Improving maximum margin matrix factorization

Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful learning approach to this task and has been recently extended to structured ranking losses. In this paper we discuss a number of extensions to MMMF by introducing offset terms, item dependent regularization and a graph kernel on the recommender graph. We show equivalence between graph kernels and the recent MMMF extensions by Mnih and Salakhutdinov (Advances in Neural Information Processing Systems 20, 2008). Experimental evaluation of the introduced extensions show improved performance over the original MMMF formulation.     

Leiomyosarcoma of the inferior vena cava. Diagnosis and surgical management

Leiomyosarcoma of vascular origin are rare tumors arising most frequently from the inferior vena cava (IVC). We report on three patients one of whom underwent definitive resection. These tumors most commonly involve the upper segment of the IVC, and appear with manifestations of the Budd-Chiari syndrome. Lesions at this level are not amenable to surgical therapy. Tumors of the middle and lower segments of the IVC usually cause right-sided pain. Diagnosis is difficult, but is best approached preoperatively by angiography and vena cavography. Optimal therapy of lesions at these levels is surgical resection. Resection of the IVC below the hepatic veins is possible with renal function preserved by collateral drainage of the left renal vein.     

Aerosol lidar intercomparison in the framework of the EARLINET project. 2. Aerosol backscatter algorithms

An intercomparison of aerosol backscatter lidar algorithms was performed in 2001 within the framework of the European Aerosol Research Lidar Network to Establish an Aerosol Climatology (EARLINET). The objective of this research was to test the correctness of the algorithms and the influence of the lidar ratio used by the various lidar teams involved in the EARLINET for calculation of backscatter-coefficient profiles from the lidar signals. The exercise consisted of processing synthetic lidar signals of various degrees of difficulty. One of these profiles contained height-dependent lidar ratios to test the vertical influence of those profiles on the various retrieval algorithms. Furthermore, a realistic incomplete overlap of laser beam and receiver field of view was introduced to remind the teams to take great care in the nearest range to the lidar. The intercomparison was performed in three stages with increasing knowledge on the input parameters. First, only the lidar signals were distributed; this is the most realistic stage. Afterward the lidar ratio profiles and the reference values at calibration height were provided. The unknown height-dependent lidar ratio had the largest influence on the retrieval, whereas the unknown reference value was of minor importance. These results show the necessity of making additional independent measurements, which can provide us with a suitable approximation of the lidar ratio. The final stage proves in general, that the data evaluation schemes of the different groups of lidar systems work well.     

Economics of Dynamic Pricing in a Reputation Brokered Agent Mediated Marketplace

We present a framework to study the microeconomic effects in a reputation brokered Agent mediated Knowledge Marketplace, when we introduce dynamic pricing algorithms. We study the market with computer simulations of multiagent interactions. In this marketplace, the seller reputations are updated in a collaborative fashion based on the performance of the user in the delegated tasks. To the best of our knowledge this is the first agent mediated marketplace where the agents use dynamic pricing based on dynamically updated reputations. The framework can be used to investigate the different equilibria reached, based on the level of intelligence of the selling agents, the level of price-importance elasticity of the buying agents, and the level of unemployment in the marketplace. Preliminary experiments addressing these issues are presented.     

Visualising deep network time-series representations

Neural Computing and Applications - Despite the popularisation of machine learning models, more often than not, they still operate as black boxes with no insight into what is happening inside the...     

Cone Calorimeter and Thermogravimetric Analysis of Glass Phenolic Composites Used in Aircraft Applications

The increasing use of composite materials in aircraft cabins and structures poses significant challenges in order to maintain and improve the fire safety of aviation. In this work, the flammability characteristics of a commercial glass-fibre reinforced phenolic composite (GFRP) used for aircraft cabin partitions and furnishing are investigated experimentally. Thermogravimetric analysis under inert atmosphere at several heating rates provided information on the thermal decomposition process. The degradation process is modelled with one and two-step mechanisms using the Ozawa–Flynn–Wall iso-conversional method and the GPYRO numerical code which utilizes a genetic algorithm optimization scheme. The estimated activation energy and pre-exponential factor values, especially in the two-step case (77.18 and 104.69 kJ/mol and 2.60 × 106 and 3.19 × 106 min−1 for the first and the second step respectively), recover reasonably well the conversion degree and its derivative. Tests with a cone calorimeter (CC), performed at different incident heat fluxes, provided information on the reaction to fire characteristics of the material and the influence of the heat flux on the combustion process. In general, combustion proceeds in two stages, flaming and smoldering combustion. The CC results assisted by scanning electron microscopy photos provide information on the charring characteristics of the material. The critical heat flux for ignition and the corresponding ignition temperature are estimated, correlating heat fluxes with time to ignition. Thermally thin and thick models are considered, as well as a modified technique bridging the gap between these limit cases and therefore valid for thermally thin and thick but also intermediate conditions (more pertinent in the present case). The results for this latter approach are $$\dot{q}^{\prime\prime}_{ig,cr}$$ ~ 20 kW/m2 and Tig = 469°C, providing also complementing information on thermophysical properties, such as thermal diffusivity, α = 1.23 × 10−7 m2/s, thermal conductivity, k = 0.325 W/(m K) and specific heat capacity, c = 1.330 kJ/(kg K). This work provides information on the reaction to fire characteristics of GFRP, but also on physical and flammability properties in a form suitable to be used in numerical codes, for the prediction of fire and evacuation scenarios. The influence of the reinforcement structure on the fire behaviour of the composite is also illustrated and discussed.     

Evaluation of per-pixel linked lists for distributed rendering and comparative analysis

Rendering scenes with overlapping transparent faces is challenging for several reasons, including sorting geometry, managing multiple per-pixel fragments, and compositing. These questions have been solved for local rendering previously, for example by order-independent transparency approaches like Depth Peeling or A-buffer implementations. We discuss order-independent transparency algorithms in context of distributed rendering for large data sets or simulations which by design split the work load among a number of computation nodes. Furthermore, we evaluate a per-pixel linked list approach for distributed mesh rendering and multi-variant analysis of molecule data sets.     

Methacrylated Calix[6]arenes as Low Shrinking Additives for Dental Restorative Composites

p‐tert‐Butylcalix[6]arene was acylated with different carboxylic acid anhydrides to improve their solubility in dimethacrylate cross‐linkers. An esterification of p‐tert‐butylcalix[6]arene 1 with octanoic anhydride followed by methacrylation of the residual hydroxy groups with methacrylic anhydride resulted mainly in the formation of a pentaoctanoatemonomethacrylate 2a . In the radical polymerization of methyl methacrylate the inhibition effect of residual hydroxy groups in 2a was evaluated. Dimethacrylate containing composites based on a monomer matrix of cross‐linking dimethacrylates and 0–30 wt.% of 2a were prepared. The addition of 2a resulted in a significant decrease of the polymerization shrinkage, whereas the modulus of elasticity of the visible light cured composites was not affected.

     

Hydrogen absorption/desorption kinetics of magnesium nano-nickel composites synthesized by dry particle coating technique

Dry particle coating technique was utilized for coating nano-nickel on magnesium particles. The objectives of this study were to evaluate the effects of the nanocatalyst (Ni) on the hydrogen absorption and desorption kinetics of the Mg-based composite (Mg–Ni). Hydrogen absorption curves plotted as a function of time showed that composites processed for longer periods of time exhibited significantly higher hydrogen absorption rates. With increased coating time, the catalyst was more evenly distributed over the Mg surface, resulting in the formation of a composite with increased hydrogen capacity and kinetics. Meanwhile, no significant morphology change in the composites was observed. A change in the hydrogen absorption rate as a function of time was observed. This change in rate implies a change in the rate limiting mechanism from chemical absorption on the Mg particle to diffusion into the Mg particle. TGA results showed that lower coating speeds resulted in lower initial desorption temperatures as well as steeper desorption rates. Higher heating rates resulted in faster reaction rates and therefore reduced hydrogen absorption time and increased hydrogen storage capacity.     

Manipulating surface states in topological insulator nanoribbons

Topological insulators display unique properties, such as the quantum spin Hall effect, because time-reversal symmetry allows charges and spins to propagate along the edge or surface of the topological insulator without scattering. However, the direct manipulation of these edge/surface states is difficult because they are significantly outnumbered by bulk carriers. Here, we report experimental evidence for the modulation of these surface states by using a gate voltage to control quantum oscillations in Bi(2)Te(3) nanoribbons. Surface conduction can be significantly enhanced by the gate voltage, with the mobility and Fermi velocity reaching values as high as ~5,800?cm(2)?V(-1)?s(-1) and ~3.7?×?10(5)?m?s(-1), respectively, with up to ~51% of the total conductance being due to the surface states. We also report the first observation of h/2e periodic oscillations, suggesting the presence of time-reversed paths with the same relative zero phase at the interference point. The high surface conduction and ability to manipulate the surface states demonstrated here could lead to new applications in nanoelectronics and spintronics.