Archivio della ricerca - Fondazione Bruno Kessler
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Transmission of autochthonous Aedes-borne arboviruses and related public health challenges in Europe 2007–2023: a systematic review and secondary analysis
No full textBackground
Local transmission of dengue, chikungunya, and Zika infection is an emerging public health threat in Europe. Monitoring the epidemiological trends can help define the intervention strategy. The aim of this work was to analyse epidemiological characteristics of autochthonous transmission of Aedes-borne arboviruses in Europe.
Methods
A systematic review of the literature published from January 1, 2007, to January 31, 2024, reporting autochthonous cases of dengue, chikungunya, and Zika detected in Europe was performed. We searched MEDLINE, EMBASE, and the ECDC reports. Descriptive statistics and a secondary analysis were used to summarize the epidemiological characteristics of local transmission events (LTEs), explore potential temporal trends and identify relevant associations between epidemiological variables. Time intervals between key events were analysed to identify potential delays in LTE identification and intervention.
Findings
A total of 59 studies were included, describing 56 LTEs. The frequency of LTEs increased over time, with an average of 1.25 (95% CI: 1.17–1.35) times increment every year. While the highest number of dengue LTEs was reported in France (N = 37), Italy faced the largest number of cases detected in an LTE (N = 41). Considering all the arboviral LTEs, the median time between the symptom onset of the primary case and the diagnosis of the index case (“outbreak detection”) was 35.5 days (range 23.0–76.0). Only for chikungunya, higher delays correlated with higher cumulative number of cases detected per LTE, though this may be biased due to the low sample size.
Interpretation
We have observed a gradual increase of Aedes-borne arboviral LTEs in Europe over time, and a considerable delay in outbreak detection. Improving the timeliness of LTE identification is essential
Combination of searches for singly produced vectorlike top quarks in pp collisions at √s =13 TeV with the ATLAS detector
No full text
Toward Compliance and Transparency in Raw Material Sourcing With Blockchain and Edge AI
No full textThe global push for green technologies and digital transformation has intensified the demand for critical raw materials, prompting the European Union to enact the Critical Raw Materials Act (CRMA) to ensure ethical, transparent, and resilient mineral supply chains. As the world advances toward the 6G and IoT era, characterized by ultra-low latency, ubiquitous connectivity, and intelligent edge computing, there is an urgent need to empower all levels of the supply chain, especially artisanal small-scale mining (ASM), which remains largely disconnected from such innovations. To address this gap, we propose the Raw Material Radar (RMR) framework, centered on a smart barrel that integrates IoT sensing, edge AI processing, and blockchain-based record-keeping. This low-power device enables real-time detection of shipment anomalies such as tampering or unauthorized access, even in offline and resource-limited environments. Our fully functional prototype achieves high performance (94% F1-score, 98% recall), with minimal resource usage (8.45KB RAM, 407KB flash) and fast inference (5.25 ms), making it well-suited for deployment at the network edge. By enabling verifiable, autonomous custody tracking, the RMR solution exemplifies how edge AI can enhance supply chain transparency and regulatory compliance—critical components for ethical sourcing in the 6G-driven IoT landscape
Carbon-Aware Spatio-Temporal Workload Shifting in Edge–Cloud Environments: A Review and Novel Algorithm
Get PDFDue to its rising carbon footprint, new paradigms for carbon-efficient computing are needed. For distributed computing systems, one option is to shift computing loads in space or time to take advantage of low-carbon electricity, a paradigm known as carbon-aware computing. We present a literature review of carbon-aware scheduling techniques, which shows that most of the literature carried out either spatial or temporal shifting but not both. Of the 28 analyzed studies, 11 considered both spatial and temporal shifting, and only 2 developed a combined optimization algorithm. Additionally, existing approaches typically focus on operational electricity alone. With the growing decarbonization of electricity, however, device production (which involves various industrial processes and cannot be easily decarbonized) is bound to become more relevant and needs to be considered. We thus suggest a novel spatio-temporal scheduling algorithm for cloud and edge computing. Our algorithm performs simultaneous spatio-temporal shifting while taking into consideration both device production and operation. As temporal shifting requires forecasts of future workloads, we also put forward a workload predictor. Although not fully implemented yet, we bring various theoretical arguments in support of our proposed algorithm
Facing the Limits: Designing Data Physicalizations to Reduce Water Consumption in Mountain Huts
No full textMountain huts are buildings in remote mountain areas that depend on local water sources, such as snow, rain, and springs, as they are not connected to centralized water systems. In this pictorial, we report the design process undertaken to explore how data physicalization can communicate the problem of water scarcity in mountain huts with the ultimate goal of encouraging visitors to reduce water usage. The process led to two concepts: one that materializes the impact of each visitor on the water reserve of the hut through a participatory installation, and the other that invites visitors to explore the concept of limit, encouraging reflection on what they are willing to renounce and
helping them to make informed choices within tight water constraints. With our work, we aim to contribute to the ongoing efforts in Sustainable HCI to shift the purpose of behavior change from personal gain to the common good
Dal disordine all’ordine, e viceversa. L’antropologia incontra la fisica delle particelle
No full textThe paper explores the intersection between cultural anthropology
and quantum physics. It examines how humanity’s quest to impose order on cha-
os is mirrored in both mythological narratives and scientific endeavors. Starting
from ancient concepts of primordial chaos, the author connects historical myths,
such as Gilgamesh and Pangu, to humanity’s drive to manage uncertainty and
create order and structured civilizations. The quantum revolution challenges
this perspective, presenting a new understanding of reality characterized by
interconnectedness and uncertainty. The paper discusses the implications of
quantum mechanics for human culture, emphasizing how it disrupts established
boundaries between observer and observed, leading to a reconsideration of the
nature of knowledge and power. It also highlights how quantum ideas have per-
meated popular culture, transforming into simplified narratives that, paradoxi-
cally, continue humanity’s effort to master chaos. Ultimately, the paper suggests
that embracing quantum uncertainty may lead to a cultural redefinition of our
species and a shift in how we perceive our role within the universe
Neuropsychological and clinical variables associated with cognitive trajectories in patients with Alzheimer's disease
No full textBackground: The NeuroArtP3 (NET-2018-12366666) is a multicenter study funded by the Italian Ministry of Health. The aim of the project is to identify the prognostic trajectories of Alzheimer's disease (AD) through the application of artificial intelligence (AI). Only a few AI studies investigated the clinical variables associated with cognitive worsening in AD. We used Mini Mental State Examination (MMSE) scores as outcome to identify the factors associated with cognitive decline at follow up.
Methods: A sample of N = 126 patients diagnosed with AD (MMSE >19) were followed during 3 years in 4 time-points: T0 for the baseline and T1, T2 and T3 for the years of follow-ups. Variables of interest included demographics: age, gender, education, occupation; measures of functional ability: Activities of Daily Living (ADLs) and Instrumental (IADLs); clinical variables: presence or absence of comorbidity with other pathologies, severity of dementia (Clinical Dementia Rating Scale), behavioral symptoms; and the equivalent scores (ES) of cognitive tests. Logistic regression, random forest and gradient boosting were applied on the baseline data to estimate the MMSE scores (decline of at least >3 points) measured at T3. Patients were divided into multiple splits using different model derivation (training) and validation (test) proportions, and the optimization of the models was carried out through cross validation on the derivation subset only. The models predictive capabilities (balanced accuracy, AUC, AUPCR, F1 score and MCC) were computed on the validation set only. To ensure the robustness of the results, the optimization was repeated 10 times. A SHAP-type analysis was carried out to identify the predictive power of individual variables.
Results: The model predicted MMSE outcome at T3 with a mean AUC of 0.643. Model interpretability analysis revealed that the global cognitive state progression in AD patients is associated with: low spatial memory (Corsi block-tapping), verbal episodic long-term memory (Babcock's story recall) and working memory (Stroop Color) performances, the presence of hypertension, the absence of hypercholesterolemia, and functional skills inabilities at the IADL scores at baseline.
Conclusion: This is the first AI study to predict cognitive trajectories of AD patients using routinely collected clinical data, while at the same time providing explainability of factors contributing to these trajectories. Also, our study used the results of single cognitive tests as a measure of specific cognitive functions allowing for a finer-grained analysis of risk factors with respect to the other studies that have principally used aggregated scores obtained by short neuropsychological batteries. The outcomes of this work can aid prognostic interpretation of the clinical and cognitive variables associated with the initial phase of the disease towards personalized therapies
Preparing assessment literate teachers: A cross-national trend analysis
No full textPreparing teachers for assessment (i.e., assessment literacy) represents a contested issue, both at the educational policy and practice levels. Entering this debate, we explored patterns of initial teacher education (ITE), continuous professional development (CPD), assessment practices, and teachers’ learning needs in the assessment domain. Using data from the IEA-PIRLS teacher questionnaire (2011–2021) and the OECD-TALIS (2008–2018), a cross-national trend analysis was performed. Variability across countries and over time was found in both ITE and CPD. Furthermore, a mismatch emerged between perceived professional needs in the assessment domain and ITE and CPD paths. Teachers’ use of assessment strategies also varies, with homework being the most common practice among primary teachers - often in summative forms - while formative feedback and self-assessment are more frequent in lower secondary schools. Highlighting limitations in current large-scale survey instruments, this study calls for better alignment between teacher preparation and current models of assessment literacy
Direct Ammonia Solid Oxide Fuel Cell Stack: Modelling and Experimental Validation
Get PDFInterest in ammonia as an energy carrier is growing due toits superior storage and transport properties compared tohydrogen. The objective of this work is to construct auseful tool for predicting the behavior of a solid oxidefuel cell (SOFC) stack fed directly with ammonia. Thisconfiguration is particularly interesting because theinternal cracking of ammonia eliminates the need for anexternal cracker, thus reducing the overall cost of thesystem. The ammonia decomposition reaction was implementedin the anode channel of the stack and calibrated againstliterature results. The model was then validated in theohmic region only by calculating the area specificresistance (ASR) and comparing the results withexperimental data collected at the Bruno Kessler Foundation(FBK) laboratory. This SOFC model can therefore be used asa starting point for the analysis of a scale-up application