Folate: Methods of analysis

Folates and its derivatives occur as polyglutamates in nature. The multiplicity of forms and the generally low levels in foods makes quantitative analysis of folate a difficult task. The assay of folates from foods generally involves three steps: liberation of folates from the cellular matrix; deconjugation from the polyglutamate to the mono and di-glutamate forms; and the detection of the biological activity or chemical concentration of the resulting folates. The detection methods used are the microbiological assay relying on the turbidimetric bacterial growth of Lactobacillus rhamnosus which is by far the most commonly used method; the HPLC and LC/MS techniques and bio-specific procedures. This review attempts to describe the methods along with the merits and demerits of using each of these methods.

Rule extraction from technology IPOs in the US stock market

Machine learning techniques for prediction and rule extraction from artificial neural network methods are used. The hypothesis that market sentiment and IPO specific attributes are equally responsible for first-day IPO returns in the US stock market is tested. Machine learning methods used are Bayesian classifications, support vector machines, decision tree techniques, rule learners and artificial neural networks. The outcomes of the research are predictions and rules associated With first-day returns of technology IPOs. The hypothesis that first-day returns of technology IPOs are equally determined by IPO specific and market sentiment is rejected. Instead lower yielding IPOs are determined by IPO specific and market sentiment attributes, while higher yielding IPOs are largely dependent on IPO specific attributes.

Assessing the competitiveness of loss allocation methods in a deregulated electricity market

This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.

Calculation of line integrals in boundary integral methods

We propose quadrature rules for the approximation of line integrals possessing logarithmic singularities and show their convergence. In some instances a superconvergence rate is demonstrated.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

A demonstration of artificial dissipation effects in some finite volume solution methods for the Navier-Stokes equations

The artificial dissipation effects in some solutions obtained with a Navier-Stokes flow solver are demonstrated. The solvers were used to calculate the flow of an artificially dissipative fluid, which is a fluid having dissipative properties which arise entirely from the solution method itself. This was done by setting the viscosity and heat conduction coefficients in the Navier-Stokes solvers to zero everywhere inside the flow, while at the same time applying the usual no-slip and thermal conducting boundary conditions at solid boundaries. An artificially dissipative flow solution is found where the dissipation depends entirely on the solver itself. If the difference between the solutions obtained with the viscosity and thermal conductivity set to zero and their correct values is small, it is clear that the artificial dissipation is dominating and the solutions are unreliable.

A shift from passive teaching at medical conferences to more interactive methods improves physician learning

Conferences that deliver interactive sessions designed to enhance physician participation, such as role play, small discussion groups, workshops, hands-on training, problem- or case-based learning and individualised training sessions, are effective for physician education.

Appropriate surveying methods in the Philippines: Can modern GPS units help?

An investigation was undertaken to test the effectiveness of two procedures for recording boundaries and plot positions for scientific studies on farms on Leyte Island, the Philippines. The accuracy of a Garmin 76 Global Positioning System (GPS) unit and a compass and chain was checked under the same conditions. Tree canopies interfered with the ability of the satellite signal to reach the GPS and therefore the GPS survey was less accurate than the compass and chain survey. Where a high degree of accuracy is required, a compass and chain survey remains the most effective method of surveying land underneath tree canopies, providing operator error is minimised. For a large number of surveys and thus large amounts of data, a GPS is more appropriate than a compass and chain survey because data are easily up-loaded into a Geographic Information System (GIS). However, under dense canopies where satellite signals cannot reach the GPS, it may be necessary to revert to a compass survey or a combination of both methods.

Chemical treatment of Escherichia coli. II. Direct extraction of recombinant protein from cytoplasmic inclusion bodies in intact cells

A method is presented for the direct extraction of the recombinant protein Long-R-3-IGF-I from inclusion bodies located in the cytoplasm of intact Escherichia coli cells. Chemical treatment with 6M urea, 3 mM EDTA, and 20 mM dithiothreitol (DTT) at pH 9.0 proved an effective combination for extracting recombinant protein from intact cells. Comparable levels of Long-R-3-IGF-I were recovered by direct extraction as achieved by in vitro dissolution following mechanical disruption. However, the purity of directly extracted recombinant protein was lower due to contamination by bacterial cell components. The kinetics of direct extraction are described using a first-order equation with the time constant of 3 min. Urea appears important for permeabilization of the cell and dissolution of the inclusion body. Conversely, EDTA is involved in permeabilization of the cell wall and DTT enhances protein release. pH proved to be important with lower levels of protein release achieved at low pH values (