Dynamical Component Analysis (DyCA) and Dynamic Mode Decomposition (DMD), both data-driven dimension reduction methods, are introduced. After application to multivariate simulated signals the techniques of mode selection and the resulting amplitudes are compared with respect to noise robustness and sampling periods. The results indicate that DyCA is a useful alternative to DMD and outperforms DMD under certain conditions. These conditions are based on the underlying dynamics in the terms of differential equations and on the noise ratios of the signals.

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Industrial parts often demand high dimensional accuracy and mechanical strength. This study introduces a method using Response Surface Methodology and composite desirability to simultaneously optimize these performances in components manufactured through additive processes. The approach was validated on Polylactic Acid parts fabricated through Fused Filament Fabrication. Optimized process parameters included a print speed of 80 mm/s, a layer height of 0.2 mm, a fan speed of 50%, and an extrusion temperature of 210 °C, yielding tensile strength of 53.27 MPa and dimensional deviations under 5%. Experimental validations showed less than a 5% deviation between predictions and outcomes. The findings provide valuable insights into improving the quality and performance of printed components in various industrial applications, such as gears, highlighting the significance of multi-response optimisation in 3D printing processes. This study ultimately contributes to more efficient and cost-effective manufacturing processes.

This study explores the unique operating behavior of an alkaline water electrolysis cell equipped with an ion-solvating membrane, operated with a diluted alkaline electrolyte, specifically 1-M potassium hydroxide (1M KOH), in anode feed mode. Our investigations reveal several key insights.

This study examines the effectiveness of digital nudging in enhancing email marketing strategies for non-profit organizations (NPOs) involved in emergency and disaster relief (EDR). Specifically, it aims to explore the potential of digital nudges to convert one-time and occasional donors into regular contributors. By investigating whether, and to what extent, digital nudging can facilitate this conversion, the research provides insights into optimizing donor engagement. Based on literature, four digital nudges were developed and tested in a quantitative field experiment conducted in partnership with the German emergency and disaster relief organization, Caritas international. The findings reveal that the phantom decoy and identity coherence nudges are particularly effective in increasing click-through rates on recurring donation buttons in emails from NPOs focused on EDR, highlighting their potential as tools for improving donor retention.

Synchronous online learning is situated in synchronous webinars, virtual classrooms, and videoconferences, in which students and teachers communicate live over the Internet across distant geographical locations. Shared virtual platforms with voice-over-IP technology and webcams are used to interact ubiquitously and synchronously in real-time. During the COVID-19 pandemic, the use of synchronous online learning environments in primary, secondary, higher, and continuous education has grown massively. In this chapter, we aim to identify design recommendations that help increase the effectiveness of synchronous online learning. First, we provide an overview of recent meta-analyses on the effectiveness of synchronous online learning compared to synchronous face-to-face and asynchronous online learning. Second, we use this empirical evidence to develop design principles that can guide teachers, trainers, and educators in designing effective synchronous online learning environments. Third, we discuss a research agenda for future studies on synchronous online learning, webinars, and videoconferences in education, and we reflect on some practical affordances, including the use of webcams and breakout rooms.

This paper investigates anthropomorphism of a robot arm during a cooperative human-robot pick-and-place task, while varying cognitive load of test persons. Test persons are required to repeatedly provide a Lego brick for the robot by alternatingly putting it onto one of two trays. The robot then picks it up and puts it in front of the test person again. Cognitive load is varied by whether or not an initially given 8-digit number has to be remembered by the test person. Dimensions of anthropomorphism are acquired using the HRIES questionnaire and cognitive load is acquired using two state-of-the-art questionnaires. Results show a significant correlation of perceived sociability and animacy on mental demand and cognitive load, but only in the high load condition. It is suggested, that cognitive load should be considered during cooperative task design because resulting variations of anthropomorphism may impact cooperative task performance.