A Relative Impact Ranking of Political Studies In Ireland

Against a background of the Irish government’s concerns with Key Performance Indicators (KPIs) and the British government’s wishes for a more quantitative Research Assessment Exercise (RAE), our study conducts a relative impact assessment of the study of politics, government, political science, and international relations in Ireland. Impact is measured as citations from the publications of permanent staff in eight Irish politics departments, based on data compiled in April 2008 from two leading academic indexes – ISI’s Web of Science and Scopus – as well as the now popular Google Scholar. We discuss some of the criticisms that naturally arise in a study of this nature. Then, following similar exercises in other disciplines (e.g. economics), we use the impact measures to compare and rank individual scholars as well as departments. We also explore the extent to which the choice of different indexes, and different measures, influences the results that we obtain. While there are differences, in particular between indexes based purely on articles and those that access books and other material, the results from the different indexes are strongly correlated.

Mapping the Irish Policy Space:Voter and Party Spaces in Preferential

In this note we map the Irish policy space, locating both voters and parties on the most salient policy dimensions in Ireland. Estimates of the voter locations are based on the Irish National Election Survey (INES), conducted in 2002. Estimates of the party positions are based on an expert survey of party positions conducted by the authors in late 2002. We show that respondent self-placements on a priori policy scales are highly biased and difficult to interpret, and we rely instead on building scale positions for respondents from their answers to relevant attitude questions in the INES. The results provide a methodological template for locating voters and parties in a common space – a significant problem for any analyst who wants to create an empirical elaboration of a spatial model of party competition.

Spin-orbit evolution of Mercury revisited

While it is accepted that the eccentricity of Mercury (0.206) favours entrapment into the 3:2 spin-orbit resonance, open is the question how and when the capture took place. A recent work by Makarov (2012) has demonstrated that trapping into this resonance is certain if the eccentricity is larger than 0.2, provided that we use a realistic tidal model, the one which is based on the Darwin-Kaula expansion of the tidal torque. The physics-based tidal model changes dramatically the statistics of the possible final spin states. First, we discover that after only one encounter with the spin-orbit 3:2 resonance this resonance becomes the most probable end-state. Second, if a capture into this (or any other) resonance takes place, the capture becomes final, several crossings of the same state being forbidden by our model. Third, within our model the trapping of Mercury happens much faster than previously believed: for most histories, 10 - 20 Myr are sufficient. Fourth, even a weak laminar friction between the solid mantle and a molten core would most likely result in a capture in the 2:1 or even higher resonance. So the principal novelty of our paper is that the 3:2 end-state is more ancient than the same end-state obtained when the constant time lag model is employed. The swift capture justifies our treatment of Mercury as a homogeneous, unstratified body whose liquid core had not yet formed by the time of trapping. We also provide a critical analysis of the hypothesis by Wieczorek et al. (2012) that the early Mercury might had been retrograde, whereafter it synchronised its spin and then accelerated it to the 3:2 resonance. Accurate processing of the available data on cratering does not support that hypothesis, while the employment of a realistic rheology invalidates a key element of the hypothesis, an intermediate pseudosynchronous state needed to spin-up to the 3:2 resonance.Comment: Extended version of the submitted paper, accepted for publication in Icaru

Populational adaptive evolution, chemotherapeutic resistance and multiple anti-cancer therapies

Resistance to chemotherapies, particularly to anticancer treatments, is an increasing medical concern. Among the many mechanisms at work in cancers, one of the most important is the selection of tumor cells expressing resistance genes or phenotypes. Motivated by the theory of mutation-selection in adaptive evolution, we propose a model based on a continuous variable that represents the expression level of a resistance gene (or genes, yielding a phenotype) influencing in healthy and tumor cells birth/death rates, effects of chemotherapies (both cytotoxic and cytostatic) and mutations. We extend previous work by demonstrating how qualitatively different actions of chemotherapeutic and cytostatic treatments may induce different levels of resistance. The mathematical interest of our study is in the formalism of constrained Hamilton-Jacobi equations in the framework of viscosity solutions. We derive the long-term temporal dynamics of the fittest traits in the regime of small mutations. In the context of adaptive cancer management, we also analyse whether an optimal drug level is better than the maximal tolerated dose

Evaluation of the Beam Coupling Impedance of New Beam Screen Designs for the LHC Injection Kicker Magnets

During the 2011 run of the LHC there was a significant measured temperature increase in the LHC Injection Kicker Magnets (MKI) during operation with 50ns bunch spacing. This was due to increased beam-induced heating of the magnet due to beam impedance. Due to concerns about future heating with the increased total intensity to nominal and ultimate luminosities a review of the impedance reduction techniques within the magnet was required. A number of new beam screen designs are proposed and their impedance evaluated. Heating estimates are also given with a particular attention paid to future intensity upgrades to ultimate parameters

Computing Double Precision Euclidean Distances using GPU Tensor Cores

Tensor cores (TCs) are a type of Application-Specific Integrated Circuit (ASIC) and are a recent addition to Graphics Processing Unit (GPU) architectures. As such, TCs are purposefully designed to greatly improve the performance of Matrix Multiply-Accumulate (MMA) operations. While TCs are heavily studied for machine learning and closely related fields, where their high efficiency is undeniable, MMA operations are not unique to these fields. More generally, any computation that can be expressed as MMA operations can leverage TCs, and potentially benefit from their higher computational throughput compared to other general-purpose cores, such as CUDA cores on Nvidia GPUs. In this paper, we propose the first double precision (FP64) Euclidean distance calculation algorithm, which is expressed as MMA operations to leverage TCs on Nvidia GPUs, rather than the more commonly used CUDA cores. To show that the Euclidean distance can be accelerated in a real-world application, we evaluate our proposed TC algorithm on the distance similarity self-join problem, as the most computationally intensive part of the algorithm consists of computing distances in a multi-dimensional space. We find that the performance gain from using the tensor core algorithm over the CUDA core algorithm depends weakly on the dataset size and distribution, but is strongly dependent on data dimensionality. Overall, TCs are a compelling alternative to CUDA cores, particularly when the data dimensionality is low ($\leq{4}$), as we achieve an average speedup of $1.28\times$ and up to $2.23\times$ against a state-of-the-art GPU distance similarity self-join algorithm. Furthermore, because this paper is among the first to explore the use of TCs for FP64 general-purpose computation, future research is promising.Comment: Accepted for publicatio

Life cycle analysis for the cultivation and combustion of miscanthus for biofuel compared with natural gas

As negative environmental and economic impacts of fossil fuels have escalated, so has the importance of renewable bioenergy crops whose feedstocks are noncompetitive with food supplies. Compared with fossil fuels, use of lignocellulosic feedstocks offers potential for greenhouse gas reduction and highly positive net energy returns because of low input demand and high yields per unit of land area, thus making them advantageous for the emerging biofuel industry. The aim of this study was to simulate environmental impacts of producing a biofuel grass for combustion use based on the inventory of inputs and their effects on eutrophication of surface waters; acidification of land and water; photochemical ozone-creation potential (i.e. smog); global atmospheric warming; and nonrenewable resource depletion (mainly fossil fuels). Hybrid miscanthus (Miscanthus x giganteus, or giant miscanthus), a perennial C4 grass originating from East Asia, was compared with natural gas by using a life-cycle analysis model for biomass production in France. The analysis showed a trade-off between natural gas and miscanthus. The latter had a lower global-warming potential and consumed less primary nonrenewable energy but produced more emissions that promote acidification and eutrophication than did natural gas

The Automated Aircraft Rework System (AARS): A system integration approach

The Mercer Engineering Research Center (MERC), under contract to the United States Air Force (USAF) since 1989, has been actively involved in providing the Warner Robins Air Logistics Center (WR-ALC) with a robotic workcell designed to perform rework automated defastening and hole location/transfer operations on F-15 wings. This paper describes the activities required to develop and implement this workcell, known as the Automated Aircraft Rework System (AARS). AARS is scheduled to be completely installed and in operation at WR-ALC by September 1994