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Reframing involuntary treatment as a sentinel event: a model for improving rights-based mental health care
No full textBackground: The UN Convention on the Rights of Persons with Disabilities (CRPD) has sparked debates on psychosocial disabilities, particularly Article 12, which guarantees legal capacity without restrictions. The CRPD Committee opposes involuntary treatment and strongly advocates for support mechanisms to ensure autonomy. This raises questions about decision-making in psychiatric care and the role of involuntary treatment. Advocacy groups, which push for the elimination of involuntary treatment in favor of alternative measures, argue that involuntary treatment results from inadequate resources, while psychiatric associations highlight ethical concerns about withholding care and emphasize risks to service users and others. Methods: This article presents a model that reframes involuntary treatment as a preventable sentinel event. The approach outlines the components of a monitoring and quality improvement system, including structured reporting, root cause analysis, and co-designed interventions involving service staff members and service users. Results: The application of this model may identify key structural and systemic drivers of involuntary treatment, such as insufficient community-based services, lack of training, and power asymmetries. It also highlights the potential of participatory governance mechanisms and user-led monitoring to foster accountability and drive rights-based reforms. Conclusion: This approach may help align mental health services with CRPD principles, reduce involuntary treatment, and enhance accountability, legitimacy, and foster collaborative relationships between users and providers. It may also help overcome the current impasse around coercive practices by enabling the identification and analysis of the structural and cultural mechanisms that sustain them over time, thereby opening up new possibilities for their management and overcoming
Aerothermal–Structural Optimization of a High-Pressure Turbine Rotor With Robustness Evaluation to in-Service Deterioration
No full textThis article presents a multidisciplinary optimization conducted on the high-pressure turbine rotor of a commercial turbofan engine. The rotor geometry is parametrized using a compact orthogonal design space, and the system's response is studied under the aerodynamic, thermal, and structural aspects via high-fidelity numerical simulations. The analysis is conducted using proprietary Rolls-Royce flow and structural solvers. The objective functions considered for the aerodynamic, thermal, and structural disciplines are, respectively, high-pressure stage isentropic efficiency, peak near-wall gas temperature, and peak von Mises stress on the rotor. The optimization is constrained by rotor capacity and high-pressure stage reaction degree. On the final three-dimensional Pareto front, two designs are selected, achieving a peak stress reduction of 17.5 MPa and a peak temperature reduction of 27.5 K, respectively. The sensitivity of these optimal designs to in-service degradation is then evaluated by applying various degrees of deterioration to the nominal designs. This deterioration is intended to replicate the erosion and deformation patterns observed on in-service blades after different numbers of operational cycles. The aerothermal performance of the optima is verified at a higher fidelity by conducting unsteady simulations
Studiare i festival: fonti e metodi. Una ricerca sul campo fra giacimenti documentali e memorie orali
No full textIl contributo presenta la metodologia utilizzata nel progetto PRIN 2022 "Il teatro dei festival tra locale e globale", incentrato sui festival teatrali italiani fra anni Cinquanta e Settanta, indagati tramite un approccio che intreccia ricerca d'archivio e storia orale; il contributo dell'autrice si focalizza in particolare sul Festival Internazionale del Teatro in Piazza a Santarcangelo di Romagna
Associations between intraplaque hemorrhage and other high-risk plaque features in atherosclerotic plaques
No full textBackground: Little is known about the association between intraplaque hemorrhage (IPH) and other features of high-risk carotid atherosclerotic plaques, such as the presence of plaque ulceration, plaque enhancement, and lipid-rich necrotic core (LRNC). This study set out to assess the relationship between IPH and other vulnerable plaque features. Materials and Methods: A retrospective review was done of 102 patients with IPH in one or both of the internal carotid arteries (ICA) on neck MRA between 1/1/2016 and 3/31/2021. IPH was defined as a ≥200% signal intensity of the adjacent sternocleidomastoid muscle on MPRAGE images. All ICA plaques were assessed for the presence or absence of IPH, plaque ulceration, plaque enhancement, and LRNC, as well as IPH volume. IPH volume was measured manually by outlining the region of interest. Results: A total of 102 patients were included, with 88 (86.3%) being male. The average age was 73.5 years (SD = 9.0). Both IPH and LRNC were more commonly seen in the left carotid artery (p =.018 and p =.047, respectively). For right-sided ICAs, there was a significant association between IPH and LRNC (p <.0001). Lesions without IPH were more likely to have plaque enhancement than lesions with IPH (p =.04). For left-sided ICAs, there was also a significant association between the presence of IPH and LRNC (p <.0001). Conclusions: There is a significant association between the presence of IPH and LRNC. An inverse relationship was found between the presence of IPH and plaque enhancement for right-sided plaques. No associations were found between IPH and plaque ulceration
Selecting Between Clustering Methods: An Innovative Approach
No full textThe paper presents a new method for validating clustering partitions, addressing the challenges associated with assessing clustering algorithms when true class labels are unknown. Clustering algorithms aim to group similar objects, but determining the quality of these groupings can be difficult without external benchmarks. The proposed method combines internal and relative validation criteria with machine learning (ML) algorithms to create a ranking system for different clustering partitions. This method stands out by explicitly considering the structure of the dataset’s features and offering a robust solution for high-dimensional data.
Traditional validation methods for clustering include external, internal, and relative criteria. External criteria compare the obtained clustering results with known external classifications, but such information is not always available. Internal criteria rely solely on the dataset’s properties, like the proximity matrix, but they can fail to capture the true quality of the partitions. Relative criteria compare a set of partitions but do not take into account the dataset’s feature structure. The proposed method fills this gap by incorporating ML algorithms to assess the coherence between the clustering results and the dataset's features, making it more flexible and accurate in varied contexts.
The validation process works by using the assigned clusters as a response variable and the features of the dataset as independent variables in a machine learning model. The model's performance, represented by an index such as accuracy, sensitivity, or specificity, serves as an indicator of the clustering algorithm’s effectiveness. Rather than assessing the absolute quality of a partition, the method ranks partitions relative to one another. This ranking highlights the clustering algorithms that best capture the underlying structure of the data.
To test the effectiveness of the proposed approach, the authors conducted a simulation study. They generated datasets with varying levels of noise and applied 11 classical clustering algorithms. The ML-based validation method was then used to rank the partitions produced by these algorithms. The results showed that the method correctly ranked the partitions, with higher-quality partitions (those with less noise) receiving better rankings. This demonstrates the method's ability to rank partitions without knowing the true classification of the data, making it a powerful tool for cluster validation.
In comparison to other methods, the proposed approach offers several advantages. It does not require external reference labels, as with external validation methods. Additionally, it considers the structure of the dataset’s features, addressing limitations in internal and relative validation criteria. Moreover, it has the flexibility to handle high-dimensional data, which is often a challenge for existing cluster validation methods.
In conclusion, the proposed validation method provides a novel and effective way to rank clustering algorithms based on their ability to partition data according to its underlying structure. By leveraging machine learning algorithms, this method offers a more robust and versatile solution for cluster validation. The authors suggest future work could explore the method’s applicability to big data scenarios, where computational efficiency becomes crucial
Mediterranean Wild Edible Plants: Diversity, Conservation and Potential Use
No full textThe gathering and consumption of Wild Edible Plants (WEPs) has provided a fundamental resource for food security in the Mediterranean for centuries. WEPs are highly nutritious, well adapted to local environments, and deeply rooted in traditional cultures. However, they are currently disappearing due to changes in food systems and habitat degradation. Today, fewer than ten cultivated species account for 90% of the world’s caloric intake, while climate change increasingly threatens their cultivation. In this context, reintegrating WEPs into agricultural systems can contribute to dietary diversification and strengthen crop resilience.
This PhD thesis aims to explore the potential of Mediterranean WEPs in relation to the impacts of climate change, through an interdisciplinary approach that integrates ethnobotany and seed ecology. The research led to the development of the first comprehensive checklist of Mediterranean WEPs and a detailed analysis of their in situ and ex situ conservation status in the Levant region. Subsequently, germination tests were conducted on a subset of priority species at the Sardinian Germplasm Bank (BG-SAR), assessing their resilience under future climate scenarios. The results identify the species most suitable for sustainable food use and those of highest conservation priority, providing a foundation for local strategies of protection and valorisation
La transizione energetica e le Regioni: osservazioni a margine della sentenza della Corte costituzionale n. 184 del 2025
No full textCon la decisione in commento, la Corte costituzionale torna ancora una volta sul rapporto tra disciplina statale e leggi regionali nel quadro dei vincoli europei sulla transizione energetica verso fonti rinnovabili. La vicenda testimonia come, in ragione dell’esigenza di una disciplina uniforme, lo spazio di intervento che residua in capo ai legislatori regionali si sia estremamente compresso e, quindi, le Regioni debbano privilegiare la loro “vocazione amministrativa”
Retraducciones y mediaciones: La recepción de Laozi en América Latina entre el Tradicionalismo y la Contracultura
No full textThe reception of the Laozi in Latin America has been shaped mainly through European mediations that influenced both its translation and interpretation. This article examines two emblematic twentiethcentury retranslations: that of Onorio Ferrero, published in Peru in 1972, and that of Gastón Soublette, which appeared in Chile in 1990. Both share a spiritual and practical reading of the text, yet they respond to different intellectual contexts: Ferrero approaches it from Guénonian Traditionalism and its esoteric conception of Daoism, while Soublette interprets it through the lenses of counterculture and spiritual ecology, following the hermeneutical line established by Richard Wilhelm. Through a comparative analysis, the study shows how both versions reveal a tendency toward the domestication of the text and the perpetuation of Eurocentric hermeneutical frameworks, in which Daoism is adapted to the spiritual pursuits of Western modernity. It argues that this mediation reflects the epistemic asymmetries in the global circulation of knowledge, positioning Latin America in an intermediate space between reception and reinterpretation
All-Spiking ECG Analysis for Arrhythmia Classification on Low-Power FPGA
No full textAccurate and energy-efficient classification of cardiac arrhythmias is essential for real-time electrocardiogram (ECG) monitoring in wearable healthcare systems. This work introduces an end-to-end, spike-driven approach for ECG analysis, in which Spiking Neural Network (SNN) address arrhythmia detection on a event-based input. The signal encoding employs delta modulation on the raw ECG waveform as well as its first and second derivatives, capturing richer temporal and morphological features and enhancing classification performance compared to baseline approaches. Heartbeats are classified into five categories, as defined by the AAMI standard, achieving 98.4% accuracy on the MIT-BIH Arrhythmia Database. Unlike traditional methods, our approach removes the need for separate filtering, segmentation, or peak detection algorithms, relying instead on a unified, event-driven architecture. To support this enhanced processing methodology, we have implemented an optimized hardware architecture based on a low-power Lattice iCE40-UltraPlus FPGA. This design eliminates redundant computations by unifying peak detection and classification within the same processing pipeline, reducing power consumption while maintaining low inference times. Performance evaluations indicate an execution time of just 4.05 ms per classification, with energy usage optimized to 36.86 μJ, substantially outperforming existing FPGA-based solutions