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New discoveries reveal unexpectedly wide taxonomic diversity and call for a new classification of the green algal family Prasiolaceae (Trebouxiophyceae)
No full textAlgal lineages with small size and low morphological complexity are typically among the most difficult to resolve taxonomically. They are often characterized by high levels of cryptic diversity and environment-driven plasticity that complicate species recognition. Their full taxonomic diversity is even more difficult to unravel when their evolution has also resulted in great ecological diversity, encompassing many different habitats including unusual ones. An example of this case is the Prasiolaceae, a family of filamentous, leafy and packet-like green algae occurring in marine, freshwater and terrestrial environments. They are well known for their preference for habitats subject to high loads of organically derived nutrients, mainly in the form of seabird guano found in upper littoral habitats. In recent years, new surveys and new molecular phylogenetic studies have produced the surprising discovery of many new lineages, revealing an unexpected high taxonomic diversity. DNA sequence data obtained from cultured strains called for the description of several new genera and species. Prasiola, type genus of the family, was subjected to a major rearrangement. The genus was shown to be polyphyletic, which required its splitting into four genera: the real Prasiola (in which the type species Prasiola crispa belongs), Eaprasiola, Mariprasiola and Vittaprasiola. The marine species of this grouping, classified in the genus Mariprasiola, represent a remarkable case: they exhibit clear morphological and life history differences, although sequences of the most common markers used for species delimitation are identical. Conversely, in the genus Vittaprasiola DNA sequence divergence demonstrates the existence of cryptic entities that require separation at species level. Further studies of this group should expand the body of molecular markers available and, in combination with fieldbased studies making use of environmental DNA, might reveal an even higher phylogenetic and taxonomic diversity
Detection of Diabetic Retinopathy Using Deep Learning
No full textThe human eye is a complex organ responsible for vision, enabling us to perceive the world in intricate detail. Diabetes, a metabolic disorder characterized by chronic high blood sugar levels, can lead to severe complications, including heart disease, kidney failure, and vision impairment. One such vision-threatening condition is Diabetic Retinopathy (DR), a progressive disorder that can cause blindness if left untreated. Early detection is crucial for preventing further retinal damage and preserving vision. The proposed methodology exploits the VGG-16 deep learning model, known for its robust feature extraction capabilities, to accurately classify DR stages. To address the class imbalance in the dataset, Synthetic Minority Over-sampling TEchnique and Tomek Links are employed. The model is trained on a dataset of 88702 retinal images, categorized into five DR stages: No DR, Mild DR, Moderate DR, Severe DR, and Proliferative DR. Performance evaluation metrics, including accuracy, precision, recall, F1 score, and support, are analyzed and discussed to validate the effectiveness of the proposed approach
Le forme di autoregolamentazione del processo costituzionale. I poteri della Corte costituzionale nella “disciplina” del giudizio in via incidentale
No full textIl volume indaga le diverse forme di autoregolamentazione del proprio processo di cui è dotata la Corte costituzionale italiana, con particolare riferimento alla disciplina dei giudizi in via incidentale. Da un lato, si ricostruiscono i presupposti, la genesi e l’evoluzione storica del singolare potere di autonormazione di cui alle Norme integrative; dall’altro, si mette in luce come la capacità di autoregolamentazione processuale della Corte si sia espressa sin da subito anche in via prettamente giurisprudenziale, tramite un amplissimo uso dei suoi poteri di interpretazione e di integrazione della scarna e lacunosa disciplina normativa. L’analisi unitaria e integrata dei due peculiari strumenti - entrambi espressione dell’unicità della posizione e delle attribuzioni costituzionali della Corte - trae origine dal rilievo del loro inscindibile nesso di interdipendenza
Continuous Dynamic Monitoring and Model-Based Damage Assessment of a RC Frame Building
No full textThe study focuses on Structural Health Monitoring (SHM) for early damage detection and localization in civil structures, which is crucial for safety and prompt intervention after extreme events. A model-based methodology originally developed for masonry towers is adapted to a reinforced concrete frame building. By tracking natural frequencies using a few strategically placed sensors, structural damage can be identified and localized, as damage induces frequency changes tied to its location. The SHM strategy includes three key steps: (1) simulating damage scenarios with a calibrated structural model to create a Damage Location Reference Matrix (DLRM) based on frequency shifts; (2) detecting damage through statistical analysis of continuously monitored frequencies; and (3) localizing damage by comparing detected frequency changes to those in the DLRM. This approach is applied to a 54-m-tall RC frame building from the 1980s, permanently instrumented with 5 accelerometers. The FE model of the building is calibrated using the modal data from the initial ambient vibration testing. Modal parameters from continuous monitoring are identified using an automated SSI-based technique, with environmental effects mitigated via Principal Component Analysis (PCA). Subsequently, three damage scenarios are inflicted on the identified natural frequencies, showing the DLRM method's effectiveness in identifying damage. The findings highlight the feasibility of using limited sensors and model-based techniques for precise damage localization in RC structures
Handling emergency calls overload; the 112 Response Services during the COVID-19 pandemic in Liguria, Italy
Get PDFThe COVID-19 pandemic severely disrupted healthcare systems worldwide, generating widespread public concern. During the early stages, the European Emergency Number 112 – a standardized hotline providing access to emergency services across EU countries – faced an unprecedented surge of calls as citizens sought guidance. This study advances the hypothesis that emergency calls generate a form of collective intelligence, capturing real-time patterns in population behavior and healthcare system stress, thereby providing empirical evidence to inform policy and operational responses during public health crises. Focusing on the 112 Response Services in Liguria, Italy, during March 2020, the research investigates operational challenges and addresses four key questions: (1) How did the surge in calls affect operational efficiency? (2) How did rising COVID-19 cases and national containment measures influence call volumes? (3) Which factors primarily drove systemic overload in the emergency communication network? (4) Which strategies were implemented to mitigate challenges in emergency communication and response? Employing a mixed-methods approach, the study combines quantitative analysis of call volumes, call types, and COVID-19 data with qualitative analysis of government decrees and interviews with 112 regional managers. Findings indicate that, beyond managing medical emergencies, 112 Response Services played a pivotal role in addressing public uncertainty regarding governmental measures. A substantial portion of calls were non-urgent informational inquiries, contributing to system overload. In response, managers implemented adaptive strategies that effectively preserved service quality, offering valuable insights for managing future crises. These results underscore the critical role of citizen-reported data within healthcare systems. By delivering near real-time insights into public concerns, 112 Response Services support evidence-based decision-making, thereby guiding the development of more resilient crisis management strategies for future public health emergencies
Bad signals? Foreign aid and tax morale across Sub-Saharan Africa
Get PDFDoes exposure to foreign aid projects affect citizens’ attitudes towards the state? We examine this question by combining geo-coded data on World Bank aid projects and survey data for 30 Sub-Saharan African countries. We compare individuals across administrative units that vary in the presence and type of aid projects and complement this approach with an unexpected event design that accounts for potential selection concerns. In both analyses, we find that projects focusing on public goods that do not involve the state reduce citizens’ tax morale. However, in locations where the state is not expected to be a public goods’ provider, externally provided public goods do not curb citizens’ tax morale. We interpret these results as evidence of foreign aid sending a public signal of the state's inability to deliver basic services. Our results can inform multilateral donors on the types and targets of interventions that can backfire on the state
Urban Sprawl Monitoring by VHR Images Using Active Contour Loss and Improved U-Net with Mix Transformer Encoders
Get PDFMonitoring the variation of urban expansion is crucial for sustainable urban planning and cultural heritage management. This paper proposes an approach for the semantic segmentation of very-high-resolution (VHR) satellite imagery to detect the changes in urban sprawl in the surroundings of Chan Chan, a UNESCO World Heritage Site in Peru. This study explores the effectiveness of combining Mix Transformer encoders with U-Net architectures to improve feature extraction and spatial context understanding in VHR satellite imagery. The integration of active contour loss functions further enhances the model’s ability to delineate complex urban boundaries, addressing the challenges posed by the heterogeneous landscape surrounding the archaeological complex of Chan Chan. The results demonstrate that the proposed approach achieves accurate semantic segmentation on images of the study area from different years. Quantitative results showed that the U-Net-scse model with an MiTB5 encoder achieved the best performance with respect to SegFormer and FT-UNet-Former, with IoU scores of 0.8288 on OpenEarthMap and 0.6743 on Chan Chan images. Qualitative analysis revealed the model’s effectiveness in segmenting buildings across diverse urban and rural environments in Peru. Utilizing this approach for monitoring urban expansion over time can enable managers to make informed decisions aimed at preserving cultural heritage and promoting sustainable urban development
Stress Analysis in Single-Lap Adhesive Joints: Comparison of Unreinforced, Reinforced and Prestressed Configurations Assembled with Brittle Structural Adhesives
Get PDFAdhesive joints provide an effective and lightweight solution for the assembly of structures and offer both mechanical and operational advantages over conventional mechanical fastening systems. In this study, a new single-layer adhesive joint is investigated in which a thin, pretensioned textile reinforcement is inserted into the adhesive layer. In the first part, a simplified analytical model is proposed to describe the distribution of axial stresses in the adhesives and the reinforcement as well as the shear stresses in the adhesive layer. In the second part, the effects of geometric, mechanical and loading variables are investigated in a parametric analysis, focussing on the role of the initial pre-compression on the tensile response of the joint. The third part of this study compares the theoretical results with experimental data obtained with static tests on specimens made of unreinforced GFRP and epoxy resin. The results show small deviations (3–8%) between model and test. Finally, a simplified method for estimating the load-bearing capacity of brittle joints, both conventional and reinforced, is proposed. It is shown how the introduction of reinforcement and prestressing can modulate the stiffness and improve the stability of the joint without significantly affecting the load-bearing capacity
Urinary Cell-Free DNA as a potential diagnostic biomarker for bladder cancer in older adults
No full textPhoto-selective nets on flat peach: a study in central Italy
No full textThe use of photo-selective anti-hail nets represents one of the latest technical advancements in fruit cultivation, offering an improvement over commonly-used anti-hail or anti-insect nets. These nets can protect crops from excessive radiation, as well as from hail and pests, while simultaneously enhancing the environment beneath them in terms of temperature and humidity. However, there may be some potential side effects such as reduced yields and/or quality, hence the characteristics of the nets (mesh type, colour, shading) must be tailored to the climate and the specific plant species and cultivars. In 2021, a study was conducted on the flat peach (Prunus persica (L.) Batsch. var. compressa Bean.) cultivar ‘Platibelle’. Photo-selective anti-hail nets of different colours (red, yellow, pearl with mesh size of 2.4×4.8 mm) were tested to assess their effect on the physiological and productive response of the plants. Some differences were observed in the qualitative and quantitative characteristics of the fruit: under the yellow net, the fruits had greater weight and diameter. Similar behaviour was observed in the gas exchange of the plants under different colours, although shading was greater under the red net. These data can help understand the effect of different net characteristics and assist producers in choosing the best net to achieve their objective