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AXIAL-FLOW PUMP/INTAKE FLUID DYNAMIC INTERACTIONS: NUMERICAL PREDICTIONS OF OUTBOARD DYNAMIC-INLET WATERJETS OPERATING UNDER INLET DISTORTION
No full textThe Outboard Dynamic-inlet Waterjet (ODW) has already proved to innovate marine propulsion, outperforming existing technologies during near-nominal operations. Representing the naval equivalent to aero-engines, ODWs operate independently, isolated from the ship. Therefore, as in aviation the propulsive performance strictly depends on the quality of the free-stream, a similar behaviour is expected on ODWs, potentially compromising its mission envelope. With the existing literature discussing the details of nominal operations, the present numerical study aims to address the issues occurring when the system experiences inlet distortion. A structured computational domain is generated around the full annulus geometry, derived by matching an axisymmetric inlet with an axial-flow pump. Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations, coupled with k − w SST and Zwart models for turbulence and cavitation, respectively, are solved to simulate the flow past an ODW operating with a 16◦ free-stream incidence, as pump blades rotate at 1400 r pm. The solution indicates that the entering flow separates on the lower half of the propulsor, breaking into several vortical structures downstream. These vortexes time evolution obstructs the capture stream-tube, deteriorating its distribution. Pump non-uniform inflows affect the incidence on rotor blades, resulting in unbalanced loads and anticipated tip cavitation in the lower right quadrant
Racconti teatrali di molte città. Contatti, appropriazioni, migrazioni, relazioni teatrali fra Parigi e le capitali occidentali (1789-1855)
No full textIl volume comprende gli atti del convegno "Racconti teatrali di molte città. Contatti, appropriazioni e migrazioni fra Parigi e le capitali occidentali (1789-1855)", tenutosi a Padova il 16 e 17 maggio 2024. I contributi raccolti approfondiscono i meccanismi di scambio tra le culture teatrali delle capitali occidentali intendendo indagare la progressiva assunzione del ruolo di centro dominante delle attività performative ottocentesche da parte di Parigi
Recombination-Driven Interface Trap Generation in SiC MOSFETs Under Constant Voltage and Constant Current Stress
No full textWe investigate the generation of interface traps during stress at low gate current and moderate gate voltage of SiC MOSFETs. Several stress tests are performed with a custom made, on-wafer, in-situ measurement setup; device degradation is monitored by charge pumping measurements and dc characterization. In essence we observe the following: (i) Ig-Vg curves are dominated by Fowler-Nordheim tunneling up to 8.1 MV/cm at RT; above this threshold, a kink is observed, due to hole generation via impact ionization; (ii) stresses at fields below 8.1 MV/cm result in negligible interface trap generation and moderate threshold voltage shift, due to electron trapping at border states; (iii) stress above 8.1 MV/cm results in a significant generation of interface traps, detected by charge pumping measurements. This interface trap generation is ascribed to the recombination enhanced defect reaction (REDR) caused by the recombination of the holes generated via impact ionization, taking place near the SiO2/SiC interface. Evidence for electron-hole recombination is obtained through electroluminescence investigation
Documenting the Sensory Mosaic: An Integrated Methodological Proposal for the Analysis of Urban Antinomies in Guangzhou
No full textThe growth and development of Asian urban areas, particularly those in China, which has occurred with extreme rapidity in recent years, has resulted in changes in the landscape for the benefit of megacity construction. The development and use of new technologies have resulted in improved lifestyles for the inter-urban population, new infrastructure lines, and improved efficiency of public services, often at the expense of and in stark contrast to peripheral and rural neighbours. The over-scaling of the territory forces a dimension of travel and displacement in city space, measured in hours, during which we cross neighbourhoods connoted by substantial differences in urban landscape from one another. Nomads, are we travelling from one city to another, or are we always in the same one? In this centripetal hyper-motion, millions of people draw tangible maps from one place to another every day while always remaining in the same city; therefore, the contribution presents a graphic-perceptual reconstruction of some of the streets of the metropolis of Guangzhou, elements symbolising par excellence the journey, so different and immersed in such different urban contexts while still in the same city
Advanced Machine Learning Approaches for Quality Estimation in Polymer Industry 4.0
Get PDFThe evolving demands of modern polymer manufacturing require advancements in process optimization and quality monitoring. Laboratory-based systems, characterized by delays, infrequent measurements, and high costs, are insufficient for dynamic industrial environments. Industry 4.0 offers transformative potential, particularly through soft sensors, which exploit real-time process data to estimate quality parameters. First-principles models provide high accuracy but are costly and process-specific, while data-driven models are more flexible and accessible. Models used for polymer quality monitoring rely on very complex approaches, such as deep learning methodologies and non-linear mathematical models, resulting in accurate though less interpretable. In cases with limited training data and need for interpretability, models like Partial Least Squares (PLS) are more suitable. PLS model is robust, interpretable, and well-established but it has limitations, particularly its inability to adapt to changing process conditions. Recursive methodologies have been developed to enable model adaptation, by considering the sequential nature of the data or by focusing on the most relevant observations. Another limitation of PLS is its inability to account for autocorrelation, where a variable’s current value is influenced by its previous measurements. Methodologies incorporating autoregressive terms have been proposed to effectively model such temporal dependencies. Another general challenge is the need to identify optimal parameters for the models to ensure their effectiveness. Formal optimization methodologies offer high accuracy but they are complex, require expertise, and can be difficult to implement in practice. Heuristics and iterative approaches present more flexible alternatives, but they also pose challenges, such as accounting for the sequential nature of the data and the interactions between parameters.
While established approaches provide reliable and robust solutions to many challenges, they fall short of fully addressing the complex scenarios examined in this work. This Dissertation addresses two key challenges in the development of adaptive soft sensors in polymer manufacturing: quality estimation in datasets with weak cross-correlation between process variables and product quality but high autocorrelation of the quality variable, in high-variability environments while maintaining model interpretability; joint parameter optimization in processes characterized by frequent campaign changes and the need for regular recalibration, accounting for temporal dependencies in the data.
To address the first challenge, the Proportional-Integral-Derivative Partial Least Squares (PID-PLS) model is proposed. This methodology incorporates temporal variability through proportional, integral, and derivative components to model both abrupt changes (e.g., grade transitions) and more subtle cumulative effects (e.g., fouling or set point shifts). The model is validated using Versalis’ industrial case study on Ethylene-Propylene Diene Monomer (EPDM) production and a controlled numerical scenario. Results show superior performance compared to state-of-the-art methods, improving predictive accuracy under time-varying and autocorrelated conditions by effectively capturing both sharp transitions and gradual process changes.
For the second challenge, the Recursive Adaptation (RA) algorithm is introduced to optimize model parameters jointly and adaptively. Validated on Versalis’ industrial case studies for EPDM and General-Purpose Polystyrene (GPPS) production, this algorithm outperforms conventional heuristics approaches. This algorithm facilitates rapid and efficient optimization, enabling real-time adaptable models for quality monitoring. A key improvement achieved through the soft sensors optimized by this methodology is the enhanced estimation accuracy during critical production periods, such as the initiation of a new production campaign
Does longer-muscle length resistance training cause greater longitudinal growth in humans? A systematic review
No full textBackground: This paper aimed to systematically review the literature regarding the effects of resistance training (RT) performed at longer-muscle length (LML) versus shorter-muscle length (SML) on proxy measurements for longitudinal hypertrophy. Methods: We included studies that satisfied the following criteria: (1) be a resistance training intervention with a comparison of LML vs SML-RT; (2) assess both fascicle length (FL) and muscle size pre- and post-intervention; (3) involve healthy adults aged ≥ 18 years; (4) be published in an English-language journal, and; (5) have a minimum training intervention duration of 4 weeks. Three databases were searched in February 2024 (Google Scholar, PubMed/Medline, Scopus) for relevant articles, alongside 'forward' and 'backward' citation searching of articles included and additions via authors' personal knowledge. The results of studies were described narratively, compared, and contrasted. Eight studies met the inclusion criteria, totaling a sample size of 120. Results: Our results suggest that both muscle size and fascicle length increases may be greater following LML-RT versus SML-RT, suggesting LML-RT may lead to greater longitudinal hypertrophy than SML-RT. Notably, evidence is largely mixed; no studies to date have attempted to estimate serial sarcomere number changes from LML versus SML-RT, and all but one study used linear extrapolation methods to estimate FL, which has questionable validity. Therefore, the structural adaptations underlying hypertrophy from LML-RT remain undetermined. Conclusion: In conclusion, results suggest that LML-RT may be superior to SML-RT for inducing muscle hypertrophy and, more specifically, longitudinal growth, though evidence is mixed
One welfare: bibliometric review of world literature
Get PDF: The One Welfare framework emphasizes the interconnection between animal, human, and environmental well-being, extending One Health principles to address broader welfare dimensions. Despite its relevance, One Welfare remains underexplored. This study investigates global research trends and thematic priorities in One Welfare literature published from 2013 to 2024. A bibliometric review was conducted using PubMed, Elsevier, Springer, Web of Science, Scopus, and CABI databases. A literature search was conducted using keywords translated into five of the world's most widely spoken languages: Hindi, Chinese, Spanish, English, and French. A total of 111 publications were identified and categorized into four main domains-Policy, Governance, Economy (PGE); Applied Human-Animal Sciences (AHAS); Societal, Economic, Environmental Dimensions (SEED); and Human-Animal Bond and Mental Health (HAB-MH)-and eight subcategories: Legal Framework and Economy (LFE); Education and Philosophy (EP); Sustainable Resource Management (SRM); Traditional Knowledge and Societal Impact (TKSI); Animal Management (AM); Human-Animal Diseases (HAD); Human-Animal Interaction (HAI); and Psychology (PSY). The analysis also considered animal types-companion animals (CA), production animals (PA), wild animals (WA), working/sport animals (WS), and general (GE)-and divided data into two time periods (2013-2018, 2019-2024). Most publications (78) emerged after 2018, with Animal Management (AM) subcategory as the dominant theme, particularly in relation to PA reflecting their significance in food security. Human-Animal Interaction (HAI) was the second most represented theme among the subcategories, particularly in relation to CA underlining their significance in human lives. Conversely, wild animals (WA), climate change, and working/sport animals (WS) remain underrepresented. Education and Philosophy was the least addressed subcategory, exposing a critical gap in integrating One Welfare into veterinary and animal science education. Given the limited number of publications identified over the past 11 years, there is a clear need to promote increased interdisciplinary research, policy development, and educational reform to fully implement the One Welfare framework and align it with global sustainability goals
Kernel-Based Quadratic Distance Testing: Sensitivity and Robustness
No full textIn statistical analysis, the reliability of test procedures is crucial for accurate inference from the data. However, the presence of measurement errors in the data and model misspecification constitute important challenges that can lead to wrong conclusions. Robust methods aim to maintain reliability even under contamination, outliers, and misspecifications of the model. Kernel-Based Quadratic Distances (KBQDs) are efficient tools in nonparametric statistics and have been used for constructing goodness-of-fit tests. This research explores the robustness of KBQD tests for normality, evaluating their sensitivity in terms of level and power under data contamination. Through a simulation study, we illustrate the performance of these tests by assessing the trade-offs between sensitivity and robustness and reinforcing the need for more reliable and accurate statistical tests dealing with imperfect data
Beyond failure: a case report on brain state changes during virtual reality-induced hypnosis in pediatric patient
Get PDFBackground: Management of fear in anxious patients is challenging, particularly in children. Virtual reality induced hypnosis may help during the procedures, changing vital parameters and brain states. Modifications in brain activity can be easily traced with wearable instruments. Case presentation: An 11-years old boy was scheduled for avulsion of teeth 15 and 25, which were misplaced in the hard palate. Due to his fear of procedure, he was exposed to virtual reality-induced hypnosis. The brain state was continuously monitored, showing light sedation, associated to low spectral edge frequency values, below 20 Hz, indicating a relaxed/hypnotic state. In both sessions, the electrical activity was higher in the right hemisphere compared to the left, which is conceivable in hypnotic state. During the first session, a technical problem ensued, which was detected by the patient and readily managed with additional anesthesia. Despite the negative experience, one week later the hypnotic state was readily induced and tooth extraction was accomplished without any problem. Conclusions: Virtual reality-induced hypnotic state may be an easy and safe procedure to use with anxious patients even in pediatric age. If coupled to brain state monitoring, also adverse events can be promptly managed. In addition, hypnotic state may be induced also after the negative experience due to unexpected problems, prompting for the use of this technique in the dental setting also after initial, partial failure