Characterization of entanglement transformation via group representation theory

Entanglement transformation of composite quantum systems is investigated in the context of group representation theory. Representation of the direct product group SL(2, C) circle times SL(2, C), composed of local operators acting on the binary composite system, is realized in the four-dimensional complex space in terms of a set of novel bases that are pseudo-orthonormalized. The two-to-one homomorphism is then established for the group SL(2, C) circle times SL(2, C) onto the SO(4, C). It is shown that the resulting representation theory leads to the complete characterization for the entanglement transformation of the binary composite system.

Extinction of lean near-limit methane/air flames at elevated pressures under normal- and reduced-gravity

perimentally at evaluated pressures and under normal- and micro-gravity conditions utilizing the 3.5 s drop tower of the National Microgravity Laboratory of China. The results showed that under micro-gravity conditions the natural convection is minimized and the flames become more planar and symmetric compared to normal gravity. In both normal- and micro-gravity experiments and for a given strain rate and fuel concentration, the flame luminosity was found to enhance as the pressure increases. On the other hand, at a given pressure, the flame luminosity was determined to weaken as the strain rate decreases. At a given strain rate, the fuel concentration at extinction was found to vary non-monotonically with pressure, namely it first increases and subsequently decreases with pressure. The limit fuel concentration peaks around 3 and 4 atm under normal- and micro-gravity, respectively. The extinction limits measured at micro-gravity were in good agreement with predictions obtained through detailed numerical simulations but they are notably lower compared to the data obtained under normal gravity. The simulations confirmed the non-monotonic variation of flammability limits with pressure, in agreement with previous studies. Sensitivity analysis showed that for pressures between one and 5 atm, the near-limit flame response is dominated by the competition between the main branching, H + O2 ? OH + O, and the pressure sensitive termination, H+O2+M? HO2 + M, reaction. However, for pressures greater than 5 atm it was determined that the HO2 kinetics result in further chain branching in a way that is analogous to the third explosion limit of H2/O2 mixtures. 2010 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Influence of structure and lonic radius on solubility limit in the Mg-Re systems

The relationship between structure, ionic radius and electronegativity and solubility of the various rare-earth elements in Mg was studied. It is found that light RE(La-Sm, Eu, Yb) have more complicated phase relation with Mg but the heavy RE(Gd-Lu, Sc) have the similar crystal structure with magnesium. Also it is found that the less electronegativity difference between Mg and RE is, the more solubility limit of RE in Mg is. The fact of the RE solubility decreased in magnesium with lowering temperature suggests that there is a possibility of Mg supersaturated solid solution formation and it will decomposition during aging. According to the rule, an megnesium alloy with higher strength feature was developed. Their mechanical properties are UTS 347MPa, YTS 290MPa and elongation 12.5% at room temperature.

Theoretical calculation of Flory-Huggins and scattering interaction parameters by means of the lattice fluid theory for PVME/PSD blends

By fitting the spinodals of poly(vinyl methyl ether)/deuterated polystyrene (PVME/PSD) systems, the adjustable parameters epsilon (12)* and delta epsilon* in the Sanchez-Balasz lattice fluid (SBLF) theory could be determined for different molecular weights. According to these parameters, Flory-Huggins and scattering interaction parameters were calculated for PVME/PSD with different molecular weights by means of the SELF theory. From our calculation, Flory-Huggins and scattering interaction parameters are both Linearly dependent on the reciprocal of the temperature, and almost linearly on the concentration of PSD. Compared with the scattering interaction parameters, the Flory-Huggins interaction parameters decreased more slowly with an increase in the concentration for all three series of blends.

Application of the Sanchez-Lacombe lattice fluid theory to the system pvme/ps and model calculations

Cloud point curves reported in the literature for five representatives of the system poly(vinyl methyl ether)/polystyrene were evaluated theoretically by means of the Sanchez-Lacombe lattice fluid theory. The measured phase separation behavior can be described within experimental error using only one adjustable parameter (quantifying the interaction between the unlike mers). The Flory-Huggins interaction parameters calculated from this theoretical description depend in good approximation linearly on composition (volume fractions) and on the inverse temperature. An evaluation of these data yields a maximum heat effect which is almost one order of magnitude less (ca. -0.25 J/cm(3)) than obtained via Hess's cycle (dissolution of the components and of the blend) from calorimetric measurements. Model calculations on the basis of the present theory demonstrate that the critical points shift to a different extent upon a certain relative change in the molar mass of the blend components. The sensitivity of the calculated phase diagrams against changes in the scaling parameter decreases in the following order: interaction energies between unlike mers, differences in the scaling temperatures, pressures and densities.

Getting Constitutional Theory into Proportion: A Matter of Interpretation?

Gibbs, N., Getting Constitutional Theory into Proportion: A Matter of Interpretation?, Oxford Journal of Legal Studies, 27 (1), 175-191. RAE2008

AIRSTREAM: A Neural Network Model of Auditory Scene Analysis and Source Segregation

Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an "auditory scene analysis" enables the brain to solve the cocktail party problem. A neural network model of auditory scene analysis, called the AIRSTREAM model, is presented to propose how the brain accomplishes this feat. The model clarifies how the frequency components that correspond to a give acoustic source may be coherently grouped together into distinct streams based on pitch and spatial cues. The model also clarifies how multiple streams may be distinguishes and seperated by the brain. Streams are formed as spectral-pitch resonances that emerge through feedback interactions between frequency-specific spectral representaion of a sound source and its pitch. First, the model transforms a sound into a spatial pattern of frequency-specific activation across a spectral stream layer. The sound has multiple parallel representations at this layer. A sound's spectral representation activates a bottom-up filter that is sensitive to harmonics of the sound's pitch. The filter activates a pitch category which, in turn, activate a top-down expectation that allows one voice or instrument to be tracked through a noisy multiple source environment. Spectral components are suppressed if they do not match harmonics of the top-down expectation that is read-out by the selected pitch, thereby allowing another stream to capture these components, as in the "old-plus-new-heuristic" of Bregman. Multiple simultaneously occuring spectral-pitch resonances can hereby emerge. These resonance and matching mechanisms are specialized versions of Adaptive Resonance Theory, or ART, which clarifies how pitch representations can self-organize durin learning of harmonic bottom-up filters and top-down expectations. The model also clarifies how spatial location cues can help to disambiguate two sources with similar spectral cures. Data are simulated from psychophysical grouping experiments, such as how a tone sweeping upwards in frequency creates a bounce percept by grouping with a downward sweeping tone due to proximity in frequency, even if noise replaces the tones at their interection point. Illusory auditory percepts are also simulated, such as the auditory continuity illusion of a tone continuing through a noise burst even if the tone is not present during the noise, and the scale illusion of Deutsch whereby downward and upward scales presented alternately to the two ears are regrouped based on frequency proximity, leading to a bounce percept. Since related sorts of resonances have been used to quantitatively simulate psychophysical data about speech perception, the model strengthens the hypothesis the ART-like mechanisms are used at multiple levels of the auditory system. Proposals for developing the model to explain more complex streaming data are also provided.

Adaptive Neural Networks for Control of Movement Trajectories Invariant under Speed and Force Rescaling

This article describes two neural network modules that form part of an emerging theory of how adaptive control of goal-directed sensory-motor skills is achieved by humans and other animals. The Vector-Integration-To-Endpoint (VITE) model suggests how synchronous multi-joint trajectories are generated and performed at variable speeds. The Factorization-of-LEngth-and-TEnsion (FLETE) model suggests how outflow movement commands from a VITE model may be performed at variable force levels without a loss of positional accuracy. The invariance of positional control under speed and force rescaling sheds new light upon a familiar strategy of motor skill development: Skill learning begins with performance at low speed and low limb compliance and proceeds to higher speeds and compliances. The VITE model helps to explain many neural and behavioral data about trajectory formation, including data about neural coding within the posterior parietal cortex, motor cortex, and globus pallidus, and behavioral properties such as Woodworth's Law, Fitts Law, peak acceleration as a function of movement amplitude and duration, isotonic arm movement properties before and after arm-deafferentation, central error correction properties of isometric contractions, motor priming without overt action, velocity amplification during target switching, velocity profile invariance across different movement distances, changes in velocity profile asymmetry across different movement durations, staggered onset times for controlling linear trajectories with synchronous offset times, changes in the ratio of maximum to average velocity during discrete versus serial movements, and shared properties of arm and speech articulator movements. The FLETE model provides new insights into how spina-muscular circuits process variable forces without a loss of positional control. These results explicate the size principle of motor neuron recruitment, descending co-contractive compliance signals, Renshaw cells, Ia interneurons, fast automatic reactive control by ascending feedback from muscle spindles, slow adaptive predictive control via cerebellar learning using muscle spindle error signals to train adaptive movement gains, fractured somatotopy in the opponent organization of cerebellar learning, adaptive compensation for variable moment-arms, and force feedback from Golgi tendon organs. More generally, the models provide a computational rationale for the use of nonspecific control signals in volitional control, or "acts of will", and of efference copies and opponent processing in both reactive and adaptive motor control tasks.

Fuzzy ART: An Adaptive Resonance Algorithm for Rapid, Stable Classification of Analog Patterns

The Fuzzy ART system introduced herein incorporates computations from fuzzy set theory into ART 1. For example, the intersection (n) operator used in ART 1 learning is replaced by the MIN operator (A) of fuzzy set theory. Fuzzy ART reduces to ART 1 in response to binary input vectors, but can also learn stable categories in response to analog input vectors. In particular, the MIN operator reduces to the intersection operator in the binary case. Learning is stable because all adaptive weights can only decrease in time. A preprocessing step, called complement coding, uses on-cell and off-cell responses to prevent category proliferation. Complement coding normalizes input vectors while preserving the amplitudes of individual feature activations.

Fuzzy ART: Fast Stable Learning and Categorization of Analog Patterns by an Adaptive Resonance System

A Fuzzy ART model capable of rapid stable learning of recognition categories in response to arbitrary sequences of analog or binary input patterns is described. Fuzzy ART incorporates computations from fuzzy set theory into the ART 1 neural network, which learns to categorize only binary input patterns. The generalization to learning both analog and binary input patterns is achieved by replacing appearances of the intersection operator (n) in AHT 1 by the MIN operator (Λ) of fuzzy set theory. The MIN operator reduces to the intersection operator in the binary case. Category proliferation is prevented by normalizing input vectors at a preprocessing stage. A normalization procedure called complement coding leads to a symmetric theory in which the MIN operator (Λ) and the MAX operator (v) of fuzzy set theory play complementary roles. Complement coding uses on-cells and off-cells to represent the input pattern, and preserves individual feature amplitudes while normalizing the total on-cell/off-cell vector. Learning is stable because all adaptive weights can only decrease in time. Decreasing weights correspond to increasing sizes of category "boxes". Smaller vigilance values lead to larger category boxes. Learning stops when the input space is covered by boxes. With fast learning and a finite input set of arbitrary size and composition, learning stabilizes after just one presentation of each input pattern. A fast-commit slow-recode option combines fast learning with a forgetting rule that buffers system memory against noise. Using this option, rare events can be rapidly learned, yet previously learned memories are not rapidly erased in response to statistically unreliable input fluctuations.

Cortical Dynamics of Visual Motion Perception: Short-Range and Long-Range Apparent Motion

This article describes further evidence for a new neural network theory of biological motion perception. The theory clarifies why parallel streams Vl --> V2, Vl --> MT, and Vl --> V2 --> MT exist for static form and motion form processing among the areas Vl, V2, and MT of visual cortex. The theory suggests that the static form system (Static BCS) generates emergent boundary segmentations whose outputs are insensitive to direction-ofcontrast and insensitive to direction-of-motion, whereas the motion form system (Motion BCS) generates emergent boundary segmentations whose outputs are insensitive to directionof-contrast but sensitive to direction-of-motion. The theory is used to explain classical and recent data about short-range and long-range apparent motion percepts that have not yet been explained by alternative models. These data include beta motion; split motion; gamma motion and reverse-contrast gamma motion; delta motion; visual inertia; the transition from group motion to element motion in response to a Ternus display as the interstimulus interval (ISI) decreases; group motion in response to a reverse-contrast Ternus display even at short ISIs; speed-up of motion velocity as interflash distance increases or flash duration decreases; dependence of the transition from element motion to group motion on stimulus duration and size; various classical dependencies between flash duration, spatial separation, ISI, and motion threshold known as Korte's Laws; dependence of motion strength on stimulus orientation and spatial frequency; short-range and long-range form-color interactions; and binocular interactions of flashes to different eyes.

Becoming a CEO: an exploration of the theory and practice of effective organisational leadership

This Thesis is an exploration of potential enhancement in effectiveness, personally, professionally and organisationally through the use of Theory as an Apparatus of Thought. Enhanced effectiveness was sought by the practitioner (Subject), while in transition to becoming Chief Executive of his organization. The introduction outlines the content and the structure of the University College Cork DBA. Essay One outlines what Theory is, what Adult Mental Development is and an exploration of Theories held in the Authors past professional practice. Immunity to change is also reflected on. Essay Two looks at the construct of the key Theories used in the Thesis. Prof. Robert Kegan’s Theory of Adult Mental Development was used to aid the generation of insight. The other key Theories used were The Theory of The Business, Theory of the Co‐operative and a Theory of Organisational Leadership. Essay Three explores the application of the key Theories in a professional setting. The findings of the Thesis were that the subject was capable of dealing with increased environmental complexity and uncertainty by using Theory as an Apparatus of Thought, which in turn enhanced personal, professional and organisational effectiveness. This was achieved by becoming more aware of the Theories held by the practitioner, the experiences from the application of those Theories, which then led to greater insight. The author also found that a detailed understanding of the Theory of the Business and a Theory of Leadership would support any new CEO in the challenging early part of their tenure.

Theory of elasticity and electric polarization effects in the group-III nitrides

In this work, the properties of strained tetrahedrally bonded materials are explored theoretically, with special focus on group-III nitrides. In order to do so, a multiscale approach is taken: accurate quantitative calculations of material properties are carried out in a quantum first-principles frame, for small systems. These properties are then extrapolated and empirical methods are employed to make predictions for larger systems, such as alloys or nanostructures. We focus our attention on elasticity and electric polarization in semiconductors. These quantities serve as input for the calculation of the optoelectronic properties of these systems. Regarding the methods employed, our first-principles calculations use highly- accurate density functional theory (DFT) within both standard Kohn-Sham and generalized (hybrid functional) Kohn-Sham approaches. We have developed our own empirical methods, including valence force field (VFF) and a point-dipole model for the calculation of local polarization and local polarization potential. Our local polarization model gives insight for the first time to local fluctuations of the electric polarization at an atomistic level. At the continuum level, we have studied composition-engineering optimization of nitride nanostructures for built-in electrostatic field reduction, and have developed a highly efficient hybrid analytical-numerical staggered-grid computational implementation of continuum elasticity theory, that is used to treat larger systems, such as quantum dots.

Anticipatory vigilance: A classic grounded theory of risk reduction and management in the perioperative setting

This research aimed to investigate the main concern facing nurses in minimising risk within the perioperative setting and to generate an explanatory substantive theory of how they resolve this through anticipatory vigilance. In the context of the perioperative setting, nurses encounter challenges in minimising risks for their patients on a continuous basis. Current explanations of minimising risk in the perioperative setting offers insights into how perioperative nurses undertake their work. Currently research in minimising risk is broadly related to dealing with errors as opposed to preventing them. To date, little is known about how perioperative nurses practice and maintain safety. This study was guided by the principles of classic grounded theory as described by Glaser (1978, 1998, 2001). Data was collected through individual unstructured interviews with thirty seven perioperative nurses (with varying lengths of experiences of working in the area) and thirty three hours of non-participant observation within eight different perioperative settings in the Republic of Ireland. Data was simultaneously collected and analysed. The theory of anticipatory vigilance emerged as the pattern of behaviour through which nurse’s deal with their main concern of minimising risk in a high risk setting. Anticipatory vigilance is enacted through orchestrating, routinising and momentary adapting within a spirit of trusting relations within the substantive area of the perioperative setting. This theory of offers an explanation on how nurses resolve their main concern of minimising risk within the perioperative setting. The theory of anticipatory vigilance will be useful to nurses in providing a comprehensive framework of explanation and understanding on how nurses deal with minimising risk in the perioperative setting. The theory links perioperative nursing, risk and vigilance together. Clinical improvements through understanding and awareness of the theory of anticipatory vigilance will result in an improved quality environment, leading to safe patient outcomes.

Beyond simple imaging with energetic beams – nanopatterning, correlative microscopy and statistical analysis of inclusions

Electron microscopy (EM) has advanced in an exponential way since the first transmission electron microscope (TEM) was built in the 1930’s. The urge to ‘see’ things is an essential part of human nature (talk of ‘seeing is believing’) and apart from scanning tunnel microscopes which give information about the surface, EM is the only imaging technology capable of really visualising atomic structures in depth down to single atoms. With the development of nanotechnology the demand to image and analyse small things has become even greater and electron microscopes have found their way from highly delicate and sophisticated research grade instruments to key-turn and even bench-top instruments for everyday use in every materials research lab on the planet. The semiconductor industry is as dependent on the use of EM as life sciences and pharmaceutical industry. With this generalisation of use for imaging, the need to deploy advanced uses of EM has become more and more apparent. The combination of several coinciding beams (electron, ion and even light) to create DualBeam or TripleBeam instruments for instance enhances the usefulness from pure imaging to manipulating on the nanoscale. And when it comes to the analytic power of EM with the many ways the highly energetic electrons and ions interact with the matter in the specimen there is a plethora of niches which evolved during the last two decades, specialising in every kind of analysis that can be thought of and combined with EM. In the course of this study the emphasis was placed on the application of these advanced analytical EM techniques in the context of multiscale and multimodal microscopy – multiscale meaning across length scales from micrometres or larger to nanometres, multimodal meaning numerous techniques applied to the same sample volume in a correlative manner. In order to demonstrate the breadth and potential of the multiscale and multimodal concept an integration of it was attempted in two areas: I) Biocompatible materials using polycrystalline stainless steel and II) Semiconductors using thin multiferroic films. I) The motivation to use stainless steel (316L medical grade) comes from the potential modulation of endothelial cell growth which can have a big impact on the improvement of cardio-vascular stents – which are mainly made of 316L – through nano-texturing of the stent surface by focused ion beam (FIB) lithography. Patterning with FIB has never been reported before in connection with stents and cell growth and in order to gain a better understanding of the beam-substrate interaction during patterning a correlative microscopy approach was used to illuminate the patterning process from many possible angles. Electron backscattering diffraction (EBSD) was used to analyse the crystallographic structure, FIB was used for the patterning and simultaneously visualising the crystal structure as part of the monitoring process, scanning electron microscopy (SEM) and atomic force microscopy (AFM) were employed to analyse the topography and the final step being 3D visualisation through serial FIB/SEM sectioning. II) The motivation for the use of thin multiferroic films stems from the ever-growing demand for increased data storage at lesser and lesser energy consumption. The Aurivillius phase material used in this study has a high potential in this area. Yet it is necessary to show clearly that the film is really multiferroic and no second phase inclusions are present even at very low concentrations – ~0.1vol% could already be problematic. Thus, in this study a technique was developed to analyse ultra-low density inclusions in thin multiferroic films down to concentrations of 0.01%. The goal achieved was a complete structural and compositional analysis of the films which required identification of second phase inclusions (through elemental analysis EDX(Energy Dispersive X-ray)), localise them (employing 72 hour EDX mapping in the SEM), isolate them for the TEM (using FIB) and give an upper confidence limit of 99.5% to the influence of the inclusions on the magnetic behaviour of the main phase (statistical analysis).