Major Congenital Metabolic Disorders in the First 12 years of Life in 79,100 Consecutively Born Children in Qazvin Province

ObjectiveDeficient enzyme activity may cause congenital metabolic defects. These defectsare inherited in an autosomal recessive, autosomal dominant, and X-linkedpatterns. This study was aimed at investigating the occurrence of metabolicdiseases in Qazvin Province.Materials & MethodsThis cross-sectional study was performed on 79,100 children aged 12 years orless between 2000 and 2010. Clinical manifestations, laboratory findings, and allother essential information were assessed to precisely diagnose the metabolicdiseases. The sorted information on congenital metabolic defects of the patients,information included in a checklist, and data were analyzed usnig SPSS.ResultsA total of 57 metabolic disorders were recorded. The difference in the prevalenceof metabolic disorders between male (29 cases) and female (28 cases) wasnot statistically significant. The most frequent congenital metabolic disorderamong our patients was phenylketonuria (PKU; 5 per 1,000 cases), and the leastcommon disorder was galactosemia (3 per 1,000 cases).ConclusionTimely detection and management of congenital metabolic disorders canhelp save the affected children. Prenatal screening programs, molecular genetherapy, and counseling for consanguineous marriage can play important rolesin reducing the rate of metabolic disorders in this province.Keywords: Congenital metabolic disorders; prevalence; population; Qazvin  

A New Method for Multisensor Data Fusion Based on Wavelet Transform in a Chemical Plant

Abstract This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet "db4" functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter for the final state estimation. The recent data are recursively utilized to apply wavelet transform and extract the variance of the updated data, which makes it suitable to be applied to both static and dynamic systems corrupted by noisy environments. The method has suitable performance in state estimation in comparison with the other alternative algorithms. A three-tank benchmark system has been adopted to comparatively demonstrate the performance merits of the method compared to a known algorithm in terms of efficiently satisfying signal-tonoise (SNR) and minimum square error (MSE) criteria

Gaussian Process Modelling for Uncertainty Quantification in Convectively-Enhanced Dissolution Processes in Porous Media

Numerical groundwater flow and dissolution models of physico-chemical processes in deep aquifers are usually subject to uncertainty in one or more of the model input parameters. This uncertainty is propagated through the equations and needs to be quantified and characterised in order to rely on the model outputs. In this paper we present a Gaussian process emulation method as a tool for performing uncertainty quantification in mathematical models for convection and dissolution processes in porous media. One of the advantages of this method is its ability to significantly reduce the computational cost of an uncertainty analysis, while yielding accurate results, compared to classical Monte Carlo methods. We apply the methodology to a model of convectively-enhanced dissolution processes occurring during carbon capture and storage. In this model, the Gaussian process methodology fails due to the presence of multiple branches of solutions emanating from a bifurcation point, i.e., two equilibrium states exist rather than one. To overcome this issue we use a classifier as a precursor to the Gaussian process emulation, after which we are able to successfully perform a full uncertainty analysis in the vicinity of the bifurcation point

Interfacial instability of reactive and anisotropic dispersive miscible displacements flows

Bibliography: p. 185-192Some pages are in colour

The computational dialectometry of Talysh varieties across western-southern side of Caspian Sea

Dialectometrics is a quantitative approach to measure the differences among varying dialects using statistical measurement on a large number of linguistic features in a dialectal area. A dialect atlas, as such, displays variations of language across a geographical area. The present study employs an aggregate data analysis method as well as RuG/L04 dialectometry and cartography software to provide a perspective of phonological and lexical variation in Guilan province, Iran. The statistical population of the study includes residents of five Talysh-speaking towns in Guilan province, i.e. Talysh, Rezvanshahr, Masal, Fuman and Shaft. In each town/area 10 villages with more than 100 Talysh-speaking households were selected. The selected participants were male and they were classified in three age groups including the teen, the middle-aged and the elderly. The data were collected using Leipzig and Swadesh language questionnaires which include 65 words and 7 sentences. The results indicate that Talysh speakers tend to behave similarly in phonetic and lexical items in some semantic fields whereas in some other fields differences surface. The age variable proves to be significant in using older local words and the younger subjects tend to use standard Persian. In sum, three general dialects are recognized in Talysh, and each dialect has its own phonetic and lexical variations