Ant genomics (Hymenoptera: Formicidae): challenges to overcome and opportunities to seize

SN is funded by the Danish National Research Foundation (DNRF57). YW is funded by BBSRC grant BB/K004204/1, NERC grant NE/L00626X/1, and is a fellow of the Software Sustainability Institute

09-03 "Economic Writing on the Pressing Problems of the Day: The Roles of Moral Intuition and Methodological Confusion"

Economists are often called on to help address pressing problems of the day, yet many economists are uncomfortable about disclosing the values that they bring to this work. This essay explores how an inadequate understanding of the role of methodology, as related to ethics and human emotions of concern, underlies this reluctance and compromises the quality of economic advice. The tension between caring about the problems, on the one hand, and writing within the existing culture of the discipline, on the other, are illustrated with examples from U.S. policymaking, behavioral economics, and the economics of climate change and global poverty. Potential steps towards a more responsible, "strongly objective," and policy-useful economics are discussed.

User interfaces in space science instrumentation

This thesis examines user interaction with instrumentation in the specific context of space science. It gathers together existing practice in machine interfaces with a look at potential future usage and recommends a new approach to space science projects with the intention of maximising their science return. It first takes a historical perspective on user interfaces and ways of defining and measuring the science return of a space instrument. Choices of research methodology are considered. Implementation details such as the concepts of usability, mental models, affordance and presentation of information are described, and examples of existing interfaces in space science are given. A set of parameters for use in analysing and synthesizing a user interface is derived by using a set of case studies of diverse failures and from previous work. A general space science user analysis is made by looking at typical practice, and an interview plus persona technique is used to group users with interface designs. An examination is made of designs in the field of astronomical instrumentation interfaces, showing the evolution of current concepts and including ideas capable of sustaining progress in the future. The parameters developed earlier are then tested against several established interfaces in the space science context to give a degree of confidence in their use. The concept of a simulator that is used to guide the development of an instrument over the whole lifecycle is described, and the idea is proposed that better instrumentation would result from more efficient use of the resources available. The previous ideas in this thesis are then brought together to describe a proposed new approach to a typical development programme, with an emphasis on user interaction. The conclusion shows that there is significant room for improvement in the science return from space instrumentation by attention to the user interface

Handling a messy world: lessons learned when trying to make the ecosystem services concept operational

The concept of ecosystem services is widely used in the scientific literature and increasingly also in policy and practice. Nevertheless, operationalising the concept, i.e. putting it into practice, is still a challenge. We describe the approach of the EU-project OpenNESS (Operationalisation of Ecosystem Services and Natural Capital), which was created in response to this challenge to critically evaluate the concept when applied to real world problems at different scales and in different policy sectors. General requirements for operationalization, the relevance of conceptual frameworks and lessons learnt from 27 case study applications are synthesized in a set of guiding principles. We also briefly describe some integrative tools as developed in OpenNESS which support the implementation of the principles. The guiding principles are grouped under three major headlines: “Defining the problem and opening up the problem space”, “Considering ethical issues” and “Assessing alternative methods, tools and actions”. Real world problems are often “wicked” problems, which at first are seldom clear-cut and well-defined, but often rather complex and subject to differing interpretations and interests. We take account of that complexity and emphasise that there is not one simple and straightforward way to approach real world problems involving ecosystem services. The principles and tools presented are meant to provide some guidance for tackling this complexity by means of a transdisciplinary methodology that facilitates the operationalisation of the ecosystem services concept

Mathematics and Statistics in the Social Sciences

Over the years, mathematics and statistics have become increasingly important in the social sciences1 . A look at history quickly confirms this claim. At the beginning of the 20th century most theories in the social sciences were formulated in qualitative terms while quantitative methods did not play a substantial role in their formulation and establishment. Moreover, many practitioners considered mathematical methods to be inappropriate and simply unsuited to foster our understanding of the social domain. Notably, the famous Methodenstreit also concerned the role of mathematics in the social sciences. Here, mathematics was considered to be the method of the natural sciences from which the social sciences had to be separated during the period of maturation of these disciplines. All this changed by the end of the century. By then, mathematical, and especially statistical, methods were standardly used, and their value in the social sciences became relatively uncontested. The use of mathematical and statistical methods is now ubiquitous: Almost all social sciences rely on statistical methods to analyze data and form hypotheses, and almost all of them use (to a greater or lesser extent) a range of mathematical methods to help us understand the social world. Additional indication for the increasing importance of mathematical and statistical methods in the social sciences is the formation of new subdisciplines, and the establishment of specialized journals and societies. Indeed, subdisciplines such as Mathematical Psychology and Mathematical Sociology emerged, and corresponding journals such as The Journal of Mathematical Psychology (since 1964), The Journal of Mathematical Sociology (since 1976), Mathematical Social Sciences (since 1980) as well as the online journals Journal of Artificial Societies and Social Simulation (since 1998) and Mathematical Anthropology and Cultural Theory (since 2000) were established. What is more, societies such as the Society for Mathematical Psychology (since 1976) and the Mathematical Sociology Section of the American Sociological Association (since 1996) were founded. Similar developments can be observed in other countries. The mathematization of economics set in somewhat earlier (Vazquez 1995; Weintraub 2002). However, the use of mathematical methods in economics started booming only in the second half of the last century (Debreu 1991). Contemporary economics is dominated by the mathematical approach, although a certain style of doing economics became more and more under attack in the last decade or so. Recent developments in behavioral economics and experimental economics can also be understood as a reaction against the dominance (and limitations) of an overly mathematical approach to economics. There are similar debates in other social sciences. It is, however, important to stress that problems of one method (such as axiomatization or the use of set theory) can hardly be taken as a sign of bankruptcy of mathematical methods in the social sciences tout court. This chapter surveys mathematical and statistical methods used in the social sciences and discusses some of the philosophical questions they raise. It is divided into two parts. Sections 1 and 2 are devoted to mathematical methods, and Sections 3 to 7 to statistical methods. As several other chapters in this handbook provide detailed accounts of various mathematical methods, our remarks about the latter will be rather short and general. Statistical methods, on the other hand, will be discussed in-depth

Low-carbon after-life : Sustainable use of flooded coal mine voids as a thermal energy source : a baseline activity for minimising post-closure environmental risks (LoCAL) : final report

The LoCAL project aimed at facilitating wider use of thermal energy from mine water for both heating and cooling purposes. In order to achieve that, LoCAL project have developed new technical tools and have tested them on pilot implementations in 3 countries. In particular, the project have provided bespoke tools for investigating flow and heat transfer in flooded mine workings. New tools for quantifying and modelling heat transfer in networks of flooded mine workings have been also developed . Another aspect of LoCAL project was to overcome the hydrochemical barriers to effective heat transfer from raw and treated mine waters. Ochre clogging is a well-known phenomenon which affects a lot of mine water heating and cooling systems. LoCAL project not only covered technical and engineering issues, but also provided economic and management models for efficient energy extraction and distribution. Technical, legal, managerial and cost-benefit analyses of various types of decentralised and centralised heat pump systems have been carried out. Project activities were simultaneously undertaken in mining areas of UK, Spain and Poland by research organizations in partnership with industrial enterprises. University of Glasgow in partnership with Alkane Energy Ltd. have implemented pilot applications in UK: Caphouse Colliery, Overton, near Wakefield, Yorkshire and Markham Colliery, Bolsover, Derbyshire. In Spain University of Oviedo and industrial partner HUNOSA have performed pilot implementation at Barredo shaft in Mieres, Asturias, while in Poland Central Mining Institute in partnership with Armada Development have performed pilot application in former Szombierki mine at Bytom, Upper Silesian Coal Basin

A comparative study of forecast combinations in tourism

With the rapid expansion of the tourist sector in many nations, tourism forecasting has piqued the interest of marketers and academic researchers. Despite that interest, necessary knowledge about tourism forecasting is still lacking. This study addresses crucial questions to better understand the mechanisms underlying forecasting in tourism. In the present study, we investigate whether forecasting performance could be improved by merging tourism forecasts given by two different models: LF and PMI. The investigation measures forecasting of two different metrics over four distinct lead periods. Two error measures are employed to assess forecast accuracy: the mean absolute percentage error and the mean squared error. To combine the forecasts, we used four established methods, i.e. The simple average method (SA), the geometric mean method (GEOM), the inverse of the mean squared forecast error method (INVM), and ultimately the variance-covariance method (VACO). Our results show remarkable consistency. For the first metric, the combination of forecasts ranks between the two single model forecasts for both error measures. The findings of the other metric reveal that the forecast combination gives the most accurate forecast. In addition to the four different weighting methods, this study proposes a method of combining forecasts using neural networking. This latter approach shows results that differs from the other four methodologies. The neural networks reveal inconsistent and erroneous results when the mean absolute percentage error is used to rank forecast accuracy. However, when using the mean squared error, the approach rates first out of all the other methods for all lead times. Altogether, we demonstrate that combining two reasonably accurate forecasts decreases forecast error. Across all forecasting horizons, the combined forecast is much more accurate than the worst single model forecast. Furthermore, the results reveal that when two relatively accurate forecasts are merged, as with metric 2 in the current study, the combined forecast has more minor errors than both single forecasts. The findings indicate that a forecast combination in tourism might yield positive outcomes

A comparative study of forecast combinations in tourism

With the rapid expansion of the tourist sector in many nations, tourism forecasting has piqued the interest of marketers and academic researchers. Despite that interest, necessary knowledge about tourism forecasting is still lacking. This study addresses crucial questions to better understand the mechanisms underlying forecasting in tourism. In the present study, we investigate whether forecasting performance could be improved by merging tourism forecasts given by two different models: LF and PMI. The investigation measures forecasting of two different metrics over four distinct lead periods. Two error measures are employed to assess forecast accuracy: the mean absolute percentage error and the mean squared error. To combine the forecasts, we used four established methods, i.e. The simple average method (SA), the geometric mean method (GEOM), the inverse of the mean squared forecast error method (INVM), and ultimately the variance-covariance method (VACO). Our results show remarkable consistency. For the first metric, the combination of forecasts ranks between the two single model forecasts for both error measures. The findings of the other metric reveal that the forecast combination gives the most accurate forecast. In addition to the four different weighting methods, this study proposes a method of combining forecasts using neural networking. This latter approach shows results that differs from the other four methodologies. The neural networks reveal inconsistent and erroneous results when the mean absolute percentage error is used to rank forecast accuracy. However, when using the mean squared error, the approach rates first out of all the other methods for all lead times. Altogether, we demonstrate that combining two reasonably accurate forecasts decreases forecast error. Across all forecasting horizons, the combined forecast is much more accurate than the worst single model forecast. Furthermore, the results reveal that when two relatively accurate forecasts are merged, as with metric 2 in the current study, the combined forecast has more minor errors than both single forecasts. The findings indicate that a forecast combination in tourism might yield positive outcomes

Economic Writing on the Pressing Problems of the Day: The Roles of Moral Intuition and Methodological Confusion

Economists are often called on to help address pressing problems of the day, yet many economists are uncomfortable about disclosing the values that they bring to this work. This essay explores how an inadequate understanding of the role of methodology, as related to ethics and human emotions of concern, underlies this reluctance and compromises the quality of economic advice. The tension between caring about the problems, on the one hand, and writing within the existing culture of the discipline, on the other, are illustrated with examples from U.S. policymaking, behavioral economics, and the economics of climate change and global poverty. Potential steps towards a more responsible, strongly objective, and policy-useful economics are discussed