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The Routledge Handbook on Cultural Heritage and Climate Justice
No full textThis volume contains contributions from over 60 authors from 20 countries exploring the importance of climate justice and equity in climate action. While focused on cultural heritage, its relevance extends into other fields including policy, just transitions, development studies and climate adaptation. Its central message is that climate action and climate justice are inseparable in our response to the climate crisis.
Key cross-cutting themes explored in 25 contributions and ten information boxes include economic and non-economic loss and damage with a particular focus on intangible cultural heritage, the importance of plural ways of knowing and bridging different epistemologies, the intersectionality of risk, loss and action with a particular focus on the historical and ongoing impacts of colonialism and other forms of historical injustice and the importance of community-centred approaches to climate action including climate literacy and education.
This book is targeted widely to those both within and outside of the heritage sector. It addresses themes of importance to those working in heritage practice and research, policy development and climate adaption and mitigation. It will also be of relevance to those working with communities impacted by climate change
Dual-Criterion Approach Incorporating Historical Information to Seek Accelerated Approval With Application in Time-to-Event Group Sequential Trials
Get PDFThe urgency of delivering novel, effective treatments against life-threatening diseases has brought various health authorities to allow for Accelerated Approvals (AAs). AA is the “fast track” program where promising treatments are evaluated based on surrogate (short term) endpoints likely to predict clinical benefit. This allows treatments to get an early approval, subject to providing further evidence of efficacy, for example, on the primary (long term) endpoint. Despite this procedure being quite consolidated, a number of conditionally approved treatments do not obtain full approval (FA), mainly due to lack of correlation between surrogate and primary endpoint. This implies a need to improve the criteria for controlling the risk of AAs for noneffective treatments, while maximizing the chance of AAs for effective ones. We first propose a novel adaptive group sequential design that includes an early dual-criterion “Accelerated Approval” interim analysis, where efficacy on a surrogate endpoint is tested jointly with a predictive metric based on the primary endpoint. Secondarily, we explore how the predictive criterion may be strengthened by historical information borrowing, in particular using: (i) historical control data on the primary endpoint, and (ii) the estimated historical relationship between the surrogate and the primary endpoints. We propose various metrics to characterize the risk of correct and incorrect early AAs and demonstrate how the proposed design allows explicit control of these risks, with particular attention to the family-wise error rate (FWER). The methodology is then evaluated through a simulation study motivated by a Phase-III trial in metastatic colorectal cancer (mCRC)
Individuation of predictive parameters of posterior cranial fossa decompression in pediatric patients with Chiari I malformation and autism spectrum disorder
No full textPurpose: There are no specific guidelines for posterior cranial fossa decompression (PCFD) in asymptomatic Chiari Malformation Type I (CM-I) patients with autism spectrum disorder (ASD). However, some studies suggest that surgery for symptomatic CM-I may improve ASD symptoms. This study aims to identify skull and brain morphometric parameters that could predict surgical outcomes in symptomatic CM-I with ASD, using artificial intelligence (AI). Methods: This study included pediatric patients diagnosed with both symptomatic CM-I and ASD who underwent posterior cranial fossa (PCF) surgery. Eleven morphometric parameters were measured using computed tomography (CT) and magnetic resonance imaging (MRI) scans, including cerebellar tonsil descent, tentorium length and angle, cerebellum-to-PCF area ratio, PCF-to-cerebrum area ratio, PCF height and diameter, and various distances involving the corpus callosum, pons, fastigium, foramen magnum, and clivus length. ASD symptom changes were assessed through phone interviews and outpatient evaluations. A binary tree classifier AI model was used to identify patients who improved post-surgically. Results: Our analysis showed that patients with a larger tentorium angle experienced some improvements in ASD symptoms after surgery, whereas those with a significantly smaller tentorium angle showed no improvement. AI identified a tentorium angle of 89.55° as a potential cut-off for distinguishing between outcome groups. No other morphometric parameters significantly influenced ASD symptom outcomes. Conclusions: This study evaluates the relevance of the tentorium angle width as a potentially valuable MRI-based morphometric parameter that could guide neurosurgeons in the decision-making process for this unique patient population. These findings may contribute to a more tailored approach for managing patients with CM-I and coexistent ASD
Few-Shot Bearing Fault Diagnosis with Multimodal LLMs and Prototypical Networks
No full textInitial release of the few-shot bearing fault diagnosis framework using multimodal LLMs and prototypical networks. Features: Support for multiple MLLMs: GPT-4o, GPT-5.1, Claude 4.5 Haiku/Sonnet, LLaVA-1.5-7B, Prototypical Networks baseline with ResNet-50 and Swin Transformer V2-T, 1-shot, 5-shot, and 10-shot evaluation, Automated metrics computation with confidence intervals, CWT image preprocessing for vibration signal analysis
"Governance approaches" to study planning systems
No full textPrevious comparative studies on spatial planning systems have revealed some critical issues: the weight to be attributed to planning cultures, the missing definition of the nature of the system itself and the limited usefulness of purely descriptive comparisons. Addressing these issues in the last two decades has led to a reconceptualisation of the planning system, centred on its social function (and construction) rather than on the multiplicity of possible characteristics. Recognising that the political process through which the public authority assigns the rights of spatial development matters at least as much as the technical function serving this process has led to the introduction of more articulated terminologies, such as ‘spatial governance and planning systems’. This progress has mainly matured in Europe through various research projects dedicated to the understanding and improvement of ‘territorial governance’ within the European Observation Network for Territorial Development and Cohesion (ESPON) programme. Three system models are currently recognised here which, according to the technical-political devices for assigning land rights, are usually defined as conformative, performative and neo-performative. Based on the characteristics of these institutional technology models and their ability to ensure public control over spatial development, a new typology of systems in Europe has been proposed. Overall, this indicates that systems that tend to assign rights on a case-by-case basis after the evaluation of projects would be more effective than the more traditional ones based on generalised binding zoning. While such typology of systems seems to find confirmation in the medium to long term data on land consumption in Europe, the concept of institutional technology has also proved useful for studying the phenomenon of the “Europeanisation” of territorial governance
The invisible problem of microplastics and microfibres in karst systems and aquifers: a multidisciplinary approach
Get PDFL'abstract è presente nell'allegato / the abstract is in the attachmen
NeSyLAD: A Neuro-Symbolic Approach for Unsupervised Logical Anomaly Detection
No full textDetecting logical anomalies in industrial settings remains a significant challenge for conventional anomaly detection methods. Unlike structural anomalies such as scratches or dents, logical anomalies involve violations of component relationships, quantities, and arrangements that require reasoning about complex constraints. In this paper, we propose a NeuroSymbolic Logical Anomaly Detection (\methname) framework that combines deep learning-based component segmentation with symbolic rule extraction and logical reasoning. Our approach extracts interpretable rules from neural network activations and applies logical reasoning to detect and explain anomalies in industrial images. We evaluate our approach on the MVTec LOCO dataset, demonstrating its effectiveness in detecting logical anomalies across various product categories including breakfast boxes, juice bottles, screw bags, pushpins, and splicing connectors. Experimental results show that our approach not only achieves high detection accuracy but also provides human-readable explanations of detected anomalies, making it particularly valuable in industrial quality control settings
Effect of resultant force direction in machining of single crystal (100)Ge
No full textOn-axis single point diamond turning experiments were conducted on (100)Ge to investigate the relation between the direction of the resultant force and the surface topography. This was done by measuring cutting and thrust forces for feedrates ranging from 0.3 μm/rev to 12 μm/rev. The geometrical relation between the resultant force, slip systems and fracture systems was investigated using the Schmid factor Sf and the fracture factor Ff. Their ratio
was used to identify the cutting directions that were more favorable for slip and fracture. The surface topography, measured by AFM, corresponded with the
prediction. Three regimes were identified on (100)Ge depending on the resultant force angle f. When φ . When 40° and . When φ > 55°, fracture is predicted for cutting directions along . The study of
for the Ge lattice indicates that fracture is the most favorable when the force is aligned with the and direction families. This study shows that the slip and fracture systems can be used in machining of Ge in order to suppress fracture and favor shear deformation
BIM-to-BEM Framework for Energy Retrofit in Industrial Buildings: From Simulation Scenarios to Decision Support Dashboards
Get PDFThe digital and ecological transition of the industrial sector requires methodological tools that integrate information modelling, performance simulation, and operational decision support. In this context, the present study introduces and tests a semi-automatic BIM-to-BEM framework to optimise human–machine interaction and support critical data interpretation through Graphical User Interfaces. The objective is to propose and validate a BIM-to-BEM workflow for an existing industrial facility to enable comparative evaluation of energy retrofit scenarios. The information model, developed through an interdisciplinary federated approach and calibrated using parametric procedures, was exported in the gbXML format to generate a dynamic, interoperable energy model. Six simulation scenarios were defined incrementally, including interventions on the building envelope, Heating, Ventilation and Air Conditioning (HVAC) systems, photovoltaic production, and relamping. Results are made accessible through dashboards developed with Business Intelligence tools, allowing direct comparison of different design configurations in terms of thermal loads and indoor environmental stability, highlighting the effectiveness of integrated solutions. For example, the combined interventions reduced heating demand by up to 32% without compromising thermal comfort, while in the relamping scenario alone, the building could achieve an estimated 300 MWh reduction in annual electricity consumption. The proposed workflow serves as a technical foundation for developing an operational and evolving Digital Twin, oriented toward the sustainable governance of building–system interactions. The method proves to be replicable and scalable, offering a practical reference model to support the energy transition of existing industrial environments
A Web-Based Georeferenced Model of the Urban Traction Electrification System in Turin
Get PDFTransport accounts for approximately 25% of Green House Gas emissions in Europe, with urban road transport being a major contributor to air pollution. Decarbonizing urban transport is essential, particularly as over 70% of Europeans reside in urban areas. Strengthening public transport, the most sustainable travel option for large populations, is a key strategy. This article focuses on urban tramways, formed by the urban traction electrification systems and electric public transport vehicles. A digital twin approach is proposed to improve the operational activities of tramways, aiming to optimize system design, enhance maintenance, improve reliability, and unlock unused infrastructure potential, such as using the tramway infrastructure for off-peak charging stations. This article presents the methodology adopted to develop the model of the tramway in Turin, Italy. This step is a milestone to implement the tramway digital twin. Moreover, this article presents the validation process of the model, which was carried out through a comparison with both simulated and field measurement data