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"Russo, Michele"
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AR in the Architecture Domain: State of the Art
Augmented reality (AR) allows the real and digital worlds to converge and overlap in a new way of observation and understanding. The architectural field can significantly benefit from AR applications, due to their systemic complexity in terms of knowledge and process management. Global interest and many research challenges are focused on this field, thanks to the conjunction of technological and algorithmic developments from one side, and the massive digitization of built data. A significant quantity of research in the AEC and educational fields describes this state of the art. Moreover, it is a very fragmented domain, in which specific advances or case studies are often described without considering the complexity of the whole development process. The article illustrates the entire AR pipeline development in architecture, from the conceptual phase to its application, highlighting each step’s specific aspects. This storytelling aims to provide a general overview to a non-expert, deepening the topic and stimulating a democratization process. The aware and extended use of AR in multiple areas of application can lead a new way forward for environmental understanding, bridging the gap between real and virtual space in an innovative perception of architecture.
Journal Article
Superbonus 110%. An Italian Government measure to boost Energy Efficiency
This paper examines the implementation and outcomes of the Superbonus 110%, a fiscal incentive mechanism for building renovation that operated in Italy during recent years. The Superbonus 110% program catalyzed significant revitalization within the Italian construction industry and substantially accelerated renovation works specifically targeting enhanced energy efficiency in residential structures. Notwithstanding considerable criticism, the experience suggests that the Superbonus 110% demonstrated sufficient efficacy to warrant consideration for reintroduction, albeit with substantive modifications as delineated in the concluding section of this analysis.
Journal Article
A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification
The recent years saw an extensive use of 3D point cloud data for heritage documentation, valorisation and visualisation. Although rich in metric quality, these 3D data lack structured information such as semantics and hierarchy between parts. In this context, the introduction of point cloud classification methods can play an essential role for better data usage, model definition, analysis and conservation. The paper aims to extend a machine learning (ML) classification method with a multi-level and multi-resolution (MLMR) approach. The proposed MLMR approach improves the learning process and optimises 3D classification results through a hierarchical concept. The MLMR procedure is tested and evaluated on two large-scale and complex datasets: the Pomposa Abbey (Italy) and the Milan Cathedral (Italy). Classification results show the reliability and replicability of the developed method, allowing the identification of the necessary architectural classes at each geometric resolution.
Journal Article
Melatonin and Myo-Inositol: Supporting Reproduction from the Oocyte to Birth
Human pregnancy is a sequence of events finely tuned by several molecular interactions that come with a new birth. The precise interlocking of these events affecting the reproductive system guarantees safe embryo formation and fetal development. In this scenario, melatonin and myo-inositol seem to be pivotal not only in the physiology of the reproduction process, but also in the promotion of positive gestational outcomes. Evidence demonstrates that melatonin, beyond the role of circadian rhythm management, is a key controller of human reproductive functions. Similarly, as the most representative member of the inositol’s family, myo-inositol is essential in ensuring correct advancing of reproductive cellular events. The molecular crosstalk mediated by these two species is directly regulated by their availability in the human body. To date, biological implications of unbalanced amounts of melatonin and myo-inositol in each pregnancy step are growing the idea that these molecules actively contribute to reduce negative outcomes and improve the fertilization rate. Clinical data suggest that melatonin and myo-inositol may constitute an optimal dietary supplementation to sustain safe human gestation and a new potential way to prevent pregnancy-associated pathologies.
Journal Article
Navigating the integration of large language models in healthcare: challenges, opportunities, and implications under the EU AI Act
Discussion Transformative potential of LLMs in healthcare LLMs are increasingly recognized for their ability to process vast datasets and generate human-like text, with applications spanning medical diagnostics, administrative tasks, and patient engagement [3]. LLMs process large datasets that may inadvertently include sensitive patient information, raising questions about data security and consent. Summary table: integration of large language models in healthcare Category Key points Transformative potential Streamlines clinical workflows with tasks like medical document summarization and discharge summaries Enhances medical education and personalized care through rapid synthesis of literature and tailored health advice Supports multimodal LLMs (M-LLMs) for integrating text, images, and sensor data to improve diagnostic accuracy Challenges Concerns over data privacy, particularly handling sensitive patient information Risks of biased outputs from nonrepresentative datasets perpetuating healthcare inequities Issues with model reliability and interpretability in critical clinical decisions Ethical concerns Ensuring fairness and transparency in AI-generated content Addressing biases to prevent exacerbating existing disparities in healthcare delivery Safeguarding patient trust through robust ethical and regulatory oversight Role of EU AI Act Establishes a risk-based framework categorizing AI systems by risk (limited, high, and unacceptable) Mandates transparency and prohibits high-risk systems like biometric categorization Encourages innovation via regulatory sandboxes, balancing progress with safety Future directions Calls for interdisciplinary collaboration among clinicians, technologists, and ethicists Promotes continuous evaluation and refinement of AI models to align with evolving healthcare needs Advocates for global standardization of regulations for consistent AI governance Conclusion LLMs present a dual-edged sword: immense potential to enhance healthcare delivery paired with challenges that demand meticulous oversight. Cascella, M; Montomoli, J; Bellini, V; Bignami, E. Evaluating the feasibility of ChatGPT in healthcare: an analysis of multiple clinical and research scenarios.
Journal Article
Machine Learning and Deep Learning for the Built Heritage Analysis: Laser Scanning and UAV-Based Surveying Applications on a Complex Spatial Grid Structure
The reconstruction of 3D geometries starting from reality-based data is challenging and time-consuming due to the difficulties involved in modeling existing structures and the complex nature of built heritage. This paper presents a methodological approach for the automated segmentation and classification of surveying outputs to improve the interpretation and building information modeling from laser scanning and photogrammetric data. The research focused on the surveying of reticular, space grid structures of the late 19th–20th–21st centuries, as part of our architectural heritage, which might require monitoring maintenance activities, and relied on artificial intelligence (machine learning and deep learning) for: (i) the classification of 3D architectural components at multiple levels of detail and (ii) automated masking in standard photogrammetric processing. Focusing on the case study of the grid structure in steel named La Vela in Bologna, the work raises many critical issues in space grid structures in terms of data accuracy, geometric and spatial complexity, semantic classification, and component recognition.
Journal Article
Inhibition of HuR/ELAVL-1 attenuates fibrotic progression in Mdx mice with dilated cardiomyopathy
Duchenne muscular dystrophy (DMD) arises from dystrophin deficiency, a crucial component of the dystrophin-glycoprotein complex (DGC) essential for maintaining cellular structural integrity by linking intracellular actin filaments to the basal lamina. Dysfunctions within this complex, coupled with increased inflammatory immune cell infiltration, contribute to the onset of dilated cardiomyopathy (DCM). This cardiac condition, characterized by necrosis and fibrosis, significantly impairs left ventricular function. Despite various treatment approaches, reliable effects on these pathogenic mechanisms remain elusive. RNA-binding proteins play pivotal roles in modulating pathways often dysregulated in cardiac pathology. Notably, HuR, which is upregulated in fibrotic cardiac regions and modulates innate immune system activation, emerges as a promising target. We investigated HuR expression in cardiac tissues of mdx murine model of DMD and assessed the impact of its inhibition with regards to DCM progression. Our findings reveal that HuR is indeed upregulated in mdx mice, and its inhibition leads to attenuation of cardiac fibrosis and improvement in heart function. These preclinical results underscore the potential of targeting HuR for therapeutic intervention to mitigate DCM-associated pathological changes, warranting further exploration for the development of effective treatments.
Journal Article
A Markov-model simulation of IVF programs for PCOS patients indicates that coupling myo-Inositol with rFSH is cost-effective for the Italian Health System
Accumulating evidence suggests that oral supplementation with myo-Inositol (myo-Ins) is able to reduce the amount of gonadotropins and days of controlled ovarian hyperstimulation (COS) necessary to achieve adequate oocyte maturation in assisted reproduction technology (ART) protocols, particularly in women affected by polycystic ovary syndrome (PCOS). We used computational calculations based on simulation modellings. We simulated in vitro fertilization (IVF) procedures—with or without intracytoplasmic sperm injection (ICSI)—with 100,000 virtual patients, accounting for all the stages of the entire IVF procedure. A Monte Carlo technique was used to account for data uncertainty and to generate the outcome distribution at each stage. We considered virtual patients with PCOS undergoing IVF cycles to achieve pregnancy. Computational data were retrieved from clinical experience and published data. We investigated three parameters related to ART protocols: cost of single procedure; efficacy to achieve ongoing pregnancy at 12 gestational weeks; overall cost per single pregnancy. The administration of oral myo-Ins during COH protocols, compared to the standard COH with recombinant Follicle Stimulating Hormone (rFSH) only, may be considered a potential strategy to reduce costs of ART for the Italian Health System.
Journal Article
Comparison of Rosuvastatin Versus Atorvastatin for Coronary Plaque Stabilization
Statins are widely used to lower cholesterol and to reduce cardiovascular events. Whether all statins have similar effects on plaque stabilization is unknown. We aimed to investigate coronary plaque response to treatment with different statins that result in similar lipid reduction using serial multimodality intracoronary imaging. Patients with de novo coronary artery disease requiring intervention were randomized to rosuvastatin 10mg (R10) or atorvastatin 20mg (A20) daily. Optical coherence tomography and intravascular ultrasound were performed at baseline, 6 months, and 12 months. Untreated nonculprit plaques were analyzed by optical coherence tomography for thin-cap fibroatheroma, minimum fibrous cap thickness, lipid arc, and lipid length. Total and percent atheroma volume, respectively were analyzed by intravascular ultrasound. Forty-three patients completed the protocol (R10: 24 patients, 31 plaques; A20: 19 patients, 30 plaques). The decrease in serum lipids was similar. From baseline to 6 months to 12 months, minimum fibrous cap thickness increased in the R10 group (61.4 ± 15.9 µm to 120.9 ± 57.9 µm to 171.5 ± 67.8 µm, p <0.001) and the A20 group (60.8 ± 18.1 µm to 99.2 ± 47.7 µm to 127.0± 66.8 µm, p <0.001). Prevalence of thin-cap fibroatheroma significantly decreased in the R10 and A20 groups (−48% and −53%, respectively, p <0.001 for intragroup comparisons). Only the R10 group had a decrease in macrophage density (−23%, p = 0.04) and microvessels (−12%, p = 0.002). Total atheroma volume decreased in the R10 group (109.2 ± 62.1 mm3 to 101.8 ± 61.1 mm3 to 102.5 ± 62.2 mm3, p = 0.047) but not in the A20 group (83.3 ± 48.5mm3 to 77.6 ± 43.0 mm3 to 77.9 ± 48.6 mm3, p = 0.07). In conclusion, although both statins demonstrated similar reductions in lipid profiles, the rosuvastatin group showed more rapid and robust plaque stabilization, and regression of plaque volume compared to the atorvastatin group.
Journal Article