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.     

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.     

Techniques and results of direct-access minimally invasive mitral valve surgery: a paradigm for the future

As a model of the meconium aspiration syndrome (MAS) of human infants, adult rabbits and newborn rhesus monkeys received intratracheal instillation of human meconium to induce pulmonary injury. Injured rabbits were ventilated with 100% O2 and divided into four treatment groups, receiving: 1) bronchoalveolar lavages (BAL) with dilute KL4-Surfactant; 2) lavages with equal volumes of sterile saline; 3) a single intratracheal bolus of KL4-Surfactant, 100 mg/kg; and 4) no treatment. The untreated rabbits developed atelectasis, a fall in pressure-volume levels and in partial pressure of O2 in arterial blood (PaO2) from approximately 500 to < 100 mm Hg, and severe pulmonary inflammation between 3 and 5 h after instillation of meconium. Rabbits treated by BAL with dilute KL4-Surfactant showed rapid and sustained recovery of PaO2 to approximately 300 mm Hg within minutes, a return toward normal pressure-volume levels, and diminished inflammation. Rabbits receiving BAL with saline failed to show recovery, and rabbits treated with a bolus of surfactant intratracheally exhibited a transient response by 1-2 h after treatment, but then returned to the initial atelectatic state. Newborn rhesus monkeys, after receiving human meconium intratracheally before the first breath, developed severe loss of pulmonary function. Treatment of these monkeys 1-5 h after birth with BAL with dilute KL4-Surfactant produced clearing of chest radiographs and a rapid improvement in pulmonary function with ratios of partial pressure of O2 in arterial blood to the fraction of O2 in the inspired air rising into the normal range where they remained through the 20-h period of study. The studies indicate that pulmonary function in two models of severe meconium injury respond rapidly to BAL with dilute KL4-Surfactant.     

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.     

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.     

An open-loop venetian blind control to avoid direct sunlight and enhance daylight utilization

Shading devices, such as venetian blinds, are widely used to eliminate glare and maintain a comfortable working environment for occupants. This paper proposes an open-loop control of blind height and slat angle based on an analytic model of solar position, and geometry of venetian blinds and the windows. The algorithm enables completely blocking direct sunlight from entering the room beyond a certain user specified interior distance from the window while enhancing daylight utilization. We derive closed-form solutions for blind height and angle which are easily implemented in practice. Moreover, the proposed blind control algorithm is simulated with favorable performance. The algorithm has also been implemented and verified in real-time test-beds.     

Prediction accuracy of direct and indirect approaches,and their relationships with prediction ability of calibration models

Milk infrared spectra are routinely used for phenotyping traits of interest through links developed between the traits and spectra. Predicted individual traits are then used in genetic analyses for estimated breeding value (EBV) or for phenotypic predictions using a single-trait mixed model; this approach is referred to as indirect prediction (IP). An alternative approach [direct prediction (DP)] is a direct genetic analysis of (a reduced dimension of) the spectra using a multitrait model to predict multivariate EBV of the spectral components and, ultimately, also to predict the univariate EBV or phenotype for the traits of interest. We simulated 3 traits under different genetic (low: 0.10 to high: 0.90) and residual (zero to high: ±0.90) correlation scenarios between the 3 traits and assumed the first trait is a linear combination of the other 2 traits. The aim was to compare the IP and DP approaches for predictions of EBV and phenotypes under the different correlation scenarios. We also evaluated relationships between performances of the 2 approaches and the accuracy of calibration equations. Moreover, the effect of using different regression coefficients estimated from simulated phenotypes (β_p), true breeding values (β_g), and residuals (β_r) on performance of the 2 approaches were evaluated. The simulated data contained 2,100 parents (100 sires and 2,000 cows) and 8,000 offspring (4 offspring per cow). Of the 8,000 observations, 2,000 were randomly selected and used to develop links between the first and the other 2 traits using partial least square (PLS) regression analysis. The different PLS regression coefficients, such as β_p, β_g, and β_r, were used in subsequent predictions following the IP and DP approaches. We used BLUP analyses for the remaining 6,000 observations using the true (co)variance components that had been used for the simulation. Accuracy of prediction (of EBV and phenotype) was calculated as a correlation between predicted and true values from the simulations. The results showed that accuracies of EBV prediction were higher in the DP than in the IP approach. The reverse was true for accuracy of phenotypic prediction when using β_p but not when using β_g and β_r, where accuracy of phenotypic prediction in the DP was slightly higher than in the IP approach. Within the DP approach, accuracies of EBV when using β_g were higher than when using β_p only at the low genetic correlation scenario. However, we found no differences in EBV prediction accuracy between the β_p and β_g in the IP approach. Accuracy of the calibration models increased with an increase in genetic and residual correlations between the traits. Performance of both approaches increased with an increase in accuracy of the calibration models. In conclusion, the DP approach is a good strategy for EBV prediction but not for phenotypic prediction, where the classical PLS regression-based equations or the IP approach provided better results.