Let\u27s Knock The Bull Out Of The Bolsheviki

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A Reconstruction Approach for Imaging in 3D Cone Beam Vector Field Tomography

3D cone beam vector field tomography (VFT) aims for reconstructing and visualizing the velocity field of a moving fluid by measuring line integrals of projections of the vector field. The data are obtained by ultrasound measurements along a scanning curve which surrounds the object. From a mathematical point of view, we have to deal with the inversion of the vectorial cone beam transform. Since the vectorial cone beam transform of any gradient vector field with compact support is identically equal to zero, we can only hope to reconstruct the solenoidal part of an arbitrary vector field. In this paper we will at first summarize important properties of the cone beam transform for three-dimensional solenoidal vector fields and then propose a solution approach based on the method of approximate inverse. In this context, we intensively make use of results from scalar 3D computerized tomography. The findings presented in the paper will continuously be illustrated by pictures from first numerical experiments done with exact, simulated data

Modelling the electrophysiological endothelial cell response to bradykinin

The goal of the present study is to construct a biophysical model of the coronary artery endothelial cell response to bradykinin. This model takes into account intracellular Ca2+ dynamics, membrane potential, a non-selective cation channel, and two Ca2+-dependent K+ channels, as well as intra- and extracellular Ca2+ sources. The model reproduces the experimental data available, and predicts certain quantities which would be hard to obtain experimentally, like the individual K+ channel currents when the membrane potential is allowed to freely evolve, the implication of epoxyeicosatrienoic acids (EETs), and the total K+ released during stimulation. The main results are: (1) the large-conductance K+ channel participates only very little in the overall response; (2) EETs are required in order to explain the experimental current-potential relationships, but are not an essential component of the bradykinin response; and (3) the total K+ released during stimulation gives rise to a concentration in the intercellular space which is of millimolar order. This concentration change is compatible with the hypothesis that K+ contributes to the endothelium-derived hyperpolarizing factor phenomeno

Integrating Time-Series Data in Large-Scale Discrete Cell-Based Models

International audienceIn this work we propose an automatic way of generating and verifying formal hybrid models of signaling and transcriptional events, gathered in large-scale regulatory networks.This is done by integrating temporal and stochastic aspects of the expression of some biological components. The hybrid approach lies in the fact that measurements take into account both times of lengthening phases and discrete switches between them. The model proposed is based on a real case study of keratinocytes differentiation, in which gene time-series data was generated upon Calcium stimulation. To achieve this we rely on the Process Hitting (PH) formalism that was designed to consider large-scale system analysis. We first propose an automatic way of detecting and translating biological motifs from the Pathway Interaction Database to the PH formalism. Then, we propose a way of estimating temporal and stochas-tic parameters from time-series expression data of action on the PH. Simulations emphasize the interest of synchronizing concurrent events

Full length interleukin 33 aggravates radiation-induced skin reaction

The interleukin (IL)-1 family member IL-33 has been described as intracellular alarmin with broad roles in wound healing, skin inflammation but also autoimmunity. Its dichotomy between full length (fl) IL-33 and the mature (m) form of IL-33 and its release by necrosis is still not fully understood. Here, we compare functional consequences of both forms in the skin in vivo, and therefore generated two lines of transgenic mice which selectively overexpress mmIL-33 and flmIL-33 in basal keratinocytes. Transgene mRNA was expressed at high level in skin of both lines but not in organs due to the specific K14 promoter. We could demonstrate that transgenic overexpression of mmIL-33 in murine keratinocytes leads to a spontaneous skin inflammation as opposed to flmIL-33. K14-mmIL-33 mice synthesize and secrete high amounts of mmIL-33 along with massive cutaneous manifestations, like increased epidermis and dermis thickness, infiltration of mast cells in the epidermis and dermis layers and marked hyperkeratosis. Using skin inflammation models such as IL-23 administration, imiquimod treatment, or mechanical irritation did not lead to exacerbated inflammation in the K14-flmIL-33 strain. As radiation induces a strong dermatitis due to apoptosis and necrosis, we determined the effect of fractionated radiation (12 Gy, 4 times). In comparison to wild-type mice, an increase in ear thickness in flmIL-33 transgenic mice was observed 25 days after irradiation. Macroscopic examination showed more severe skin symptoms in irradiated ears compared to controls. In summary, secreted mmIL-33 itself has a potent capacity in skin inflammation whereas fl IL-33 is limited due to its intracellular retention. During tissue damage, fl IL-33 exacerbated radiation-induced skin reaction

Modelling the electrophysiological endothelial cell response to bradykinin

The goal of the present study is to construct a biophysical model of the coronary artery endothelial cell response to bradykinin. This model takes into account intracellular Ca2+ dynamics, membrane potential, a non-selective cation channel, and two Ca(2+)-dependent K+ channels, as well as intra- and extracellular Ca2+ sources. The model reproduces the experimental data available, and predicts certain quantities which would be hard to obtain experimentally, like the individual K+ channel currents when the membrane potential is allowed to freely evolve, the implication of epoxyeicosatrienoic acids (EETs), and the total K+ released during stimulation. The main results are: (1) the large-conductance K+ channel participates only very little in the overall response; (2) EETs are required in order to explain the experimental current-potential relationships, but are not an essential component of the bradykinin response; and (3) the total K+ released during stimulation gives rise to a concentration in the intercellular space which is of millimolar order. This concentration change is compatible with the hypothesis that K+ contributes to the endothelium-derived hyperpolarizing factor phenomenon

Siamese hierarchical attention networks for extractive summarization

[EN] In this paper, we present an extractive approach to document summarization based on Siamese Neural Networks. Specifically, we propose the use of Hierarchical Attention Networks to select the most relevant sentences of a text to make its summary. We train Siamese Neural Networks using document-summary pairs to determine whether the summary is appropriated for the document or not. By means of a sentence-level attention mechanism the most relevant sentences in the document can be identified. Hence, once the network is trained, it can be used to generate extractive summaries. The experimentation carried out using the CNN/DailyMail summarization corpus shows the adequacy of the proposal. In summary, we propose a novel end-to-end neural network to address extractive summarization as a binary classification problem which obtains promising results in-line with the state-of-the-art on the CNN/DailyMail corpus.This work has been partially supported by the Spanish MINECO and FEDER founds under project AMIC (TIN2017-85854-C4-2-R). Work of Jose-Angel Gonzalez is also financed by Universitat Politecnica de Valencia under grant PAID-01-17.González-Barba, JÁ.; Segarra Soriano, E.; García-Granada, F.; Sanchís Arnal, E.; Hurtado Oliver, LF. (2019). Siamese hierarchical attention networks for extractive summarization. Journal of Intelligent & Fuzzy Systems. 36(5):4599-4607. https://doi.org/10.3233/JIFS-179011S45994607365N. Begum , M. Fattah , and F. Ren . Automatic text summarization using support vector machine 5(7) (2009), 1987–1996.J. Cheng and M. Lapata . Neural summarization by extracting sentences and words. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, August 7-12, 2016, Berlin, Germany, Volume 1: Long Papers, 2016.K.M. Hermann , T. Kocisky , E. Grefenstette , L. Espeholt , W. Kay , M. Suleyman , and P. Blunsom . Teaching machines to read and comprehend, CoRR, abs/1506.03340, 2015.D.P. Kingma and J. Ba . Adam: A method for stochastic optimization. CoRR, abs/1412.6980, 2014.Lloret, E., & Palomar, M. (2011). Text summarisation in progress: a literature review. Artificial Intelligence Review, 37(1), 1-41. doi:10.1007/s10462-011-9216-zLouis, A., & Nenkova, A. (2013). Automatically Assessing Machine Summary Content Without a Gold Standard. Computational Linguistics, 39(2), 267-300. doi:10.1162/coli_a_00123Miao, Y., & Blunsom, P. (2016). Language as a Latent Variable: Discrete Generative Models for Sentence Compression. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/d16-1031R. Mihalcea and P. Tarau . Textrank: Bringing order into text. In Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, 2004.T. Mikolov , K. Chen , G. S. Corrado , and J. Dean . Efficient estimation of word representations in vector space, CoRR, abs/1301.3781, 2013.Minaee, S., & Liu, Z. (2017). Automatic question-answering using a deep similarity neural network. 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP). doi:10.1109/globalsip.2017.8309095R. Paulus , C. Xiong , and R. Socher , A deep reinforced model for abstractive summarization. CoRR, abs/1705.04304, 2017.Schuster, M., & Paliwal, K. K. (1997). Bidirectional recurrent neural networks. IEEE Transactions on Signal Processing, 45(11), 2673-2681. doi:10.1109/78.650093See, A., Liu, P. J., & Manning, C. D. (2017). Get To The Point: Summarization with Pointer-Generator Networks. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). doi:10.18653/v1/p17-1099Takase, S., Suzuki, J., Okazaki, N., Hirao, T., & Nagata, M. (2016). Neural Headline Generation on Abstract Meaning Representation. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/d16-1112G. Tur and R. De Mori . Spoken language understanding: Systems for extracting semantic information from speech, John Wiley & Sons, 2011

Inheritance of resistance to cotton blue disease

O objetivo deste trabalho foi determinar a herança da resistência do algodoeiro à doença-azul. Populações derivadas das variedades resistentes CD 401 e Delta Opal foram avaliadas em casa de vegetação, por meio da inoculação de pulgões virulíferos. A resistência à doença-azul do algodoeiro é condicionada por um gene dominante, tanto em 'DC 401' quanto em 'Delta Opal'.The objective of this work was to determine the inheritance of cotton blue disease resistance by cotton plants. Populations derived from the CD 401 and Delta Opal resistant varieties were evaluated, through a greenhouse test with artificial inoculation by viruliferous aphids. Cotton blue disease resistance is conditioned by one dominant gene, both in CD 401 and Delta Opal varieties