Unidimensional model of the ad-atom diffusion on a substrate submitted to a standing acoustic wave II. Solutions of the ad-atom motion equation

The ad-atom dynamic equation, a Langevin type equation is analyzed and solved using some non-linear analytical and numerical tools. We noticeably show that the effect of the surface acoustic wave is to induce an effective potential that governs the diffusion of the ad-atom: the minima of this effective potential correspond to the preferential sites in which the ad-atom spends more time. The strength of this effective potential is compared to the destructuring role of the thermal diffusion and to the crystalline potential induced by the substrate

Large (d, D, D′, s)-bipartite digraphs

AbstractA (d, D, D′, s)-digraph is a directed graph with diameter D and maximum out-degree d such that after the deletion of any s of its vertices the resulting digraph has diameter at most D′. Our concern is to find large, i.e. with order as large as possible, (d, D, D′, s)-bipartite digraphs. To this end, it is proved that some members of a known family of large bipartite digraphs satisfy a Menger-type condition. Namely, between any pair of non-adjacent vertices they have s + 1 internally disjoint paths of length at most D′. Then, a new family of (d, D, D′, s)-bipartite digraphs with order very close to the upper bound is obtained

Statistical Mechanics of finite arrays of coupled bistable elements

We discuss the equilibrium of a single collective variable characterizing a finite set of coupled, noisy, bistable systems as the noise strength, the size and the coupling parameter are varied. We identify distinct regions in parameter space. The results obtained in prior works in the asymptotic infinite size limit are significantly different from the finite size results. A procedure to construct approximate 1-dimensional Langevin equation is adopted. This equation provides a useful tool to understand the collective behavior even in the presence of an external driving force

Unidimensional model of the ad-atom diffusion on a substrate submitted to a standing acoustic wave I. Derivation of the ad-atom motion equation

The effect of a standing acoustic wave on the diffusion of an ad-atom on a crystalline surface is theoretically studied. We used an unidimensional space model to study the ad-atom+substrate system. The dynamic equation of the ad-atom, a Generalized Langevin equation, is analytically derived from the full Hamiltonian of the ad-atom+substrate system submitted to the acoustic wave. A detailed analysis of each term of this equation, as well as of their properties, is presented. Special attention is devoted to the expression of the effective force induced by the wave on the ad-atom. It has essentially the same spatial and time dependences as its parent standing acoustic wave

Diversidad genética de ibias (Oxalis tuberosa Molina) y cubios (Tropaeolum tuberosum Ruíz y Pavón) en Boyacá

The Andean region is considered as an area which has a great diversity of species including roots and Andean tubers like ibias (Oxalis tuberosa Molina) and cubios (Tropaeolum tuberosum Ruíz and Pavón). They are basic components of the diet of rural communities. Their tubers feature high content of primary and secondary metabolites that confers antibiotic, antioxidant, insecticides, nematicides, anticarcinogenic and diuretic properties. Considering their huge potential and the fact that there are no studies of genetic diversity of these species in Boyacá, the molecular characterization of 10 ibias and 11 cubios from Soracá, Ventaquemada, Tuta, San Pedro de Iguaque and Puente de Boyacá municipalities was proposed. The analysis by the coefficient of Nei-Li discriminated the population into two groups according to the morphological characteristics of the tuber and per species. The average heterozygosity estimated was 0,41 and a genetic differentiation coefficient of 0.15. The results obtained in this study demonstrated the existence of a genetic variation at an intraspecific level and a gene flow between the two evaluated species, which can be used in breeding programs tending to the production of hybrids and the exploitation of heterotic effects.Key words: Andean tubers, microsatellites, variability, hybridization.La región andina es considerada un área que alberga una gran diversidad de especies entre ellas las raíces y tubérculos andinos como las ibias (Oxalis tuberosa Molina) y los cubios (Tropaeolum tuberosum Ruíz y Pavón), los cuales constituyen un componente básico de la dieta de las comunidades rurales. Sus tubérculos presentan altos contenidos de metabolitos primarios y secundarios que les confiere propiedades antibióticas, antioxidantes insecticidas, nematicidas, anticancerígenas y diuréticas. Teniendo en cuenta su enorme potencial y que en Boyacá no existen estudios de diversidad genética en estas especies se planteó la caracterización molecular de 10 materiales de ibias y 11 de cubios procedentes de los municipios de Soracá, Ventaquemada, Tuta, San Pedro de Iguaque y el Puente de Boyacá. El análisis mediante el coeficiente de NeiLi diferenció a la población en dos grandes grupos de acuerdo a las características morfológicas del tubérculo y a la especie. La heterocigosidad promedio estimada fue de 0,41 y un coeficiente de diferenciación genética de 0,15. Los resultados obtenidos en este estudio mostraron la existencia de una variabilidad genética a nivel intraespecífico y flujo genético entre las dos especies evaluadas lo cual puede ser aprovechado en esquemas de mejoramiento tendientes a la producción de híbridos y la explotación de los efectos heteróticos. Palabras clave: Tubérculos andinos, microsatélites, variabilidad, hibridación

Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models

[EN] This paper introduces the Group Linear Algorithm with Sparse Principal decomposition, an algorithm for supervised variable selection and clustering. Our approach extends the Sparse Group Lasso regularization to calculate clusters as part of the model fit. Therefore, unlike Sparse Group Lasso, our idea does not require prior specification of clusters between variables. To determine the clusters, we solve a particular case of sparse Singular Value Decomposition, with a regularization term that follows naturally from the Group Lasso penalty. Moreover, this paper proposes a unified implementation to deal with, but not limited to, linear regression, logistic regression, and proportional hazards models with right-censoring. Our methodology is evaluated using both biological and simulated data, and details of the implementation in R and hyperparameter search are discussed.Laria, JC.; Aguilera-Morillo, MC.; Lillo, RE. (2022). Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models. Statistical Papers. 64(1):227-253. https://doi.org/10.1007/s00362-022-01313-z227253641Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X et al (2000) Distinct types of diffuse large b-cell lymphoma identified by gene expression profiling. Nature 403(6769):503–511Bair E, Hastie T, Paul D, Tibshirani R (2006) Prediction by supervised principal components. J Am Stat Assoc 101(473):119–137Beck A, Teboulle M (2009) A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J Imag Sci 2(1):183–202Beisser D, Klau GW, Dandekar T, Müller T, Dittrich MT (2010) Bionet: an r-package for the functional analysis of biological networks. Bioinformatics 26(8):1129–1130Bergstra J, Bengio Y (2012) Random search for hyper-parameter optimization. J Mach Learn Res 13(Feb):281–305Bühlmann P, Rütimann P, van de Geer S, Zhang CH (2013) Correlated variables in regression: clustering and sparse estimation. J Stat Plan Inference 143(11):1835–1858Chen K, Chen K, Müller HG, Wang JL (2011) Stringing high-dimensional data for functional analysis. J Am Stat Assoc 106(493):275–284Ciuperca G (2020) Adaptive elastic-net selection in a quantile model with diverging number of variable groups. Statistics 54(5):1147–1170Dittrich MT, Klau GW, Rosenwald A, Dandekar T, Müller T (2008) Identifying functional modules in protein-protein interaction networks: an integrated exact approach. Bioinformatics 24(13):i223–i231Eddelbuettel D, François R (2011) Rcpp: seamless R and C++ integration. J Stat Softw 40(8):1–18Friedman J, Hastie T, Tibshirani R (2010a) A note on the group lasso and a sparse group lasso. arXiv preprint arXiv:1001.0736Friedman J, Hastie T, Tibshirani R (2010b) Regularization paths for generalized linear models via coordinate descent. J Stat Softw 33(1):1Kuhn M (2020) tune: Tidy Tuning Tools. https://CRAN.R-project.org/package=tune, r package version 0.1.0Kuhn M, Vaughan D (2020) parsnip: a Common API to Modeling and Analysis Functions. https://CRAN.R-project.org/package=parsnip, r package version 0.0.5Laria JC, Carmen Aguilera-Morillo M, Lillo RE (2019) An iterative sparse-group lasso. J Comput Graph Stat 28(3):722–731Luo S, Chen Z (2020) Feature selection by canonical correlation search in high-dimensional multiresponse models with complex group structures. J Am Stat Assoc 115(531):1227–1235Moore DF (2016) Applied survival analysis using R. Springer, New YorkNdiaye E, Fercoq O, Gramfort A, Salmon J (2016) Gap safe screening rules for sparse-group lasso. In: Advances in Neural Information Processing Systems, pp 388–396Price BS, Sherwood B (2017) A cluster elastic net for multivariate regression. J Mach Learn Res 18(1):8685–8723Rand WM (1971) Objective criteria for the evaluation of clustering methods. J Am Stat Assoc 66(336):846–850Ren S, Kang EL, Lu JL (2020) Mcen: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression. Stat Comput 30(2):291–304Rosenwald A, Wright G, Chan WC, Connors JM, Campo E, Fisher RI, Gascoyne RD, Muller-Hermelink HK, Smeland EB, Giltnane JM et al (2002) The use of molecular profiling to predict survival after chemotherapy for diffuse large-b-cell lymphoma. N Engl J Med 346(25):1937–1947Shen H, Huang JZ (2008) Sparse principal component analysis via regularized low rank matrix approximation. J Multivar Anal 99(6):1015–1034Simon N, Friedman J, Hastie T, Tibshirani R (2013) A sparse-group lasso. J Comput Graph Stat 22(2):231–245Snoek J, Larochelle H, Adams RP (2012) Practical bayesian optimization of machine learning algorithms. In: Advances in Neural Information Processing Systems, pp 2951–2959Therneau TM (2015) A package for survival analysis in S. https://CRAN.R-project.org/package=survival, version 2.38Therneau TM, Grambsch PM (2000) Modeling survival data: extending the cox model. Springer, New YorkTibshirani R (1996) Regression shrinkage and selection via the lasso. J R Stat Soc 58(1):267–288Tibshirani R, Bien J, Friedman J, Hastie T, Simon N, Taylor J, Tibshirani RJ (2012) Strong rules for discarding predictors in lasso-type problems. J R Stat Soc Ser B 74(2):245–266Witten DM, Shojaie A, Zhang F (2014) The cluster elastic net for high-dimensional regression with unknown variable grouping. Technometrics 56(1):112–122Zhang Y, Zhang N, Sun D, Toh KC (2020) An efficient hessian based algorithm for solving large-scale sparse group lasso problems. Math Program 179(1):223–263Zhao H, Wu Q, Li G, Sun J (2019) Simultaneous estimation and variable selection for interval-censored data with broken adaptive ridge regression. J Am Stat Assoc 1–13Zhou N, Zhu J (2010) Group variable selection via a hierarchical lasso and its oracle property. Stat Interface 3:557–574Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J R Stat Soc Ser B 67(2):301–32

Xps Study of the Oxidation State of Uranium Dioxide

In this article we report an investigation of the oxidation state of uranium dioxide using X-Ray Photoelectron Spectroscopy, and by comparing to results obtained in previous studies. We find that uranium dioxide in powder appears to share its six valence electrons with the oxygen atoms to form crystalline UO3

Microcanonical quantum fluctuation theorems

Previously derived expressions for the characteristic function of work performed on a quantum system by a classical external force are generalized to arbitrary initial states of the considered system and to Hamiltonians with degenerate spectra. In the particular case of microcanonical initial states explicit expressions for the characteristic function and the corresponding probability density of work are formulated. Their classical limit as well as their relations to the respective canonical expressions are discussed. A fluctuation theorem is derived that expresses the ratio of probabilities of work for a process and its time reversal to the ratio of densities of states of the microcanonical equilibrium systems with corresponding initial and final Hamiltonians.From this Crooks-type fluctuation theorem a relation between entropies of different systems can be derived which does not involve the time reversed process. This entropy-from-work theorem provides an experimentally accessible way to measure entropies.Comment: revised and extended versio

Síntesis y eficacia de formulaciones de liberación lenta del herbicida Mesotriona

Ponencia presentada en el XV Congreso de la Sociedad Española de Malherbología SEMh 2015 “La Malherbología y la Transferencia Tecnológica” Sevilla, 19 al 22 de octubre de 2015[ES]: Se ha comprobado la eficacia de formulaciones desarrolladas mediante complejos surfactante-sepiolita en la reducción de la lixiviación del herbicida mesotriona. Entre las formulaciones desarrolladas se ha escogido aquella que presentaba un perfil de liberación más lento en ensayos in vitro. Al aplicarse en columnas de suelo se observó una lixiviación del herbicida y acumulación con la formulación comercial en los segmentos inferiores a diferencia de la formulación desarrollada, que se correlacionaba con un incremento de la bioeficacia en los segmentos superiores. En experimentos en parcelas de campo, a diferencia de la formulación comercial, no se observó un rebrote de las malas hierbas al usar la formulación desarrollada. [EN]: Synthesis and efficiency of slow release formulations of the herbicide mesotrione. The bioefficay of developed formulations based on surfactant-sepiolite complexes for reduced leaching of the herbicide mesotrione was tested. The formulation with a slower release pattern in in-vitro experiments was chosen for soil column and field experiments. In soil columns, the commercial formulation was leached and accumulated in the lower segments unlike the synthesized formulation, with a higher amount retained in the upper segments which was also correlated with a higher bioefficacy. In field experiments, a regrowth of weeds with the clay-based formulation was not observed, unlike the commercial formulation.Esta investigación ha recibido financiación a través de los proyectos CMT2009-07425 (MEC) cofinanciado por el Fondo Europeo de Desarrollo Regional (FEDER) y el Proyecto Bilateral Hispano-Argentino PRI-PIBAR-2011-1393 (MINECO-MINCYT). Carmen Galán agradece la beca Predoctoral disfrutada y asociada al Proyecto de Excelencia P09- RNM-4581.Peer Reviewe