Rhetoric in the language of real estate marketing

“Des. Res.”, “rarely available”, “viewing essential” – these are all part of the peculiar parlance of housing advertisements which contain a heady mix of euphemism, hyperbole and superlative. Of interest is whether the selling agent’s penchant for rhetoric is spatially uniform or whether there are variations across the urban system. We are also interested in how the use of superlatives varies over the market cycle and over the selling season. For example, are estate agents more inclined to use hyperbole when the market is buoyant or when it is flat, and does it matter whether a house is marketed in the summer or winter? This paper attempts to answer these questions by applying textual analysis to a unique dataset of 49,926 records of real estate transactions in the Strathclyde conurbation over the period 1999 to 2006. The analysis opens up a new avenue of research into the use of real estate rhetoric and its interaction with agency behaviour and market dynamics

Metal plasma immersion ion implantation and deposition using polymer substrates

This thesis investigates the application of plasma immersion ion implantation (PIII) to polymers. PIII requires that a high negative potential be applied to the surface of the material while it is immersed in a plasma. This presents a problem for insulating materials such as polymers, since the implanting ions carry charge to the surface, resulting in a charge accumulation that effectively neutralises the applied potential. This causes the plasma sheath at the surface to collapse a short time after the potential is applied. Measurements of the sheath dynamics, including the collapsing sheath, are performed using an electric probe. The results are compared to theoretical models of the plasma sheath based on the Child-Langmuir law for high voltage sheaths. The theoretical model predicts well the sheath dynamics for conductive substrates. For insulating substrates the model can account for the experimental observations if the secondary electron coefficient is modified, justified on the basis of the poly-energetic nature of the implanting ions. If a conductive film is applied to the insulator surface the problem of charge accumulation can be avoided without compromising the effectiveness of PIII. The requirement for the film is that it be conductive, yet transparent to the incident ions. Experimental results are presented which confirm the effectiveness of the method. Theoretical estimates of the surface potential show that a film of the order of 5nm thickness can effectively circumvent the charge accumulation problem. Efforts to produce and characterise such a film form the final two chapters of this thesis. The optimal thickness is determined to be near the percolation threshold, where a marked increase in conductivity occurs. Spectroscopic ellipsometry is shown to be an excellent method to determine the film thickness and percolation threshold non-invasively. Throughout this work cathodic vacuum arcs are used to deposit thin films and as a source of metal plasmas. The design and construction of a pulsed cathodic vacuum arc forms a significant part of this thesis. Investigations of the cathode spots and power supply requirements are presented

A modern retrospective on probabilistic numerics

This article attempts to place the emergence of probabilistic numerics as a mathematical–statistical research field within its historical context and to explore how its gradual development can be related both to applications and to a modern formal treatment. We highlight in particular the parallel contributions of Sul′din and Larkin in the 1960s and how their pioneering early ideas have reached a degree of maturity in the intervening period, mediated by paradigms such as average-case analysis and information-based complexity. We provide a subjective assessment of the state of research in probabilistic numerics and highlight some difficulties to be addressed by future works

The ridgelet prior: A covariance function approach to prior specification for bayesian neural networks

Bayesian neural networks attempt to combine the strong predictive performance of neural networks with formal quantification of uncertainty associated with the predictive output in the Bayesian framework. However, it remains unclear how to endow the parameters of the network with a prior distribution that is meaningful when lifted into the output space of the network. A possible solution is proposed that enables the user to posit an appropriate Gaussian process covariance function for the task at hand. Our approach constructs a prior distribution for the parameters of the network, called a ridgelet prior, that approximates the posited Gaussian process in the output space of the network. In contrast to existing work on the connection between neural networks and Gaussian processes, our analysis is non-asymptotic, with finite sample-size error bounds provided. This establishes the universality property that a Bayesian neural network can approximate any Gaussian process whose covariance function is sufficiently regular. Our experimental assessment is limited to a proof-of-concept, where we demonstrate that the ridgelet prior can out-perform an unstructured prior on regression problems for which a suitable Gaussian process prior can be provided

Frequency evaluation of the doubly forbidden 1S0→3P0^1S_0\to ^3P_0 transition in bosonic 174^{174}Yb

We report an uncertainty evaluation of an optical lattice clock based on the $^1S_0\leftrightarrow^3P_0$ transition in the bosonic isotope $^{174}$Yb by use of magnetically induced spectroscopy. The absolute frequency of the $^1S_0\leftrightarrow^3P_0$ transition has been determined through comparisons with optical and microwave standards at NIST. The weighted mean of the evaluations is $\nu$($^{174}$Yb)=518 294 025 309 217.8(0.9) Hz. The uncertainty due to systematic effects has been reduced to less than 0.8 Hz, which represents $1.5\times10^{-15}$ in fractional frequency.Comment: 4 pages, 3 figure -Submitted to PRA Rapid Communication

The Apriori Stochastic Dependency Detection (ASDD) algorithm for learning Stochastic logic rules

Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environment. ASDD is based on features of the Apriori algorithm for mining association rules in large databases of sales transactions [1] and the MSDD algorithm for discovering stochastic dependencies in multiple streams of data [15]. Once these rules have been acquired the Precedence algorithm assigns operator precedence when two or more rules matching the input data are applicable to the same output variable. These algorithms currently learn propositional rules, with future extensions aimed towards learning first-order models. We show that stochastic rules produced by this algorithm are capable of reproducing an accurate world model in a simple predator-prey environment

Measurement of excited-state transitions in cold calcium atoms by direct femtosecond frequency-comb spectroscopy

We apply direct frequency-comb spectroscopy, in combination with precision cw spectroscopy, to measure the ${\rm 4s4p} ^3P_1 \to {\rm 4s5s} ^3S_1$ transition frequency in cold calcium atoms. A 657 nm ultrastable cw laser was used to excite atoms on the narrow ($\gamma \sim 400$ Hz) ${\rm 4s^2} ^1S_0 \to {\rm 4s4p} ^3P_1$ clock transition, and the direct output of the frequency comb was used to excite those atoms from the ${\rm 4s4p} ^3P_1$ state to the ${\rm 4s5s} ^3S_1$ state. The resonance of this second stage was detected by observing a decrease in population of the ground state as a result of atoms being optically pumped to the metastable ${\rm 4s4p} ^3P_{0,2}$ states. The ${\rm 4s4p} ^3P_1 \to {\rm 4s5s} ^3S_1$ transition frequency is measured to be $\nu = 489 544 285 713(56)$ kHz; which is an improvement by almost four orders of magnitude over the previously measured value. In addition, we demonstrate spectroscopy on magnetically trapped atoms in the ${\rm 4s4p} ^3P_2$ state.Comment: 4 pages 5 figure

Quenched Narrow-Line Laser Cooling of 40Ca to Near the Photon Recoil Limit

We present a cooling method that should be generally applicable to atoms with narrow optical transitions. This technique uses velocity-selective pulses to drive atoms towards a zero-velocity dark state and then quenches the excited state to increase the cooling rate. We demonstrate this technique of quenched narrow-line cooling by reducing the 1-D temperature of a sample of neutral 40Ca atoms. We velocity select and cool with the 1S0(4s2) to 3P1(4s4p) 657 nm intercombination line and quench with the 3P1(4s4p) to 1S0(4s5s) intercombination line at 553 nm, which increases the cooling rate eight-fold. Limited only by available quenching laser power, we have transferred 18 % of the atoms from our initial 2 mK velocity distribution and achieved temperatures as low as 4 microK, corresponding to a vrms of 2.8 cm/s or 2 recoils at 657 nm. This cooling technique, which is closely related to Raman cooling, can be extended to three dimensions.Comment: 5 pages, 4 figures; Submitted to PRA Rapid Communication