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Magnetic field effects on the proton EDM in a continuous all-electric storage ring
Hacıö,meroğ,lu, Selcuk,Orlov, Yuri F.,Semertzidis, Yannis K. Elsevier 2019 Nuclear instruments & methods in physics research. Vol.927 No.-
<P><B>Abstract</B></P> <P>The electric dipole moment of the proton can be searched in an electric storage ring by measuring the spin precession rate of the proton beam on the vertical plane. In the ideal case, the spin precession originates from the coupling between the electric field and the electric dipole moment. In a more realistic scenario, the magnetic field becomes a major systematic error source as it couples with the magnetic dipole moment in a similar way. The beam can see the magnetic field in various configurations which include direction, time dependence, etc. For instance, geometric phase effect is observed when the beam sees the field at different directions and phases periodically. We have simulated the effect of magnetic fields in major independent scenarios and found consistent results with the analytical estimations of the static magnetic field cases. We have set a limit for the magnetic field in each scenario and proposed solutions to avoid systematic errors from magnetic fields.</P>
GENERATIVE AI FOR CONTENT MARKETING: HELPFUL OR HARMFUL?
Risqo Wahid,Joel Mero,Paavo Ritala 글로벌지식마케팅경영학회 2023 Global Marketing Conference Vol.2023 No.07
Generative artificial intelligence (AI) tools such as ChatGPT, Dall-E, and Steve AI can facilitate instant content creation. As an illustration, a fashion brand can simply command ChatGPT to: “Write an Instagram caption about the importance of good clothes during winter in two hundred words”. In seconds, ChatGPT generates the output. This minimum effort and short production time in the usage of generative AI may enhance content marketing outcomes. However—as warned by scholars (Bruyn et al., 2020)—not only is it advantageous for businesses, AI can also be disastrous. Underpinned by this, and the fact that generative AI and content marketing are nonexistent in the pertinent literature (see streams of research on AI in marketing e.g., Eriksson et al., 2020; Huang & Rust, 2021, 2022; Vla?i? et al., 2022), this research aims to explore the potential benefits and drawbacks of generative AI for content marketing.
Homeira Sajjadi,Gholamreza Ghaedamini Harouni,Hassan Rafiey,Mohammadreza Vaez-Mahdavi,Meroe Vameghi,Seyed Hossein Mohaqeqi Kamal 대한예방의학회 2020 Journal of Preventive Medicine and Public Health Vol.53 No.3
Objectives: Our aim was to answer the following questions: (1) Can mental health variance be partitioned to individual and higher levels (e.g., neighborhood and district); (2) How much (as a percentage) do individual-level determinants explain the variability of mental health at the individual-level; and (3) How much do determinants at the neighborhood- or district-level explain the variability of mental health at the neighborhood- or district-level? Methods: We used raw data from the second round of the Urban Health Equity Assessment and Response Tool in Tehran (in 2012-2013, n=34 700 samples nested in 368 neighborhoods nested in 22 districts) and the results of the official report of Tehran’s Center of Studies and Planning (in 2012-2013, n=22 districts). Multilevel linear regression models were used to answer the study questions. Results: Approximately 40% of Tehran residents provided responses suggestive of having mental health disorders (30-52%). According to estimates of residual variance, 7% of mental health variance was determined to be at the neighborhood-level and 93% at the individual-level. Approximately 21% of mental health variance at the individual-level and 49% of the remaining mental health variance at the neighborhood-level were determined by determinants at the individual-level and neighborhood-level, respectively. Conclusions: If we want to make the most effective decisions about the determinants of mental health, in addition to considering the therapeutic perspective, we should have a systemic or contextual view of the determinants of mental health.
78 fs SWCNT-SA mode-locked Tm:CLNGG disordered garnet crystal laser at 2017 nm
Wang, Yicheng,Zhao, Yongguang,Pan, Zhongben,Bae, Ji Eun,Choi, Sun Young,Rotermund, Fabian,Loiko, Pavel,Serres, Josep Maria,Mateos, Xavier,Yu, Haohai,Zhang, Huaijin,Mero, Mark,Griebner, Uwe,Petrov, Val The Optical Society 2018 Optics letters Vol.43 No.17