Echocardiography determination of shunt volume in children with atrial septal defect

The accuracy of echocardiographic estimation of left-to-right shunts was studied prospectively in children with secundum ASD. Fifty-one consecutive patients were examined from March 1987 to August 1991. Mean age was 64/12 years with a minimum age of 12/12 and a maximum of 131/12 years. Twenty-five children were included in the first part of the study. The ratios of right and left atrial and ventricular areas and pulmonary and aortic diameters were correlated with the left-to-right shunts determined by oximetry (mean shunt 48.7%; min. 10.1%, max. 73.2%). The pulmonary/aortic diameter ratio provided the closest correlation (r = 0.95; p < 0.01). During the second part of the study the left-to-right shunt was estimated using the regression equations developed from part one. Thus, in 26 subsequent patients these values were compared with oximetric shunt values. Again, the pulmonary/aortic diameter ratio provided the closest correlation (r = 0.97). The pair comparison yielded a difference of 0.7 +/- 3.8%. Based on these results since 1991, surgery for ASD II has been performed without preoperative cardiac catheterization in 33 patients, provided echocardiographic shunt estimation was > or = 48%.     

An attempt at predicting blood β-hydroxybutyrate from Fourier-transform mid-infrared spectra of milk using multivariate mixed models in Polish dairy cattle

Fourier transform mid-infrared (FT-MIR) spectra of milk are commonly used for phenotyping of traits of interest through links developed between the traits and milk FT-MIR spectra. Predicted traits are then used in genetic analysis for ultimate phenotypic prediction using a single-trait mixed model that account for cows' circumstances at a given test day. Here, this approach is referred to as indirect prediction (IP). Alternatively, FT-MIR spectral variable can be kept multivariate in the form of factor scores in REML and BLUP analyses. These BLUP predictions, including phenotype (predicted factor scores), were converted to single-trait through calibration outputs; this method is referred to as direct prediction (DP). The main aim of this study was to verify whether mixed modeling of milk spectra in the form of factors scores (DP) gives better prediction of blood β-hydroxybutyrate (BHB) than the univariate approach (IP). Models to predict blood BHB from milk spectra were also developed. Two data sets that contained milk FT-MIR spectra and other information on Polish dairy cattle were used in this study. Data set 1 (n = 826) also contained BHB measured in blood samples, whereas data set 2 (n = 158,028) did not contain measured blood values. Part of data set 1 was used to calibrate a prediction model (n = 496) and the remaining part of data set 1 (n = 330) was used to validate the calibration models, as well as to evaluate the DP and IP approaches. Dimensions of FT-MIR spectra in data set 2 were reduced either into 5 or 10 factor scores (DP) or into a single trait (IP) with calibration outputs. The REML estimates for these factor scores were found using WOMBAT. The BLUP values and predicted BHB for observations in the validation set were computed using the REML estimates. Blood BHB predicted from milk FT-MIR spectra by both approaches were regressed on reference blood BHB that had not been used in the model development. Coefficients of determination in cross-validation for untransformed blood BHB were from 0.21 to 0.32, whereas that for the log-transformed BHB were from 0.31 to 0.38. The corresponding estimates in validation were from 0.29 to 0.37 and 0.21 to 0.43, respectively, for untransformed and logarithmic BHB. Contrary to expectation, slightly better predictions of BHB were found when univariate variance structure was used (IP) than when multivariate covariance structures were used (DP). Conclusive remarks on the importance of keeping spectral data in multivariate form for prediction of phenotypes may be found in data sets where the trait of interest has strong relationships with spectral variables.     

Variability in oil content and fatty acid composition of Ethiopian and introduced cultivars of linseed

This study was undertaken to assess the variability in oil content, oil yield and fatty acid composition of 60 linseed cultivars and to identify suitable accessions for use in future breeding and development endeavours in Ethiopia. Mean oil contents ranged from 291 to 359 g kg^?1, while oil yields varied between 1443 and 3276 g m^?2. Exotic introductions, especially those from Canada such as CDC‐VG, had higher oil contents than the local cultivars. Thus the introduction of exotic materials should be given more emphasis through germplasm exchange programmes. Unsaturated fatty acids were the major components in the oils, varying significantly (P < 0.01) from 859 to 906 g kg^?1, while minor saturated fatty acids were present at 84–119 g kg^?1. The contents of oleic, linoleic and linolenic acids were 148–293, 109–161 and 470–591 g kg^?1 respectively. Although accessions with variable linolenic acid contents were identified, this variability was insufficient to develop genotypes with less than 20 g kg^?1 linolenic acid for cooking oil through conventional crossing and selection methods. Hence mutation techniques and the introduction of exotic lines should be regarded as alternative approaches to obtain linseed genotypes with low linolenic acid contents. Copyright © 2004 Society of Chemical Industry     

Design considerations for a high-speed CMOS comparator

Design considerations for a high-speed CMOS comparator for application in highspeed analogue-to-digital conversion are presented. Extensive simulations show that the comparator designed accordingly operates well above 250MHz clock speed in standard 0.5µm CMOS technology. An accuracy of 5mV and average power consumption of 0.3mW on 3.3V power supply is observed using simulations when it operates at 250MHz.     

Evaluating the Effectiveness of Best Management Practices in Gilgel Gibe Basin WatershedmEthiopia

Soil erosion/sedimentation is an immense problem threatening the live storage capacity of dam reservoirs in Ethiopia. This in turn reduces the power generation capacities of hydropower reservoirs. Therefore, studies which give insight into soil erosion/sedimentation mechanisms and mitigation methods is important. The high rate of soil erosion/sedimentation threats the lifespan of Gilgel Gibe-I hydropower reservoir, The problem of sedimentation in Gilgel Gibe-I will also affect Gilgel Gibe-2 which uses the water released from Gilgel Gibe-1. The sustainability of these hydropower plants needs catchment management practices that will reduce soil erosion. This paper presents the results of monthly and yearly sediment yield simulations experiments conducted for Gilgel Gibe-1 under different BMP （best management practice） scenarios. The scenarios applied in this paper are： （1） maintaining existing conditions; （2） introducing filter strips; （3） applying stone/soil bunds; （4） reforestation. The SWAT （soil and water assessment tool） was used to model soil erosion, identify soil erosion prone areas and assess the impact of BMPs on sediment reduction via simulations. The simulation results showed that applying filter strips, stone bunds and reforestation scenarios could reduce the current sediment yields at soil erosion prone areas and at the outlet of the catchment area which is the inlet to Gilgel Gibe-I reservoir.     

The changing face of the Ethiopian rift lakes and their environs: call of the time

The Ethiopian rift is characterized by many perennial rivers, and a chain of lakes that vary in size, and hydrological and hydrogeological settings. The water resources of the Rift lakes are one of the focal points for large‐scale development in Ethiopia over the last few decades. Some of the lakes and their influent rivers are used for irrigation, soda abstraction, fish farming and recreation, and also support a wide variety of endemic birds and wild animals. Ethiopia's major mechanized irrigation farms and commercial fishery are confined within the Rift region. A few of the lakes have shrunk in surface area because of excessive water abstractions, while others have expanded because of increased surface run‐off and groundwater inflows from percolated irrigation water. Excessive land degradation, deforestation and over‐irrigation have changed the hydrological setting of a few Rift lakes. Human activities, in combination with changes in climate and geology, have influenced the hydrological setting and the water quality of the lakes, with the salinity and major ion composition dramatically changed in some of them. This study tries to address the challenges associated with development of these surface‐water resources, focusing on environmental problems arising over the past few decades on three lakes (Abiyata, Beseka and Ziway) situated along the tectonically active Rift floor. The methods utilized in this study include field hydrological and hydrogeological mapping, supported by aerial photographs and satellite imagery interpretations, as well as hydrometeorological and hydrochemical data analysis, and catchment hydrological modeling. A converging‐evidence approach was adapted to reconstruct the temporal and spatial variations of the lake water levels and surface areas. The study results revealed that the major changes in the Rift Valley are related primarily to recent improper use of water from the large rivers draining the Rift Valley floor and the lake catchments, and from direct lake water abstractions aggravated intermittently by climatic and land use changes. These changes represent grave environmental consequences on the fragile Rift ecosystem that demands urgent intervention in the context of an integrated, basin‐wide water management approach. This study emphasizes lake water level changes and human influences on these changes. It also assesses human interactions and water quality changes, including land use changes and environmental repercussions on the lakes, as well as providing recommendations on how these issues should be addressed.     

Genetic variation of susceptibility to Mycobacterium avium subsp. paratuberculosis infection in dairy cattle

Paratuberculosis is an infectious disease that is not easily amenable to classical control methods such as treatment and vaccination. Experimental animal models suggest that there could be genetic factors responsible for susceptibility or resistance to infection with the causative agent, Mycobacterium avium subsp. paratuberculosis. The aim of this study was to estimate genetic variation in susceptibility to paratuberculosis in Dutch dairy cattle. Data collected during a vaccination trial, conducted from 1984 to 1994, was used. A total of 3020 cows, with complete pedigree records and infection status at slaughter, were available for analysis. A standard polygenic statistical probit model was used to estimate heritabilities. The estimated heritability of susceptibility to M. avium. subsp. paratuberculosis infection was 0.06 for the overall population. In the subpopulation of vaccinated animals the estimated heritability was 0.09. Other calculations based on the model used in this study argue against a prominent role for vertical transmission. Because the establishment of genetic variation is one of the first steps towards the exploration of the possible use of selection for genetic improvement, the present study provides evidence for the presence of genetic variation in the susceptibility of cattle to paratuberculosis. Because the economic impact of the disease is substantial, the development and application of genetic tools, along with other control methods, could be instrumental in the eradication of paratuberculosis.     

Reduced-sample-rate sigma–delta modulation using recursive deconvolution

A reduced-sample-rate sigma–delta modulation method using a recursive deconvolution technique for application in digital-to-analogue conversion is proposed and analysed. The method allows the sigma–delta modulators to operate at a sampling rate which is lower than the output bitstream rate by an integer factor. With the proposed in-loop mapping algorithm to map an m-bit sample to qb-bit samples, the total system inherits the advantages of a multilevel quantization conventional ΣΔ modulator in the digital part with regard to suppression of tones, improved stability and low power, while its output remains single-bit. The effectiveness of the technique is illustrated using simulations for second-and third-order modulators. © by John Wiley & Sons, Ltd.     

Genetic components of milk Fourier-transform infrared spectra used to predict breeding values for milk composition and quality traits in dairy goats

The usual practice today is that milk component phenotypes are predicted using Fourier-transform infrared (FTIR) spectra and they are then, together with pedigree information, used in BLUP for calculation of individual estimated breeding values. Here, this is referred to as the indirect prediction (IP) approach. An alternative approach—a direct prediction (DP) method—is proposed, where genetic analyses are directly conducted on the milk FTIR spectral variables. Breeding values of all derived milk traits (protein, fat, fatty acid composition, and coagulation properties, among others) can then be predicted as traits correlated only to the genetic information of the spectra. For the DP, no need exists to predict the phenotypes before calculating breeding values for each of the traits—the genetic analysis is done once for the spectra, and is applicable to all traits derived from the spectra. The aim of the study was to compare the effects of DP and IP of milk composition and quality traits on prediction error variance (PEV) and genetic gain. A data set containing 27,927 milk FTIR spectral observations and milk composition phenotypes (fat, lactose, and protein) belonging to 14,869 goats of 271 herds was used for training and evaluating models. Partial least squares regression was used for calibrating prediction models for fat, protein, and lactose percentages. Restricted maximum likelihood was used to estimate variance components of the spectral variables after principal components analysis was applied to reduce the spectral dimension. Estimated breeding values were predicted for fat, lactose, and protein percentages using DP and IP methods. The DP approach reduced the mean PEV by 3.73, 4.07, and 7.04% for fat, lactose, and protein percentages, respectively, compared with the IP method. Given the reduction in PEV, relative genetic gains were 2.99, 2.78, and 4.85% for fat, lactose, and protein percentages, respectively. We concluded that more accurate estimated breeding values could be found using genetic components of milk FTIR spectra compared with single-trait animal model analyses on phenotypes predicted from the spectra separately. The potential and application is not only limited to milk FTIR spectra, but could also be extended to any spectroscopy techniques implemented in other species and for other traits.