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.
The magnetic properties of amorphous Fe–Pd–B and Fe–Pt–B alloys are presented. The basis of our research were DTMD‐DTA (derivative thermo‐magnetogravimetry and differential thermal analysis) ...measurements, magnetic saturation measurements and low, ac field hysteresis loop measurements. The changes in the magnetic moment, Curie and crystallization temperature when Pt and Pd atoms substitute for Fe atoms are discussed. The most significant features of the hysteresis loop, such as the initial and maximum permeability, the saturation and remanence induction, the coercivity and the losses are presented.
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.
Pannexin 1 (Panx1) is a membrane channel implicated in numerous physiological and pathophysiological processes via its ability to support release of ATP and other cellular metabolites for local ...intercellular signaling. However, to date, there has been no direct demonstration of large molecule permeation via the Panx1 channel itself, and thus the permselectivity of Panx1 for different molecules remains unknown. To address this, we expressed, purified, and reconstituted Panx1 into proteoliposomes and demonstrated that channel activation by caspase cleavage yields a dye-permeable pore that favors flux of anionic, large-molecule permeants (up to ~1 kDa). Large cationic molecules can also permeate the channel, albeit at a much lower rate. We further show that Panx1 channels provide a molecular pathway for flux of ATP and other anionic (glutamate) and cationic signaling metabolites (spermidine). These results verify large molecule permeation directly through caspase-activated Panx1 channels that can support their many physiological roles.
This work presents a new methodological approach to evaluating the long-term performance of an existing air quality monitoring network (AQMN). The AQMN is essential in controlling human beings’ ...exposure to air pollutants, and the performance should be assessed over time. Still, there is not a harmonised method at the legislative level. In this work, 2008–2016 NO
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data recorded by the Community of Madrid’s AQMN were used for developing the suggested methodology, and 2007, 2017, and 2020 NO
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data were involved in testing the aptitude of the proposed methodology to check the performance along the time. Chemometric techniques were employed to suggest the most representative non-redundant fixed stations within the target AQMN, reducing up to ~ 80% of the original number of fixed monitoring stations (from 23 to 5 fixed stations). The influence of the temporal frame used in developing the exposed methodology showed a variability lower than 5%. The spatial NO
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distribution pictured by the current versus recommended fixed stations showed a higher than 95% similarity. This recommended approach can also be applied to short-time data. The exhibited methodology is a valuable tool for supporting AQMN managers in decision-making concerning AQMN management and complementing European Legislation guidelines concerning air pollutants monitoring using AQMN.
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