450 research outputs found

    Fast and spectrally accurate summation of 2-periodic Stokes potentials

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    We derive a Ewald decomposition for the Stokeslet in planar periodicity and a novel PME-type O(N log N) method for the fast evaluation of the resulting sums. The decomposition is the natural 2P counterpart to the classical 3P decomposition by Hasimoto, and is given in an explicit form not found in the literature. Truncation error estimates are provided to aid in selecting parameters. The fast, PME-type, method appears to be the first fast method for computing Stokeslet Ewald sums in planar periodicity, and has three attractive properties: it is spectrally accurate; it uses the minimal amount of memory that a gridded Ewald method can use; and provides clarity regarding numerical errors and how to choose parameters. Analytical and numerical results are give to support this. We explore the practicalities of the proposed method, and survey the computational issues involved in applying it to 2-periodic boundary integral Stokes problems

    High-efficiency protein expression in plants from agroinfection-compatible Tobacco mosaic virus expression vectors

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    <p>Abstract</p> <p>Background</p> <p>Plants are increasingly being examined as alternative recombinant protein expression systems. Recombinant protein expression levels in plants from <it>Tobacco mosaic virus </it>(TMV)-based vectors are much higher than those possible from plant promoters. However the common TMV expression vectors are costly, and at times technically challenging, to work with. Therefore it was a goal to develop TMV expression vectors that express high levels of recombinant protein and are easier, more reliable, and more cost-effective to use.</p> <p>Results</p> <p>We have constructed a <it>Cauliflower mosaic virus </it>(CaMV) 35S promoter-driven TMV expression vector that can be delivered as a T-DNA to plant cells by <it>Agrobacterium tumefaciens</it>. Co-introduction (by agroinfiltration) of this T-DNA along with a 35S promoter driven gene for the RNA silencing suppressor P19, from <it>Tomato bushy stunt virus </it>(TBSV) resulted in essentially complete infection of the infiltrated plant tissue with the TMV vector by 4 days post infiltration (DPI). The TMV vector produced between 600 and 1200 micrograms of recombinant protein per gram of infiltrated tissue by 6 DPI. Similar levels of recombinant protein were detected in systemically infected plant tissue 10–14 DPI. These expression levels were 10 to 25 times higher than the most efficient 35S promoter driven transient expression systems described to date.</p> <p>Conclusion</p> <p>These modifications to the TMV-based expression vector system have made TMV vectors an easier, more reliable and more cost-effective way to produce recombinant proteins in plants. These improvements should facilitate the production of recombinant proteins in plants for both research and product development purposes. The vector should be especially useful in high-throughput experiments.</p

    DeepPy: Pythonic deep learning

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    CUDArray: CUDA-based NumPy

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    Learned image representations for visual recognition

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    Studying effects of light pollution and aquacultural light regimes using the teleost model medaka (Oryzias latipes)

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    Light is the main cue in synchronizing daily circadian rhythm in most animals, in addition to synchronizing the perception of the year for some species. Due to the steady increase of light pollution around the world, and especially near water bodies, this study aims to investigate the effects of different light regimes. Those regimes include light pollution and the continuous light regime used in aquaculture, mainly to increase growth and delay sexual maturation, is also studied. Firstly, light pollution levels were measured in Oslo’s main river, and the harbor area. I found that urban light pollution is severe in some places and can reach relatively deep as I detected it at 5 meters depth in the fjord. These results suggest that aquatic animals may be exposed to light pollution in the Oslo area and thus the effects should be studied. I then investigated in a laboratory setup the effect of light pollution on the teleost model Japanese medaka (Oryzias latipes). In addition to the continuous light regime was also studied. I found several effects of the altered light regimes. The reproductive cycle was found to be desynchronized for both light regimes. The fish’s behavior was also found to be altered. Additionally, fish development was found to be affected with promoted growth and altered brain and heart morphology. The artificial light regimes were also found to affect neurochemistry and the gene expression of one pituitary gene. A clear noradrenergic response was found, with the control fish having higher noradrenergic activity. Fish exposed to light pollution had a higher serotonergic brain activity. The pituitary gonadotropin lhb was found to be decreased in the continuous light regime. All together these results demonstrate that light pollution and continuous light clearly affect the fish, having welfare implications for aquaculture production, and suggesting that light pollution indeed affects wild fish

    Autoencoding beyond pixels using a learned similarity metric

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    We present an autoencoder that leverages learned representations to better measure similarities in data space. By combining a variational autoencoder with a generative adversarial network we can use learned feature representations in the GAN discriminator as basis for the VAE reconstruction objective. Thereby, we replace element-wise errors with feature-wise errors to better capture the data distribution while offering invariance towards e.g. translation. We apply our method to images of faces and show that it outperforms VAEs with element-wise similarity measures in terms of visual fidelity. Moreover, we show that the method learns an embedding in which high-level abstract visual features (e.g. wearing glasses) can be modified using simple arithmetic
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