11,468 research outputs found

    A new estimation method for multivariate Markov chain model with application in demand predictions

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    In this paper, we propose a new estimation method for the parameters of a multivariate Markov chain model. In the new method, we calculate the correlations of the sequences first and establish multivariate Markov chain models for those positively correlated sequences. The parameters are estimated by minimizing the error of prediction. We apply the method to demand predictions for a soft-drink company in Hong Kong. Numerical experiments are given to show the effectiveness of our proposed method. © 2010 IEEE.published_or_final_versionThe 3rd International Conference on Business Intelligence and Financial Engineering (BIFE 2010), Hong Kong, 13-15 August 2010. In Proceedings of the 3rd BIFE, 2010, p. 126-13

    The inhabited environment, infrastructure development and advanced urbanization in China's Yangtze River Delta Region

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    This paper analyzes the relationship among the inhabited environment, infrastructure development and environmental impacts in China's heavily urbanized Yangtze River Delta region. Using primary human environment data for the period 2006-2014, we examine factors affecting the inhabited environment and infrastructure development: urban population, GDP, built-up area, energy consumption, waste emission, transportation, real estate and urban greenery. Then we empirically investigate the impact of advanced urbanization with consideration of cities' differences. Results from this study show that the growth rate of the inhabited environment and infrastructure development is strongly influenced by regional development structure, functional orientations, traffic network and urban size and form. The effect of advanced urbanization is more significant in large and mid-size cities than huge and mega cities. Energy consumption, waste emission and real estate in large and mid-size cities developed at an unprecedented rate with the rapid increase of economy. However, urban development of huge and mega cities gradually tended to be saturated. The transition development in these cities improved the inhabited environment and ecological protection instead of the urban construction simply. To maintain a sustainable advanced urbanization process, policy implications included urban sprawl control polices, ecological development mechanisms and reforming the economic structure for huge and mega cities, and construct major cross-regional infrastructure, enhance the carrying capacity and improvement of energy efficiency and structure for large and mid-size cities

    Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users

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    If people with high risk of suicide can be identified through social media like microblog, it is possible to implement an active intervention system to save their lives. Based on this motivation, the current study administered the Suicide Probability Scale(SPS) to 1041 weibo users at Sina Weibo, which is a leading microblog service provider in China. Two NLP (Natural Language Processing) methods, the Chinese edition of Linguistic Inquiry and Word Count (LIWC) lexicon and Latent Dirichlet Allocation (LDA), are used to extract linguistic features from the Sina Weibo data. We trained predicting models by machine learning algorithm based on these two types of features, to estimate suicide probability based on linguistic features. The experiment results indicate that LDA can find topics that relate to suicide probability, and improve the performance of prediction. Our study adds value in prediction of suicidal probability of social network users with their behaviors

    Searching edges in the overlap of two plane graphs

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    Consider a pair of plane straight-line graphs, whose edges are colored red and blue, respectively, and let n be the total complexity of both graphs. We present a O(n log n)-time O(n)-space technique to preprocess such pair of graphs, that enables efficient searches among the red-blue intersections along edges of one of the graphs. Our technique has a number of applications to geometric problems. This includes: (1) a solution to the batched red-blue search problem [Dehne et al. 2006] in O(n log n) queries to the oracle; (2) an algorithm to compute the maximum vertical distance between a pair of 3D polyhedral terrains one of which is convex in O(n log n) time, where n is the total complexity of both terrains; (3) an algorithm to construct the Hausdorff Voronoi diagram of a family of point clusters in the plane in O((n+m) log^3 n) time and O(n+m) space, where n is the total number of points in all clusters and m is the number of crossings between all clusters; (4) an algorithm to construct the farthest-color Voronoi diagram of the corners of n axis-aligned rectangles in O(n log^2 n) time; (5) an algorithm to solve the stabbing circle problem for n parallel line segments in the plane in optimal O(n log n) time. All these results are new or improve on the best known algorithms.Comment: 22 pages, 6 figure

    Exact Hybrid Covariance Thresholding for Joint Graphical Lasso

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    This paper considers the problem of estimating multiple related Gaussian graphical models from a pp-dimensional dataset consisting of different classes. Our work is based upon the formulation of this problem as group graphical lasso. This paper proposes a novel hybrid covariance thresholding algorithm that can effectively identify zero entries in the precision matrices and split a large joint graphical lasso problem into small subproblems. Our hybrid covariance thresholding method is superior to existing uniform thresholding methods in that our method can split the precision matrix of each individual class using different partition schemes and thus split group graphical lasso into much smaller subproblems, each of which can be solved very fast. In addition, this paper establishes necessary and sufficient conditions for our hybrid covariance thresholding algorithm. The superior performance of our thresholding method is thoroughly analyzed and illustrated by a few experiments on simulated data and real gene expression data

    Revealing the Structure and Oxygen Transport at Interfaces in Complex Oxide Heterostructures via Âč⁷O NMR Spectroscopy

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    Vertically aligned nanocomposite (VAN) films, comprising nanopillars of one phase embedded in a matrix of another, have shown great promise for a range of applications due to their high interfacial areas oriented perpendicular to the substrate. In particular, oxide VANs show enhanced oxide-ion conductivity in directions that are orthogonal to those found in more conventional thin-film heterostructures; however, the structure of the interfaces and its influence on conductivity remain unclear. In this work, 17O NMR spectroscopy is used to study CeO2–SrTiO3 VAN thin films: selective isotopic enrichment is combined with a lift-off technique to remove the substrate, facilitating detection of the 17O NMR signal from single atomic layer interfaces. By performing the isotopic enrichment at variable temperatures, the superior oxide-ion conductivity of the VAN films compared to the bulk materials is shown to arise from enhanced oxygen mobility at this interface; oxygen motion at the interface is further identified from 17O relaxometry experiments. The structure of this interface is solved by calculating the NMR parameters using density functional theory combined with random structure searching, allowing the chemistry underpinning the enhanced oxide-ion transport to be proposed. Finally, a comparison is made with 1% Gd-doped CeO2–SrTiO3 VAN films, for which greater NMR signal can be obtained due to paramagnetic relaxation enhancement, while the relative oxide-ion conductivities of the phases remain similar. These results highlight the information that can be obtained on interfacial structure and dynamics with solid-state NMR spectroscopy, in this and other nanostructured systems, our methodology being generally applicable to overcome sensitivity limitations in thin-film studies

    Methane storms as a driver of Titan's dune orientation

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    Titan's equatorial regions are covered by eastward propagating linear dunes. This direction is opposite to mean surface winds simulated by Global Climate Models (GCMs), which are oriented westward at these latitudes, similar to trade winds on Earth. Different hypotheses have been proposed to address this apparent contradiction, involving Saturn's gravitational tides, large scale topography or wind statistics, but none of them can explain a global eastward dune propagation in the equatorial band. Here we analyse the impact of equinoctial tropical methane storms developing in the superrotating atmosphere (i.e. the eastward winds at high altitude) on Titan's dune orientation. Using mesoscale simulations of convective methane clouds with a GCM wind profile featuring superrotation, we show that Titan's storms should produce fast eastward gust fronts above the surface. Such gusts dominate the aeolian transport, allowing dunes to extend eastward. This analysis therefore suggests a coupling between superrotation, tropical methane storms and dune formation on Titan. Furthermore, together with GCM predictions and analogies to some terrestrial dune fields, this work provides a general framework explaining several major features of Titan's dunes: linear shape, eastward propagation and poleward divergence, and implies an equatorial origin of Titan's dune sand.Comment: Published online on Nature Geoscience on 13 April 201

    A biophysical model of cell adhesion mediated by immunoadhesin drugs and antibodies

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    A promising direction in drug development is to exploit the ability of natural killer cells to kill antibody-labeled target cells. Monoclonal antibodies and drugs designed to elicit this effect typically bind cell-surface epitopes that are overexpressed on target cells but also present on other cells. Thus it is important to understand adhesion of cells by antibodies and similar molecules. We present an equilibrium model of such adhesion, incorporating heterogeneity in target cell epitope density and epitope immobility. We compare with experiments on the adhesion of Jurkat T cells to bilayers containing the relevant natural killer cell receptor, with adhesion mediated by the drug alefacept. We show that a model in which all target cell epitopes are mobile and available is inconsistent with the data, suggesting that more complex mechanisms are at work. We hypothesize that the immobile epitope fraction may change with cell adhesion, and we find that such a model is more consistent with the data. We also quantitatively describe the parameter space in which binding occurs. Our results point toward mechanisms relating epitope immobility to cell adhesion and offer insight into the activity of an important class of drugs.Comment: 13 pages, 5 figure

    BICS01 Mediates Reversible Anti-seizure Effects in Brain Slice Models of Epilepsy

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    Drug-resistant epilepsy remains a significant clinical and societal burden, with one third of people with epilepsy continuing to experience seizures despite the availability of around 30 anti-seizure drugs (ASDs). Further, ASDs often have substantial adverse effects, including impacts on learning and memory. Therefore, it is important to develop new ASDs, which may be more potent or better tolerated. Here, we report the preliminary preclinical evaluation of BICS01, a synthetic product based on a natural compound, as a potential ASD. To model seizure-like activity in vitro, we prepared hippocampal slices from adult male Sprague Dawley rats, and elicited epileptiform bursting using high extracellular potassium. BICS01 (200 ÎŒM) rapidly and reversibly reduced the frequency of epileptiform bursting but did not change broad measures of network excitability or affect short-term synaptic facilitation. BICS01 was well tolerated following systemic injection at up to 1,000 mg/kg. However, we did not observe any protective effect of systemic BICS01 injection against acute seizures evoked by pentylenetetrazol. These results indicate that BICS01 is able to acutely reduce epileptiform activity in hippocampal networks. Further preclinical development studies to enhance pharmacokinetics and accumulation in the brain, as well as studies to understand the mechanism of action, are now required

    Lack of effectiveness of adherence counselling in reversing virological failure among patients on long-term antiretroviral therapy in rural Uganda.

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    OBJECTIVES: The current World Health Organization and Uganda Ministry of Health HIV treatment guidelines recommend that asymptomatic patients who have a viral load (VL) ≄ 1000 HIV-1 RNA copies/mL should receive adherence counselling and repeat VL testing before switching to second-line therapy. We evaluated the effectiveness of this strategy in a large HIV treatment programme of The AIDS Support Organisation Jinja in Jinja, Uganda. METHODS: We measured the HIV VL at enrolment, and for participants with VL ≄ 1000 copies/mL we informed them of their result, offered enhanced adherence counselling and repeated the VL measurement after 3 months. All blood samples with VL ≄ 1000 copies/mL were sequenced in the polymerase (pol) region, a 1257-bp fragment spanning the protease and reverse transcriptase genes. RESULTS: One thousand and ninety-one participants were enrolled in the study; 74.7% were female and the median age was 44 years [interquartile range (IQR) 39-50 years]. The median time on antiretroviral therapy (ART) at enrolment was 6.75 years (IQR 5.3-7.6 years) and the median CD4 cell count was 494 cells/ÎŒL (IQR 351-691 cells/ÎŒL). A total of 113 participants (10.4%) had VLs ≄ 1000 copies/mL and were informed of the VL result and its implications and given adherence counselling. Of these 113 participants, 102 completed 3 months of follow-up and 93 (91%) still had VLs ≄ 1000 copies/mL. We successfully genotyped HIV for 105 patients (93%) and found that 103 (98%) had at least one mutation: eight (7.6%) had only one mutation, 94 (89.5%) had two mutations and one sample (1%) had three mutations. CONCLUSIONS: In this study, enhanced adherence counselling was not effective in reversing virologically defined treatment failure for patients on long-term ART who had not previously had a VL test
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