A von Bertalanffy Based Model for the Estimation of Oyster (Crassostrea virginica) Growth on Restored Oyster Reefs in Chesapeake Bay

A model to estimate the mean monthly growth of Crassostrea virginica oysters in Chesapeake Bay was developed. This model is based on the classic von Bertalanffy growth function, however the growth constant is changed every monthly timestep in response to short term changes in temperature and salinity. Using a dynamically varying growth constant allows the model to capture seasonal oscillations in growth, and growth responses to changing environmental conditions that previous applications of the von Bertalanffy model do not capture. This model is further expanded to include an estimation of Perkinsus marinus impacts on growth rates as well as estimations of ecosystem services provided by a restored oyster bar over time. The model was validated by comparing growth estimates from the model to oyster shell height observations from a variety of restoration sites in the upper Chesapeake Bay. Without using the P. marinus impact on growth, the model consistently overestimates mean oyster growth. However, when P. marinus effects are included in the model, the model estimates match the observed mean shell height closely for at least the first 3 years of growth. The estimates of ecosystem services suggested by this model imply that even with high levels of mortality on an oyster reef, the ecosystem services provided by that reef can still be maintained by growth for several years. Because larger oyster filter more water than smaller ones, larger oysters contribute more to the filtration and nutrient removal ecosystem services of the reef. Therefore a reef with an abundance of larger oysters will provide better filtration and nutrient removal. This implies that if an oyster restoration project is trying to improve water quality through oyster filtration, it is important to maintain the larger older oysters on the reef.

Guidelines on artificial nutrition versus hydration in terminal cancer patients

Whether a terminally ill cancer patient should be actively fed or simply hydrated through subcutaneous or intravenous infusion of isotonic fluids is a matter of ongoing controversy among clinicians involved in the care of these patients. Under the auspices of the European Association for Palliative Care, a committee of experts developed guidelines to help clinicians make a reasonable decision on what type of nutritional support should be provided on a case-by-case basis. It was acknowledged that part of the controversy related to the definition of the terminal cancer patient, since this is a heterogeneous group of patients with different needs, expectations, and potential for a medical intervention. A major difficulty is the prediction of life expectancy and the patient's likely response to vigorous nutritional support. In an attempt to reach a decision on the type of treatment support (artificial nutrition vs. hydration) which would best meet the needs and expectations of the patient, we propose a three-step process: Step I: define the eight key elements necessary to reach a decision: Step II: make the decision; and Step III: reevaluate the patient and the proposed treatment at specified intervals. Step I involves assessing the patient concerning the following: 1) oncological/clinical condition; 2) symptoms; 3) expected length of survival; 4) hydration and nutritional status; 5) spontaneous or voluntary nutrient intake; 6) psychological profile; 7) gut function and potential route of administration; and 8) need for special services based on type of nutritional support prescribed. Step II involves the overall assessment of pros and cons, based on information determined in Step I, in order to reach an appropriate decision based on a well-defined end point (i.e. improvement of quality of life; maintaining patient survival; attaining rehydration). Step III involves the periodic reevaluation of the decision made in Step II based on the proposed goal and the attained result.

Culture-bound technological solutions: An artificial theoretic insight

Sometimes, technological solutions to practical problems are devised that conspicuously take into account the constraints to which a given culture is subjecting the particular task or the manner in which it is carried out. The culture may be a professional culture (e.g., the practice of law), or an ethnic-cum-professional culture (e.g., dance in given ethnic cultures from South-East Asia), or, again, a denominational culture prescribing an orthopraxy impinging on everyday life through, for example, prescribed abstinence from given categories of workday activities, or dietary laws. Massimo Negrotti's Theory of the artificial is a convenient framework for discussing some of these techniques. We discuss a few examples, but focus on the contrast of two that are taken from the same cultural background, namely, technological applications in compliance with Jewish Law orthopraxy. •Soya-, mycoprotein- or otherwise derived meat surrogates are an example ofnaturoid; they emulate the flavours and olfactory properties, as well as the texture and the outer and inner appearance, of the meat product (its kind, cut, form) they set out to emulate (including amenability to cooking in the usual manner for the model), while satisfying cultural dietary prohibitions. •In contrast, the Sabbath Notebook, a writing surrogate we describe in this paper, is atechnoid: it emulates a technique (writing to store alphanumeric information), while satisfying the prohibition of writing at particular times of the liturgical calendar (the Sabbath and the major holidays).

Guest editorial. [Computers and Artificial Intelligence. 1998. Vol. 17, No. 2-3]

Editorial

Multicomponent gas-mixture measurements using an array of gas sensors and an artificial neural-network

An Electronic Nose is being jointly developed between the University of Greenwich and the Institute of Intelligent Machines to detect the gases given off from an oil filled transformer when it begins to break down. The gas sensors being used are very simple, consisting of a layer of Tin Oxide (SnO2) which is heated to approximately 640 K and the conductivity varies with the gas concentrations. Some of the shortcomings introduced by the commercial gas sensors available are being overcome by the use of an integrated array of gas sensors and the use of artificial neural networks which can be 'taught' to recognize when the gas contains several components. At present simulated results have achieved up to a 94% success rate of recognizing two component gases and future work will investigate alternative neural network configurations to maintain this success rate with practical measurements.

Artificial neural networks in modelling osmotic dehydration of foods

Artificial neural network (ANN) models for water loss (WL) and solid gain (SG) were evaluated as potential alternative to multiple linear regression (MLR) for osmotic dehydration of apple, banana and potato. The radial basis function (RBF) network with a Gaussian function was used in this study. The RBF employed the orthogonal least square learning method. When predictions of experimental data from MLR and ANN were compared, an agreement was found for ANN models than MLR models for SG than WL. The regression coefficient for determination (R2) for SG in MLR models was 0.31, and for ANN was 0.91. The R2 in MLR for WL was 0.89, whereas ANN was 0.84.Osmotic dehydration experiments found that the amount of WL and SG occurred in the following descending order: Golden Delicious apple > Cox apple > potato > banana. The effect of temperature and concentration of osmotic solution on WL and SG of the plant materials followed a descending order as: 55 > 40 > 32.2C and 70 > 60 > 50 > 40%, respectively.

Recovery of a biodiversity action plans species in northwest England: possible role of climate change, artificial habitat and water quality amelioration. Occasional Publication of the Marine Biological Association 16

The honeycomb reef worm Sabellaria alveolata is recognised as being an important component of intertidal communities. It is a priority habitat within the UK Biodiversity Action Plan and as a biogenic reef forming species is covered by Annex 1 of the EC habitats directive. S. alveolata has a lusitanean (southern) distribution, being largely restricted to the south and west coasts of England. A broad-scale survey of S. alveolata distribution along the north-west coasts was undertaken in 2003/2004. These records were then compared with previous distribution records, mainly those collected by Cunningham in 1984. More detailed mapping was carried out at Hilbre Island at the mouth of the River Dee, due to recent reports that S. alveolata had become re-established there after a long absence.