Fisheries Production: Management Institutions, Spatial Choice, and the Quest for Policy Invariance

The fishery-dependent data used to estimate fishing production technologies are shaped by the incentive structures that influence fishermen’s purposeful choices across their multiple margins of production. Using a combination of analytical and simulation methods, we demonstrate how market prices and regulatory institutions influence a dominant short-run margin of production—the deployment of fishing time over space. We show that institutionally driven spatial selection leads to only a partial exploration of the full production set, yielding poorly identified estimates of production possibilities outside of the institutionally dependent status quo. The implication is that many estimated fisheries production functions suffer from a lack of policy invariance and may yield misleading predictions for even the most short-run of policy evaluation tasks. Our findings suggest that accurate assessment of the impacts of a policy intervention requires a description of the fishing production process that is sufficiently structural so as to be invariant to institutional changes.Ye

Optimizing genetic algorithm strategies for evolving networks

This paper explores the use of genetic algorithms for the design of networks, where the demands on the network fluctuate in time. For varying network constraints, we find the best network using the standard genetic algorithm operators such as inversion, mutation and crossover. We also examine how the choice of genetic algorithm operators affects the quality of the best network found. Such networks typically contain redundancy in servers, where several servers perform the same task and pleiotropy, where servers perform multiple tasks. We explore this trade-off between pleiotropy versus redundancy on the cost versus reliability as a measure of the quality of the network.Comment: 9 pages, 5 figure

Techniques for noise removal from EEG, EOG and air flow signals in sleep patients

Noise is present in the wide variety of signals obtained from sleep patients. This noise comes from a number of sources, from presence of extraneous signals to adjustments in signal amplification and shot noise in the circuits used for data collection. The noise needs to be removed in order to maximize the information gained about the patient using both manual and automatic analysis of the signals. Here we evaluate a number of new techniques for removal of that noise, and the associated problem of separating the original signal sources.Comment: 9 pages, 3 figure

Conditions Responsible For The Success Of Carnivorous Plants In Nutrient-Poor Wetlands

Despite the vast array of past research focused on carnivorous plants, few studies have investigated the ecological interactions between carnivorous and non-carnivorous plant species. I addressed the following three questions: (1) does niche complementarity promote coexistence between fire-adapted carnivorous and non-carnivorous species? (2) do carnivorous plants rely on both leaf traps and arbuscular mycorrhizal fungi to access different nutrients that are in high demand after fire in nutrient poor bogs? (3) why are carnivorous plants largely absent from nutrient-rich wetlands? I addressed the first question by examining the three-way interacting effects of fire, prey-derived nutrient availability, and root competition from neighbors on sarracenia alata growth. I found no evidence of belowground competition on growth, nor did belowground competition interact with fire to influence growth. To address the second question, I used carnivorous drosera tracyi to experimentally test the effects of light availability and the availability of nutrients found in higher concentrations in prey versus nutrients found in higher concentrations in post-fire ash on relative investment in carnivory versus amf colonization. Although the addition of phosphorus and other nutrients besides nitrogen appeared to slightly reduce investment in carnivory, I found no effect of late season fire on carnivory or amf colonization in d. Tracyi. To address the third question, I compared the performance of s. Alata in a nutrient-rich marsh and a nutrient-poor bog, with and without neighbors. I also measured multiple soil characteristics potentially responsible for transplant performance. I found no evidence of competition from neighboring plants on s. Alata growing in either the nutrient rich marsh or the nutrient-poor bog. Rather, I found that s. Alata were intolerant of the low oxygen levels within the nutrient-rich marsh soils. Together, these results suggest interspecific competition between non-carnivorous and carnivorous plants may be weak in the wet pine savannas studied here. I suggest that the ability of a large number of species to tolerate the abiotic conditions present in wet pine savannas, combined with weak resource competition among herbaceous plants (carnivorous and non-carnivorous) enables species coexistence in these uniquely diverse ecosystems

Fluctuations and noise in cancer development

This paper explores fluctuations and noise in various facets of cancer development. The three areas of particular focus are the stochastic progression of cells to cancer, fluctuations of the tumor size during treatment, and noise in cancer cell signalling. We explore the stochastic dynamics of tumor growth and response to treatment using a Markov model, and fluctutions in tumor size in response to treatment using partial differential equations. We also explore noise within gene networks in cancer cells, and noise in inter-cell signalling.Comment: 11 pages, 6 figure

Biological processing in oscillatory baffled reactors (OBRs)

EngD ThesisBioprocessing involves using complete cells or any of their components for the manufacture of products such as pharmaceuticals, fuel, health products and precursor compounds for plastics. Bioprocessing can provide sustainable routes for the manufacture of products which are traditionally manufactured from fossil-derived chemicals. The stirred tank reactor (STR) is the prevalent fermenter/reaction vessel in industry due to its simplicity and cost. However; the basic design has not changed for centuries. This thesis describes the use of oscillatory baffled reactors (OBRs) for bioprocessing. Generally, the “niche application” of OBRs is in performing ‘long’ processes in plug flow conditions, so they should be suitable for many bioprocesses. In this thesis, four research projects using OBRs are presented: modelling of plug flow and OBR design; enzymatic saccharification; microalgae culture; and anaerobic digestion (AD). A robust method to maximise plug flow in various OBR designs is described. Second order, polynomial models (R2=92.1% and 97.3%) were used to maximise plug flow at Ψ=1.9. The net flow rate (Q) was shown to affect the quality of plug flow which has implications for OBR design. Enzymatic saccharification was conducted in reactors based on OBR and STR technology. The OBR required 94-99% less power to achieve the necessary mixing intensities to maximise glucose production. Chlamydomonas reinhardtii was cultured in a modified OBR for use as a photobioreactor (PBR). Maximum growth rates were increased by 95% in the OBR compared to cultures conducted in T-flasks. A flotation effect was observed that suggests that a dual culture and harvest device for microalgae is possible. Anaerobic digestion of dairy slurry and co-digestion with glycerol was conducted in digesters based on OBR and STR technology. The OBR achieved a maximum specific methane yield 28% higher than the STR. However, blockages occurred in the OBR and 89% less power was required for temperature control in the STR, predominantly due to differences in surface areas to volume ratios. Overall, OBR technology was successfully used in three bioprocesses, with improvements demonstrated over traditional technologies such as STR and/or T- flasks. Commercial systems based on OBR technology could be designed, provided that sufficient data is generated to overcome the risks associated with adoption of a novel technology such as OBRs.The Centre for Process Innovation (CPI): EPSRC