المؤلفون: Doronzo, Domenico, Delle Donne, Dario, Bellucci Sessa, Eliana, Convertito, Vincenzo, de' Michieli Vitturi, Mattia, de Vita, Sandro, Di Traglia, Federico, Nappi, Rosa, Nardone, Lucia, Nave, Rosella, Sansivero, Fabio, Di Vito, Mauro Antonio

المساهمون: Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OV, Napoli, Italia, Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Pisa, Pisa, Italia

مصطلحات موضوعية: Ischia island, landslide

الوصف: Lahars, landslides and debris flows are rapid natural phenomena that can heavily impact on and modify the environment, not only that from which they are triggered but also the one in which they propagate or leave deposits. In particular, lahars can reach significant runout distances from source areas (e.g., several km) and this can mainly depend, among other factors, on the morphology experienced by such propagation. There are cases in the recent history of natural occurrences in which lahars impacted catastrophically on rural and urban settings, such as for example at Nevado del Ruiz volcano (Colombia) in 1985 causing the death of thousands of people living around there. A more recent event occurred on November 26, 2022 at Ischia island (Italy), which is an active volcano particularly subjected to the recurrence of these phenomena. In this case, the emplacement of some lahars caused the death of a few tens of people and the damaging of tens of building, besides the direct impact on local agriculture and tourism. In the nearby Neapolitan volcanic area, several other lahar events occurred in the historical past, not only during but also after or well after explosive eruptions, as the evidence that these phenomena are still to be considered as complex and often unpredictable extreme natural events, also exacerbated by the climate changes, but also that they have some recurrence that cannot be neglected. Such kind of recurrence is mainly related to the local weather, which can even affect the intrinsic behavior of the flows that detach from the source areas and invade the territory. On the other hand, this is not a strictly statistical issue, as there are instrumental measurements that support the fact that heavy rains can exacerbate a landscape already prone to sliding, avalanching, and other catastrophic phenomena. For this, the November 26, 2022 Ischia case study was chosen with the goal of reconstructing the physical features that led to the lahar generation and invasion, which is something that might occur in ...

العلاقة: EGU General Assembly 2024; http://hdl.handle.net/2122/17178Test

الإتاحة: https://doi.org/10.5194/egusphere-egu24-10028Test
http://hdl.handle.net/2122/17178Test

المؤلفون: Paparatto G., Chinelli A., Musco A., Ubbiali M., Meli P., Fallace P., Nardone P., Pierannunzio D., Donati S., Ciardullo S., Martinelli D., Tavoschi L.

المساهمون: Paparatto, G., Chinelli, A., Musco, A., Ubbiali, M., Meli, P., Fallace, P., Nardone, P., Pierannunzio, D., Donati, S., Ciardullo, S., Martinelli, D., Tavoschi, L.

مصطلحات موضوعية: Comprehensive sexuality education, evaluation, school

الوصف: Existing evidence demonstrated the effectiveness of Comprehensive Sexuality Education (CSE) in providing adolescents with rightful and appropriate information to improve knowledge, attitudes, and behaviours about sexuality. However, there is no consensus on the optimal methodological approach to evaluate CSE interventions. Here we propose a protocol to assess the outcome of a standardized evaluation strategy on adolescents’ knowledge about sexuality. This research is part of a national Italian project on school-based CSE (EduForIST), funded by the Italian Ministry of health.

وصف الملف: ELETTRONICO

العلاقة: ispartofbook:Abstract book of the 26th Congress of the World Association For Sexual Health, 2-5 November 2023, Antalya (Türkiye); 26th Congress of the World Association For Sexual Health; volume:Abstract book of the 26th Congress of the World Association For Sexual Health; firstpage:267; lastpage:267; numberofpages:1; https://hdl.handle.net/11562/1121331Test; https://www.was2023.org/files/downloads/WAS2023-Abstract-Book.pdfTest

الإتاحة: https://hdl.handle.net/11562/1121331Test
https://www.was2023.org/files/downloads/WAS2023-Abstract-Book.pdfTest

المؤلفون: Italiano, Cristina, Saker, Assia, Laganà, Massimo, Thomas, Minju, Hary, Benjamin, Nardone, Steve, Meynet, Nicolas, Pino, Lidia, Ramirez Santos, Alvaro, Vita, Antonio

الوصف: The present work deals with the design, manufacturing (by Laser Powder Bed Fusion), characterization, and catalytic activation (by a washcoating method) of Periodical Cellular Structures (POCS) 3D-printed in a cylindrical shape (Ø = 1cm, Length = 1.5 cm), in different materials (Al-, Cu-, Ni-alloys) and with various structural parameters (porosity, density, cell type and strut dimensions). The general aim is to intensify the ammonia synthesis throughout the development of structured catalysts with geometries that allow the integration with ammonia selective membranes in a membrane-based reactor to increase productivity at low temperatures (250-300°C) and pressure (20-25bar).

العلاقة: https://zenodo.org/communities/ambher-projectTest; https://zenodo.org/record/8362361Test; https://doi.org/10.5281/zenodo.8362361Test; oai:zenodo.org:8362361

الإتاحة: https://doi.org/10.5281/zenodo.8362361Test
https://doi.org/10.5281/zenodo.8362360Test
https://zenodo.org/record/8362361Test

المؤلفون: Morabito, Simona, Nardone, Lucia, Petrosino, Simona, Cusano, Paola

المساهمون: Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OV, Napoli, Italia

مصطلحات موضوعية: seismic noise, seismological temporal pattern, Mefite d'Ansanto, CO2 emission site

الوصف: Mefite d’Ansanto (Italy) is the largest non-volcanic CO2 emission field on the Earth. The isotopic signature of the CO2 testifies a deep origin of the gases emitted at this site, whose source is probably the mantle wedge beneath the Apennines along the Tyrrhenian side (Chiodini et al., 2010). Mefite is located between the Sannio and the Irpinia seismogenic regions, that are considered among the most active areas of the southern Apennines. The emission site falls at the northern tip of the Irpinia fault system that is associated with the destructive MS = 6.9, 1980 Irpinia earthquake. The gas leakage from this zone is linked to active faulting that characterized the area and determined large historical earthquakes A temporary acquisition survey close to the Mefite emission field was carried out between 8 June and 28 September 2020 by using a seismic array, named Array MEfite (AME), composed of seven short-period stations. We have analyzed the characteristics of the recorded background seismic noise, e.g., spectral properties, energy temporal pattern (RMS) and polarization (Montalbetti et al., 1970), and estimated site effects (Nakamura, 1989; http://www.geopsy.orgTest/). The seismological temporal patterns have been compared with the meteorological parameters, such as temperature and rainfall, to find possible relationships with exogenous factors. We found a well-defined spatial pattern for the spectral components above 5 Hz, which appear clearly linked to the emission field dynamics. On the other hand, the spectral components below 5 Hz result from the overlapping of multiple sources, of both exogenous, such as anthropogenic and meteorological factors, and endogenous nature. Application of the Independent Component Analysis (ICA) technique (Hyvärinen et al., 2001) contributed to discriminate between natural and anthropogenic sources. ; Published ; Vienna, Austria ; 3T. Fisica dei terremoti e Sorgente Sismica

العلاقة: EGU General Assembly 2023; Chiodini, G., D. Granieri, R. Avino, S. Caliro, A. Costa, C. Minopoli, and G. Vilardo (2010). Non‐volcanic CO2 Earth degassing: Case of Mefite d’Ansanto (southern Apennines), Italy, Geophys. Res. Lett. 37, L11303, doi:10.1029/2010GL042858. Hyvärinen, A., Karhunen, J. & Oja, E. (2001). Independent Component Analysis. Wiley, New York, Montalbetti, J. R., Kanasevich, E. R. (1970): Enhancement of teleseismic body phase with a polarization filter. Geophys. J. Int. 21 (2), 119–129. Nakamura, Y. (1989). A method for dynamic characteristics estimation of subsurface using microtremor on the ground surface, Railway Technical Research Institute, Quarterly Reports, 30 (1), 25-33.; http://hdl.handle.net/2122/16318Test

الإتاحة: https://doi.org/10.5194/egusphere-egu23-12806Test
https://doi.org/10.1029/2010GL042858Test
http://hdl.handle.net/2122/16318Test

المؤلفون: Marco Borzì, Alfio, Minio, Vittorio, Cannavò, Flavio, Cavallaro, Angelo, D'Amico, Sebastiano, De Plaen, Raphael, Gauci, Adam, Lecocq, Thomas, Nardone, Gabriele, Orasi, Arianna, Picone, Marco, Cannata, Andrea, EGU General Assembly

مصطلحات موضوعية: Microseisms, Severe storms -- Mediterranean region, Environmental monitoring -- Mediterranean region, Weather -- Environmental aspects, Storms -- Mediterranean region, Remote sensing

الوصف: Microseism is the most continuous and ubiquitous seismic signal on the Earth and is caused by the interaction between the atmosphere, the hydrosphere and the Solid Earth. In literature, there are several studies that deal with the relationship between microseism and cyclonic activity considering in particular hurricanes, tropical cyclones and typhoons. However, the relationships between microseism and the small-scale tropical cyclones that occur in the Mediterranean Sea, called Medicanes, have never been analysed. For this reason, we considered the Medicane Apollo, which developed in the Ionian Sea and impacted the eastern part of Sicily during the period 25th October to 5th November 2021 causing heavy rainfall (> 400 mm/48h), strong wind gusts (104 km/h) and violent sea waves (significant wave height > 3.5 m). Furthermore, the heavy rainfall induced by the presence of Apollo, caused damage to infrastructure and agriculture forcing the Sicilian regional government to declare a state of emergency for 32 municipalities (in the provinces of Catania, Messina, Siracusa and Ragusa) that were mostly affected by the Medicane Apollo. ; peer-reviewed

العلاقة: Borzì, A. M., Minio, V., Cannavò, F., Cavallaro, A., D'Amico, S., De Plaen, R.,.Cannata, A. (2023, Apr). Microseism and Medicane Apollo: a new approach to investigate the Mediterranean extreme weather events (No. EGU23-3193), Austria. 10-15.; https://www.um.edu.mt/library/oar/handle/123456789/108567Test

الإتاحة: https://doi.org/10.5194/egusphere-egu23-3193Test
https://www.um.edu.mt/library/oar/handle/123456789/108567Test

المؤلفون: Stramaccioni, Claudia, Bianco, Andrea, Devoti, Saverio, Macaluso, Domenico, Mazzotta, Giuseppe, Orasi, Arianna, Parlagreco, Luca, Picone, Marco, Nardone, Gabriele, Ferla, Maurizio

المساهمون: Stramaccioni, Claudia, Bianco, Andrea, Devoti, Saverio, Macaluso, Domenico, Mazzotta, Giuseppe, Orasi, Arianna, Parlagreco, Luca, Picone, Marco, Nardone, Gabriele, Ferla, Maurizio

مصطلحات موضوعية: tide, meteorological residual, negative sea level, sea monitoring, RMN

الوصف: The aim of this paper is to discuss the case of an extreme negative sea level phenomenon that occurred along Sicily Island’s coasts (Italy). Sea level time series associated to six stations that are part of the Italian tide gauge network have been analysed. By deriving the tidal residual and by evaluating meteorological parameters’ trends, it was possible to give an explanation to this phenomenon.

العلاقة: info:eu-repo/semantics/altIdentifier/isbn/978-1-6654-9942-2; info:eu-repo/semantics/altIdentifier/wos/WOS:000894276700002; ispartofbook:2022 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea); 2022 IEEE International Workshop on Metrology for the Sea; firstpage:7; lastpage:11; numberofpages:5; https://hdl.handle.net/11573/1663025Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85143724473

الإتاحة: https://doi.org/10.1109/MetroSea55331.2022.9950938Test
https://hdl.handle.net/11573/1663025Test

المؤلفون: Claudia, Tucci, Nardone, Luca, Orlandi, Gretha, Bonis, Francesca De, Maccarrone, Claudia, Fambrini, Massimiliano, Sorbi, Flavia

المصدر: Video and Cinema Session

الإتاحة: https://doi.org/10.1136/ijgc-2024-esgo.83Test

المؤلفون: De Donato, Lorenzo, Flammini, Francesco, Marrone, Stefano, Nardone, Roberto, Vittorini, Valeria

مصطلحات موضوعية: Artificial Intelligence, Machine Learning, Safety, Explainability, Autonomous Trains

الوصف: In this paper, we present some of the results achieved during the ongoing RAILS (Roadmaps for Artificial Intelligence Integration in the Rail Sector) research project, funded by the European Union Shift2Rail Joint Undertaking, and specifically in Work Package 2, addressing AI for autonomous and cooperative driving in future smart railways. We will provide a brief state-of-the-art and opportunities for future research, focusing on the trustworthiness of intelligent train control, also based on the analysis of related transportation sectors. As for other safety-critical sectors, the use of AI for autonomous driving in railways represents a challenge. This happens when an appropriate “safety envelope” cannot be guaranteed, such as when the Automatic Train Protection (ATP) is missing or not working properly (e.g., in limited supervision operating modes), or in cases when it is specifically used to improve safety (e.g., when employed for on-track obstacle detection). In many situations, however, AI can be advantageously adopted to optimize several parameters when supporting Automatic Train Operation (ATO), while the ATP supervises safety. Furthermore, in limited or no supervision by the ATP, AI can be effectively used to support train drivers in respecting signals and keeping safe headways, i.e., as an advanced driving assistance system, in analogy with the latest developments in the automotive sector. Fundings and Disclaimer: This research has received funding from the Shift2Rail Joint Undertaking (JU) under grant agreement No 881782 RAILS (Roadmaps for Artificial Intelligence (A.I.) integration in the raiL Sector). The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Shift2Rail JU members other than the Union. The information and views set out in this document are those of the author(s) and do not necessarily reflect the official opinion of Shift2Rail Joint Undertaking. The JU does not guarantee the accuracy of the data included in this document. Neither ...

العلاقة: info:eu-repo/grantAgreement/EC/H2020/881782/; https://zenodo.org/communities/railsTest; https://zenodo.org/record/8327293Test; https://doi.org/10.5281/zenodo.8327293Test; oai:zenodo.org:8327293

الإتاحة: https://doi.org/10.5281/zenodo.8327293Test
https://doi.org/10.5281/zenodo.8327292Test
https://zenodo.org/record/8327293Test

المؤلفون: Iacucci, M, Cannatelli, R, Parigi, TL, Buda, A, Labarile, N, Nardone, OM, Tontini, GE, Rimondi, A, Bazarova, A, Bhandari, P, Bisschops, R, De Hertogh, G, Del Amor, R, Ferraz, JG, Goetz, M, Gui, X, Hayee, B, Kiesslich, R, Lazarev, M, Naranjo, V, Panaccione, R, Parra-Blanco, A, Pastorelli, L, Rath, T, Røyset, ES, Vieth, M, Villanacci, V, Zardo, D, Ghosh, S, Grisan, E.

الوصف: Background Endoscopic and histologic activity are important therapeutic targets in ulcerative colitis (UC). The Paddington International Virtual ChromoendoScopy ScOre (VCE-PICaSSO)1 demonstrated that enhanced visualisation of subtle mucosal and vascular inflammatory changes correlated strongly with histology. However, without adequate training, the subjective evaluation of white light (WL) and VCE endoscopic scores varies between observers. We aimed to develop an artificial intelligence (AI) system for objective assessment of endoscopic disease activity and predict histology related to both white light and VCE videos. Methods 469 endoscopy videos (48512 frames) from 235 patients representative of all grades of inflammation, from our prospective PICaSSO multicentre study1 were used to develop a convolutional neural network (CNN). 316 videos were divided into training (254) and validation (62) sets. 153 additional videos (78 patients) were used as test cohort. The videos were edited to separate clips with WL and with VCE, and assessed using Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and PICaSSO, respectively. The classification stage of a pre-trained ResNet50 CNN classifier was trained to predict the healing or active inflammation on video frames. One network was trained to predict endoscopic remission (ER) as UCEIS≤1 from WL frames, and a second network was trained to predict PICaSSO≤3 from VCE. Histological remission (HR) was defined as Robarts Histological Index (RHI) ≤3 with no neutrophils in lamina propria or epithelium. Results In the validation cohort, our system predicted ER (UCEIS ≤1) in WL videos with 82% sensitivity (Se), 94% specificity (Sp) and an area under the ROC curve (AUROC) of 0.92. For the detection of remission in VCE videos (PICaSSO ≤3) Se was 74%, Sp 95%, and AUROC 0.95. In the testing cohort of independent videos, the diagnostic performance for both cut offs of ER remained similar. Our system also had an excellent diagnostic performance for the prediction of HR in the ...

وصف الملف: application/vnd.openxmlformats-officedocument.wordprocessingml.document

العلاقة: https://openresearch.lsbu.ac.uk/download/3630925c252b593196fbff7c78ceded49b1fb7825e5d28fae655d43092abb596/1670746/PICaSSO%20AI%20Abstract-final.docxTest; https://doi.org/10.1093/ecco-jcc/jjab232.015Test; Iacucci, M, Cannatelli, R, Parigi, TL, Buda, A, Labarile, N, Nardone, OM, Tontini, GE, Rimondi, A, Bazarova, A, Bhandari, P, Bisschops, R, De Hertogh, G, Del Amor, R, Ferraz, JG, Goetz, M, Gui, X, Hayee, B, Kiesslich, R, Lazarev, M, Naranjo, V, Panaccione, R, Parra-Blanco, A, Pastorelli, L, Rath, T, Røyset, ES, Vieth, M, Villanacci, V, Zardo, D, Ghosh, S and Grisan, E. (2022). OP16 The first virtual chromoendoscopy artificial intelligence system to detect endoscopic and histologic remission in Ulcerative Colitis. 17th Congress of ECCO - European Crohn’s and Colitis Organisation. 16 - 19 Feb 2022 Oxford University Press (OUP). https://doi.org/10.1093/ecco-jcc/jjab232.015Test

الإتاحة: https://doi.org/10.1093/ecco-jcc/jjab232.015Test
https://openresearch.lsbu.ac.uk/item/8z59qTest
https://openresearch.lsbu.ac.uk/download/3630925c252b593196fbff7c78ceded49b1fb7825e5d28fae655d43092abb596/1670746/PICaSSO%20AI%20Abstract-final.docxTest

المؤلفون: Iacucci, M., Cannatelli, R., Parigi, T.L., Buda, A., Labarile, N., Nardone, O.M., Tontini, G.E., Rimondi, A., Bazarova, A., Bhandari, P., Bisschops, R., De Hertogh, G., del Amor, R., Ferraz, J.G, Goetz, M., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Naranjo, V., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Røyset, E.S, Vieth, M., Villanacci, V., Zardo, D., Ghosh, S., Grisan, E.

الوصف: Aims We aimed to develop an artificial intelligence (AI) system to assess endoscopic remission (ER) and histologic remission (HR) of ulcerative colitis (UC) in both white light (WL, using Ulcerative Colitis Endoscopic Index of Severity [UCEIS]) and virtual chromoendoscopy (VCE, using Paddington International Virtual ChromoendoScopy ScOre [PICaSSO]). Methods A convolutional neural network (CNN) was developed based on 559 endoscopy videos, from 302 UC patients prospectively included in the PICaSSO multicentre study. The videos were divided in training (254), validation (62), and testing (243), and comprised 67280 frames in total. The CNN was trained to predict both ER (defined as UCEIS≤1 in WL and as PICaSSO≤3 in VCE) and HR (defined as Robarts Histological Index ≤ 3 with no neutrophils in lamina propria or epithelium) in video clips. Results In the validation cohort, our system predicted ER in WL videos with 82% sensitivity, 94% specificity and an area under the ROC curve (AUROC) of 0.92. In VCE, sensitivity was 74%, specificity 95%, and AUROC 0.95. In the testing cohort, the diagnostic performance remained similar. The diagnostic performance for the prediction of HR in the validation set had sensitivity, specificity, and accuracy of 92%, 83%, and 85%, respectively, using VCE; and 83%, 87%, and 86% respectively, with WL. In the testing set, these metrics declined modestly while remaining good. Of note, the algorithm’s prediction of histology was similar with VCE and WL videos. Conclusions Our AI system accurately recognizes ER in videos and predicts HR equally well.

وصف الملف: application/vnd.openxmlformats-officedocument.wordprocessingml.document

العلاقة: https://openresearch.lsbu.ac.uk/download/c787d51cce330f87665f948a8ec500c8e9ae99a7409c8a5dfce302b6dc3ddde3/869899/A%20VIRTUAL%20CHROMOENDOSCOPY%20ARTIFICIAL%20INTELLIGENCE%20SYSTEM%20TO%20DETECT%20ENDOSCOPIC%20AND%20HISTOLOGIC%20REMISSION%20IN%20ULCERATIVE%20COLITIS.docxTest; https://doi.org/10.1055/s-0042-1744593Test; Iacucci, M., Cannatelli, R., Parigi, T.L., Buda, A., Labarile, N., Nardone, O.M., Tontini, G.E., Rimondi, A., Bazarova, A., Bhandari, P., Bisschops, R., De Hertogh, G., del Amor, R., Ferraz, J.G, Goetz, M., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Naranjo, V., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Røyset, E.S, Vieth, M., Villanacci, V., Zardo, D., Ghosh, S. and Grisan, E. (2022). A Virtual Chromoendoscopy Artificial Intelligence System To Detect Endoscopic And Histologic Remission In Ulcerative Colitis. ESGE Days 2022. 28 Apr 2022 Georg Thieme Verlag KG. https://doi.org/10.1055/s-0042-1744593Test

الإتاحة: https://doi.org/10.1055/s-0042-1744593Test
https://openresearch.lsbu.ac.uk/item/8zy86Test
https://openresearch.lsbu.ac.uk/download/c787d51cce330f87665f948a8ec500c8e9ae99a7409c8a5dfce302b6dc3ddde3/869899/A%20VIRTUAL%20CHROMOENDOSCOPY%20ARTIFICIAL%20INTELLIGENCE%20SYSTEM%20TO%20DETECT%20ENDOSCOPIC%20AND%20HISTOLOGIC%20REMISSION%20IN%20ULCERATIVE%20COLITIS.docxTest