55 research outputs found

    Dynamic spatio-temporal graph neural networks for hot topic prediction in scientific literature

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    With information explosion occurring in past decades, the rapid growth of papers published results in the rapid change of hot topics, especially in the biomedical domain. It turns out very hard for researchers who are interested in biomedical domain to track hot topics over time, as well as to predict the trends of them in the near future. Based on the above demand, it is important to have a model which is able to follow and predict the trend of hot topics continuously. Deep learning has been proven to be an efficient method to extract information from texts and use the information to predict the future trends. Under the thriving background of Deep Learning, Graph Neural Network (GNN) is able to capture the information from graph structures. There are various applications using GNN models, such as traffic flow prediction, chemical structure discovering, etc. In this research project, a dynamic spatio-temporal graph neural network is presented to keep track of the selected hot keywords and topics in the biomedical domain and predict the possible frequencies in the near future. The input of the model is obtained by extracting the monthly frequency information of selected keywords and topics from paper abstracts in PubMed, the largest biomedical literature collection. After training with data over a decade, the model is able to predict trends of selected hot keywords and topics in next 5 months. Thus, the presented model can help follow the trend of hot topics in the biomedical domain.Includes bibliographical reference

    Regularization Method for the Approximate Split Equality Problem in Infinite-Dimensional Hilbert Spaces

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    We studied the approximate split equality problem (ASEP) in the framework of infinite-dimensional Hilbert spaces. Let , , and   be infinite-dimensional real Hilbert spaces, let and   be two nonempty closed convex sets, and let and   be two bounded linear operators. The ASEP in infinite-dimensional Hilbert spaces is to minimize the function over and . Recently, Moudafi and Byrne had proposed several algorithms for solving the split equality problem and proved their convergence. Note that their algorithms have only weak convergence in infinite-dimensional Hilbert spaces. In this paper, we used the regularization method to establish a single-step iterative for solving the ASEP in infinite-dimensional Hilbert spaces and showed that the sequence generated by such algorithm strongly converges to the minimum-norm solution of the ASEP. Note that, by taking in the ASEP, we recover the approximate split feasibility problem (ASFP)

    Thrombospondin-1 Contributes to Mortality in Murine Sepsis through Effects on Innate Immunity

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    BACKGROUND:Thrombospondin-1 (TSP-1) is involved in many biological processes, including immune and tissue injury response, but its role in sepsis is unknown. Cell surface expression of TSP-1 on platelets is increased in sepsis and could activate the anti-inflammatory cytokine transforming growth factor beta (TGFβ1) affecting outcome. Because of these observations we sought to determine the importance of TSP-1 in sepsis. METHODOLOGY/PRINCIPAL FINDINGS:We performed studies on TSP-1 null and wild type (WT) C57BL/6J mice to determine the importance of TSP-1 in sepsis. We utilized the cecal ligation puncture (CLP) and intraperitoneal E. coli injection (i.p. E. coli) models of peritoneal sepsis. Additionally, bone-marrow-derived macrophages (BMMs) were used to determine phagocytic activity. TSP-1-/- animals experienced lower mortality than WT mice after CLP. Tissue and peritoneal lavage TGFβ1 levels were unchanged between animals of each genotype. In addition, there is no difference between the levels of major innate cytokines between the two groups of animals. PLF from WT mice contained a greater bacterial load than TSP-1-/- mice after CLP. The survival advantage for TSP-1-/- animals persisted when i.p. E. coli injections were performed. TSP-1-/- BMMs had increased phagocytic capacity compared to WT. CONCLUSIONS:TSP-1 deficiency was protective in two murine models of peritoneal sepsis, independent of TGFβ1 activation. Our studies suggest TSP-1 expression is associated with decreased phagocytosis and possibly bacterial clearance, leading to increased peritoneal inflammation and mortality in WT mice. These data support the contention that TSP-1 should be more fully explored in the human condition

    The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016)

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    Measurement of enterprise management efficiency based upon information entropy and evidence theory

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    The measurement of enterprise management efficiency is a complex and important system involving many mutual-coupling and unknown or uncertain factors. Using the information entropy principle, the weight vector of these factors can be calculated objectively. Based on this, the evidences were given by the product vector of the factor weight vector and the factor sample vector and the basic probability assignment (BPA) was obtained using matrix theory. Furthermore, the measurement model of management efficiency was established by D-S evidence. Finally, a verification case of management efficiency was given using the data that is stored in the database of enterprise management information system and the information that is given by management experts. The case results indicated that both the above method and model could decouple these mutual-coupling factors and could measure the enterprise management efficiency objectively and accurately. The method and model are not only capable for measuring management efficiency of same and different enterprises, but also for extracting decision-making information to improve enterprise management efficiency.enterprise management efficiency; information entropy principle; Dempster-Shafer theory; D-S evidence theory; uncertain reasoning technology; management science; factor weight vectors; factor sample vectors; basic probability assignment; BPA; matrix theories; management information systems; MIS; decision making.

    Regularization Method for the Approximate Split Equality Problem in Infinite-Dimensional Hilbert Spaces

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    We studied the approximate split equality problem (ASEP) in the framework of infinite-dimensional Hilbert spaces. Let 1 , 2 , and 3 be infinite-dimensional real Hilbert spaces, let ⊂ 1 and ⊂ 2 be two nonempty closed convex sets, and let : 1 → 3 and : 2 → 3 be two bounded linear operators. The ASEP in infinite-dimensional Hilbert spaces is to minimize the function ( , ) = (1/2)‖ − ‖ 2 2 over ∈ and ∈ . Recently, Moudafi and Byrne had proposed several algorithms for solving the split equality problem and proved their convergence. Note that their algorithms have only weak convergence in infinite-dimensional Hilbert spaces. In this paper, we used the regularization method to establish a single-step iterative for solving the ASEP in infinite-dimensional Hilbert spaces and showed that the sequence generated by such algorithm strongly converges to the minimum-norm solution of the ASEP. Note that, by taking = in the ASEP, we recover the approximate split feasibility problem (ASFP)

    Ecosystem Service Trade-Offs and Spatial Pattern Optimisation under Different Land Use Scenarios: A Case Study in Guanzhong Region, China

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    Understanding the complex interactions (i.e., trade-offs and synergies) among ecosystem services (ESs) and exploring land use optimisation are important to realize regional ecological governance and sustainable development. This study examined Guanzhong Region, Shaanxi Province, as the research object. We established 12 future land use scenarios and projected the future land use patterns under the future climate change scenarios and local development policies. Next, we assessed the four main ecosystem services—carbon sequestration (CS), habitat quality (HQ), soil conservation (SC), and food supply (FS) by using related formulas and the InVEST model. Furthermore, the production possibility frontier (PPF) was used to measure trade-offs and synergistic relationships among ESs, and extract the optimal ES group under the different target needs. The results are as follows: (1) In the future 12 land use scenarios of 2050 in Guanzhong Region, forested land increased evidently in the RCP2.6 ecological protection scenario (18,483.64 km). In the RCP6.0 rapid urban development scenario, construction land showed evident expansion in the central and northeastern areas (4764.52 km2). (2) Compared with the ESs under the future multiple scenarios, CS and HQ achieved the maximum value in the RCP8.5 ecological protection scenario. In the RCP2.6 ecological protection scenario, the amount of SC was the largest (3.81 × 106 t). FS in the RCP2.6 business as usual scenario got the maximum value (18.53 × 106 t). (3) By drawing the optimal PPF curve of multiple scenarios in 2050, trade-off relationships were found between FS and CS, HQ, and SC, and synergistic relationships were found between CS, HQ, and SC. Next, the optimal ES groups under the fitted curve were selected by comparing with the ESs of 2018, and adjusting the land use areas and spatial pattern to finally optimise the relationships between ES and achieve the best land use spatial pattern

    Resonant Coupling of Hermite-Gaussian Transverse Modes in the Triangular Cavity of a Cavity Ring-down Spectroscope

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    During resonance in resonant cavities, such as those used in laser or cavity ring-down spectroscopes (CRDS), resonant coupling between higher-order transverse modes and fundamental modes can seriously affect the quality of the beam and introduce measurement errors. Several coupling models, such as thermal deformation coupling and scattering coupling, have been established according to existing coupling theory and specific application scenarios; however, these coupling models have not been attributed to a unified theory. In this paper, we reveal that the same resonant coupling excitation factors exist under different types of environmental perturbation. The conditions and range of resonant coupling in a CRDS ring-down cavity are systematically analyzed, and a preferential coupling model of the middle-order modes is proposed. The time-domain characteristics of the CRDS are used in experiments to analyze the resonant coupling between the modes in a weak energy system. The order and coupling range of the middle-order modes involved in resonant coupling are verified using the modal filtering characteristics of the triangular cavity; this paper presents a unified explanation for various types of resonant coupling and also provides a new approach to resonant coupling experiments performed in high-finesse resonant cavities

    Responses of <i>Larix principis-rupprechtii</i> Radial Growth to Climatic Factors at Different Elevations on Guancen Mountain, North-Central China

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    Larix principis-rupprechtii is an important afforestation tree species in the North China alpine coniferous forest belt. Studying the correlations and response relationships between Larix principis-rupprechtii radial growth and climatic factors at different elevations is helpful for understanding the growth trends of L. principis-rupprechtiind its long-term sensitivity and adaptability to climate change. Pearson correlation, redundancy (RDA), and sliding analysis were performed to study the correlations and dynamic relationships between radial growth and climatic factors. The main conclusions are as follows: (1) The three-elevation standard chronologies all exhibited high characteristic values, contained rich climate information and were suitable for tree-ring climatological analyses. (2) Both temperature and precipitation restricted low-elevation L. principis-rupprechtii radial growth, while monthly maximum temperatures mainly affected mid-high-elevation L. principis-rupprechtii radial growth. (3) Mid-elevation L. principis-rupprechtii radial growth responded to climate factors with a “lag effect” and was not restricted by spring and early summer drought. (4) Long-term sliding analysis showed that spring temperatures and winter precipitation were the main climatic factors restricting L. principis-rupprechtii growth under warming and drying climate trends at different elevations. The tree-ring width index and Palmer drought severity index (PDSI) were positively correlated, indicating that L. principis-rupprechtii growth is somewhat restricted by drought. These results provide a reference and guidance for L. principis-rupprechtii management and sustainable development in different regions under warming and drying background climate trends
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