2022
Journal article
Open Access
Horticultural therapy may reduce psychological and physiological stress in adolescents with anorexia nervosa: a pilot study
Curzio O, Billeci L, Belmonti V, Colantonio S, Cotrozzi L, De Pasquale Cf, Morales Ma, Nali C, Pascali Ma, Venturi F, Tonacci A, Zannoni N, Maestro S
Studies in psychiatric populations have found a positive effect of Horticultural therapy (HCT) on reductions in stress levels. The main objective of the present pilot study was to evaluate the impact of the addition of HCT to conventional clinical treatment (Treatment as Usual, TaU) in a sample of six female adolescents with anorexia nervosa restricting type (AN-R), as compared to six AN-R patients, matched for sex and age, under TaU only. This is a prospective, non-profit, pilot study on patients with a previous diagnosis of AN-R and BMI < 16, recruited in 2020 in clinical settings. At enrolment (T0) and after treatment completion (TF), psychiatric assessment was performed. At T0, all the patients underwent: baseline electrocardiogram acquisition with a wearable chest strap for recording heart rate and its variability; skin conductance registration and thermal mapping of the individual's face. An olfactory identification test was administered both to evaluate the olfactory sensoriality and to assess the induced stress. One-way analyses of variance (ANOVAs) were performed to analyze modifications in clinical and physiological variables, considering time (T0, TF) as a within-subjects factor and group (experimental vs. control) as between-subjects factors. When the ANOVA was significant, post hoc analysis was performed by Paired Sample T-tests. Only in the HCT group, stress response levels, as measured by the biological parameters, improved over time. The body uneasiness level and the affective problem measures displayed a significant improvement in the HCT subjects. HCT seems to have a positive influence on stress levels in AN-R.Source: NUTRIENTS, vol. 14 (issue 24)
DOI: 10.3390/nu14245198
Metrics:
Curzio O, Billeci L, Belmonti V, Colantonio S, Cotrozzi L, De Pasquale Cf, Morales Ma, Nali C, Pascali Ma, Venturi F, Tonacci A, Zannoni N, Maestro S
Studies in psychiatric populations have found a positive effect of Horticultural therapy (HCT) on reductions in stress levels. The main objective of the present pilot study was to evaluate the impact of the addition of HCT to conventional clinical treatment (Treatment as Usual, TaU) in a sample of six female adolescents with anorexia nervosa restricting type (AN-R), as compared to six AN-R patients, matched for sex and age, under TaU only. This is a prospective, non-profit, pilot study on patients with a previous diagnosis of AN-R and BMI < 16, recruited in 2020 in clinical settings. At enrolment (T0) and after treatment completion (TF), psychiatric assessment was performed. At T0, all the patients underwent: baseline electrocardiogram acquisition with a wearable chest strap for recording heart rate and its variability; skin conductance registration and thermal mapping of the individual's face. An olfactory identification test was administered both to evaluate the olfactory sensoriality and to assess the induced stress. One-way analyses of variance (ANOVAs) were performed to analyze modifications in clinical and physiological variables, considering time (T0, TF) as a within-subjects factor and group (experimental vs. control) as between-subjects factors. When the ANOVA was significant, post hoc analysis was performed by Paired Sample T-tests. Only in the HCT group, stress response levels, as measured by the biological parameters, improved over time. The body uneasiness level and the affective problem measures displayed a significant improvement in the HCT subjects. HCT seems to have a positive influence on stress levels in AN-R.Source: NUTRIENTS, vol. 14 (issue 24)
DOI: 10.3390/nu14245198
Metrics:
See at:
CNR IRIS 
| ISTI Repository | www.mdpi.com | CNR IRIS 
2022
Journal article
Open Access
Groundwater modeling with process-based and data-driven approaches in the context of climate change
Menichini M, Franceschi L, Raco B, Masetti G, Scozzari A, Doveri M
In the context of climate change, the correct management of groundwater, which is strategic for meeting water needs, becomes essential. Groundwater modeling is particularly crucial for the sustainable and efficient management of groundwater. This manuscript provides different types of modeling according to data availability and features of three porous aquifer systems in Italy (Empoli, Magra, and Brenta systems). The models calibrated on robust time series enabled the performing of forecast simulations capable of representing the quantitative and qualitative response to expected climate regimes. For the Empoli aquifer, the process-based models highlighted the system's ability to mitigate the effects of dry climate conditions thanks to its storage capability. The data-driven models concerning the Brenta foothill aquifer pointed out the high sensitivity of the system to climate extremes, thus suggesting the need for specific water management actions. The integrated datadriven/process-based approach developed for the Magra Valley aquifer remarked that the water quantity and quality effects are tied to certain boundary conditions over dry climate periods. This work shows that, for groundwater modeling, the choice of the suitable approach is mandatory, and it mainly depends on the specific aquifer features that result in different ways to be sensitive to climate. This manuscript also provides a novel outcome involving the integrated approach wherein it is a very efficient tool for forecasting modeling when boundary conditions, which significantly affect the behavior of such systems, are subjected to evolve under expected climate scenarios.Source: WATER, vol. 14 (issue 23)
DOI: 10.3390/w14233956
Metrics:
Menichini M, Franceschi L, Raco B, Masetti G, Scozzari A, Doveri M
In the context of climate change, the correct management of groundwater, which is strategic for meeting water needs, becomes essential. Groundwater modeling is particularly crucial for the sustainable and efficient management of groundwater. This manuscript provides different types of modeling according to data availability and features of three porous aquifer systems in Italy (Empoli, Magra, and Brenta systems). The models calibrated on robust time series enabled the performing of forecast simulations capable of representing the quantitative and qualitative response to expected climate regimes. For the Empoli aquifer, the process-based models highlighted the system's ability to mitigate the effects of dry climate conditions thanks to its storage capability. The data-driven models concerning the Brenta foothill aquifer pointed out the high sensitivity of the system to climate extremes, thus suggesting the need for specific water management actions. The integrated datadriven/process-based approach developed for the Magra Valley aquifer remarked that the water quantity and quality effects are tied to certain boundary conditions over dry climate periods. This work shows that, for groundwater modeling, the choice of the suitable approach is mandatory, and it mainly depends on the specific aquifer features that result in different ways to be sensitive to climate. This manuscript also provides a novel outcome involving the integrated approach wherein it is a very efficient tool for forecasting modeling when boundary conditions, which significantly affect the behavior of such systems, are subjected to evolve under expected climate scenarios.Source: WATER, vol. 14 (issue 23)
DOI: 10.3390/w14233956
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2022
Journal article
Open Access
Video conferencing tools: comparative study of the experiences of screen reader users and the development of more inclusive design guidelines
Leporini B, Buzzi M, Hersh M
Since the first lockdown in 2020, video conferencing tools have become increasingly important for employment, education, and social interaction, making them essential tools in everyday life. This study investigates the accessibility and usability of the desktop and mobile versions of three popular video conferencing tools, Zoom, Google Meet and MS Teams, for visually impaired people interacting via screen readers and keyboard or gestures. This involved two inspection evaluations to test the most important features of the desktop and mobile device versions and two surveys of visually impaired users to obtain information about the accessibility of the selected video conferencing tools. 65 and 94 people answered the surveys for desktop and mobile platforms respectively. The results showed that Zoom was preferred to Google Meet and MS Teams, but that none of the tools was fully accessible via screen reader and keyboard or gestures. Finally, the results of this empirical study were used to develop a set of guidelines for designers of video conferencing tools and assistive technology.Source: ACM TRANSACTIONS ON ACCESSIBLE COMPUTING, vol. 16 (issue 1)
DOI: 10.1145/3573012
Metrics:
Leporini B, Buzzi M, Hersh M
Since the first lockdown in 2020, video conferencing tools have become increasingly important for employment, education, and social interaction, making them essential tools in everyday life. This study investigates the accessibility and usability of the desktop and mobile versions of three popular video conferencing tools, Zoom, Google Meet and MS Teams, for visually impaired people interacting via screen readers and keyboard or gestures. This involved two inspection evaluations to test the most important features of the desktop and mobile device versions and two surveys of visually impaired users to obtain information about the accessibility of the selected video conferencing tools. 65 and 94 people answered the surveys for desktop and mobile platforms respectively. The results showed that Zoom was preferred to Google Meet and MS Teams, but that none of the tools was fully accessible via screen reader and keyboard or gestures. Finally, the results of this empirical study were used to develop a set of guidelines for designers of video conferencing tools and assistive technology.Source: ACM TRANSACTIONS ON ACCESSIBLE COMPUTING, vol. 16 (issue 1)
DOI: 10.1145/3573012
Metrics:
See at:
dl.acm.org | CNR IRIS | ISTI Repository | CNR IRIS | CNR IRIS
2022
Journal article
Open Access
Improving plant disease classification by adaptive minimal ensembling
Bruno A, Moroni D, Dainelli R, Rocchi L, Toscano P, Morelli S, Ferrari E, Martinelli M
A novel method for improving plant disease classification, a challenging and time-consuming process, is proposed. First, using as baseline EfficientNet, a recent and advanced family of architectures having an excellent accuracy/complexity trade-off, we have introduced, devised, and applied refined techniques based on transfer learning, regularization, stratification, weighted metrics, and advanced optimizers in order to achieve improved performance. Then, we go further by introducing adaptive minimal ensembling, which is a unique input to the knowledge base of the proposed solution. This represents a leap forward since it allows improving the accuracy with limited complexity using only two EfficientNet-b0 weak models, performing ensembling on feature vectors by a trainable layer instead of classic aggregation on outputs. To the best of our knowledge, such an approach to ensembling has never been used before in literature. Our method was tested on PlantVillage, a public reference dataset used for benchmarking models' performances for crop disease diagnostic, considering both its original and augmented versions. We noticeably improved the state of the art by achieving 100% accuracy in both the original and augmented datasets. Results were obtained using PyTorch to train, test, and validate the models; reproducibility is granted by providing exhaustive details, including hyperparameters used in the experimentation. A Web interface is also made publicly available to test the proposed methods.Source: FRONTIERS IN ARTIFICIAL INTELLIGENCE
DOI: 10.3389/frai.2022.868926
Metrics:
Bruno A, Moroni D, Dainelli R, Rocchi L, Toscano P, Morelli S, Ferrari E, Martinelli M
A novel method for improving plant disease classification, a challenging and time-consuming process, is proposed. First, using as baseline EfficientNet, a recent and advanced family of architectures having an excellent accuracy/complexity trade-off, we have introduced, devised, and applied refined techniques based on transfer learning, regularization, stratification, weighted metrics, and advanced optimizers in order to achieve improved performance. Then, we go further by introducing adaptive minimal ensembling, which is a unique input to the knowledge base of the proposed solution. This represents a leap forward since it allows improving the accuracy with limited complexity using only two EfficientNet-b0 weak models, performing ensembling on feature vectors by a trainable layer instead of classic aggregation on outputs. To the best of our knowledge, such an approach to ensembling has never been used before in literature. Our method was tested on PlantVillage, a public reference dataset used for benchmarking models' performances for crop disease diagnostic, considering both its original and augmented versions. We noticeably improved the state of the art by achieving 100% accuracy in both the original and augmented datasets. Results were obtained using PyTorch to train, test, and validate the models; reproducibility is granted by providing exhaustive details, including hyperparameters used in the experimentation. A Web interface is also made publicly available to test the proposed methods.Source: FRONTIERS IN ARTIFICIAL INTELLIGENCE
DOI: 10.3389/frai.2022.868926
Metrics:
See at:
CNR IRIS | ISTI Repository | ISTI Repository | www.frontiersin.org | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
A user-centered approach to artificial sensory substitution for blind people assistance
Barontini F, Bettelani Gc, Leporini B, Averta G, Bianchi M
Artificial sensory substitution plays a crucial role in different domains, including prosthetics, rehabilitation and assistive technologies. The sense of touch has historically represented the ideal candidate to convey information on the external environment, both contact-related and visual, when the natural action-perception loop is broken or not available. This is particularly true for blind people assistance, in which touch elicitation has been used to make content perceivable (e.g. Braille text or graphical reproduction), or to deliver informative cues for navigation. However, despite the significant technological advancements for what concerns both devices for touch-mediated access to alphanumeric stimuli, and technology-enabled haptic navigation supports, the majority of the proposed solutions has met with scarce acceptance in end users community. Main reason for this, in our opinion, is the poor involvement of the blind people in the design process. In this work, we report on a user-centric approach that we successfully applied for haptics-enabled systems for blind people assistance, whose engineering and validation have received significant inputs from the visually-impaired people. We also present an application of our approach to the design of a single-cell refreshable Braille device and to the development of a wearable haptic system for indoor navigation. After a summary of our previous results, we critically discuss next avenues and propose novel solutions for touch-mediated delivery of information for navigation, whose implementation has been totally driven by the feedback collected from real end-users.Source: BIOSYSTEMS & BIOROBOTICS, pp. 599-603. Online conference, 13-16/10/2020
DOI: 10.1007/978-3-030-70316-5_96
Metrics:
Barontini F, Bettelani Gc, Leporini B, Averta G, Bianchi M
Artificial sensory substitution plays a crucial role in different domains, including prosthetics, rehabilitation and assistive technologies. The sense of touch has historically represented the ideal candidate to convey information on the external environment, both contact-related and visual, when the natural action-perception loop is broken or not available. This is particularly true for blind people assistance, in which touch elicitation has been used to make content perceivable (e.g. Braille text or graphical reproduction), or to deliver informative cues for navigation. However, despite the significant technological advancements for what concerns both devices for touch-mediated access to alphanumeric stimuli, and technology-enabled haptic navigation supports, the majority of the proposed solutions has met with scarce acceptance in end users community. Main reason for this, in our opinion, is the poor involvement of the blind people in the design process. In this work, we report on a user-centric approach that we successfully applied for haptics-enabled systems for blind people assistance, whose engineering and validation have received significant inputs from the visually-impaired people. We also present an application of our approach to the design of a single-cell refreshable Braille device and to the development of a wearable haptic system for indoor navigation. After a summary of our previous results, we critically discuss next avenues and propose novel solutions for touch-mediated delivery of information for navigation, whose implementation has been totally driven by the feedback collected from real end-users.Source: BIOSYSTEMS & BIOROBOTICS, pp. 599-603. Online conference, 13-16/10/2020
DOI: 10.1007/978-3-030-70316-5_96
Metrics:
See at:
CNR IRIS | link.springer.com | ISTI Repository | CNR IRIS | CNR IRIS
2022
Journal article
Open Access
Short-term abandonment versus mowing in a mediterranean-temperate meadow: effects on floristic composition, plant functionality, and soil properties - a case study
Vannucchi F, Lazzeri V, Rosellini I, Scatena M, Caudai C, Bretzel F
Hay meadows are secondary grasslands maintained by mowing, and their ecological importance resides in the inherent biodiversity and carbon stocking. We investigated the plant community and soil properties of a sub humid acid grassland near the Fucecchio marshes (Italy), managed as a hay meadow, mowed once a year, and not fertilized. Part of the meadow had been abandoned for three years. We analysed the soil properties (i.e., organic carbon and total nitrogen content, available phosphorus, pH, cation-exchange capacity, texture, and conductibility) and the plant community structure (composition, functionality, and species richness) of the two sides of the meadow (mowed and abandoned). Our aim was to highlight the changes in soil properties and vegetation community, and to find out to what extent abandonment can affect those dynamics. Our results showed that after short-term abandonment, soil pH, C and N increased; litter biomass and perennial forbs increased; and annual forbs decreased. New species colonising after abandonment, thus enriching the flora, may keep spreading and eventually hinder the growth of the specialists if mowing is not resumed. Certain valuable meadow habitats need constant human intervention to maintain their peculiar vegetation, most especially if they are a buffer zone in the proximity of natural protected areas.Source: AGRICULTURE, vol. 12 (issue 1)
DOI: 10.3390/agriculture12010078
Metrics:
Vannucchi F, Lazzeri V, Rosellini I, Scatena M, Caudai C, Bretzel F
Hay meadows are secondary grasslands maintained by mowing, and their ecological importance resides in the inherent biodiversity and carbon stocking. We investigated the plant community and soil properties of a sub humid acid grassland near the Fucecchio marshes (Italy), managed as a hay meadow, mowed once a year, and not fertilized. Part of the meadow had been abandoned for three years. We analysed the soil properties (i.e., organic carbon and total nitrogen content, available phosphorus, pH, cation-exchange capacity, texture, and conductibility) and the plant community structure (composition, functionality, and species richness) of the two sides of the meadow (mowed and abandoned). Our aim was to highlight the changes in soil properties and vegetation community, and to find out to what extent abandonment can affect those dynamics. Our results showed that after short-term abandonment, soil pH, C and N increased; litter biomass and perennial forbs increased; and annual forbs decreased. New species colonising after abandonment, thus enriching the flora, may keep spreading and eventually hinder the growth of the specialists if mowing is not resumed. Certain valuable meadow habitats need constant human intervention to maintain their peculiar vegetation, most especially if they are a buffer zone in the proximity of natural protected areas.Source: AGRICULTURE, vol. 12 (issue 1)
DOI: 10.3390/agriculture12010078
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2022
Journal article
Open Access
Machine and deep learning prediction of prostate cancer aggressiveness using multiparametric MRI
E Bertelli, L Mercatelli, C Marzi, E Pachetti, M Baccini, A Barucci, S Colantonio, L Gherardini, L Lattavo, Ma Pascali, S Agostini, V Miele
Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa aggressiveness, for which a biopsy is required, is fundamental for patient management. Currently, multiparametric (mp) MRI is strongly recommended before biopsy. Quantitative assessment of mpMRI might provide the radiologist with an objective and noninvasive tool for supporting the decision-making in clinical practice and decreasing intra- and inter-reader variability. In this view, high dimensional radiomics features and Machine Learning (ML) techniques, along with Deep Learning (DL) methods working on raw images directly, could assist the radiologist in the clinical workflow. The aim of this study was to develop and validate ML/DL frameworks on mpMRI data to characterize PCas according to their aggressiveness. We optimized several ML/DL frameworks on T2w, ADC and T2w+ADC data, using a patient-based nested validation scheme. The dataset was composed of 112 patients (132 peripheral lesions with Prostate Imaging Reporting and Data System (PI-RADS) score >= 3) acquired following both PI-RADS 2.0 and 2.1 guidelines. Firstly, ML/DL frameworks trained and validated on PI-RADS 2.0 data were tested on both PI-RADS 2.0 and 2.1 data. Then, we trained, validated and tested ML/DL frameworks on a multi PI-RADS dataset. We reported the performances in terms of Area Under the Receiver Operating curve (AUROC), specificity and sensitivity. The ML/DL frameworks trained on T2w data achieved the overall best performance. Notably, ML and DL frameworks trained and validated on PI-RADS 2.0 data obtained median AUROC values equal to 0.750 and 0.875, respectively, on unseen PI-RADS 2.0 test set. Similarly, ML/DL frameworks trained and validated on multi PI-RADS T2w data showed median AUROC values equal to 0.795 and 0.750, respectively, on unseen multi PI-RADS test set. Conversely, all the ML/DL frameworks trained and validated on PI-RADS 2.0 data, achieved AUROC values no better than the chance level when tested on PI-RADS 2.1 data. Both ML/DL techniques applied on mpMRI seem to be a valid aid in predicting PCa aggressiveness. In particular, ML/DL frameworks fed with T2w images data (objective, fast and non-invasive) show good performances and might support decision-making in patient diagnostic and therapeutic management, reducing intra- and inter-reader variability.Source: FRONTIERS IN ONCOLOGY, vol. 11 (issue 802964)
DOI: 10.3389/fonc.2021.802964
Project(s): ProCAncer-I
Metrics:
E Bertelli, L Mercatelli, C Marzi, E Pachetti, M Baccini, A Barucci, S Colantonio, L Gherardini, L Lattavo, Ma Pascali, S Agostini, V Miele
Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa aggressiveness, for which a biopsy is required, is fundamental for patient management. Currently, multiparametric (mp) MRI is strongly recommended before biopsy. Quantitative assessment of mpMRI might provide the radiologist with an objective and noninvasive tool for supporting the decision-making in clinical practice and decreasing intra- and inter-reader variability. In this view, high dimensional radiomics features and Machine Learning (ML) techniques, along with Deep Learning (DL) methods working on raw images directly, could assist the radiologist in the clinical workflow. The aim of this study was to develop and validate ML/DL frameworks on mpMRI data to characterize PCas according to their aggressiveness. We optimized several ML/DL frameworks on T2w, ADC and T2w+ADC data, using a patient-based nested validation scheme. The dataset was composed of 112 patients (132 peripheral lesions with Prostate Imaging Reporting and Data System (PI-RADS) score >= 3) acquired following both PI-RADS 2.0 and 2.1 guidelines. Firstly, ML/DL frameworks trained and validated on PI-RADS 2.0 data were tested on both PI-RADS 2.0 and 2.1 data. Then, we trained, validated and tested ML/DL frameworks on a multi PI-RADS dataset. We reported the performances in terms of Area Under the Receiver Operating curve (AUROC), specificity and sensitivity. The ML/DL frameworks trained on T2w data achieved the overall best performance. Notably, ML and DL frameworks trained and validated on PI-RADS 2.0 data obtained median AUROC values equal to 0.750 and 0.875, respectively, on unseen PI-RADS 2.0 test set. Similarly, ML/DL frameworks trained and validated on multi PI-RADS T2w data showed median AUROC values equal to 0.795 and 0.750, respectively, on unseen multi PI-RADS test set. Conversely, all the ML/DL frameworks trained and validated on PI-RADS 2.0 data, achieved AUROC values no better than the chance level when tested on PI-RADS 2.1 data. Both ML/DL techniques applied on mpMRI seem to be a valid aid in predicting PCa aggressiveness. In particular, ML/DL frameworks fed with T2w images data (objective, fast and non-invasive) show good performances and might support decision-making in patient diagnostic and therapeutic management, reducing intra- and inter-reader variability.Source: FRONTIERS IN ONCOLOGY, vol. 11 (issue 802964)
DOI: 10.3389/fonc.2021.802964
Project(s): ProCAncer-I
Metrics:
See at:
CNR IRIS | ISTI Repository | www.frontiersin.org | CNR IRIS
2022
Other
Restricted
Barilla Agrosat+ Aggiornamento 1/22
Bruno A, Moroni D, Martinelli M
Nuovi modelli, miglioramenti, to-do list, progetto Barilla Agrosat+
Bruno A, Moroni D, Martinelli M
Nuovi modelli, miglioramenti, to-do list, progetto Barilla Agrosat+
2022
Other
Restricted
Barilla Agrosat+ Aggiornamento 2/22
Bruno A, Moroni D, Martinelli M
Nuovi modelli, miglioramenti, to-do list, progetto Barilla Agrosat+.
Bruno A, Moroni D, Martinelli M
Nuovi modelli, miglioramenti, to-do list, progetto Barilla Agrosat+.
2022
Other
Open Access
SpaghettiData and SpaghettiPlot: two Python classes for analysing and visualising SST trends
Papini O
This document describes the formalization of a "spaghetti plot" (i.e. a graph that captures the sea surface temperature trends in a target area) as a Python object, for which we defined two custom classes (SpaghettiData and SpaghettiPlot). In particular, we list the attributes and methods of these classes, together with the utilities that we use to create objects belonging to them.DOI: https://doi.org/10.32079/isti-tr-2022/001
DOI: 10.32079/isti-tr-2022/001
Project(s): NAUTILOS
Metrics:
Papini O
This document describes the formalization of a "spaghetti plot" (i.e. a graph that captures the sea surface temperature trends in a target area) as a Python object, for which we defined two custom classes (SpaghettiData and SpaghettiPlot). In particular, we list the attributes and methods of these classes, together with the utilities that we use to create objects belonging to them.DOI: https://doi.org/10.32079/isti-tr-2022/001
DOI: 10.32079/isti-tr-2022/001
Project(s): NAUTILOS
Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2022
Conference article
Open Access
Augmented reality, artificial intelligence and machine learning in Industry 4.0: case studies at SI-Lab
Bruno A, Coscetti S, Leone Gr, Germanese D, Magrini M, Martinelli M, Moroni D, Pascali Ma, Pieri G, Reggiannini M, Tampucci M
In recent years, the impressive advances in artificial intelligence, computer vision, pervasive computing, and augmented reality made them rise to pillars of the fourth industrial revolution. This short paper aims to provide a brief survey of current use cases in factory applications and industrial inspection under active development at the Signals and Images Lab, ISTI-CNR, Pisa.DOI: 10.5281/zenodo.6322733
Metrics:
Bruno A, Coscetti S, Leone Gr, Germanese D, Magrini M, Martinelli M, Moroni D, Pascali Ma, Pieri G, Reggiannini M, Tampucci M
In recent years, the impressive advances in artificial intelligence, computer vision, pervasive computing, and augmented reality made them rise to pillars of the fourth industrial revolution. This short paper aims to provide a brief survey of current use cases in factory applications and industrial inspection under active development at the Signals and Images Lab, ISTI-CNR, Pisa.DOI: 10.5281/zenodo.6322733
Metrics:
See at:
CNR IRIS | ISTI Repository | www.ital-ia2022.it | CNR IRIS
2022
Journal article
Open Access
A case study of upper limb robotic-assisted therapy using the track-hold device
Righi M, Magrini M, Dolciotti C, Moroni D
The Track-Hold System (THS) project, developed in a healthcare facility and therefore in a controlled and protected healthcare environment, contributes to the more general and broad context of Robotic-Assisted Therapy (RAT). RAT represents an advanced and innovative rehabilitation method, both motor and cognitive, and uses active, passive, and facilitating robotic devices. RAT devices can be equipped with sensors to detect and track voluntary and involuntary movements. They can work in synergy with multimedia protocols developed ad hoc to achieve the highest possible level of functional re-education. The THS is based on a passive robotic arm capable of recording and facilitating the movements of the upper limbs. An operational interface completes the device for its use in the clinical setting. In the form of a case study, the researchers conducted the experimentation in the former Tabarracci hospital (Viareggio, Italy). The case study develops a motor and cognitive rehabilitation protocol. The chosen subjects suffered from post-stroke outcomes affecting the right upper limb, including strength deficits, tremors, incoordination, and motor apraxia. During the first stage of the enrolment, the researchers worked with seven patients. The researchers completed the pilot with four patients because three of them got a stroke recurrence. The collaboration with four patients permitted the generation of an enlarged case report to collect preliminary data. The preliminary clinical results of the Track-Hold System Project demonstrated good compliance by patients with robotic-assisted rehabilitation; in particular, patients underwent a gradual path of functional recovery of the upper limb using the implemented interface.Source: SENSORS (BASEL), vol. 22 (issue 3)
DOI: 10.3390/s22031009
Metrics:
Righi M, Magrini M, Dolciotti C, Moroni D
The Track-Hold System (THS) project, developed in a healthcare facility and therefore in a controlled and protected healthcare environment, contributes to the more general and broad context of Robotic-Assisted Therapy (RAT). RAT represents an advanced and innovative rehabilitation method, both motor and cognitive, and uses active, passive, and facilitating robotic devices. RAT devices can be equipped with sensors to detect and track voluntary and involuntary movements. They can work in synergy with multimedia protocols developed ad hoc to achieve the highest possible level of functional re-education. The THS is based on a passive robotic arm capable of recording and facilitating the movements of the upper limbs. An operational interface completes the device for its use in the clinical setting. In the form of a case study, the researchers conducted the experimentation in the former Tabarracci hospital (Viareggio, Italy). The case study develops a motor and cognitive rehabilitation protocol. The chosen subjects suffered from post-stroke outcomes affecting the right upper limb, including strength deficits, tremors, incoordination, and motor apraxia. During the first stage of the enrolment, the researchers worked with seven patients. The researchers completed the pilot with four patients because three of them got a stroke recurrence. The collaboration with four patients permitted the generation of an enlarged case report to collect preliminary data. The preliminary clinical results of the Track-Hold System Project demonstrated good compliance by patients with robotic-assisted rehabilitation; in particular, patients underwent a gradual path of functional recovery of the upper limb using the implemented interface.Source: SENSORS (BASEL), vol. 22 (issue 3)
DOI: 10.3390/s22031009
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2022
Contribution to conference
Open Access
New technology and data collection for improving our understanding of the marine environment
Pieri G, Bebianno M, Chatzinikolaou E, Cocco M, Dimitrova L, Fahning J, Geraskova V, João A, King A, Lusher A, Malardé D, Martinelli M, Martins F, Mazza M, Novellino A, Ntoumas M, Sá S, Smerdon A, Triantafyllou G, Torres A
Introduction and Objective The H2020 NAUTILOS project aims to fill existing gaps in marine observation and modelling through the development of innovative and cost-effective technologies and observational methodologies for use in a wide range of crucial environmental contexts and sectors that can further support EU policies. The H2020 NAUTILOS project fills marine observation and modelling gaps by developing and deploying new technologies, promoting innovative and cost-effective methods in a wide range of crucial environmental settings and EU policy-related applications. Material and Methods NAUTILOS is developing innovative and cost-effective sensors and samplers for physical, chemical, and biological essential ocean variables in addition to micro-/nano-plastics. Newly developed technologies are integrated into diverse observing platforms, i.e. ships of opportunity, research vessels, surface and autonomous underwater vehicles, landers, fixed observatories, Argo floats, and Animal-borne instrumentation modules, to be deployed in key environmental settings. Results and Data relevance NAUTILOS will contribute to improving future ocean observation and forecasting capabilities through its holistic approach, which includes new sensors, new data to feed metocean forecast models, and the assessment of the forecasting capabilities, i.e. (OSSE) NAUTILOS data products FAIRness includes adopting standard vocabularies and open data publishing systems interoperable with European and international Ocean Data integrators. Moreover, synergies with relevant initiatives, Citizen Science campaigns and capacity building courses are also planned to reach out to all relevant stakeholders and users and promote free access and exchange of scientific data and knowledge. Conclusion The project will improve our understanding of environmental fluctuations and anthropogenic impacts in the oceans, relevant to aquaculture, fisheries and marine litter. Moreover, it will also complement and contribute to expanding European observation tools and services to obtain data collection at a much higher spatial resolution, temporal regularity and length than currently available at the European scale, and further democratise the marine environment's monitoring.Project(s): NAUTILOS
Pieri G, Bebianno M, Chatzinikolaou E, Cocco M, Dimitrova L, Fahning J, Geraskova V, João A, King A, Lusher A, Malardé D, Martinelli M, Martins F, Mazza M, Novellino A, Ntoumas M, Sá S, Smerdon A, Triantafyllou G, Torres A
Introduction and Objective The H2020 NAUTILOS project aims to fill existing gaps in marine observation and modelling through the development of innovative and cost-effective technologies and observational methodologies for use in a wide range of crucial environmental contexts and sectors that can further support EU policies. The H2020 NAUTILOS project fills marine observation and modelling gaps by developing and deploying new technologies, promoting innovative and cost-effective methods in a wide range of crucial environmental settings and EU policy-related applications. Material and Methods NAUTILOS is developing innovative and cost-effective sensors and samplers for physical, chemical, and biological essential ocean variables in addition to micro-/nano-plastics. Newly developed technologies are integrated into diverse observing platforms, i.e. ships of opportunity, research vessels, surface and autonomous underwater vehicles, landers, fixed observatories, Argo floats, and Animal-borne instrumentation modules, to be deployed in key environmental settings. Results and Data relevance NAUTILOS will contribute to improving future ocean observation and forecasting capabilities through its holistic approach, which includes new sensors, new data to feed metocean forecast models, and the assessment of the forecasting capabilities, i.e. (OSSE) NAUTILOS data products FAIRness includes adopting standard vocabularies and open data publishing systems interoperable with European and international Ocean Data integrators. Moreover, synergies with relevant initiatives, Citizen Science campaigns and capacity building courses are also planned to reach out to all relevant stakeholders and users and promote free access and exchange of scientific data and knowledge. Conclusion The project will improve our understanding of environmental fluctuations and anthropogenic impacts in the oceans, relevant to aquaculture, fisheries and marine litter. Moreover, it will also complement and contribute to expanding European observation tools and services to obtain data collection at a much higher spatial resolution, temporal regularity and length than currently available at the European scale, and further democratise the marine environment's monitoring.Project(s): NAUTILOS
See at:
CNR IRIS | oceandataconference.org | ISTI Repository | CNR IRIS
2022
Journal article
Open Access
Anorexia nervosa, body image perception and virtual reality therapeutic applications: state of the art and operational proposal
Magrini M, Curzio O, Tampucci M, Donzelli G, Cori L, Imiotti Mc, Maestro S, Moroni D
Anorexia Nervosa (AN) patients exhibit distorted body representation. The purpose of this study was to explore studies that analyze virtual reality (VR) applications, related to body image issues, to propose a new tool in this field. We conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, EMBASE, Scopus, and Web of Science databases were explored; the review included 25 studies. Research has increased over the last five years. The selected studies, clinical observational studies (n = 16), mostly concerning patients' population with AN (n = 14) or eating disorders (EDs) diagnosis, presented multiple designs, populations involved, and procedures. Some of these studies included healthy control groups (n = 7). Studies on community sample populations were also selected if oriented toward clinical applications (n = 9). The VR technologies in the examined period (about 20 years) have evolved significantly, going from very complex and bulky systems, requiring very powerful computers, to agile systems. The advent of low-cost VR devices has given a big boost to research works. Moreover, the operational proposal that emerges from this work supports the use of biofeedback techniques aimed at evaluating the results of therapeutic interventions in the treatment of adolescent patients diagnosed with AN.Source: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (ONLINE), vol. 19 (issue 5), pp. 1-30
DOI: 10.3390/ijerph19052533
Metrics:
Magrini M, Curzio O, Tampucci M, Donzelli G, Cori L, Imiotti Mc, Maestro S, Moroni D
Anorexia Nervosa (AN) patients exhibit distorted body representation. The purpose of this study was to explore studies that analyze virtual reality (VR) applications, related to body image issues, to propose a new tool in this field. We conducted a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, EMBASE, Scopus, and Web of Science databases were explored; the review included 25 studies. Research has increased over the last five years. The selected studies, clinical observational studies (n = 16), mostly concerning patients' population with AN (n = 14) or eating disorders (EDs) diagnosis, presented multiple designs, populations involved, and procedures. Some of these studies included healthy control groups (n = 7). Studies on community sample populations were also selected if oriented toward clinical applications (n = 9). The VR technologies in the examined period (about 20 years) have evolved significantly, going from very complex and bulky systems, requiring very powerful computers, to agile systems. The advent of low-cost VR devices has given a big boost to research works. Moreover, the operational proposal that emerges from this work supports the use of biofeedback techniques aimed at evaluating the results of therapeutic interventions in the treatment of adolescent patients diagnosed with AN.Source: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (ONLINE), vol. 19 (issue 5), pp. 1-30
DOI: 10.3390/ijerph19052533
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2022
Journal article
Open Access
Bathymetric and capacity relationships based on Sentinel-3 mission data for Aswan High Dam Lake, Egypt
Hossen H, Khairy M, Ghaly S, Scozzari A, Negm A, Elsahabi M
Aswan High Dam Lake (AHDL) is one of the most relevant hot spots at both local and global levels after construction of the Grand Ethiopian Renaissance Dam (GERD) was announced. The management of AHDL is a vital task, which requires the input of reliable information such as the lake bathymetry, water level, and the water surface area. Traditional, bathymetric methods are still very expensive and difficult to operate. Nowadays, satellite data and remote sensing techniques are easily accessible. In particular, datasets produced by operational missions are freely and globally available, and may provide efficient and inexpensive solutions for the retrieval of quantitative parameters concerning strategic water bodies, such as AHDL. This work identifies the performance of Sentinel-3A optical imagery data in the visible and NIR bands from the two optical instruments SLSTR and OLCI, and proposes the integration with Sentinel-3A radar altimetry from SRAL instrument applied to AHDL. This preliminary and first study investigated the relationship between the reflectance data and in situ data for water depth after a bathymetric campaign in the deep-water region using statistical regression models. These statistical models showed promising results in terms of correlation value (R > 0.8) and normalized root mean square errors (NRMSE < 0.4). Also, Heron's formula was applied to combine optical imagery and Sentinel-3 altimetry water level datasets to estimate water storage variations in AHDL. In addition, equations governing the relationship between water level, water surface area, and water volume were analyzed. The work is very useful for all authorities and stakeholders dealing with large water bodies.Source: WATER, vol. 14 (issue 711)
DOI: 10.3390/w14050711
Metrics:
Hossen H, Khairy M, Ghaly S, Scozzari A, Negm A, Elsahabi M
Aswan High Dam Lake (AHDL) is one of the most relevant hot spots at both local and global levels after construction of the Grand Ethiopian Renaissance Dam (GERD) was announced. The management of AHDL is a vital task, which requires the input of reliable information such as the lake bathymetry, water level, and the water surface area. Traditional, bathymetric methods are still very expensive and difficult to operate. Nowadays, satellite data and remote sensing techniques are easily accessible. In particular, datasets produced by operational missions are freely and globally available, and may provide efficient and inexpensive solutions for the retrieval of quantitative parameters concerning strategic water bodies, such as AHDL. This work identifies the performance of Sentinel-3A optical imagery data in the visible and NIR bands from the two optical instruments SLSTR and OLCI, and proposes the integration with Sentinel-3A radar altimetry from SRAL instrument applied to AHDL. This preliminary and first study investigated the relationship between the reflectance data and in situ data for water depth after a bathymetric campaign in the deep-water region using statistical regression models. These statistical models showed promising results in terms of correlation value (R > 0.8) and normalized root mean square errors (NRMSE < 0.4). Also, Heron's formula was applied to combine optical imagery and Sentinel-3 altimetry water level datasets to estimate water storage variations in AHDL. In addition, equations governing the relationship between water level, water surface area, and water volume were analyzed. The work is very useful for all authorities and stakeholders dealing with large water bodies.Source: WATER, vol. 14 (issue 711)
DOI: 10.3390/w14050711
Metrics:
See at:
CNR IRIS | ISTI Repository | www.mdpi.com | CNR IRIS
2022
Conference article
Open Access
Measuring the uptaking of digital health platforms on AAL/AHA domain
Juiz C, Bermejo B, Nikolov A, Rus S, Carboni A, Russo D, Moroni D, Karanastasis We, Andronikou V, Samuelsson C, Lievens F, Van Berlo A, Van Staalduinen W, Cabreraumpierrez Mf
This paper presents a method to determine the metrics to assess the uptake of Ambient Assisted Living (AAL) platforms. The different platforms are offering various resources to construct digital health products oriented to Active and Healthy Ageing (AHA) and social health care. This research work is ad-dressed to identify and define which metrics could be Key Performance Indicators (KPIs) to be tracked for successful uptake, interoperability, synergies, and cost-benefit analysis of open platforms.DOI: 10.1007/978-981-19-1610-6_45
Project(s): PlatformUptake.eu
Metrics:
Juiz C, Bermejo B, Nikolov A, Rus S, Carboni A, Russo D, Moroni D, Karanastasis We, Andronikou V, Samuelsson C, Lievens F, Van Berlo A, Van Staalduinen W, Cabreraumpierrez Mf
This paper presents a method to determine the metrics to assess the uptake of Ambient Assisted Living (AAL) platforms. The different platforms are offering various resources to construct digital health products oriented to Active and Healthy Ageing (AHA) and social health care. This research work is ad-dressed to identify and define which metrics could be Key Performance Indicators (KPIs) to be tracked for successful uptake, interoperability, synergies, and cost-benefit analysis of open platforms.DOI: 10.1007/978-981-19-1610-6_45
Project(s): PlatformUptake.eu
Metrics:
See at:
CNR IRIS | link.springer.com | ISTI Repository | doi.org | hal.archives-ouvertes.fr | CNR IRIS | CNR IRIS
2022
Conference article
Open Access
Computer vision per sistemi di trasporto intelligenti: il progetto S.Pa.Ce.
Leone Gr, Carboni A, Nardi S, Moroni D
Lo Smart Passenger Center (SPaCe) è una piattaforma integrata che mira a superare la complessità della gestione centralizzata delle infrastrutture di trasporto pubblico e dei veicoli. Il motore di intelligenza artificiale esamina i flussi quotidiani di persone, correla dati ed eventi diversi, prevede minacce ed eventi critici e propone contromisure. Questa enorme mole di dati proviene da una rete pervasiva di telecamere intelligenti che monitora costantemente le attività in stazioni, treni, autobus e altri luoghi di interesse. In questo lavoro, presentiamo il sottosistema distribuito di visione artificiale, lo stato dell'arte delle tecniche adottate e le funzionalità avanzate che questo sistema di sorveglianza intelligente offre ai livelli superiori di SPaCe. Tutto è sviluppato seguendo il paradigma della privacy-by-design: nessuna immagine viene registrata o trasmessa, ma tutte le elaborazioni avvengono sui nodi periferici del sistema.
Leone Gr, Carboni A, Nardi S, Moroni D
Lo Smart Passenger Center (SPaCe) è una piattaforma integrata che mira a superare la complessità della gestione centralizzata delle infrastrutture di trasporto pubblico e dei veicoli. Il motore di intelligenza artificiale esamina i flussi quotidiani di persone, correla dati ed eventi diversi, prevede minacce ed eventi critici e propone contromisure. Questa enorme mole di dati proviene da una rete pervasiva di telecamere intelligenti che monitora costantemente le attività in stazioni, treni, autobus e altri luoghi di interesse. In questo lavoro, presentiamo il sottosistema distribuito di visione artificiale, lo stato dell'arte delle tecniche adottate e le funzionalità avanzate che questo sistema di sorveglianza intelligente offre ai livelli superiori di SPaCe. Tutto è sviluppato seguendo il paradigma della privacy-by-design: nessuna immagine viene registrata o trasmessa, ma tutte le elaborazioni avvengono sui nodi periferici del sistema.
See at:
CNR IRIS | ISTI Repository | ISTI Repository | www.ital-ia2022.it | CNR IRIS | CNR IRIS
2022
Journal article
Open Access
Skewed t-Distribution for hyperspectral anomaly detection based on autoencoder
Kayabol K, Aytekin Eb, Arisoy S, Kuruoglu Ee
We propose multivariate skewed t-distribution (MVSkt) for hyperspectral anomaly detection (AD). The proposed distribution model is able to increase the detection performance of autoencoder (AE)-based anomaly detectors. In the proposed method, the reconstruction error of a deep AE is modeled with a skewed t-distribution. The deep AE network is trained based on adversarial learning strategy by feeding its input with the hyperspectral data cubes. The parameters of the t-distribution model are estimated using variational Bayesian approach. We define an MVSkt-based detection rule for pixel-wise AD. We compare our proposed method with those based on the multivariate normal (MVN) distribution and the robust MVN variance-mean mixture distributions on real hyperspectral datasets. The experimental results show that the proposed approach outperforms other detectors in the benchmark.Source: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (PRINT), vol. 19 (issue 9583260)
DOI: 10.1109/lgrs.2021.3121876
Metrics:
Kayabol K, Aytekin Eb, Arisoy S, Kuruoglu Ee
We propose multivariate skewed t-distribution (MVSkt) for hyperspectral anomaly detection (AD). The proposed distribution model is able to increase the detection performance of autoencoder (AE)-based anomaly detectors. In the proposed method, the reconstruction error of a deep AE is modeled with a skewed t-distribution. The deep AE network is trained based on adversarial learning strategy by feeding its input with the hyperspectral data cubes. The parameters of the t-distribution model are estimated using variational Bayesian approach. We define an MVSkt-based detection rule for pixel-wise AD. We compare our proposed method with those based on the multivariate normal (MVN) distribution and the robust MVN variance-mean mixture distributions on real hyperspectral datasets. The experimental results show that the proposed approach outperforms other detectors in the benchmark.Source: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (PRINT), vol. 19 (issue 9583260)
DOI: 10.1109/lgrs.2021.3121876
Metrics:
See at:
CNR IRIS | ieeexplore.ieee.org | ISTI Repository | IEEE Geoscience and Remote Sensing Letters | CNR IRIS | CNR IRIS
2022
Other
Restricted
Slide corso di Elementi di informatica e applicazioni giuridiche - CdL in Diritto dell'Innovazione per l'impresa e le istituzioni
Righi M
Slide utilizzate durante docenza del corso Elementi di informatica e applicazioni giuridiche - CdL in Diritto dell'Innovazione per l'impresa e le istituzioni.
Righi M
Slide utilizzate durante docenza del corso Elementi di informatica e applicazioni giuridiche - CdL in Diritto dell'Innovazione per l'impresa e le istituzioni.
See at:
CNR IRIS | CNR IRIS | CNR IRIS | CNR IRIS | CNR IRIS
2022
Journal article
Open Access
Low productivity substrate leads to functional diversification of green roof plant assemblage
Vannucchi F, Buoncristiano A, Scatena M, Caudai C, Bretzel F
Green roofs are roof free spaces where living organisms can find an appropriate habitat to colonise. The establishment of plant species with different functionality can enhance biodiversity and provide ecosystem services. However, drought and nutrient availability can affect the plant development. The extensive green roof was set up in Pisa (Italy) in 2014, 12 modules of 10 cm depth were filled with three substrates composed of compost from municipal mixed waste, pelletised paper sludge, and commercial tephra product (Vulcaflor), as follows: Vulcaflor + compost, Vulcaflor + pellet + compost, and Vulcaflor + pellet, characterised by decreasing level of nitrogen content. The species planted in 2014 were chosen from the herbaceous spontaneous vegetation of urban and rural swards not often mowed, plus two sedum species. After the establishment phase, the green roof community was progressively dominated by Sedum species and other species were seeded in 2016. In 2018-19 the plant functional types and the community structure were monitored. Besides seasonal fluctuations, nitrogen shaped the composition of the community, and Sedum species showed high cover values in nitrogen-richer substrates. Annual forbs colonised the plots with a lower nitrogen content. In summer, the number of species drastically fell, and Sedum album was dominant in the three substrates. Seedling recruitment regenerated the community in the cooler season, increasing the diversity in the poor substrate. The scarcity of nitrogen led to the development of stress-tolerator annuals increasing the biodiversity in the rainy-cool season. Annual species constitute a transient seed bank which enables the system to regenerate when rain follows periods of heat and drought.Source: ECOLOGICAL ENGINEERING, vol. 176
DOI: 10.1016/j.ecoleng.2022.106547
Metrics:
Vannucchi F, Buoncristiano A, Scatena M, Caudai C, Bretzel F
Green roofs are roof free spaces where living organisms can find an appropriate habitat to colonise. The establishment of plant species with different functionality can enhance biodiversity and provide ecosystem services. However, drought and nutrient availability can affect the plant development. The extensive green roof was set up in Pisa (Italy) in 2014, 12 modules of 10 cm depth were filled with three substrates composed of compost from municipal mixed waste, pelletised paper sludge, and commercial tephra product (Vulcaflor), as follows: Vulcaflor + compost, Vulcaflor + pellet + compost, and Vulcaflor + pellet, characterised by decreasing level of nitrogen content. The species planted in 2014 were chosen from the herbaceous spontaneous vegetation of urban and rural swards not often mowed, plus two sedum species. After the establishment phase, the green roof community was progressively dominated by Sedum species and other species were seeded in 2016. In 2018-19 the plant functional types and the community structure were monitored. Besides seasonal fluctuations, nitrogen shaped the composition of the community, and Sedum species showed high cover values in nitrogen-richer substrates. Annual forbs colonised the plots with a lower nitrogen content. In summer, the number of species drastically fell, and Sedum album was dominant in the three substrates. Seedling recruitment regenerated the community in the cooler season, increasing the diversity in the poor substrate. The scarcity of nitrogen led to the development of stress-tolerator annuals increasing the biodiversity in the rainy-cool season. Annual species constitute a transient seed bank which enables the system to regenerate when rain follows periods of heat and drought.Source: ECOLOGICAL ENGINEERING, vol. 176
DOI: 10.1016/j.ecoleng.2022.106547
Metrics:
See at:
ISTI Repository | CNR IRIS | CNR IRIS | CNR IRIS | www.sciencedirect.com