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Economic analysis of 15-valent and 20-valent pneumococcal conjugate vaccines among older adults in Ontario, Canada

Expert Review of Vaccines 2025年第1期24卷 1-10页

作者： Gebretekle, Gebremedhin B. O’Reilly, Ryan Mac, Stephen Fadel, Shaza Crowcroft, Natasha S. Sander, Beate Institute of Health Policy Management and Evaluation University of Toronto ON Canada Toronto Health Economics and Technology Assessment (THETA) Collaborative University Health Network ON Canada Institute for Management & Innovation University of Toronto Mississauga Mississauga ON Canada Clinical Public Health Division Dalla Lana School of Public Health University of Toronto Mississauga ON Canada Centre for Vaccine Preventable Diseases Dalla Lana School of Public Health University of Toronto Mississauga ON Canada Primary Care & Health Systems Research Program ICES ON Canada Communicable Disease Control Public Health Ontario ON Canada

Background: Health Canada approved two new pneumococcal conjugate vaccines (PCV), 15-valent (PCV15) and 20-valent (PCV20), and we assessed their cost-effectiveness for older Ontarians. Research design and methods: We conducted a cost-utility analysis using an individual-level state transition model to compare one dose of PCV (alone or in series with PPV23) with PPV23-only. We estimated incremental cost-effectiveness ratios (ICERs) expressed in costs (C$2022) per quality-adjusted life year (QALY) from the healthcare payer perspective, discounted at 1.5% annually. Results: A sequential comparison of vaccinations with no indirect effect from childhood vaccination resulted in an ICER of $44,324/QALY for PCV15-alone compared to PPV23-only, and $70,751/QALY for PCV20-alone versus PCV15-alone. None of the PCV15/20 combined with PPV23 programs were cost-effective at a C$50,000/QALY threshold. PCV20 alone had an ICER of C$46,961/QALY compared to PPV23-only. When considering indirect effects, PCV15/20 alone or in series with PPV23 were not cost-effective. ICERs were mostly influenced by vaccine characteristics (effectiveness, waning, cost) and the incidence of pneumococcal community-acquired pneumonia. Conclusions: Vaccinating older adults with PCV15/20 likely reduces burden of pneumococcal disease and would be cost-effective initially, but is expected to be less economically attractive in the longer term when herd immunity benefits from childhood vaccination programs are considered. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Canada cost-effectiveness analysis older adults pneumococcal disease pneumococcal vaccination

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Human-Exoskeleton Interaction Force Estimation Based on Quasi-Direct Drive Actuators

Human-Exoskeleton Interaction Force Estimation Based on Quas...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Julian Seiler Niklas Schêfer Guoping Zhao Bastian Latsch Martin Grimmer Philipp Beckerle Mario Kupnik Measurement and Sensor Technology Group Technical University of Darmstadt Germany School of Mechanical Engineering Southeast University China Lauflabor Locomotion Laboratory Technical University of Darmstadt Germany Control and Cyber-Physical Systems Technical University of Darmstadt Germany Chair of Autonomous Systems and Mechatronics Friedrich-Alexander-Universität Erlangen Nurnberg Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Exoskeletons have emerged as a promising tech-nological solution to provide functional compensation, training support, physical enhancement, and rehabilitation for an aging population. High torque density and control bandwidth are essential for exoskeleton actuation. In addition, monitoring and control of human-exoskeleton interaction forces is essential for the effectiveness, safety, and comfort of exoskeletons. Quasi-direct drives (QDD) have the potential to address the actuation requirements by enabling proprioceptive actuation with low mechanical output impedance. We present a test bench system to identify and validate the system dynamics, including torque constant, inertia, and friction properties of the QDD Cube-Mars AK10-9 V1.1. The actuator is employed in a hip exoskeleton to evaluate open-loop torque tracking and interaction force estimation in an assisted gait scenario with one participant walking on a treadmill. The model estimates interaction forces with a mean absolute error (MAE) of 2.78±0.58N (6.4% of rated force output). Model-based open-loop control improves the torque tracking MAE by 23%. Our analysis indicates that considering the soft coupling between human and exoskeleton has the potential to further improve the torque tracking and interaction force estimation accuracy. Altogether, the findings demonstrate that QDD actuation enables backdrivability, re-liable force estimation and controllable assistance, thereby providing an effective solution for exoskeleton actuation.

关键词： Actuators Torque Accuracy Friction Exoskeletons Force Dynamics Estimation Impedance Hip

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Data-driven Force Observer for Human-Robot Interaction with Series Elastic Actuators using Gaussian Processes

Data-driven Force Observer for Human-Robot Interaction with ...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Samuel Tesfazgi Markus Keßler Emilio Trigili Armin Lederer Sandra Hirche Chair of Information-Oriented Control (ITR) TUM School of Computation Information and Technology Technical University of Munich Munich Germany Scuola Superiore Sant’Anna BioRobotics Institute Pontedera Italy Department of Computer Science Learning & Adaptive Systems Group ETH Zurich Zurich Switzerland

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Ensuring safety and adapting to the user’s behavior are of paramount importance in physical human-robot interaction. Thus, incorporating elastic actuators in the robot’s mechanical design has become popular, since it offers intrinsic compliance and additionally provide a coarse estimate for the interaction force by measuring the deformation of the elastic components. While observer-based methods have been shown to improve these estimates, they rely on accurate models of the system, which are challenging to obtain in complex operating environments. In this work, we overcome this issue by learning the unknown dynamics components using Gaussian process (GP) regression. By employing the learned model in a Bayesian filtering framework, we improve the estimation accuracy and additionally obtain an observer that explicitly considers local model uncertainty in the confidence measure of the state estimate. Furthermore, we derive guaranteed estimation error bounds, thus, facilitating the use in safety-critical applications. We demonstrate the effectiveness of the proposed approach experimentally in a human-exoskeleton interaction scenario.

关键词： Estimation error Actuators Uncertainty Force measurement Accuracy Measurement uncertainty Force Human-robot interaction Gaussian processes Observers

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Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

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A Noise Mitigation Approach for Improving Position Estimate in Indoor Vehicle Navigation Using Inertial Measurement Unit

A Noise Mitigation Approach for Improving Position Estimate ...

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control Conference (ICC), 2019 Sixth Indian

作者： Vasumathi R Subhadeep Kumar Ramkrishna Pasumarthy Nirav Bhatt Department of Electrical Engineering Robert Bosch Center of Data Sciences and Artificial Intelligence Indian Institute of Technology Madras Chennai India Department of Electrical Engineering Robert Bosch Center of Data Sciences and Artificial Intelligence and Prospective Center of Excellence for Network Systems Learning Control and Evolution Group Indian Institute of Technology Madras Chennai India Department of Biotechnology Robert Bosch Center of Data Sciences and Artificial Intelligence Prospective Center of Excellence for Network Systems Learning Control and Evolution Group Indian Institute of Technology Madras Chennai India

Accurate position estimation, especially in indoor environments, presents a formidable challenge despite significant advancements in estimation methodologies. The integration of additional sensors is often imperative to refine estimates, particularly within indoor settings. The choice of additional sensors depends on the specific applications and operational range. This study focuses on devising a position estimation framework utilizing the internal sensors such as the Inertial Measurement Unit (IMU) and wheel encoders within a scaled-down Electric Vehicle. The proposed approach entails a combination of crafting a digital filter and implementing a Kalman filter to effectively attenuate noise and errors in the IMU data, thereby enhancing the position estimate, and the methodology is validated through experiments. This work contributes to the broader discourse on advancing indoor position estimation while bypassing the need for external positioning systems.

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Asymptotic Observers for Heterogeneous Reaction systems using the Concepts of Reaction and Mass-transfer Extents

Asymptotic Observers for Heterogeneous Reaction Systems usin...

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control Conference (ICC), 2019 Sixth Indian

作者： Nirav Bhatt Department of Biotechnology Bhupat and Jyoti Mehta School of Biosciences and prospective Centre of Excellence for Network Systems Learning Control and Evolution Indian Institute of Technology Madras India

For reaction systems, the state variables (the number of moles) can be expressed using the concepts of extents of reaction and mass transfer for homogeneous and heterogeneous reaction systems. In this work, a general framework for designing asymptotic observers for homogeneous and gas-liquid reaction systems is presented using the concept of the extents. For gas-liquid reaction systems, it is shown that asymptotic observers can be designed using measurements in the gas-phase. The effect of noisy measurements on the estimation of unmeasured concentrations is also discussed. The proposed asymptotic observer approach is illustrated using an example of the chlorination of butanoic acid (gas-liquid reaction system).

关键词： Phase measurement Liquids Ethanol Estimation Observers Noise measurement

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Bayesian Framework for Multi-User Cooperative Radio SLAM 35

Bayesian Framework for Multi-User Cooperative Radio SLAM

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Que, Hang Yang, Jie Du, Tao Xia, Shuqiang Wen, Chao-Kai Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing211189 China Southeast University Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Zte Corporation Shenzhen518001 China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518001 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan

ISBN: (纸本)9798350362244

The advancement of millimeter-wave communication technology heralds new sensing capabilities. By leveraging channel multipath parameter estimates, we can harness simultaneous localization and mapping (SLAM) for precise user equipment (UE) localization and radio map construction in 6 G communication systems. Particularly in multi-UE scenarios, SLAM empowers base stations to amalgamate the local radio maps of various UEs efficiently. This study introduces a novel Bayesian framework specifically designed for multi-UE SLAM, complemented by a tailored factor graph. We also unveil a two-stage multi-UE SLAM algorithm. Our simulation results reveal that this algorithm substantially enhances radio map construction accuracy by 4 8. 5 % and UE localization accuracy by 13.5 %, outperforming single-UE cases. Moreover, the algorithm demonstrates remarkable adaptability to environmental changes, showcasing its potential for long-term evolution in dynamic settings. © 2024 IEEE.

关键词： Long Term Evolution (LTE)

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Observer design for 2×2 linear hyperbolic PDEs that are bidirectionally coupled with nonlinear ODEs

Observer design for 2×2 linear hyperbolic PDEs that are bid...

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European control Conference (ECC)

作者： Abdurrahman Irscheid Nicole Gehring Joachim Deutscher Joachim Rudolph Chair of Systems Theory and Control Engineering Saarland University Saarbrücken Germany Institute of Automatic Control and Control Systems Technology Johannes Kepler University Linz Austria Institute for Measurement Control and Microtechnology Ulm University Ulm Germany

A prediction-based observer is designed for systems consisting of 2×2 linear heterodirectional hyperbolic partial differential equations (PDEs) with collocated actuation and measurement at one boundary and bidirectional coupling with nonlinear ordinary differential equations (ODEs) at the other one. Following a preliminary backstepping transformation, a solution-based analysis of the plant allows to draw upon well-known results on the observer design for nonlinear ODEs. For that, the design is split into several steps, with a retarded observer for the ODE state and a prediction thereupon, thus significantly extending existing results for PDE-ODE systems. It is shown that the resulting error system admits a cascaded structure, from which (local) asymptotic convergence follows. Numerical studies underline the performance of the observer.

关键词： Couplings Backstepping Partial differential equations Europe Observers Ordinary differential equations Error correction codes

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Green Routing Game: Strategic Logistical Planning using Mixed Fleets of ICEVs and EVs

Green Routing Game: Strategic Logistical Planning using Mixe...

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IEEE Conference on Decision and control

作者： Hampei Sasahara György Dán Saurabh Amin Henrik Sandberg Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan Division of Network and Systems Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper introduces a “green” routing game between multiple logistic operators (players), each owning a mixed fleet of internal combustion engine vehicle (ICEV) and electric vehicle (EV) trucks. Each player faces the cost of delayed delivery (due to charging requirements of EVs) and a pollution cost levied on the ICEVs. This cost structure models: 1) limited battery capacity of EVs and their charging requirement; 2) shared nature of charging facilities; 3) pollution cost levied by regulatory agency on the use of ICEVs. We characterize Nash equilibria of this game and derive a condition for its uniqueness. We also use the gradient projection method to compute this equilibrium in a distributed manner. Our equilibrium analysis is useful to analyze the trade-off faced by players in incurring higher delay due to congestion at charging locations when the share of EVs increases versus a higher pollution cost when the share of ICEVs increases. A numerical example suggests that to increase marginal pollution cost can reduce inefficiency of equilibria.

关键词： Costs Pollution Green products Internal combustion engines Games Routing Planning

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Improved Context-Sensitive Transformer Model for Inland Vessel Trajectory Prediction

Improved Context-Sensitive Transformer Model for Inland Vess...

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International Conference on Intelligent Transportation

作者： Kathrin Donandt Karim Böttger Dirk Söffker Institute of Ship Technology Ocean Engineering and Transport Systems (ISMT) University of Duisburg-Essen Duisburg Germany German Federal Waterways Engineering and Research Institute Karlsruhe Germany Chair of Dynamics and Control (SRS) University of Duisburg-Essen Duisburg Germany

Physics-related and model-based vessel trajectory prediction is highly accurate but requires specific knowledge of the vessel under consideration which is not always practical. Machine learning-based trajectory prediction models do not require expert knowledge, but rely on the implicit knowledge extracted from massive amounts of data. Several deep learning (DL) methods for vessel trajectory prediction have recently been suggested. The DL models developed typically only process information about the (dis)location of vessels defined with respect to a global reference system. In the context of inland navigation, this can be problematic, since without knowledge of the limited navigable space, irrealistic trajectories are likely to be determined. If spatial constraintes are introduced, e.g., by implementing an additional submodule to process map data, however, overall complexity increases. Instead of processing the vessel displacement information on the one hand and the spatial information on the other hand, the paper proposes the merging of both information. Here, fairway-related and navigation-related displacement information are used directly. In this way, the previously proposed context-sensitive Classification Transformer (CSCT) shows an improved spatial awareness. Additionally, the CSCT is adapted to assess the model uncertainty by enabling dropout during inference. This approach is trained on different inland waterways to analyze its generalizability. As the improved CSCT obtains lower prediction errors and enables to estimate the trustworthiness of each prediction, it is more suitable for safety-critical applications in inland navigation than previously developed models.

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