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Article ; Online: Does ABS ensure good performance in emergency braking for less skilled motorcyclists?

Huertas-Leyva, P / Savino, G / Baldanzini, N / Pierini, M

2023 Volume 190, Page(s) 107148

Abstract: This study aims to investigate whether motorcyclists are able to use the full potential of anti-lock braking systems (ABS) in demanding braking situations that maintain the natural coupling of action and perception of emergency events, or whether instead ...

Abstract	This study aims to investigate whether motorcyclists are able to use the full potential of anti-lock braking systems (ABS) in demanding braking situations that maintain the natural coupling of action and perception of emergency events, or whether instead the lack of braking skills in riders makes ABS almost ineffective and comparable to non-ABS brakes on dry pavement. Six experienced riders performed two experimental tests. First test included 12 emergency braking trials in a realistic scenario using a mock-up of an intersection conflict with a car initiating a left turn manoeuvre across the path (LTAP) of a motorcycle approaching from the opposite direction as an unpredicted moving hazard. Second test included three trials in a planned self-timed hard braking. The speed at the onset of braking was 35-45 km/h. The braking performance was measured from the initiation of brake pressure until the full stop of the vehicle. Front wheel ABS usage was determined by the pressure in the master cylinder and wheel callipers. The testing resulted in 85 data runs with full stop braking manoeuvres. Results revealed four categories of riders classified by their front wheel ABS usage during the emergency braking tests, which included two riders who underused front wheel ABS (9.6% and 27.4% of braking time on average). The worst case resulted in a significantly longer braking distance (braking deceleration of 5.2 m/s
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Protective Devices ; Motorcycles
Language	English
Publishing date	2023-06-20
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2023.107148
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Article: Trends and Spatiotemporal Patterns of Avian Influenza Outbreaks in Italy: A Data-Driven Approach.

Branda, Francesco / Mazzoli, Sandra / Pierini, Massimo / Ciccozzi, Massimo

Infectious disease reports

2023 Volume 16, Issue 1, Page(s) 1–12

Abstract: In recent years, the unprecedented spread of the Avian Influenza Viruses (AIVs) among birds and mammals has caused devastation in animal populations, including poultry, wild birds, and some mammals, damaging farmers' livelihoods and the food trade. Given ...

Abstract	In recent years, the unprecedented spread of the Avian Influenza Viruses (AIVs) among birds and mammals has caused devastation in animal populations, including poultry, wild birds, and some mammals, damaging farmers' livelihoods and the food trade. Given the urgency of the situation, it is particularly important that scientists and the public can access research results and data as soon as possible. The main aim of this study is to present a global open-access dataset of Avian Influenza outbreaks to enable researchers and policymakers (i) to rapidly detect, and respond to animal outbreaks as the first line of defense; (ii) to conduct epidemiological and virological investigations around animal outbreaks and human infections; and (iii) to communicate the risk. We show the potential use of this dataset to the research community by analyzing the most updated information on past and current Highly Pathogenic Avian Influenza (HPAI) outbreaks in domestic poultry and wild birds over the period from October 2021 to July 2023 in Italy. In addition, we applied indices borrowed from Economics (such as Homogeneity, Specialization, and Location Index) to the wild birds dataset to show their possible usage in epidemiology.
Language	English
Publishing date	2023-12-19
Publishing country	Switzerland
Document type	Journal Article
ISSN	2036-7430
ISSN	2036-7430
DOI	10.3390/idr16010001
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Article: The challenges of open data for future epidemic preparedness: The experience of the 2022 Ebolavirus outbreak in Uganda.

Branda, Francesco / Mahal, Ahmed / Maruotti, Antonello / Pierini, Massimo / Mazzoli, Sandra

Frontiers in pharmacology

2023 Volume 14, Page(s) 1101894

Abstract: On 20 September 2022, the Ministry of Health in Uganda, together with the World Health Organization-Regional Office for Africa (WHO AFRO) confirmed an outbreak of EVD due to Sudan ebolavirus in Mubende District, after one fatal case was confirmed. Real- ... ...

Abstract	On 20 September 2022, the Ministry of Health in Uganda, together with the World Health Organization-Regional Office for Africa (WHO AFRO) confirmed an outbreak of EVD due to Sudan ebolavirus in Mubende District, after one fatal case was confirmed. Real-time information are needed to provide crucial information to understand transmissibility, risk of geographical spread, routes of transmission, risk factors of infection, and provide the basis for epidemiological modelling that can inform response and containment planning to reduce the burden of disease. We made an effort to build a centralized repository of the Ebola virus cases from verified sources, providing information on dates of symptom onset, locations (aggregated to the district level), and when available, the gender and status of hospitals, reporting bed capacity and isolation unit occupancy rate according to the severity status of the patient. The proposed data repository provides researchers and policymakers timely, complete, and easy-accessible data to monitor the most recent trends of the Ebola outbreak in Ugandan districts with informative graphical outputs. This favors a rapid global response to the disease, enabling governments to prioritize and adjust their decisions quickly and effectively in response to the rapidly evolving emergency, with a solid data basis.
Language	English
Publishing date	2023-02-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2023.1101894
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Article: Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020-March 2022.

Branda, Francesco / Abenavoli, Ludovico / Pierini, Massimo / Mazzoli, Sandra

Diseases (Basel, Switzerland)

2022 Volume 10, Issue 3

Abstract: Despite the stunning speed with which highly effective and safe vaccines have been developed, the emergence of new variants of SARS-CoV-2 causes high rates of (re)infection, a major impact on health care services, and a slowdown to the socio-economic ... ...

Abstract	Despite the stunning speed with which highly effective and safe vaccines have been developed, the emergence of new variants of SARS-CoV-2 causes high rates of (re)infection, a major impact on health care services, and a slowdown to the socio-economic system. For COVID-19, accurate and timely forecasts are therefore essential to provide the opportunity to rapidly identify risk areas affected by the pandemic, reallocate the use of health resources, design countermeasures, and increase public awareness. This paper presents the design and implementation of an approach based on autoregressive models to reliably forecast the spread of COVID-19 in Italian regions. Starting from the database of the Italian Civil Protection Department (DPC), the experimental evaluation was performed on real-world data collected from February 2020 to March 2022, focusing on Calabria, a region of Southern Italy. This evaluation shows that the proposed approach achieves a good predictive power for out-of-sample predictions within one week (R-squared > 0.9 at 1 day, R-squared > 0.7 at 7 days), although it decreases with increasing forecasted days (R-squared > 0.5 at 14 days).
Language	English
Publishing date	2022-06-30
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2720869-2
ISSN	2079-9721
ISSN	2079-9721
DOI	10.3390/diseases10030038
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Article ; Online: Monkeypox: EpiMPX Surveillance System and Open Data with a Special Focus on European and Italian Epidemic.

Branda, Francesco / Pierini, Massimo / Mazzoli, Sandra

Journal of clinical virology plus

2022 Volume 2, Issue 4, Page(s) 100114

Abstract: Background: The current out-of-Africa 2022 outbreak of Monkeypox requires a coordinated, international response through the rapid sharing of data and research results, as we have seen with COVID-19 and the previous Ebola and Zika outbreaks, which ... ...

Abstract	Background: The current out-of-Africa 2022 outbreak of Monkeypox requires a coordinated, international response through the rapid sharing of data and research results, as we have seen with COVID-19 and the previous Ebola and Zika outbreaks, which demonstrated how important real-world data are to inform public health, to create surveillance systems, to determine policy decisions and to improve clinical trials. Objectives: To support global response efforts by providing public access to real-time Monkeypox-related data for effective use of open data that could accelerate scientific knowledge and discoveries in terms of understanding, preventing, and treating the disease. In practice, to create a new surveillance system easy to consult and utilize. Study design: This work aims to build a surveillance system, namely EpiMPX, that allows researchers and policymakers to monitor the impact of Monkeypox in Europe, with a special focus on the epidemic trends in the Italian regions, based on an open-access database containing information on the laboratory confirmed Monkeypox cases reported by EU/EEA countries and updated once a week. In addition, users will be provided open-access R codes to estimate key epidemiological parameters such as the reproduction number (updating the Serial Interval distribution when new estimates will be published) and produce real-time results on their devices. Results: EpiMPX monitors the space-time distribution of cases and their characteristics, such as age, gender, symptoms, clinical status, and sexual orientation, when available. Even if it is currently too early for reliable calculation of epidemiological parameters, we estimated reproduction number Conclusions: The proposed EpiMPX surveillance system provides an overview of the European and Italian Monkeypox epidemiological situation with an open-access database to support epidemiological understanding of the origins and transmission dynamics of the disease with informative graphical outputs. These data confirmed the prevalent expression of Monkeypox within males, both in Europe and Italy. European MSM patients were affected by Monkeypox in a high percentage, confirming close sexual contact and possible sexual transmission. For the first time, Italian data on the regional distribution of cases and gender distribution were graphically evaluated. The data and research results are freely available and can be easily enriched to provide a prompt response to the scientific community and accelerate global efforts to contain the Monkeypox virus.
Language	English
Publishing date	2022-10-04
Publishing country	England
Document type	Journal Article
ISSN	2667-0380
ISSN (online)	2667-0380
DOI	10.1016/j.jcvp.2022.100114
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Article ; Online: Hepatitis of unknown origin in children: Why and how to create an open access database.

Branda, Francesco / Pierini, Massimo / Mazzoli, Sandra

Journal of clinical virology plus

2022 Volume 2, Issue 3, Page(s) 100102

Abstract: During the early stages of an epidemic, obtaining reliable data is a challenge, especially on a global scale. The COVID-19 pandemic has underlined the importance of having "open data" (i.e., data which are made accessible and available in a standardized ... ...

Abstract	During the early stages of an epidemic, obtaining reliable data is a challenge, especially on a global scale. The COVID-19 pandemic has underlined the importance of having "open data" (i.e., data which are made accessible and available in a standardized machine-readable format and under a license that allows it to be re-used and reshared) to inform health policy decisions and improve clinical trials. The main goal of our work is to provide effective, timely and comprehensive data to investigate this emerging virus, i.e., the acute hepatitis of unknown origin in children. These data can be used: 1) to conduct real-time situation analysis, and early and timely diagnosis for effective containment; 2) to facilitate coordination and collaboration between national and local governments; 3) to inform citizens on the spread of the disease in the world; and 4) to support governments in the future prevention decisions.
Language	English
Publishing date	2022-07-30
Publishing country	England
Document type	Journal Article
ISSN	2667-0380
ISSN (online)	2667-0380
DOI	10.1016/j.jcvp.2022.100102
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Article ; Online: Monkeypox: Early estimation of basic reproduction number R

Branda, Francesco / Pierini, Massimo / Mazzoli, Sandra

Journal of medical virology

2022 Volume 95, Issue 1, Page(s) e28270

Abstract: This world outbreak of Monkeypox (MPX) infections outside Africa emerged on May 2022 in Europe and spread worldwide with unique characteristics: inter-human contagion and infection in men without specific previous immunization, prevalently men-who-have- ... ...

Abstract	This world outbreak of Monkeypox (MPX) infections outside Africa emerged on May 2022 in Europe and spread worldwide with unique characteristics: inter-human contagion and infection in men without specific previous immunization, prevalently men-who-have-sex-with-men (MSM). Phylogenetic analysis confirmed a unique clade, the West African clade, subclade IIb. On August 30, WHO stated 48 895 laboratory confirmed cases from 101 different countries, of which 28 050 were in Europe. It has therefore become important to define new epidemiological indices. Starting from our new surveillance system EpiMPX open data, we defined an early R
MeSH term(s)	Male ; Humans ; Mpox (monkeypox)/epidemiology ; Homosexuality, Male ; Basic Reproduction Number ; Phylogeny ; Sexual and Gender Minorities ; Europe/epidemiology ; Disease Outbreaks
Language	English
Publishing date	2022-11-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	752392-0
ISSN	1096-9071 ; 0146-6615
ISSN (online)	1096-9071
ISSN	0146-6615
DOI	10.1002/jmv.28270
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Article ; Online: Kinetic and mechanism study of the spontaneous, solvent- and base-catalyzed degradation of the precursor of the β-nitro alcohol metaraminol by combining HPLC/electronic circular dichroism/theoretical methods.

Cantatore, Chiara / Visconti, Paolo / Pierini, Marco / Cirilli, Roberto

Journal of pharmaceutical and biomedical analysis

2022 Volume 220, Page(s) 114972

Abstract: Chiral β-nitro alcohols are key intermediates in the synthesis of a wide range of active pharmaceutical ingredients. Despite their massive use for pharmaceutical applications, in-depth kinetics studies concerning their stability during formation and ... ...

Abstract	Chiral β-nitro alcohols are key intermediates in the synthesis of a wide range of active pharmaceutical ingredients. Despite their massive use for pharmaceutical applications, in-depth kinetics studies concerning their stability during formation and transformation reactions are scarce in the literature. In this study, the (1R,2S)-1-(m-benzyloxy)-2-nitro-1-propanol) (BNA), the precursor of the metaraminol, was selected as a molecular model and the retro-Henry reaction was explored by a multidisciplinary approach involving HPLC, electronic circular dichroism and theoretical methods. The enantio-, diastereo-, and chemo-selective high-performance liquid chromatographic method for determining the purity of β-nitro alcohol during its formation and degradation is based on the use of an amylose-derived chiral stationary phase under normal-phase eluent conditions. The influence of various factors (e.g. temperature, type of reaction solvent, basic and acid catalysts) on the degradation kinetics has been investigated. The retro-Henry reaction was found to be the major degradation of BNA, under spontaneous, solvent- and base-catalyzed conditions, resulting in the formation of its precursors 3-benzyloxybenzaldehyde and nitroethane.
MeSH term(s)	Amylose/chemistry ; Catalysis ; Chromatography, High Pressure Liquid/methods ; Circular Dichroism ; Electronics ; Ethanol/chemistry ; Kinetics ; Metaraminol ; Pharmaceutical Preparations ; Solvents ; Stereoisomerism
Chemical Substances	Pharmaceutical Preparations ; Solvents ; Ethanol (3K9958V90M) ; Metaraminol (818U2PZ2EH) ; Amylose (9005-82-7)
Language	English
Publishing date	2022-07-27
Publishing country	England
Document type	Journal Article
ZDB-ID	604917-5
ISSN	1873-264X ; 0731-7085
ISSN (online)	1873-264X
ISSN	0731-7085
DOI	10.1016/j.jpba.2022.114972
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Article ; Online: Analysis-Specific Fast Simulation at the LHC with Deep Learning.

Chen, C / Cerri, O / Nguyen, T Q / Vlimant, J R / Pierini, M

Computing and software for big science

2021 Volume 5, Issue 1, Page(s) 15

Abstract: We present a fast-simulation application based on a deep neural network, designed to create large analysis-specific datasets. Taking as an example the generation ... ...

Abstract	We present a fast-simulation application based on a deep neural network, designed to create large analysis-specific datasets. Taking as an example the generation of
Language	English
Publishing date	2021-06-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2908677-2
ISSN	2510-2044 ; 2510-2036
ISSN (online)	2510-2044
ISSN	2510-2036
DOI	10.1007/s41781-021-00060-4
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Book ; Online: Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier

Grönroos, Sonja / Pierini, Maurizio / Chernyavskaya, Nadezda

2023

Abstract: More than a thousand 8" silicon sensors will be visually inspected to look for anomalies on their surface during the quality control preceding assembly into the High-Granularity Calorimeter for the CMS experiment at CERN. A deep learning-based algorithm ... ...

Abstract	More than a thousand 8" silicon sensors will be visually inspected to look for anomalies on their surface during the quality control preceding assembly into the High-Granularity Calorimeter for the CMS experiment at CERN. A deep learning-based algorithm that pre-selects potentially anomalous images of the sensor surface in real time has been developed to automate the visual inspection. The anomaly detection is done by an ensemble of independent deep convolutional neural networks: an autoencoder and a classifier. The performance is evaluated on images acquired in production. The pre-selection reduces the number of images requiring human inspection by 85%, with recall of 97%. Data gathered in production can be used for continuous learning to improve the accuracy incrementally.
Keywords	Physics - Instrumentation and Detectors ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning
Subject code	006
Publishing date	2023-03-09
Publishing country	us
Document type	Book ; Online
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