Surface Quasigeostrophic Turbulence : The Study of an Active Scalar

We study the statistical and geometrical properties of the potential temperature (PT) field in the Surface Quasigeostrophic (SQG) system of equations. In addition to extracting information in a global sense via tools such as the power spectrum, the g-beta spectrum and the structure functions we explore the local nature of the PT field by means of the wavelet transform method. The primary indication is that an initially smooth PT field becomes rough (within specified scales), though in a qualitatively sparse fashion. Similarly, initially 1D iso-PT contours (i.e., PT level sets) are seen to acquire a fractal nature. Moreover, the dimensions of the iso-PT contours satisfy existing analytical bounds. The expectation that the roughness will manifest itself in the singular nature of the gradient fields is confirmed via the multifractal nature of the dissipation field. Following earlier work on the subject, the singular and oscillatory nature of the gradient field is investigated by examining the scaling of a probability measure and a sign singular measure respectively. A physically motivated derivation of the relations between the variety of scaling exponents is presented, the aim being to bring out some of the underlying assumptions which seem to have gone unnoticed in previous presentations. Apart from concentrating on specific properties of the SQG system, a broader theme of the paper is a comparison of the diagnostic inertial range properties of the SQG system with both the 2D and 3D Euler equations.Comment: 26 pages, 11 figures. To appear in Chao

An Ontology-Based Recommender System with an Application to the Star Trek Television Franchise

Collaborative filtering based recommender systems have proven to be extremely successful in settings where user preference data on items is abundant. However, collaborative filtering algorithms are hindered by their weakness against the item cold-start problem and general lack of interpretability. Ontology-based recommender systems exploit hierarchical organizations of users and items to enhance browsing, recommendation, and profile construction. While ontology-based approaches address the shortcomings of their collaborative filtering counterparts, ontological organizations of items can be difficult to obtain for items that mostly belong to the same category (e.g., television series episodes). In this paper, we present an ontology-based recommender system that integrates the knowledge represented in a large ontology of literary themes to produce fiction content recommendations. The main novelty of this work is an ontology-based method for computing similarities between items and its integration with the classical Item-KNN (K-nearest neighbors) algorithm. As a study case, we evaluated the proposed method against other approaches by performing the classical rating prediction task on a collection of Star Trek television series episodes in an item cold-start scenario. This transverse evaluation provides insights into the utility of different information resources and methods for the initial stages of recommender system development. We found our proposed method to be a convenient alternative to collaborative filtering approaches for collections of mostly similar items, particularly when other content-based approaches are not applicable or otherwise unavailable. Aside from the new methods, this paper contributes a testbed for future research and an online framework to collaboratively extend the ontology of literary themes to cover other narrative content.Comment: 25 pages, 6 figures, 5 tables, minor revision

Quantification of abnormal repetitive behaviour in captive European starlings (Sturnus vulgaris).

Stereotypies are repetitive, unvarying and goalless behaviour patterns that are often considered indicative of poor welfare in captive animals. Quantifying stereotypies can be difficult, particularly during the early stages of their development when behaviour is still flexible. We compared two methods for objectively quantifying the development of route-tracing stereotypies in caged starlings. We used Markov chains and T-pattern analysis (implemented by the software package, Theme) to identify patterns in the sequence of locations a bird occupied within its cage. Pattern metrics produced by both methods correlated with the frequency of established measures of stereotypic behaviour and abnormal behaviour patterns counted from video recordings, suggesting that both methods could be useful for identifying stereotypic individuals and quantifying stereotypic behaviour. We discuss the relative benefits and disadvantages of the two approaches

An assessment of EU Cohesion Policy in the UK regions: direct effects and the dividend of targeting. LEQS Discussion Paper No. 135/2018 June 2018

With the prospective exit of the UK from the European Union, a crucial question is whether EU Structural Funds have been beneficial for the country and which aspects of Cohesion Policy should be maintained if EU funds are to be replaced. This paper addresses this question through a twofold investigation, assessing not only whether but also how EU funds have contributed to regional growth in the UK over three programming periods from 1994 to 2013. We document a significant and robust effect of Cohesion Policy in the UK, with higher proportions of Structural Funds associated to higher economic growth both on the whole and particularly in the less developed regions of the country. In addition, we show that the strategic orientation of investments also plays a distinct role for regional growth. While concentration of investments on specific pillars seems to have no direct growth effects, unless regions can rely on pre-existing competitive advantages in key development areas, we unveil clear evidence that targeting investments on specific areas of relative regional need has a significant and autonomous effect on growth. These findings have important implications for the design of regional policy interventions in Britain after Brexit

Writing with Discipline: A Call for Avoiding APA Style Guide Errors in Manuscript Preparation

The education community in the United States—as in many countries—is extremely large and diverse. Indeed, as documented by Mosteller, Nave, and Miech (2004), The United States has more than 3.6 million teachers in elementary and secondary education, more than 100,000 principals, and about 15,000 school districts, each with its own set of district administrators, school board members, and concerned citizens. The parents and family members of the 60 million students in elementary and secondary education represent another constituency, as do the policymakers and legislators in the 50 states (along with the District of Columbia) and at the federal level. Postsecondary education represents another 1 million faculty members, along with an enrollment of 15 million undergraduates and 1.8 million graduate students. (p. 29) Indeed, with the number of individuals involved in the educational system, educational research has the potential to play a pivotal role in improving the quality of education—from Kindergarten through primary, through secondary, through tertiary education. Yet, for educational research to play such a role, its findings must be disseminated to individuals (e.g., educators, administrators, stakeholders, policymakers) and groups (e.g., teacher associations) who can most effectively use them (Mosteller et al., 2004; Onwuegbuzie, Leech, & Whitmore, 2008). Unfortunately, research findings do not disseminate themselves, regardless of how statistically, practically, clinically, or economically significant they are for the field of education. Rather, it is educational researchers in general and practitioner-researchers in particular who must convey these findings