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557 results on '"Naccarato, P."'

1. The arithmetic of critical values I: equicritical quartic polynomials

Author

Naccarato, Francesco

Subjects
Mathematics - Number Theory
Abstract

A polynomial $f$ of degree $d$ and coefficients in an algebraically closed field $k$ defines a morphism $f:\mathbb{P}^1_k\longrightarrow\mathbb{P}^1_k$ which, if char$(k)\nmid d$, is unramified outside a finite set of points in the image: the critical values of $f$. In this work we establish a rigorous framework for the study of their arithmetic, which we carry out for $d=4$ and $k=\overline{\mathbb{Q}}$, uncovering a connection to the arithmetic of elliptic curves. Recent progress in the theory of Weyl sums has sparked some interest in finding pairs of polynomials having the same critical values for "nontrivial" reasons: building on our analysis, we provide a complete classification of such pairs in the case of quartics over number fields.

Published
2024

2. Changes in boiling controlled by molar concentration-dependent diffusion of surfactants

Author

Mata, Mario R., Može, Matic, Hadžić, Armin, Lee, Giseop, Naccarato, Blake, Berk, Isaac, Golobič, Iztok, and Cho, H. Jeremy

Subjects
Physics - Fluid Dynamics, Condensed Matter - Materials Science, Physics - Applied Physics, Physics - Chemical Physics
Abstract

Boiling is a prevalent phase-change process that plays a vital role in facilitating efficient heat transfer from a heating surface. While this heat transfer mechanism is generally effective, a rapid increase in surface temperature can lead to hydrodynamic instabilities, resulting in a boiling crisis. Previous studies have shown that surfactants often improve boiling performance and change the boiling crisis behavior. Conventional wisdom in this field attributes that these changes in boiling behavior are tied to the critical micelle concentration (CMC) of the particular surfactant. However, our work reveals that these changes in boiling behavior are independent of the CMC for three nonionic surfactants across a wide range of molar concentrations. In addition, visual snapshots of the bubbling behavior indicate changes in bubble formation, such as bubble size and nucleation site density, influenced by the molar concentration-dependent diffusion timescale of surfactants. Hence, these findings offer compelling evidence that boiling behavior, encompassing both boiling performance and boiling crisis, is governed by the dynamic adsorption of surfactants rather than dictated by the CMC. This becomes evident when quantifying the heat transfer coefficient (HTC) and critical heat flux (CHF) using the logarithm of molar concentration, as predicted by theory. Building upon these findings, we propose insights for controlling when CHF modification occurs in specific scenarios involving any surfactants. These insights hold significant potential for optimizing heat transfer processes and leveraging surfactants in energy-related applications to maximize boiling efficiency., Comment: 21 pages, 7 figures, 2 appendices

Published
2024
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5. PD-L1 Classification of Weakly-Labeled Whole Slide Images of Breast Cancer

Author

Cignoni, Giacomo, Scatena, Cristian, Frascarelli, Chiara, Fusco, Nicola, Naccarato, Antonio Giuseppe, Fanelli, Giuseppe Nicoló, and Sîrbu, Alina

Subjects
Computer Science - Computational Engineering, Finance, and Science, Computer Science - Computer Vision and Pattern Recognition, J.3, I.4.9
Abstract

Specific and effective breast cancer therapy relies on the accurate quantification of PD-L1 positivity in tumors, which appears in the form of brown stainings in high resolution whole slide images (WSIs). However, the retrieval and extensive labeling of PD-L1 stained WSIs is a time-consuming and challenging task for pathologists, resulting in low reproducibility, especially for borderline images. This study aims to develop and compare models able to classify PD-L1 positivity of breast cancer samples based on WSI analysis, relying only on WSI-level labels. The task consists of two phases: identifying regions of interest (ROI) and classifying tumors as PD-L1 positive or negative. For the latter, two model categories were developed, with different feature extraction methodologies. The first encodes images based on the colour distance from a base color. The second uses a convolutional autoencoder to obtain embeddings of WSI tiles, and aggregates them into a WSI-level embedding. For both model types, features are fed into downstream ML classifiers. Two datasets from different clinical centers were used in two different training configurations: (1) training on one dataset and testing on the other; (2) combining the datasets. We also tested the performance with or without human preprocessing to remove brown artefacts Colour distance based models achieve the best performances on testing configuration (1) with artefact removal, while autoencoder-based models are superior in the remaining cases, which are prone to greater data variability.

Published
2024

11. Educators' Perceptions of Professional Growth Plans in the Context of Professional Learning Communities

Author

Cyndi Caniglia, Kathryn Picanco, Kristen Arnold, and Sharon Naccarato

Abstract

Professional Growth Plans (PGPs), a model of professional development for educators, were completed in the context of Professional Learning Communities (PLCs) as part of a grant from a state Professional Educator Standards Board. Participants were in the Pacific Northwest of the United States and represented different educator roles in two urban elementary schools. The PGP process was introduced in PLCs and focused on the implementation of High Leverage Practices (HLPs) for inclusive classrooms (McLeskey et al., 2019). In a collaborative effort with university facilitators, educators engaged in tenets of Participatory Action Research (PAR) through the enactment of the PGP process to implement and reflect on outcomes related to their use of HLPs. Educators selected PGP goals focused on areas of instructional growth and improvement of student performance. PAR was enacted in the context of educators' individual instructional settings through the implementation of PGPs. The purpose of the grant was to familiarize and support educators in the PGP process. The purpose of the study was to identify educators' perceived benefits and challenges with the implementation of PGPs within the context of a collaborative PLC. Educators indicated that collaboration with educators across roles, including university partners, and the structure of the PGP process within the context of a PLC positively influenced their professional growth and student outcomes.

Published
2023

17. SnP$_2$S$_6$: A Promising Infrared Nonlinear Optical Crystal with Strong Non-Resonant Second Harmonic Generation and Phase-matchability

Author

He, Jingyang, Lee, Seng Huat, Naccarato, Francesco, Brunin, Guillaume, Zu, Rui, Wang, Yuanxi, Miao, Leixin, Wang, Huaiyu, Alem, Nasim, Hautier, Geoffroy, Rignanese, Gian-Marco, Mao, Zhiqiang, and Gopalan, Venkatraman

Subjects
Physics - Optics
Abstract

High-power infrared laser systems with broadband tunability are of great importance due to their wide range of applications in spectroscopy and free-space communications. These systems require nonlinear optical (NLO) crystals for wavelength up/down conversion using sum/difference frequency generation, respectively. NLO crystals need to satisfy many competing criteria, including large nonlinear optical susceptibility, large laser induced damage threshold (LIDT), wide transparency range and phase-matchability. Here, we report bulk single crystals of SnP_2S_6 with a large non-resonant SHG coefficient of d33= 53 pm/V at 1550nm and a large LIDT of 350 GW/cm^2 for femtosecond laser pulses. It also exhibits a broad transparency range from 0.54 {\mu}m to 8.5{\mu}m (bandgap of ~2.3 eV) and can be both Type I and Type II phase-matched. The complete linear and SHG tensors are measured as well as predicted by first principles calculations, and they are in excellent agreement. A proximate double-resonance condition in the electronic band structure for both the fundamental and the SHG light is shown to enhance the non-resonant SHG response. Therefore, SnP2S6 is an outstanding candidate for infrared laser applications.

Published
2022

19. Counting rational points on elliptic curves with a rational 2-torsion point

Author

Naccarato, Francesco

Subjects
Mathematics - Number Theory
Abstract

Let $E/\mathbb{Q}$ be an elliptic curve over the rational numbers. It is known, by the work of Bombieri and Zannier, that if $E$ has full rational $2$-torsion, the number $N_E(B)$ of rational points with Weil height bounded by $B$ is $\exp\left(O\left(\frac{\log B}{\sqrt{\log\log B}}\right)\right)$. In this paper we exploit the method of descent via $2$-isogeny to extend this result to elliptic curves with just one nontrivial rational $2$-torsion point. Moreover, we make use of a result of Petsche to derive the stronger upper bound $N_{E}(B) = \exp\left(O\left(\frac{\log B}{\log\log B}\right)\right)$ for these curves and to remove a deep transcendence theory ingredient from the proof.

Published
2021

24. Searching for Materials with High Refractive Index and Wide Band Gap: A First-Principles High-Throughput Study

Author

Naccarato, Francesco, Ricci, Francesco, Suntivich, Jin, Hautier, Geoffroy, Wirtz, Ludger, and Rignanese, Gian-Marco

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics, Physics - Optics
Abstract

Materials combining both a high refractive index and a wide band gap are of great interest for optoelectronic and sensor applications. However, these two properties are typically described by an inverse correlation with high refractive index appearing in small gap materials and vice-versa. Here, we conduct a first-principles high-throughput study on more than 4000 semiconductors (with a special focus on oxides). Our data confirm the general inverse trend between refractive index and band gap but interesting outliers are also identified. The data are then analyzed through a simple model involving two main descriptors: the average optical gap and the effective frequency. The former can be determined directly from the electronic structure of the compounds, but the latter cannot. This calls for further analysis in order to obtain a predictive model. Nonetheless, it turns out that the negative effect of a large band gap on the refractive index can counterbalanced in two ways: (i) by limiting the difference between the direct band gap and the average optical gap which can be realized by a narrow distribution in energy of the optical transitions and (ii) by increasing the effective frequency which can be achieved through either a high number of transitions from the top of the valence band to the bottom of the conduction or a high average probability for these transitions. Focusing on oxides, we use our data to investigate how the chemistry influences this inverse relationship and rationalize why certain classes of materials would perform better. Our findings can be used to search for new compounds in many optical applications both in the linear and non-linear regime (waveguides, optical modulators, laser, frequency converter, etc.)., Comment: The manuscript is made of 10 pages with 6 figures and 1 table. At the end of the main text, there is an appendix with 2 figures. Supplemental material includes 7 figures and 6 tables. In the db.csv file there are the materials properties we computed in this work

Published
2018
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27. The impact of COVID-19 on myocardial infarctions, strokes and out-of-hospital cardiopulmonary arrests: an observational retrospective study on time-sensitive disorders in the Friuli Venezia Giulia region (Italy)

Author

Pegani, Carlo, Buttignon, Giovanni, Tullio, Annarita, Naccarato, Marcello, Manganotti, Paolo, Rakar, Serena, Fabris, Enrico, Nadalin, Federico, Mione, Vincenzo, Gigli, Gian Luigi, Lorenzut, Simone, Spedicato, Leonardo, Passadore, Paolo, Pavan, Daniela, Lutman, Cristina, Andrian, Manila, Borelli, Massimo, Novello, Stefano, Belfiore, Rita, Daneluzzi, Chiara, Sinagra, Gianfranco, and Peratoner, Alberto

Published
2022
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28. Stroke management during the coronavirus disease 2019 (COVID-19) pandemic: experience from three regions of the north east of Italy (Veneto, Friuli-Venezia-Giulia, Trentino-Alto-Adige)

Author

Manganotti, Paolo, Naccarato, Marcello, Scali, Ilario, Cappellari, Manuel, Bonetti, Bruno, Burlina, Alessandro, Turinese, Emanuele, Bogo, Sabrina, Teatini, Francesco, Franchini, Enrica, Caneve, Giorgio, Ruzza, Giampietro, Gaudenzi, Anna, Bombardi, Roberto, Bozzato, Giulio, Padoan, Roberta, Gentile, Carolina, Rana, Michele, Turazzini, Michelangelo, Alessandra, Danese, Brigo, Francesco, Nardone, Raffaele, Quatrale, Rocco, Menegazzo, Elisabetta, Masato, Maela, Novello, Stefano, Passadore, Paolo, Baldi, Antonio, Valentinis, Luca, Baracchini, Claudio, Pieroni, Alessio, Basile, Anna Maria, Semplicini, Claudio, Piffer, Silvio, Giometto, Bruno, Tonello, Simone, Bonifatti, Domenico Marco, Lorenzut, Simone, Merlino, Giovanni, Valente, Maria Rosaria, Paladin, Francesco, Tonon, Agnese, de Luca, Cristina, Perini, Francesco, Centonze, Sandro, and Bovi, Paolo

Published
2021
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35. Association of XRCC3 rs1799794 polymorphism with survival of glioblastoma multiforme patients treated with combined radio-chemotherapy

Author

Pasqualetti, Francesco, Gonnelli, Alessandra, Orlandi, Paola, Palladino, Eleonora, Giannini, Noemi, Gadducci, Giovanni, Mattioni, Roberto, Montrone, Sabrina, Calistri, Elisa, Mazzanti, Chiara Maria, Franceschi, Sara, Ortenzi, Valerio, Scatena, Cristian, Zavaglia, Katia, Fanelli, Giuseppe Nicolo, Morganti, Riccardo, Santonocito, Orazio, Bocci, Guido, Naccarato, Giuseppe Antonio, and Paiar, Fabiola

Published
2021
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37. Stereotactic body radiotherapy for oligometastatic castration sensitive prostate cancer using 1.5 T MRI-Linac: preliminary data on feasibility and acute patient-reported outcomes

Author

Mazzola, Rosario, Cuccia, Francesco, Figlia, Vanessa, Rigo, Michele, Nicosia, Luca, Giaj-Levra, Niccolò, Ricchetti, Francesco, Vitale, Claudio, Mantoan, Beatrice, Di Paola, Gioacchino, De Simone, Antonio, Gurrera, Davide, Sicignano, Gianluisa, Naccarato, Stefania, Ruggieri, Ruggero, and Alongi, Filippo

Published
2021
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39. Optimizing machine learning models for classification of stroke patients with epileptiform EEG pattern: the impact of dataset balancing techniques.

Author

Iscra, Katerina, Biscontin, Alessandro, Miladinovic, Aleksandar, Bonini, Andrea, Furlanis, Giovanni, Prandin, Gabriele, Malesani, Michele, Naccarato, Marcello, Manganotti, Paolo, Accardo, Agostino, and Ajčević, Miloš

Subjects
ARTIFICIAL neural networks, SUPPORT vector machines, EPILEPSY, STROKE, STROKE patients
Abstract

Epileptiform electroencephalogram (EEG) patterns are commonly observed in stroke patients and can significantly impact clinical management and patient outcomes. Therefore, the classification of the stroke patients in order to identify the subjects with high probability of epileptiform EEG patterns may improve the stroke management. In recent years, there has been a notable increase in interest and utilization of machine learning, especially in the domain of classification tasks. Nevertheless, the presence of imbalanced datasets presents hurdles for machine learning algorithms, resulting in skewed predictions toward dominant classes and diminished accuracy, especially for underrepresented ones. Hence, the study aims to evaluate the effects of dataset balancing methods on the classification efficacy of machine learning models for classification of stroke patients with epileptiform EEG patterns by conducting a comparative analysis between models trained on imbalanced and balanced datasets. Four different sampling techniques were employed: an oversampling technique, SMOTENC; an undersampling technique, NearMiss; and two techniques that combine over- and undersampling methods, SMOTEToken and SMOTEENN. The features selection was made using the ReliefF scoring method and for model construction, only features that presented a contribution value greater than 0.01 were utilized. Five different machine learning models were considered in the study: classification tree, logistic regression, naïve Bayes, artificial neural network and support vector machine. The produced models were trained on the original and resampled training set and subsequently the models' performances were evaluated on the test set. The results showed that SMOTENC was the most effective among the considered dataset balancing techniques, showing superior classification performance compared to other methods and the original dataset. Models utilizing SMOTENC exhibited significant improvements in AUC (0.76 vs 0.67) and specificity values (0.73 vs 0.43) while maintaining comparable accuracy (0.72 vs 0.74) to those trained on the original dataset, respectively. Furthermore, it has been noted that different sampling techniques result in different selection of the most predictive features. In conclusion, our study highlights the crucial role of utilizing dataset balancing methods to improve the classification performances of predictive models in case of highly unbalanced datasets such as case of stratification of stroke patients with epileptiform EEG patterns. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Acute revascularization treatments for ischemic stroke in the Stroke Units of Triveneto, northeast Italy: time to treatment and functional outcomes

Author

Cappellari, Manuel, Bonetti, Bruno, Forlivesi, Stefano, Sajeva, Giulia, Naccarato, Marcello, Caruso, Paola, Lorenzut, Simone, Merlino, Giovanni, Viaro, Federica, Pieroni, Alessio, Giometto, Bruno, Bignamini, Valeria, Perini, Francesco, De Boni, Antonella, Morra, Michele, Critelli, Adriana, Tamborino, Carmine, Tonello, Simone, Guidoni, Silvia Vittoria, L’Erario, Roberto, Russo, Monia, Burlina, Alessandro, Turinese, Emanuele, Passadore, Paolo, Zanet, Luca, Polo, Alberto, Turazzini, Michelangelo, Basile, Anna Maria, Atzori, Matteo, Marini, Bruno, Bruno, Martina, Carella, Simona, Campagnaro, Alessandro, Baldi, Antonio, Corazza, Elisa, Zanette, Giampietro, Idone, Domenico, Gaudenzi, Anna, Bombardi, Roberto, Cadaldini, Morena, Lanzafame, Salvatore, Ferracci, Franco, Zambito, Sandro, Ruzza, Giampietro, Simonetto, Marco, Menegazzo, Elisabetta, Masato, Maela, Padoan, Roberta, Bozzato, Giulio, Paladin, Francesco, Tonon, Agnese, and Bovi, Paolo

Published
2021
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47. Predicting Alumni Giving at a Public Comprehensive Regional University: Predictive Multivariate Causal Models for Annual Giving, Significant Cumulative Giving, Major Giving, and Planned Giving

Author

Naccarato, Shawn L.

Abstract

A historic period of state divestment in public higher education, exacerbated by the "Great Recession" and attendant financial repercussions, has significantly altered public higher education financing. The most significant impact has been cost shift from the state to students via increasing tuition rates. These changes threaten student access, quality public education, and the American Dream. Vitality of American public higher education will depend upon institutional capacity to increase revenue sources other than tuition. Increasing alumni donation could be a key strategy in increasing alternate revenue. A preponderance of existing literature on alumni donor characteristics has focused on traditional private non-profit institutions and larger research focused public institutions with limited focus on regional comprehensive public institutions. The purpose of this study was expansion of the understanding of alumni donative behavior with specific focus on a medium-sized comprehensive regional public university. The author first sought to develop a strong theoretical alumni-giving decision model and second the development and testing of four multivariate causal models useful in predicting the four primary gift types: (a) annual gift model, (b) significant cumulative giving model, (c) major giving model, and, (d) planned giving model.Utilizing discriminant function analysis (DFA), all predictive models were built and tested. All predictive models demonstrated at least 97% predictive accuracy with regard to non-givers in each giving type with mixed results in predicting givers in each category. The significant cumulative giving and major giving models showed relatively high predictive accuracy of givers, 58.7% and 54% respectively, while predictive accuracy of givers in the annual giving and planned giving models fell to 25% or less. The exceptionally strong predictive accuracy with regard to non-givers coupled with other statistically significant findings provide optimism for further refinement of the models and additional research. Based on this study, the researcher articulates three primary theories and implications for practice: (a) central importance of alumni experience and the role of alumni relations and programming; (b) the interconnectedness of giving types, need for holistic approach, and the foundational role of annual giving; and (c) the need for improved data-based decision making in the field. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2019

50. Role of the pharmacist caring for people at risk of or living with HIV in Canada

Author

Tkachuk, Stacey, Ready, Erin, Chan, Shanna, Hawkes, Jennifer, Janzen Cheney, Tracy, Kapler, Jeff, Kreutzwiser, Denise, Akagi, Linda, Coombs, Michael, Giguere, Pierre, Hughes, Christine, Kelly, Deborah, Livingston, Sheri, Martel, Dominic, Naccarato, Mark, Nhean, Salin, Pozniak, Carley, Ramsey, Tasha, Robinson, Linda, Smith, Jonathan, Swidrovich, Jaris, Symes, Jodi, Yoong, Deborah, and Tseng, Alice

Published
2024
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