Modelling and performance analysis of four and eight element TCAS

This semi-annual report describes the work performed during the period September 1989 through March 1990. The first section presents a description of the effect of the engines of the Boeing 737-200 on the performance of a bottom mounted eight-element traffic alert and collision avoidance system (TCAS). The second section deals exclusively with a four element TCAS antenna. The model obtained to simulate the four element TCAS and new algorithms developed for studying its performance are described. The effect of location on its performance when mounted on top of a Boeing 737-200 operating at 1060 MHz is discussed. It was found that the four element TCAS generally does not perform as well as the eight element TCAS III

M dwarfs in the b201 tile of the VVV survey: Colour-based Selection, Spectral Types and Light Curves

The intrinsically faint M dwarfs are the most numerous stars in the Galaxy, have main-sequence lifetimes longer than the Hubble time, and host some of the most interesting planetary systems known to date. Their identification and classification throughout the Galaxy is crucial to unravel the processes involved in the formation of planets, stars and the Milky Way. The ESO Public Survey VVV is a deep near-IR survey mapping the Galactic bulge and southern plane. The VVV b201 tile, located in the border of the bulge, was specifically selected for the characterisation of M dwarfs. We used VISTA photometry to identify M dwarfs in the VVV b201 tile, to estimate their subtypes, and to search for transit-like light curves from the first 26 epochs of the survey. UKIDSS photometry from SDSS spectroscopically identified M dwarfs was used to calculate their expected colours in the $YJHK_s$ VISTA system. A colour-based spectral subtype calibration was computed. Possible giants were identified by a $(J-K_s, H_{J})$ reduced proper motion diagram. The light curves of 12.8<$K_s$<15.8 colour-selected M dwarfs were inspected for signals consistent with transiting objects. We identified 23,345 objects in VVV b201 with colours consistent with M dwarfs. We provided their spectral types and photometric distances, up to $\sim$ 300 pc for M9s and $\sim$ 1.2 kpc for M4s, from photometry. In the range 12<$K_s$<16, we identified 753 stars as possible giants out of 9,232 M dwarf candidates. While only the first 26 epochs of VVV were available, and 1 epoch was excluded, we were already able to identify transit-like signals in the light curves of 95 M dwarfs and of 12 possible giants. Thanks to its deeper photometry ($\sim$4 magnitudes deeper than 2MASS), the VVV survey will be a major contributor to the discovery and study of M dwarfs and possible companions towards the center of the Milky Way.Comment: 11 pages, 4 figures. Accepted for publication in Catalogs and data of Astronomy and Astrophysic

A holistic approach to enhance the use of neglected and underutilized species: the case of Andean grains in Bolivia and Peru

The IFAD-NUS project, implemented over the course of a decade in two phases, represents the first UN-supported global effort on neglected and underutilized species (NUS). This initiative, deployed and tested a holistic and innovative value chain framework using multi-stakeholder, participatory, inter-disciplinary, pro-poor gender- and nutrition-sensitive approaches. The project has been linking aspects often dealt with separately by R&D, such as genetic diversity, selection, cultivation, harvest, value addition, marketing, and final use, with the goal to contribute to conservation, better incomes, and improved nutrition and strengthened livelihood resilience. The project contributed to the greater conservation of Andean grains and their associated indigenous knowledge, through promoting wider use of their diversity by value chain actors, adoption of best cultivation practices, development of improved varieties, dissemination of high quality seed, and capacity development. Reduced drudgery in harvest and postharvest operations, and increased food safety were achieved through technological innovations. Development of innovative food products and inclusion of Andean grains in school meal programs is projected to have had a positive nutrition outcome for targeted communities. Increased income was recorded for all value chain actors, along with strengthened networking skills and self-reliance in marketing. The holistic approach taken in this study is advocated as an effective strategy to enhance the use of other neglected and underutilized species for conservation and livelihood benefits

Constraint-based sequence mining using constraint programming

The goal of constraint-based sequence mining is to find sequences of symbols that are included in a large number of input sequences and that satisfy some constraints specified by the user. Many constraints have been proposed in the literature, but a general framework is still missing. We investigate the use of constraint programming as general framework for this task. We first identify four categories of constraints that are applicable to sequence mining. We then propose two constraint programming formulations. The first formulation introduces a new global constraint called exists-embedding. This formulation is the most efficient but does not support one type of constraint. To support such constraints, we develop a second formulation that is more general but incurs more overhead. Both formulations can use the projected database technique used in specialised algorithms. Experiments demonstrate the flexibility towards constraint-based settings and compare the approach to existing methods.Comment: In Integration of AI and OR Techniques in Constraint Programming (CPAIOR), 201

Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression

This paper studies the connections among quantile regression, the asymmetric Laplace distribution, maximum likelihood and maximum entropy. We show that the maximum likelihood problem is equivalent to the solution of a maximum entropy problem where we impose moment constraints given by the joint consideration of the mean and median. Using the resulting score functions we propose an estimator based on the joint estimating equations. This approach delivers estimates for the slope parameters together with the associated “most probable” quantile. Similarly, this method can be seen as a penalized quantile regression estimator, where the penalty is given by deviations from the median regression. We derive the asymptotic properties of this estimator by showing consistency and asymptotic normality under certain regularity conditions. Finally, we illustrate the use of the estimator with a simple application to the U.S. wage data to evaluate the effect of training on wages

A cluster mode-coupling approach to weak gelation in attractive colloids

Mode-coupling theory (MCT) predicts arrest of colloids in terms of their volume fraction, and the range and depth of the interparticle attraction. We discuss how effective values of these parameters evolve under cluster aggregation. We argue that weak gelation in colloids can be idealized as a two-stage ergodicity breaking: first at short scales (approximated by the bare MCT) and then at larger scales (governed by MCT applied to clusters). The competition between arrest and phase separation is considered in relation to recent experiments. We predict a long-lived `semi-ergodic' phase of mobile clusters, showing logarithmic relaxation close to the gel line.Comment: 4 pages, 3 figure