Further Establishment of the Field Perturbation Theory of the Pseudogaps in HTSC

Here I establish the field perturbation theory of pseudogaps in HTSC. The proposed ground state suggests an internal particle-hole field, which is normal to nesting surfaces, and having twice the Fermi wave number. It is proved that the system violates momentum conservation by the wave vector of this internal field. This violation applies to the quasi-particle propagators, as well as to the interactions. Interaction vertices via the Pauli matrix-τ₁ are established. This, in turn, establishes the validity of the pseudogap Hartree self-energy.     

Multiplicative Operator Splittings in Nonlinear Diffusion: From Spatial Splitting to Multiple Timesteps

Operator splitting is a powerful concept used in many diversed fields of applied mathematics for the design of effective numerical schemes. Following the success of the additive operator splitting (AOS) in performing an efficient nonlinear diffusion filtering on digital images, we analyze the possibility of using multiplicative operator splittings to process images from different perspectives.We start by examining the potential of using fractional step methods to design a multiplicative operator splitting as an alternative to AOS schemes. By means of a Strang splitting, we attempt to use numerical schemes that are known to be more accurate in linear diffusion processes and apply them on images. Initially we implement the Crank-Nicolson and DuFort-Frankel schemes to diffuse noisy signals in one dimension and devise a simple extrapolation that enables the Crank-Nicolson to be used with high accuracy on these signals. We then combine the Crank-Nicolson in 1D with various multiplicative operator splittings to process images. Based on these ideas we obtain some interesting results. However, from the practical standpoint, due to the computational expenses associated with these schemes and the questionable benefits in applying them to perform nonlinear diffusion filtering when using long timesteps, we conclude that AOS schemes are simple and efficient compared to these alternatives.We then examine the potential utility of using multiple timestep methods combined with AOS schemes, as means to expedite the diffusion process. These methods were developed for molecular dynamics applications and are used efficiently in biomolecular simulations. The idea is to split the forces exerted on atoms into different classes according to their behavior in time, and assign longer timesteps to nonlocal, slowly-varying forces such as the Coulomb and van der Waals interactions, whereas the local forces like bond and angle are treated with smaller timesteps. Multiple timestep integrators can be derived from the Trotter factorization, a decomposition that bears a strong resemblance to a Strang splitting. Both formulations decompose the time propagator into trilateral products to construct multiplicative operator splittings which are second order in time, with the possibility of extending the factorization to higher order expansions. While a Strang splitting is a decomposition across spatial dimensions, where each dimension is subsequently treated with a fractional step, the multiple timestep method is a decomposition across scales. Thus, multiple timestep methods are a realization of the multiplicative operator splitting idea. For certain nonlinear diffusion coefficients with favorable properties, we show that a simple multiple timestep method can improve the diffusion process.     

THE IMPORTANCE OF NEUTRAL EXAMPLES FOR LEARNING SENTIMENT

Most research on learning to identify sentiment ignores "neutral" examples, learning only from examples of significant (positive or negative) polarity. We show that it is crucial to use neutral examples in learning polarity for a variety of reasons. Learning from negative and positive examples alone will not permit accurate classification of neutral examples. Moreover, the use of neutral training examples in learning facilitates better distinction between positive and negative examples.     

The attentional demands of encoding and retrieval in younger and older adults: I. Evidence from divided attention costs.

Four studies examined the effects of divided attention in younger and older adults. Attention was divided at encoding or retrieval in free recall (Experiment 1), cued recall (Experiments 2 and 3), and recognition (Experiment 4). Dividing attention at encoding disrupted memory performance equally for the two age groups; by contrast, for both age groups, dividing attention at retrieval had little or no effect on memory performance. Secondary task reaction times (RTs) were slowed to a greater extent for the older adults than for the younger adults, especially at retrieval. Age-related differences in RTs costs at retrieval were largest in free recall, smaller in cued recall, and smallest in recognition. These results provide evidence for an age-related increase in the attentional demands of encoding and retrieval. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Deep neural network architectures for dysarthric speech analysis and recognition

Neural Computing and Applications - This paper investigates the ability of deep neural networks (DNNs) to improve the automatic recognition of dysarthric speech through the use of convolutional...     

A stochastic controller for a scalar linear system with additive Cauchy noise

A stochastic control scheme is developed for scalar, discrete-time, and linear-dynamic systems driven by Cauchy distributed process and measurement noises. When addressing the optimal control problem for such systems, the standard quadratic cost criteria cannot be used. In this study we introduce a new objective function that is functionally similar to the Cauchy probability density function. The performance index, defined as the expectation of this objective function with respect to the Cauchy densities, exists. The dynamic programming solution to the fixed and finite horizon optimal control problem that uses this performance index appears to be intractable. Therefore, a moving horizon optimal model predictive control problem is implemented, for which the conditional expected value of the objective function and its gradients can be computed in closed   form and without assumptions such as certainty equivalence. Numerical results are shown for this m$m$-step model predictive optimal controller and compared to a similar, Linear-Exponential-Gaussian model predictive controller. An essential difference between the Cauchy and Gaussian controllers when applied to a system with Cauchy noises is that, while the Gaussian controller is linear and reacts strongly to all noise pulses, the Cauchy controller can differentiate between measurement and process noise pulses by ignoring the former while responding to the latter. This property of the Cauchy controller occurs when an impulsive measurement noise is more likely than an impulsive process noise. The Cauchy and Gaussian controllers react similarly when applied to a system with Gaussian noises, demonstrating the robustness of the proposed control scheme.     

Phase diagrams for oil/methanol/ether mixtures

One-phase transmethylations of vegetable oils with methanol to form methyl esters occur considerably faster than conventional two-phase reactions. Addition of simple ethers is an efficient method for producing a single phase. Ternary phase diagrams have been determined at 23°C for oil/methanol/ether mixtures; these are useful when applying the one-phase method across a wide range of conditions. Soybean, canola, palm, and coconut oils were used in combination with five ethers, namely, tetrahydrofuran (THF), 1,4-dioxane (DO), diethyl ether (DE), diisopropyl ether (DI), andtert-butyl methyl ether (TBM). All five ethers can produce miscibility for all methanol/oil compositions. The ether/methanol volumetric ratios required for miscibility at a methanol/soybean or canola oil volumetric ratio of 0.20 (5.4 molar ratio) at 23°C are: THF, 1.15; DO, 1.60; DE, 1.38 DI, 1.57; and TBM, 1.57. For THF, this results in one-phase mixtures that contain 65 vol% oil. Soybean and canola oil form identical diagrams. Palm oil requires slightly less ether at the lower methanol concentrations, but coconut oil requires considerably less across the whole concentration range. Acid-catalyzed reactions, when performed at the boiling point of the most volatile component, require less ether than predicted from the diagrams.     

Hydrotreating processes for catalytic abatement of water pollutants

Opportunities and problems in application of catalytic hydrotreating processes, which are presented a viable approach in the abatement of water pollutants, are discussed. Analysis of the hydrodechlorination (HDC) and hydrodenitrification (HDN) using Pd-based catalysts supported on various materials like granulated activated carbon (GAC), fibrous activated carbon cloths (ACCs) or glass fiber cloths (GFCs) studied recently in our laboratory suggests the following perspectives:

Exhaustive regeneration of Pd/GAC saturated with p-chlorophenol can be achieved in a two-step approach, incorporating gas-phase HDC by hydrogen followed by oxidation by air.

Pd/ACC catalysts are good candidates for the liquid-phase HDC showing activity higher than that of Pd/GAC or Pd/GFC; the high adsorption capacity of Pd/ACC lead suggesting its use in a technology with periodic adsorption and HDC, in similarity to adsorption with regeneration of GAC.

Pd/GFC and Pd–Cu/GFC are promising catalyst for removal of nitrites and nitrates, showing activity and selectivity that compares favorably with those of powdered catalysts.

Synthesis with rational environments

Synthesis is the automated construction of a system from its specification. The system has to satisfy its specification in all possible environments. The environment often consists of agents that have objectives of their own. Thus, it makes sense to soften the universal quantification on the behavior of the environment and take the objectives of its underlying agents into an account. Fisman et al. introduced rational synthesis: the problem of synthesis in the context of rational agents. The input to the problem consists of temporal logic formulas specifying the objectives of the system and the agents that constitute the environment, and a solution concept (e.g., Nash equilibrium). The output is a profile of strategies, for the system and the agents, such that the objective of the system is satisfied in the computation that is the outcome of the strategies, and the profile is stable according to the solution concept; that is, the agents that constitute the environment have no incentive to deviate from the strategies suggested to them. In this paper we continue to study rational synthesis. First, we suggest an alternative definition to rational synthesis, in which the agents are rational but not cooperative. We call such problem strong rational synthesis. In the strong rational synthesis setting, one cannot assume that the agents that constitute the environment take into account the strategies suggested to them. Accordingly, the output is a strategy for the system only, and the objective of the system has to be satisfied in all the compositions that are the outcome of a stable profile in which the system follows this strategy. We show that strong rational synthesis is 2ExpTime-complete, thus it is not more complex than traditional synthesis or rational synthesis. Second, we study a richer specification formalism, where the objectives of the system and the agents are not Boolean but quantitative. In this setting, the objective of the system and the agents is to maximize their outcome. The quantitative setting significantly extends the scope of rational synthesis, making the game-theoretic approach much more relevant. Finally, we enrich the setting to one that allows coalitions of agents that constitute the system or the environment.