scispace - formally typeset
Search or ask a question
Institution

Polytechnic University of Turin

EducationTurin, Piemonte, Italy
About: Polytechnic University of Turin is a education organization based out in Turin, Piemonte, Italy. It is known for research contribution in the topics: Finite element method & Computer science. The organization has 11553 authors who have published 41395 publications receiving 789320 citations. The organization is also known as: POLITO & Politecnico di Torino.


Papers
More filters
Journal ArticleDOI
TL;DR: The electric current activated/assisted sintering (ECAS) is an ever growing class of versatile techniques for sinterding particulate materials as discussed by the authors. But despite the tremendous advances over the last two decades in ECASed materials and products, there is a lack of comprehensive reviews on ECAS apparatuses and methods.

383 citations

Journal ArticleDOI
TL;DR: The analysis shows the potential for an early epidemic peak occurring in October/November in the Northern hemisphere, likely before large-scale vaccination campaigns could be carried out, and suggests that the planning of additional mitigation policies such as systematic antiviral treatments might be the key to delay the activity peak in order to restore the effectiveness of the vaccination programs.
Abstract: On 11 June the World Health Organization officially raised the phase of pandemic alert (with regard to the new H1N1 influenza strain) to level 6. As of 19 July, 137,232 cases of the H1N1 influenza strain have been officially confirmed in 142 different countries, and the pandemic unfolding in the Southern hemisphere is now under scrutiny to gain insights about the next winter wave in the Northern hemisphere. A major challenge is pre-empted by the need to estimate the transmission potential of the virus and to assess its dependence on seasonality aspects in order to be able to use numerical models capable of projecting the spatiotemporal pattern of the pandemic. In the present work, we use a global structured metapopulation model integrating mobility and transportation data worldwide. The model considers data on 3,362 subpopulations in 220 different countries and individual mobility across them. The model generates stochastic realizations of the epidemic evolution worldwide considering 6 billion individuals, from which we can gather information such as prevalence, morbidity, number of secondary cases and number and date of imported cases for each subpopulation, all with a time resolution of 1 day. In order to estimate the transmission potential and the relevant model parameters we used the data on the chronology of the 2009 novel influenza A(H1N1). The method is based on the maximum likelihood analysis of the arrival time distribution generated by the model in 12 countries seeded by Mexico by using 1 million computationally simulated epidemics. An extended chronology including 93 countries worldwide seeded before 18 June was used to ascertain the seasonality effects. We found the best estimate R 0 = 1.75 (95% confidence interval (CI) 1.64 to 1.88) for the basic reproductive number. Correlation analysis allows the selection of the most probable seasonal behavior based on the observed pattern, leading to the identification of plausible scenarios for the future unfolding of the pandemic and the estimate of pandemic activity peaks in the different hemispheres. We provide estimates for the number of hospitalizations and the attack rate for the next wave as well as an extensive sensitivity analysis on the disease parameter values. We also studied the effect of systematic therapeutic use of antiviral drugs on the epidemic timeline. The analysis shows the potential for an early epidemic peak occurring in October/November in the Northern hemisphere, likely before large-scale vaccination campaigns could be carried out. The baseline results refer to a worst-case scenario in which additional mitigation policies are not considered. We suggest that the planning of additional mitigation policies such as systematic antiviral treatments might be the key to delay the activity peak in order to restore the effectiveness of the vaccination programs.

382 citations

Journal ArticleDOI
TL;DR: The aim of this tutorial is to highlight a novel chapter of control theory, dealing with applications to social systems, to the attention of the broad research community.

382 citations

Journal ArticleDOI
TL;DR: A snapshot of the abrupt changes seen on campus traffic due to COVID-19 is presented, and how the Internet has proved robust to successfully cope with challenges while maintaining the university operations is testified.

382 citations

Journal ArticleDOI
TL;DR: In this paper, three mesoporous manganese oxide catalysts (Mn 2 O 3, Mn 3 O 4 and Mn x O y ) have been prepared, by means of the solution combustion synthesis, and tested for the total oxidation of volatile organic compounds (VOCs; ethylene, propylene, toluene and their mixture).
Abstract: Three mesoporous manganese oxide catalysts (Mn 2 O 3 , Mn 3 O 4 and Mn x O y ) have been prepared, by means of the solution combustion synthesis, and tested for the total oxidation of volatile organic compounds (VOCs; ethylene, propylene, toluene and their mixture). The best results, in terms of the total oxidation of VOCs, were achieved with the Mn 3 O 4 catalyst, which showed the highest amount of electrophilic oxygen on the surface (O α -species). The most active powder catalyst was then deposited on a cordierite-type monolith through a novel direct synthesis and tested for the total oxidation of the VOCs mixture. The Mn 3 O 4 -based monolith exhibited high activity towards the total oxidation of VOCs, which is comparable to that obtained with powdered Mn 3 O 4 . The monolithic catalyst showed excellent catalytic activity for the total combustion of the mixture of VOCs (conversion to CO 2 = 99.2% ± 0.5) over a time-on-stream of 10 h at 310 °C and no deactivation occurred during this time span.

382 citations


Authors

Showing all 11854 results

NameH-indexPapersCitations
Rodney S. Ruoff164666194902
Silvia Bordiga10749841413
Sergio Ferrara10572644507
Enrico Rossi10360641255
Stefano Passerini10277139119
James Barber10264242397
Markus J. Buehler9560933054
Dario Farina9483232786
Gabriel G. Katul9150634088
M. De Laurentis8427554727
Giuseppe Caire8282540344
Christophe Fraser7626429250
Erasmo Carrera7582923981
Andrea Califano7530531348
Massimo Inguscio7442721507
Network Information
Related Institutions (5)
Royal Institute of Technology
68.4K papers, 1.9M citations

95% related

Delft University of Technology
94.4K papers, 2.7M citations

94% related

École Polytechnique Fédérale de Lausanne
98.2K papers, 4.3M citations

93% related

Georgia Institute of Technology
119K papers, 4.6M citations

93% related

Karlsruhe Institute of Technology
82.1K papers, 2.1M citations

92% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023210
2022487
20212,789
20202,969
20192,779
20182,509