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Introduçâo: O planejamento estético consiste em urna etapa muito importante para o sucesso do tratamento odontológico. Mock-up ou ensaio restaurador é urna ferramenta utilizada para o planej amento de facetas e lentes de contato que permite ao paciente e ao cirurgiâo-dentista (CD) visualizar o possível resultado do tratamento restaurador. Objetivo: Descrever a relevancia da realizaçâo do mock-up na satisfaçâo do paciente e no planejamento do tratamento de reabilitaçâo oral estética. Materials e Métodos: Foi realizada uma revisâo de literatura com artigos selecionados nas plataformas Pubmed, Google académico e BVS utilizando os seguintes descritores: Ensaio restaurador e Reabilitaçâo bucal.Resultados: Esse método permite estipular o formato e o tamanho dos futuros laminados cerámicos, podendo servir como guia para o controle do desgaste dos dentes. Assim, viabiliza um procedimento com maior segurança para o paciente, bem como para o CD em relaçâo ao tratamento que está sendo proposto. Conclusâo: Com o mock-up, consegue-se prever o resultado final do procedimento, possibilitando ao paciente opinar, aprovar e fazer alteraçöes no resultado final do trabalho, além de servir como guia cirúrgico. Trata-se, portanto, de uma ferramenta que evita tratamentos invasivos e previne resultados insatisfatórios, aumentando a relaçâo de confiança paciente-profissional.

The development and design of renewable energy systems relies on system simulations to evaluate constantly changing environments and new requirements. This can require the extension or development of new simulation models, which is a time consuming effort, making reusing models desirable. However, this flexibility is not always given in existing tools. Co-Simulation provides a technique to overcome these issues, but it has not been applied yet for aero-elastic simulation of wind farms. This study investigates how co-simulation techniques can be applied to create modular simulations of wind farms. We utilize functional mock-up units as a model base to wrap existing models as components for a wind farm simulation framework, which we call farmQSim. Additionally, a continuously generating wind model is used to remove the necessity of a precursor wind generating model. The wind farm co-simulation approach shows a good match with results from FAST.farm and allows for flexible setup of simulation. Models of different complexity can be combined into a single simulation case to decrease simulation time while achieving comparable results. Overall, co-simulation has been proven to be suitable for wind farm simulations and therefore enables reusability of simulation models and provides extensibility of the simulation cases.

This paper develops and studies a sensor element mock-up based on the Faraday effect with multiple reflections. The authors show that as the length of the optical path in a magneto-optical crystal increases, it prompts the increase in the current sensor sensitivity. The paper also establishes the correspondence of the current waveform and the optical response of the sensor mock-up. It is shown that in developed sensor, the output signal magnitude directly correlates with the magnetic field induction.

Model simulation plays an important role in modern engineering design and system development. It simulates and validates complex systems through a virtual environment, reduces the cost and risk of physical tests, and improves the design efficiency and accuracy. Generating a functional mock-up unit (FMU) is the core of model simulation. Most FMU is generated by Modelica, but this generation method is not only very complicated but also requires experimentalists to be familiar with Modelica. Nowadays, physical models are becoming more and more complex. With the development of artificial intelligence, more and more intelligent models are involved in the simulation process. Therefore, it is essential to realize the simulation process of automatic and rapid generation of FMU by multi-source languages. In this paper, by combining Python and Modelica, two methods of automatic FMU generation are designed. Through simulation tests, it is verified that the FMU generated by these two methods can be applied to the simulation process, which brings significant efficiency improvement to the model design.

This paper presents an experimental investigation of the evolution of the wetted surface and of the hydrodynamic force during the water exit of a body initially floating at the water surface, and during combined water entry and exit. The evolution of the surface of contact between the body and the water is measured using transparent mock-ups and an LED edge-lighting system. This technique makes it possible to follow the evolution of the wetted surface during both the entry and exit phases with a high-speed video camera placed above the mock-up. The feasibility of the technique is shown for different axisymmetric bodies: a circular disc, a cone and a sphere. The evolution of the hydrodynamic force and of the radius of the wetted surface measured during the experiments are compared with theoretical results obtained with a combined Wagner-modified von Karman approach (Tassin et al. J. Fluids Struct., vol. 40, 2013, pp. 317–336), the linearized water exit model of Korobkin et al. (J. Fluids Struct., vol. 69, 2017a, pp. 16–33) and the small-time self-similar solution of Korobkin et al. (J. Engng Maths, vol. 102, 2017b, pp. 117–130).

The fusion community is looking for solutions to qualify the breeding blankets (BB) before their final testing in DEMO. Thus, ambitious and attractive proposals, like the Volumetric Neutron Source, are being explored. In parallel, other possible solutions are being analyzed. Among them, IFMIF-DONES has been considered a suitable candidate since the reactions in its lithium target will produce an intense, high-energy fusion-like neutron flux, allowing the development of different fusion-related experiments. The main goal of IFMIF-DONES is the validation and qualification of structural materials to be used in DEMO, within the so-called high flux test area. In addition, the medium flux area, with a larger irradiation volume, constitutes a perfect test bench for tritium technologies validation. This paper analyzes the characteristics of the medium flux area, and presents the idea of a Test Blanket Unit (TBU), a mock-up of the BB considered representative of a certain concept (e.g. Helium Cooled Pebble Bed or Water Cooled Lead-Lithium). It is anticipated that the TBU will increase the technology readiness level of this important component. Its main goal will be to contribute to the BB qualification in an irradiation environment similar to that expected in a fusion reactor, performing multi-physics experiments in an integrated testing. It is important to note that the IFMIF-DONES engineering design has been developed to maximize flexibility, and at this stage, this kind of new experiment can be proposed.

Reinforcement learning (RL) is a computational approach to understanding and automating goal-directed learning and decision-making. The difference from other computational approaches is the emphasis on learning by an agent from direct interaction with its environment to achieve long-term goals [1]. In this work, the RL algorithm was implemented using Python. This then enables the RL algorithm to make decisions to optimize the output from the system and provide real-time adaptation to changes and their retention for future usage. A diesel engine is a complex system where a RL algorithm can address the NOx–soot emissions trade-off by controlling fuel injection quantity and timing. This study used RL to optimize the fuel injection timing to get a better NO–soot trade-off for a common rail diesel engine. The diesel engine utilizes a pilot–main and a pilot–main–post-fuel injection strategy. Change of fuel injection quantity was not attempted in this study as the main objective was to demonstrate the use of RL algorithms while maintaining a constant indicated mean effective pressure. A change in fuel quantity has a larger influence on the indicated mean effective pressure than a change in fuel injection timing. The focus of this work was to present a novel methodology of using the 3D combustion data from analysis software in the form of a functional mock-up unit (FMU) and showcasing the implementation of a RL algorithm in Python language to interact with the FMU to reduce the NO and soot emissions by suggesting changes to the main injection timing in a pilot–main and pilot–main–post-injection strategy. RL algorithms identified the operating injection strategy, i.e., main injection timing for a pilot–main and pilot–main–post-injection strategy, reducing NO emissions from 38% to 56% and soot emissions from 10% to 90% for a range of fuel injection strategies.

IntroductionThere needs to be more awareness and agreement on value criteria important to digital health stakeholders (DHSs), including health technology assessment agencies, especially in low- and middle-income countries (LMICs). To overcome these challenges, we focused on the feasibility of a dashboard to improve low confidence and assessment readiness of digital health technologies (DHTs) among DHSs in Malaysia.Methods“Artificial Intelligence Embedded X-ray for Lung Cancer Screening” from the Malaysian Health Technology Assessment Section (MaHTAS) was selected as a DHT use case. Representatives from MaHTAS, health informatics, research and innovation agencies, the digital health industry, patient advocates, and bioethicists attended an information briefing session and workshops. Participants completed a value assessment checklist questionnaire on the completeness of the information for the use case. Data and insights from these online workshops were incorporated into the development of Figma dashboard mock-up. Feedback from participants, other Malaysian DHSs, additional LMICs, and high-income countries was incorporated into the mock-up.ResultsFor the use case, average ratings from participants on the completeness of information on the seven value domains (VDs) were 3.4 and 3.1 for “healthcare system challenges and current use of technology” and “effectiveness” out of a maximum rating of 4 for “sufficient.” Both VDs were classified as “partially sufficient.” Ratings for the remaining VDs were 2.9 on “technical product information and use,” 2.8 on “safety,” 2.5 on “cost and economic impact,” 2.2 for “usability and accessibility,” and “ethical aspects.” These VDs were classified as “not sufficient.” The dashboard and its use were evaluated positively by 17 of 22 DHSs, including participants.ConclusionsIt was feasible to develop a useful dashboard applying a value assessment framework for DHTs on a use case with clear visualizations and a systematic approach. Our results have potential for applications in early scientific advice. It is to be considered that workshop participants’ profiles may create a bias regarding their subjectivity in rating completeness of information on a DHT.

Indoor positioning systems (IPS) differ from outdoor navigation in technological foundations and typical use cases, yet real-world deployments remain relatively rare. For an early-stage acceptance evaluation, literature-derived IPS functions were implemented as an interactive, task-based UI mock-up for a university setting. UTAUT2 was assessed with a pooled sample of 181 potential users across three independent data collections using PLS-SEM with one-tailed BCa bootstrap confidence intervals (90%; 5%/95% bounds). Performance expectancy showed the largest positive association with behavioral intention (β = 0.585, CI [0.480; 0.678]). Social influence (β = 0.179, CI [0.115; 0.245]), price value under a communicated one-time fee of €0.99 (β = 0.179, CI [0.096; 0.260]), and habit (β = 0.179, CI [0.097; 0.265]) also related positively to intention (R² = 0.781). Effort expectancy (β = −0.051, CI [−0.136; 0.023]), facilitating conditions (β = −0.027, CI [−0.108; 0.046]), and hedonic motivation (β = −0.002, CI [−0.109; 0.113]) were not supported; a robustness model indicated a negative age × price value interaction (β = −0.164, CI [−0.314; −0.071]). The findings extend UTAUT2 evidence to prototype-based IPS UI evaluation and suggest that performance-related beliefs dominate early intention formation. Practically, prototype concepts should prioritize and clearly communicate features that reduce uncertainty, time cost, and search effort in complex indoor environments. Because the stimulus was a UI mock-up and the outcome was self-reported intention, IPS-specific technical frictions (e.g., localization inaccuracies, latency, route deviations) and sustained real-world use were not observed, which may limit transferability to deployed IPS.

Ships and offshore structures use anchors for safe mooring or emergency maneuvers to stop the vessel’s operation in critical situations. Among the anchoring types, vessels with large block coefficients (e.g., tankers and LNG carriers) use bell mouth types made of cast iron installed between the hull exterior and the anchor. However, since these are made from cast steel, operational issues frequently arise due to discrepancies between the planned dimensions and the actual dimensions compared to steel cutting and processing. To address these problems, this study has developed a new anchoring system that modifies the vessel’s bow structure and does not require a bell mouth. Before applying it to actual vessels, a mock up test was conducted to examine the anchor’s motion and identify critical structural points in the developed anchoring system. Future research will focus on evaluating the structural strength of the vessel’s bow equipped with the new anchoring system using Korean Register’s structural analysis program, See Trust Hull Scan. The newly developed type of anchoring system is expected to resolve operational issues in advance through 3D simulations and reduce costs by doing away with the need for continuous mock up testing.