State Differentiation by Transient Truncation in Coupled Threshold Dynamics

Dynamics with a threshold input--output relation commonly exist in gene, signal-transduction, and neural networks. Coupled dynamical systems of such threshold elements are investigated, in an effort to find differentiation of elements induced by the interaction. Through global diffusive coupling, novel states are found to be generated that are not the original attractor of single-element threshold dynamics, but are sustained through the interaction with the elements located at the original attractor. This stabilization of the novel state(s) is not related to symmetry breaking, but is explained as the truncation of transient trajectories to the original attractor due to the coupling. Single-element dynamics with winding transient trajectories located at a low-dimensional manifold and having turning points are shown to be essential to the generation of such novel state(s) in a coupled system. Universality of this mechanism for the novel state generation and its relevance to biological cell differentiation are briefly discussed.Comment: 8 pages. Phys. Rev. E. in pres

Online learning via dynamic reranking for Computer Assisted Translation

New techniques for online adaptation in computer assisted translation are explored and compared to previously existing approaches. Under the online adaptation paradigm, the translation system needs to adapt itself to real-world changing scenarios, where training and tuning may only take place once, when the system is set-up for the first time. For this purpose, post-edit information, as described by a given quality measure, is used as valuable feedback within a dynamic reranking algorithm. Two possible approaches are presented and evaluated. The first one relies on the well-known perceptron algorithm, whereas the second one is a novel approach using the Ridge regression in order to compute the optimum scaling factors within a state-of-the-art SMT system. Experimental results show that such algorithms are able to improve translation quality by learning from the errors produced by the system on a sentence-by-sentence basis.This paper is based upon work supported by the EC (FEDER/FSE) and the Spanish MICINN under projects MIPRCV “Consolider Ingenio 2010” (CSD2007-00018) and iTrans2 (TIN2009-14511). Also supported by the Spanish MITyC under the erudito.com (TSI-020110-2009-439) project, by the Generalitat Valenciana under grant Prometeo/2009/014 and scholarship GV/2010/067 and by the UPV under grant 20091027Martínez Gómez, P.; Sanchis Trilles, G.; Casacuberta Nolla, F. (2011). Online learning via dynamic reranking for Computer Assisted Translation. En Computational Linguistics and Intelligent Text Processing. Springer Verlag (Germany). 6609:93-105. https://doi.org/10.1007/978-3-642-19437-5_8S931056609Brown, P., Pietra, S.D., Pietra, V.D., Mercer, R.: The mathematics of machine translation. 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In: Proc. of EACL 2003, pp. 387–393 (2003)Sanchis-Trilles, G., Casacuberta, F.: Log-linear weight optimisation via bayesian adaptation in statistical machine translation. In: Proceedings of COLING 2010, Beijing, China (2010)Callison-Burch, C., Bannard, C., Schroeder, J.: Improving statistical translation through editing. In: Proc. of 9th EAMT Workshop Broadening Horizons of Machine Translation and its Applications, Malta (2004)Barrachina, S., et al.: Statistical approaches to computer-assisted translation. Computational Linguistics 35, 3–28 (2009)Casacuberta, F., et al.: Human interaction for high quality machine translation. Communications of the ACM 52, 135–138 (2009)Ortiz-Martínez, D., García-Varea, I., Casacuberta, F.: Online learning for interactive statistical machine translation. In: Proceedings of NAACL HLT, Los Angeles (2010)España-Bonet, C., Màrquez, L.: Robust estimation of feature weights in statistical machine translation. In: 14th Annual Conference of the EAMT (2010)Reverberi, G., Szedmak, S., Cesa-Bianchi, N., et al.: Deliverable of package 4: Online learning algorithms for computer-assisted translation (2008)Crammer, K., Dekel, O., Keshet, J., Shalev-Shwartz, S., Singer, Y.: Online passive-aggressive algorithms. Journal of Machine Learning Research 7, 551–585 (2006)Snover, M., Dorr, B., Schwartz, R., Micciulla, L., Makhoul, J.: A study of translation edit rate with targeted human annotation. In: Proc. of AMTA, Cambridge, MA, USA (2006)Papineni, K., Roukos, S., Ward, T., Zhu, W.: Bleu: A method for automatic evaluation of machine translation. In: Proc. of ACL 2002 (2002)Rosenblatt, F.: The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review 65, 386–408 (1958)Collins, M.: Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms. 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Analysis of Models for Decentralized and Collaborative AI on Blockchain

Machine learning has recently enabled large advances in artificial intelligence, but these results can be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models can quickly become out of date without effort to acquire more data and maintain them. Published proposals to provide models and data for free for certain tasks include Microsoft Research's Decentralized and Collaborative AI on Blockchain. The framework allows participants to collaboratively build a dataset and use smart contracts to share a continuously updated model on a public blockchain. The initial proposal gave an overview of the framework omitting many details of the models used and the incentive mechanisms in real world scenarios. In this work, we evaluate the use of several models and configurations in order to propose best practices when using the Self-Assessment incentive mechanism so that models can remain accurate and well-intended participants that submit correct data have the chance to profit. We have analyzed simulations for each of three models: Perceptron, Na\"ive Bayes, and a Nearest Centroid Classifier, with three different datasets: predicting a sport with user activity from Endomondo, sentiment analysis on movie reviews from IMDB, and determining if a news article is fake. We compare several factors for each dataset when models are hosted in smart contracts on a public blockchain: their accuracy over time, balances of a good and bad user, and transaction costs (or gas) for deploying, updating, collecting refunds, and collecting rewards. A free and open source implementation for the Ethereum blockchain and simulations written in Python is provided at https://github.com/microsoft/0xDeCA10B. This version has updated gas costs using newer optimizations written after the original publication.Comment: Accepted to ICBC 202

Gene identification for the cblD defect of vitamin B12 metabolism

Background Vitamin B12 (cobalamin) is an essential cofactor in several metabolic pathways. Intracellular conversion of cobalamin to its two coenzymes, adenosylcobalamin in mitochondria and methylcobalamin in the cytoplasm, is necessary for the homeostasis of methylmalonic acid and homocysteine. Nine defects of intracellular cobalamin metabolism have been defined by means of somatic complementation analysis. One of these defects, the cblD defect, can cause isolated methylmalonic aciduria, isolated homocystinuria, or both. Affected persons present with multisystem clinical abnormalities, including developmental, hematologic, neurologic, and metabolic findings. The gene responsible for the cblD defect has not been identified. Methods We studied seven patients with the cblD defect, and skin fibroblasts from each were investigated in cell culture. Microcell-mediated chromosome transfer and refined genetic mapping were used to localize the responsible gene. This gene was transfected into cblD fibroblasts to test for the rescue of adenosylcobalamin and methylcobalamin synthesis. Results The cblD gene was localized to human chromosome 2q23.2, and a candidate gene, designated MMADHC (methylmalonic aciduria, cblD type, and homocystinuria), was identified in this region. Transfection of wild-type MMADHC rescued the cellular phenotype, and the functional importance of mutant alleles was shown by means of transfection with mutant constructs. The predicted MMADHC protein has sequence homology with a bacterial ATP-binding cassette transporter and contains a putative cobalamin binding motif and a putative mitochondrial targeting sequence. Conclusions Mutations in a gene we designated MMADHC are responsible for the cblD defect in vitamin B12 metabolism. Various mutations are associated with each of the three biochemical phenotypes of the disorder

Drone IV - The Final Chapter (Parasol Drone)

Project to create a controllable, aerial drone capable of providing shading from UVA/UVB radiation. Consumers will be able to participate in outdoor activities (run, walk, play sports, etc.) while being protected from the sun. Shading mechanism can open and close midflight with the press of a button. No prior experience necessary for operation. Appropriate for all weather conditions except rain or snow (electronics of drone should not get wet). Adult supervision is necessary for children under the age of twelve

Automation and Organizational Change in Libraries (Book Review)

published or submitted for publicatio

Fast cosmological parameter estimation using neural networks

We present a method for accelerating the calculation of CMB power spectra, matter power spectra and likelihood functions for use in cosmological parameter estimation. The algorithm, called CosmoNet, is based on training a multilayer perceptron neural network and shares all the advantages of the recently released Pico algorithm of Fendt & Wandelt, but has several additional benefits in terms of simplicity, computational speed, memory requirements and ease of training. We demonstrate the capabilities of CosmoNet by computing CMB power spectra over a box in the parameter space of flat \Lambda CDM models containing the 3\sigma WMAP1 confidence region. We also use CosmoNet to compute the WMAP3 likelihood for flat \Lambda CDM models and show that marginalised posteriors on parameters derived are very similar to those obtained using CAMB and the WMAP3 code. We find that the average error in the power spectra is typically 2-3% of cosmic variance, and that CosmoNet is \sim 7 \times 10^4 faster than CAMB (for flat models) and \sim 6 \times 10^6 times faster than the official WMAP3 likelihood code. CosmoNet and an interface to CosmoMC are publically available at www.mrao.cam.ac.uk/software/cosmonet.Comment: 5 pages, 5 figures, minor changes to match version accepted by MNRAS letter

P619Role of Toll-like receptor 5 in the development of post-myocardial infarction inflammation

Background: Inflammatory processes play a key role in the pathophysiology of myocardial infarction (MI). Genetic deletion of toll-like recpetors (TLRs), especially TLR2 and TLR4 have shown protective role in murine models of MI. The role of other TLRs remains unknown. We have previously shown that cardiomyocytes express TLR5 and that the ligand of TLR5, flagellin, activates the NF-kappaB and MAPK pathways in cardiomyocytes. We also have shown that injection of flagellin induces acute systolic dysfunction in vivo in mice. Aim: Determine the role of TLR5 in the development of post-MI inflammation. Methods: A murine model of myocardial infarction was done by a 30 minutes ligation of the left anterior descending coronary artery followed by 2 hours of reperfusion. Infarct size was measured by standard Evans blue/TTC staining. Plasma creatine kinase (CK) was quantified as a read out of myocardial necrosis. Tissue and plasma cytokines (MIP-2, MCP-1, IL-6) were quantified by ELISA. To determine the extent of tissue lipid peroxidation we used malondialdehyde and 4-hydroxynonenal-HIS adduct assays. Tissue protein oxidation was tested by protein carbonyl ELISA kit. Phosphorylation of MAPK was analyzed by western blot. Results: Genetic suppression of TLR5 induced a significant increase of myocardial infarct size and plasma CK, of biochemical markers of myocardial oxidative stress, and cytokine levels in the heart and the plasma after MI. These effects were associated with a marked enhancement of p38 phosphorylation in the heart from TLR5 KO mice. Conclusion: TLR5 protects from acute myocardial injury and reduces local and systemic inflammation during myocardial infarction. The mechanisms may involve reduced p38 signaling, decreased oxidative stress and attenuated cytokine expression. Research supported by the Swiss National Science Foundation, Grant n° 310030_135394/