364 research outputs found

    Approximate Closed-Form Solution to a Linear Quadratic Optimal Control Problem with Disturbance

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143067/1/1.G001666.pd

    Multiple exciton generation in nano-crystals revisited: Consistent calculation of the yield based on pump-probe spectroscopy

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    Multiple exciton generation (MEG) is a process in which more than one exciton is generated upon the absorption of a high energy photon, typically higher than two times the band gap, in semiconductor nanocrystals. It can be observed experimentally using time resolved spectroscopy such as the transient absorption measurements. Quantification of the MEG yield is usu- ally done by assuming that the bi-exciton signal is twice the signal from a single exciton. Herein we show that this assumption is not always justified and may lead to significant errors in the estimated MEG yields. We develop a methodology to determine proper scaling factors to the signals from the transient absorption experiments. Using the methodology we find modest MEG yields in lead chalcogenide nanocrystals including the nanorods

    Effect of amlodipine on cardiovascular events in hypertensive haemodialysis patients

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    Background. Hypertensive haemodialysis patients may be at a high risk for cardiovascular events. This study was undertaken to ascertain whether the calcium channel blocker amlodipine reduces mortality and cardiovascular events in these high-risk patients

    The enzymatic activity of the VEGFR2-receptor for the biosynthesis of dinucleoside polyphosphates

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    The group of dinucleoside polyphosphates encompasses a large number of molecules consisting of two nucleosides which are connected by a phosphate chain of variable length. While the receptors activated by dinucleoside polyphosphates as well as their degradation have been studied in detail, its biosynthesis has not been elucidated so far. Since endothelial cells released the dinucleoside polyphosphate uridine adenosine tetraphosphate (Up4A), we tested cytosolic proteins of human endothelial cells obtained from dermal vessels elicited for enzymatic activity. When incubated with ADP and UDP, these cells showed increasing concentrations of Up4A. The underlying enzyme was isolated by chromatography and the mass spectrometric analysis revealed that the enzymatic activity was caused by the vascular endothelial growth factor receptor 2 (VEGFR2). Since VEGFR2 but neither VEGFR1 nor VEGFR3 were capable to synthesise dinucleoside polyphosphates, Tyr-1175 of VEGFR2 is most likely essential for the enzymatic activity of interest. Further, VEGFR2-containing cells like HepG2, THP-1 and RAW264.7 were capable of synthesising dinucleoside polyphosphates. VEGFR2-transfected HEK 293T/17 but not native HEK 293T/17 cells synthesised dinucleoside polyphosphates in vivo too. The simultaneous biosynthesis of dinucleoside polyphosphates could amplify the response to VEGF, since dinucleoside polyphosphates induce cellular growth via P2Y purinergic receptors. Thus the biosynthesis of dinucleoside polyphosphates by VEGFR2 may enhance the proliferative response to VEGF. Given that VEGFR2 is primarily expressed in endothelial cells, the biosynthesis of dinucleoside polyphosphates is mainly located in the vascular system. Since the vasculature is also the main site of action of dinucleoside polyphosphates, activating vascular purinoceptors, blood vessels appear as an autocrine system with respect to dinucleoside polyphosphates. We conclude that VEGFR2 receptor is capable of synthesising dinucleoside polyphosphates. These mediators may modulate the effects of VEGFR2 due to their proliferative effects

    Data Integration Model for Air Quality: A Hierarchical Approach to the Global Estimation of Exposures to Ambient Air Pollution

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    This is the author accepted manuscript. Available from arXiv via the URL in this record.Air pollution is a major risk factor for global health, with both ambient and household air pollution contributing substantial components of the overall global disease burden. One of the key drivers of adverse health effects is fine particulate matter ambient pollution (PM2:5) to which an estimated 3 million deaths can be attributed annually. The primary source of information for estimating exposures has been measurements from ground monitoring networks but, although coverage is increasing, there remain regions in which monitoring is limited. Ground monitoring data therefore needs to be supplemented with information from other sources, such as satellite retrievals of aerosol optical depth and chemical transport models. A hierarchical modelling approach for integrating data from multiple sources is proposed allowing spatially-varying relationships between ground measurements and other factors that estimate air quality. Set within a Bayesian framework, the resulting Data Integration Model for Air Quality (DIMAQ) is used to estimate exposures, together with associated measures of uncertainty, on a high resolution grid covering the entire world. Bayesian analysis on this scale can be computationally challenging and here approximate Bayesian inference is performed using Integrated Nested Laplace Approximations. Model selection and assessment is performed by cross-validation with the final model offering substantial increases in predictive accuracy, particularly in regions where there is sparse ground monitoring, when compared to previous approaches: root mean square error (RMSE) reduced from 17.1 to 10.7, and population weighted RMSE from 23.1 to 12.1 gm3. Based on summaries of the posterior distributions for each grid cell, it is estimated that 92% of the world’s population reside in areas exceeding the World Health Organization’s Air Quality Guidelines.Matthew Lloyd Thomas is supported by a scholarship from the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath (SAMBa), under the project EP/L015684/1. Amelia Jobling was supported for this work by WHO contracts APW 201255146 and 201255393

    Improved protein structure prediction using potentials from deep learning

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    Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence1. This problem is of fundamental importance as the structure of a protein largely determines its function2; however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures3. Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force4 that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction5 (CASP13)—a blind assessment of the state of the field—AlphaFold created high-accuracy structures (with template modelling (TM) scores6 of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined7

    Emergency open cholecystectomy is associated with markedly lower incidence of postoperative nausea and vomiting (PONV) than elective open cholecystectomy: a retrospective cohort study

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    <p>Abstract</p> <p>Background</p> <p>During a previous study to define and compare incidence risks of postoperative nausea and vomiting (PONV) for elective laparoscopic and open cholecystectomy at two hospitals in Jamaica, secondary analysis comparing PONV risk in elective open cholecystectomy to that after emergency open cholecystectomy suggested that it was markedly reduced in the latter group. The decision was made to collect data on an adequate sample of emergency open cholecystectomy cases and further explore this unexpected finding in a separate study.</p> <p>Methods</p> <p>Data were collected for 91 emergency open cholecystomy cases identified at the two paricipating hospitals from May 2007 retrograde, as was done for the 175 elective open cholecystectomy cases (from the aforementioned study) with which the emergency cases were to be compared. Variables selected for extraction and statistical analysis included all those known, suspected and plausibly associated with the risk of PONV and with urgency of surgery.</p> <p>Results</p> <p>Emergency open cholecystectomy was associated with a markedly reduced incidence risk of PONV compared to elective open cholecystectomy (6.6% versus 28.6%, P < 0.001). The suppressive effect of emergency increased after adjustment for confounders in a multivariable logistic regression model (odds ratio 0.103, P < 0.001). This finding also identifies, by extrapolation, an association between reduced risk of PONV and preoperative nausea and vomiting, which occurred in 80.2% of emergency cases in the 72 hour period preceding surgery.</p> <p>Conclusions</p> <p>The incidence risk of postoperative nausea and vomiting is markedly decreased after emergency open cholecystectomy compared to elective open cholecystectomy. The study, by extrapolation, also identifies a paradoxical association between pre-operative nausea and vomiting, observed in 80.2% of emergency cases, and suppression of PONV. This association, if confirmed in prospective cohort studies, may have implications for PONV prophylaxis if it can be exploited at a sub-clinical level.</p

    Refractory Materials for Flame Deflector Protection System Corrosion Control: Similar Industries and/or Launch Facilities Survey

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    A trade study and litera ture survey of refractory materials (fi rebrick. refractory concrete. and si licone and epoxy ablatives) were conducted to identify candidate replacement materials for Launch Complexes 39A and 398 at Kennedy Space Center (KSC). In addition, site vis its and in terviews with industry expens and vendors of refractory materials were conducted. As a result of the si te visits and interviews, several products were identified for launch applications. Firebrick is costly to procure and install and was not used in the si tes studied. Refractory concrete is gunnable. adheres well. and costs less 10 install. Martyte. a ceramic fi lled epoxy. can protect structural stccl but is costly. difficullto apply. and incompatible with silicone ablatives. Havanex, a phenolic ablative material, is easy to apply but is costly and requires frequent replacement. Silicone ablatives are ineJ[pensive, easy to apply. and perl'onn well outside of direct rocket impingement areas. but refractory concrete and epoxy ablatives provide better protection against direcl rocket exhaust. None of the prodUCIS in this trade study can be considered a panacea for these KSC launch complexes. but the refractory products. individually or in combination, may be considered for use provided the appropriate testing requirements and specifications are met
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