On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables

Influence diagrams are intuitive and concise representations of structured decision problems. When the problem is non-Markovian, an optimal strategy can be exponentially large in the size of the diagram. We can avoid the inherent intractability by constraining the size of admissible strategies, giving rise to limited memory influence diagrams. A valuable question is then how small do strategies need to be to enable efficient optimal planning. Arguably, the smallest strategies one can conceive simply prescribe an action for each time step, without considering past decisions or observations. Previous work has shown that finding such optimal strategies even for polytree-shaped diagrams with ternary variables and a single value node is NP-hard, but the case of binary variables was left open. In this paper we address such a case, by first noting that optimal strategies can be obtained in polynomial time for polytree-shaped diagrams with binary variables and a single value node. We then show that the same problem is NP-hard if the diagram has multiple value nodes. These two results close the fixed-parameter complexity analysis of optimal strategy selection in influence diagrams parametrized by the shape of the diagram, the number of value nodes and the maximum variable cardinality.

Solving Limited Memory Influence Diagrams

We present a new algorithm for exactly solving decision making problems represented as influence diagrams. We do not require the usual assumptions of no forgetting and regularity; this allows us to solve problems with simultaneous decisions and limited information. The algorithm is empirically shown to outperform a state-of-the-art algorithm on randomly generated problems of up to 150 variables and 10^64 solutions. We show that these problems are NP-hard even if the underlying graph structure of the problem has low treewidth and the variables take on a bounded number of states, and that they admit no provably good approximation if variables can take on an arbitrary number of states.

Solving Limited Memory Influence Diagrams

We present a new algorithm for exactly solving decision making problems represented as influence diagrams. We do not require the usual assumptions of no forgetting and regularity; this allows us to solve problems with simultaneous decisions and limited information. The algorithm is empirically shown to outperform a state-of-the-art algorithm on randomly generated problems of up to 150 variables and 10^64 solutions. We show that the problem is NP-hard even if the underlying graph structure of the problem has small treewidth and the variables take on a bounded number of states, but that a fully polynomial time approximation scheme exists for these cases. Moreover, we show that the bound on the number of states is a necessary condition for any efficient approximation scheme.

Patterning and switching of nano-size ferroelectric memory cells

A "top-down" approach using a-beam lithography and a "bottom-up" one using self-assembly methods were used to fabricate ferroelelectric Pb(Zr,Ti)O-3, SrBi2Ta2O9 and BaTiO3 nanostructures with lateral sizes in the range of 30 nm to 100 nm. Switching of single sub-100 nm cells was achieved and piezoelectric hysteresis loops were recorded using a scanning force microscope working in piezoresponse mode. The piezoelectricity and its hysteresis acquired for 100 nm PZT cells demonstrate that a further decrease in lateral size under 100 nm appears to be possible and that the size effects are not fundamentally limiting on increase density of non-volatile ferroelectric memories in the Gbit range.

Film, History and Memory

Film, History and Memory examines the relationship between film and history, exploring the multiplicity of ways in which films depict, contest, reinforce or subvert historical understanding. This volume broadens the focus from 'history', the study of past events, to 'memory', the processes – individual, generational, collective or state-driven – by which meanings are attached to the past. This approach acknowledges how the significance of the historical film lies less in its empirical qualities than in its powerful capacity to influence public thinking and discourses about the past, whether by shaping collective memory, popular history and social memory, or by retrieving suppressed or marginalized histories. This study aims to contribute to the growing literature on history and film through the breadth of its approach, both in disciplinary and geographical terms. Contributors are drawn not only from the discipline of history but also film studies, film practice, art history, languages and literature, and cultural studies.

Energy-Efficient In-Memory Data Stores on Hybrid Memory Hierarchies

Increasingly large amounts of data are stored in main memory of data center servers. However, DRAM-based memory is an important consumer of energy and is unlikely to scale in the future. Various byte-addressable non-volatile memory (NVM) technologies promise high density and near-zero static energy, however they suffer from increased latency and increased dynamic energy consumption.

This paper proposes to leverage a hybrid memory architecture, consisting of both DRAM and NVM, by novel, application-level data management policies that decide to place data on DRAM vs. NVM. We analyze modern column-oriented and key-value data stores and demonstrate the feasibility of application-level data management. Cycle-accurate simulation confirms that our methodology reduces the energy with least performance degradation as compared to the current state-of-the-art hardware or OS approaches. Moreover, we utilize our techniques to apportion DRAM and NVM memory sizes for these workloads.

Epigenetic Changes in Endothelial Progenitors as a Possible Cellular Basis for Glycemic Memory in Diabetic Vascular Complications

The vascular complications of diabetes significantly impact the quality of life and mortality in diabetic patients. Extensive evidence from various human clinical trials has clearly established that a period of poor glycemic control early in the disease process carries negative consequences, such as an increase in the development and progression of vascular complications that becomes evident many years later. Importantly, intensive glycemic control established later in the disease process cannot reverse or slow down the onset or progression of diabetic vasculopathy. This has been named the glycemic memory phenomenon. Scientists have successfully modelled glycemic memory using various in vitro and in vivo systems. This review emphasizes that oxidative stress and accumulation of advanced glycation end products are key factors driving glycemic memory in endothelial cells. Furthermore, various epigenetic marks have been proposed to closely associate with vascular glycemic memory. In addition, we comment on the importance of endothelial progenitors and their role as endogenous vasoreparative cells that are negatively impacted by the diabetic milieu and may constitute a "carrier" of glycemic memory. Considering the potential of endothelial progenitor-based cytotherapies, future studies on their glycemic memory are warranted to develop epigenetics-based therapeutics targeting diabetic vascular complications.

Who Tells What to Whom and How: The Prisons Memory Archive

This essay will consider the recording and exhibition of stories from a conflicted past in a contested present; who gets to tell what stories to whom and under what conditions? I will use the case study of the online Prisons Memory Archive (PMA) – a collection of filmed interviews at the locations of the Maze and Long Kesh Prison, which held male prisoners, and Armagh Gaol, which held female prisoners. Both operated during the period of political violence during the last third of the 20th century in the North of Ireland (www.prisonsmemoryarchive.com). As Director of the PMA, I was involved from research through production to exhibition.

Potential applications of shape memory alloys in seismic retrofitting of exterior RC beam-column joints

Shape memory alloys (SMAs) have the ability to undergo large deformations with minimum residual strain and also the extraordinary ability to undergo reversible hysteretic shape change known as the shape memory effect. The shape memory effect of these alloys can be utilised to develop a convenient way of actively confine concrete sections to improve their shear strength, flexural ductility and ultimate strain. Most of the previous work on active confinement of concrete using SMA has been carried out on circular sections. In this study retrofitting strategies for active confinement of non-circular sections have been proposed. The proposed schemes presented in this paper are conceived with an aim to seismically retrofit beam-column joints in non-seismically designed reinforced concrete buildings. SMAs are complex materials and their material behaviour depends on number of parameters. Depending upon the alloying elements, SMAs exhibit different behaviour in different conditions and are highly sensitive to variation in temperature, phase in which it is used, loading pattern, strain rate and pre-strain conditions. Therefore, a detailed discussion on the behaviour of SMAs under different thermo-mechanical conditions is presented first.