University of Tabriz

About: University of Tabriz is a education organization based out in Tabriz, Iran. It is known for research contribution in the topics: Population & Nanocomposite. The organization has 12141 authors who have published 20976 publications receiving 313982 citations.

Potential of radial basis function based support vector regression for global solar radiation prediction

Abstract: Among the different forms of clean energies, solar energy has attracted a lot of attention because it is not only sustainable, but also is renewable and this means that we will never run out of it but the potential of using this form of renewable energy depends on its accessibility. Due to the fact that the number of meteorological stations where global solar radiation (GSR) is recorded, is limited in Iran we were meant to develop four distinctive models based on artificial intelligence in order to prognosticate GSR in Tehran province, Iran. Accordingly, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) and input energies from different meteorological data obtained from the only station in the studied region were selected as the inputs of the model and the GSR was chosen as the output of the models. Instead of minimizing the observed training error, SVR_poly and SVR_rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the proposed approach. The calculated root mean square error and correlation coefficient disclosed that SVR_ rbf performed well in predicting GSR. Comparing SVR_rbf results with SVR_poly, ANFIS, and ANN reveals that SVR_rbf outperforms the POLY model in terms of prediction accuracy.

Whole-exome Sequencing Efficiently Detects Rare Mutations in Autosomal Recessive Nonsyndromic Hearing Loss

Abstract: Identification of the pathogenic mutations underlying autosomal recessive nonsyndromic hearing loss (ARNSHL) is difficult, since causative mutations in 39 different genes have so far been reported. After excluding mutations in the most common ARNSHL gene, GJB2, via Sanger sequencing, we performed whole-exome sequencing (WES) in 30 individuals from 20 unrelated multiplex consanguineous families with ARNSHL. Agilent SureSelect Human All Exon 50 Mb kits and an Illumina Hiseq2000 instrument were used. An average of 93%, 84% and 73% of bases were covered to 1X, 10X and 20X within the ARNSHL-related coding RefSeq exons, respectively. Uncovered regions with WES included those that are not targeted by the exome capture kit and regions with high GC content. Twelve homozygous mutations in known deafness genes, of which eight are novel, were identified in 12 families: MYO15A-p.Q1425X, -p.S1481P, -p.A1551D; LOXHD1-p.R1494X, -p.E955X; GIPC3-p.H170N; ILDR1-p.Q274X; MYO7A-p.G2163S; TECTA-p.Y1737C; TMC1-p.S530X; TMPRSS3-p.F13Lfs*10; TRIOBP-p.R785Sfs*50. Each mutation was within a homozygous run documented via WES. Sanger sequencing confirmed co-segregation of the mutation with deafness in each family. Four rare heterozygous variants, predicted to be pathogenic, in known deafness genes were detected in 12 families where homozygous causative variants were already identified. Six heterozygous variants that had similar characteristics to those abovementioned variants were present in 15 ethnically-matched individuals with normal hearing. Our results show that rare causative mutations in known ARNSHL genes can be reliably identified via WES. The excess of heterozygous variants should be considered during search for causative mutations in ARNSHL genes, especially in small-sized families.