Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna
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Environmental actions, support for policy, and information’sprovision: experimental evidence from the US
Get PDFWe investigate the effectiveness of providing prospective versus retrospective informationon local climate change to promote pro-environmental behavior and support for greenpolicies. A randomized experiment on a representative sample of American adults findsthat providing prospective local climate change information is most effective at increas-ing pro-environmental actions and policy support, regardless of partisanship. The impactof this information provision increases when individuals feel responsible for addressingclimate change, have young children, and trust the central government. Prospective infor-mation on local climate change can thus contribute to promoting the vast support for thenecessary actions to address the climate crisis
Istituzioni cittadine, luoghi di mercato e mercanti a Bologna: un esempio di inclusione tra Basso Medioevo e prima Età Moderna
No full textMuovendo da un’analisi delle normative statutarie cittadine, corporative e mercantesche il contributo si propone di illustrare i molteplici rapporti tra la città e i mercanti bolognesi tra Basso Medioevo e prima Età Moderna.
Il contributo si snoda lungo tre direttrici. Una prima, che si propone di analizzare il coinvolgimento degli operatori economici nell’organigramma politico-giudiziario cittadino attraverso alcune magistrature. Una seconda, che intende evidenziare l’integrazione anche urbanistica tra i mercanti e la città attraverso una ricostruzione dei luoghi deputati al commercio e alle attività produttive. Un’ultima direttrice, infine, volta a sottolineare gli obblighi reciproci tra mercanti e governo
New Media Literacies per progettare e promuovere l’inclusione
No full textIl contributo esplora le nuove literacies necessarie per gli insegnanti inclusivi richiamando i
principi dell’Universal Design for Learning (UDL) e dell’Inclusive Design, considerando anche
il framework europeo DigCompEdu. Viene affrontato il ruolo cruciale dell’Intelligenza
Artificiale (IA) e come la digitalizzazione e i nuovi sviluppi nel campo della IA richiedano ai
docenti di acquisire nuove competenze per promuovere e sostenere un accesso equo ai
processi di insegnamento-apprendimento. Attraverso una panoramica delle dimensioni
di competenza digitale per l’inclusione, si evidenzia come un approccio olistico e multimodale
possa favorire la progettazione e l’implementazione di didattiche inclusive
Recognition of horse behaviours using deep learning techniques
No full textThe observation of horse behaviour offers important understanding into their state, making it a key indicator of their welfare. Among these be-haviours, sleep is particularly important due to its critical biological role in recovery and its cogni-tive function in memory consolidation [1]. As-sessing lying behaviour is an essential aspect of equine welfare evaluation, as horses generally tend to sleep shortly after lying down [3]. As prey animals, horses typically spend between 4 to 15 hours per day to standing rest, while the time spent lying down can range from minutes to several hours [2]. On average, adult horses spent about 80% of their resting time standing [4]. Moreover, monitoring additional behaviours such as access to drinking water and feeding time can provide further information into their welfare. However, di-rectly observing these behaviours, whether in per-son or via video recordings, can be time-consuming, especially since horses spend only a small portion of their day lying down or drinking. To improve daily management, computer vision technology offers automated methods to interpret and analyze visual data in animal environments [5]. Utilizing methods from image processing and machine learning, computer vision can extract meaningful data and improve the understanding of animal behaviours.
This study investigates the use of a deep learning-based computer vision system to identify the behaviours of individual stabled horses. The initial step involved fine-tuning a pre-trained YOLO architecture to recognize specific behaviours, such as lying, active standing, non-active standing, and drinking, for a single horse housed in a closed box. Object detection methods were used to identify lying and standing behaviours, while pose estimation techniques were utilized to detect drinking activity. To differentiate between active and non-active standing, a pixel-based threshold was applied. The system was then utilized for continuous monitoring over one month, generating a 24-hour time budget for the horse.
The performance of the model was evaluated using precision-recall curves and by comparing its behaviour classifications with manual annotations of the same video data. The system demonstrated an 86% accuracy in behaviour identification relative to human labelling. In conclusion, the technology presented in this study allows real-time recognition and pro-vides valuable information on the welfare of monitored animals. The results highlight the potential of this approach for improving the monitoring and understanding of horse behaviour
Value-adaptive clinical trial designs for efficient delivery of publicly funded trials - a discussion of methods, case studies, opportunities and challenges
Get PDFBackground: Value-adaptive designs for clinical trials are a novel set of emerging methods for delivering greater value for clinical research. There is increasing interest in using them within publicly funded health systems. A value-adaptive design permits ‘in progress’ changes to be made to the trial according to criteria which reflect its overall value to the healthcare system, including the cost-effectiveness of the technologies under investigation, the cost of running the trial and the total health benefit delivered to patients. These trial designs offer the potential to explicitly balance the costs and benefits of adaptive clinical trials with the health economic benefits expected for populations that are affected by any subsequent health technology adoption decisions. They may also improve the expected value of learning from the budget that is spent within a trial. Main body: This paper introduces value-adaptive designs for publicly funded clinical trials. It discusses the idea of delivering ‘value for money’ in health technology assessment, what is meant by being ‘value-adaptive’ and the key features that characterise these designs. The methodology behind one kind of value-adaptive design – the value-based sequential model of a two-armed clinical trial proposed by Chick et al. (2017) – is described and illustrated using three retrospective case studies from the United Kingdom. The paper concludes by reviewing a range of perspectives provided by stakeholders, together with our own thoughts, on the practical opportunities and changes required for implementing a value-adaptive approach. Conclusions: Value-adaptive clinical trial designs offer the potential to align health research funding allocations with population health economic goals. Many of the systems required to deploy value-adaptive designs within a publicly funded health system already exist and, with increased application, experience, and refinement they have the potential to deliver improved value for money
Synthesis and conclusions
No full textFrom a cultural perspective, the Ca’ Nova site
is a significant landmark in the Ligurian-Emilian
Apennines for the definition of the BINO
culture, which appears here (as in the sites of
Drusco in the Ceno Valley and Travo in the
Trebbia Valley), to be devoid of Terramare influences.
It should be remembered that the Parma
Apennines is a culturally nonhomogeneous territory,
being divided between the Terramare and
the BINO Cultures. As is well known, the former
occupies the central part of the Po Valley and the
Apennines of Reggio Emilia and Modena, the
latter the vast territories from western Lombardy
to Provence. A sort of border strip between
these two cultural aspects seems to run from the
upper valley of the Enza stream in the east to the
first hills between the river Taro and the Stirone
stream in the west. Ca’ Nova falls entirely within
the Western Culture territory, although it was
active as early as the middle phase of the Middle
Bronze Age, a period in which the Terramare
area of influence appears particularly extensive,
as indicated by the spread of Terramare-style
pottery finds in the Parma Apennines, much
wider in this phase than later
Argentina. Biografia di una nazione dall’indipendenza ad oggi
No full textDalle grandi migrazioni dell'Ottocento alla globalizzazione, l'Argentina ha vissuto una traiettoria complessa, segnata da promesse mancate e ritorni ricorrenti del passato. Questo libro ripercorre le tappe fondamentali della sua storia contemporanea, mostrando come, fin dall'inizio del XX secolo, si siano stratificati elementi destinati a modellarne il destino: populismi nati nel vuoto lasciato dai fascismi europei, cicli di crescita e crisi economica, conflitti tra rivoluzionari e reazionari, e un ruolo costante della Chiesa e dei militari nella vita pubblica. Attraverso una lettura attenta delle discontinuità e delle permanenze, gli autori arrivano all'Argentina di oggi, dove le fratture storiche continuano a esercitare un'influenza profonda. In questo scenario si inserisce la figura controversa del presidente Javier Milei, simbolo di una nuova stagione politica che divide il paese secondo linee antiche, tra adesioni entusiastiche e rifiuti radicali
Consumers’ acceptance of eggs as a function of hen genotype and rearing system
No full textThe aim of this study was to evaluate consumers’ acceptance of eggs as a function of hen genotype and rearing system. In view of supporting biodiversity safeguard and animal welfare, two Italian dual-purpose breeds (i.e., Bionda Piemontese, BP; Robusta Maculata, RM) and their crossbreeds with the commercial hybrid Sasso ` (BPxS; RMxS) were considered, reared in two different systems (i.e., enriched cage, C; free-range, F). As a reference, the commercial hybrid Lohmann Brown (L) was included in the experimental design. Eggs for sensory analysis were collected from 59-week-old layers and boiled for presentation to 80 untrained consumers. Panellists were instructed to indicate the liking degree in unstructured 9-point hedonic scales for the following attributes: overall
appearance, general aroma, general flavour, yolk colour, texture, and overall liking. Cage-free and organic eggs were bought by 44% and 39% of the respondents, respectively, thus indicating a significant (p < 0.001) attention towards production system and animal welfare. Statistically significant differences (p < 0.05) were detected only for overall appearance, yolk colour, and overall liking. The maximum median score was always obtained for the eggs RMxS reared in F. Eggs from L reared F got the lowest median scores for overall appearance and yolk colour. Considering the overall liking attribute, the significantly most preferred samples (p < 0.05) resulted RM_C (6.60), BPxS_C (5.90), and RMxS_F (6.80). The hen genotype resulted significant (p < 0.05) for yolk colour and overall liking, whereas the rearing system significantly affected (p < 0.05) yolk colour and general aroma
Non-Terrestrial Networks for 6G: Integrated, Intelligent and Ubiquitous Connectivity
No full textTo enable seamless 5G service continuity for mobile ground users traversing infrastructure-limited or obstructed regions, the integration of Non-Terrestrial Networks (NTNs) based on Low Earth Orbit (LEO) satellite constellations is being
actively pursued. However, the mobility dynamics of ground terminals frequently result in sudden Line-of-Sight (LoS) loss, which undermines the feasibility of conventional handover preparation involving context transfer, synchronization, and identity continuity. Without pre-coordination, such transitions lead to uplink blindness, session interruption, and degraded performance. This paper addresses the handover problem under NTN-specific constraints by (i) defining a structured taxonomy of service continuity mechanisms suited for LoS-impaired conditions, (ii)
introducing an analytical model that captures handover delay, authentication feasibility, and buffer dimensioning under varying visibility regimes, and (iii) quantitatively evaluating these metnisms in a high-mobility highway scenario. The results underline that while context mirroring ensures superior continuity under
full coordination, handover with reactive preparation emerges as the most practical and resilient fallback under constrained NTN conditions
Assessing feature extraction, selection, and classification combinations for crop mapping using Sentinel-2 time series: A case study in northern Italy
No full textRural areas need constant monitoring to ensure sustainable farming and respond to environmental and climatic impacts. Over the last few decades, remote sensing data have been extensively used in agricultural monitoring, allowing cost-effective and efficient crop management. Selecting the suitable data combinations for crop mapping while reducing dimensionality and redundancy to speed up processing remains a challenge. This study address the challenges by testing and assessing the efficiency of various combinations of feature extraction, feature selection, and feature classification methods. We used Sentinel-2 time series data, which focused on spectral features and derived vegetation indices. Particularly, the red-edge indices which are critical for crop discrimination. To select the optimal data for classifiers, we have tested two feature selection techniques: Random Forest and Principal Component Analysis, for both spectral bands and vegetational indices. Then, we have employed three machine learning algorithms: Extreme Gradient Boost (XGB), Random Forest (RF), and Support Vector Machine (SVM) along with one deep learning approach, Pixel-Set Encoders and Temporal Self-Attention (PSETAE), to evaluate the datasets. The results suggest that the most effective feature set is the Sentinel-2 spectral bands selected by the Random Forest feature selection method. The results obtained from the previous step achieve the highest overall accuracy with the XGB classifier and outperform the RF, SVM, and PSETAE classifiers. Further, quantitative analysis of overall classification accuracies showed that Random Forest is the second-best performing classifier, and PSETAE classifier produced the lowest results for all data models