4,354 research outputs found

    Graduate Catalog of Studies, 2023-2024

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    Investigating the effects of palmitoylation on the dopamine 1 receptor (D1)

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    The dopamine D1 receptor (D1) is a G protein-coupled receptor (GPCR) which regulates various key brain functions like attention, movement, reward, and memory. Understanding D1 signalling may open the horizon for novel treatments for neurological disorders. Upon agonist activation, the heterotrimeric G proteins Gαs activate adenylyl cyclase to increase cAMP/PKA signalling. D1 also engages β-arrestin proteins leading to β-arrestin dependent signalling. The D1 has two palmitoylation sites on cysteines 347&351 in its C-tail domain. However, the distinct roles and implications of palmitoylation on the D1 signalling, trafficking and β-arrestins recruitment are still largely unexplored. A palmitoylation D1 mutant was generated and luminescent based techniques such as BRET and split-Nanoluc complementation assay were employed, to delineate D1 palmitoylation effects on its pharmacology and signalling. The D1 agonists induced 50% less cAMP production in the mutant compared to wildtype (WT) and WT showed a more efficient dissociation of its Gαs. Moreover, the mutant receptor failed to recruit β-arrestin1&2, induced less ERK1/2 activation and internalises in an agonist-independent process while showing an altered intracellular Golgi trafficking. Also, in β-arrestin 1&2 KO HEK 293 cells similar cAMP production levels were reported for D1 WT and palmitoylation mutant. β-arrestin 1&2 KO blocked agonist-induced WT D1 plasma membrane trafficking, indicating that these β-arrestins are driving the differences between WT and the palmitoylation mutant D1. Taken together, our studies indicate that Gαs is the main transducer for D1 cAMP and ERK1/2 signalling and that palmitoylation is essential for its β-arrestin 1&2 interactions and modulating D1 signalling cascades in a drug-dependant process

    Southern Adventist University Undergraduate Catalog 2023-2024

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    Southern Adventist University\u27s undergraduate catalog for the academic year 2023-2024.https://knowledge.e.southern.edu/undergrad_catalog/1123/thumbnail.jp

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Graduate Catalog of Studies, 2023-2024

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    A Simple and Effective Method of Cross-Lingual Plagiarism Detection

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    We present a simple cross-lingual plagiarism detection method applicable to a large number of languages. The presented approach leverages open multilingual thesauri for candidate retrieval task and pre-trained multilingual BERT-based language models for detailed analysis. The method does not rely on machine translation and word sense disambiguation when in use, and therefore is suitable for a large number of languages, including under-resourced languages. The effectiveness of the proposed approach is demonstrated for several existing and new benchmarks, achieving state-of-the-art results for French, Russian, and Armenian languages

    UMSL Bulletin 2022-2023

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    The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp

    Approximating Human-Like Few-shot Learning with GPT-based Compression

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    In this work, we conceptualize the learning process as information compression. We seek to equip generative pre-trained models with human-like learning capabilities that enable data compression during inference. We present a novel approach that utilizes the Generative Pre-trained Transformer (GPT) to approximate Kolmogorov complexity, with the aim of estimating the optimal Information Distance for few-shot learning. We first propose using GPT as a prior for lossless text compression, achieving a noteworthy compression ratio. Experiment with LLAMA2-7B backbone achieves a compression ratio of 15.5 on enwik9. We justify the pre-training objective of GPT models by demonstrating its equivalence to the compression length, and, consequently, its ability to approximate the information distance for texts. Leveraging the approximated information distance, our method allows the direct application of GPT models in quantitative text similarity measurements. Experiment results show that our method overall achieves superior performance compared to embedding and prompt baselines on challenging NLP tasks, including semantic similarity, zero and one-shot text classification, and zero-shot text ranking

    “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

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    Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

    A Tale of Two Trees: A Comparative Study on the Effects of Scale and Biodiversity Efforts in Ghana’s Cocoa and Shea Production Networks

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    This thesis presents two case studies on Ghana’s cocoa and shea production networks, focusing on the effects of scale on biodiversity sustainability dissemination. Analysis is done through my unique holistic framework for action-based production network analysis, which provides a robust and multiscalar analysis to answer my main research question How does scale affect biodiversity sustainability throughout Ghana’s cocoa and shea production networks? The two case studies focus on Ghana’s cocoa and shea production network coordination and the action taken up by different levels of actors within scale, their considerations of, approaches to, and outcomes of biodiversity sustainability dissemination throughout their Ghanaian cocoa production networks. These case studies focus on the history and context of the cocoa and shea sectors as they function within Ghana’s agricultural industry, the influencers, and barriers to biodiversity sustainability dissemination throughout the studied production networks, and the effects of scale on this sustainability attainment. My research is support through primary data collected in Ghana and secondary data. The two case studies are then cross-analysed to draw out the commonalities in context, issues faced, and effects of scale on the studied sustainability aspects. The findings of this research show that in order to achieve biodiversity sustainability, social sustainability must be incorporated into production network coordination and that the level of actors’ scale and scalar approach to network coordination significantly impact achievement of biodiversity sustainability dissemination. The results of this thesis are novel in the fact that it combines several streams of analytical consideration into a holistic framework and presents clear and applicable results that can significantly impact the approach to sustainability dissemination throughout global production networks in an equitable manner that is fit to the context within which production takes place
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