Measuring Skill in More-Person Games with Applications to Poker

In several jurisdictions, commercially exploiting a game of chance (rather than skill) is subject to a licensing regime. It is obvious that roulette is a game of chance and chess a game of skill, but the law does not provide a precise description of where the boundary between the two classes is drawn. We build upon the framework of Borm and Van der Genugten (2001) and Dreef et al. (2004) and propose a modification of the skill concept for more-person games. We apply our new skill measure to a simplified version of poker called Straight Poker and conclude that this game should be classified as a game of skill.games of chance;games of skill;poker

Importance subsampling for power system planning under multi-year demand and weather uncertainty

This paper introduces a generalised version of importance subsampling for time series reduction/aggregation in optimisation-based power system planning models. Recent studies indicate that reliably determining optimal electricity (investment) strategy under climate variability requires the consideration of multiple years of demand and weather data. However, solving planning models over long simulation lengths is typically computationally unfeasible, and established time series reduction approaches induce significant errors. The importance subsampling method reliably estimates long-term planning model outputs at greatly reduced computational cost, allowing the consideration of multi-decadal samples. The key innovation is a systematic identification and preservation of relevant extreme events in modeling subsamples. Simulation studies on generation and transmission expansion planning models illustrate the method’s enhanced performance over established "representative days" clustering approaches. The models, data and sample code are made available as open-source software

Importance subsampling: improving power system planning under climate-based uncertainty

Recent studies indicate that the effects of inter-annual climate-based variability in power system planning are significant and that long samples of demand & weather data (spanning multiple decades) should be considered. At the same time, modelling renewable generation such as solar and wind requires high temporal resolution to capture fluctuations in output levels. In many realistic power system models, using long samples at high temporal resolution is computationally unfeasible. This paper introduces a novel subsampling approach, referred to as importance subsampling, allowing the use of multiple decades of demand & weather data in power system planning models at reduced computational cost. The methodology can be applied in a wide class of optimisation based power system simulations. A test case is performed on a model of the United Kingdom created using the open-source modelling framework Calliope and 36 years of hourly demand and wind data. Standard data reduction approaches such as using individual years or clustering into representative days lead to significant errors in estimates of optimal system design. Furthermore, the resultant power systems lead to supply capacity shortages, raising questions of generation capacity adequacy. In contrast, importance subsampling leads to accurate estimates of optimal system design at greatly reduced computational cost, with resultant power systems able to meet demand across all 36 years of demand & weather scenarios

Molecular dynamics study of vesicle deformation mechanisms

Lipid bilayer membranes are known to form various structures like large sheets or vesicles. When both bilayer leaflets have equal composition, membranes preferentially form flat sheets or spherical vesicles. However, vesicles with a wide variety of shapes, including ellipsoids, discoids, pear-shaped, cup-shaped and budded vesicles, have been shown experimentally. Such shapes were predicted theoretically from energy minimization of continuous sheets as well. We show, using coarse-grained molecular dynamics simulations, how relatively small asymmetry in composition between the two leaflets may result in spontaneously curved bilayers and all these vesicle shapes. Three types of bilayer asymmetry are considered. Firstly, the situation where the headgroup-solvent interaction and thus the lipid packing alters due to a change in pH or ion-concentration of the vesicle interior/exterior (A). Secondly, where asymmetry arises from phase separation of two lipid types (B). And thirdly, where asymmetry arises from growth of one of the bilayer leaflets by incorporation of additional lipids from the solvent (C)

Directional interactions in semiflexible single-chain polymer folding

Precise control over folded conformations of synthetic polymers is highly desirable in the development of functional nanomaterials for diverse applications. Introducing monomers capable of strong intramolecular hydrogen bonding is a promising route to achieve this control. In the present work we report the use of Wang–Landau Monte Carlo simulations of coarse-grained copolymers to explore the design parameters of these systems on their pathway to collapse. The highly directional nature of hydrogen-bonded supramolecular interactions is modelled by a directional non-bonded potential while a harmonic bending potential is used to take into account the flexibility of the polymer chain, thus making it possible to look at the interplay of both factors. The introduction of directional interactions in the copolymer chain leads to a sharper coil-globule collapse when compared to homopolymers composed of isotropic interacting beads only. Simultaneously, some of the stiffness-dependent structural properties become exacerbated when directional beads are present. Finally, from the heat capacity profiles for the different chain stiffness values we are able to distinguish the prevalence of the collapse of the backbone for highly flexible chains, while as chain stiffness increases folding of the co-polymer due to the directional interactions becomes the dominant feature

Coarse Grained Molecular Dynamics Simulations of the Fusion of Vesicles Incorporating Water Channels

As the dynamics of the cell membrane and the working mechanisms of proteins cannot be readily asserted at a molecular level, many different hypotheses exist that try to predict and explain these processes, for instance vesicle fusion. Therefore, we use coarse grained molecular dynamics simulations to elucidate the fusion mechanism of vesicles. The implementation of this method with hydrophilic and hydrophobic particles is known for its valid representation of bilayers. With a minimalistic approach, using only 3 atom types, 12 atoms per two-tailed phospholipids and incorporating only a bond potential and Lennard-Jones potential, phospholipid bilayers and vesicles can be simulated exhibiting authentic dynamics. We have simulated the spontaneous full fusion of both tiny (6 nm diameter) and larger (13 nm diameter) vesicles. We showed that, without applying constraints to the vesicles, the initial contact between two fusing vesicles, the stalk, is initiated by a bridging lipid tail that extends from the membrane spontaneously. Subsequently it is observed that the evolution of the stalk can proceed via two pathways, anisotropic and radial expansion, which is in accordance with literature. Contrary to the spherical vesicles of in vitro experiments, the fused vesicles remain tubular since the internal volume of these vesicles is too small compared to their membrane area. While the lipid bilayer has some permeability for water, it is not high enough to allow for the large flux required to equilibrate the vesicle content in the time accessible to our simulations. To increase the membrane permeability, we incorporate proteinaceous water channels, by applying the coarse grained technique to aquaporin. Even though incorporating water channels in the vesicles does significantly increase water permeability, the vesicles do not become spherical. Presumably the lipids have to be redistributed as well

Dual-mode humidity detection using a lanthanide-based metal-organic framework: towards multifunctional humidity sensors

Combined photoluminescence and impedance spectroscopy studies show that a europium-based metal–organic framework behaves as a highly effective and reliable humidity sensor, enabling dual-mode humidity detection

Reducing climate risk in energy system planning: a posteriori time series aggregation for models with storage

The growth in variable renewables such as solar and wind is increasing the impact of climate uncertainty in energy system planning. Addressing this ideally requires high-resolution time series spanning at least a few decades. However, solving capacity expansion planning models across such datasets often requires too much computing time or memory. To reduce computational cost, users often employ time series aggregation to compress demand and weather time series into a smaller number of time steps. Methods are usually a priori, employing information about the input time series only. Recent studies highlight the limitations of this approach, since reducing statistical error metrics on input time series does not in general lead to more accurate model outputs. Furthermore, many aggregation schemes are unsuitable for models with storage since they distort chronology. In this paper, we introduce a posteriori time series aggregation schemes that preserve chronology and hence allow modelling of storage technologies. Our methods adapt to the underlying energy system model; aggregation may differ in systems with different technologies or topologies even with the same time series inputs. They do this by using operational variables (generation, transmission and storage patterns) in addition to time series inputs when aggregating. We investigate a number of approaches. We find that a posteriori methods can perform better than a priori ones, primarily through a systematic identification and preservation of relevant extreme events. We hope that these tools render long demand and weather time series more manageable in capacity expansion planning studies. We make our models, data, and code publicly available