisabetta, Bulgheroni, Monica, Bucciarelli, Loredana, Ceccarelli, Elena, Fondelli, Cecilia, Santacroce, Clorinda, Guarino, Elisa, Nigi, Laura, Lalli, Carlo, Di Vizia, Giovanni, Scarponi, Maura, Montani, Valeria, Di Bernardino, Paolo, Romagni, Paola, Dolcetti, Katia, Forte, Elisa, Tamburo, Lucilla, Perin, Paolo Cavallo, Prinzis, Tania, Gruden, Gabriella, Bruno, Graziella, Zucco, Chiara, Perotta, Massimo, Marena, Saverio, Monsignore, Simona, Panero, Francesco, Ponzi, Fulvia, Bossi, Antonio Carlo, Carpinteri, Rita, Casagrande, Maria Linda, Coletti, Maria Francesca, Balini, Annalisa, Filopanti, Marcello, Madaschi, Sara, Pulcina, Anna, Grimaldi, Franco, Venturini, Giorgio, Agus, Sandra, Pagnutti, Stefania, Guidotti, Francesca, Cavarape, Alessandro, Cigolini, Massimo, Pichiri, Isabella, Brangani, Corinna, Fainelli, Giulia, Tomasetto, Elena, Zoppini, Giacomo, Galletti, Anna, Perrone, Dominica, Capra, Claudio, Bianchini, Francesca, Ceseri, Martina, Di Nardo, Barbara, Sasso, Elisa, Bartolomei, Barbara, Suliman, Irina, Fabbri, Gianna, Romano, Geremia, Maturo, Nicola, Nunziata, Giuseppe, Capobianco, Giuseppe, De Simone, Giuseppina, Villa, Valeria, Rota, Giuseppe, Pentangelo, Carmine, Carbonara, Ornella, Caiazzo, Gennaro, Cutolo, Michele, Sorrentino, Tommasina, Mastrilli, Valeria, Amelia, Umberto, Masi, Stefano, Corigliano, Gerardo, Gaeta, Iole, Armentano, Vincenzo, Calatola, Pasqualino, Capuano, Gelsomina, Angiulli, Bruno, Auletta, Pasquale, Petraroli, Ettore, Iodice, Cinzia E., Agrusta, Mariano, Vaccaro, O, Masulli, M, Nicolucci, A, Bonora, E, Del Prato, S, Maggioni, A, Rivellese, A, Squatrito, S, Giorda, C, Sesti, G, Mocarelli, P, Lucisano, G, Sacco, M, Signorini, S, Cappellini, F, Perriello, G, Babini, A, Lapolla, A, Gregori, G, Giordano, C, Corsi, L, Buzzetti, R, Clemente, G, Di Cianni, G, Iannarelli, R, Cordera, R, La Macchia, O, Zamboni, C, Scaranna, C, Boemi, M, Iovine, C, Lauro, D, Leotta, S, Dall'Aglio, E, Cannarsa, E, Tonutti, L, Pugliese, G, Bossi, A, Anichini, R, Dotta, F, Di Benedetto, A, Citro, G, Antenucci, D, Ricci, L, Giorgino, F, Santini, C, Gnasso, A, De Cosmo, S, Zavaroni, D, Vedovato, M, Consoli, A, Calabrese, M, di Bartolo, P, Fornengo, P, Riccardi, G, D'Angelo, F, Giansanti, R, Tanase, L, Lanari, L, Testa, I, Pancani, F, Ranchelli, A, Vagheggi, P, Scatona, A, Fontana, L, Laviola, L, Tarantino, L, Ippolito, C, Gigantelli, V, Manicone, M, Conte, E, Trevisan, R, Rota, R, Dodesini, A, Reggiani, G, Montesi, L, Mazzella, N, Forlani, G, Caselli, C, Di Luzio, R, Mazzotti, A, Aiello, A, Barrea, A, Musto, A, D'Amico, F, Sinagra, T, Longhitano, S, Trowpea, V, Sparti, M, Italia, S, Lisi, E, Grasso, G, Pezzino, V, Insalaco, F, Carallo, C, Scicchitano, C, De Franceschi, M, Calbucci, G, Ripani, R, Cuneo, G, Corsi, S, Romeo, F, Lesina, A, Comoglio, M, Bonetto, C, Robusto, A, Nada, E, Asprino, V, Cetraro, R, Impieri, M, Lucchese, G, Donnarumma, G, Tizio, B, Lenza, L, Paraggio, P, Tomasi, F, Dozio, N, Scalambra, E, Mannucci, E, Lamanna, C, Cignarelli, M, Macchia, O, Fariello, S, Sorrentino, M, Franzetti, I, Radin, R, Annunziata, F, Bonabello, L, Durante, A, Dolcino, M, Gallo, F, Mazzucchelli, C, Aleo, A, Melga, P, Briatore, L, Maggi, D, Storace, D, Cecoli, F, D'Ugo, E, Pupillo, M, Baldassarre, M, Salvati, F, Minnucci, A, De Luca, A, Zugaro, A, Santarelli, L, Bosco, A, Petrella, V, La Verghetta, G, D'Andrea, S, Giuliani, A, Polidoro, W, Sperandio, A, Sciarretta, F, Pezzella, A, Carlone, A, Potenziani, S, Venditti, C, Foffi, C, Carbone, S, Cipolloni, L, Moretti, C, Leto, G, Serra, R, Petrachi, F, Romano, I, Lacaria, E, Russo, L, Goretti, C, Sannino, C, Dolci, M, Bruselli, L, Mori, M, Baccetti, F, Del Freo, M, Cucinotta, D, Giunta, L, Ruffo, M, Cannizzaro, D, Pintaudi, B, Perrone, G, Pata, P, Ragonese, F, Lettina, G, Mancuso, T, Coppolino, A, Piatti, P, Monti, L, Stuccillo, M, Lucotti, P, Setola, M, Crippa, G, Loi, C, Oldani, M, Bottalico, M, Pellegata, B, Bonomo, M, Menicatti, L, Resi, V, Bertuzzi, F, Disoteo, E, Pizzi, G, Annuzzi, G, Capaldo, B, Nappo, R, Auciello, S, Turco, A, Costagliola, L, Corte, G, Vallefuoco, P, Nappi, F, Vitale, M, Cocozza, S, Ciano, O, Massimino, E, Garofalo, N, Avogaro, A, Guarneri, G, Fedele, D, Sartore, G, Chilelli, N, Burlina, S, Bonsembiante, B, Galluzzo, A, Torregrossa, V, Mancastroppa, G, Arsenio, L, Cioni, F, Caronna, S, Papi, M, Santeusanio, F, Calagreti, G, Timi, A, Tantucci, A, Marino, C, Ginestra, F, Di Biagio, R, Taraborelli, M, Miccoli, R, Bianchi, C, Garofolo, M, Politi, K, Penno, G, Livraga, S, Calzoni, F, Corsini, E, Tedeschi, A, Gagliano, M, Ippolito, G, Salutini, E, Cervellino, F, Natale, M, Salvatore, V, Zampino, A, Sinisi, R, Arcangeli, A, Zogheri, A, Guizzotti, S, Longo, R, Pellicano, F, Scolozzi, P, Termine, S, Luberto, A, Ballardini, G, Trojani, C, Mazzuca, P, Bruglia, M, Ciamei, M, Genghini, S, Zannoni, C, Rangel, G, Salvi, L, Zappaterreno, A, Cordone, S, Simonelli, P, Meggiorini, M, Frasheri, A, Di Pippo, C, Maglio, C, Mazzitelli, G, Rinaldi, M, Galli, A, Romano, M, D'Angelo, P, Suraci, C, Bacci, S, Palena, A, Genovese, S, Mancino, M, Rondinelli, M, Capone, F, Calabretto, E, Bulgheroni, M, Bucciarelli, L, Ceccarelli, E, Fondelli, C, Santacroce, C, Guarino, E, Nigi, L, Lalli, C, Di Vizia, G, Scarponi, M, Montani, V, Di Bernardino, P, Romagni, P, Dolcetti, K, Forte, E, Tamburo, L, Perin, P, Prinzis, T, Gruden, G, Bruno, G, Zucco, C, Perotta, M, Marena, S, Monsignore, S, Panero, F, Ponzi, F, Carpinteri, R, Casagrande, M, Coletti, M, Balini, A, Filopanti, M, Madaschi, S, Pulcina, A, Grimaldi, F, Venturini, G, Agus, S, Pagnutti, S, Guidotti, F, Cavarape, A, Cigolini, M, Pichiri, I, Brangani, C, Fainelli, G, Tomasetto, E, Zoppini, G, Galletti, A, Perrone, D, Capra, C, Bianchini, F, Ceseri, M, Di Nardo, B, Sasso, E, Bartolomei, B, Suliman, I, Fabbri, G, Romano, G, Maturo, N, Nunziata, G, Capobianco, G, De Simone, G, Villa, V, Rota, G, Pentangelo, C, Carbonara, O, Caiazzo, G, Cutolo, M, Sorrentino, T, Mastrilli, V, Amelia, U, Masi, S, Corigliano, G, Gaeta, I, Armentano, V, Calatola, P, Capuano, G, Angiulli, B, Auletta, P, Petraroli, E, Iodice, C, Agrusta, M, di Bartolo, Paolo, Polidoro, w Lorella, Sartore, Giovanni, and Gaglianò, Maria Sole

Subjects
Male, Diabetes and Metabolism, ipoglycemic drugs, cardiovascualr event, Settore MED/09 - Medicina Interna, endocrine system diseases, IMPACT, pioglitazone versus sulfonylureas, Endocrinology, Diabetes and Metabolism, GLIMEPIRIDE, Diabetes, cardiovascular events, metformin, pioglitazone, sulphonylureas, Type 2 diabetes, 030204 cardiovascular system & hematology, Internal Medicine, Endocrinology, law.invention, Settore MED/13 - Endocrinologia, Glibenclamide, 0302 clinical medicine, Randomized controlled trial, law, GLYCEMIC CONTROL, Gliclazide, Internal medicine, diabetes and metabolism, RISK, education.field_of_study, diabetes, Incidence, endocrinology, diabetes and metabolism, endocrinology, Middle Aged, INSULIN, Metformin, Treatment Outcome, Editorial, sulphonylureas, Cardiovascular Diseases, Combination, Drug Therapy, Combination, Female, Type 2, medicine.drug, medicine.medical_specialty, Population, 030209 endocrinology & metabolism, Aged, Diabetes Mellitus, Type 2, Humans, Hypoglycemic Agents, Pioglitazone, Sulfonylurea Compounds, Thiazolidinediones, Cardiovascular events, 03 medical and health sciences, GLUCOSE-LOWERING DRUGS, Drug Therapy, Diabetes Mellitus, medicine, sulfonylureas, education, TOSCA.IT, business.industry, MORTALITY, nutritional and metabolic diseases, Insulin resistance, medicine.disease, Surgery, Glimepiride, business, FOLLOW-UP
Abstract

Background The best treatment option for patients with type 2 diabetes in whom treatment with metformin alone fails to achieve adequate glycaemic control is debated. We aimed to compare the long-term effects of pioglitazone versus sulfonylureas, given in addition to metformin, on cardiovascular events in patients with type 2 diabetes. Methods TOSCA.IT was a multicentre, randomised, pragmatic clinical trial, in which patients aged 50–75 years with type 2 diabetes inadequately controlled with metformin monotherapy (2–3 g per day) were recruited from 57 diabetes clinics in Italy. Patients were randomly assigned (1:1), by permuted blocks randomisation (block size 10), stratified by site and previous cardiovascular events, to add-on pioglitazone (15–45 mg) or a sulfonylurea (5–15 mg glibenclamide, 2–6 mg glimepiride, or 30–120 mg gliclazide, in accordance with local practice). The trial was unblinded, but event adjudicators were unaware of treatment assignment. The primary outcome, assessed with a Cox proportional-hazards model, was a composite of first occurrence of all-cause death, non-fatal myocardial infarction, non-fatal stroke, or urgent coronary revascularisation, assessed in the modified intention-to-treat population (all randomly assigned participants with baseline data available and without any protocol violations in relation to inclusion or exclusion criteria). This study is registered with ClinicalTrials.gov, number NCT00700856. Findings Between Sept 18, 2008, and Jan 15, 2014, 3028 patients were randomly assigned and included in the analyses. 1535 were assigned to pioglitazone and 1493 to sulfonylureas (glibenclamide 24 [2%], glimepiride 723 [48%], gliclazide 745 [50%]). At baseline, 335 (11%) participants had a previous cardiovascular event. The study was stopped early on the basis of a futility analysis after a median follow-up of 57·3 months. The primary outcome occurred in 105 patients (1·5 per 100 person-years) who were given pioglitazone and 108 (1·5 per 100 person-years) who were given sulfonylureas (hazard ratio 0·96, 95% CI 0·74–1·26, p=0·79). Fewer patients had hypoglycaemias in the pioglitazone group than in the sulfonylureas group (148 [10%] vs 508 [34%], p

Published
2017
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6. Separation of Cultivars of Soybeans by Chemometric Methods Using Near Infrared Spectroscopy

Author

PANERO, J. S., SILVA, H. E. B. da, PANERO, P. S., SMIDERLE, O. J., PANERO, F. S., FARIA, F. S. E. D. V., RODRIGUEZ, A. F. R., and OSCAR JOSE SMIDERLE, CPAF-Roraima.

Subjects
Hierarchical cluster analysis, Soybean classification
Abstract

Made available in DSpace on 2018-03-13T00:35:06Z (GMT). No. of bitstreams: 1 727942750021PB.pdf: 1034238 bytes, checksum: 5285573c242e3cac13b8cf10044c4eb3 (MD5) Previous issue date: 2018-03-12

Published
2018

14. Incidence of type 1 diabetes is increasing both in children and young adults in Northern Italy: 1984-2004 temporal trend

Author

Bruno, Graziella, Novelli, G, Panero, F, Perotto, M, Monasterolo, F, Bona, G, Perino, A, Rabbone, I, CAVALLO PERIN, Paolo, Cerutti, Franco, and Trovati, Mariella

Subjects
Adult, Male, medicine.medical_specialty, Pediatrics, Time Factors, Adolescent, Endocrinology, Diabetes and Metabolism, Prevalence, Young Adult, Diabetes mellitus, Epidemiology, Internal Medicine, medicine, Humans, Young adult, Age of Onset, Child, Demography, Type 1 diabetes, Sex Characteristics, business.industry, Incidence (epidemiology), Incidence, Age Factors, Infant, medicine.disease, Diabetes Mellitus, Type 1, El Niño, Italy, Child, Preschool, Regression Analysis, Female, Age of onset, business
Abstract

A shift towards younger age at onset of diabetes in susceptible people has been suggested as a possible explanation for the increasing temporal trend in incidence of type 1 diabetes. We aimed to test this hypothesis by assessing trends in incidence rates in the period 1984-2004 in children and young adults in Northern Italy.The study bases were: (1) children resident in the Province of Turin in the period 1984-2004 and in the remaining areas of the Piedmont Region in the period 1990-2004; and (2) young adults (15-29 years) resident in the Province of Turin in the period 1984-2003. Temporal trends in rates were analysed using Poisson regression models.A total of 1,773 incident cases were identified. Overall incidence rates/100,000 person-years in the age groups 0-14 and 15-29 years were 11.3 (95% CI 10.7-12.0) and 7.1 (95% CI 6.6-7.7), respectively, with sex differences among young adults only (incidence rate ratio [IRR] in males vs females 1.41 [95% CI 1.20-1.64]). Average annual increases in incidence rates were similar in children and young adults at 3.3% (95% CI 2.5-4.1). Compared with the period 1984-89, in 2000-2004 a 60% higher risk was found in both age 0-14 years (IRR 1.60, 95% CI 1.31-1.95) and 15-29 years (IRR 1.57, 95% CI 1.26-1.96) groups. The Poisson modelling showed no interaction between calendar period and age at onset.Incidence of type 1 diabetes in Northern Italy is increasing over time in both children and young adults, not supporting the hypothesis of a shift towards younger age as the main explanation for the increasing temporal trend in children.

Published
2009

16. Application of the exploratory analysis of data in the geographical discrimination of okra from Rio Grande do Norte and Pernambuco

Author

Panero,F. S., Vieira,M. F. P., Cruz,Â. M. F., Moura,M. F. V., and Silva,H. E. B. da

Subjects
Quimiometria, PCA, okra, HCA, Análise exploratória de dados, exploratory analysis, chemometrics, quiabo
Abstract

Foram analisadas amostras de quiabo dos municípios de Caruaru e Vitória de Santo Antão, em Pernambuco, assim como nos municípios de Ceará-Mirim, Macaíba e Extremoz no estado do Rio Grande do Norte. A aplicação de dois métodos de análise exploratória de dados: Análise de Componentes principais - PCA e Análise de Agrupamentos Hierárquicos - HCA permitiu a discriminação geográfica do quiabo proveniente dos dois estados. Samples of okra from Caruaru and Vitória of Santo Antão, in the State of Pernambuco, and Ceará-Mirim, Macaíba and Extremoz in the State of Rio Grande do Norte have been analysed. Two different methods were applied in the data treatment allowing to geographically discriminate samples from different origins: Principal Component Analysis - PCA and Hierarquical Cluster Analysis - HCA.

Published
2009

19. Optimal disclosure risk assessment

Author

Francesca Panero, Zacharie Naulet, Federico Camerlenghi, Stefano Favaro, Camerlenghi, F, Favaro, S, Naulet, Z, and Panero, F

Subjects
Statistics and Probability, Poisson abundance model, Polynomial approximation, Population, Mathematics - Statistics Theory, Sample (statistics), 02 engineering and technology, Statistics Theory (math.ST), Sampling fraction, Nonparametric inference, Poisson distribution, 01 natural sciences, Upper and lower bounds, Disclosure risk assessment, 62G05, 62C20, 010104 statistics & probability, symbols.namesake, Statistics, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, HA Statistics, 0101 mathematics, education, Categorical variable, Mathematics, Microdata sample, education.field_of_study, Estimator, 020206 networking & telecommunications, 16. Peace & justice, Minimax, Optimal minimax procedure, SECS-S/01 - STATISTICA, symbols, Statistics, Probability and Uncertainty
Abstract

Protection against disclosure is a legal and ethical obligation for agencies releasing microdata files for public use. Consider a microdata sample of size $n$ from a finite population of size $\bar{n}=n+\lambda n$, with $\lambda>0$, such that each record contains two disjoint types of information: identifying categorical information and sensitive information. Any decision about releasing data is supported by the estimation of measures of disclosure risk, which are functionals of the number of sample records with a unique combination of values of identifying variables. The most common measure is arguably the number $\tau_{1}$ of sample unique records that are population uniques. In this paper, we first study nonparametric estimation of $\tau_{1}$ under the Poisson abundance model for sample records. We introduce a class of linear estimators of $\tau_{1}$ that are simple, computationally efficient and scalable to massive datasets, and we give uniform theoretical guarantees for them. In particular, we show that they provably estimate $\tau_{1}$ all of the way up to the sampling fraction $(\lambda+1)^{-1}\propto (\log n)^{-1}$, with vanishing normalized mean-square error (NMSE) for large $n$. We then establish a lower bound for the minimax NMSE for the estimation of $\tau_{1}$, which allows us to show that: i) $(\lambda+1)^{-1}\propto (\log n)^{-1}$ is the smallest possible sampling fraction; ii) estimators' NMSE is near optimal, in the sense of matching the minimax lower bound, for large $n$. This is the main result of our paper, and it provides a precise answer to an open question about the feasibility of nonparametric estimation of $\tau_{1}$ under the Poisson abundance model and for a sampling fraction $(\lambda+1)^{-1}

Published
2021

20. Down to air. Atmosfera e pratiche terra terra in Palestina

Author

Van Aken, M, Alliegro, EV, Armiero, M, Battaglini, L, Bonato, L, Bougleux, E, Cavaglià, G, Debili, P, Genovese, D, Gentile, C, Mascadri, G, Mondo, D, Panero, F, Tondolo, M, Turroni, M, Van Aken, M, Vianello, R, Villa, M, and Zola, L

Subjects
M-DEA/01 - DISCIPLINE DEMOETNOANTROPOLOGICHE, ambiente, Territori Occupati, Antropocene, saperi locali, cambiamenti climatici
Abstract

“Terra terra” è una metafora italiana che mi ha sempre attratto per la capacità di rendere conto della condizione contadina e del lavoro agricolo: visualizza il guardare basso, le condizioni spesso dipendenti di chi lavora in agricoltura, proprio raddoppiando la presenza della terra come attore principale. Simile a down to earth in inglese, nella svalutazione del lavoro agricolo come dipendenza e ignoranza, è venuto a definire la “semplicità” del lavoro con la terra, rivalutato oggi all’interno delle questioni ambientali e dopo decenni di abbandono del lavoro agricolo, e non solo in Italia. Questa metafora porta però con sé un distanziamento, un’ “emancipazione” dalle relazioni atmosferiche e da vicoli ambientali, che invece hanno sempre costituito la base dei saperi rurali locali nell’orientare le pratiche lavorative, nei limiti e potenzialità delle risorse: un distanziamento dalle relazione dal tempo “su nell’aria” (Strauss and Orlove, 2003) che oggi è amplificato nell’immaginario comune dai cambiamenti climatici e atmosferici, dove le stagioni non propongono più regolarità e uniformità e sono alla base di un disorientamento e spaesamento, tanto dei piccoli agricoltori quanto, seppur più diniegato, della società in generale. L’ambiente cambia, tanto più a partire dalla dimensione più aleatoria, invisibile, imprevedibile dall’alto, un aspetto che lo rende oggi impensabile e perturbante. Se il rapporto con l’atmosfera è sempre stato ambivalente, oggi è centrale nel ripensare e comprendere i rapporti tra società e ambiente e pone in luce le contraddizioni dei nostri modelli “materiali” schiacciati a terra e sconnessi dal tempo atmosferico. Invertire la metafora quindi, con down to air meglio esprime la antica connessione incorporata nei saperi locali dell’intima connessione tra saperi dell’incertezza e della relazionalità con il tempo e pratiche, queste sì, tutte “terra terra” ma che si orientano guardando in alto, sentendo il vento, o la reazione degli insetti per condividere sistemi di significati sociali ed ecologici assieme. Il calendario atmosferico palestinese, sopravvissuto in racconti orali dei rifugiati ma tanto più nelle pratiche agricole di agricoltori nella West Bank, è un esempio storico di relazione culturale all’imprevedibilità e variabilità del tempo, attraverso sistemi di significato, rituali, partiche lavorative co-involte nell’ambiente atmosferico e nei suoi cambiamenti e capricci, orientati storicamente in Medio Oriente a definire i ritmi dell’aridità e della piovosità come spartiacque fondamentale.

Published
2017

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