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The Taranta1 project, a collaboration between the MAX IV Institute1 and Square Kilometre Array (SKAO)2 within the Tango3 Collaboration, presents a web-based, no-code approach for creating graphical interfaces dedicated to monitoring and controlling Tango-based systems. Through an active development phase and close collaboration with the community, the software has seen the introduction of advanced
Selecting the most suitable procurement strategy is crucial to the efficient management of supply chain operations and the prevention of stock shortages. Nevertheless, when dealing with a wide variety of products, this task becomes an intricate challenge. While traditional and advanced procurement tools are available, applying them across such diverse product ranges is often impractical. This rese
Background: Global supply chains are confronted with the challenge of ensuring on-time deliveries while simultaneously enhancing supply chain resilience. Conventional methods aim to address the complexities of modern supply chains, promoting the transition to intelligent and data-driven strategies. Methods: This research represents an innovative methodology for predicting the risk of late deliveri
Moving in straight lines is a behaviour that enables organisms to search for food, move away from threats, and ultimately seek suitable environments in which to survive and reproduce. This study explores a vision-based technique for detecting a change in heading direction using the Milky Way (MW), one of the navigational cues that are known to be used by night-active insects. An algorithm is propo
Accurate eye tracking is crucial for gaze-dependent research, but calibrating eye trackers in subjects who cannot follow instructions, such as human infants and nonhuman primates, presents a challenge. Traditional calibration methods rely on verbal instructions, which are ineffective for these populations. To address this, researchers often use attention-grabbing stimuli in known locations; howeve
Over the past decade, sequencing data generated by large microbiome projects showed that taxa exhibit patchy geographical distribution, raising questions about the geospatial dynamics that shape natural microbiomes and the spread of antimicrobial resistance genes. Answering these questions requires distinguishing between local and nonlocal microorganisms and identifying the source sites for the la
Researchers using eye tracking are heavily dependent on software and hardware tools to perform their studies, from recording eye tracking data and visualizing it, to processing and analyzing it. This article provides an overview of available tools for research using eye trackers and discusses considerations to make when choosing which tools to adopt for one's study.
Constructed with used plastic bottles, the eco-cooler has been widely adopted in resource-poor communities in Bangladesh and other countries. We tested the eco-cooler under controlled conditions using a scientific wind tunnel in a climatic chamber. In our tests, we used seven eco-cooler designs in 27 climate conditions typical of Bangladesh (temperatures of 40 °C, 35 °C, and 30 °C; humidity levels
In this article, we discuss operationalizations and examples of experimental design in eye-tracking research. First, we distinguish direct operationalization for entities like saccades, which are closely aligned with their original concepts, and indirect operationalization for concepts not directly measurable, such as attention or mind-wandering. The latter relies on selecting a measurable proxy.
We investigate the dynamics of the adaptive Kuramoto model with slow adaptation in the continuum limit, N → ∞ . This model is distinguished by dense multistability, where multiple states coexist for the same system parameters. The underlying cause of this multistability is that some oscillators can lock at different phases or switch between locking and drifting depending on their initial condition
This thesis investigates morality from a computational perspective by examining how machines can be developed with capacities for moral reasoning and action. It addresses how to overcome interdisciplinary boundaries between moral philosophy and computer science (Paper I), proposes a virtue-theoretic framework for artificial moral cognition (Papers II and III), and highlights issues of using normat
Artificial empathy (AE) is a hotly contested topic. Recently, several empathy researchers have voiced criticism on the prospect of AE, arguing that it is impossible, unethical, or both. Contrary to these sentiments, we believe that further nuance and research are needed to better understand AE, its risks, and what it can potentially contribute to human well-being. We will focus on one obstacle to
Can AI ‘solve’ politics? In this paper, I explore optipolitics, i.e., the idea that politics along with other complex social issues can be framed as mathematical optimization problems and solved as such. I begin by describing politics, optimization, and some reasons for applying the latter to the former. I then present a liberal democratic version of optipolitics and try to defend it against eight
Extensive studies have shown that humans process faces holistically, considering not only individual features but also the relationships among them. Knowing where humans and dogs fixate first and the longest when they view faces is highly informative, because the locations can be used to evaluate whether they use a holistic face processing strategy or not. However, the conclusions reported by prev
Cardiac diffusion tensor imaging (cDTI) is highly prone to image corruption, yet robust-fitting methods are rarely used. Single voxel outlier detection (SVOD) can overlook corruptions that are visually obvious, perhaps causing reluctance to replace whole-image shot-rejection (SR) despite its own deficiencies. SVOD's deficiencies may be relatively unimportant: corrupted signals that are not statist
The accurate representation of mixed-phase monsoon clouds and their phase distribution is of great importance for numerical models used to predict monsoon rainfall. Therefore, it is essential for these models to correctly capture the phase fraction of clouds, which includes the proportions of liquid and ice. Ice particle formation in clouds occurs through primary ice production and secondary ice p
Deep learning methods have significantly advanced the field of gaze estimation, yet the development of these algorithms is often hindered by a lack of appropriate publicly accessible training datasets. Moreover, models trained on the few available datasets often fail to generalize to new datasets due to both discrepancies in hardware and biological diversity among subjects. To mitigate these chall
