4,763 research outputs found

    The production of charmonium pentaquark from b-baryon and B-meson decay: SU(3) analysis

    Full text link
    In this paper, we study the production of charmonium pentaquark ccˉqqqc \bar c q q q from bottom baryon and B-meson decays under the flavor SU(3) symmetry. Decay amplitudes for various processes are parametrized in terms of the SU(3) irreducible nonperturbative amplitudes. A number of relations between decay widths have been deduced. Moreover, the strong decays of pentaquark is also taken into account. These results can be tested in future measurements at LHCb, Belle II and CEPC. Once a few decay branching fractions have been measured, our work could provide hints for exploring new decay channels or new pentaquark states.Comment: 10 pages,2 figure

    NExT-GPT: Any-to-Any Multimodal LLM

    Full text link
    While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides, they mostly fall prey to the limitation of only input-side multimodal understanding, without the ability to produce content in multiple modalities. As we humans always perceive the world and communicate with people through various modalities, developing any-to-any MM-LLMs capable of accepting and delivering content in any modality becomes essential to human-level AI. To fill the gap, we present an end-to-end general-purpose any-to-any MM-LLM system, NExT-GPT. We connect an LLM with multimodal adaptors and different diffusion decoders, enabling NExT-GPT to perceive inputs and generate outputs in arbitrary combinations of text, images, videos, and audio. By leveraging the existing well-trained highly-performing encoders and decoders, NExT-GPT is tuned with only a small amount of parameter (1%) of certain projection layers, which not only benefits low-cost training and also facilitates convenient expansion to more potential modalities. Moreover, we introduce a modality-switching instruction tuning (MosIT) and manually curate a high-quality dataset for MosIT, based on which NExT-GPT is empowered with complex cross-modal semantic understanding and content generation. Overall, our research showcases the promising possibility of building an AI agent capable of modeling universal modalities, paving the way for more human-like AI research in the community. Project page: https://next-gpt.github.io/Comment: work in progres

    Buccal Transmucosal Delivery System of Enalapril for Improved Cardiac Drug Delivery: Preparation and Characterization

    Get PDF
    Purpose: To prepare and characterize buccal transmucosal delivery system of enalapril maleate for overcoming its low bioavailability, and hence provide improved therapeutic efficacy and patient compliance.Methods: Transmucosal drug delivery systems of enalapril maleate were formulated as buccal films by solvent casting technique using polyvinylpyrrolidone K90, hydroxypropyl methylcellulose, sodium carboxymethylcellulose (high viscosity). The films were evaluated for film weight, thickness, folding endurance, drug content uniformity, surface pH, in vitro residence time, in vitro drug release and ex-vivo permeation.Results: All the formulations showed high drug content (96.45 to 98.49 %). Those with good swelling showed good residence time. In vitro drug release was highest for films prepared with high viscosity grade sodium carboxymethylcellulose (SCMC- HV,F2), releasing 92.24 % of drug in 1.5 h) followed by F4 (containing polyvinyl pyrrolidone K-90 1 % w/v and SCMC (HV) 1 % w/v). Ex-vivo drug permeation at the end of 10 h was 82.24 and 89.9 % for F2 and F4, respectively.Conclusion: Prompt drug release was obtained from the formulation (F2) containing SCMC 2 % w/v with 10 mg enalapril. However, on the basis of the highest swelling and residence time, and controlled drug release, formulation F4 (containing PVP K-90 and SCMC HV) would be suitable for the development of buccal film for effective therapy of cardiac diseases.Keywords: Cardiac disease, Transmucosal, Buccal films, Enalapril maleate, Drug release, Ex-vivo permeatio

    Surface variation analysis of freeform optical systems over surface frequency bands for prescribed wavefront errors

    Full text link
    The surface errors of freeform surfaces reflect the manufacturing complexities and significantly impact the feasibility of processing designed optical systems. With multiple degrees of freedom, freeform surfaces pose challenges in surface tolerance analysis in the field. Nevertheless, current research has neglected the influence of surface slopes on the directions of ray propagation. A sudden alteration in the surface slope will lead to a corresponding abrupt shift in the wavefront, even when the change in surface sag is minimal. Moreover, within the realm of freeform surface manufacturing, variation in surface slope across different frequency bands may give rise to unique surface variation. Within the context of this study, we propose a tolerance analysis method to analyze surface variation in freeform surfaces considering surface frequency band slopes based on real ray data. This approach utilizes real ray data to rapidly evaluate surface variation within a specified frequency band of surface slopes. Crucially, our proposed method yields the capability to obtain system surface variation with significant wavefront aberration, in contrast to previous methodologies. The feasibility and advantages of this framework are assessed by analyzing a single-mirror system with a single field and an off-axis two-mirror system. We expect to integrate the proposed methodology with freeform surface design and manufacturing, thereby expanding the scope of freeform optics
    corecore