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Dressed in Nature: Women and Text/Styles in Painting and Literature, from Renaissance Aesthetics to Pre‐Raphaelite Poetics and to Art Nouveau Painting
No full textThis contribution focuses on paintings and poetry, visualizing fashionable design in clothing, such
as flowers, foliage and greenery — characterizing pre-Raphaelite poetry and painting. This paper
analyses Sandro Botticelli’s Spring (1477–82) and its representation of clothing, flowers and natural
patterns which take on transformative, symbolical and connotative traits especially in Chloris’ metamorphosis. John Everett Millais’ Ophelia (1851–2) is then framed through Shakespeare’s Hamlet
and Rossetti’s poem The Portrait (1870). The nature-steeped poem The Lady of Shalott — which inspired the singer Loreena McKennit — is then made to address the photograph The Lady of Shalott
by the contemporary American-German photographer Julia Fullerton-Batten, who recreates John
William Waterhouse’s painting emphasizing the textile dimension and the symbolic power of greenery. This dialogue between painting and poetry foregrounds the description of garments and textiles,
their connection with the natural world, and human vs nonhuman kinship which offers symbolical,
allegorical and pictorial readings of artworks and poems. In conclusion, the critical analysis moves
on to Gustav Klimt’s painting The Kiss (1907–1908), example of Art Nouveau epitomizing this diachronic comparatist discourse and showing the culmination of all the elements discussed. This paper employs the frameworks of art history criticism, literary theory and environmental humanities
Why Are You Upset?A Framework for Dynamic Behavior Management in Child-Robot Interactions
No full textSocially assistive robots (SARs) are increasingly present in
educational settings, supporting teachers in typical classroom environments
by providing individualized attention to students. This paper introduces
a novel framework for dynamic behavior management in childrobot
interactions (CRI), leveraging Applied Behavior Analysis (ABA)
principles to enhance educational robotics. The system features a social
robot that (1) learns a model of a child’s goals, beliefs, and intentions,
grounded in observations and conversations to clarify the detected
behavior, and (2) responds effectively to behaviors by planning
appropriate sequences of actions to implement strategies suggested by
experts. The proposed architecture integrates real-time behavior monitoring,
functional behavior assessment (FBA), and adaptive response
planning, enabling socially assistive robots to facilitate individualized
learning experiences. By utilizing cloud-based processing and local execution,
as well as large language models (LLMs) and Planning Domain
Definition Language (PDDL), the robot dynamically adjusts its actions
based on the identified purpose of a child’s behavior, providing educational
activities, monitoring, and applying behavior management strategies.
Results from the experimental evaluations highlight the system’s
replanning and cloud response times, along with its overall effectiveness
Robust Bayesian inference for moving horizon estimation
No full textThe accuracy of moving horizon estimation (MHE) suffers significantly in the presence of measurement outliers. Existing methods address this issue by treating measurements leading to large MHE cost function values as outliers and subsequently discarding them, which may lead to undesirable removal of uncontaminated data. Also, these methods are solved by combinatorial optimization problems, restricted to linear systems to guarantee computational tractability and stability. Contrasting these heuristic approaches, our work reexamines MHE from a Bayesian perspective, revealing that MHE's sensitivity to outliers results from its reliance on the Kullback-Leibler (KL) divergence, where both outliers and inliers are equally considered. To tackle this problem, we propose a robust Bayesian inference framework for MHE, integrating a robust divergence measure to reduce the impact of outliers. Specifically, the proposed approach prioritizes the fitting of uncontaminated data and lowers the weight of outliers, instead of directly discarding all potential outliers. A tuning parameter is incorporated into the framework to adjust the degree of robustness, and the classical MHE can be regarded as a special case of the proposed approach as the parameter converges to zero. Our method involves only minor modification to the classical MHE stage cost, thus avoiding the high computational complexity associated with previous outlier-robust methods, making it inherently suitable for nonlinear systems. Additionally, it is proven to have robustness and stability guarantees, which are often missing in other outlier-robust Bayes filters. The effectiveness of the proposed method is finally demonstrated in a vehicle localization experiment. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies
Role of Abscisic Acid in the Whole-Body Regulation of Glucose Uptake and Metabolism
No full textAbscisic acid (ABA) is a hormone with a long evolutionary history, dating back to the earliest living organisms, of which modern (ABA-producing) cyanobacteria are likely descendants, which existed long before the separation of the plant and animal kingdoms, with a conserved role as signals regulating cell responses to environmental challenges. In mammals, along with the anti-inflammatory and neuroprotective function of ABA, nanomolar ABA regulates the metabolic response to glucose availability by stimulating glucose uptake in skeletal muscle and adipose tissue via an insulin-independent mechanism and increasing metabolic energy production and also dissipation in brown and white adipocytes. Chronic ABA intake of micrograms per Kg body weight improves blood glucose, lipids, and morphometric parameters (waist circumference and body mass index) in borderline subjects for prediabetes and metabolic syndrome. This review summarizes the most recent in vitro and in vivo data obtained with nanomolar ABA, the involvement of the receptors LANCL1 and LANCL2 in the hormone's action, and the importance of mammals' endowment with two distinct hormones governing the metabolic response to glucose availability. Finally, unresolved issues and future directions for the clinical use of ABA in diabetes are discussed
The Use of Proximal Femur Maturity Index in Guiding Brace Weaning for Adolescents Idiopathic Scoliosis
No full text
Evaluation of dynamic computer-assisted implant placement accuracy by means of a novel digital method: A feasibility clinical study
No full textPurpose: To present a novel digital method to evaluate dynamic computer-assisted implant surgery (dCAIS) accuracy comparing digital implant planning to real implant position. Methods: Twenty patients in need of implant supported single unit-crowns (SUC), were consequently treated following a standardized digital protocol encompassing (1) a diagnostic digital intra-oral scan (IOS), (2) a cone beam computed tomography (CBCT), (3) 3D digital implant planning, (4) dynamic navigated implant placement (X-Guide, X-Nav Technologies, LLC, Lansdale, PA, USA) and (5) a post-operative IOS with the scan body in situ. Implant position accuracy was evaluated by superimposing the post-operative IOS with the pre-operative digital planning and calculating the resulting angular deviation (o), global head deviation (mm) and global tip deviation (mm). Results: From the original 30 installed implants, 29 could be analyzed. All surgical procedures were successfully completed without any complication. The calculated mean angular deviation was 4.50° ± 2.59°, while the mean deviation at the implant head was 1.18 ± 0.52 mm. Finally, the global tip deviation was 1.43 ± 0.78 mm. Flapless implant placement was significantly associated with a reduction in both head and tip linear deviations (p = 0.026; p = 0.007), as well as with a significant reduction in angular deviation (p < 0.001). Implants placed in the anterior region showed a mean statistically significantly higher deviation at the implant head compared to those in posterior sites (difference: 0.39 mm; p = 0.043). Conclusions: Despite its limitations, the proposed digital method does represent a promising and patient friendly approach to evaluate dCAIS accuracy. Clinical significance: The proposed digital method represents a promising workflow for the evaluation of dCAIS implant placement avoiding the need of post-operative radiations
Diagnosed Patients With Chronic Hepatitis B and Delta Virus in Italy in 2024: An Estimation From a National Real‐World Database
No full textBackground and aims: Hepatitis B (HBV) and Hepatitis Delta virus (HDV) infection have undergone significant changes in Italy over the past few decades, but reliable and updated prevalence of chronic hepatitis B (CHB) and Delta (CHD) data are lacking. The aim of the study was to describe the epidemiology of CHB and CHD in Italy in 2024, based on real-world data. Methods: The number of patients with a healthcare expenditure exemption for CHB (016.070.32) and CHD (016.070.33) was obtained from 21 Regional Health Authorities. To understand how many CHB or CHD patients did not have these specific exemptions, a survey was conducted in 30 Gastroenterology, Hepatology and Infectious Diseases Units across the country. Results: Health Authorities data reported 67 514 and 5216 subjects with an exemption for CHB and for CHD, respectively. However, among 6775 CHB and 504 CHD patients, only 60.3% and 55.7% of them had the specific exemption, respectively. Based on these results, we estimated 111 960 (95% CI: 109 780-114 240) CHB and 9360 (95% CI: 8690-10 150) CHD patients, with a prevalence of 0.22% and 0.019% of the adult overall population. Moreover, anti-HDV prevalence was 7.7% from this cohort. Conclusion: Our study provides a plausible estimate of the current number of adult patients diagnosed with CHB and CHD in Italy and may be considered the basis for decision-making health policies
Virtual Reality as a Tool for Upper Limb Rehabilitation in Rett Syndrome: Reducing Stereotypies and Improving Motor Skills
No full textBackground/Objectives: Rett Syndrome (RTT) is a rare neurodevelopmental disorder that causes the loss of motor, communicative, and cognitive skills. While no cure exists, rehabilitation plays a crucial role in improving quality of life. Virtual Reality (VR) has shown promise in enhancing motor function and reducing stereotypic behaviors in RTT. This study aims to assess the impact of VR training on upper limb motor skills in RTT patients, focusing on reaching and hand-opening tasks, as well as examining its role in motivation and engagement during rehabilitation. Methods: Twenty RTT patients (aged 5–33) were randomly assigned to an experimental group (VR training) and a control group (standard rehabilitation). Pre- and post-tests evaluated motor skills and motivation in both VR and real-world contexts. The VR training involved 40 sessions over 8 weeks, focusing on fine motor tasks. Non-parametric statistical methods were used to analyze the data. Results: Results indicated significant improvements in the experimental group for motor parameters, including reduced stereotypy intensity and frequency, faster response times, and increased correct performance. These improvements were consistent across VR and ecological conditions. Moreover, attention time increased, while the number of aids required decreased, highlighting enhanced engagement and independence. However, motivation levels remained stable throughout the sessions. Conclusions: This study demonstrates the potential of VR as a tool for RTT rehabilitation, addressing both motor and engagement challenges. Future research should explore the customization of VR environments to maximize the generalization of skills and sustain motivation over extended training periods