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Training pathways and formal curricula in robotic bariatric surgery: a systematic review
No full textThe adoption of robotic platforms in bariatric and metabolic surgery has increased steadily, raising important questions
regarding how surgeons are trained to safely acquire robotic skills. While structured and competency-based training
models are increasingly adopted in other fields of robotic surgery, training approaches in robotic bariatric surgery remain
less standardized. A systematic review was conducted in accordance with PRISMA 2020 guidelines to identify studies
describing structured training pathways or formal curricula for robotic bariatric surgery. PubMed, Embase, Scopus, and
Cochrane Library, were searched from inception without date restrictions. Eligible studies explicitly reported training
programs, curricula, or educational pathways for robotic bariatric procedures. Learning curve analyses without a defined
curriculum were excluded. Data were synthesized using a structured narrative approach. Five studies met the inclusion
criteria. Training models included stepwise intraoperative curricula, simulation-based and proficiency-driven programs,
and modular educational interventions. Common components across curricula were simulation training, task decomposition,
supervised progression, and defined competency benchmarks. Assessment strategies were heterogeneous and ranged
from simulation-based proficiency thresholds to operative participation metrics and subjective workload measures. No
study reported standardized certification or long-term competency outcomes. Structured training pathways for robotic bariatric
surgery have been described and incorporate elements aimed at supporting safe skill acquisition. However, existing
curricula remain heterogeneous and lack standardized assessment frameworks. Future efforts should focus on developing
competency-driven and proficiency-based progression training models to support reproducible and safe adoption of robotic
bariatric surgery
Spatial resolution characterization of a clinical Photon Counting Computed Tomography
No full textComputed Tomography (CT) is a cornerstone of diagnostic imaging but conventional systems, equipped with energy-integrating detectors (EIDs), present limitations in spatial resolution, noise, and tissue contrast. Photon-Counting CT (PCCT) addresses these limitations using photon-counting detectors (PCDs) that directly convert incoming X-ray photons into electric signals, enabling energy discrimination, material quantification, and virtual monoenergetic image reconstruction. Clinical applications have already included cardiovascular, thoracic, and neuroimaging examinations. We performed a characterization of the spatial resolution of the first clinical PCCT scanner, the Naeotom Alpha® (Siemens Healthineers), equipped with CdTe PCDs. High-contrast presampled Modulation Transfer Function (MTF) was measured using a custom-built tungsten wire phantom tilted by 3∘C. Spatial resolution in radial and tangential was evaluated by shifting the phantom within the field of view. Three acquisition protocols were tested (head, abdomen/thorax, inner ear), including standard and Ultra-High Resolution (UHR) modes. Images were reconstructed with multiple iterative algorithms and kernels, and MTF analysis was automated via Python. Results showed that spatial resolution increases with sharper reconstruction kernels across all anatomical protocols, with negligible differences between standard and vascular algorithms. UHR mode significantly improved resolution in the inner ear protocol (f50% from 0.56 to 0.73 mm-1; f10% from 0.87 to 1.09 mm-1). In conclusion, this work provides an initial assessment of PCCT spatial resolution for acquisition protocols and reconstructions usually adopted in clinical routine. Future investigations will employ standardized phantoms and comparisons with other CT systems to further validate performance and assess its potential to enhance diagnostic imaging quality
From glacier retreat to proglacial dynamics: a multi-scale, multi-method perspective since the Little Ice Age
No full textGlacial and proglacial environments are rapidly changing in response to climate warming, resulting in glaciers fragmentation, rapid proglacial geomorphological change, and increased hazard potential. We investigate these processes in a glacierized catchment at the head of the Valtournenche Valley (western Italian Alps). To assess glacial and proglacial changes across multiple temporal and spatial scales, we integrated historical imagery, orthophotos, repeated Unmanned Aerial Vehicle (UAV) surveys, and field observations. Historical aerial images and orthophotos were used to repeatedly map geomorphological features as they evolved and to quantify glacier retreat and fragmentation since the Little Ice Age (LIA). The two glaciers in the study area have lost half of their surface area since 1820, and around 2005 the upper and lower sectors completely disconnected, leading to increased retreat from an average of 4.3 m/year (1956-2005) to 13.0 m/year (2005-2024). This highlights the strong influence of glacier fragmentation on the acceleration of glacier shrinkage, a process relevant to other alpine glacierized settings. Without any connection with the upper part, the ice front is becoming increasingly steeper and more concave, meaning that there is no longer any downstream ice movement, i.e. a dead-ice body. Annual-scale changes (from 29/08/2024 to 05/08/2025) of the dead-ice body and adjacent proglacial plain were analysed using two high-resolution (0.05 m) UAV-derived DEMs; after error assessment, surface and volume changes were quantified. The geomorphological features that exhibited the greatest losses in volume and surface elevation were the dead-ice body (-5,18 x 104 m3, -0,6 m) and its ice cliff (-5,67 x 104 m3, -1,9 m). It was also detected a proglacial plain volume change of +2,19 x 103 m3 (or +0,05m of surface elevation), due to the reworking and deposition of the debris from the dead-ice body. The availability of loose material, transported downstream by these sediment fluxes, increases the likelihood of potentially dangerous mass-transport events. Overall, these results provide new insights into the integrated evolution of an alpine glacial–proglacial landsystem, linking glacier fragmentation, stagnation, melt and associated sediment reworking to rapid downstream geomorphological changes
Disclosure, Explainability e Human Oversight: nuovi diritti fondamentali nell’era dell’IA e dei Private Governors
No full textEvaluating Urban Perception: Using Explainable Machine Learning Predict Through the Best Pipeline
No full textUnderstanding subjective urban experiences is essential for designing cities that enhance well-being. Urban design should account for the psychological effects of environments on individuals, as these significantly shape perceptions and behaviors. However, a major challenge is the limited availability of urban perception data. Recent studies have leveraged large, crowdsourced datasets like Place Pulse 2.0 (PP2) to inform machine learning (ML) models for urban perception prediction, but the accuracy and reliability of outcomes remain underexplored. There is a critical need to evaluate whether these datasets truly capture human perceptions. This study investigates the role of urban street images in understanding environmental perceptions, using the PP2 dataset and ML techniques. It explores various ML pipelines, employing TPot AutoML for model selection and 5-fold cross-validation to prevent overfitting. The goal is to identify the most efficient model that strengthens the link between automated predictions and human perception. The study also applies SHAP (SHapley Additive exPlanations) to interpret model outputs, revealing feature importance and interactions. This improves transparency and ensures ML-generated insights are actionable for urban planning. By rigorously testing ML pipelines, this research enhances predictive accuracy and contributes to the development of reliable urban design tools. The findings highlight ML’s potential in processing large-scale perception data, uncovering hidden patterns, and informing people-centered urban planning. However, further validation against real-world surveys is necessary to ensure robustness and generalizability in assessing urban perceptions
LA CIRCOLAZIONE DELL¿EDITORIA SPERIMENTALE RELATIVA ALLE RICERCHE ARTISTICHE VERBOVISUALI DEL NOVECENTO
No full textThis dissertation offers a historical examination of experimental publishing practices associated with verbovisual research in Italy during the second half of the twentieth century. Within this landscape – an intricate mosaic of languages, printing techniques, and modes of dissemination – the magazine “Ana Eccetera” stands at the center of the investigation. Founded in Genoa by Anna Bontempi, Martino Oberto, and Gabriele Stocchi, “Ana Eccetera” established itself, over its thirteen years of activity (1958-1971), as a crucial national and international platform promoting a complex theoretical and aesthetic discourse that brought together language theory, poetry, and the visual arts. This discourse is reconstructed through an analysis of the issues to underline the intellectual development of Martino Oberto, its principal theorist.
The study further investigates its strategies of circulation, shaped by an anarchic attitude that
deliberately resisted the mechanisms of the official cultural system and its market, favoring instead alternative models grounded in personal exchange and collaboration. This dimension is illuminated through a reconstruction of “Ana Eccetera”’s connections with the Milan-based publisher Vanni Scheiwiller, the editorial collective of the Belgian independent magazine “Phantomas”, and the Neapolitan artist Luciano Caruso – who played a decisive role in both the evolution and dissemination of the magazine’s ideas.
The final section explores the influence of “Ana Eccetera” on later editorial ventures, focusing in particular on the early work of verbovisual artist Ugo Carrega, who between 1963 and 1969 developed his practice within the journal’s editorial circle. Focusing on “TOOL. Quaderni di scrittura simbiotica” (1965-1967) and “āāā. azioni off kulchur” (1969), the dissertation highlights Martino Oberto’s impact on Carrega’s artistic trajectory, especially in relation to the tension between creative autonomy and the commodification of artistic work
Estimating spatial and temporal variability of crop growth by radiation-driven models based on satellite data assimilation
No full textPrecision agriculture aims to improve field management by accounting for spatial variability in dynamic cropping systems (CS). To support farmers in optimizing crop management, it has become important to develop tools that capture both spatial and temporal heterogeneity within crop production. Mechanistic crop models simulate aboveground biomass (AGB) accumulation by explicitly representing physiological and environmental processes linking absorbed solar radiation, transpiration, and nutrient uptake. However, these process-based models typically require site- and cultivar-specific calibration and often fail to capture fine-scale variability. Assimilating remote sensing (RS) data into radiation-driven Production Efficiency Models (PEM; Monteith, 1977; McCallum et al., 2009), offers a promising solution by providing spatio-temporal explicit predictions of biomass growth, and thus crop requirements or responses.
A PEM was developed and implemented in a PostGIS database to run at a daily time steps and with Sentinel-2 (S2) resolution (10 x 10 m). Leaf Area Index (LAI), derived from the S2 biophysical processor (Weiss et al., 2020), was assimilated daily to estimate the fraction of intercepted solar radiation by crops at pixel level via the Lambert–Beer law.
The PEM was calibrated and evaluated for wheat and maize grown in the Po Valley (northern Italy) using two independent datasets. Calibration relied on 120 AGB observations (2022-2023) from five different sites with different management practices, while evaluation was carried out on 312 observations (2025) from four additional sites.
Although the temporal and spatial dynamics of LAI should implicitly reflect the effects of limiting factors, a development stage-dependent Morris sensitivity analysis (SA) was conducted to assess how variations in LAI dynamics, air temperature, and senescence affect simulated AGB.
The simulations performed for each S2 pixel provide reliable estimates of AGB. On evaluation, the model achieved a relative Root Mean Square Error of 0.23 and a model efficiency of 0.92, effectively capturing temporal and spatial variability across and within the different CS (Figure 1). Assimilating LAI enabled the model to overcome common limits of process-based models that require site- and crop-specific tuning. SA highlighted that LAI accuracy during early growth stages strongly affects AGB predictions and in-season decisions. From stem elongation onward, radiation use efficiency (RUE) and temperature responses became dominant drivers, with senescence adjustment from milk ripening stage preventing overestimation at harvest.
Integrating daily LAI assimilation into a simplified radiation-driven framework captured spatial and temporal variability across crops, sites, management systems and seasons. Accurate early-season LAI estimates are critical, while RUE, temperature, and senescence primarily drive AGB growth in later stages. By assimilating RS data, the model overcomes common limitations of process-based approaches and provides a robust tool for monitoring crop productivity across heterogeneous CS
Complexity Results on the Bi-Level Interdiction Knapsack Problem with Unit Interdiction Costs or Unit Weights
No full textIn this contribution we pursue the study of the Bi-level Interdiction Knapsack Problem, where a leader interdicts some knapsack items subject to a budget constraint in order to maximally reduce the total profit of the Knapsack Problem that the follower solves on the remaining items. We study the computational complexity of the problem when the leader’s interdiction costs are unitary and prove that the problem remains Σ2p-complete using a reduction from the bi-level 3-SAT problem. Additionally, we prove that the version with unitary lower level weights but arbitrary interdiction costs is NP-complete
Die Transformation der öffentlichen Verwaltung durch Digitalisierung, Automatisierung und KI-Einsatz
No full textThe present analysis examines the impact of automation on public administration, with a particular focus on the use of artificial intelligence (AI). The article uses the example of the "trompe l'oeil effect" and the "default effect" to shed light on the challenges that arise for public law and its guarantees in an environment where the boundaries between full and partial automation are becoming increasingly blurred.Die vorliegende Analyse untersucht die Auswirkungen der Automatisierung auf die öffentliche Verwaltung, wobei der Fokus insbesondere auf dem Einsatz von künstlicher Intelligenz (KI) liegt. Der Beitrag beleuchtet am Beispiel des Trompe-l’Oeil-Effekts sowie des Default-Effekts öffentlicher Bediensteter die Herausforderungen, die sich für das öffentliche Recht und seine Garantien in einem Umfeld ergeben, in dem die Grenzen zwischen Voll- und Teilautomatisierung zunehmend verschwimmen
