The Other White Cube Project: Finding Museums Among Us

Content and context intersect to produce works of art, and visitors must have an awareness of both halves to be truly informed, engaged, and included. In 2013, I created the Other White Cube Project (OWCP) to deterritorialize curatorial practices and search for ways to disrupt divisions found in art museums—content/context, curator/viewer, cultural/personal. For the study, I concentrated on three constructivist keys to learning in museums—comfort, relevance, and intelligibility—and the project proceeded from the following premise: if visitors knew about curatorial strategies (comfort) and performed and personalized them (relevance), art museums would be more engaging, transparent, and comprehensible (intelligibility). For the study, participants engaged with curatorial practices through their refrigerator, one of the most common, curated spaces. Based on the findings, I argue that context-based programs, such as the OWCP, help visitors to interpret relationships, themes, and other curatorial elements that add intellectual depth to the museum experience

A Small BVAR-DSGE Model for Forecasting the Australian Economy

This paper estimates a small structural model of the Australian economy, designed principally for forecasting the key macroeconomic variables of output growth, underlying inflation and the cash rate. In contrast to models with purely statistical foundations, which are often used for forecasting, the Bayesian Vector Autoregressive Dynamic Stochastic General Equilibrium (BVAR-DSGE) model uses the theoretical information of a DSGE model to offset in-sample over-fitting. We follow the method of Del Negro and Schorfheide (2004) and use a variant of the small open economy DSGE model of Lubik and Schorfheide (2007) to provide prior information for the VAR. The forecasting performance of the model is competitive with benchmark models such as a Minnesota VAR and an independently estimated DSGE model.BVAR-DSGE; forecasting

Lower semicontinuity of attractors for non-autonomous dynamical systems

This paper is concerned with the lower semicontinuity of attractors for semilinear non-autonomous differential equations in Banach spaces. We require the unperturbed attractor to be given as the union of unstable manifolds of time-dependent hyperbolic solutions, generalizing previous results valid only for gradient-like systems in which the hyperbolic solutions are equilibria. The tools employed are a study of the continuity of the local unstable manifolds of the hyperbolic solutions and results on the continuity of the exponential dichotomy of the linearization around each of these solutions

Variational data assimilation using targetted random walks

The variational approach to data assimilation is a widely used methodology for both online prediction and for reanalysis (offline hindcasting). In either of these scenarios it can be important to assess uncertainties in the assimilated state. Ideally it would be desirable to have complete information concerning the Bayesian posterior distribution for unknown state, given data. The purpose of this paper is to show that complete computational probing of this posterior distribution is now within reach in the offline situation. In this paper we will introduce an MCMC method which enables us to directly sample from the Bayesian\ud posterior distribution on the unknown functions of interest, given observations. Since we are aware that these\ud methods are currently too computationally expensive to consider using in an online filtering scenario, we frame this in the context of offline reanalysis. Using a simple random walk-type MCMC method, we are able to characterize the posterior distribution using only evaluations of the forward model of the problem, and of the model and data mismatch. No adjoint model is required for the method we use; however more sophisticated MCMC methods are available\ud which do exploit derivative information. For simplicity of exposition we consider the problem of assimilating data, either Eulerian or Lagrangian, into a low Reynolds number (Stokes flow) scenario in a two dimensional periodic geometry. We will show that in many cases it is possible to recover the initial condition and model error (which we describe as unknown forcing to the model) from data, and that with increasing amounts of informative data, the uncertainty in our estimations reduces

Managing Saline Groundwater Impacts from Irrigation - Designing and Testing Emissions Trading in Coleambally Irrigation Area

Irrigated agriculture often leads to recharge to local and regional groundwater systems greater than what the systems can absorb, resulting in the development of shallow watertables causing salinity and waterlogging. Policy based on emissions trading offers one option for effective management of existing recharge externalities if effective property rights to diffuse emissions can be defined. In this paper we combine the conclusions drawn from biophysical research with economic principles underpinning emissions trading to present such a system. Allocation of net recharge contracts to irrigation farms will internalize the costs associated with saline aquifer impacts. Irrigators may reduce their compliance costs by creating or purchasing credits that reduce recharge through perennial vegetation, engineering solutions or crop rotation options. We discuss the economic impacts of adopting such a policy in the Coleambally Irrigation Area in southwestern New South Wales, Australia. We also demonstrate some of the conclusions drawn from our research using experimental economics.salinity, irrigation, recharge, tradeable emissions, cap and trade, hydrologic-economic modelling, experimental economics

Development of a low-maintenance measurement approach to continuously estimate methane emissions: a case study

The chemical breakdown of organic matter in landfills represents a significant source of methane gas (CH4). Current estimates suggest that landfills are responsible for between 3% and 19% of global anthropogenic emissions. The net CH4 emissions resulting from biogeochemical processes and their modulation by microbes in landfills are poorly constrained by imprecise knowledge of environmental constraints. The uncertainty in absolute CH4 emissions from landfills is therefore considerable. This study investigates a new method to estimate the temporal variability of CH4 emissions using meteorological and CH4 concentration measurements downwind of a landfill site in Suffolk, UK from July to September 2014, taking advantage of the statistics that such a measurement approach offers versus shorter-term, but more complex and instantaneously accurate, flux snapshots. Methane emissions were calculated from CH4 concentrations measured 700 m from the perimeter of the landfill with observed concentrations ranging from background to 46.4 ppm. Using an atmospheric dispersion model, we estimate a mean emission flux of 709 μg m−2 s−1 over this period, with a maximum value of 6.21 mg m−2 s−1, reflecting the wide natural variability in biogeochemical and other environmental controls on net site emission. The emissions calculated suggest that meteorological conditions have an influence on the magnitude of CH4 emissions. We also investigate the factors responsible for the large variability observed in the estimated CH4 emissions, and suggest that the largest component arises from uncertainty in the spatial distribution of CH4 emissions within the landfill area. The results determined using the low-maintenance approach discussed in this paper suggest that a network of cheaper, less precise CH4 sensors could be used to measure a continuous CH4 emission time series from a landfill site, something that is not practical using far-field approaches such as tracer release methods. Even though there are limitations to the approach described here, this easy, low-maintenance, low-cost method could be used by landfill operators to estimate time-averaged CH4 emissions and their impact downwind by simultaneously monitoring plume advection and CH4 concentrations

Blending the Old and the New: Qualitative Data Analysis a s Critical Thinking and Using NVivo with a Generic Approach

In this article the authors seek to make the case that qualitative data analysis can be explained within the framework of critical thinking and incorporates within this framework the role of technology – specifically NVivo. First they discuss critical thinking from the perspectives of Bloom, Adler, and Polanyi. They then link critical thinking to the concept of a general inductive approach to qualitative analysis as described by Thomas. Finally, they illustrate connections of both critical thinking and the general inductive approach to technology using NVivo screenshots

Natural Language Generation for Nature Conservation : Automating Feedback to help Volunteers identify Bumblebee Species

Publisher PD

Reducing the stress of drug administration:implications for the 3Rs

Restraint in animals is known to cause stress but is used during almost all scientific procedures in rodents, representing a major welfare and scientific issue. Administration of substances, a key part of most scientific procedures, almost always involves physical restraint of the animal. In this study, we developed a method to inject substances to rats using a non-restrained technique. We then compared the physiological, behavioral and emotional impacts of restrained versus non-restrained injection procedures. Our results highlight the negative welfare implications associated with physical restraint and demonstrate a method which can be used to avoid this. Our work shows how adopting strategies that avoid restraint can minimize a widespread source of stress in laboratory animals and improve welfare through refinement

Snake prices and crocodile appetites: Aquatic wildlife supply and demand on Tonle Sap Lake, Cambodia

Commercial trade is a major driver of over-exploitation of wild species, but the pattern of demand and how it responds to changes in supply is poorly understood. Here we explore the markets for snakes from Tonle Sap Lake in Cambodia to evaluate future exploitation scenarios, identify entry points for conservation and, more generally, to illustrate the value of multi-scale analysis of markets to traded wildlife conservation. In Cambodia, the largest driver of snake exploitation is the domestic trade in snakes as crocodile food. We estimate that farmed crocodiles consume between 2.7 and 12.2 million snakes per year. The market price for crocodiles has been in decline since 2003, which, combined with rising prices for their food, has led to a reduced frequency of feeding and closure of small farms. The large farms that generate a disproportionate amount of the demand for snakes continue to operate in anticipation of future market opportunities, and preferences for snakes could help maintain demand if market prices for crocodiles rise to pre 2003 levels. In the absence of a sustained demand from crocodile farms, it is also possible that alternative markets will develop, such as one for human snack food. The demand for snakes, however, also depends on the availability of substitute resources, principally fish. The substitutability and low price elasticity of demand offers a relatively sustainable form of consumerism. Given the nature of these market drivers, addressing consumer preferences and limiting the protection of snakes to their breeding season are likely to be the most effective tools for conservation. This study highlights the importance of understanding the structure of markets and the behaviour of consumer demand prior to implementing regulations on wildlife hunting and trade