19,491 research outputs found

    Stochastic simulation and spatial statistics of large datasets using parallel computing

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    Lattice models are a way of representing spatial locations in a grid where each cell is in a certain state and evolves according to transition rules and rates dependent on a surrounding neighbourhood. These models are capable of describing many phenomena such as the simulation and growth of a forest fire front. These spatial simulation models as well as spatial descriptive statistics such as Ripley\u27s K-function have wide applicability in spatial statistics but in general do not scale well for large datasets. Parallel computing (high performance computing) is one solution that can provide limited scalability to these applications. This is done using the message passing interface (MPI) framework implemented in R through the Rmpi package. Other useful techniques in spatial statistics such as point pattern reconstruction and Markov Chain Monte Carlo (MCMC) methods are discussed from a parallel computing perspective as well. In particular, an improved point pattern reconstruction is given and implemented in parallel. Single chain MCMC methods are also examined and improved upon to give faster convergence using parallel computing. Optimizations, and complications that arise from parallelizing existing spatial statistics algorithms are discussed and methods are implemented in an accompanying R package, parspatstat

    A girl with short stature and dysmorphism

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    Hybrid Simulation Safety: Limbos and Zero Crossings

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    Physical systems can be naturally modeled by combining continuous and discrete models. Such hybrid models may simplify the modeling task of complex system, as well as increase simulation performance. Moreover, modern simulation engines can often efficiently generate simulation traces, but how do we know that the simulation results are correct? If we detect an error, is the error in the model or in the simulation itself? This paper discusses the problem of simulation safety, with the focus on hybrid modeling and simulation. In particular, two key aspects are studied: safe zero-crossing detection and deterministic hybrid event handling. The problems and solutions are discussed and partially implemented in Modelica and Ptolemy II

    KIAA1114, a full-length protein encoded by the trophinin gene, is a novel surface marker for isolating tumor-initiating cells of multiple hepatocellular carcinoma subtypes

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    Identification of novel biomarkers for tumor-initiating cells (TICs) is of critical importance for developing diagnostic and therapeutic strategies against cancers. Here we identified the role of KIAA1114, a full-length translational product of the trophinin gene, as a distinctive marker for TICs in human liver cancer by developing a DNA vaccine-induced monoclonal antibody targeting the putative extracellular domain of KIAA1114. Compared with other established markers of liver TICs, KIAA1114 was unique in that its expression was detected in both alpha fetoprotein (AFP)-positive and AFP-negative hepatocellular carcinoma (HCC) cell lines with the expression levels of KIAA1114 being positively correlated to their tumorigenic potentials. Notably, KIAA1114 expression was strongly detected in primary hepatic tumor, but neither in the adjacent non-tumorous tissue from the same patient nor normal liver tissue. KIAA1114(high) cells isolated from HCC cell lines displayed TIC-like features with superior functional and phenotypic traits compared to their KIAA1114(low) counterparts, including tumorigenic abilities in xenotransplantation model, in vitro colony- and spheroid-forming capabilities, expression of stemness-associated genes, and migratory capacity. Our findings not only address the value of a novel antigen, KIAA1114, as a potential diagnostic factor of human liver cancer, but also as an independent biomarker for identifying TIC populations that could be broadly applied to the heterogeneous HCC subtypes.X1110Nsciescopu

    Diagnosing deep vein thrombosis in the lower extremity: correlation of clinical and duplex scan findings.

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    OBJECTIVE: To identify factors that predict a positive duplex scan examination result in patients with suspected deep vein thrombosis of the lower extremity. DESIGN: Retrospective study. SETTING: Vascular laboratory in a university teaching hospital. PATIENTS AND METHODS: The results of 345 lower extremity duplex venous scans performed between August 1994 and November 1998 were reviewed. All patients were in-patients referred from different specialties due to clinical suspicion of lower extremity deep vein thrombosis. Positive duplex scans were correlated with patients' demographic data (sex, age), medical history (history of malignancy, deep vein thrombosis, and pulmonary embolism) and clinical features (leg swelling, venous insufficiency, calf pain, and leg ulcer). Univariate analysis was performed using the Chi squared test. RESULTS: A total of 345 scans were performed for 313 patients. The mean age was 55 years (range, 19-92 years). Sixty-three patients (49 male, 14 female) had a positive scan, giving a yield of 18.3%. Four factors had a significant association with a positive scan: male sex (P=0.0102), history of malignancy (P=0.0040), history of deep vein thrombosis (P=0.0001), and history of pulmonary embolism (P=0.0265). CONCLUSIONS: Common presenting clinical features do not predict the result of ultrasonographic investigation for deep vein thrombosis. The chance of having a positive scan is significantly higher in male patients and those with a history of malignancy, deep vein thrombosis, or pulmonary embolism.published_or_final_versio

    Neuroprotection in steroid therapy: a rodent model

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    Key Messages 1. Chronic steroid therapy causes disturbance in cell proliferation of the hippocampus and the subventricular zone. This may be the underlying cause of altered memory and cognitive function. 2. Co-administration of paroxetine (a class of antidepressants) during steroid therapy could counteract the destruction. Modification of the current steroid therapy regimen may be required.published_or_final_versio

    Two-dimensional imaging of edge-localized modes in KSTAR plasmas unperturbed and perturbed by n=1 external magnetic fields

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    The temporal evolution of edge-localized modes (ELMs) has been studied using a 2-D electron cyclotron emission imaging system in the KSTAR tokamak. The ELMs are observed to evolve in three distinctive stages: the initial linear growth of multiple filamentary structures having a net poloidal rotation, the interim state of regularly spaced saturated filaments, and the final crash through a short transient phase characterized by abrupt changes in the relative amplitudes and distance among filaments. The crash phase, typically consisted of multiple bursts of a single filament, involves a complex dynamics, poloidal elongation of the bursting filament, development of a fingerlike bulge, and fast localized burst through the finger. Substantial alterations of the ELM dynamics, such as mode number, poloidal rotation, and crash time scale, have been observed under external magnetic perturbations with the toroidal mode number n = 1. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3694842]X1125sciescopu

    Control of multivariable Hammerstein systems by using feedforward passivation

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    This paper presents a new control method for processes which can be described by Hammerstein models. The control design is based on the concept of passive systems. The proposed method is based on feedforward passivation and thus can be applied to nonminimum phase processes and/or processes of high relative degree. A synthesis technique for marginally stable positive real systems has been developed to achieve offset free control. The new control design can be easily implemented by solving a set of linear matrix inequalities. The proposed approach is illustrated using the example of an acid-base pH control problem

    Evolution of Parathyroid Hormone Receptor Family and Their Ligands in Vertebrate

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