Statistics of Partial Minima

Motivated by multi-objective optimization, we study extrema of a set of N points independently distributed inside the d-dimensional hypercube. A point in this set is k-dominated by another point when at least k of its coordinates are larger, and is a k-minimum if it is not k-dominated by any other point. We obtain statistical properties of these partial minima using exact probabilistic methods and heuristic scaling techniques. The average number of partial minima, A, decays algebraically with the total number of points, A ~ N^{-(d-k)/k}, when 1<=k<d. Interestingly, there are k-1 distinct scaling laws characterizing the largest coordinates as the distribution P(y_j) of the jth largest coordinate, y_j, decays algebraically, P(y_j) ~ (y_j)^{-alpha_j-1}, with alpha_j=j(d-k)/(k-j) for 1<=j<=k-1. The average number of partial minima grows logarithmically, A ~ [1/(d-1)!](ln N)^{d-1}, when k=d. The full distribution of the number of minima is obtained in closed form in two-dimensions.Comment: 6 pages, 1 figur

Parasite Dynamics in Untreated Horses Through One Calendar Year

Background: Horses are host to a plethora of parasites. Knowledge of the seasonality of parasite egg shedding and transmission is important for constructing parasite control programs. However, studies describing these patterns are sparse, and have largely been conducted only in the United Kingdom. This study evaluated strongylid egg shedding patterns and transmission dynamics of Strongylus vulgaris in naturally infected and untreated mares and foals through one calendar year in Kentucky, USA. The study also investigated the existence of a peri-parturient rise (PPR) in strongylid egg counts in foaling mares and collected information about Strongyloides westeri and Parascaris spp. in the foals. Methods: This study was conducted from January to December 2018. A herd of 18 mares, one stallion, and 14 foals born in 2018 were followed throughout the year. Sera and feces were collected biweekly from all horses, and worm burdens enumerated in 13 foals at necropsy. An S. vulgaris ELISA antibody test was run on all serum samples. Fecal egg counts were determined for all horses, and coproculture and qPCR assay were employed to test for the presence of S. vulgaris in the mature horses. Data were analyzed using the proc glimmix procedure in the SAS 9.4 software program. Results: We found a general lack of seasonality in strongylid egg shedding throughout the year among the mature horses, and no PPR was demonstrated. Shedding of S. vulgaris eggs displayed a higher abundance during the spring, but fndings were variable and not statistically signifcant. Anti-S. vulgaris antibody concentrations did not display signifcant fuctuations in the mature horses, but evidence of passive transfer of antibodies to the foals was demonstrated, and foals assumed their own production of antibodies starting at approximately 20 weeks of age. Overall, colts shed higher numbers of strongylid, ascarid, and S. westeri eggs than fllies. Conclusions: This study demonstrated a lack of seasonality in strongylid egg shedding for the study population, which is in stark contrast to previous studies conducted elsewhere. This strongly suggests that more studies should be done investigating these patterns under diferent climatic condition

Parasite Dynamics in Untreated Horses through One Calendar Year

BACKGROUND: Horses are host to a plethora of parasites. Knowledge of the seasonality of parasite egg shedding and transmission is important for constructing parasite control programs. However, studies describing these patterns are sparse, and have largely been conducted only in the United Kingdom. This study evaluated strongylid egg shedding patterns and transmission dynamics of Strongylus vulgaris in naturally infected and untreated mares and foals through one calendar year in Kentucky, USA. The study also investigated the existence of a peri-parturient rise (PPR) in strongylid egg counts in foaling mares and collected information about Strongyloides westeri and Parascaris spp. in the foals. METHODS: This study was conducted from January to December 2018. A herd of 18 mares, one stallion, and 14 foals born in 2018 were followed throughout the year. Sera and feces were collected biweekly from all horses, and worm burdens enumerated in 13 foals at necropsy. An S. vulgaris ELISA antibody test was run on all serum samples. Fecal egg counts were determined for all horses, and coproculture and qPCR assay were employed to test for the presence of S. vulgaris in the mature horses. Data were analyzed using the proc glimmix procedure in the SAS 9.4 software program. RESULTS: We found a general lack of seasonality in strongylid egg shedding throughout the year among the mature horses, and no PPR was demonstrated. Shedding of S. vulgaris eggs displayed a higher abundance during the spring, but findings were variable and not statistically significant. Anti-S. vulgaris antibody concentrations did not display significant fluctuations in the mature horses, but evidence of passive transfer of antibodies to the foals was demonstrated, and foals assumed their own production of antibodies starting at approximately 20 weeks of age. Overall, colts shed higher numbers of strongylid, ascarid, and S. westeri eggs than fillies. CONCLUSIONS: This study demonstrated a lack of seasonality in strongylid egg shedding for the study population, which is in stark contrast to previous studies conducted elsewhere. This strongly suggests that more studies should be done investigating these patterns under different climatic conditions

Estimating Mutual Information

We present two classes of improved estimators for mutual information $M(X,Y)$, from samples of random points distributed according to some joint probability density $\mu(x,y)$. In contrast to conventional estimators based on binnings, they are based on entropy estimates from $k$-nearest neighbour distances. This means that they are data efficient (with $k=1$ we resolve structures down to the smallest possible scales), adaptive (the resolution is higher where data are more numerous), and have minimal bias. Indeed, the bias of the underlying entropy estimates is mainly due to non-uniformity of the density at the smallest resolved scale, giving typically systematic errors which scale as functions of $k/N$ for $N$ points. Numerically, we find that both families become {\it exact} for independent distributions, i.e. the estimator $\hat M(X,Y)$ vanishes (up to statistical fluctuations) if $\mu(x,y) = \mu(x) \mu(y)$. This holds for all tested marginal distributions and for all dimensions of $x$ and $y$. In addition, we give estimators for redundancies between more than 2 random variables. We compare our algorithms in detail with existing algorithms. Finally, we demonstrate the usefulness of our estimators for assessing the actual independence of components obtained from independent component analysis (ICA), for improving ICA, and for estimating the reliability of blind source separation.Comment: 16 pages, including 18 figure

Quasiperiodic time dependent current in driven superlattices: distorted Poincare maps and strange attractors

Intriguing routes to chaos have been experimentally observed in semiconductor superlattices driven by an ac field. In this work, a theoretical model of time dependent transport in ac driven superlattices is numerically solved. In agreement with experiments, distorted Poincare maps in the quasiperiodic regime are found. They indicate the appearance of very complex attractors and routes to chaos as the amplitude of the AC signal increases. Distorted maps are caused by the discrete well-to-well jump motion of a domain wall during spiky high-frequency self-sustained oscillations of the current.Comment: 10 pages, 4 figure

Systematic Analysis of Stability Patterns in Plant Primary Metabolism

Metabolic networks are characterized by complex interactions and regulatory mechanisms between many individual components. These interactions determine whether a steady state is stable to perturbations. Structural kinetic modeling (SKM) is a framework to analyze the stability of metabolic steady states that allows the study of the system Jacobian without requiring detailed knowledge about individual rate equations. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. Until now, SKM experiments applied univariate tests to detect the network components with the largest influence on stability. In this work, we present an extended SKM approach relying on supervised machine learning to detect patterns of enzyme-metabolite interactions that act together in an orchestrated manner to ensure stability. We demonstrate its application on a detailed SK-model of the Calvin-Benson cycle and connected pathways. The identified stability patterns are highly complex reflecting that changes in dynamic properties depend on concerted interactions between several network components. In total, we find more patterns that reliably ensure stability than patterns ensuring instability. This shows that the design of this system is strongly targeted towards maintaining stability. We also investigate the effect of allosteric regulators revealing that the tendency to stability is significantly increased by including experimentally determined regulatory mechanisms that have not yet been integrated into existing kinetic models

The transition between stochastic and deterministic behavior in an excitable gene circuit

We explore the connection between a stochastic simulation model and an ordinary differential equations (ODEs) model of the dynamics of an excitable gene circuit that exhibits noise-induced oscillations. Near a bifurcation point in the ODE model, the stochastic simulation model yields behavior dramatically different from that predicted by the ODE model. We analyze how that behavior depends on the gene copy number and find very slow convergence to the large number limit near the bifurcation point. The implications for understanding the dynamics of gene circuits and other birth-death dynamical systems with small numbers of constituents are discussed.Comment: PLoS ONE: Research Article, published 11 Apr 201

A multiobjective model for passive portfolio management: an application on the S&P 100 index

This is an author's accepted manuscript of an article published in: “Journal of Business Economics and Management"; Volume 14, Issue 4, 2013; copyright Taylor & Francis; available online at: http://dx.doi.org/10.3846/16111699.2012.668859Index tracking seeks to minimize the unsystematic risk component by imitating the movements of a reference index. Partial index tracking only considers a subset of the stocks in the index, enabling a substantial cost reduction in comparison with full tracking. Nevertheless, when heterogeneous investment profiles are to be satisfied, traditional index tracking techniques may need different stocks to build the different portfolios. The aim of this paper is to propose a methodology that enables a fund s manager to satisfy different clients investment profiles but using in all cases the same subset of stocks, and considering not only one particular criterion but a compromise between several criteria. For this purpose we use a mathematical programming model that considers the tracking error variance, the excess return and the variance of the portfolio plus the curvature of the tracking frontier. The curvature is not defined for a particular portfolio, but for all the portfolios in the tracking frontier. This way funds managers can offer their clients a wide range of risk-return combinations just picking the appropriate portfolio in the frontier, all of these portfolios sharing the same shares but with different weights. An example of our proposal is applied on the S&P 100.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). A multiobjective model for passive portfolio management: an application on the S&P 100 index. Journal of Business Economics and Management. 14(4):758-775. doi:10.3846/16111699.2012.668859S758775144Aktan, B., Korsakienė, R., & Smaliukienė, R. (2010). TIME‐VARYING VOLATILITY MODELLING OF BALTIC STOCK MARKETS. Journal of Business Economics and Management, 11(3), 511-532. doi:10.3846/jbem.2010.25Ballestero, E., & Romero, C. (1991). A theorem connecting utility function optimization and compromise programming. Operations Research Letters, 10(7), 421-427. doi:10.1016/0167-6377(91)90045-qBeasley, J. E. (1990). OR-Library: Distributing Test Problems by Electronic Mail. Journal of the Operational Research Society, 41(11), 1069-1072. doi:10.1057/jors.1990.166Beasley, J. E., Meade, N., & Chang, T.-J. (2003). An evolutionary heuristic for the index tracking problem. European Journal of Operational Research, 148(3), 621-643. doi:10.1016/s0377-2217(02)00425-3Canakgoz, N. A., & Beasley, J. E. (2009). Mixed-integer programming approaches for index tracking and enhanced indexation. European Journal of Operational Research, 196(1), 384-399. doi:10.1016/j.ejor.2008.03.015Connor, G., & Leland, H. (1995). Cash Management for Index Tracking. Financial Analysts Journal, 51(6), 75-80. doi:10.2469/faj.v51.n6.1952Corielli, F., & Marcellino, M. (2006). Factor based index tracking. Journal of Banking & Finance, 30(8), 2215-2233. doi:10.1016/j.jbankfin.2005.07.012Derigs, U., & Nickel, N.-H. (2004). On a Local-Search Heuristic for a Class of Tracking Error Minimization Problems in Portfolio Management. Annals of Operations Research, 131(1-4), 45-77. doi:10.1023/b:anor.0000039512.98833.5aDose, C., & Cincotti, S. (2005). Clustering of financial time series with application to index and enhanced index tracking portfolio. Physica A: Statistical Mechanics and its Applications, 355(1), 145-151. doi:10.1016/j.physa.2005.02.078Focardi, S. M., & Fabozzi 3, F. J. (2004). A methodology for index tracking based on time-series clustering. Quantitative Finance, 4(4), 417-425. doi:10.1080/14697680400008668Gaivoronski, A. A., Krylov, S., & van der Wijst, N. (2005). Optimal portfolio selection and dynamic benchmark tracking. European Journal of Operational Research, 163(1), 115-131. doi:10.1016/j.ejor.2003.12.001Hallerbach, W. G., & Spronk, J. (2002). The relevance of MCDM for financial decisions. Journal of Multi-Criteria Decision Analysis, 11(4-5), 187-195. doi:10.1002/mcda.328Jarrett, J. E., & Schilling, J. (2008). DAILY VARIATION AND PREDICTING STOCK MARKET RETURNS FOR THE FRANKFURTER BÖRSE (STOCK MARKET). Journal of Business Economics and Management, 9(3), 189-198. doi:10.3846/1611-1699.2008.9.189-198Roll, R. (1992). A Mean/Variance Analysis of Tracking Error. The Journal of Portfolio Management, 18(4), 13-22. doi:10.3905/jpm.1992.701922Rudolf, M., Wolter, H.-J., & Zimmermann, H. (1999). A linear model for tracking error minimization. Journal of Banking & Finance, 23(1), 85-103. doi:10.1016/s0378-4266(98)00076-4Ruiz-Torrubiano, R., & Suárez, A. (2008). A hybrid optimization approach to index tracking. Annals of Operations Research, 166(1), 57-71. doi:10.1007/s10479-008-0404-4Rutkauskas, A. V., & Stasytyte, V. (s. f.). Decision Making Strategies in Global Exchange and Capital Markets. Advances and Innovations in Systems, Computing Sciences and Software Engineering, 17-22. doi:10.1007/978-1-4020-6264-3_4Tabata, Y., & Takeda, E. (1995). Bicriteria Optimization Problem of Designing an Index Fund. Journal of the Operational Research Society, 46(8), 1023-1032. doi:10.1057/jors.1995.139Teresienė, D. (2009). LITHUANIAN STOCK MARKET ANALYSIS USING A SET OF GARCH MODELS. Journal of Business Economics and Management, 10(4), 349-360. doi:10.3846/1611-1699.2009.10.349-36

Augmented Reality: What Motivates Late Millennials towards Fashion Mobile Apps?

Generation Z is expected to be a dominant demographic and economic group. Cyber-waviness, constant reliance on smart devices that allows them to be always connected are among some of their intrinsic characteristics. The combination of this reality with the ever-changing technological environment is compelling retailers to reshape their business strategies, to meet this group desires and expectations and to foster their engagement. Augmented reality (AR) is emerging as a technological solution that pleases both consumers and retailers. This paper aims to answer two main questions: (1) How does generation Z evaluate an AR experience? (2) Which attributes/benefits do they value or not during an AR experience? Drawing on a qualitative methodology – content analysis of 34 interviewees – we discuss six main dimensions the potential customer value of the relationship between them and AR experiences under retailer context.info:eu-repo/semantics/publishedVersio

Protons in near earth orbit

The proton spectrum in the kinetic energy range 0.1 to 200 GeV was measured by the Alpha Magnetic Spectrometer (AMS) during space shuttle flight STS-91 at an altitude of 380 km. Above the geomagnetic cutoff the observed spectrum is parameterized by a power law. Below the geomagnetic cutoff a substantial second spectrum was observed concentrated at equatorial latitudes with a flux ~ 70 m^-2 sec^-1 sr^-1. Most of these second spectrum protons follow a complicated trajectory and originate from a restricted geographic region.Comment: 19 pages, Latex, 7 .eps figure