Thank you for sharing this story! However, please do so in a way that respects the copyright of this text. If you want to share or reproduce this full text, please ask permission from Innovation Origins (partners@innovationorigins.com) or become a partner of ours! You are of course free to quote this story with source citation. Would you like to share this article in another way? Then use this link to the article: https://innovationorigins.com/en/silicon-sampling-ai-powered-personas-offer-new-insights-for-market-research-but-have-limitations/ n the rapidly evolving field of marketing and communication, staying ahead means embracing technological innovations. The latest breakthrough, silicon sampling, leverages AI to revolutionize market research by creating synthetic personas that mimic human responses. This method, which utilizes large language models (LLMs) like GPT-4o, offers a cost-efficient and less time-consuming alternative to traditional market research. Roberta Vaznyte and Marieke van Vliet (Fontys University of Applied Science) have explored the promise and challenges of silicon sampling, highlighting key findings from recent experiments and the implications for the future of market research.
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We present a simple analytical formalism based on the Lorentz-Scherrer equation and Bernoulli statistics for estimating the fraction of crystallites (and the associated uncertainty parameters) contributing to all finite Bragg peaks of a typical powder pattern obtained from a static polycrystalline sample. We test and validate this formalism using numerical simulations, and show that they can be applied to experiments using monochromatic or polychromatic (pink-beam) radiation. Our results show that enhancing the sampling efficiency of a given powder diffraction experiment for such samples requires optimizing the sum of the multiplicities of reflections included in the pattern along with the wavelength used in acquiring the pattern. Utilizing these equations in planning powder diffraction experiments for sampling efficiency is also discussed.
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This systematic review describes and discusses three commercially available integrated systems for forensic DNA analysis, i.e., ParaDNA, RapidHIT, and ANDE. A variety of aspects, such as performance, time-to-result, ease-of-use, portability, and costs (per analysis run) of these three (modified) rapid DNA analysis systems, are considered. Despite their advantages and developmental progress, major steps still have to be made before rapid systems can be broadly applied at crime scenes for full DNA profiling. Aspects in particular that need (further) improvement are portability, performance, the possibility to analyze a (wider) variety of (complex) forensic samples, and (cartridge) costs. Moreover, steps forward regarding ease-of-use and time-to-result will benefit the broader use of commercial rapid DNA systems. In fact, it would be a profit if rapid DNA systems could be used for full DNA profile generation as well as indicative analyses that can give direction to forensic investigators which will speed up investigations.
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