Topic modeling applied to business research: A latent dirichlet allocation (LDA)-based classification for organization studies

More than 1.5 million academic documents are published each year, and this trend shows an incremental tendency for the following years. One of the main challenges for the academic community is how to organize this huge volume of documentation to have a sense of the knowledge frontier. In this study we applied Latent Dirichlet Allocation (LDA) techniques to identify primary topics in organization studies, and analyzed the relationships between academic impact and belonging to the topics detected by LDA

A decentralized spectrum allocation and partitioning scheme for a two-tier macro-femtocell network with downlink beamforming

This article examines spectrum allocation and partitioning schemes to mitigate cross-tier interference under downlink beamforming environments. The enhanced SIR owing to beamforming allows more femtocells to share their spectrum with the macrocell and accordingly improves overall spectrum efficiency. We first design a simplified centralized scheme as the optimum and then propose a practical decentralized algorithm that determines which femtocells to use the full or partitioned spectrum with acceptable control overhead. To exploit limited information of the received signal strength efficiently, we consider two types of probabilistic femtocell base station (HeNB) selection policies. They are equal selection and interference weighted selection policies, and we drive their outage probabilities for a macrocell user. Through performance evaluation, we demonstrate that the outage probability and the cell capacity in our decentralized scheme are significantly better than those in a conventional cochannel deployment scheme. Furthermore, we show that the cell utility in our proposed scheme is close to that in the centralized scheme and better than that in the spectrum partitioning scheme with a fixed ratio.open0

phase ii trial of tepotinib vs sorafenib for treatment naive advanced hepatocellular carcinoma hcc in asian patients

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621PDPhase II trial of tepotinib vs sorafenib in Asian patients (pts) with advanced hepatocellular carcinoma (HCC)

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Fast network centrality analysis using GPUs

<p>Abstract</p> <p>Background</p> <p>With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU) provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs.</p> <p>Results</p> <p>We proposed an efficient data parallel formulation of the All-Pairs Shortest Path problem, which is the key component for shortest path-based centrality computation. A betweenness centrality algorithm built upon this formulation was developed and benchmarked against the most recent GPU-based algorithm. Speedup between 11 to 19% was observed in various simulated scale-free networks. We further designed three algorithms based on this core component to compute closeness centrality, eccentricity centrality and stress centrality. To make all these algorithms available to the research community, we developed a software package <it>gpu</it>-<it>fan </it>(GPU-based Fast Analysis of Networks) for CUDA enabled GPUs. Speedup of 10-50× compared with CPU implementations was observed for simulated scale-free networks and real world biological networks.</p> <p>Conclusions</p> <p><it>gpu</it>-<it>fan </it>provides a significant performance improvement for centrality computation in large-scale networks. Source code is available under the GNU Public License (GPL) at <url>http://bioinfo.vanderbilt.edu/gpu-fan/</url>.</p

Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

Mesoporous carbon-containing voltammetric biosensor for determination of tyramine in food products

A voltammetric biosensor based on tyrosinase (TYR) was developed for determination of tyramine. Carbon material (multi-walled carbon nanotubes or mesoporous carbon CMK-3-type), polycationic polymer—i.e., poly(diallyldimethylammonium chloride) (PDDA), and Nafion were incorporated into titania dioxide sol (TiO(2)) to create an immobilization matrix. The features of the formed matrix were studied by scanning electron microscopy (SEM) and cyclic voltammetry (CV). The analytical performance of the developed biosensor was evaluated with respect to linear range, sensitivity, limit of detection, long-term stability, repeatability, and reproducibility. The biosensor exhibited electrocatalytic activity toward tyramine oxidation within a linear range from 6 to 130 μM, high sensitivity of 486 μA mM(−1) cm(−2), and limit of detection of 1.5 μM. The apparent Michaelis–Menten constant was calculated to be 66.0 μM indicating a high biological affinity of the developed biosensor for tyramine. Furthermore, its usefulness in determination of tyramine in food product samples was also verified. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-016-9612-y) contains supplementary material, which is available to authorized users

Further evidence on the (in-) efficiency of the U.S. housing market

Extending the controversial findings from relevant literature on testing the efficient market hypothesis for the U.S. housing market, the results from the monthly and quarterly transaction-based Case-Shiller indices from 1987 to 2009 provide further empirical evidence on the rejection of the weak-form version of efficiency in the U.S. housing market. In addition to conducting parametric and non-parametric tests, we apply technical trading strategies to test whether or not the inefficiencies can be exploited by investors earning excess returns. The empirical findings suggest that investors might be able to obtain excess returns from both autocorrelation- and moving average-based trading strategies compared to a buy-and-hold strategy