7,233 research outputs found

    An ectopic hamartomatous thymoma compressing left jugular vein

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    Ectopic hamartomatous thymoma (EHT) is an extremely rare benign neoplasm. It is usually found at the root of theĀ neck (frequently on the left) and does not usually impact adjacent tissues in clinically significant ways. While EHTĀ manifests distinct pathological features, the lesion is either asymptomatic or may show nonspecific clinical features.Ā We report one case of EHT which was assumed to be of low malignant potential since it severely compressed the inletĀ of left internal jugular vein as seen by computed tomography scan. To the best of our knowledge, this clinical findingĀ of EHT is very rare. After the diagnosis and treatment of this patient, we believe that EHT or suspected EHT shouldĀ be treated less invasively.Key words: Ectopia, harmatoma, miniā€‘sternotomy, thymom

    Determination of Intrinsic Ferroelectric Polarization in Orthorhombic Manganites with E-type Spin Order

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    By directly measuring electrical hysteresis loops using the Positive-Up Negative-Down (PUND) method, we accurately determined the remanent ferroelectric polarization Pr of orthorhombic RMnO3 (R = Ho, Tm, Yb, and Lu) compounds below their E-type spin ordering temperatures. We found that LuMnO3 has the largest Pr of 0.17 uC/cm^2 at 6 K in the series, indicating that its single-crystal form can produce a Pr of at least 0.6 \muuC/cm^2 at 0 K. Furthermore, at a fixed temperature, Pr decreases systematically with increasing rare earth ion radius from R = Lu to Ho, exhibiting a strong correlation with the variations in the in-plane Mn-O-Mn bond angle and Mn-O distances. Our experimental results suggest that the contribution of the Mn t2g orbitals dominates the ferroelectric polarization.Comment: 16 pages, 4 figure

    Genetic polymorphisms and periodontitis in Hong Kong Chinese

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    Effects of VEGF on bone cells' metabolism and activity

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    Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

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    Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

    Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

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    Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

    Energy efficient cooperative coalition selection in cluster-based capillary networks for CMIMO IoT systems

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    The Cooperative Multiple-input-multiple-output (CMIMO) scheme has been suggested to extend the lifetime of cluster heads (CHs) in cluster-based capillary networks in Internet of Things (IoT) systems. However, the CMIMO scheme introduces extra energy overhead to cooperative devices and further reduces the lifetime of these devices. In this paper, we first articulate the problem of cooperative coalitionā€™s selection for CMIMO scheme to extend the average battery capacity among the whole network, and then propose to apply the quantum-inspired particle swarm optimization (QPSO) to select the optimum cooperative coalitions of each hop in the routing path. Simulation results proved that the proposed QPSO-based cooperative coalitionā€™s selection scheme could select the optimum cooperative sender and receiver devices in every hop dynamically and outperform the virtual MIMO scheme with a fixed number of cooperative devices

    A Census of Eddy Activities in the South China Sea During 1993-2007

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    Numerous mesoscale eddies occur each year in the South China Sea (SCS), but their statistical characteristics are still not well documented. A Pacific basin-wide three dimensional physical-biogeochemical model has been developed and the result in the SCS subdomain is used to quantify the eddy activities during the period of 1993-2007. The modeled results are compared with a merged and gridded satellite product of sea level anomaly by using the same eddy identification and tracking method. On average, there are about 32.9 +/- 2.4 eddies predicted by the model and 32.8 +/- 3.4 eddies observed by satellite each year, and about 52% of them are cyclonic eddies. The radius of these eddies ranges from about 46.5 to 223.5 km, with a mean value of 87.4 km. More than 70% of the eddies have a radius smaller than 100 km. The mean area covered by these eddies each year is around 160,170 km(2), equivalent to 9.8% of the SCS area with water depths greater than 1000 m. Linear relationships are found between eddy lifetime and eddy magnitude and between eddy vertical extent and eddy magnitude, showing that strong eddies usually last longer and penetrate deeper than weak ones. Interannual variations in eddy numbers and the total eddy-occupied area indicate that eddy activities in the SCS do not directly correspond to the El Nino-Southern Oscillation events. The wind stress curls are thought to be an important but not the only mechanism of eddy genesis in the SCS

    The activation energy for GaAs/AlGaAs interdiffusion

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    Copyright 1997 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. This article appeared in Journal of Applied Physics 82, 4842 (1997) and may be found at

    Students\u27 Views on General Education: Insights Gained from the Narratives of Chinese Students in Hong Kong

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    The General University Requirements (GUR) is a component of the new 4-year undergraduate program at The Hong Kong Polytechnic University (PolyU). This study examined studentsā€™ views and experiences of the GUR using a qualitative methodology. Written comments of 240 freshmen, sophomores, and senior-year students with reference to open-ended questions on their memorable experiences in the GUR study were collected. The qualitative findings suggested that students generally had positive views on the GUR in terms of its widely adopted active and experiential learning pedagogy, useful and attractive contents, caring teaching staff, and rich learning outcomes. Challenges were also identified for further improvement of the GUR
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