Effect of photo-oxidation of major milk proteins on protein structure and hydrolysis by chymosin

Changes in the protein structure of different major milk proteins in response to photo-oxidation and its effect on hydrolysis by chymosin were studied by determination of free amino-terminal groups and by peptide mapping using liquid chromatography coupled with mass spectrometry. Changes were seen in the formation of peptides by chymosin after photo-oxidation of all substrates studied, but the extent of changes varied between the different substrates. Oxidative changes involving tryptophan residues and formation of dityrosines were high in the casein, and conformational changes of both α_S- and β-casein were indicated by changes in the micro-environment of the tryptophan residues after oxidation. A decreased accessibility of chymosin to oxidized caseins was reflected in a lower overall level of free amino-terminal groups, and changed peptide maps. Although β-lactoglobulin and lactoferrin showed marginal conformational changes, a higher level of free amino-terminal groups was observed, and a range of peptides were found to increase for these two proteins.     

Prediction of mechanical dough development,water absorption and baking performance from farinograph parameters

Two systems for measuring flour water absorption (WA), the farinograph (FAR) and the Wheat Research Institute, 125 g mechanical dough development (MDD) standard bake test system, were compared using a representative sample of 20 commercial flours. A highly significant correlation (r = 0.93) was found which yielded the predictive equation: WA_MDD = 0.66 × WA_FAR + 181 The 95% prediction limits for 125 g MDD water absorptions from this equation were ± 15 g kg^?1. This degree of accuracy was largely due to excellent farinograph reproducibility. Other farinograph parameters (development time, stability and breakdown) were highly correlated with the work input required for 125 g mechanical dough development, but only development time was significantly correlated with the volume of loaves baked on the 125 g standard bake system. This lack of prediction of baking quality for the farinograph could partly be because it simulates bulk fermentation mixing, rather than the more intensive mixing of the mechanical dough development process used for the loaves in this experiment. However, the loaf volume range was diminished since sample preparation involved bulking flours by water absorption.     

Cofiring coal and straw in a 150 MWe power boiler experiences

In 1995 ELSAM/MIDTKRAFT equipped the 150 MW_e pulverised coal-fired Studstrup power station, unit 1, for a technology demonstration cofiring of coal and straw. The conversion consisted of establishing a straw pre-processing plant and modifying the burner system. After plant commissioning in January 1996, a 2-year demonstration program was initiated. The objective of the program was to evaluate the influence of cofiring on boiler plant performance, combustion chemistry, heat surface deposits and corrosion, residue quality, emissions, and selective catalytic reduction (SCR) systems. This paper presents the plant conversion and results from the demonstration period.     

Identifying twin gestations at low risk for preterm birth with a transvaginal ultrasonographic cervical measurement at 24 to 26 weeks' gestation

OBJECTIVE: Because twins are a high-risk group for preterm birth, many clinicians routinely use prophylactic interventions such as home bed rest, hospital bed rest, oral tocolytics, or home uterine activity monitoring to prevent preterm delivery. We sought to identify twin gestations at low risk for spontaneous preterm birth with transvaginal ultrasonography of the cervix to avoid the unnecessary use of prophylactic interventions in these pregnancies. STUDY DESIGN: We measured cervical length at 24 to 26 weeks' gestation by transvaginal ultrasonography in women with twin gestations referred to our prematurity prevention clinic. Each delivery was classified as (1) spontaneous preterm birth < 34 weeks' gestation, (2) delivery at > or = 34 weeks' gestation with intervention, or (3) delivery at > or = 34 weeks' gestation without intervention. Intervention included strict bed rest at home or in the hospital, either parenteral or oral tocolysis, or both, or home uterine activity monitoring. Indicated preterm deliveries and patients with cerclage were excluded from this analysis. The ability of transvaginal cervical length to predict women who would deliver at > or = 34 weeks without intervention was evaluated. A cervical length of 35 mm was chosen by scatter diagram as the best cutoff to discriminate between the group delivered at term without intervention and the other two groups. RESULTS: Of 85 women with twin gestations who underwent ultrasonographic cervical length measurements at 24 to 26 weeks' gestation, 17 had spontaneous preterm birth at < 34 weeks, 23 were delivered at > or = 34 weeks but required intervention, and 45 were delivered at > or = 34 weeks without intervention. The mean cervical length for those delivered at > or = 34 weeks' gestation without intervention (36.4 +/- 5.8 mm) was significantly greater (p < 0.0001) than the mean for those delivered preterm (27.4 +/- 8.5) and those delivered at > or = 34 weeks' gestation who required intervention (27.7 +/- 10.5 mm). The sensitivity, specificity, and positive and negative predictive values of a cervical length > 35 mm for predicting delivery at > or = 34 weeks' gestation are 49%, 94%, 97%, and 31%, respectively. CONCLUSION: A transvaginal ultrasonographic measurement of the cervix of > 35 mm at 24 to 26 weeks in twin gestations can identify patients who are at low risk for delivery before 34 weeks' gestation.     

A framework for fuzzy recognition technology

Presents a scheme for object recognition by classificatory problem solving in the framework of fuzzy sets and possibility theory. The scheme has a particular focus on handling the imperfection problems that are common in application domains where the objects to be recognized (detected and identified) represent undesirable situations, referred to as crises. Crises develop over time, and observations typically increase in number and precision as the crisis develops. Early detection and precise recognition of crises is desired, since it increases the possibility of an effective treatment. The crisis recognition problem is central in several areas of decision support, such as medical diagnosis, financial decision making and early warning systems. The problem is characterized by vague knowledge and observations suffering from several kinds of imperfections, such as missing information, imprecision, uncertainty, unreliability of the source, and mutual (possibly conflicting or reinforcing) observations of the same phenomena. The problem of handling possibly imperfect observations from multiple sources includes the problems of information fusion and multiple-sensor data fusion. The different kinds of imperfection are handled in the framework of fuzzy sets and possibility theory     

Sensitivity study of a semi-automatic training set generator

This paper addresses the problem of assessing the robustness with respect to change in parameters of an integrated training and classification routine. Extensions to traditional multivariate statistical methods are applied to perform the classification. Training sets are grown from one or a few seed points by a method that ensures spatial and spectral closeness of observations. Spatial closeness is obtained by requiring connectivity. Spectral closeness is obtained by excluding observations that have high Mahalanobis distances to the training class mean. The marginal effects of changes in the parameters that are input to the seed growing algorithm are evaluated. Initially, the seed is expanded to a small area in order to allow for the estimation of a dispersion matrix. This expansion is controlled by upper limits for the spatial and Euclidean spectral distances from the seed point. Second, after this initial expansion, the growing of the training set is controlled by an upper limit for the Mahalanobis distance to the current estimate of the class centre. Also, the estimates of class centres and dispersion matrices may be continuously updated, or the initial estimates may be used. Finally, the effect of the operator's choice of seed among a number of potential seed points is evaluated. An evaluation of the sensitivity of the seed algorithm with respect to parameter settings is carried out by applying it to the classification of minerals commonly encountered in siliciclastic or carbonate rocks from twelve chemical elements mapped from thin sections by energy-dispersive spectroscopy (EDS) in a scanning electron microscope (SEM), using a standard quadratic classifier. The performance for each parameter setting is measured by the overall misclassification rate on an independently generated validation set. The integrated training and classification method is presently used as a routine petrographical analysis method at Norsk Hydro Research Centre.     

Quantifying the effect of riparian forest versus agricultural vegetation on river meander migration rates,central Sacramento River,California, USA

Riparian forest vegetation is widely believed to protect riverbanks from erosion, but few studies have quantified the effect of riparian vegetation removal on rates of river channel migration. Measured historical changes in a river channel centreline, combined with mapped changes in floodplain vegetation, provide an opportunity to test how riparian vegetation cover affects the erodibility of riverbanks. We analysed meander migration patterns from 1896 to 1997 for the central reach of the Sacramento River between Red Bluff and Colusa, using channel planform and vegetation cover data compiled from maps and aerial photography. We used a numerical model of meander migration to back‐calculate local values for bank erodibility (i.e. the susceptibility of bank materials to erosion via lateral channel migration, normalized for variations in near‐bank flow velocities due to channel curvature). A comparison of migration rates for approximately 50 years before and after the construction of Shasta dam suggests that bank migration rates and erodibility increased roughly 50%, despite significant flow regulation, as riparian floodplains were progressively converted to agriculture. A comparison of migration rates and bank erodibilities between 1949 and 1997, for reaches bordered by riparian forest versus agriculture, shows that agricultural floodplains are 80 to 150% more erodible than riparian forest floodplains. An improved understanding of the effect of floodplain vegetation on river channel migration will aid efforts to predict future patterns of meander migration for different river management and restoration scenarios. Copyright © 2004 John Wiley & Sons, Ltd.