The Age, Metallicity and Alpha-Element Abundance of Galactic Globular Clusters from Single Stellar Population Models

Establishing the reliability with which stellar population parameters can be measured is vital to extragalactic astronomy. Galactic GCs provide an excellent medium in which to test the consistency of Single Stellar Population (SSP) models as they should be our best analogue to a homogeneous (single) stellar population. Here we present age, metallicity and $\alpha$-element abundance measurements for 48 Galactic globular clusters (GCs) as determined from integrated spectra using Lick indices and SSP models from Thomas, Maraston & Korn, Lee & Worthey and Vazdekis et al. By comparing our new measurements to independent determinations we are able to assess the ability of these SSPs to derive consistent results -- a key requirement before application to heterogeneous stellar populations like galaxies. We find that metallicity determinations are extremely robust, showing good agreement for all models examined here, including a range of enhancement methods. Ages and $\alpha$-element abundances are accurate for a subset of our models, with the caveat that the range of these parameters in Galactic GCs is limited. We are able to show that the application of published Lick index response functions to models with fixed abundance ratios allows us to measure reasonable $\alpha$-element abundances from a variety of models. We also examine the age-metallicity and [$\alpha$/Fe]-metallicity relations predicted by SSP models, and characterise the possible effects of varied model horizontal branch morphology on our overall results.Comment: 22 pages, 19 figures, accepted for publication in MNRA

Measured descent: A new embedding method for finite metrics

We devise a new embedding technique, which we call measured descent, based on decomposing a metric space locally, at varying speeds, according to the density of some probability measure. This provides a refined and unified framework for the two primary methods of constructing Frechet embeddings for finite metrics, due to [Bourgain, 1985] and [Rao, 1999]. We prove that any n-point metric space (X,d) embeds in Hilbert space with distortion O(sqrt{alpha_X log n}), where alpha_X is a geometric estimate on the decomposability of X. As an immediate corollary, we obtain an O(sqrt{(log lambda_X) \log n}) distortion embedding, where \lambda_X is the doubling constant of X. Since \lambda_X\le n, this result recovers Bourgain's theorem, but when the metric X is, in a sense, ``low-dimensional,'' improved bounds are achieved. Our embeddings are volume-respecting for subsets of arbitrary size. One consequence is the existence of (k, O(log n)) volume-respecting embeddings for all 1 \leq k \leq n, which is the best possible, and answers positively a question posed by U. Feige. Our techniques are also used to answer positively a question of Y. Rabinovich, showing that any weighted n-point planar graph embeds in l_\infty^{O(log n)} with O(1) distortion. The O(log n) bound on the dimension is optimal, and improves upon the previously known bound of O((log n)^2).Comment: 17 pages. No figures. Appeared in FOCS '04. To appeaer in Geometric & Functional Analysis. This version fixes a subtle error in Section 2.

A Comment on "A direct approach for determining the switch soints in the Karnik-Mendel algorithm"

This letter is a supplement to the previous paper “A Direct Approach for Determining the Switch Points in the Karnik-Mendel Algorithm”. In the previous paper, the enhanced iterative algorithm with stop condition (EIASC) was shown to be the most inefficient in R. Such outcome is apparently different from the results in another paper in which EIASC was illustrated to be the most efficient in Matlab. An investigation has been made into this apparent inconsistency and it can be confirmed that both the results in R and Matlab are valid for the EIASC algorithm. The main reason for such phenomenon is the efficiency difference of loop operations in R and Matlab. It should be noted that the efficiency of an algorithm is closely related to its implementation in practice. In this letter, we update the comparisons of the three algorithms in the previous paper based on optimised implementations under five programming languages (Matlab, R, Python, C and Java). From this, we conclude that results in one programming language cannot be simply extended to all languages

The First Step of Neurospora crassa Molybdenum Cofactor Biosynthesis: Regulatory Aspects under N-Derepressing and Nitrate-Inducing Conditions

Molybdenum cofactor (Moco) is the active site prosthetic group found in all Moco dependent enzymes, except for nitrogenase. Mo-enzymes are crucial for viability throughout all kingdoms of life as they catalyze a diverse set of two electron transfer reactions. The highly conserved Moco biosynthesis pathway consists of four different steps in which guanosine triphosphate is converted into cyclic pyranopterin monophosphate, molybdopterin (MPT), and subsequently adenylated MPT and Moco. Although the enzymes and mechanisms involved in these steps are well characterized, the regulation of eukaryotic Moco biosynthesis is not. Within this work, we described the regulation of Moco biosynthesis in the filamentous fungus Neurospora crassa, which revealed the first step of the multi-step pathway to be under transcriptional control. We found, that upon the induction of high cellular Moco demand a single transcript variant of the nit-7 gene is increasingly formed pointing towards, that essentially the encoded enzyme NIT7-A is the key player for Moco biosynthesis activity in Neurospora

Comparing Performance Potentials of Classical and Intuitionistic Fuzzy Systems in Terms of Sculpting the State Space

This paper provides new application-independent perspectives about the performance potential of an intuitionistic (I-) fuzzy system over a (classical) TSK fuzzy system. It does this by extending sculpting the state space works from a TSK fuzzy system to an I-fuzzy system. It demonstrates that, for piecewise-linear membership functions (trapezoids and triangles), an I-fuzzy system always has significantly more first-order rule partitions of the state space-the coarse sculpting of the state space-than does a TSK fuzzy system, and that some I-fuzzy systems also have more second-order rule partitions of the state space-the fine sculpting of the state space-than does a TSK fuzzy system. It is the author's conjecture that, for piecewise-linear membership functions (trapezoids and triangles): It is the always-significantly greater coarse (and possibly fine) sculpting of the state space that provides an I-fuzzy system with the potential to outperform a TSK fuzzy system; and, that a type-1 I-fuzzy system has the potential to outperform an interval type-2 fuzzy system. Index Terms-intuitionistic fuzzy sets, intuitionistic fuzzy systems, TSK fuzzy systems, rule partitions, sculpting the state space

A Comprehensive Study of the Efficiency of Type-Reduction Algorithms

Improving the efficiency of type-reduction algorithms continues to attract research interest. Recently, there have been some new type-reduction approaches claiming that they are more efficient than the well-known algorithms such as the enhanced Karnik-Mendel (EKM) and the enhanced iterative algorithm with stopping condition (EIASC). In a previous paper, we found that the computational efficiency of an algorithm is closely related to the platform, and how it is implemented. In computer science, the dependence on languages is usually avoided by focusing on the complexity of algorithms (using big O notation). In this paper, the main contribution is the proposal of two novel type-reduction algorithms. Also, for the first time, a comprehensive study on both existing and new type-reduction approaches is made based on both algorithm complexity and practical computational time under a variety of programming languages. Based on the results, suggestions are given for the preferred algorithms in different scenarios depending on implementation platform and application context

Interval-valued fuzzy decision trees with optimal neighbourhood perimeter

This research proposes a new model for constructing decision trees using interval-valued fuzzy membership values. Most existing fuzzy decision trees do not consider the uncertainty associated with their membership values, however, precise values of fuzzy membership values are not always possible. In this paper, we represent fuzzy membership values as intervals to model uncertainty and employ the look-ahead based fuzzy decision tree induction method to construct decision trees. We also investigate the significance of different neighbourhood values and define a new parameter insensitive to specific data sets using fuzzy sets. Some examples are provided to demonstrate the effectiveness of the approach

An automated system for measuring parameters of nematode sinusoidal movement

BACKGROUND: Nematode sinusoidal movement has been used as a phenotype in many studies of C. elegans development, behavior and physiology. A thorough understanding of the ways in which genes control these aspects of biology depends, in part, on the accuracy of phenotypic analysis. While worms that move poorly are relatively easy to describe, description of hyperactive movement and movement modulation presents more of a challenge. An enhanced capability to analyze all the complexities of nematode movement will thus help our understanding of how genes control behavior. RESULTS: We have developed a user-friendly system to analyze nematode movement in an automated and quantitative manner. In this system nematodes are automatically recognized and a computer-controlled microscope stage ensures that the nematode is kept within the camera field of view while video images from the camera are stored on videotape. In a second step, the images from the videotapes are processed to recognize the worm and to extract its changing position and posture over time. From this information, a variety of movement parameters are calculated. These parameters include the velocity of the worm's centroid, the velocity of the worm along its track, the extent and frequency of body bending, the amplitude and wavelength of the sinusoidal movement, and the propagation of the contraction wave along the body. The length of the worm is also determined and used to normalize the amplitude and wavelength measurements. To demonstrate the utility of this system, we report here a comparison of movement parameters for a small set of mutants affecting the Go/Gq mediated signaling network that controls acetylcholine release at the neuromuscular junction. The system allows comparison of distinct genotypes that affect movement similarly (activation of Gq-alpha versus loss of Go-alpha function), as well as of different mutant alleles at a single locus (null and dominant negative alleles of the goa-1 gene, which encodes Go-alpha). We also demonstrate the use of this system for analyzing the effects of toxic agents. Concentration-response curves for the toxicants arsenite and aldicarb, both of which affect motility, were determined for wild-type and several mutant strains, identifying P-glycoprotein mutants as not significantly more sensitive to either compound, while cat-4 mutants are more sensitive to arsenite but not aldicarb. CONCLUSIONS: Automated analysis of nematode movement facilitates a broad spectrum of experiments. Detailed genetic analysis of multiple alleles and of distinct genes in a regulatory network is now possible. These studies will facilitate quantitative modeling of C. elegans movement, as well as a comparison of gene function. Concentration-response curves will allow rigorous analysis of toxic agents as well as of pharmacological agents. This type of system thus represents a powerful analytical tool that can be readily coupled with the molecular genetics of nematodes