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Algorithm building, creating a step-by-step procedure to carry out a solution, is a challenging concept for youth to learn and practice. Kinetic sculpture is a novel context for examining how students may learn algorithms through designing and making. As part of a larger study, we collected and analyzed a total of 18 student pre- and post-tests on computational thinking, physical computing, and arts. To examine how students build algorithms in the process of designing and making a kinetic sculpture, we analyze two vignettes from two small groups in a STEAM-based workshop. Findings show that while designing and building kinetic sculpture, students learned computational thinking and applied algorithms by incorporating inputs, outputs, and variables during the process. This study offers a springboard to investigate how students create and apply algorithms in designing and making kinetic sculpture and provides empirical evidence on how students learn algorithms in a STEAM learning context. 

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.

 

Abstract—This paper presents a control co-design method for designing the mechanical power takeoff (PTO) system of a dual- flap oscillating surge wave energy converter. Unlike most existing work’s simplified representation of harvested power, this paper derives a more realistic electrical power representation based on a concise PTO modelling. This electrical power is used as the objective for PTO design optimization with energy maxi- mization control also taken into consideration to enable a more comprehensive design evaluation. A simple PI control structure speeds up the simultaneous co-optimization of control and PTO parameters, and an equivalent circuit model of the WEC not only streamlines power representation but also facilitates more insightful evaluation of the optimization results. The optimized PTO shows a large improvement in terms of power potential and actual power performance. It’s found the generator’s 

Past research has recognized culture and gender variation in the experience of emotion, yet this has not been examined on a level of effective connectivity. To determine culture and gender differences in effec-tive connectivity during emotional experiences, we applied dynamic causal modeling (DCM) to electro-encephalography (EEG) measures of brain activity obtained from Chinese and American participants while they watched emotion-evoking images. Relative to US participants, Chinese participants favored a model bearing a more integrated dorsolateral prefrontal cortex (dlPFC) during fear v. neutral experiences. Meanwhile, relative to males, females favored a model bearing a less integrated dlPFC during fear v. neutral experiences. A culture-gender interaction for winning models was also observed; only US partici-pants showed an effect of gender, with US females favoring a model bearing a less integrated dlPFC compared to the other groups. These findings suggest that emotion and its neural correlates depend in part on the cultural background and gender of an individual. To our knowledge, this is also the first study to apply both DCM and EEG measures in examining culture-gender interaction and emotion.