627 research outputs found

    Master of Science

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    thesisThe induced polarization (IP) effect, in general, is related to the complex resistivity of rocks. Modeling IP phenomena is important for developing effective methods for remote sensing of subsurface geology. The Generalized Effective Medium Theory of Induced Polarization (GEMTIP) has been derived based on the effective medium approach to the characterization of heterogeneous, multiphase, polarized medium typical in rock formations. It describes the relationships between petrophysical and structural properties of rock and the parameters of the corresponding resistivity relaxation model (Zhdanov, 2008). The parameters of the GEMTIP model are determined by the intrinsic petrophysical and geometrical characteristics of the medium: the mineralization, the matrix composition, porosity, anisotropy, and polarizability of the formations. In this paper, two igneous rock samples and three shale samples were tested by the randomly oriented ellipsoidal GEMTIP model, both two-phases and three-phases models were used in the study. Inversion routines were developed and tested using synthetic data to recover the three variables: volume fraction (f), relaxation parameters (C), and time constant (τ). Both Regularized Conjugate Gradient (RCG) method and extensive search method were implemented in the study. Complex resistivity were calculated from recorded EM data from 0.005 Hz to 10000 Hz at 33 different frequencies, detailed geologic analysis using Quantitative Evaluation of Materials using Scanning Electron Microscope (QEMSCAN) and X-ray is conducted to determine GEMTIP model parameters and help better understand the inversion results. The application of shale samples shows that the shale samples are characterized by a significant IP response, and the GEMTIP model can be applied to hydrocarbon bearing shale rocks. The results of our study show that the ellipsoidal GEMTIP model can successfully interpret the IP effect of the mineral rocks and shale samples. By comparing the two-phases with three-phases inversion results, the mineral rock samples study shows that the three-phases model can separate the different mineral sizes and different mineral types from the same sample, the shale samples show the three- phases GEMTIP model can separate the membrane polarization caused by the internal structure of the shale samples from electrode polarization caused by disseminated pyrite. The GEMTIP parameter time constant increases with increases of the grain size. Successful GEMTIP model of the rock samples provided insight into controlling factors of the IP effect

    Mechanisms controlling the infection of Culicoides biting midges with bluetongue virus

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    The mechanisms controlling the transmission of bluetongue virus (DTV) by vector Clilicoides species were studied using immunohistochemistry, virus titration assays, in vitro transmission tests, viral binding protein analyses and transmission electron microscopy. After infection with BTV by intrathoracic (IT) inoculation, 100% of C. variipennis individuals from a susceptible colony developed a fully disseminated infection and transmitted the virus through their saliva. However only 35.4% of midges were . persistently infected after ingestion of an infectious blood meal, while only 12.1 % of persistently infected midges transmitted the virus through their saliva. The titres of BTV were about 10,·oTCIDsJmidge [Standard error of means (SEM) of log-transformed data=0.15, n=1400] in IT inoculated midges and varied from 0.32 to lQs.oTCIDsJmidge in orally infected individuals. Only those midges containing ~1 03.oTCIDso of BTV could transmit the virus through their saliva. The following patterns were observed in orally (persistently) infected individuals: 1) virus was restricted to the anterior and posterior midgut, and the foregut-midgut junction; 2) virus replicated in the gut cells, disseminated into the haemocoel but could only be detected in a few sporadic fat body cells beyond the gut; 3) virus escaped from the gut cells into the haemocoel and replicated in some secondary organs/tissues but at low levels; 4) a fully disseminated infection was observed and virus replicated in the haemocoel and secondary organs/tissues, including the salivary glands, at high levels. The infection of the gut can be divided into two main types: 1) virus replication in gut cells ranging from very low to higher levels but with virus spread throughout the cytoplasm of the infected cells; 2) virus positive reaction restricted to endosome-like structures in the cytoplasm of some gut cells. BTV was detected in the anterior and posterior midgut, foregut-midgut junction, fat body, ganglia, salivary glands and ommatidia of the compound eyes of some infected midges. No virus was ever found in the hindgut cells, muscles, Malpighian tubes and oocytes/nurse cells of the ovaries. BTV infection of the salivary glands of C. l'ariipcnnis was shown to follow a typical pattern. Virus entered the acinar cells from the haemococl passing through the basement membrane, then localised and replicated in virus inclusion bodies (VIBs) in the cytoplasm of acinar cells. Mature progeny virus particles were released into acini, then transported through intermediate ducts and accumulated in crystalline arrays in the lumen of the major secretory ducts. No virus was released back into the haemocoel through the basement membrane; nor was virus released back into acinar cells from the acini. Nervous tissue of C. l'ariipennis is one of the most susceptible tissues to BTV. Ultrastructural observation showed characteristics ofBTV replication, including formation of VIBs, large amounts of progeny virus particles and tubules, in infected thoracic ganglia. A 60-kD viral protein adhered to both BHK-21 (mammalian) cells and a Culicoides cell line, KC cells. A 44-kD BTV viral protein, co-migrating with non structural protein NS2, adsorbed to BHK-21 cells but not to KC cells, while a 39.6 kD viral protein, co-migrating with major inner capsid protein VP7, adhered only to KC cells but not to BHK-21 cells

    Nonlinear Instability for a Volume-Filling Chemotaxis Model with Logistic Growth

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    This paper deals with a Neumann boundary value problem for a volume-filling chemotaxis model with logistic growth in a d-dimensional box Td=(0,π)d  (d=1,2,3). It is proved that given any general perturbation of magnitude δ, its nonlinear evolution is dominated by the corresponding linear dynamics along a finite number of fixed fastest growing modes, over a time period of the order ln⁡(1/δ). Each initial perturbation certainly can behave drastically different from another, which gives rise to the richness of patterns

    Sequential Wnt Agonist then Antagonist Treatment Accelerates Tissue Repair and Minimizes Fibrosis

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    Tissue fibrosis compromises organ function and occurs as a potential long-term outcome in response to acute tissue injuries. Currently, lack of mechanistic understanding prevents effective prevention and treatment of the progression from acute injury to fibrosis. Here, we combined quantitative experimental studies with a mouse kidney injury model and a computational approach to determine how the physiological consequences are determined by the severity of ischemia injury, and to identify how to manipulate Wnt signaling to accelerate repair of ischemic tissue damage while minimizing fibrosis. The study reveals that Wnt-mediated memory of prior injury contributes to fibrosis progression, and ischemic preconditioning reduces the risk of death but increases the risk of fibrosis. Furthermore, we validated the prediction that sequential combination therapy of initial treatment with a Wnt agonist followed by treatment with a Wnt antagonist can reduce both the risk of death and fibrosis in response to acute injuries

    Predicting Berth Stay for Tanker Terminals: A Systematic and Dynamic Approach

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    Given the trend of digitization and increasing number of maritime transport, prediction of vessel berth stay has been triggered for requirements of operation research and scheduling optimization problem in the era of maritime big data, which takes a significant part in port efficiency and maritime logistics enhancement. This study proposes a systematic and dynamic approach of predicting berth stay for tanker terminals. The approach covers three innovative aspects: 1) Data source employed is multi-faceted, including cargo operation data from tanker terminals, time-series data from automatic identification system (AIS), etc. 2) The process of berth stay is decomposed into multiple blocks according to data analysis and information extraction innovatively, and practical operation scenarios are also developed accordingly. 3) The predictive models of berth stay are developed on the basis of prior data analysis and information extraction under two methods, including regression and decomposed distribution. The models are evaluated under four dynamic scenarios with certain designated cargoes among two different terminals. The evaluation results show that the proposed approach can predict berth stay with the accuracy up to 98.81% validated by historical baselines, and also demonstrate the proposed approach has dynamic capability of predicting berth stay among the scenarios. The model may be potentially applied for short-term pilot-booking or scheduling optimizations within a reasonable time frame for advancement of port intelligence and logistics efficiency
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