On the complexity of the water-gas shift reaction mechanism over a Pt/CeO2 catalyst: Effect of the temperature on the reactivity of formate surface species studied by operando DRIFT during isotopic transient at chemical steady-state

The present report investigates the role of formate species as potential reaction intermediates for the WGS reaction (CO + H2O -> CO2 + H-2) over a Pt-CeO2 catalyst. A combination of operando techniques, i.e., in situ diffuse reflectance FT-IR (DRIFT) spectroscopy and mass spectrometry (MS) during steady-state isotopic transient kinetic analysis (SSITKA), was used to relate the exchange of the reaction product CO2 to that of surface formate species. The data presented here suggest that a switchover from a non-formate to a formate-based mechanism could take place over a very narrow temperature range (as low as 60 K) over our Pt-CeO2 catalyst. This observation clearly stresses the need to avoid extrapolating conclusions to the case of results obtained under even slightly different experimental conditions. The occurrence of a low-temperature mechanism, possibly redox or Mars van Krevelen-like, that deactivates above 473 K because of ceria over-reduction is suggested as a possible explanation for the switchover, similarly to the case of the CO-NO reaction over Cu, I'd and Rh-CeZrOx (see Kaspar and co-workers [1-3]). (c) 2006 Elsevier B.V. All rights reserved.

‘The ‘Complexity of Imprisonment: The Northern Ireland Experience'

This article will examine the thesis that Northern Ireland experiences a relatively low level of crime. It will explore the possible reasons why crime in the North has not witnessed a dramatic increase. In light of this, the article will highlight the difficulties surrounding the current prison system and illustrate that once again Northern Ireland is experiencing a very different criminal justice system in comparison to Great Britain. Although the prisons are now being used predominately to deal with “ordinary’ crime”, they are still part of the political process.

ON THE MOLECULAR COMPLEXITY OF THE HOT CORES IN ORION-A - GRAIN SURFACE-CHEMISTRY AS THE LAST REFUGE OF THE SCOUNDREL

We have modeled the gas phase chemistry of warm molecular material around protostars that is seeded with evaporating grain mantles. We show that the release of simple molecules into the gas drives ion-molecule and neutral chemistries which can account for many of the complex 0-bearing and N-bearing molecules observed in hot cores. Initial grain mantle components and secondary product molecules are identified, and the observational consequences are discussed.

Holocene tephras highlight complexity of volcanic signals in Greenland ice cores

Acidity peaks in Greenland ice cores have been used as critical reference horizons for synchronizing ice core records, aiding the construction of a single Greenland Ice Core Chronology (GICC05) for the Holocene. Guided by GICC05, we examined sub-sections of three Greenland cores in the search for tephra from specific eruptions that might facilitate the linkage of ice core records, the dating of prehistoric tephras and the understanding of the eruptions. Here we report the identification of 14 horizons with tephra particles, including 11 that have not previously been reported from the North Atlantic region and that have the potential to be valuable isochrons. The positions of tephras whose major element data are consistent with ash from the Katmai AD 1912 and Öraefajökull AD 1362 eruptions confirm the annually resolved ice core chronology for the last 700 years. We provide a more refined date for the so-called “AD860B” tephra, a widespread isochron found across NW Europe, and present new evidence relating to the 17th century BC Thera/Aniakchak debate that shows N. American eruptions likely contributed to the acid signals at this time. Our results emphasize the variable spatial and temporal distributions of volcanic products in Greenland ice that call for a more cautious approach in the attribution of acid signals to specific eruptive events.

The Computational Complexity of Dominance and Consistency in CP-Nets

We investigate the computational complexity of testing dominance and consistency in CP-nets. Previously, the complexity of dominance has been determined for restricted classes in which the dependency graph of the CP-net is acyclic. However, there are preferences of interest that define cyclic dependency graphs; these are modeled with general CP-nets. In our main results, we show here that both dominance and consistency for general CP-nets are PSPACE-complete. We then consider the concept of strong dominance, dominance equivalence and dominance incomparability, and several notions of optimality, and identify the complexity of the corresponding decision problems. The reductions used in the proofs are from STRIPS planning, and thus reinforce the earlier established connections between both areas.

On the Complexity of Universal Leader Election

Electing a leader is a fundamental task in distributed computing. In its implicit version, only the leader must know who is the elected leader. This paper focuses on studying the message and time complexity of randomized implicit leader election in synchronous distributed networks. Surprisingly, the most "obvious" complexity bounds have not been proven for randomized algorithms. The "obvious" lower bounds of O(m) messages (m is the number of edges in the network) and O(D) time (D is the network diameter) are non-trivial to show for randomized (Monte Carlo) algorithms. (Recent results that show that even O(n) (n is the number of nodes in the network) is not a lower bound on the messages in complete networks, make the above bounds somewhat less obvious). To the best of our knowledge, these basic lower bounds have not been established even for deterministic algorithms (except for the limited case of comparison algorithms, where it was also required that some nodes may not wake up spontaneously, and that D and n were not known).

We establish these fundamental lower bounds in this paper for the general case, even for randomized Monte Carlo algorithms. Our lower bounds are universal in the sense that they hold for all universal algorithms (such algorithms should work for all graphs), apply to every D, m, and n, and hold even if D, m, and n are known, all the nodes wake up simultaneously, and the algorithms can make anyuse of node's identities. To show that these bounds are tight, we present an O(m) messages algorithm. An O(D) time algorithm is known. A slight adaptation of our lower bound technique gives rise to an O(m) message lower bound for randomized broadcast algorithms.

An interesting fundamental problem is whether both upper bounds (messages and time) can be reached simultaneously in the randomized setting for all graphs. (The answer is known to be negative in the deterministic setting). We answer this problem partially by presenting a randomized algorithm that matches both complexities in some cases. This already separates (for some cases) randomized algorithms from deterministic ones. As first steps towards the general case, we present several universal leader election algorithms with bounds that trade-off messages versus time. We view our results as a step towards understanding the complexity of universal leader election in distributed networks.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Complexity of concern: Social acceptance of wind energy and the inevitability of dissensus

This presentation will explore the  role that social acceptance of onshore wind can play in understanding and progressing the low carbon transition in Europe. Although this is commonly perceived as arising simply from the overall level of renewable energy generated (and ‘dirty’ energy displaced), its significance goes well beyond this as it helps us understand some of the key issues facing the electricity sector as a social-technical system.  As such it is not only a matter of delivering the necessary infrastructure, but requires the long term mediation of complex multi-governmental arrangements involving a very wide range of actors. The interests of these actors engage hugely different timescales, geographic scales of concern and rationalities that make the arena of social acceptance a cauldron of complexity, mediating between overlapping and incompatible concerns. The presentation will briefly review the nature of some of these relationships and discuss what this means for how we conceive and act on the social acceptance of wind, and what this means for the long term low carbon transition

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.