2023
Conference article
Open Access
Self-assess momentary mood in mobile devices: a case study with mature female participants
Senette C., Buzzi M. C., Paratore M. T.
Starting from the assumption that mood has a central role in domain-specific persuasion systems for well-being, the main goal of this study was to investigate the feasibility and acceptability of single-input methods to assess momentary mood as a medium for further interventions in health-related mobile apps destined for mature women. To this aim, we designed a very simple android App providing four user interfaces, each one showing one interactive widget to self-assess mood. Two widgets report a hint about the momentary mood they represent; the last two do not have the hints but were previously refined through questionnaires administered to 63 women (age 45-65) in order to reduce their expressive ambiguity. Next, fifteen women (age 45-65 years) were recruited to use the app for 15 days. Participants were polled about their mood four times a day and data were saved in a remote database. Moreover, users were asked to fill out a preliminary questionnaire, at the first access to the app, and a feedback questionnaire at the end of the testing period. Results appear to prove the feasibility and acceptability of this approach to self-assess momentary mood in the target population and provides some potential input methods to be used in this context.Source: ICCT 2023, Jaipur, India, 9-12/10/2023
Senette C., Buzzi M. C., Paratore M. T.
Starting from the assumption that mood has a central role in domain-specific persuasion systems for well-being, the main goal of this study was to investigate the feasibility and acceptability of single-input methods to assess momentary mood as a medium for further interventions in health-related mobile apps destined for mature women. To this aim, we designed a very simple android App providing four user interfaces, each one showing one interactive widget to self-assess mood. Two widgets report a hint about the momentary mood they represent; the last two do not have the hints but were previously refined through questionnaires administered to 63 women (age 45-65) in order to reduce their expressive ambiguity. Next, fifteen women (age 45-65 years) were recruited to use the app for 15 days. Participants were polled about their mood four times a day and data were saved in a remote database. Moreover, users were asked to fill out a preliminary questionnaire, at the first access to the app, and a feedback questionnaire at the end of the testing period. Results appear to prove the feasibility and acceptability of this approach to self-assess momentary mood in the target population and provides some potential input methods to be used in this context.Source: ICCT 2023, Jaipur, India, 9-12/10/2023
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2023
Conference article
Open Access
GAM Forest explanation
Lucchese C., Orlando S., Perego R., Veneri A.
Most accurate machine learning models unfortunately produce black-box predictions, for which it is impossible to grasp the internal logic that leads to a specific decision. Unfolding the logic of such black-box models is of increasing importance, especially when they are used in sensitive decision-making processes. In thisworkwe focus on forests of decision trees, which may include hundreds to thousands of decision trees to produce accurate predictions. Such complexity raises the need of developing explanations for the predictions generated by large forests.We propose a post hoc explanation method of large forests, named GAM-based Explanation of Forests (GEF), which builds a Generalized Additive Model (GAM) able to explain, both locally and globally, the impact on the predictions of a limited set of features and feature interactions.We evaluate GEF over both synthetic and real-world datasets and show that GEF can create a GAM model with high fidelity by analyzing the given forest only and without using any further information, not even the initial training dataset.Source: EDBT 2022 - 26th International Conference on Extending Database Technology, pp. 171–182, Ioannina, Greece, 28-31/03/2023
DOI: 10.48786/edbt.2023.14
Metrics:
Lucchese C., Orlando S., Perego R., Veneri A.
Most accurate machine learning models unfortunately produce black-box predictions, for which it is impossible to grasp the internal logic that leads to a specific decision. Unfolding the logic of such black-box models is of increasing importance, especially when they are used in sensitive decision-making processes. In thisworkwe focus on forests of decision trees, which may include hundreds to thousands of decision trees to produce accurate predictions. Such complexity raises the need of developing explanations for the predictions generated by large forests.We propose a post hoc explanation method of large forests, named GAM-based Explanation of Forests (GEF), which builds a Generalized Additive Model (GAM) able to explain, both locally and globally, the impact on the predictions of a limited set of features and feature interactions.We evaluate GEF over both synthetic and real-world datasets and show that GEF can create a GAM model with high fidelity by analyzing the given forest only and without using any further information, not even the initial training dataset.Source: EDBT 2022 - 26th International Conference on Extending Database Technology, pp. 171–182, Ioannina, Greece, 28-31/03/2023
DOI: 10.48786/edbt.2023.14
Metrics:
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openproceedings.org | CNR ExploRA
2023
Conference article
Closed Access
Haptic-based cognitive mapping to support shopping malls exploration
Paratore M. T., Leporini B.
This paper describes a study, which is currently underway, whose aim is to investigate how the haptic channel can be effectively exploited by visually impaired users in a mobile app for the preliminary exploration of an indoor environment, namely a shopping mall. Our goal was to use haptics to convey knowledge of how the points of interest (POIs) are distributed within the physical space, and at the same time provide information about the function of each POI, so that users can get a perception of how functional areas are distributed in the environment "at a glance". Shopping malls are typical indoor environments in which orientation aids are highly appreciated by customers, and many different functional areas persist. We identified seven typical categories of POIs which can be encountered in a mall, and then associated a different vibration pattern each. In order to validate our approach, we designed and developed a prototype for preliminary testing, based on the Android platform. The prototype was periodically debugged with the aid of two visually impaired experienced users, who gave us precious advice throughout the development process. We will describe how this app was conceived, the issues emerged during its development and the positive outcomes produced by a very early testing stage. Finally, we will show that the proposed approach is promising and is worthy of further investigation.Source: EAI GOODTECHS 2022 - 8th EAI International Conference on Smart Objects and Technologies for Social Good, pp. 54–62, Online event, 16-18/11/2022
DOI: 10.1007/978-3-031-28813-5_4
Metrics:
Paratore M. T., Leporini B.
This paper describes a study, which is currently underway, whose aim is to investigate how the haptic channel can be effectively exploited by visually impaired users in a mobile app for the preliminary exploration of an indoor environment, namely a shopping mall. Our goal was to use haptics to convey knowledge of how the points of interest (POIs) are distributed within the physical space, and at the same time provide information about the function of each POI, so that users can get a perception of how functional areas are distributed in the environment "at a glance". Shopping malls are typical indoor environments in which orientation aids are highly appreciated by customers, and many different functional areas persist. We identified seven typical categories of POIs which can be encountered in a mall, and then associated a different vibration pattern each. In order to validate our approach, we designed and developed a prototype for preliminary testing, based on the Android platform. The prototype was periodically debugged with the aid of two visually impaired experienced users, who gave us precious advice throughout the development process. We will describe how this app was conceived, the issues emerged during its development and the positive outcomes produced by a very early testing stage. Finally, we will show that the proposed approach is promising and is worthy of further investigation.Source: EAI GOODTECHS 2022 - 8th EAI International Conference on Smart Objects and Technologies for Social Good, pp. 54–62, Online event, 16-18/11/2022
DOI: 10.1007/978-3-031-28813-5_4
Metrics:
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2023
Journal article
Closed Access
Shallow portion of an active geothermal system revealed by multidisciplinary studies: the case of Le Biancane (Larderello, Italy)
Granieri D., Mazzarini F., Cerminara M., Calusi B., Scozzari A., Menichini M., Lelli M.
The natural park of Le Biancane is located in the southern sector of the Larderello-Travale geothermal field (LTGF). It extends over an approximately 100,000 m2 area where the impermeable caprock is locally absent and deep fluids may directly reach the surface. Through a multidisciplinary approach including measurements of soil CO2 flux (total output of 11.5 t day-1), soil temperature (average 34.4 °C), stable isotope and chemical data on fluids from fumaroles (dominated by a mixture of geothermal gases and air or gases from air-saturated meteoric water), and structural analysis of the formation outcropping, we found that anomalous CO2 emissions are positively correlated with shallow temperature anomalies. These are in restricted locations adjacent to vents and fumaroles, where a network of well-connected fractures (preferentially NW-SE and NE-SW orientated and with steep dips) drains efficiently allowing upward migration of the deep fluids and the energy toward the surface.Source: Geothermics 108 (2023). doi:10.1016/j.geothermics.2022.102616
DOI: 10.1016/j.geothermics.2022.102616
Metrics:
Granieri D., Mazzarini F., Cerminara M., Calusi B., Scozzari A., Menichini M., Lelli M.
The natural park of Le Biancane is located in the southern sector of the Larderello-Travale geothermal field (LTGF). It extends over an approximately 100,000 m2 area where the impermeable caprock is locally absent and deep fluids may directly reach the surface. Through a multidisciplinary approach including measurements of soil CO2 flux (total output of 11.5 t day-1), soil temperature (average 34.4 °C), stable isotope and chemical data on fluids from fumaroles (dominated by a mixture of geothermal gases and air or gases from air-saturated meteoric water), and structural analysis of the formation outcropping, we found that anomalous CO2 emissions are positively correlated with shallow temperature anomalies. These are in restricted locations adjacent to vents and fumaroles, where a network of well-connected fractures (preferentially NW-SE and NE-SW orientated and with steep dips) drains efficiently allowing upward migration of the deep fluids and the energy toward the surface.Source: Geothermics 108 (2023). doi:10.1016/j.geothermics.2022.102616
DOI: 10.1016/j.geothermics.2022.102616
Metrics:
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CNR ExploRA | www.sciencedirect.com
2023
Journal article
Open Access
Brain metastases from NSCLC treated with stereotactic radiotherapy: prediction mismatch between two different radiomic platforms
Carloni G., Garibaldi C., Marvaso G., Volpe S., Zaffaroni M., Pepa M., Isaksson L. J., Colombo F., Durante S., Lo Presti G., Raimondi S., Spaggiari L. J., De Marinis F., Piperno G., Vigorito S., Gandini S., Cremonesi M., Positano V., Jereczek-Fossa B. A.
Background and purpose. Radiomics enables the mining of quantitative features from medical images. The influence of the radiomic feature extraction software on the final performance of models is still a poorly understood topic. This study aimed to investigate the ability of radiomic features extracted by two different radiomic platforms to predict clinical outcomes in patients treated with radiosurgery for brain metastases from non-small cell lung cancer. We developed models integrating pre-treatment magnetic resonance imaging (MRI)-derived radiomic features and clinical data. Materials and methods. Pre-radiotherapy gadolinium enhanced axial T1-weighted MRI scans were used. MRI images were re-sampled, intensity-shifted, and histogram-matched before radiomic extraction by means of two different platforms (PyRadiomics and SOPHiA Radiomics). We adopted LASSO Cox regression models for multivariable analyses by creating radiomic, clinical, and combined models using three survival clinical endpoints (local control, distant progression, and overall survival). The statistical analysis was repeated 50 times with different random seeds and the median concordance index was used as performance metric of the models. Results. We analysed 276 metastases from 148 patients. The use of the two platforms resulted in differences in both the quality and the number of extractable features. That led to mismatches in terms of end-to-end performance, statistical significance of radiomic scores, and clinical covariates found significant in combined models. Conclusion. This study shed new light on how extracting radiomic features from the same images using two different platforms could yield several discrepancies. That may lead to acute consequences on drawing conclusions, comparing results across the literature, and translating radiomics into clinical practice.Source: Radiotherapy and oncology 178 (2023). doi:10.1016/j.radonc.2022.11.013
DOI: 10.1016/j.radonc.2022.11.013
Metrics:
Carloni G., Garibaldi C., Marvaso G., Volpe S., Zaffaroni M., Pepa M., Isaksson L. J., Colombo F., Durante S., Lo Presti G., Raimondi S., Spaggiari L. J., De Marinis F., Piperno G., Vigorito S., Gandini S., Cremonesi M., Positano V., Jereczek-Fossa B. A.
Background and purpose. Radiomics enables the mining of quantitative features from medical images. The influence of the radiomic feature extraction software on the final performance of models is still a poorly understood topic. This study aimed to investigate the ability of radiomic features extracted by two different radiomic platforms to predict clinical outcomes in patients treated with radiosurgery for brain metastases from non-small cell lung cancer. We developed models integrating pre-treatment magnetic resonance imaging (MRI)-derived radiomic features and clinical data. Materials and methods. Pre-radiotherapy gadolinium enhanced axial T1-weighted MRI scans were used. MRI images were re-sampled, intensity-shifted, and histogram-matched before radiomic extraction by means of two different platforms (PyRadiomics and SOPHiA Radiomics). We adopted LASSO Cox regression models for multivariable analyses by creating radiomic, clinical, and combined models using three survival clinical endpoints (local control, distant progression, and overall survival). The statistical analysis was repeated 50 times with different random seeds and the median concordance index was used as performance metric of the models. Results. We analysed 276 metastases from 148 patients. The use of the two platforms resulted in differences in both the quality and the number of extractable features. That led to mismatches in terms of end-to-end performance, statistical significance of radiomic scores, and clinical covariates found significant in combined models. Conclusion. This study shed new light on how extracting radiomic features from the same images using two different platforms could yield several discrepancies. That may lead to acute consequences on drawing conclusions, comparing results across the literature, and translating radiomics into clinical practice.Source: Radiotherapy and oncology 178 (2023). doi:10.1016/j.radonc.2022.11.013
DOI: 10.1016/j.radonc.2022.11.013
Metrics:
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ISTI Repository | CNR ExploRA | www.sciencedirect.com
2023
Journal article
Open Access
Privacy by design in systems for assisted living, personalized care and well-being: a stakeholder analysis
Carboni A., Russo D., Moroni D., Barsocchi P.
The concept of privacy-by-design within a system for assisted living, personalized care and well-being is crucial to protect users from misuse of the data collected about their health. Especially if the information is collected through audio-video devices, the question is even more delicate due to the nature of this data. In fact, in addition to guaranteeing a high level of privacy, it is necessary to reassure end-users about the correct use of these streams. The evolution of data analysis techniques began to take In review on an important role and increasingly defined characteristics in recent years. In this article, with reference to European projects in the AHA/AAL domain, we will see a differentiation of the concept of privacy-by-design according to different dimensions (Technical, Contextual, Business) and to the Stakeholders involved. The analysis is intended to cover technical aspects, legislative and policies-related aspects also regarding the point of view of the municipalities and aspects related to the acceptance and, therefore, to the perception of the safety of these technologies by the final end-users.Source: Frontiers in digital health (2023). doi:10.3389/fdgth.2022.934609
DOI: 10.3389/fdgth.2022.934609
Project(s): PlatformUptake.eu
Metrics:
Carboni A., Russo D., Moroni D., Barsocchi P.
The concept of privacy-by-design within a system for assisted living, personalized care and well-being is crucial to protect users from misuse of the data collected about their health. Especially if the information is collected through audio-video devices, the question is even more delicate due to the nature of this data. In fact, in addition to guaranteeing a high level of privacy, it is necessary to reassure end-users about the correct use of these streams. The evolution of data analysis techniques began to take In review on an important role and increasingly defined characteristics in recent years. In this article, with reference to European projects in the AHA/AAL domain, we will see a differentiation of the concept of privacy-by-design according to different dimensions (Technical, Contextual, Business) and to the Stakeholders involved. The analysis is intended to cover technical aspects, legislative and policies-related aspects also regarding the point of view of the municipalities and aspects related to the acceptance and, therefore, to the perception of the safety of these technologies by the final end-users.Source: Frontiers in digital health (2023). doi:10.3389/fdgth.2022.934609
DOI: 10.3389/fdgth.2022.934609
Project(s): PlatformUptake.eu
Metrics:
See at:
ISTI Repository | CNR ExploRA | www.frontiersin.org
2023
Journal article
Open Access
A self-training automatic infant-cry detector
Coro G., Bardelli S., Cuttano A., Scaramuzzo R. T., Ciantelli M.
Infant cry is one of the first distinctive and informative life signals observed after birth. Neonatologists and automatic assistive systems can analyse infant cry to early-detect pathologies. These analyses extensively use reference expert-curated databases containing annotated infant-cry audio samples. However, these databases are not publicly accessible because of their sensitive data. Moreover, the recorded data can under-represent specific phenomena or the operational conditions required by other medical teams. Additionally, building these databases requires significant investments that few hospitals can afford. This paper describes an open-source workflow for infant-cry detection, which identifies audio segments containing high-quality infant-cry samples with no other overlapping audio events (e.g. machine noise or adult speech). It requires minimal training because it trains an LSTM-with-self-attention model on infant-cry samples automatically detected from the recorded audio through cluster analysis and HMM classification. The audio signal processing uses energy and intonation acoustic features from 100-ms segments to improve spectral robustness to noise. The workflow annotates the input audio with intervals containing infant-cry samples suited for populating a database for neonatological and early diagnosis studies. On 16 min of hospital phone-audio recordings, it reached sufficient infant-cry detection accuracy in 3 neonatal care environments (nursery--69%, sub-intensive--82%, intensive--77%) involving 20 infants subject to heterogeneous cry stimuli, and had substantial agreement with an expert's annotation. Our workflow is a cost-effective solution, particularly suited for a sub-intensive care environment, scalable to monitor from one to many infants. It allows a hospital to build and populate an extensive high-quality infant-cry database with a minimal investment.Source: Neural computing & applications (Print) (2023). doi:10.1007/s00521-022-08129-w
DOI: 10.1007/s00521-022-08129-w
Project(s): EcoScope
Metrics:
Coro G., Bardelli S., Cuttano A., Scaramuzzo R. T., Ciantelli M.
Infant cry is one of the first distinctive and informative life signals observed after birth. Neonatologists and automatic assistive systems can analyse infant cry to early-detect pathologies. These analyses extensively use reference expert-curated databases containing annotated infant-cry audio samples. However, these databases are not publicly accessible because of their sensitive data. Moreover, the recorded data can under-represent specific phenomena or the operational conditions required by other medical teams. Additionally, building these databases requires significant investments that few hospitals can afford. This paper describes an open-source workflow for infant-cry detection, which identifies audio segments containing high-quality infant-cry samples with no other overlapping audio events (e.g. machine noise or adult speech). It requires minimal training because it trains an LSTM-with-self-attention model on infant-cry samples automatically detected from the recorded audio through cluster analysis and HMM classification. The audio signal processing uses energy and intonation acoustic features from 100-ms segments to improve spectral robustness to noise. The workflow annotates the input audio with intervals containing infant-cry samples suited for populating a database for neonatological and early diagnosis studies. On 16 min of hospital phone-audio recordings, it reached sufficient infant-cry detection accuracy in 3 neonatal care environments (nursery--69%, sub-intensive--82%, intensive--77%) involving 20 infants subject to heterogeneous cry stimuli, and had substantial agreement with an expert's annotation. Our workflow is a cost-effective solution, particularly suited for a sub-intensive care environment, scalable to monitor from one to many infants. It allows a hospital to build and populate an extensive high-quality infant-cry database with a minimal investment.Source: Neural computing & applications (Print) (2023). doi:10.1007/s00521-022-08129-w
DOI: 10.1007/s00521-022-08129-w
Project(s): EcoScope
Metrics:
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link.springer.com | ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
Global-scale parameters for ecological models
Coro G., Bove P., Kesner-Reyes K.
This paper presents a collection of environmental, geophysical, and other marine-related data for marine ecological models and ecological-niche models. It consists of 2132 raster data for 58 distinct parameters at regional and global scales in the ESRI-GRID ASCII format. Most data originally belonged to open data owned by the authors of this article but residing on heterogeneous repositories with different formats and resolutions. Other data were specifically created for the present publication. The collection includes 565 data with global scale range; 154 at 0.5° resolution and 411 at 0.1° resolution; 196 data with annual temporal aggregation over ~10 key years between 1950 and 2100; 369 data with monthly aggregation at 0.1° resolution from January 2017 to ~May 2021 continuously. Data were also cut out on 8 European marine regions. The collection also includes forecasts for different future scenarios such as the Representative Concentration Pathways 2.6 (63 data), 4.5 (162 data), and 8.5 (162 data), and the A2 scenario of the Intergovernmental Panel on Climate Change (180 data).Source: Scientific data 10 (2023). doi:10.1038/s41597-022-01904-3
DOI: 10.1038/s41597-022-01904-3
Project(s): EcoScope
Metrics:
Coro G., Bove P., Kesner-Reyes K.
This paper presents a collection of environmental, geophysical, and other marine-related data for marine ecological models and ecological-niche models. It consists of 2132 raster data for 58 distinct parameters at regional and global scales in the ESRI-GRID ASCII format. Most data originally belonged to open data owned by the authors of this article but residing on heterogeneous repositories with different formats and resolutions. Other data were specifically created for the present publication. The collection includes 565 data with global scale range; 154 at 0.5° resolution and 411 at 0.1° resolution; 196 data with annual temporal aggregation over ~10 key years between 1950 and 2100; 369 data with monthly aggregation at 0.1° resolution from January 2017 to ~May 2021 continuously. Data were also cut out on 8 European marine regions. The collection also includes forecasts for different future scenarios such as the Representative Concentration Pathways 2.6 (63 data), 4.5 (162 data), and 8.5 (162 data), and the A2 scenario of the Intergovernmental Panel on Climate Change (180 data).Source: Scientific data 10 (2023). doi:10.1038/s41597-022-01904-3
DOI: 10.1038/s41597-022-01904-3
Project(s): EcoScope
Metrics:
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ISTI Repository | CNR ExploRA | www.nature.com
2023
Conference article
Open Access
Towards adaptation of humanoid robot behaviour in serious game scenarios using reinforcement learning
Zedda E., Manca M., Paternò F.
Repetitive cognitive training can be seen as tedious by older adults and cause participants to drop out. Humanoid robots can be exploited to reduce boredom and the cognitive burden in playing serious games as part of cognitive training. In this paper, an adaptive technique to select the best actions for a robot is proposed to maintain the attention level of elderly users during a serious game. The goal is to create a strategy to adapt the robot's behaviour to stimulate the user to remain attentive through reinforcement learning. Specifically, a learning algorithm (QL) has been applied to obtain the best adaptation strategy for the selection of the robot's actions. The robot's actions consist of a combination of verbal and nonverbal interaction aspects. We have applied this approach to the behaviour of a Pepper robot for which two possible personalities have been defined. Each personality is exhibited by performing specific actions in the various modalities supported. Simulation results indicate learning convergence and seem promising to validate the effectiveness of the obtained strategy. Preliminary test results with three participants suggest that the adaption in the robot is perceived.Source: ALTRUIST 2022 - 2nd Workshop on sociAL roboTs for peRsonalized, continUous and adaptIve aSsisTance, pp. 93–99, Florence, Italy, 16/12/2022
Zedda E., Manca M., Paternò F.
Repetitive cognitive training can be seen as tedious by older adults and cause participants to drop out. Humanoid robots can be exploited to reduce boredom and the cognitive burden in playing serious games as part of cognitive training. In this paper, an adaptive technique to select the best actions for a robot is proposed to maintain the attention level of elderly users during a serious game. The goal is to create a strategy to adapt the robot's behaviour to stimulate the user to remain attentive through reinforcement learning. Specifically, a learning algorithm (QL) has been applied to obtain the best adaptation strategy for the selection of the robot's actions. The robot's actions consist of a combination of verbal and nonverbal interaction aspects. We have applied this approach to the behaviour of a Pepper robot for which two possible personalities have been defined. Each personality is exhibited by performing specific actions in the various modalities supported. Simulation results indicate learning convergence and seem promising to validate the effectiveness of the obtained strategy. Preliminary test results with three participants suggest that the adaption in the robot is perceived.Source: ALTRUIST 2022 - 2nd Workshop on sociAL roboTs for peRsonalized, continUous and adaptIve aSsisTance, pp. 93–99, Florence, Italy, 16/12/2022
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ceur-ws.org | ISTI Repository | CNR ExploRA
2023
Conference article
Closed Access
Assessment of the acceleration floor spectra through dynamic identification: the Museum of Bargello in Florence
Azzara R. M., Pellegrini D., Cardinali V., Viti S., Tanganelli M.
Artworks represent a priceless asset to the economic and cultural features of communities. Most art collections are hosted in Museums, which can be new buildings, appositely made for an expositive purpose, or monumental buildings, whose high artistic and historical value enhances the exposed art pieces. In this latter case, however, the Museums can disregard the seismic safety requirements provided for new constructions, becoming the main source of hazard for the precious contents they should preserve. In this paper, the dynamic behavior of the National Museum of Bargello in Florence is studied by means of a dynamic identification, focusing the attention on the "Sala di Donatello". An experimental campaign was performed by simultaneously installing two sets of three seismometric stations in the mentioned room and inside the corresponding one at the base of the building ("Sala Michelangelo"). Analysis of the recorded data via Operational Modal Analysis techniques has furnished the structure's natural frequencies, damping ratio and mode shapes allowing the assessment of the amplification of the seismic acceleration experienced by the art works exposed in "Sala di Donatello". The effect of the seismic acceleration on the artifacts has been checked on a case-study, i.e. the masterpiece "Marzocco". It is the statue of the lion considered the symbol of Florence, realized by Donatello in 1420, placed on a marble pedestal made by Benedetto da Maiano in 1480, which is a work of art as well. The assessment has been made by performing a simplified rigid-block analysis. The geometrical data of Marzocco has been stated based on a detailed photogrammetric survey, which provided a reliable representation of the mass distribution.Source: WCSI 2023 - 17th World Conference on Seismic Isolation, Torino, Italy, 12-16/09/2022
DOI: 10.1007/978-3-031-21187-4_88
Metrics:
Azzara R. M., Pellegrini D., Cardinali V., Viti S., Tanganelli M.
Artworks represent a priceless asset to the economic and cultural features of communities. Most art collections are hosted in Museums, which can be new buildings, appositely made for an expositive purpose, or monumental buildings, whose high artistic and historical value enhances the exposed art pieces. In this latter case, however, the Museums can disregard the seismic safety requirements provided for new constructions, becoming the main source of hazard for the precious contents they should preserve. In this paper, the dynamic behavior of the National Museum of Bargello in Florence is studied by means of a dynamic identification, focusing the attention on the "Sala di Donatello". An experimental campaign was performed by simultaneously installing two sets of three seismometric stations in the mentioned room and inside the corresponding one at the base of the building ("Sala Michelangelo"). Analysis of the recorded data via Operational Modal Analysis techniques has furnished the structure's natural frequencies, damping ratio and mode shapes allowing the assessment of the amplification of the seismic acceleration experienced by the art works exposed in "Sala di Donatello". The effect of the seismic acceleration on the artifacts has been checked on a case-study, i.e. the masterpiece "Marzocco". It is the statue of the lion considered the symbol of Florence, realized by Donatello in 1420, placed on a marble pedestal made by Benedetto da Maiano in 1480, which is a work of art as well. The assessment has been made by performing a simplified rigid-block analysis. The geometrical data of Marzocco has been stated based on a detailed photogrammetric survey, which provided a reliable representation of the mass distribution.Source: WCSI 2023 - 17th World Conference on Seismic Isolation, Torino, Italy, 12-16/09/2022
DOI: 10.1007/978-3-031-21187-4_88
Metrics:
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link.springer.com | CNR ExploRA
2023
Journal article
Open Access
From unstructured texts to semantic story maps
Bartalesi V., Coro G., Lenzi E., Pagano P., Pratelli N.
Digital maps greatly support storytelling about territories, especially when enriched with data describing cultural, societal, and ecological aspects, conveying emotional messages that describe the territory as a whole. Story maps are interactive online digital narratives that can describe a territory beyond its map by enriching the map with text, pictures, videos, and other multimedia information. This paper presents a semi-automatic workflow to produce story maps from textual documents containing territory data. An expert first assembles one territory-contextual document containing text and images. Then, automatic processes use natural language processing and Wikidata services to (i) extract key concepts (entities) and geospatial coordinates associated with the territory, (ii) assemble a logically-ordered sequence of enriched story-map events, and (iii) openly publish online story maps and an interoperable Linked Open Data semantic knowledge base for event exploration and inter-story correlation analyses. Our workflow uses an Open Science-oriented methodology to publish all processes and data. Through our workflow, we produced story maps for the value chains and territories of 23 rural European areas of 16 countries. Through numerical evaluation, we demonstrated that territory experts considered the story maps effective in describing their territories, and appropriate for communicating with citizens and stakeholders.Source: International journal of digital earth (Online) 16 (2023): 234–250. doi:10.1080/17538947.2023.2168774
DOI: 10.1080/17538947.2023.2168774
Project(s): MOVING
Metrics:
Bartalesi V., Coro G., Lenzi E., Pagano P., Pratelli N.
Digital maps greatly support storytelling about territories, especially when enriched with data describing cultural, societal, and ecological aspects, conveying emotional messages that describe the territory as a whole. Story maps are interactive online digital narratives that can describe a territory beyond its map by enriching the map with text, pictures, videos, and other multimedia information. This paper presents a semi-automatic workflow to produce story maps from textual documents containing territory data. An expert first assembles one territory-contextual document containing text and images. Then, automatic processes use natural language processing and Wikidata services to (i) extract key concepts (entities) and geospatial coordinates associated with the territory, (ii) assemble a logically-ordered sequence of enriched story-map events, and (iii) openly publish online story maps and an interoperable Linked Open Data semantic knowledge base for event exploration and inter-story correlation analyses. Our workflow uses an Open Science-oriented methodology to publish all processes and data. Through our workflow, we produced story maps for the value chains and territories of 23 rural European areas of 16 countries. Through numerical evaluation, we demonstrated that territory experts considered the story maps effective in describing their territories, and appropriate for communicating with citizens and stakeholders.Source: International journal of digital earth (Online) 16 (2023): 234–250. doi:10.1080/17538947.2023.2168774
DOI: 10.1080/17538947.2023.2168774
Project(s): MOVING
Metrics:
See at:
ISTI Repository | ISTI Repository | CNR ExploRA | www.tandfonline.com
2023
Journal article
Open Access
The impact of noise on evaluation complexity: the deterministic trust-region case
Bellavia S., Gurioli G., Morini B., Toint P. L.
Intrinsic noise in objective function and derivatives evaluations may cause premature termination of optimization algorithms. Evaluation complexity bounds taking this situation into account are presented in the framework of a deterministic trust-region method. The results show that the presence of intrinsic noise may dominate these bounds, in contrast with what is known for methods in which the inexactness in function and derivatives' evaluations is fully controllable. Moreover, the new analysis provides estimates of the optimality level achievable, should noise cause early termination. Numerical experiments are reported that support the theory. The analysis finally sheds some light on the impact of inexact computer arithmetic on evaluation complexity.Source: Journal of optimization theory and applications (2023). doi:10.1007/s10957-022-02153-5
DOI: 10.1007/s10957-022-02153-5
Metrics:
Bellavia S., Gurioli G., Morini B., Toint P. L.
Intrinsic noise in objective function and derivatives evaluations may cause premature termination of optimization algorithms. Evaluation complexity bounds taking this situation into account are presented in the framework of a deterministic trust-region method. The results show that the presence of intrinsic noise may dominate these bounds, in contrast with what is known for methods in which the inexactness in function and derivatives' evaluations is fully controllable. Moreover, the new analysis provides estimates of the optimality level achievable, should noise cause early termination. Numerical experiments are reported that support the theory. The analysis finally sheds some light on the impact of inexact computer arithmetic on evaluation complexity.Source: Journal of optimization theory and applications (2023). doi:10.1007/s10957-022-02153-5
DOI: 10.1007/s10957-022-02153-5
Metrics:
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ISTI Repository | link.springer.com | CNR ExploRA
2023
Conference article
Open Access
An environment to collect personal memories of older adults and use them to personalise serious games with humanoid robots
Catricalà B., Ledda M., Manca M., Paternò F., Santoro C., Zedda E.
One of the goals of Ambient Assisted Living (AAL) solutions is to be able to stimulate the cognitive resources of older adults. An innovative way to address such stimulation is the use of serious games delivered through humanoid robots, as they can provide an engaging way to perform exercises useful for training human memory, attention, processing, and planning activities. This paper presents an approach to supporting cognitive stimulation based on personal memories. The humanoid robot can exhibit different behaviours using various modalities, and propose the games in a way personalised to specific individuals' requirements, preferences, abilities, and motivations, which can vary among older adults, and even dynamically evolve over time for the same person depending on changing user needs and health conditions. Using personal memories associated with facts and events that occurred in older adults life in the serious games can increase their engagement, and thus potentially reduce the cognitive training drop-out.Source: ALTRUIST 2022 - 2nd Workshop on sociAL roboTs for peRsonalized, continUous and adaptIve aSsisTance, pp. 44–54, Florence, Italy, 16/12/2022
Catricalà B., Ledda M., Manca M., Paternò F., Santoro C., Zedda E.
One of the goals of Ambient Assisted Living (AAL) solutions is to be able to stimulate the cognitive resources of older adults. An innovative way to address such stimulation is the use of serious games delivered through humanoid robots, as they can provide an engaging way to perform exercises useful for training human memory, attention, processing, and planning activities. This paper presents an approach to supporting cognitive stimulation based on personal memories. The humanoid robot can exhibit different behaviours using various modalities, and propose the games in a way personalised to specific individuals' requirements, preferences, abilities, and motivations, which can vary among older adults, and even dynamically evolve over time for the same person depending on changing user needs and health conditions. Using personal memories associated with facts and events that occurred in older adults life in the serious games can increase their engagement, and thus potentially reduce the cognitive training drop-out.Source: ALTRUIST 2022 - 2nd Workshop on sociAL roboTs for peRsonalized, continUous and adaptIve aSsisTance, pp. 44–54, Florence, Italy, 16/12/2022
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2023
Report
Open Access
Implementation of a drug discovery pipeline on the D4Science platform
Orro A., D'Ursi P., Fossa P., Candela L., Panichi G.
This report documents the implementation of drug discovery pipeline in the D4Science platform realised in the context of the EOSC-Pillar project. In particular, it documents the pipeline and its constituents. Moreover, it describes how this pipeline has been integrated into the D4Science platform and exploited to create a dedicated Virtual Research Environment facilitating its exploitation and promoting a collaborative oriented approach for screening activities.Source: ISTI Technical Report, ISTI-2023-TR/001, 2023
DOI: 10.32079/isti-tr-2023/001
Project(s): EOSC-Pillar
Metrics:
Orro A., D'Ursi P., Fossa P., Candela L., Panichi G.
This report documents the implementation of drug discovery pipeline in the D4Science platform realised in the context of the EOSC-Pillar project. In particular, it documents the pipeline and its constituents. Moreover, it describes how this pipeline has been integrated into the D4Science platform and exploited to create a dedicated Virtual Research Environment facilitating its exploitation and promoting a collaborative oriented approach for screening activities.Source: ISTI Technical Report, ISTI-2023-TR/001, 2023
DOI: 10.32079/isti-tr-2023/001
Project(s): EOSC-Pillar
Metrics:
See at:
ISTI Repository | CNR ExploRA
2023
Book
Restricted
Semantic Web - Introduction to Semantic Web languages
Meghini C., Bartalesi Lenzi V.
The Web makes a very large amount of information available to users in the form of documents. The Semantic Web is a fundamental extension of the web as it allows, in addition to documents, the sharing of data (including document metadata) in a standard format along with their semantic context expressed in a formal and shared language. Applications in documentary science, biology, cultural heritage and electronic commerce have already demonstrated the validity of this approach. This volume constitutes a gentle introduction to the technologies and languages of the semantic web, clearly illustrating the steps necessary to transform a product published on the web into a set of data that can be processed and reused across applications, users and communities. This is the second monograph of the ebook series "Digital Culture Notebooks" edited by the Laboratory of Digital Culture of the University of Pisa (http://www.labcd.unipi.it) and published by Simonelli editore. The series houses short monographs on tools and research in the field of Digital Humanities which emerged from the work of teachers and students who collaborate with the Laboratory itself. It aims to support a wider dissemination of digital culture, understood as the field in which the humanities and some sectors of informatics interact and collaborate.Source: Milano: Simonelli, 2023
Meghini C., Bartalesi Lenzi V.
The Web makes a very large amount of information available to users in the form of documents. The Semantic Web is a fundamental extension of the web as it allows, in addition to documents, the sharing of data (including document metadata) in a standard format along with their semantic context expressed in a formal and shared language. Applications in documentary science, biology, cultural heritage and electronic commerce have already demonstrated the validity of this approach. This volume constitutes a gentle introduction to the technologies and languages of the semantic web, clearly illustrating the steps necessary to transform a product published on the web into a set of data that can be processed and reused across applications, users and communities. This is the second monograph of the ebook series "Digital Culture Notebooks" edited by the Laboratory of Digital Culture of the University of Pisa (http://www.labcd.unipi.it) and published by Simonelli editore. The series houses short monographs on tools and research in the field of Digital Humanities which emerged from the work of teachers and students who collaborate with the Laboratory itself. It aims to support a wider dissemination of digital culture, understood as the field in which the humanities and some sectors of informatics interact and collaborate.Source: Milano: Simonelli, 2023
See at:
CNR ExploRA | www.mondadoristore.it
2023
Journal article
Open Access
The application of SWAT model and remotely sensed products to characterize the dynamic of streamflow and snow in a mountainous watershed in the High Atlas
Taia S., Erraioui L., Arjdal Y., Chao J., El Mansouri B., Scozzari A.
Snowfall, snowpack, and snowmelt are among the processes with the greatest influence on the water cycle in mountainous watersheds. Hydrological models may be significantly biased if snow estimations are inaccurate. However, the unavailability of in situ snow data with enough spatiotemporal resolution limits the application of spatially distributed models in snow-fed watersheds. This obliges numerous modellers to reduce their attention to the snowpack and its effect on water distribution, particularly when a portion of the watershed is predominately covered by snow. This research demonstrates the added value of remotely sensed snow cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) in evaluating the performance of hydrological models to estimate seasonal snow dynamics and discharge. The Soil and Water Assessment Tool (SWAT) model was used in this work to simulate discharge and snow processes in the Oued El Abid snow-dominated watershed. The model was calibrated and validated on a daily basis, for a long period (1981-2015), using four discharge-gauging stations. A spatially varied approach (snow parameters are varied spatially) and a lumped approach (snow parameters are unique across the whole watershed) have been compared. Remote sensing data provided by MODIS enabled the evaluation of the snow processes simulated by the SWAT model. Results illustrate that SWAT model discharge simulations were satisfactory to good according to the statistical criteria. In addition, the model was able to reasonably estimate the snow-covered area when comparing it to the MODIS daily snow cover product. When allowing snow parameters to vary spatially, SWAT model results were more consistent with the observed streamflow and the MODIS snow-covered area (MODIS-SCA). This paper provides an example of how hydrological modelling using SWAT and snow coverage products by remote sensing may be used together to examine seasonal snow cover and snow dynamics in the High Atlas watershed.Source: Sensors (Basel) 23 (2023). doi:10.3390/s23031246
DOI: 10.3390/s23031246
Metrics:
Taia S., Erraioui L., Arjdal Y., Chao J., El Mansouri B., Scozzari A.
Snowfall, snowpack, and snowmelt are among the processes with the greatest influence on the water cycle in mountainous watersheds. Hydrological models may be significantly biased if snow estimations are inaccurate. However, the unavailability of in situ snow data with enough spatiotemporal resolution limits the application of spatially distributed models in snow-fed watersheds. This obliges numerous modellers to reduce their attention to the snowpack and its effect on water distribution, particularly when a portion of the watershed is predominately covered by snow. This research demonstrates the added value of remotely sensed snow cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) in evaluating the performance of hydrological models to estimate seasonal snow dynamics and discharge. The Soil and Water Assessment Tool (SWAT) model was used in this work to simulate discharge and snow processes in the Oued El Abid snow-dominated watershed. The model was calibrated and validated on a daily basis, for a long period (1981-2015), using four discharge-gauging stations. A spatially varied approach (snow parameters are varied spatially) and a lumped approach (snow parameters are unique across the whole watershed) have been compared. Remote sensing data provided by MODIS enabled the evaluation of the snow processes simulated by the SWAT model. Results illustrate that SWAT model discharge simulations were satisfactory to good according to the statistical criteria. In addition, the model was able to reasonably estimate the snow-covered area when comparing it to the MODIS daily snow cover product. When allowing snow parameters to vary spatially, SWAT model results were more consistent with the observed streamflow and the MODIS snow-covered area (MODIS-SCA). This paper provides an example of how hydrological modelling using SWAT and snow coverage products by remote sensing may be used together to examine seasonal snow cover and snow dynamics in the High Atlas watershed.Source: Sensors (Basel) 23 (2023). doi:10.3390/s23031246
DOI: 10.3390/s23031246
Metrics:
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ISTI Repository | CNR ExploRA | www.mdpi.com
2023
Conference article
Open Access
Strategies, benefits and challenges of app store-inspired requirements elicitation
Ferrari A., Spoletini P.
App store-inspired elicitation is the practice of exploring competitors' apps, to get inspiration for requirements. This activity is common among developers, but little insight is available on its practical use, advantages and possible issues. This paper aims to empirically analyse this technique in a realistic scenario, in which it is used to extend the requirements of a product that were initially captured by means of more traditional requirements elicitation interviews. Considering this scenario, we conduct an experimental simulation with 58 analysts and collect qualitative data. We perform thematic analysis of the data to identify strategies, benefits, and challenges of app store-inspired elicitation, as well as differences with respect to interviews in the considered elicitation setting. Our results show that: (1) specific guidelines and procedures are required to better conduct app store-inspired elicitation; (2) current search features made available by app stores are not suitable for this practice, and more tool support is required to help analysts in the retrieval and evaluation of competing products; (3) while interviews focus on the why dimension of requirements engineering (i.e., goals), app store-inspired elicitation focuses on how (i.e., solutions), offering indications for implementation and improved usability. Our study provides a framework for researchers to address existing challenges and suggests possible benefits to fostering app store-inspired elicitation among practitioners.Source: ICSE 2023 - 45th International Conference on Software Engineering, Melbourne, Australia, 14-20/05/2023
Ferrari A., Spoletini P.
App store-inspired elicitation is the practice of exploring competitors' apps, to get inspiration for requirements. This activity is common among developers, but little insight is available on its practical use, advantages and possible issues. This paper aims to empirically analyse this technique in a realistic scenario, in which it is used to extend the requirements of a product that were initially captured by means of more traditional requirements elicitation interviews. Considering this scenario, we conduct an experimental simulation with 58 analysts and collect qualitative data. We perform thematic analysis of the data to identify strategies, benefits, and challenges of app store-inspired elicitation, as well as differences with respect to interviews in the considered elicitation setting. Our results show that: (1) specific guidelines and procedures are required to better conduct app store-inspired elicitation; (2) current search features made available by app stores are not suitable for this practice, and more tool support is required to help analysts in the retrieval and evaluation of competing products; (3) while interviews focus on the why dimension of requirements engineering (i.e., goals), app store-inspired elicitation focuses on how (i.e., solutions), offering indications for implementation and improved usability. Our study provides a framework for researchers to address existing challenges and suggests possible benefits to fostering app store-inspired elicitation among practitioners.Source: ICSE 2023 - 45th International Conference on Software Engineering, Melbourne, Australia, 14-20/05/2023
See at:
ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
A survey on deep learning for human mobility
Luca M., Barlacchi G., Lepri B., Pappalardo L.
The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS traces, and social media posts, combined with the predictive power of artificial intelligence, triggered the application of deep learning to human mobility. Existing surveys focus on single tasks, data sources, mechanistic or traditional machine learning approaches, while a comprehensive description of deep learning solutions is missing. This survey provides a taxonomy of mobility tasks, a discussion on the challenges related to each task and how deep learning may overcome the limitations of traditional models, a description of the most relevant solutions to the mobility tasks described above, and the relevant challenges for the future. Our survey is a guide to the leading deep learning solutions to next-location prediction, crowd flow prediction, trajectory generation, and flow generation. At the same time, it helps deep learning scientists and practitioners understand the fundamental concepts and the open challenges of the study of human mobility.Source: ACM computing surveys 55 (2023). doi:10.1145/3485125
DOI: 10.1145/3485125
DOI: 10.48550/arxiv.2012.02825
Project(s): SoBigData-PlusPlus
Metrics:
Luca M., Barlacchi G., Lepri B., Pappalardo L.
The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS traces, and social media posts, combined with the predictive power of artificial intelligence, triggered the application of deep learning to human mobility. Existing surveys focus on single tasks, data sources, mechanistic or traditional machine learning approaches, while a comprehensive description of deep learning solutions is missing. This survey provides a taxonomy of mobility tasks, a discussion on the challenges related to each task and how deep learning may overcome the limitations of traditional models, a description of the most relevant solutions to the mobility tasks described above, and the relevant challenges for the future. Our survey is a guide to the leading deep learning solutions to next-location prediction, crowd flow prediction, trajectory generation, and flow generation. At the same time, it helps deep learning scientists and practitioners understand the fundamental concepts and the open challenges of the study of human mobility.Source: ACM computing surveys 55 (2023). doi:10.1145/3485125
DOI: 10.1145/3485125
DOI: 10.48550/arxiv.2012.02825
Project(s): SoBigData-PlusPlus
Metrics:
See at:
arXiv.org e-Print Archive | ACM Computing Surveys | ISTI Repository | dl.acm.org | ACM Computing Surveys | doi.org | CNR ExploRA
2023
Journal article
Open Access
Cognitive network neighborhoods quantify feelings expressed in suicide notes and Reddit mental health communities
Joseph S. M., Citraro S., Morini V., Rossetti G., Stella M.
Writing messages is key to expressing feelings. This study adopts cognitive network science to reconstruct how individuals report their feelings in clinical narratives like suicide notes or mental health posts. We achieve this by reconstructing syntactic/semantic associations between concepts in texts as co-occurrences enriched with affective data. We transform 142 suicide notes and 77,000 Reddit posts from the r/anxiety, r/depression, r/schizophrenia, and r/do-it-your-own (r/DIY) forums into 5 cognitive networks, each one expressing meanings and emotions as reported by authors. These networks reconstruct the semantic frames surrounding "feel", stem for "to feel" and "feelings", enabling a quantification of prominent associations and emotions focused around feelings. We find strong feelings of sadness across all clinical Reddit boards, added to fear r/depression, and replaced by joy/anticipation in r/DIY. Semantic communities and topic modeling both highlight key narrative topics of "regret", "unhealthy lifestyle" and "low mental well-being". Importantly, negative associations and emotions co-existed with trustful/positive language, focused on "getting better". This emotional polarization provides quantitative evidence that online clinical boards possess a complex structure, where users mix both positive and negative outlooks. This dichotomy is absent in the DIY reference board and in suicide notes, where negative emotional associations about regret and pain persist but are overwhelmed by positive jargon addressing loved ones. Our network-based comparisons provide quantitative evidence that suicide notes encapsulate different ways of expressing feelings compared to online Reddit boards, the latter acting more like personal diaries and relief valves. Our findings provide an interpretable network-based aid for supporting psychological inquiries of human feelings in digital and clinical settings.Source: Physica. A (Print) 610 (2023). doi:10.1016/j.physa.2022.128336
DOI: 10.1016/j.physa.2022.128336
Project(s): SoBigData-PlusPlus
Metrics:
Joseph S. M., Citraro S., Morini V., Rossetti G., Stella M.
Writing messages is key to expressing feelings. This study adopts cognitive network science to reconstruct how individuals report their feelings in clinical narratives like suicide notes or mental health posts. We achieve this by reconstructing syntactic/semantic associations between concepts in texts as co-occurrences enriched with affective data. We transform 142 suicide notes and 77,000 Reddit posts from the r/anxiety, r/depression, r/schizophrenia, and r/do-it-your-own (r/DIY) forums into 5 cognitive networks, each one expressing meanings and emotions as reported by authors. These networks reconstruct the semantic frames surrounding "feel", stem for "to feel" and "feelings", enabling a quantification of prominent associations and emotions focused around feelings. We find strong feelings of sadness across all clinical Reddit boards, added to fear r/depression, and replaced by joy/anticipation in r/DIY. Semantic communities and topic modeling both highlight key narrative topics of "regret", "unhealthy lifestyle" and "low mental well-being". Importantly, negative associations and emotions co-existed with trustful/positive language, focused on "getting better". This emotional polarization provides quantitative evidence that online clinical boards possess a complex structure, where users mix both positive and negative outlooks. This dichotomy is absent in the DIY reference board and in suicide notes, where negative emotional associations about regret and pain persist but are overwhelmed by positive jargon addressing loved ones. Our network-based comparisons provide quantitative evidence that suicide notes encapsulate different ways of expressing feelings compared to online Reddit boards, the latter acting more like personal diaries and relief valves. Our findings provide an interpretable network-based aid for supporting psychological inquiries of human feelings in digital and clinical settings.Source: Physica. A (Print) 610 (2023). doi:10.1016/j.physa.2022.128336
DOI: 10.1016/j.physa.2022.128336
Project(s): SoBigData-PlusPlus
Metrics:
See at:
ISTI Repository | Physica A Statistical Mechanics and its Applications | CNR ExploRA | www.sciencedirect.com
2023
Journal article
Open Access
A dataset to assess mobility changes in Chile following local quarantines
Pappalardo L., Cornacchia G., Navarro V., Bravo L., Ferres L.
Fighting the COVID-19 pandemic, most countries have implemented non-pharmaceutical interventions like wearing masks, physical distancing, lockdown, and travel restrictions. Because of their economic and logistical effects, tracking mobility changes during quarantines is crucial in assessing their efficacy and predicting the virus spread. Unlike many other heavily affected countries, Chile implemented quarantines at a more localized level, shutting down small administrative zones, rather than the whole country or large regions. Given the non-obvious effects of these localized quarantines, tracking mobility becomes even more critical in Chile. To assess the impact on human mobility of the localized quarantines, we analyze a mobile phone dataset made available by Telefónica Chile, which comprises 31 billion eXtended Detail Records and 5.4 million users covering the period February 26th to September 20th, 2020. From these records, we derive three epidemiologically relevant metrics describing the mobility within and between comunas. The datasets made available may be useful to understand the effect of localized quarantines in containing the COVID-19 pandemic.Source: Scientific data 10 (2023). doi:10.1038/s41597-022-01893-3
DOI: 10.1038/s41597-022-01893-3
Project(s): SoBigData-PlusPlus
Metrics:
Pappalardo L., Cornacchia G., Navarro V., Bravo L., Ferres L.
Fighting the COVID-19 pandemic, most countries have implemented non-pharmaceutical interventions like wearing masks, physical distancing, lockdown, and travel restrictions. Because of their economic and logistical effects, tracking mobility changes during quarantines is crucial in assessing their efficacy and predicting the virus spread. Unlike many other heavily affected countries, Chile implemented quarantines at a more localized level, shutting down small administrative zones, rather than the whole country or large regions. Given the non-obvious effects of these localized quarantines, tracking mobility becomes even more critical in Chile. To assess the impact on human mobility of the localized quarantines, we analyze a mobile phone dataset made available by Telefónica Chile, which comprises 31 billion eXtended Detail Records and 5.4 million users covering the period February 26th to September 20th, 2020. From these records, we derive three epidemiologically relevant metrics describing the mobility within and between comunas. The datasets made available may be useful to understand the effect of localized quarantines in containing the COVID-19 pandemic.Source: Scientific data 10 (2023). doi:10.1038/s41597-022-01893-3
DOI: 10.1038/s41597-022-01893-3
Project(s): SoBigData-PlusPlus
Metrics:
See at:
ISTI Repository | CNR ExploRA | www.nature.com