Impact of pressure dissipation on fluid injection into layered aquifers

Carbon dioxide (CO2) capture and subsurface storage is one method for reducing anthropogenic CO2 emissions to mitigate climate change. It is well known that large-scale fluid injection into the subsurface leads to a buildup in pressure that gradually spreads and dissipates through lateral and vertical migration of water. This dissipation can have an important feedback on the shape of the CO2 plume during injection, and the impact of vertical pressure dissipation, in particular, remains poorly understood. Here, we investigate the impact of lateral and vertical pressure dissipation on the injection of CO2 into a layered aquifer system. We develop a compressible, two-phase model that couples pressure dissipation to the propagation of a CO2 gravity current. We show that our vertically integrated, sharp-interface model is capable of efficiently and accurately capturing water migration in a layered aquifer system with an arbitrary number of aquifers. We identify two limiting cases --- `no leakage' and `strong leakage' --- in which we derive analytical expressions for the water pressure field for the corresponding single-phase injection problem. We demonstrate that pressure dissipation acts to suppress the formation of an advancing CO2 tongue during injection, resulting in a plume with a reduced lateral extent. The properties of the seals and the number of aquifers determine the strength of pressure dissipation and subsequent coupling with the CO2 plume. The impact of pressure dissipation on the shape of the CO2 plume is likely to be important for storage efficiency and security

A Hierarchical Bayesian Trust Model based on Reputation and Group Behaviour

In many systems, agents must rely on their peers to achieve their goals. However, when trusted to perform an action, an agent may betray that trust by not behaving as required. Agents must therefore estimate the behaviour of their peers, so that they may identify reliable interaction partners. To this end, we present a Bayesian trust model (HABIT) for assessing trust based on direct experience and (potentially unreliable) reputation. Although existing approaches claim to achieve this, most rely on heuristics with little theoretical foundation. In contrast, HABIT is based on principled statistical techniques; can be used with any representation of behaviour; and can assess trust based on observed similarities between groups of agents. In this paper, we describe the theoretical aspects of the model and present experimental results in which HABIT was shown to be up to twice as accurate at predicting trustee performance as an existing state-of-the-art trust model

A Study on the Parallelization of Terrain-Covering Ant Robots Simulations

Agent-based simulation is used as a tool for supporting (time-critical) decision making in differentiated contexts. Hence, techniques for speeding up the execution of agent-based models, such as Parallel Discrete Event Simulation (PDES), are of great relevance/benefit. On the other hand, parallelism entails that the final output provided by the simulator should closely match the one provided by a traditional sequential run. This is not obvious given that, for performance and efficiency reasons, parallel simulation engines do not allow the evaluation of global predicates on the simulation model evolution with arbitrary time-granularity along the simulation time-Axis. In this article we present a study on the effects of parallelization of agent-based simulations, focusing on complementary aspects such as performance and reliability of the provided simulation output. We target Terrain Covering Ant Robots (TCAR) simulations, which are useful in rescue scenarios to determine how many agents (i.e., robots) should be used to completely explore a certain terrain for possible victims within a given time. © 2014 Springer-Verlag Berlin Heidelberg

Hybridization gap versus hidden order gap in URu2_2Si2_2 as revealed by optical spectroscopy

We present the in-plane optical reflectance measurement on single crystals of URu$_2$As$_2$. The study revealed a strong temperature-dependent spectral evolution. Above 50 K, the low frequency optical conductivity is rather flat without a clear Drude-like response, indicating a very short transport life time of the free carriers. Well below the coherence temperature, there appears an abrupt spectral weight suppression below 400 cm$^{-1}$, yielding evidence for the formation of a hybridization energy gap arising from the mixing of the conduction electron and narrow f-electron bands. A small part of the suppressed spectral weight was transferred to the low frequency side, leading to a narrow Drude component, while the majority of the suppressed spectral weight was transferred to the high frequency side centered near 4000 cm$^{-1}$. Below the hidden order temperature, another very prominent energy gap structure was observed, which leads to the removal of a large part of the Drude component and a sharp reduction of the carrier scattering rate. The study revealed that the hybridization gap and the hidden orger gap are distinctly different: they occur at different energy scales and exhibit completely different spectral characteristics.Comment: 5 page

Muon spin rotation/relaxation measurements of the non-centrosymmetric superconductor Mg10Ir19B16

We have searched for time-reversal symmetry breaking fields in the non-centrosymmetric superconductor Mg$_{10}$Ir$_{19}$B$_{16}$ via muon spin relaxation in zero applied field, and we measured the temperature dependence of the superfluid density by muon spin rotation in transverse field to investigate the superconducting pairing symmetry in two polycrystalline samples of signficantly different purities. In the high purity sample, we detected no time-reversal symmetry breaking fields greater than 0.05 G. The superfluid density was also found to be exponentially-flat as T$\to$0, and so can be fit to a single-gap BCS model. In contrast, the lower purity sample showed an increase in the zero-field $\mu$SR relaxation rate below T$_c$ corresponding to a characteristic field strength of 0.6 G. While the temperature-dependence of the superfluid density was also found to be consistent with a single-gap BCS model, the magnitude as T$\to$0 was found to be much lower for a given applied field than in the case of the high purity sample. These findings suggest that the dominant pairing symmetry in high quality Mg$_{10}$Ir$_{19}$B$_{16}$ samples corresponds to the spin-singlet channel, while sample quality drastically affects the superconducting properties of this system.Comment: 6 pages, 5 figures, revised version resubmitted to PR

The tarantula toxin GxTx detains K+ channel gating charges in their resting conformation.

Allosteric ligands modulate protein activity by altering the energy landscape of conformational space in ligand-protein complexes. Here we investigate how ligand binding to a K+ channel's voltage sensor allosterically modulates opening of its K+-conductive pore. The tarantula venom peptide guangxitoxin-1E (GxTx) binds to the voltage sensors of the rat voltage-gated K+ (Kv) channel Kv2.1 and acts as a partial inverse agonist. When bound to GxTx, Kv2.1 activates more slowly, deactivates more rapidly, and requires more positive voltage to reach the same K+-conductance as the unbound channel. Further, activation kinetics are more sigmoidal, indicating that multiple conformational changes coupled to opening are modulated. Single-channel current amplitudes reveal that each channel opens to full conductance when GxTx is bound. Inhibition of Kv2.1 channels by GxTx results from decreased open probability due to increased occurrence of long-lived closed states; the time constant of the final pore opening step itself is not impacted by GxTx. When intracellular potential is less than 0 mV, GxTx traps the gating charges on Kv2.1's voltage sensors in their most intracellular position. Gating charges translocate at positive voltages, however, indicating that GxTx stabilizes the most intracellular conformation of the voltage sensors (their resting conformation). Kinetic modeling suggests a modulatory mechanism: GxTx reduces the probability of voltage sensors activating, giving the pore opening step less frequent opportunities to occur. This mechanism results in K+-conductance activation kinetics that are voltage-dependent, even if pore opening (the rate-limiting step) has no inherent voltage dependence. We conclude that GxTx stabilizes voltage sensors in a resting conformation, and inhibits K+ currents by limiting opportunities for the channel pore to open, but has little, if any, direct effect on the microscopic kinetics of pore opening. The impact of GxTx on channel gating suggests that Kv2.1's pore opening step does not involve movement of its voltage sensors