Geochemistry-based coral palaeoclimate studies and the potential of ‘non-traditional’ (non-massive Porites) corals : recent developments and future progression

Understanding the natural variability of the Earth's climate system and accurately identifying potential anthropogenic influences requires long term, geographically distributed records of key climate indicators, such as temperature and precipitation that extend prior to the last 400. years of the Holocene. Reef corals provide an excellent source of high resolution climate records, and importantly represent the tropical marine environment where palaeoclimate data are urgently required. Recent decades have seen significant improvement in our understanding of coral biomineralisation, the associated uptake of geochemical proxies and methods of identifying and understanding the effects of both early and late, post depositional diagenetic alteration. These processes all have significant implications for interpreting geochemical proxies relevant to palaeoclimatic reconstructions. This paper reviews the current 'state of the art' in terms of coral based palaeoclimate reconstructions and highlights a key remaining problem. The majority of coral based palaeoclimate research has been derived from massive colonies of Porites. However, massive Porites are not globally abundant and may not provide material of a particular age of interest in those regions where they are present. Therefore, there is great potential for alternate coral genera to act as complimentary climate archives. While it remains critical to consider five key factors - vital effects, differential growth morphologies, geochemical heterogeneity in the skeletal ultrastructure, transfer equation selection and diagenetic screening of skeletal material - in order to allow the highest level of accuracy in coral palaeoclimate reconstructions, it is also important to develop alternate taxa for palaeoclimate studies in regions where Porites colonies are absent or rare. Currently as many as nine genera other than Porites have proven at least limited utility in palaeothermometry, most of which are found in the Atlantic/Caribbean region where massive Porites do not exist. Even branching taxa such as Acropora have significant potential to preserve environmental archives. Increasing this capability will greatly expand the number of potential geochemical archives available for longer term temporal records of palaeoclimate.

Onset of Mediterranean outflow into the North Atlantic

Sediments cored along the southwestern Iberian margin during Integrated Ocean Drilling Program Expedition 339 provide constraints on Mediterranean Outflow Water (MOW) circulation patterns from the Pliocene epoch to the present day. After the Strait of Gibraltar opened (5.33 million years ago), a limited volume of MOW entered the Atlantic. Depositional hiatuses indicate erosion by bottom currents related to higher volumes of MOW circulating into the North Atlantic, beginning in the late Pliocene. The hiatuses coincide with regional tectonic events and changes in global thermohaline circulation (THC). This suggests that MOW influenced Atlantic Meridional Overturning Circulation (AMOC), THC, and climatic shifts by contributing a component of warm, saline water to northern latitudes while in turn being influenced by plate tectonics.

Lady Nugent and Tom Cringle on the veranda : early nineteenth century observations on a Caribbean architectural feature

This study of the veranda as seen through the eyes of Lady Maria Nugent and Michael Scott, alias Tom Cringle, clearly demonstrates the important role that the piazza, as it was then more commonly known, played in the life of early nineteenth century Caribbean colonial society. The popularity of the veranda throughout the region, in places influenced by different European as well as African cultures, and among all classes of people, suggests that the appeal of this typical feature was based on something more than architectural fashion. A place of relative comfort in hot weather, the veranda is also a space at the interface of indoors and outdoors which allows for a wide variety of uses, for solitary or small or large group activities, many of which were noted by Nugent and Scott. Quintessentially, the veranda is a place in which to relax and take pleasure, not least of which is the enjoyment of the prospect, be it a panoramic view, a peaceful garden or a lively street scene. Despite the great changes in the nature of society, in the Caribbean and in many other parts of the world, the veranda and related structures such as the balcony continue to play at least as important a role in daily life as they did two centuries ago. The veranda of today’s Californian or Australian bungalow, and the balcony of the apartment block in the residential area of the modern city are among the contemporary equivalents of the lower and upper piazzas of Lady Nugent’s and Tom Cringle’s day.

Volcanic sulphate and Arctic dust plumes over the North Atlantic Ocean

High time resolution aerosol mass spectrometry measurements were conducted during a field campaign at Mace Head Research Station, Ireland, in June 2007. Observations on one particular day of the campaign clearly indicated advection of aerosol from volcanoes and desert plains in Iceland which could be traced with NOAA Hysplit air mass back trajectories and satellite images. In conjunction with this event, elevated levels of sulphate and light absorbing particles were encountered at Mace Head. While sulphate concentration was continuously increasing, nitrate levels remained low indicating no significant contribution from anthropogenic pollutants. Sulphate concentration increased about 3.8 g/m3 in comparison with the background conditions. Corresponding sulphur flux from volcanic emissions was estimated to about 0.3 TgS/yr, suggesting that a large amount of sulphur released from Icelandic volcanoes may be distributed over distances larger than 1000 km. Overall, our results corroborate that transport of volcanogenic sulphate and dust particles can significantly change the chemical composition, size distribution, and optical properties of aerosol over the North Atlantic Ocean and should be considered accordingly by regional climate models.

Large margin vector quantization

In this paper we describe the Large Margin Vector Quantization algorithm (LMVQ), which uses gradient ascent to maximise the margin of a radial basis function classifier. We present a derivation of the algorithm, which proceeds from an estimate of the class-conditional probability densities. We show that the key behaviour of Kohonen's well-known LVQ2 and LVQ3 algorithms emerge as natural consequences of our formulation. We compare the performance of LMVQ with that of Kohonen's LVQ algorithms on an artificial classification problem and several well known benchmark classification tasks. We find that the classifiers produced by LMVQ attain a level of accuracy that compares well with those obtained via LVQ1, LVQ2 and LVQ3, with reduced storage complexity. We indicate future directions of enquiry based on the large margin approach to Learning Vector Quantization.

Boosting the margin: A new explanation for the effectiveness of voting methods

One of the surprising recurring phenomena observed in experiments with boosting is that the test error of the generated classifier usually does not increase as its size becomes very large, and often is observed to decrease even after the training error reaches zero. In this paper, we show that this phenomenon is related to the distribution of margins of the training examples with respect to the generated voting classification rule, where the margin of an example is simply the difference between the number of correct votes and the maximum number of votes received by any incorrect label. We show that techniques used in the analysis of Vapnik's support vector classifiers and of neural networks with small weights can be applied to voting methods to relate the margin distribution to the test error. We also show theoretically and experimentally that boosting is especially effective at increasing the margins of the training examples. Finally, we compare our explanation to those based on the bias-variance decomposition.

Exponentiated gradient algorithms for conditional random fields and max-margin Markov Networks

Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of parameters in these models is therefore an important problem, and becomes a key factor when learning from very large data sets. This paper describes exponentiated gradient (EG) algorithms for training such models, where EG updates are applied to the convex dual of either the log-linear or max-margin objective function; the dual in both the log-linear and max-margin cases corresponds to minimizing a convex function with simplex constraints. We study both batch and online variants of the algorithm, and provide rates of convergence for both cases. In the max-margin case, O(1/ε) EG updates are required to reach a given accuracy ε in the dual; in contrast, for log-linear models only O(log(1/ε)) updates are required. For both the max-margin and log-linear cases, our bounds suggest that the online EG algorithm requires a factor of n less computation to reach a desired accuracy than the batch EG algorithm, where n is the number of training examples. Our experiments confirm that the online algorithms are much faster than the batch algorithms in practice. We describe how the EG updates factor in a convenient way for structured prediction problems, allowing the algorithms to be efficiently applied to problems such as sequence learning or natural language parsing. We perform extensive evaluation of the algorithms, comparing them to L-BFGS and stochastic gradient descent for log-linear models, and to SVM-Struct for max-margin models. The algorithms are applied to a multi-class problem as well as to a more complex large-scale parsing task. In all these settings, the EG algorithms presented here outperform the other methods.

Exponentiated gradient algorithms for large-margin structured classification

We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes supervised training of Markov random fields and weighted context-free grammars as special cases. We describe an algorithm that solves the large-margin optimization problem defined in [12], using an exponential-family (Gibbs distribution) representation of structured objects. The algorithm is efficient—even in cases where the number of labels y is exponential in size—provided that certain expectations under Gibbs distributions can be calculated efficiently. The method for structured labels relies on a more general result, specifically the application of exponentiated gradient updates [7, 8] to quadratic programs.

Margin-adaptive model selection in statistical learning

A classical condition for fast learning rates is the margin condition, first introduced by Mammen and Tsybakov. We tackle in this paper the problem of adaptivity to this condition in the context of model selection, in a general learning framework. Actually, we consider a weaker version of this condition that allows one to take into account that learning within a small model can be much easier than within a large one. Requiring this “strong margin adaptivity” makes the model selection problem more challenging. We first prove, in a general framework, that some penalization procedures (including local Rademacher complexities) exhibit this adaptivity when the models are nested. Contrary to previous results, this holds with penalties that only depend on the data. Our second main result is that strong margin adaptivity is not always possible when the models are not nested: for every model selection procedure (even a randomized one), there is a problem for which it does not demonstrate strong margin adaptivity.

From the margin to the centre : towards an art strategy for the ethnic enclaves in the city

Sunnybank represents a distinctly Australian take on the classic ‘Chinatown’ – or indeed other ethic community enclaves such as ‘little Italy’, ‘little Bombay’, ‘little Athens’ and so on. In the Northern Hemisphere these tended to grow up in the dense working class neighbourhoods of industrial cities, especially in port cities like Liverpool, London, New York and San Francisco. The existing Chinatowns of Sydney and Melbourne, and to some extent Brisbane’s Fortitude Valley, are of this variety. In the late 1970s, with the growth of suburbanisation and the de-industrialisation and consequent dereliction of the ‘inner city’, these ethnic communities were one of the few signs of life in the city. Apart from the daily commute into the CBD, business with the city council or a trip to the big shopping streets these areas were one of the few reasons for visiting city centres stigmatised by urban decay and petty crime.

Undrained sediment loading key to long-runout submarine mass movements : evidence from the Caribbean Volcanic Arc

Long undersea debris runout can be facilitated by a boundary layer formed by weak marine sediments under a moving slide mass. Undrained loading of such offshore sediment results in a profound drop of basal shear resistance, compared to subaerial shear resistance, enabling long undersea runout. Thus large long-runout submarine landslides are not truly enigmatic (Voight and Elsworth 1992, 1997), but are understandable in terms of conventional geotechnical principles. A corollary is that remoulded undrained strength, and not friction angle, should be used for basal resistance in numerical simulations. This hypothesis is testable via drilling and examining the structure at the soles of undersea debris avalanches for indications of incorporation of sheared marine sediments, by tests of soil properties, and by simulations. Such considerations of emplacement process are an aim of ongoing research in the Lesser Antilles (Caribbean Sea), where multiple offshore debris avalanche and dome-collapse debris deposits have been identified since 1999 on swath bathymetric surveys collected in five oceanographic cruises. This paper reviews the prehistoric and historic collapses that have occurred offshore of Antilles arc islands and summarizes ongoing research on emplacement processes.

‘Wide Atlantic Ocean’ : acting methods and cultural translation in mainstream theatre

A recent production of Nicholson’s Shadowlands at the Brisbane Powerhouse could have included two advertising lines: “Outspoken American-Jewish poet meets conservative British Oxford scholar” and “Emotive American Method trained actor meets contained British trained actor.” While the fusion of acting methodologies in intercultural acting has been discussed at length, little discussion has focussed on the juxtaposition of diverse acting styles in production in mainstream theatre. This paper explores how the permutation of American Method acting and a more traditional British conservatory acting in Crossbow’s August 2010 production of Shadowlands worked to add extra layers of meaning to the performance text. This sometimes inimical relationship between two acting styles had its beginnings in the rehearsal room and continued onstage. Audience reception to the play in post-performance discussions revealed the audience’s acute awareness of the transatlantic cultural tensions on stage. On one occasion, this resulted in a heated debate on cultural expression, continuing well after the event, during which audience members became co-performers in the cultural discourses of the play.

V1-inspired features induce a weighted margin in SVMs

Image representations derived from simplified models of the primary visual cortex (V1), such as HOG and SIFT, elicit good performance in a myriad of visual classification tasks including object recognition/detection, pedestrian detection and facial expression classification. A central question in the vision, learning and neuroscience communities regards why these architectures perform so well. In this paper, we offer a unique perspective to this question by subsuming the role of V1-inspired features directly within a linear support vector machine (SVM). We demonstrate that a specific class of such features in conjunction with a linear SVM can be reinterpreted as inducing a weighted margin on the Kronecker basis expansion of an image. This new viewpoint on the role of V1-inspired features allows us to answer fundamental questions on the uniqueness and redundancies of these features, and offer substantial improvements in terms of computational and storage efficiency.