995 research outputs found

    Shape computations without compositions

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    Parametric CAD supports design explorations through generative methods which compose and transform geometric elements. This paper argues that elementary shape computations do not always correspond to valid compositional shape structures. In many design cases generative rules correspond to compositional structures, but for relatively simple shapes and rules it is not always possible to assign a corresponding compositional structure of parts which account for all operations of the computation. This problem is brought into strong relief when design processes generate multiple compositions according to purpose, such as product structure, assembly, manufacture, etc. Is it possible to specify shape computations which generate just these compositions of parts or are there additional emergent shapes and features? In parallel, combining two compositions would require the associated combined computations to yield a valid composition. Simple examples are presented which throw light on the issues in integrating different product descriptions (i.e. compositions) within parametric CAD

    Metabolitos secundarios de Berberís empetrifolia

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    Berberís empetrifolia Lam. ha sido parcialmente estudiada en cuanto a su contenido de alcaloides cuaternarios. Al reestudiar la corteza y madera de tallos subterráneos de esta planta fue posible aislar un alcaloide dimérico, la paquistanina, y el lignano siringarresinol. Este lignano parece ser un componente común a varias especies chilenas de Berberís; la paquistanina, por el contrario, es una base del tipo aporfinabencilisoquinolina que hasta ahora sólo habia sido encontrada en especies asiáticas del género

    Shape exploration of designs in a style: toward generation of product designs

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    Generative specifications have been used to systematically codify established styles in several design fields including architecture and product design. We examine how designers explore new designs in the early stages of product development as they manipulate and interpret shape representations. A model of exploration is proposed with four types of shape descriptions (contour, decomposition, structure, and design) and the results of the exploration are presented. Generative rules are used to provide consistent stylistic changes first within a given decomposition and second through changing the structure. Style expresses both the analytical order of explanation and the synthetic complexity of exploration. The model of exploration is consistent with observations of design practice. The application of generative design methods demonstrates a logical pattern for early stage design exploration. The model provides the basis for tools to assist designers in exploring families of designs in a style and for following new interpretations that move the exploration from one family to another

    Correlation Functions of Complex Matrix Models

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    For a restricted class of potentials (harmonic+Gaussian potentials), we express the resolvent integral for the correlation functions of simple traces of powers of complex matrices of size NN, in term of a determinant; this determinant is function of four kernels constructed from the orthogonal polynomials corresponding to the potential and from their Cauchy transform. The correlation functions are a sum of expressions attached to a set of fully packed oriented loops configurations; for rotational invariant systems, explicit expressions can be written for each configuration and more specifically for the Gaussian potential, we obtain the large NN expansion ('t Hooft expansion) and the so-called BMN limit.Comment: latex BMN.tex, 7 files, 6 figures, 30 pages (v2 for spelling mistake and added reference) [http://www-spht.cea.fr/articles/T05/174

    Depart and approach procedures for UAS in a VFR environment

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    This paper assesses the depart and approach operations of Unmanned Aircraft Systems (UAS) in one of the most challenging scenarios: when flying under Visual Flight Rules (VFR). Inspired by some existing procedures for (manned) general aviation, some automatic and predefined procedures for UAS are proposed. Hence, standardized paths to specific waypoints close to the airport are defined for depart operations, just before starting the navigation phase. Conversely, and for the approach maneuvers, it is foreseen a first integration into a holding pattern near the landing runway (ideally above it) followed by a standard VFR airfield traffic pattern. This paper discusses the advantages of these operations which aim at minimizing possible conflicts with other existing aircraft while reducing the Pilot-in-Command workload. Finally, some preliminary simulations are shown where these procedures have been successfully tested with simulated surrounding traffic

    On gonihedric loops and quantum gravity

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    We present an analysis of the gonihedric loop model, a reformulation of the two dimensional gonihedric spin model, using two different techniques. First, the usual regular lattice statistical physics problem is mapped onto a height model and studied analytically. Second, the gravitational version of this loop model is studied via matrix models techniques. Both methods lead to the conclusion that the model has cmatter=0c_{matter}=0 for all values of the parameters of the model. In this way it is possible to understand the absence of a continuous transition

    The moderate drift towards less tetracycline-susceptible isolates of contagious agalactia causative agents might result from different molecular mechanisms.

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    ©2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Accepted version of a Published Work that appeared in final form in Veterinary Microbiology. To access the final edited and published work see https://doi.org/10.1016/j.vetmic.2018.05.001Contagious agalactia is a mycoplasmosis that affects small ruminants, is associated with loss of milk production and high morbidity rates, and is highly deleterious to dairy industries. The etiological agents are four mycoplasma (sub)species, of which the relative importance depends on the countries and the animal host. Tetracyclines are non 23 expensive, broad-spectrum antimicrobials and are often used to control mastitis in dairy herds. However, the in vitro efficiency of tetracyclines against each of the etiological agents of contagious agalactia has been poorly assessed. The aims of this study were i) to compare the tetracycline susceptibilities of various field isolates, belonging to different mycoplasma (sub)species and subtypes, collected over the years from different clinical contexts in France or Spain, and ii) to investigate the molecular mechanisms behind the decreased susceptibility of some isolates to tetracyclines. The Minimum Inhibitory Concentrations (MICs) of tetracyclines were determined in vitro on a set of 120 isolates. Statistical analyses were run to define the significance of any observed differences in MICs distribution. As mutations in the genes encoding the ttracycline targets (rrs loci) are most often associated with increased tetracycline MICs in animal mycoplasmas, these genes were sequenced. The loss of susceptibility to tetracyclines after year 2010 is not significant and recent MICs are higher in M. agalactiae, especially isolates from ovine mastitis cases, than in other etiological agents of contagious agalactia. The observed increases in MICs were not always associated with mutations in the rrs alleles which suggests the existence of other resistance mechanisms yet to be decipher

    Defining Rules for Kinematic Shapes with Variable Spatial Relations

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    Designing mechanisms can be a challenging problem, because the underlying kinematics involved are typically not intuitively incorporated into common techniques for design representation. Kinematic shapes and kinematic grammars build on the shape grammar and making grammar formalisms to enable a visually intuitive approach to model and explore mechanisms. With reference to the lower kinematic pairs this paper introduces kinematic shapes. These are connected shapes with parts which have variable spatial relations that account for the relative motion of the parts. The paper considers how such shapes can be defined, the role of elements shared by connected parts, and the motions that result. It also considers how kinematic shape rules can be employed to generate and explore the motion of mechanisms

    MultiBaC: A strategy to remove batch effects between different omic data types

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    [EN] Diversity of omic technologies has expanded in the last years together with the number of omic data integration strategies. However, multiomic data generation is costly, and many research groups cannot afford research projects where many different omic techniques are generated, at least at the same time. As most researchers share their data in public repositories, different omic datasets of the same biological system obtained at different labs can be combined to construct a multiomic study. However, data obtained at different labs or moments in time are typically subjected to batch effects that need to be removed for successful data integration. While there are methods to correct batch effects on the same data types obtained in different studies, they cannot be applied to correct lab or batch effects across omics. This impairs multiomic meta-analysis. Fortunately, in many cases, at least one omics platform-i.e. gene expression- is repeatedly measured across labs, together with the additional omic modalities that are specific to each study. This creates an opportunity for batch analysis. We have developed MultiBaC (multiomic Multiomics Batch-effect Correction correction), a strategy to correct batch effects from multiomic datasets distributed across different labs or data acquisition events. Our strategy is based on the existence of at least one shared data type which allows data prediction across omics. We validate this approach both on simulated data and on a case where the multiomic design is fully shared by two labs, hence batch effect correction within the same omic modality using traditional methods can be compared with the MultiBaC correction across data types. Finally, we apply MultiBaC to a true multiomic data integration problem to show that we are able to improve the detection of meaningful biological effects.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work is part of a research project that is totally funded by Conselleria d'Educacio, Cultura i Esport (Generalitat Valenciana) through PROMETEO grants program for excellence research groups.Ugidos, M.; Tarazona Campos, S.; Prats-Montalbán, JM.; Ferrer, A.; Conesa, A. (2020). MultiBaC: A strategy to remove batch effects between different omic data types. Statistical Methods in Medical Research. 29(10):2851-2864. https://doi.org/10.1177/0962280220907365S285128642910Kupfer, P., Guthke, R., Pohlers, D., Huber, R., Koczan, D., & Kinne, R. W. (2012). Batch correction of microarray data substantially improves the identification of genes differentially expressed in Rheumatoid Arthritis and Osteoarthritis. BMC Medical Genomics, 5(1). doi:10.1186/1755-8794-5-23Gregori, J., Villarreal, L., Méndez, O., Sánchez, A., Baselga, J., & Villanueva, J. (2012). Batch effects correction improves the sensitivity of significance tests in spectral counting-based comparative discovery proteomics. Journal of Proteomics, 75(13), 3938-3951. doi:10.1016/j.jprot.2012.05.005Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research, 43(7), e47-e47. doi:10.1093/nar/gkv007Gagnon-Bartsch, J. A., & Speed, T. P. (2011). Using control genes to correct for unwanted variation in microarray data. Biostatistics, 13(3), 539-552. doi:10.1093/biostatistics/kxr034Nueda, M. j., Ferrer, A., & Conesa, A. (2011). ARSyN: a method for the identification and removal of systematic noise in multifactorial time course microarray experiments. Biostatistics, 13(3), 553-566. doi:10.1093/biostatistics/kxr042Jansen, J. J., Hoefsloot, H. C. J., van der Greef, J., Timmerman, M. E., Westerhuis, J. A., & Smilde, A. K. (2005). ASCA: analysis of multivariate data obtained from an experimental design. Journal of Chemometrics, 19(9), 469-481. doi:10.1002/cem.952Nueda, M. J., Conesa, A., Westerhuis, J. A., Hoefsloot, H. C. J., Smilde, A. K., Talón, M., & Ferrer, A. (2007). Discovering gene expression patterns in time course microarray experiments by ANOVA–SCA. Bioinformatics, 23(14), 1792-1800. doi:10.1093/bioinformatics/btm251Giordan, M. (2013). A Two-Stage Procedure for the Removal of Batch Effects in Microarray Studies. Statistics in Biosciences, 6(1), 73-84. doi:10.1007/s12561-013-9081-1Nyamundanda, G., Poudel, P., Patil, Y., & Sadanandam, A. (2017). A Novel Statistical Method to Diagnose, Quantify and Correct Batch Effects in Genomic Studies. Scientific Reports, 7(1). doi:10.1038/s41598-017-11110-6Reese, S. E., Archer, K. J., Therneau, T. M., Atkinson, E. J., Vachon, C. M., de Andrade, M., … Eckel-Passow, J. E. (2013). A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal component analysis. Bioinformatics, 29(22), 2877-2883. doi:10.1093/bioinformatics/btt480Papiez, A., Marczyk, M., Polanska, J., & Polanski, A. (2018). BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm. Bioinformatics, 35(11), 1885-1892. doi:10.1093/bioinformatics/bty900Keel, B. N., Zarek, C. M., Keele, J. W., Kuehn, L. A., Snelling, W. M., Oliver, W. T., … Lindholm-Perry, A. K. (2018). RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers. BMC Genomics, 19(1). doi:10.1186/s12864-018-4769-8Li, M. D., Burns, T. C., Morgan, A. A., & Khatri, P. (2014). Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases. Acta Neuropathologica Communications, 2(1). doi:10.1186/s40478-014-0093-yAndres-Terre, M., McGuire, H. M., Pouliot, Y., Bongen, E., Sweeney, T. E., Tato, C. M., & Khatri, P. (2015). Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses. Immunity, 43(6), 1199-1211. doi:10.1016/j.immuni.2015.11.003Sandhu, V., Labori, K. J., Borgida, A., Lungu, I., Bartlett, J., Hafezi-Bakhtiari, S., … Haibe-Kains, B. (2019). Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma. JCO Clinical Cancer Informatics, (3), 1-16. doi:10.1200/cci.18.00102Huang, H., Liu, C.-C., & Zhou, X. J. (2010). Bayesian approach to transforming public gene expression repositories into disease diagnosis databases. Proceedings of the National Academy of Sciences, 107(15), 6823-6828. doi:10.1073/pnas.0912043107Pelechano, V., & Pérez-Ortín, J. E. (2010). There is a steady-state transcriptome in exponentially growing yeast cells. Yeast, 27(7), 413-422. doi:10.1002/yea.1768Garcı́a-Martı́nez, J., Aranda, A., & Pérez-Ortı́n, J. E. (2004). Genomic Run-On Evaluates Transcription Rates for All Yeast Genes and Identifies Gene Regulatory Mechanisms. Molecular Cell, 15(2), 303-313. doi:10.1016/j.molcel.2004.06.004Pelechano, V., Chávez, S., & Pérez-Ortín, J. E. (2010). A Complete Set of Nascent Transcription Rates for Yeast Genes. PLoS ONE, 5(11), e15442. doi:10.1371/journal.pone.0015442Zid, B. M., & O’Shea, E. K. (2014). Promoter sequences direct cytoplasmic localization and translation of mRNAs during starvation in yeast. Nature, 514(7520), 117-121. doi:10.1038/nature13578Freeberg, M. A., Han, T., Moresco, J. J., Kong, A., Yang, Y.-C., Lu, Z., … Kim, J. K. (2013). Pervasive and dynamic protein binding sites of the mRNA transcriptome in Saccharomyces cerevisiae. Genome Biology, 14(2), R13. doi:10.1186/gb-2013-14-2-r13McKinlay, A., Araya, C. L., & Fields, S. (2011). Genome-Wide Analysis of Nascent Transcription in Saccharomyces cerevisiae. G3 Genes|Genomes|Genetics, 1(7), 549-558. doi:10.1534/g3.111.000810Castells-Roca, L., García-Martínez, J., Moreno, J., Herrero, E., Bellí, G., & Pérez-Ortín, J. E. (2011). Heat Shock Response in Yeast Involves Changes in Both Transcription Rates and mRNA Stabilities. PLoS ONE, 6(2), e17272. doi:10.1371/journal.pone.0017272Wold, S., Sjöström, M., & Eriksson, L. (2001). PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58(2), 109-130. doi:10.1016/s0169-7439(01)00155-1Folch-Fortuny, A., Vitale, R., de Noord, O. E., & Ferrer, A. (2017). Calibration transfer between NIR spectrometers: New proposals and a comparative study. Journal of Chemometrics, 31(3), e2874. doi:10.1002/cem.2874García Muñoz, S., MacGregor, J. F., & Kourti, T. (2005). Product transfer between sites using Joint-Y PLS. Chemometrics and Intelligent Laboratory Systems, 79(1-2), 101-114. doi:10.1016/j.chemolab.2005.04.009Andrade, J. M., Gómez-Carracedo, M. P., Krzanowski, W., & Kubista, M. (2004). Procrustes rotation in analytical chemistry, a tutorial. Chemometrics and Intelligent Laboratory Systems, 72(2), 123-132. doi:10.1016/j.chemolab.2004.01.007Hurley, J. R., & Cattell, R. B. (2007). The procrustes program: Producing direct rotation to test a hypothesized factor structure. Behavioral Science, 7(2), 258-262. doi:10.1002/bs.3830070216Hartigan, J. A., & Wong, M. A. (1979). Algorithm AS 136: A K-Means Clustering Algorithm. Applied Statistics, 28(1), 100. doi:10.2307/234683
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