2026
Other
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Spoke 9 - AGRITECH 36-MONTH REPORT
Pucci Laura, Tomassi Elena, Arouna Nafiou, Gabriele Morena, Peres Fabbri Laryssa, Pozzo Luisa, Conte Giuseppe, Cremonesi Paola, Castiglioni Bianca, Moroni Davide, Martinelli Massimo
This document represents the 36-month report on products of animal origin intended for human consumption.Project(s): Spoke 9 AGRITECH
Pucci Laura, Tomassi Elena, Arouna Nafiou, Gabriele Morena, Peres Fabbri Laryssa, Pozzo Luisa, Conte Giuseppe, Cremonesi Paola, Castiglioni Bianca, Moroni Davide, Martinelli Massimo
This document represents the 36-month report on products of animal origin intended for human consumption.Project(s): Spoke 9 AGRITECH
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2026
Contribution to conference
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Blood pressure measurement in Italian mountain shelters: a world hypertension day initiative
Bilo Grzegorz, Zanotti Lucia, Croce Alessandro, D’angelo Carla, Faini Andrea, Martinelli Massimo, Muiesan Maria Lorenza, Pengo Martino F., Pratali Lorenza, Vega Deceno Jose Ivan, Soranna Davide, Zambon Antonella, Virdis Agostino, Strapazzon Giacomo, Agazzi Giancelso, Parati Gianfranco
World Hypertension Day and May Measurement Month are large-scale population initiatives aimed at increasing awareness of hypertension and providing opportunistic blood pressure (BP) screening. In Italy, “Blood Pressure Measurement in Mountain Shelters” has been conducted since 2016 as a joint initiative of Italian Society of Hypertension, Italian Alpine Club and Italian Society of Mountain Medicine, with the aim of providing advice and education on hypertension and cardiovascular risk among visitors of mountain shelters. Methods. Trained volunteers provided free advice to visitors of mountain shelters throughout Italy. Basic demographic, lifestyle and clinical information was collected with anonymous questionnaire. Seated BP was obtained using manual or oscillometric devices as the average of three measurements. The initiative took place in summer when mountain attendance is highest. The present analysis of merged data collected in 2019, 2022, 2023, 2024 and 2025 editions focuses on describing participant characteristics, including BP, stratified by altitude of data collection. Results. After exclusion of incomplete records (missing age, sex or BP), data of 12,317 participants from 140 mountain shelters were analysed. No relevant differences were observed across the different years in terms of participant characteristics or BP levels. Participant characteristics are reported in the Table. Median BP and body mass index were within normal limits, and the prevalence of diabetes, hypercholesterolaemia and hypertension was lower than that in the general Italian population. Fewer than 15% of participants reported taking at least one antihypertensive medication. Higher altitudes of data collection were associated with higher male sex prevalence and heart rate and with lower age, BMI, SpO2, prevalence of hypercholesterolemia and hypertension. Only minor differences were observed in measured BP. Conclusions. Blood Pressure Measurement in Mountain Shelters is a unique initiative, willingly attended by visitors to mountain areas. Participants generally displayed a favourable cardiovascular risk profile; however, a substantial proportion, including those assessed at higher altitudes, presented at least one cardiovascular risk factor. This screening and educational initiative represents a valuable opportunity to identify individuals at risk and to provide counselling on cardiovascular prevention among visitors of mountain shelters.
Bilo Grzegorz, Zanotti Lucia, Croce Alessandro, D’angelo Carla, Faini Andrea, Martinelli Massimo, Muiesan Maria Lorenza, Pengo Martino F., Pratali Lorenza, Vega Deceno Jose Ivan, Soranna Davide, Zambon Antonella, Virdis Agostino, Strapazzon Giacomo, Agazzi Giancelso, Parati Gianfranco
World Hypertension Day and May Measurement Month are large-scale population initiatives aimed at increasing awareness of hypertension and providing opportunistic blood pressure (BP) screening. In Italy, “Blood Pressure Measurement in Mountain Shelters” has been conducted since 2016 as a joint initiative of Italian Society of Hypertension, Italian Alpine Club and Italian Society of Mountain Medicine, with the aim of providing advice and education on hypertension and cardiovascular risk among visitors of mountain shelters. Methods. Trained volunteers provided free advice to visitors of mountain shelters throughout Italy. Basic demographic, lifestyle and clinical information was collected with anonymous questionnaire. Seated BP was obtained using manual or oscillometric devices as the average of three measurements. The initiative took place in summer when mountain attendance is highest. The present analysis of merged data collected in 2019, 2022, 2023, 2024 and 2025 editions focuses on describing participant characteristics, including BP, stratified by altitude of data collection. Results. After exclusion of incomplete records (missing age, sex or BP), data of 12,317 participants from 140 mountain shelters were analysed. No relevant differences were observed across the different years in terms of participant characteristics or BP levels. Participant characteristics are reported in the Table. Median BP and body mass index were within normal limits, and the prevalence of diabetes, hypercholesterolaemia and hypertension was lower than that in the general Italian population. Fewer than 15% of participants reported taking at least one antihypertensive medication. Higher altitudes of data collection were associated with higher male sex prevalence and heart rate and with lower age, BMI, SpO2, prevalence of hypercholesterolemia and hypertension. Only minor differences were observed in measured BP. Conclusions. Blood Pressure Measurement in Mountain Shelters is a unique initiative, willingly attended by visitors to mountain areas. Participants generally displayed a favourable cardiovascular risk profile; however, a substantial proportion, including those assessed at higher altitudes, presented at least one cardiovascular risk factor. This screening and educational initiative represents a valuable opportunity to identify individuals at risk and to provide counselling on cardiovascular prevention among visitors of mountain shelters.
2026
Conference article
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Reliable and trustworthy learning prototype: insight from POCUS
Ignesti G., D’angelo G., Pratali L., Moroni D., Martinelli M.
Deep learning models often lack the interpretability and trustworthiness required for clinical use. This paper proposes a prototype-regularised training method to analyse 1,208 lung ultrasound images, focusing on B-line artefacts. A ConvNeXt- Tiny architecture is used, adding a novel reconstruction loss to the standard classification loss. The model is guided to extract meaningful prototypes and uses them to classify the ultrasound images. To prevent these constraints from hindering generalisation, it is used in pairs with the proposed reconstruction loss, a set of plausible data augmentation of the ideal researched prototypes, and a geometry-aware network, a spatial transformer network, to measure which solutions help the network towards outputting the most reliable outcomes. The resulting models are precise, lightweight and interpretable, indicating that the proposed solution can be embedded in an ultrasound device to assist healthcare specialists in point-of-care applications.Project(s): TiAssisto
Ignesti G., D’angelo G., Pratali L., Moroni D., Martinelli M.
Deep learning models often lack the interpretability and trustworthiness required for clinical use. This paper proposes a prototype-regularised training method to analyse 1,208 lung ultrasound images, focusing on B-line artefacts. A ConvNeXt- Tiny architecture is used, adding a novel reconstruction loss to the standard classification loss. The model is guided to extract meaningful prototypes and uses them to classify the ultrasound images. To prevent these constraints from hindering generalisation, it is used in pairs with the proposed reconstruction loss, a set of plausible data augmentation of the ideal researched prototypes, and a geometry-aware network, a spatial transformer network, to measure which solutions help the network towards outputting the most reliable outcomes. The resulting models are precise, lightweight and interpretable, indicating that the proposed solution can be embedded in an ultrasound device to assist healthcare specialists in point-of-care applications.Project(s): TiAssisto
2026
Other
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Oxy-inflammatory profile of finishers and non-finishers in an extreme ultra-endurance trail race: the 866-km Transpyrénéa
Mrakic-Sposta Simona, Gussoni Maristella, Mrakic-Sposta Federica, Giardini Guido, Pratali Lorenza, Montorsi Michela, Tonacci Alessandro, Dellanoce Cinzia, Martinelli Massimo, Vezzoli Alessandra
This study investigates the bio-physiological responses occurring under extreme stress conditions and the characterization of oxy-inflammatory profile of finishers (FR) and non- finishers (NFR) during and following the Transpyrénéa, an 866-km extreme ultra-race across the French Pyrenees with an altitude difference of 52,900+m ascent. Thirty-nine ex- perienced ultra-marathon runners (age 43.5±9.1ys; weight 72.1±11.1kg; BMI 23.3±2.6 kg/m2) were studied, with mini-invasive methods by capillary blood and urine samples obtained from baseline (T0), along (T1, 2, 3) and to the end (T4) of the race. Reactive Oxy- gen Species (ROS) production; antioxidant capacity (TAC), oxidative damage (8-hydroxy- 2-deoxy Guanosine: 8-OH-dG; and 8-isoprostane: 8-isoPGF2α), inflammatory (IL-6), nitric oxide pathway (NOx and 3-NT), neopterin, and hematologic (lactate, and hematocrit) bi- omarkers were assessed. In both FR and NFR athletes a marked systemic increase of ROS, oxidative and nitrosative damage, inflammation, transient immune-renal dysfunction and a release of lactate were observed all along the race. NFR displayed distinct redox signatures vs FR: ROS production (T2: +35 vs +40%), oxidative damage (T2: 8-iso +219 vs +136%; 8-OH-dG +249 vs +217%), neopterin (T2: +68% vs +39%) and 3-NT (T2: +139% vs +115%) potentially reflecting superior training adaptations, greater antioxidant system, and enhanced metabolic efficiency allowing them to better tolerate extreme physiological stress.
Mrakic-Sposta Simona, Gussoni Maristella, Mrakic-Sposta Federica, Giardini Guido, Pratali Lorenza, Montorsi Michela, Tonacci Alessandro, Dellanoce Cinzia, Martinelli Massimo, Vezzoli Alessandra
This study investigates the bio-physiological responses occurring under extreme stress conditions and the characterization of oxy-inflammatory profile of finishers (FR) and non- finishers (NFR) during and following the Transpyrénéa, an 866-km extreme ultra-race across the French Pyrenees with an altitude difference of 52,900+m ascent. Thirty-nine ex- perienced ultra-marathon runners (age 43.5±9.1ys; weight 72.1±11.1kg; BMI 23.3±2.6 kg/m2) were studied, with mini-invasive methods by capillary blood and urine samples obtained from baseline (T0), along (T1, 2, 3) and to the end (T4) of the race. Reactive Oxy- gen Species (ROS) production; antioxidant capacity (TAC), oxidative damage (8-hydroxy- 2-deoxy Guanosine: 8-OH-dG; and 8-isoprostane: 8-isoPGF2α), inflammatory (IL-6), nitric oxide pathway (NOx and 3-NT), neopterin, and hematologic (lactate, and hematocrit) bi- omarkers were assessed. In both FR and NFR athletes a marked systemic increase of ROS, oxidative and nitrosative damage, inflammation, transient immune-renal dysfunction and a release of lactate were observed all along the race. NFR displayed distinct redox signatures vs FR: ROS production (T2: +35 vs +40%), oxidative damage (T2: 8-iso +219 vs +136%; 8-OH-dG +249 vs +217%), neopterin (T2: +68% vs +39%) and 3-NT (T2: +139% vs +115%) potentially reflecting superior training adaptations, greater antioxidant system, and enhanced metabolic efficiency allowing them to better tolerate extreme physiological stress.
2025
Other
Open Access
SI-Lab Annual Research Report 2024
Awais Ch Muhammad, Baiamonte A., Benassi A., Berti A., Bertini G., Buongiorno R, Bulotta D., Cafiso M., Carboni A., Carloni G., Caudai C., Colantonio S., Conti F., Daoudagh S., Del Corso G., Fusco G., Galesi G., Germanese D., Gravili S., Ignesti G., Kuruoglu E. E., Lazzini G., Leone G. R., Leporini B., Magrini M., Martinelli M., Omrani Ali Reza, Pachetti E., Papini O., Paradisi P., Pardini F., Pascali M. A., Pieri G., Reggiannini M., Righi M., Salerno E., Salvetti O., Scozzari A., Sebastiani L., Straface S., Tampucci M., Tarabella L., Tonazzini A., Moroni D.
The Signal & Images Laboratory (SI-Lab) is an interdisciplinary research group in computer vision, signal analysis, intelligent vision systems and multimedia data understanding. It is part of the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR). This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2024.DOI: 10.32079/isti-ar-2025/002
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Awais Ch Muhammad, Baiamonte A., Benassi A., Berti A., Bertini G., Buongiorno R, Bulotta D., Cafiso M., Carboni A., Carloni G., Caudai C., Colantonio S., Conti F., Daoudagh S., Del Corso G., Fusco G., Galesi G., Germanese D., Gravili S., Ignesti G., Kuruoglu E. E., Lazzini G., Leone G. R., Leporini B., Magrini M., Martinelli M., Omrani Ali Reza, Pachetti E., Papini O., Paradisi P., Pardini F., Pascali M. A., Pieri G., Reggiannini M., Righi M., Salerno E., Salvetti O., Scozzari A., Sebastiani L., Straface S., Tampucci M., Tarabella L., Tonazzini A., Moroni D.
The Signal & Images Laboratory (SI-Lab) is an interdisciplinary research group in computer vision, signal analysis, intelligent vision systems and multimedia data understanding. It is part of the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR). This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2024.DOI: 10.32079/isti-ar-2025/002
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2025
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Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU Course # 4
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
2025
Other
Open Access
Frostbite
Martinelli M.
Frostbite happens when your skin becomes frozen after being exposed to extremely cold temperatures.
Martinelli M.
Frostbite happens when your skin becomes frozen after being exposed to extremely cold temperatures.
2025
Other
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Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU Course # 3
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
2025
Other
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Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU Course # 6
Martinelli M.
Computer Vision & Applications in Agriculture Basic Techniques & Advanced ApplicationsProject(s): Agritech
Martinelli M.
Computer Vision & Applications in Agriculture Basic Techniques & Advanced ApplicationsProject(s): Agritech
2025
Other
Open Access
TiAssisto - Soluzioni per il monitoraggio clinico di pazienti in isolamento fiduciario a domicilio positivi al test per Covid-19 con associate o meno patologie croniche e situazioni di fragilità
Pratali L., Tomei A., Martinelli M.
Il poster illustra i principali obiettivi del progetto e i risultati ottenutiProject(s): TiAssisto
Pratali L., Tomei A., Martinelli M.
Il poster illustra i principali obiettivi del progetto e i risultati ottenutiProject(s): TiAssisto
2025
Other
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Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU Course # 5
Martinelli M.
Computer Vision & Applications in Agriculture - Basic Techniques & Advanced ApplicationsProject(s): Agritech
Martinelli M.
Computer Vision & Applications in Agriculture - Basic Techniques & Advanced ApplicationsProject(s): Agritech
2025
Other
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Improving weed control efficiency in maize fields: a methodological approach to site-specific weed management
Ercolini L., Grossi N., Martinelli M., Moroni D., Berton A., Silvestri N.
Methodologies to enhance precision agriculture.
Ercolini L., Grossi N., Martinelli M., Moroni D., Berton A., Silvestri N.
Methodologies to enhance precision agriculture.
2025
Other
Open Access
Batch-CAM: introduction to better reasoning in convolutional deep learning models
Ignesti G., Moroni D., Martinelli M.
Understanding the inner workings of deep learning models is crucial for advancing artificial intelligence, particularly in high-stakes fields such as healthcare, where accurate explanations are as vital as precision. This paper introduces Batch- CAM, a novel training paradigm that fuses a batch implementation of the Grad- CAM algorithm with a prototypical reconstruction loss. This combination guides the model to focus on salient image features, thereby enhancing its performance across classification tasks. Our results demonstrate that Batch-CAM achieves a simultaneous improvement in accuracy and image reconstruction quality while reducing training and inference times. By ensuring models learn from evidence- relevant information, this approach makes a relevant contribution to building more transparent, explainable, and trustworthy AI systems.DOI: 10.48550/arxiv.2510.00664
Metrics:
Ignesti G., Moroni D., Martinelli M.
Understanding the inner workings of deep learning models is crucial for advancing artificial intelligence, particularly in high-stakes fields such as healthcare, where accurate explanations are as vital as precision. This paper introduces Batch- CAM, a novel training paradigm that fuses a batch implementation of the Grad- CAM algorithm with a prototypical reconstruction loss. This combination guides the model to focus on salient image features, thereby enhancing its performance across classification tasks. Our results demonstrate that Batch-CAM achieves a simultaneous improvement in accuracy and image reconstruction quality while reducing training and inference times. By ensuring models learn from evidence- relevant information, this approach makes a relevant contribution to building more transparent, explainable, and trustworthy AI systems.DOI: 10.48550/arxiv.2510.00664
Metrics:
2025
Other
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Software di gestione del Questionario per la Giornata ipertensione nei rifugi CAI 2025
Martinelli M.
Software di gestione del Questionario per la Giornata ipertensione nei rifugi CAI 2025.DOI: 10.32079/isti-tr-2025/012
Metrics:
Martinelli M.
Software di gestione del Questionario per la Giornata ipertensione nei rifugi CAI 2025.DOI: 10.32079/isti-tr-2025/012
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2025
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Aggiornamento 2/25 Progetto Barilla Agrosat+
Martinelli M., Moroni D.
Aggiornamento modelliProject(s): Barilla Agrosat+
Martinelli M., Moroni D.
Aggiornamento modelliProject(s): Barilla Agrosat+
2025
Other
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2025
Contribution to conference
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Corn Regional Optimized Weed Decisions (CROWD): a tool for a site-specific weed management
Ercolinia L., Grossia N., Berton A., Martinelli M., Moroni D., Silvestri N.
Weed management (WM) remains a primary challenge in contemporary agriculture, particularly within the European Union's Farm to Fork strategy, which aims to reduce pesticide usage by 50% by 2030 while maintaining high crop productivity. In order to achieve this objective, innovative and sustainable approaches are required; among these, Site-Specific Weed Management (SSWM) is regarded as a promising solution. SSWM employs precision agriculture technologies, including remote sensing and artificial intelligence, to optimise herbicide application by targeting only weed-infested areas. The methodology is comprised of three fundamental phases: i) Weed Detection (WD), ii) estimation of potential crop yield loss due to weeds, and iii) precision herbicide application using ISOBUS sprayers. Despite the strides made, the adoption of SSWM is impeded by the substantial costs associated with technology, its intricate nature, and its incompatibility with less digitised farming systems. This study proposes a cost-effective and rapid-deployment Decision Support System (DSS) for maize cultivation that requires minimal calibration. Building on a previously validated method, the system estimates Weed Green Cover (WGC) using RGB drone imagery by subtracting Maize Green Cover (MGC) from Total Green Cover (TGC). The economic intervention threshold, expressed as tolerable WGC, is used to define a Green Damage Threshold (GDT) for each MZ. This enables timely and targeted weeding interventions based on image-derived metrics, offering a scalable solution for sustainable WM in diverse agricultural contexts.
Ercolinia L., Grossia N., Berton A., Martinelli M., Moroni D., Silvestri N.
Weed management (WM) remains a primary challenge in contemporary agriculture, particularly within the European Union's Farm to Fork strategy, which aims to reduce pesticide usage by 50% by 2030 while maintaining high crop productivity. In order to achieve this objective, innovative and sustainable approaches are required; among these, Site-Specific Weed Management (SSWM) is regarded as a promising solution. SSWM employs precision agriculture technologies, including remote sensing and artificial intelligence, to optimise herbicide application by targeting only weed-infested areas. The methodology is comprised of three fundamental phases: i) Weed Detection (WD), ii) estimation of potential crop yield loss due to weeds, and iii) precision herbicide application using ISOBUS sprayers. Despite the strides made, the adoption of SSWM is impeded by the substantial costs associated with technology, its intricate nature, and its incompatibility with less digitised farming systems. This study proposes a cost-effective and rapid-deployment Decision Support System (DSS) for maize cultivation that requires minimal calibration. Building on a previously validated method, the system estimates Weed Green Cover (WGC) using RGB drone imagery by subtracting Maize Green Cover (MGC) from Total Green Cover (TGC). The economic intervention threshold, expressed as tolerable WGC, is used to define a Green Damage Threshold (GDT) for each MZ. This enables timely and targeted weeding interventions based on image-derived metrics, offering a scalable solution for sustainable WM in diverse agricultural contexts.
2025
Other
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Contents of the digital agriculture for sustainable development. MASTER AGRITECH EU Course # 2 / 2025
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
2025
Other
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Computer Vision & Applications in Agriculture - Basic Techniques & Advanced Applications # 1
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
Martinelli M.
Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU CourseProject(s): Agritech
2025
Other
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Contents of the Digital agriculture for sustainable development. MASTER AGRITECH EU Course # 7
Martinelli M.
Computer Vision & Applications in Agriculture. Basic Techniques & Advanced ApplicationsProject(s): Agritech
Martinelli M.
Computer Vision & Applications in Agriculture. Basic Techniques & Advanced ApplicationsProject(s): Agritech