MELCHIORS: The Mercator Library of High Resolution Stellar Spectroscopy

Aims. Over the past decades, libraries of stellar spectra have been used in a large variety of science cases, including as sources of reference spectra for a given object or a given spectral type. Despite the existence of large libraries and the increasing number of projects of large-scale spectral surveys, there is to date only one very high-resolution spectral library offering spectra from a few hundred objects from the southern hemisphere (UVES-POP). We aim to extend the sample, offering a finer coverage of effective temperatures and surface gravity with a uniform collection of spectra obtained in the northern hemisphere.Methods. Between 2010 and 2020, we acquired several thousand echelle spectra of bright stars with the Mercator-HERMES spectrograph located in the Roque de Los Muchachos Observatory in La Palma, whose pipeline offers high-quality data reduction products. We have also developed methods to correct for the instrumental response in order to approach the true shape of the spectral continuum. Additionally, we have devised a normalisation process to provide a homogeneous normalisation of the full spectral range for most of the objects.Results. We present a new spectral library consisting of 3256 spectra covering 2043 stars. It combines high signal-to-noise and high spectral resolution over the entire range of effective temperatures and luminosity classes. The spectra are presented in four versions: raw, corrected from the instrumental response, with and without correction from the atmospheric molecular absorption, and normalised (including the telluric correction)

Contractor ability criteria: a view from the Thai construction industry

Realizing that there is a lack of commonality in selecting criteria to evaluate contractor ability, the study aim was to develop a common set of contractor ability criteria for both government and private sectors. This included a standardized set of physical characteristics (hierarchical organizational units) of contractors. The Thai construction industry was surveyed as to the degrees of importance placed on a range of criteria and measures. Similarities and differences between the government and private sectors in selecting contractor ability criteria have been analysed by comparing the importance index and ranking order and comparing mean importance placed on criteria and measures. Relationships between all criteria and measures have also been explored by using correlation coefficients. Factor analysis has been applied to group all highly correlated measures together so as to develop a common set of contractor ability criteria. The result of analysing similarities and differences indicated only slight differences in the mean importance of criteria and measures between the government and private sectors. Thus, a common set of contractor ability criteria has been developed by applying factor analysis, namely, 'engineering/construction', 'procurement/contract', 'project managers', 'human resources', 'quality management systems', 'health and safety', 'plant/equipment', 'financial strength' and 'public relations'.Contractor Ability Criteria, Contractor Ability, Thai Construction Industry, Prequalification, Factor Analysis,

Mixed-Integer Linear Optimization: Primal–Dual Relations and Dual Subgradient and Cutting-Plane Methods

This chapter presents several solution methodologies for mixed-integer linear optimization, stated as mixed-binary optimization problems, by means of Lagrangian duals, subgradient optimization, cutting-planes, and recovery of primal solutions. It covers Lagrangian duality theory for mixed-binary linear optimization, a problem framework for which ultimate success—in most cases—is hard to accomplish, since strong duality cannot be inferred. First, a simple conditional subgradient optimization method for solving the dual problem is presented. Then, we show how ergodic sequences of Lagrangian subproblem solutions can be computed and used to recover mixed-binary primal solutions. We establish that the ergodic sequences accumulate at solutions to a convexified version of the original mixed-binary optimization problem. We also present a cutting-plane approach to the Lagrangian dual, which amounts to solving the convexified problem by Dantzig–Wolfe decomposition, as well as a two-phase method that benefits from the advantages of both subgradient optimization and Dantzig–Wolfe decomposition. Finally, we describe how the Lagrangian dual approach can be used to find near optimal solutions to mixed-binary optimization problems by utilizing the ergodic sequences in a Lagrangian heuristic, to construct a core problem, as well as to guide the branching in a branch-and-bound method. The chapter is concluded with a section comprising notes, references, historical downturns, and reading tips