Blue frontiers: managing the environmental costs of aquaculture

The report begins with an overview of the current status of world aquaculture. It then goes on to describe an approach for estimating the current combined biophysical resource demands of aquaculture for producer countries and regions. Following a comparison of these results with those available for other animal food production sectors the report then examines the consequences of likely future trends in production on the environmental impacts of aquaculture. Finally, the policy implications of the report’s findings are discussed along with the research agenda that should be pursued to meet the challenge of sustainable food production

Table builder problem - confidentiality for linked tables

The aim of this project is to investigate solutions to the problem of improving access to detailed survey data, while ensuring no person or organisation is likely to be identified, or otherwise put at risk of having their data disclosed, and to link general findings back to the ABS Table Builder problem. We focussed on making contributions in two main areas, namely: 1. Identification of sensitive cells in a table, 2. Maximizing data utility and minimising information loss - ensuring the table provides useful information

Improved AURA k-Nearest Neighbour approach

The k-Nearest Neighbour (kNN) approach is a widely-used technique for pattern classification. Ranked distance measurements to a known sample set determine the classification of unknown samples. Though effective, kNN, like most classification methods does not scale well with increased sample size. This is due to their being a relationship between the unknown query and every other sample in the data space. In order to make this operation scalable, we apply AURA to the kNN problem. AURA is a highly-scalable associative-memory based binary neural-network intended for high-speed approximate search and match operations on large unstructured datasets. Previous work has seen AURA methods applied to this problem as a scalable, but approximate kNN classifier. This paper continues this work by using AURA in conjunction with kernel-based input vectors, in order to create a fast scalable kNN classifier, whilst improving recall accuracy to levels similar to standard kNN implementations

Why some fields might be rectangular: an exploration of agricultural landscapes between pre-capitalist and capitalist modes of production

This article is a preliminary investigation of possible spatial form which starts by rejecting the idea that spatial theory can be built from assumptions of isomorphism. It examines spatial form in high potential ridge valley areas which are densely populated, and identifies the transition in land configuration for pre-capitalist to capitalist modes of production. In building the argument simple geometric patterns that differentiate from the model are postulated. The basic drivers of the differing spatial systems are essentially the superstructural legal conditions which are postulated as a moving from communal, customary law to individual statutory property rights

Evaluation of dental therapists undertaking dental examinations in a school setting in Scotland

Objective: To measure agreement between dental therapists and the Scottish gold-standard dentist undertaking National Dental Inspection Programme (NDIP) examinations. Methods: A study of interexaminer agreement between 19 dental therapists and the national gold-standard dentist was carried out. Pre-calibration training used the caries diagnostic criteria and examination techniques agreed by the British Association for the Study of Community Dentistry (BASCD). Twenty-three 5-year-old children (Primary 1) and 17 11-year-old children (Primary 7) children were examined. Agreement was assessed using kappa statistics on d 3 mft and D 3 MFT for P1 and P7 children, sensitivity and specificity values, and kappa statistics on d 3 t/D 3 T and ft/FT. Calibration data on P1 and P7 children from 2009–2012 involving dentists as examiners were used for comparison. Economic evaluation was undertaken using a cost minimization analysis approach. Results: The mean kappa score was 0.84 (SD 0.07) ranging from 0.69 to 0.94. All dental therapists scored good or very good agreement with the gold-standard dentist. This compares with historic NDIP calibration data with dentists, against the same gold-standard dentist, where the mean kappa value was 0.68 (SD 0.22) with a range of 0.35-1.00. The mean sensitivity score was 0.98 (SD 0.04) (range 0.88-1.0) and mean specificity score was 0.90 (SD 0.06) (range 0.78-0.96). Health economic analysis estimated that salary costs would be 33.6% lower if dental therapists were substituted for dentists in the year 2013, with an estimated saving of approximately £103 646 per annum on the national budget. Conclusion: We conclude that dental therapists show a high level of interexaminer agreement, and with the appropriate annual training and calibration, they could undertake dental examinations as part of the NDIP programme

Blue frontiers: managing the environmental costs of aquaculture

The report begins with an overview of the current status of world aquaculture. It then goes on to describe an approach for estimating the current combined biophysical resource demands of aquaculture for producer countries and regions. Following a comparison of these results with those available for other animal food production sectors the report then examines the consequences of likely future trends in production on the environmental impacts of aquaculture. Finally, the policy implications of the reportÆs findings are discussed along with the research agenda that should be pursued to meet the challenge of sustainable food production.Aquaculture, Aquaculture systems, Life cycle analysis, Environmental impact, Resource management, Aquaculture statistics, Sustainability

On certain regular graphs of girth 5

Let f(v,5) be the number of vertices of a (v,5)-cage (v≥3). We give an upper bound for f(v,5) which is considerably better than the previously known upper bounds. In particular, when v=7, it coincides with the well-known Hoffman- Singleton graph

IRVE-II Post-Flight Trajectory Reconstruction

NASA s Inflatable Re-entry Vehicle Experiment (IRVE) II successfully demonstrated an inflatable aerodynamic decelerator after being launched aboard a sounding rocket from Wallops Flight Facility (WFF). Preliminary day of flight data compared well with pre-flight Monte Carlo analysis, and a more complete trajectory reconstruction performed with an Extended Kalman Filter (EKF) approach followed. The reconstructed trajectory and comparisons to an attitude solution provided by NASA Sounding Rocket Operations Contract (NSROC) personnel at WFF are presented. Additional comparisons are made between the reconstructed trajectory and pre and post-flight Monte Carlo trajectory predictions. Alternative observations of the trajectory are summarized which leverage flight accelerometer measurements, the pre-flight aerodynamic database, and on-board flight video. Finally, analysis of the payload separation and aeroshell deployment events are presented. The flight trajectory is reconstructed to fidelity sufficient to assess overall project objectives related to flight dynamics and overall, IRVE-II flight dynamics are in line with expectation

Optimal Population Codes for Space: Grid Cells Outperform Place Cells

Rodents use two distinct neuronal coordinate systems to estimate their position: place fields in the hippocampus and grid fields in the entorhinal cortex. Whereas place cells spike at only one particular spatial location, grid cells fire at multiple sites that correspond to the points of an imaginary hexagonal lattice. We study how to best construct place and grid codes, taking the probabilistic nature of neural spiking into account. Which spatial encoding properties of individual neurons confer the highest resolution when decoding the animal’s position from the neuronal population response? A priori, estimating a spatial position from a grid code could be ambiguous, as regular periodic lattices possess translational symmetry. The solution to this problem requires lattices for grid cells with different spacings; the spatial resolution crucially depends on choosing the right ratios of these spacings across the population. We compute the expected error in estimating the position in both the asymptotic limit, using Fisher information, and for low spike counts, using maximum likelihood estimation. Achieving high spatial resolution and covering a large range of space in a grid code leads to a trade-off: the best grid code for spatial resolution is built of nested modules with different spatial periods, one inside the other, whereas maximizing the spatial range requires distinct spatial periods that are pairwisely incommensurate. Optimizing the spatial resolution predicts two grid cell properties that have been experimentally observed. First, short lattice spacings should outnumber long lattice spacings. Second, the grid code should be self-similar across different lattice spacings, so that the grid field always covers a fixed fraction of the lattice period. If these conditions are satisfied and the spatial “tuning curves” for each neuron span the same range of firing rates, then the resolution of the grid code easily exceeds that of the best possible place code with the same number of neurons