Value-based argumentation frameworks as neural-symbolic learning systems

While neural networks have been successfully used in a number of machine learning applications, logical languages have been the standard for the representation of argumentative reasoning. In this paper, we establish a relationship between neural networks and argumentation networks, combining reasoning and learning in the same argumentation framework. We do so by presenting a new neural argumentation algorithm, responsible for translating argumentation networks into standard neural networks. We then show a correspondence between the two networks. The algorithm works not only for acyclic argumentation networks, but also for circular networks, and it enables the accrual of arguments through learning as well as the parallel computation of arguments

Lowest Landau-level description of a Bose-Einstein condensate in a rapidly rotating anisotropic trap

A rapidly rotating Bose-Einstein condensate in a symmetric two-dimensional trap can be described with the lowest Landau-level set of states. In this case, the condensate wave function psi(x,y) is a Gaussian function of r^2 = x^2 + y^2, multiplied by an analytic function P(z) of the single complex variable z= x+ i y; the zeros of P(z) denote the positions of the vortices. Here, a similar description is used for a rapidly rotating anisotropic two-dimensional trap with arbitrary anisotropy (omega_x/omega_y le 1). The corresponding condensate wave function psi(x,y) has the form of a complex anisotropic Gaussian with a phase proportional to xy, multiplied by an analytic function P(zeta), where zeta is proportional to x + i beta_- y and 0 le beta_- le 1 is a real parameter that depends on the trap anisotropy and the rotation frequency. The zeros of P(zeta) again fix the locations of the vortices. Within the set of lowest Landau-level states at zero temperature, an anisotropic parabolic density profile provides an absolute minimum for the energy, with the vortex density decreasing slowly and anisotropically away from the trap center.Comment: 13 pages, 1 figur

Oxidative Heck desymmetrisation of 2,2-disubstituted cyclopentene-1,3-diones

Oxidative Heck couplings have been successfully developed for 2,2-disubstituted cyclopentene-1,3-diones. The direct coupling onto the 2,2-disubstituted cyclopentene-1,3-dione core provides a novel expedient way of enantioselectively desymmetrising all-carbon quaternary centres

Boundary Conditions in Stepwise Sine-Gordon Equation and Multi-Soliton Solutions

We study the stepwise sine-Gordon equation, in which the system parameter is different for positive and negative values of the scalar field. By applying appropriate boundary conditions, we derive relations between the soliton velocities before and after collisions. We investigate the possibility of formation of heavy soliton pairs from light ones and vise versa. The concept of soliton gun is introduced for the first time; a light pair is produced moving with high velocity, after the annihilation of a bound, heavy pair. We also apply boundary conditions to static, periodic and quasi-periodic solutions.Comment: 14 pages, 8 figure

Chandra Observations of Arp 220: The Nuclear Source

We present the first results from 60ks of observations of Arp 220 using the ACIS-S instrument on Chandra. We report the detection of several sources near the galaxy's nucleus, including a point source with a hard spectrum that is coincident with the western radio nucleus B. This point source is mildly absorbed (N_H ~ 3 x 10^22 cm^-2) and has an estimated luminosity of 4 x 10^40 erg/s. In addition, a fainter source may coincide with the eastern nucleus A. Extended hard X-ray emission in the vicinity raises the total estimated nuclear 2-10 keV X-ray luminosity to 1.2 x 10^41 erg/s, but we cannot rule out a hidden AGN behind columns exceeding 5 x 10^24 cm^-2. We also detect a peak of soft X-ray emission to the west of the nucleus, and a hard point source 2.5 kpc from the nucleus with a luminosity of 6 x 10^39 erg/s.Comment: Accepted for publication in Ap

Long-term storage and age‐biased export of fluvial organic carbon: field evidence from West Iceland

Terrestrial organic carbon (OC) plays an important role in the carbon cycle, but questions remain regarding the controls and timescale(s) over which atmospheric CO₂ remains sequestered as particulate OC (POC). Motivated by observations that terrestrial POC is physically stored within soils and other shallow sedimentary deposits, we examined the role that sediment storage plays in the terrestrial OC cycle. Specifically, we tested the hypothesis that sediment storage impacts the age of terrestrial POC. We focused on the Efri Haukadalsá River catchment in Iceland as it lacks ancient sedimentary bedrock that would otherwise bias radiocarbon‐based determinations of POC storage duration by supplying pre‐aged “petrogenic” POC. Our radiocarbon measurements of riverine suspended sediments and deposits implicated millennial‐scale storage times. Comparison between the sample types (suspended and deposits) suggested an age offset between transported (suspended sediments) and stored (deposits) POC at the time of sampling, which is predicted by theory for the sediment age distribution in floodplains. We also observed that POC in suspended sediments is younger than the predicted mean storage duration generated from independent geomorphological data, which suggested an additional role for OC cycling. Consistent with this, we observed interparticle heterogeneity in the composition of POC by imaging our samples at the microscale using X‐ray absorption spectroscopy. Specifically, we found that particles within individual samples differed in their sulfur oxidation state, which is indicative of multiple origins and/or diagenetic histories. Altogether, our results support recent coupled sediment storage and OC cycling models and indicate that the physical drivers of sediment storage are important factors controlling the cadence of carbon cycling

Chandra Observations of Arp 220: The Nuclear Source

We present the first results from 60ks of observations of Arp 220 using the ACIS-S instrument on Chandra. We report the detection of several sources near the galaxy's nucleus, including a point source with a hard spectrum that is coincident with the western radio nucleus B. This point source is mildly absorbed (N_H ~ 3 x 10^22 cm^-2) and has an estimated luminosity of 4 x 10^40 erg/s. In addition, a fainter source may coincide with the eastern nucleus A. Extended hard X-ray emission in the vicinity raises the total estimated nuclear 2-10 keV X-ray luminosity to 1.2 x 10^41 erg/s, but we cannot rule out a hidden AGN behind columns exceeding 5 x 10^24 cm^-2. We also detect a peak of soft X-ray emission to the west of the nucleus, and a hard point source 2.5 kpc from the nucleus with a luminosity of 6 x 10^39 erg/s.Comment: Accepted for publication in Ap

Physics of puffing and microexplosion of emulsion fuel droplets

The physics of water-in-oil emulsion droplet microexplosion/puffing has been investigated using high-fidelity interface-capturing simulation. Varying the dispersed-phase (water) sub-droplet size/location and the initiation location of explosive boiling (bubble formation), the droplet breakup processes have been well revealed. The bubble growth leads to local and partial breakup of the parent oil droplet, i.e., puffing. The water sub-droplet size and location determine the after-puffing dynamics. The boiling surface of the water sub-droplet is unstable and evolves further. Finally, the sub-droplet is wrapped by boiled water vapor and detaches itself from the parent oil droplet. When the water sub-droplet is small, the detachment is quick, and the oil droplet breakup is limited. When it is large and initially located toward the parent droplet center, the droplet breakup is more extensive. For microexplosion triggered by the simultaneous growth of multiple separate bubbles, each explosion is local and independent initially, but their mutual interactions occur at a later stage. The degree of breakup can be larger due to interactions among multiple explosions. These findings suggest that controlling microexplosion/puffing is possible in a fuel spray, if the emulsion-fuel blend and the ambient flow conditions such as heating are properly designed. The current study also gives us an insight into modeling the puffing and microexplosion of emulsion droplets and sprays.This article has been made available through the Brunel Open Access Publishing Fund

Learning and Representing Temporal Knowledge in Recurrent Networks

The effective integration of knowledge representation, reasoning, and learning in a robust computational model is one of the key challenges of computer science and artificial intelligence. In particular, temporal knowledge and models have been fundamental in describing the behavior of computational systems. However, knowledge acquisition of correct descriptions of a system's desired behavior is a complex task. In this paper, we present a novel neural-computation model capable of representing and learning temporal knowledge in recurrent networks. The model works in an integrated fashion. It enables the effective representation of temporal knowledge, the adaptation of temporal models given a set of desirable system properties, and effective learning from examples, which in turn can lead to temporal knowledge extraction from the corresponding trained networks. The model is sound from a theoretical standpoint, but it has also been tested on a case study in the area of model verification and adaptation. The results contained in this paper indicate that model verification and learning can be integrated within the neural computation paradigm, contributing to the development of predictive temporal knowledge-based systems and offering interpretable results that allow system researchers and engineers to improve their models and specifications. The model has been implemented and is available as part of a neural-symbolic computational toolkit