Extending Nearly-Linear Models

Nearly-Linear Models are a family of neighbourhood models, obtaining lower/upper probabilities from a given probability by a linear affine transformation with barriers. They include a number of known models as special cases, among them the Pari-Mutuel Model, the \u3b5-contamination model, the Total Variation Model and the vacuous lower/upper probabilities. We classified Nearly-Linear models, investigating their consistency properties, in previous work. Here we focus on how to extend those Nearly-Linear Models that are coherent or at least avoid sure loss. We derive formulae for their natural extensions, interpret a specific model as a natural extension itself of a certain class of lower probabilities, and supply a risk measurement interpretation for one of the natural extensions we compute

Modelling the transitional boundary layer

Recent developments in the modelling of the transition zone in the boundary layer are reviewed (the zone being defined as extending from the station where intermittency begins to depart from zero to that where it is nearly unity). The value of using a new non-dimensional spot formation rate parameter, and the importance of allowing for so-called subtransitions within the transition zone, are both stressed. Models do reasonably well in constant pressure 2-dimensional flows, but in the presence of strong pressure gradients further improvements are needed. The linear combination approach works surprisingly well in most cases, but would not be so successful in situations where a purely laminar boundary layer would separate but a transitional one would not. Intermittency-weighted eddy viscosity methods do not predict peak surface parameters well without the introduction of an overshooting transition function whose connection with the spot theory of transition is obscure. Suggestions are made for further work that now appears necessary for developing improved models of the transition zone

Magnetic Energy and Helicity Budgets in the Active-Region Solar Corona. I. Linear Force-Free Approximation

We self-consistently derive the magnetic energy and relative magnetic helicity budgets of a three-dimensional linear force-free magnetic structure rooted in a lower boundary plane. For the potential magnetic energy we derive a general expression that gives results practically equivalent to those of the magnetic Virial theorem. All magnetic energy and helicity budgets are formulated in terms of surface integrals applied to the lower boundary, thus avoiding computationally intensive three-dimensional magnetic field extrapolations. We analytically and numerically connect our derivations with classical expressions for the magnetic energy and helicity, thus presenting a so-far lacking unified treatment of the energy/helicity budgets in the constant-alpha approximation. Applying our derivations to photospheric vector magnetograms of an eruptive and a noneruptive solar active regions, we find that the most profound quantitative difference between these regions lies in the estimated free magnetic energy and relative magnetic helicity budgets. If this result is verified with a large number of active regions, it will advance our understanding of solar eruptive phenomena. We also find that the constant-alpha approximation gives rise to large uncertainties in the calculation of the free magnetic energy and the relative magnetic helicity. Therefore, care must be exercised when this approximation is applied to photospheric magnetic field observations. Despite its shortcomings, the constant-alpha approximation is adopted here because this study will form the basis of a comprehensive nonlinear force-free description of the energetics and helicity in the active-region solar corona, which is our ultimate objective.Comment: 44 pages, 8 figures, 2 tables. The Astrophysical Journal, in pres

No way out? The double-bind in seeking global prosperity alongside mitigated climate change

In a prior study, I introduced a simple economic growth model designed to be consistent with general thermodynamic laws. Unlike traditional economic models, civilization is viewed only as a well-mixed global whole with no distinction made between individual nations, economic sectors, labor, or capital investments. At the model core is an observationally supported hypothesis that the global economy's current rate of primary energy consumption is tied through a constant to a very general representation of its historically accumulated wealth. Here, this growth model is coupled to a linear formulation for the evolution of globally well-mixed atmospheric CO2 concentrations. While very simple, the coupled model provides faithful multi-decadal hindcasts of trajectories in gross world product (GWP) and CO2. Extending the model to the future, the model suggests that the well-known IPCC SRES scenarios substantially underestimate how much CO2 levels will rise for a given level of future economic prosperity. For one, global CO2 emission rates cannot be decoupled from wealth through efficiency gains. For another, like a long-term natural disaster, future greenhouse warming can be expected to act as an inflationary drag on the real growth of global wealth. For atmospheric CO2 concentrations to remain below a "dangerous" level of 450 ppmv, model forecasts suggest that there will have to be some combination of an unrealistically rapid rate of energy decarbonization and nearly immediate reductions in global civilization wealth. Effectively, it appears that civilization may be in a double-bind. If civilization does not collapse quickly this century, then CO2 levels will likely end up exceeding 1000 ppmv; but, if CO2 levels rise by this much, then the risk is that civilization will gradually tend towards collapse

Dialogue Act Recognition via CRF-Attentive Structured Network

Dialogue Act Recognition (DAR) is a challenging problem in dialogue interpretation, which aims to attach semantic labels to utterances and characterize the speaker's intention. Currently, many existing approaches formulate the DAR problem ranging from multi-classification to structured prediction, which suffer from handcrafted feature extensions and attentive contextual structural dependencies. In this paper, we consider the problem of DAR from the viewpoint of extending richer Conditional Random Field (CRF) structural dependencies without abandoning end-to-end training. We incorporate hierarchical semantic inference with memory mechanism on the utterance modeling. We then extend structured attention network to the linear-chain conditional random field layer which takes into account both contextual utterances and corresponding dialogue acts. The extensive experiments on two major benchmark datasets Switchboard Dialogue Act (SWDA) and Meeting Recorder Dialogue Act (MRDA) datasets show that our method achieves better performance than other state-of-the-art solutions to the problem. It is a remarkable fact that our method is nearly close to the human annotator's performance on SWDA within 2% gap.Comment: 10 pages, 4figure

Numerical Simulations of Coronal Heating through Footpoint Braiding

Advanced 3D radiative MHD simulations now reproduce many properties of the outer solar atmosphere. When including a domain from the convection zone into the corona, a hot chromosphere and corona are self-consistently maintained. Here we study two realistic models, with different simulated area, magnetic field strength and topology, and numerical resolution. These are compared in order to characterize the heating in the 3D-MHD simulations which self-consistently maintains the structure of the atmosphere. We analyze the heating at both large and small scales and find that heating is episodic and highly structured in space, but occurs along loop shaped structures, and moves along with the magnetic field. On large scales we find that the heating per particle is maximal near the transition region and that widely distributed opposite-polarity field in the photosphere leads to a greater heating scale height in the corona. On smaller scales, heating is concentrated in current sheets, the thicknesses of which are set by the numerical resolution. Some current sheets fragment in time, this process occurring more readily in the higher-resolution model leading to spatially highly intermittent heating. The large scale heating structures are found to fade in less than about five minutes, while the smaller, local, heating shows time scales of the order of 2 minutes in one model and 1 minutes in the other, higher-resolution, model.Comment: 20 pages, accepted by Ap