Approaches to national fish breeding programs: pointers from a tilapia pilot study

Details are given of a framework for developing breeding programmes using experience from the Genetic Improvement of Farmed Tilapias project which focussed on Nile tilapias (Oreochromis niloticus ). The following aspects are outlined: Analysis of targeted production and marketing systems; Breeding goals; Systematic documentation and evaluation of available genetic resources and choice and genetic base; Number of strains; Breeding strategy; Selection criteria and evaluation; Production and dissemination of improved strains; and, social, economic and environmental impacts.

Bayesian and L1 Approaches to Sparse Unsupervised Learning

The use of L1 regularisation for sparse learning has generated immense research interest, with successful application in such diverse areas as signal acquisition, image coding, genomics and collaborative filtering. While existing work highlights the many advantages of L1 methods, in this paper we find that L1 regularisation often dramatically underperforms in terms of predictive performance when compared with other methods for inferring sparsity. We focus on unsupervised latent variable models, and develop L1 minimising factor models, Bayesian variants of "L1", and Bayesian models with a stronger L0-like sparsity induced through spike-and-slab distributions. These spike-and-slab Bayesian factor models encourage sparsity while accounting for uncertainty in a principled manner and avoiding unnecessary shrinkage of non-zero values. We demonstrate on a number of data sets that in practice spike-and-slab Bayesian methods outperform L1 minimisation, even on a computational budget. We thus highlight the need to re-assess the wide use of L1 methods in sparsity-reliant applications, particularly when we care about generalising to previously unseen data, and provide an alternative that, over many varying conditions, provides improved generalisation performance.

New approaches to materials education for students of engineering

A novel approach to the teaching of materials to engineering students is outlined. It starts from the overview of the "world" of materials made possible by material property charts, and develops both an understanding of material properties and skills in selecting materials and processes to meet design specifications. It is supported by extensive computer-based methods and tools, and is well adapted both for elementary and for advanced courses.

Approaches to the evaluation and management of the fish stock in Kainji Lake, Nigeria

Estimates of potential yield for Kainji Lake, and the methods of analysis by earlier workers are discussed. Also summarized is the state of the fishery after impoundment, between 1969 and 1971, based on experimental gillnet catches. Recent sampling of the young of the year along the littoral margin indicates that most of the commercially important species have spawned successful1y in the lake. An intense fishing mortality of juvenile fish, owing to the use of small mesh nets by local fishermen, presents a possible threat to the future establishment of the fish in the lake. The results of gill-net selection studies based on HOLT'S (1957) method are given. The data have been extracted from experimental gill-net catches with graded fleets of nets between 1969 and 1971. Recommendations based on the above studies have been made to ensure a successful establishment of the fish species in the lake and an increase in catch-per~unit effort in subsequent years.

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.

Proteomic approaches to environmental stress in mussel Mytilus edulis due to emerging classes of anthropogenic pollutants

Anthropogenic pollutant chemicals pose a major threat to aquatic organisms. There is a need for more research on emerging categories of environmental chemicals such as nanomaterials, endocrine disruptors and pharmaceuticals. Proteomics offers options and advantages for early warning of alterations in environmental quality by detecting sub-lethal changes in sentinel species such as the mussel, Mytilus edulis. This thesis aimed to compare the potential of traditional biomarkers (such as enzyme activity measurement) and newer redox proteomic approaches. Environmental proteomics, especially a redox proteomics toolbox, may be a novel way to study pollutant effects on organisms which can also yield information on risks to human health. In particular, it can probe subtle biochemical changes at sub-lethal concentrations and thus offer novel insights to toxicity mechanisms. In the first instance, the present research involved a field-study in three stations in Cork Harbour, Ireland (Haulbowline, Ringaskiddy and Douglas) compared to an outharbour control site in Bantry Bay, Ireland. Then, further research was carried out to detect effects of anthropogenic pollution on selected chemicals. Diclofenac is an example of veterinary and human pharmaceuticals, an emerging category of chemical pollutants, with potential to cause serious toxicity to non-target organisms. A second chemical used for this study was copper which is a key source of contamination in marine ecosystems. Thirdly, bisphenol A is a major anthropogenic chemical mainly used in polycarbonate plastics manufacturing that is widespread in the environment. It is also suspected to be an endocrine disruptor. Effects on the gill, the principal feeding organ of mussels, were investigated in particular. Effects on digestive gland were also investigated to compare different outcomes from each tissue. Across the three anthropogenic chemicals studied (diclofenac, copper and bisphenol A), only diclofenac exposure did not show any significant difference towards glutathione transferase (GST) responses. Meanwhile, copper and bisphenol A significantly increased GST in gill. Glutathione reductase (GR) enzyme analysis revealed that all three chemicals have significant responses in gill. Catalase activity showed significant differences in digestive gland exposed to diclofenac and gills exposed to bisphenol A. This study focused then on application of redox proteomics; the study of the oxidative modification of proteins, to M. edulis. Thiol proteins were labelled with 5-iodoacetamidofluorescein prior to one-dimensional and two-dimensional electrophoresis. This clearly revealed some similarities on a portion of the redox proteome across chemical exposures indicating where toxicity mechanism may be common and where effects are unique to a single treatment. This thesis documents that proteomics is a robust tool to provide valuable insights into possible mechanisms of toxicity of anthropogenic contaminants in M. edulis. It is concluded that future research should focus on gill tissue, on protein thiols and on key individual proteins discovered in this study such as calreticulin and arginine kinase which have not previously been considered as biomarkers in aquatic toxicology prior to this study.

Impact of Kidney Function on Effects of the Dietary Approaches to Stop Hypertension (Dash) Diet.

OBJECTIVES: Although the Dietary Approaches to Stop Hypertension (DASH) diet lowers blood pressure in adults with hypertension, how kidney function impacts this effect is not known. We evaluated whether Estimated Glomerular Filtration Rate (eGFR) modifies the effect of the DASH diet on blood pressure, markers of mineral metabolism, and markers of kidney function. METHODS: Secondary analysis of the DASH-Sodium trial, a multicenter, randomized, controlled human feeding study that evaluated the blood pressure lowering effect of the DASH diet at three levels of sodium intake. Data from 92 participants with pre-hypertension or stage 1 hypertension during the 3450 mg /day sodium diet assignment contributed to this analysis. Stored frozen plasma and urine specimens were used to measure kidney related laboratory outcomes. RESULTS: Effects of the DASH diet on blood pressure, phosphorus, intact parathyroid hormone, creatinine, and albuminuria were not modified by baseline eGFR (mean 84.5 ± 18.0 ml/min/1.73 m(2), range 44.1 to 138.6 ml/min/1.73 m(2)) or the presence of chronic kidney disease (N=13%). CONCLUSIONS: The impact of the DASH diet on blood pressure, markers of mineral metabolism, and markers of kidney function does not appear to be modified by eGFR in this small subset of DASH-Sodium trial participants with relatively preserved kidney function. Whether greater reduction in eGFR modifies the effects of DASH on kidney related measures is yet to be determined. A larger study in individuals with more advanced kidney disease is needed to establish the efficacy and safety of the DASH diet in this patient population.

Challenges in integrative approaches to modelling the marine ecosystems of the North Atlantic: Physics to fish and coasts to ocean

It has long been recognised that there are strong interactions and feedbacks between climate, upper ocean biogeochemistry and marine food webs, and also that food web structure and phytoplankton community distribution are important determinants of variability in carbon production and export from the euphotic zone. Numerical models provide a vital tool to explore these interactions, given their capability to investigate multiple connected components of the system and the sensitivity to multiple drivers, including potential future conditions. A major driver for ecosystem model development is the demand for quantitative tools to support ecosystem-based management initiatives. The purpose of this paper is to review approaches to the modelling of marine ecosystems with a focus on the North Atlantic Ocean and its adjacent shelf seas, and to highlight the challenges they face and suggest ways forward. We consider the state of the art in simulating oceans and shelf sea physics, planktonic and higher trophic level ecosystems, and look towards building an integrative approach with these existing tools. We note how the different approaches have evolved historically and that many of the previous obstacles to harmonisation may no longer be present. We illustrate this with examples from the on-going and planned modelling effort in the Integrative Modelling Work Package of the EURO-BASIN programme.