University of Strathclyde at TREC HARD

The motivation behind the University of Strathclyde's approach to this years HARD track was inspired from previous experiences by other participants, in particular research by [1], [3] and [4]. A running theme throughout these papers was the underlying hypothesis that a user's familiarity in a topic (i.e. their previous experience searching a subject), will form the basis for what type or style of document they will perceive as relevant. In other words, the user's context with regards to their previous search experience will determine what type of document(s) they wish to retrieve

Enhancement of surface activity in CO oxidation on Pt(110) through spatiotemporal laser actuation

We explore the effect of spatiotemporally varying substrate temperature profiles on the dynamics and resulting reaction rate enhancement for the catalytic oxidation of CO on Pt(110). The catalytic surface is "addressed" by a focused laser beam whose motion is computer-controlled. The averaged reaction rate is observed to undergo a characteristic maximum as a function of the speed of this moving laser spot. Experiments as well as modelling are used to explore and rationalize the existence of such an optimal laser speed.Comment: 9 pages, 12 figures, submitted to Phys. Rev.

Evaluating implicit feedback models using searcher simulations

In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simulations. Since these algorithms select additional terms for query modification based on inferences made from searcher interaction, not on relevance information searchers explicitly provide (as in traditional RF), we refer to them as implicit feedback models. We introduce six different models that base their decisions on the interactions of searchers and use different approaches to rank query modification terms. The aim of this article is to determine which of these models should be used to assist searchers in the systems we develop. To evaluate these models we used searcher simulations that afforded us more control over the experimental conditions than experiments with human subjects and allowed complex interaction to be modeled without the need for costly human experimentation. The simulation-based evaluation methodology measures how well the models learn the distribution of terms across relevant documents (i.e., learn what information is relevant) and how well they improve search effectiveness (i.e., create effective search queries). Our findings show that an implicit feedback model based on Jeffrey's rule of conditioning outperformed other models under investigation

Understanding Shale Gas: Recent Progress and Remaining Challenges

Because of a number of technological advancements, unconventional hydrocarbons, and in particular shale gas, have transformed the US economy. Much is being learned, as demonstrated by the reduced cost of extracting shale gas in the US over the past five years. However, a number of challenges still need to be addressed. Many of these challenges represent grand scientific and technological tasks, overcoming which will have a number of positive impacts, ranging from the reduction of the environmental footprint of shale gas production to improvements and leaps forward in diverse sectors, including chemical manufacturing and catalytic transformations. This review addresses recent advancements in computational and experimental approaches, which led to improved understanding of, in particular, structure and transport of fluids, including hydrocarbons, electrolytes, water, and CO2 in heterogeneous subsurface rocks such as those typically found in shale formations. The narrative is concluded with a suggestion of a few research directions that, by synergistically combining computational and experimental advances, could allow us to overcome some of the hurdles that currently hinder the production of hydrocarbons from shale formations

Personalisation and recommender systems in digital libraries

Widespread use of the Internet has resulted in digital libraries that are increasingly used by diverse communities of users for diverse purposes and in which sharing and collaboration have become important social elements. As such libraries become commonplace, as their contents and services become more varied, and as their patrons become more experienced with computer technology, users will expect more sophisticated services from these libraries. A simple search function, normally an integral part of any digital library, increasingly leads to user frustration as user needs become more complex and as the volume of managed information increases. Proactive digital libraries, where the library evolves from being passive and untailored, are seen as offering great potential for addressing and overcoming these issues and include techniques such as personalisation and recommender systems. In this paper, following on from the DELOS/NSF Working Group on Personalisation and Recommender Systems for Digital Libraries, which met and reported during 2003, we present some background material on the scope of personalisation and recommender systems in digital libraries. We then outline the working group’s vision for the evolution of digital libraries and the role that personalisation and recommender systems will play, and we present a series of research challenges and specific recommendations and research priorities for the field

Experimental and Simulation Study of Adsorption in Postcombustion Conditions Using a Microporous Biochar. 1. CO2 and N2 Adsorption

The influence of N2 on CO2 adsorption was evaluated using a microporous biochar with a narrow pore size distribution. The adsorption isotherms of pure CO2 and N2 were measured at 0, 30, 50, and 70 °C up to 120 kPa and fitted to the Toth adsorption model. Dynamic breakthrough experiments were carried out in a fixed-bed adsorption unit using binary mixtures with compositions representative of different postcombustion streams (8–30% CO2) from ambient temperature to 70 °C. Dynamic adsorption experiments were simulated to validate the mathematical model of the adsorption process, as a necessary step for its later use for process design. The Ideal Adsorption Solution (IAS) theory, based on the pure component adsorption models, was used to account for competitive adsorption with satisfactory results. The information gathered in the present work will be used to extend the validity of the model to the adsorption of postcombustion streams containing H2O in part 2.Work was carried out with financial support from the HiPerCap Project of the European Union 7th Framework Programme FP7 (2007-2013; Grant Agreement number: 60855). M.G.P. acknowledges funding from the CSIC (JAE-Doc program cofinanced by the European Social Fund). N.Q. acknowledges funding from the Government of the Principado de Asturias (Severo Ochoa Program). The authors also appreciate the support from the technical consultants of AspenTechnology Inc., M.M. and E.L.Peer reviewe

Large Scale Modular Quantum Computer Architecture with Atomic Memory and Photonic Interconnects

The practical construction of scalable quantum computer hardware capable of executing non-trivial quantum algorithms will require the juxtaposition of different types of quantum systems. We analyze a modular ion trap quantum computer architecture with a hierarchy of interactions that can scale to very large numbers of qubits. Local entangling quantum gates between qubit memories within a single register are accomplished using natural interactions between the qubits, and entanglement between separate registers is completed via a probabilistic photonic interface between qubits in different registers, even over large distances. We show that this architecture can be made fault-tolerant, and demonstrate its viability for fault-tolerant execution of modest size quantum circuits