9,996 research outputs found

    Variation of Mycobacterium tuberculosis antigen-specific IFN-γ and IL-17 responses in healthy tuberculin skin test (TST)-positive human subjects.

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    ObjectiveTo determine the variation of IFN-γ and IL-17 responses to M. tuberculosis antigens in healthy TST+ humans.MethodsWe isolated peripheral blood mononuclear cells from 21 TST+ healthy adults, stimulated them with phytohemagglutinin (PHA), PPD, Ag85B, ESAT-6, and live M. bovis BCG, and assayed IFN-γ and IL-17 secretion by ELISA in supernatants after 24 or 72 hours of incubation respectively.ResultsAs in other studies, we found a wide range of IFN-γ responses to M. tuberculosis antigens; the variation significantly exceeded that observed in the same donors to the polyclonal T cell stimulus, phytohemagglutinin (PHA). In addition, we assayed IL-17 secretion in response to the same stimuli, and found less subject-to-subject variation. Analysis of the ratio of IFN-γ to IL-17 secretion on a subject-to-subject basis also revealed a wide range, with the majority of results distributed in a narrow range, and a minority with extreme results all of which were greater than that in the majority of subjects. The data suggest that study of exceptional responses to M. tuberculosis antigens may reveal immunologic correlates with specific outcomes of M. tuberculosis infection.ConclusionVariation of IFNγ and IFN-γ/IL-17 responses to mycobacterial antigens exceeds that of responses to the polyclonal stimulus, PHA, in TST positive healthy humans. This indicates a quantitative spectrum of human immune responses to infection with M. tuberculosis. Since the outcome of human infection with M. tuberculosis varies greatly, systematic study of multiple immune responses to multiple antigens is likely to reveal correlations between selected immune responses and the outcomes of infection

    Product Pricing Based on Activity-Based Costing

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    Activity-based costing could provide relatively accurate cost information and better serve the enterprise’s product pricing decision. Through the analysis of cost behavior on activities, it divides product costs into unit level, batch level, product-sustaining level and facility level activity costs, which can avoid the overlapping between the costs caused by dividing the costs into variable cost, activity cost and fixed cost. On this base, product pricing model is established based on the information of activity based costing. Case study shows that different pricing methods get different prices, which will provide different product-mix pricing decisions for enterprises. Keywords: Activity-based costing, Pricing decisions, Cost behavio

    Observation of Landau level-like quantizations at 77 K along a strained-induced graphene ridge

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    Recent studies show that the electronic structures of graphene can be modified by strain and it was predicted that strain in graphene can induce peaks in the local density of states (LDOS) mimicking Landau levels (LLs) generated in the presence of a large magnetic field. Here we report scanning tunnelling spectroscopy (STS) observation of nine strain-induced peaks in LDOS at 77 K along a graphene ridge created when the graphene layer was cleaved from a sample of highly oriented pyrolytic graphite (HOPG). The energies of these peaks follow the progression of LLs of massless 'Dirac fermions' (DFs) in a magnetic field of 230 T. The results presented here suggest a possible route to realize zero-field quantum Hall-like effects at 77 K

    Finding cultural heritage images through a Dual-Perspective Navigation Framework

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    With the increasing volume of digital images, improving techniques for image findability is receiving heightened attention. The cultural heritage sector, with its vast resource of images, has realized the value of social tags and started using tags in parallel with controlled vocabularies to increase the odds of users finding images of interest. The research presented in this paper develops the Dual-Perspective Navigation Framework (DPNF), which integrates controlled vocabularies and social tags to represent the aboutness of an item more comprehensively, in order that the information scent can be maximized to facilitate resource findability. DPNF utilizes the mechanisms of faceted browsing and tag-based navigation to offer a seamless interaction between experts’ subject headings and public tags during image search. In a controlled user study, participants effectively completed more exploratory tasks with the DPNF interface than with the tag-only interface. DPNF is more efficient than both single descriptor interfaces (subject heading-only and tag-only interfaces). Participants spent significantly less time, fewer interface interactions, and less back tracking to complete an exploratory task without an extra workload. In addition, participants were more satisfied with the DPNF interface than with the others. The findings of this study can assist interface designers struggling with what information is most helpful to users and facilitate searching tasks. It also maximizes end users’ chances of finding target images by engaging image information from two sources: the professionals’ description of items in a collection and the crowd's assignment of social tags

    Nonlinear optomechanical resonance entering a self-organized energy transfer pattern

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    The energy transfer between different subsystems or different vibration modes is always one of the most interested problems in the study of the resonance phenomena in coupled nonlinear dynamical systems. With an optomechanical system operating in the regime of unresolved sideband, where its mechanical frequency is lower than the cavity field damping rate, we illustrate the existence of a special nonlinear resonance phenomenon. This type of previously unknown resonance manifests an organized pattern of the coupled cavity field and mechanical oscillation, so that the cavity field precisely pushes the mechanical oscillator within an appropriate small time window in each mechanical oscillation period and the mechanical energy will increase by a jump of almost fixed amount after each oscillation cycle. The scenario is realized at a resonance point where the frequency difference of two driving fields matches the mechanical frequency of the system, and this condition of drive-frequency match is found to trigger a mechanism to lock the two subsystems of an unresolved-sideband optomechanical system into a highly ordered energy transfer as the above mentioned. Due to a significantly enhanced nonlinearity in the vicinity of the resonance point, optical frequency combs can be generated under pump powers of thousand times lower, as compared to the use of a single-tone driving field for the purpose. An unresolved sideband system under the drives without satisfying the resonance condition also demonstrates other interesting dynamical behaviors. Most of all, by providing a realistic picture for the nonlinear optomechanical dynamics in unresolved sideband regime, our study points to a direction to observe novel dynamical phenomena and realize other applications with the systems of less technical restrictions.Comment: 13 pages, 13 figures. To be published on Chaos, Solitons & Fractal

    Green credit policy and corporate climate risk exposure

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    This paper investigates the effects of green credit policies on corporate climate risk exposure and the underlying mechanisms in China. Our results show that after the introduction of green credit policies, enterprises in polluting industries experienced a notable decline in climate risk compared to their counterparts. Further analysis reveals that the effectiveness of green credit policies in mitigating corporate climate risks can be attributed to their capacity to foster green technological innovation, refine investment strategies, facilitate the process of digitalization, and enhance the visibility of environmental issues among analysts. Moreover, we find that climate risk shaping policies vary significantly among firms, with particularly pronounced impacts on financially constrained and state-owned enterprises. This study provides critical insights for policymakers aiming to address climate challenges and bolster green financial strategies
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