Anthropogenic noise and atmospheric absorption of sound induce amplitude shifts in the songs of Southern House Wren (Troglodytes aedon musculus)

Urban Ecosystems - Birdsong is an important feature that mediates several aspects of bird reproduction, such as mate choice, territory defense, and individual recognition. Any factor that impairs...     

Legal indigeneity: knowledge,legal discourse and the construction of indigenous identity in Colombia

ABSTRACT

This paper analyses the creation of the indigenous legal subject in Colombia from the perspective of legal-knowledge regimens. It analyses the turn from medical psychiatric assessments to indigenous identity to anthropological discourses on cultural differences. This article describes the legal construction of the indigenous subject in two historical moments. On the one hand, in the context of formation of the nation-state in Colombia and, on the other hand, in the transition towards contemporary multicultural constitutionalism within which legal discourse creates taxonomies for the definition of identities and the recognition of special rights to people who claim to be indigenous.     

Bayesian estimation of a flexible bifactor generalized partial credit model to survey data

Item response theory (IRT) models provide an important contribution in the analysis of polytomous items, such as Likert scale items in survey data. We propose a bifactor generalized partial credit model (bifac-GPC model) with flexible link functions - probit, logit and complementary log-log - for use in analysis of ordered polytomous item scale data. In order to estimate the parameters of the proposed model, we use a Bayesian approach through the NUTS algorithm and show the advantages of implementing IRT models through the Stan language. We present an application to marketing scale data. Specifically, we apply the model to a dataset of non-users of a mobile banking service in order to highlight the advantages of this model. The results show important managerial implications resulting from consumer perceptions. We provide a discussion of the methodology for this type of data and extensions. Codes are available for practitioners and researchers to replicate the application.     

New MNE subsidiaries in old clusters: when,why, and how

Despite the rise of globalization, industrial clusters remain vibrant spaces for the generation of knowledge and innovation. Aware of this reality, multinational enterprises (MNEs) seek to reconcile the advantages of international operations with the specific endowments of individual territories. By studying the case of the Inditex subsidiary in the Vinalopó footwear cluster, this research shows how the creation and activity of a specialized subsidiary and the evolution of the industrial system interweave. The study shows that, rather than agglomeration per se, access to specific resources guides location as the cluster matures. Furthermore, local embeddedness shapes post-entry dynamics at the micro and meso levels. Autonomous decisions boost the subsidiary’s access to local networks and the exploitation of cluster advantages, aiding the resilience of the cluster by contributing extra-cluster knowledge.     

Zero-truncated compound Poisson integer-valued GARCH models for time series

Starting from the compound Poisson INGARCH models, we introduce in this paper a new family of integer-valued models suitable to describe count data without zeros that we name zero-truncated CP-INGARCH processes. For such class of models, a probabilistic study concerning moments existence, stationarity and ergodicity is developed. The conditional quasi-maximum likelihood method is introduced to consistently estimate the parameters of a wide zero-truncated compound Poisson subclass of models. The conditional maximum likelihood method is also used to estimate the parameters of ZTCP-INGARCH processes associated with well-specified conditional laws. A simulation study that compares some of those estimators and illustrates their finite distance behaviour as well as a real-data application conclude the paper.     

Factorial Validity and Invariance of the Rosenberg Self-Esteem Scale Among Portuguese Youngsters

The purpose of the present study was to examine the reliability, factorial validity and measurement invariance (across gender, age and physical activity participation) of a Portuguese version of the Rosenberg Self-Esteem Scale (RSES). The sample consisted of 1,763 Portuguese youngsters (731 male and 1,032 female) with ages between 15 and 20 years. Reliability estimate for the one-factor solution was .845, although some proposed RSES’s underlying dimensions were lower than .70. Confirmatory factor analysis revealed that the best-fitting model was a single self-esteem factor, plus simultaneous correlated uniqueness for positively and negatively worded items. Multigroup analysis supported measurement invariance across age and physical activity participation, and partial metric invariance across gender, as three items failed to show metric equivalence. These results provide evidence that RSES has excellent psychometric properties and it is a valid self-esteem measure to be used among Portuguese youngsters.     

A multivariate uniformity test for the case of unknown support

A test for the hypothesis of uniformity on a support S⊂ℝ ^d is proposed. It is based on the use of multivariate spacings as those studied in Janson (Ann. Probab. 15:274–280, 1987). As a novel aspect, this test can be adapted to the case that the support S is unknown, provided that it fulfils the shape condition of λ-convexity. The consistency properties of this test are analyzed and its performance is checked through a small simulation study. The numerical problems involved in the practical calculation of the maximal spacing (which is required to obtain the test statistic) are also discussed in some detail.     

New algorithms for k-center and extensions

The problem of interest is covering a given point set with homothetic copies of several convex containers C ₁,…,C _k , while the objective is to minimize the maximum over the dilatation factors. Such k-containment problems arise in various applications, e.g. in facility location, shape fitting, data classification or clustering. So far most attention has been paid to the special case of the Euclidean k-center problem, where all containers C _i are Euclidean unit balls. Recent developments based on so-called core-sets enable not only better theoretical bounds in the running time of approximation algorithms but also improvements in practically solvable input sizes. Here, we present some new geometric inequalities and a Mixed-Integer-Convex-Programming formulation. Both are used in a very effective branch-and-bound routine which not only improves on best known running times in the Euclidean case but also handles general and even different containers among the C _i .