5,961 research outputs found

    Histological and Biomechanical Evaluation of the Preserved Degenerative Dermis in Rat Autologous Skin Transplant Models after a Deep Second Degree Burn

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    To describe the histological and biomechanical changes of the preserved degenerative dermis in rat  autologous skin transplant models after a deep second-degree burn. 50 SD rats were divided into 5 groups  randomly of 10 rats of each: 7-days group, 9-days group, 14-days group, 21-days group, and 60-days group.  Deep second-degree burn wounds were prepared on the back of rats sized 3.5cm×3.5cm. Super tangential  excision was performed on the burn wound to preserve the degenerative dermis. Then, autologous epidermis  was grafted on the wound. After that, the histological changes of the preserved degenerative dermis tissues  and the graft areas were observed by macroscopic, light microscope and electron microscope in the 7, 9, 14,  21, 60 days after the operation. Moreover, the tensile properties of healing deeply burned rat skin were also  tested for each group at the same time points mentioned above. Results: (1) According to the macroscopic  observation, 7 days after the operation, the grafted skin was fused with the area of burn wound; A few hairs  were growing out on the skin at the 14th day; the injured skin recovered to normality by the 60th day. (2)  Hyaline change occurred in the preserved degenerative dermis tissues based on the observation by light  microscope. At the 7th day after operation, the dermis papillae and reticular layer could be discerned; by  the 21st day, the thickness, structures and morphology of grafted skin were similar to the normal tissues. (3)  7 days after operation, ballooning changes were observed by the electron microscope in the mitochondria  and endoplasmic reticulum of damaged cells and the number of the ribosomes was obviously reduced. The  subcellular wound improved continuously and approached normality by the 21st day. (4) 9 days after the  operation, the tensible strength and maximal strain of the grafting rat skin approached 70% and 90% of  natural skin, respectively. (5) 60 days after the operation, the tensile performance of the healing rat skin  recovered to the natural level. Conclusion: The histological and biomechanical changes of the denatured dermis of a deep second  degree burn wound may gradually recover to normality after being covered by autologous skin.

    Development of beam arrangement design for tunable diode laser absorption tomography reconstruction based on Tikhonov regularization parameter matrix

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    Improving Text Matching in E-Commerce Search with A Rationalizable, Intervenable and Fast Entity-Based Relevance Model

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    Discovering the intended items of user queries from a massive repository of items is one of the main goals of an e-commerce search system. Relevance prediction is essential to the search system since it helps improve performance. When online serving a relevance model, the model is required to perform fast and accurate inference. Currently, the widely used models such as Bi-encoder and Cross-encoder have their limitations in accuracy or inference speed respectively. In this work, we propose a novel model called the Entity-Based Relevance Model (EBRM). We identify the entities contained in an item and decompose the QI (query-item) relevance problem into multiple QE (query-entity) relevance problems; we then aggregate their results to form the QI prediction using a soft logic formulation. The decomposition allows us to use a Cross-encoder QE relevance module for high accuracy as well as cache QE predictions for fast online inference. Utilizing soft logic makes the prediction procedure interpretable and intervenable. We also show that pretraining the QE module with auto-generated QE data from user logs can further improve the overall performance. The proposed method is evaluated on labeled data from e-commerce websites. Empirical results show that it achieves promising improvements with computation efficiency

    A data analysis method for isochronous mass spectrometry using two time-of-flight detectors at CSRe

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    The concept of isochronous mass spectrometry (IMS) applying two time-of-flight (TOF) detectors originated many years ago at GSI. However, the corresponding method for data analysis has never been discussed in detail. Recently, two TOF detectors have been installed at CSRe and the new working mode of the ring is under test. In this paper, a data analysis method for this mode is introduced and tested with a series of simulations. The results show that the new IMS method can significantly improve mass resolving power via the additional velocity information of stored ions. This improvement is especially important for nuclides with Lorentz factor γ\gamma-value far away from the transition point γt\gamma _t of the storage ring CSRe.Comment: published in Chinese Physics C Vol. 39, No. 10 (2015) 10620

    XCloud-VIP: Virtual Peak Enables Highly Accelerated NMR Spectroscopy and Faithful Quantitative Measures

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    Background: Nuclear Magnetic Resonance (NMR) spectroscopy is an important bio-engineering tool to determine the metabolic concentrations, molecule structures and so on. The data acquisition time, however, is very long in multi-dimensional NMR. To accelerate data acquisition, non-uniformly sampling is an effective way but may encounter severe spectral distortions and unfaithful quantitative measures when the acceleration factor is high. Objective: To reconstruct high fidelity spectra from highly accelerated NMR and achieve much better quantitative measures. Methods: A virtual peak (VIP) approach is proposed to self-learn the prior spectral information, such as the central frequency and peak lineshape, and then feed these information into the reconstruction. The proposed method is further implemented with cloud computing to facilitate online, open, and easy access. Results: Results on synthetic and experimental data demonstrate that, compared with the state-of-the-art method, the new approach provides much better reconstruction of low-intensity peaks and significantly improves the quantitative measures, including the regression of peak intensity, the distances between nuclear pairs, and concentrations of metabolics in mixtures. Conclusion: Self-learning prior peak information can improve the reconstruction and quantitative measures of spectra. Significance: This approach enables highly accelerated NMR and may promote time-consuming applications such as quantitative and time-resolved NMR experiments
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