Broken gates and leaky graves : spectral language and Australia's ghost stories

Ghost stories are unusual amongst supernatural literatures in their modelling of a recognisable, mimetic reality interrupted or infiltrated by immaterial forces. In its discussion of Australian ghost stories, this thesis advances a new approach to ghost narratives which seeks to model and articulate the mechanics of ghosts and hauntings as something reliant on and engaged with the material and the mundane.

Phonon modes of MgB2 : Super-lattice structures and spectral response

Micrometre-sized MgB2 crystals of varying quality, synthesized at low temperature and autogeneous pressure, are compared using a combination of Raman and Infra-Red (IR) spectroscopy. These data, which include new peak positions in both spectroscopies for high quality MgB2, are interpreted using DFT calculations on phonon behaviour for symmetry-related structures. Raman and IR activity additional to that predicted by point group analyses of the P6/mmm symmetry are detected. These additional peaks, as well as the overall shapes of calculated phonon dispersion (PD) models are explained by assuming a double super-lattice, consistent with a lower symmetry structure for MgB2. A 2x super-lattice in the c-direction allows a simple correlation of the pair breaking energy and the superconducting gap by activation of corresponding acoustic frequencies. A consistent physical interpretation of these spectra is obtained when the position of a phonon anomaly defines a super-lattice modulation in the a-b plane.

Electrochemical and spectral studies of self-assembled monolayer of 1,8,15,22-tetraaminophthalocyanatocobalt(II) on indium tin oxide surface

Self-assembled monolayer (SAM) of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) was prepared on indium tin oxide (ITO) electrode by spontaneous adsorption from dimethylformamide (DMF) solution containing 4α-CoIITAPc. The SAM of 4α-CoIITAPc formed on ITO electrode was characterized by cyclic voltammetry, Raman and UV–visible spectroscopic techniques. The cyclic voltammogram (CV) of 4α-CoIITAPc SAM shows two pairs of well-defined redox peaks corresponding to CoIII/CoII and CoIIIPc−1/CoIIIPc−2. The surface coverage (Γ) was calculated by integrating the charge under the anodic wave corresponding to CoII oxidation and it was found to be 2.25 × 10−10 mol cm−2. Raman spectrum obtained for the SAM of 4α-CoIITAPc on ITO surface shows strong stretching and breathing bands of Pc macrocycle, pyrrole ring and isoindole ring. Further, the –NH2 bending mode of vibration was absent for the SAM of 4α-CoIITAPc on ITO surface which indirectly confirmed that all the amino groups of 4α-CoIITAPc are involved in bonding with ITO surface. UV–visible spectrum for the SAM of 4α-CoIITAPc on ITO surface shows an intense B-band, Q-band and n–π∗ transition with slight broadening when compared to that of 4α-CoIITAPc in DMF.

Wide-band spectral power fluctuations characterize the response of simulated cortical networks to increasing stimulus intensity

The hippocampus is an anatomically distinct region of the medial temporal lobe that plays a critical role in the formation of declarative memories. Here we show that a computer simulation of simple compartmental cells organized with basic hippocampal connectivity is capable of producing stimulus intensity sensitive wide-band fluctuations of spectral power similar to that seen in real EEG. While previous computational models have been designed to assess the viability of the putative mechanisms of memory storage and retrieval, they have generally been too abstract to allow comparison with empirical data. Furthermore, while the anatomical connectivity and organization of the hippocampus is well defined, many questions regarding the mechanisms that mediate large-scale synaptic integration remain unanswered. For this reason we focus less on the specifics of changing synaptic weights and more on the population dynamics. Spectral power in four distinct frequency bands were derived from simulated field potentials of the computational model and found to depend on the intensity of a random input. The majority of power occurred in the lowest frequency band (3-6 Hz) and was greatest to the lowest intensity stimulus condition (1% maximal stimulus). In contrast, higher frequency bands ranging from 7-45 Hz show an increase in power directly related with an increase in stimulus intensity. This trend continues up to a stimulus level of 15% to 20% of the maximal input, above which power falls dramatically. These results suggest that the relative power of intrinsic network oscillations are dependent upon the level of activation and that above threshold levels all frequencies are damped, perhaps due to over activation of inhibitory interneurons.

Memory and Epileptogenesis in Complex Biological and Simulated Systems

Oscillations of neural activity may bind widespread cortical areas into a neural representation that encodes disparate aspects of an event. In order to test this theory we have turned to data collected from complex partial epilepsy (CPE) patients with chronically implanted depth electrodes. Data from regions critical to word and face information processing was analyzed using spectral coherence measurements. Similar analyses of intracranial EEG (iEEG) during seizure episodes display HippoCampal Formation (HCF)—NeoCortical (NC) spectral coherence patterns that are characteristic of specific seizure stages (Klopp et al. 1996). We are now building a computational memory model to examine whether spatio-temporal patterns of human iEEG spectral coherence emerge in a computer simulation of HCF cellular distribution, membrane physiology and synaptic connectivity. Once the model is reasonably scaled it will be used as a tool to explore neural parameters that are critical to memory formation and epileptogenesis.

A Crank--Nicolson ADI spectral method for a two-dimensional riesz space fractional nonlinear reaction-diffusion equation

In this paper, a new alternating direction implicit Galerkin--Legendre spectral method for the two-dimensional Riesz space fractional nonlinear reaction-diffusion equation is developed. The temporal component is discretized by the Crank--Nicolson method. The detailed implementation of the method is presented. The stability and convergence analysis is strictly proven, which shows that the derived method is stable and convergent of order $2$ in time. An optimal error estimate in space is also obtained by introducing a new orthogonal projector. The present method is extended to solve the fractional FitzHugh--Nagumo model. Numerical results are provided to verify the theoretical analysis.

A Novel High Order Space-Time Spectral Method for the Time Fractional Fokker--Planck Equation

The fractional Fokker-Planck equation is an important physical model for simulating anomalous diffusions with external forces. Because of the non-local property of the fractional derivative an interesting problem is to explore high accuracy numerical methods for fractional differential equations. In this paper, a space-time spectral method is presented for the numerical solution of the time fractional Fokker-Planck initial-boundary value problem. The proposed method employs the Jacobi polynomials for the temporal discretization and Fourier-like basis functions for the spatial discretization. Due to the diagonalizable trait of the Fourier-like basis functions, this leads to a reduced representation of the inner product in the Galerkin analysis. We prove that the time fractional Fokker-Planck equation attains the same approximation order as the time fractional diffusion equation developed in [23] by using the present method. That indicates an exponential decay may be achieved if the exact solution is sufficiently smooth. Finally, some numerical results are given to demonstrate the high order accuracy and efficiency of the new numerical scheme. The results show that the errors of the numerical solutions obtained by the space-time spectral method decay exponentially.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

Influence of the structural characteristic of pyrolysis products on thermal stability of styrene-butadiene rubber composites reinforced by different particle sized kaolinites

A series of rubber composites were prepared by blending styrene-butadiene rubber (SBR) latex and the different particle sized kaolinites. The thermal stabilities of the rubber composites were characterized using thermogravimetry, digital photography, scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and Raman spectroscopy. Kaolinite SBR composites showed much greater thermal stability when compared with that of the pure SBR. With the increase of kaolinite particle size, the pyrolysis products became much looser; the char layer and crystalline carbon content gradually decreased in the pyrolysis residues. The pyrolysis residues of the SBR composites filled with the different particle sized kaolinites showed some remarkable changes in structural characteristics. The increase of kaolinite particle size was not beneficial to form the compact and stable crystalline carbon in the pyrolysis process, and resulted in a negative influence in improving the thermal stability of kaolinite/SBR composites.

Raman and infrared spectroscopic characterization of the arsenate-bearing mineral tangdanite– and in comparison with the discredited mineral clinotyrolite

The minerals clinotyrolite and fuxiaotuite are discredited in terms of the mineral tangdanite. The mixed anion mineral tangdanite Ca2Cu9(AsO4)4(SO4)0.5(OH)9 9H2O has been studied using a combination of Raman and infrared spectroscopy. Characteristic bands associated with arsenate, sulphate and hydroxyl units are identified. Broad bands in the OH stretching region are observed and are resolved into component bands. These bands are assigned to water and hydroxyl stretching vibrations. Two intense Raman bands at 837 and approximately 734 cm−1 are assigned to the ν1 (AsO4)3− symmetric stretching and ν3 (AsO4)3− antisymmetric stretching modes. Infrared bands at 1023 cm−1 are assigned to the (SO4)2− ν1 symmetric stretching mode, and infrared bands at 1052, 1110 and 1132 cm−1 assigned to (SO4)2− ν3 antisymmetric stretching modes, confirming the presence of the sulphate anion in the tangdanite structure. Raman bands at 593 and 628 cm−1 are attributed to the (SO4)2− ν4 bending modes. Low-intensity Raman bands found at 457 and 472 cm−1 are assigned to the (AsO4)3− ν2 bending modes. A comparison is made with the previously obtained spectral data on the discredited mineral clinotyrolite.