Theoretical determination of lifetimes of metastable states in Sc III and Y III

Lifetimes of the first two metastable states in Sc^{2+} and Y^{2+} are determined using the relativistic coupled-cluster theory. There is a considerable interest in studying the electron correlation effects in these ions as though their electronic configurations are similar to the neutral alkali atoms, their structures are very different from the latter. We have made a comparative study of the correlation trends between the above doubly ionized systems with their corresponding neutral and singly ionized iso-electronic systems. The lifetimes of the excited states of these ions are very important in the field of astrophysics, especially for the study of post-main sequence evolution of the cool giant stars.Comment: 13 pages, 1 figure and 5 table

High-throughput mutational analysis of TOR1A in primary dystonia

<p>Abstract</p> <p>Background</p> <p>Although the c.904_906delGAG mutation in Exon 5 of <it>TOR1A </it>typically manifests as early-onset generalized dystonia, DYT1 dystonia is genetically and clinically heterogeneous. Recently, another Exon 5 mutation (c.863G>A) has been associated with early-onset generalized dystonia and some ΔGAG mutation carriers present with late-onset focal dystonia. The aim of this study was to identify <it>TOR1A </it>Exon 5 mutations in a large cohort of subjects with mainly non-generalized primary dystonia.</p> <p>Methods</p> <p>High resolution melting (HRM) was used to examine the entire <it>TOR1A </it>Exon 5 coding sequence in 1014 subjects with primary dystonia (422 spasmodic dysphonia, 285 cervical dystonia, 67 blepharospasm, 41 writer's cramp, 16 oromandibular dystonia, 38 other primary focal dystonia, 112 segmental dystonia, 16 multifocal dystonia, and 17 generalized dystonia) and 250 controls (150 neurologically normal and 100 with other movement disorders). Diagnostic sensitivity and specificity were evaluated in an additional 8 subjects with known ΔGAG DYT1 dystonia and 88 subjects with ΔGAG-negative dystonia.</p> <p>Results</p> <p>HRM of <it>TOR1A </it>Exon 5 showed high (100%) diagnostic sensitivity and specificity. HRM was rapid and economical. HRM reliably differentiated the <it>TOR1A </it>ΔGAG and c.863G>A mutations. Melting curves were normal in 250/250 controls and 1012/1014 subjects with primary dystonia. The two subjects with shifted melting curves were found to harbor the classic ΔGAG deletion: 1) a non-Jewish Caucasian female with childhood-onset multifocal dystonia and 2) an Ashkenazi Jewish female with adolescent-onset spasmodic dysphonia.</p> <p>Conclusion</p> <p>First, HRM is an inexpensive, diagnostically sensitive and specific, high-throughput method for mutation discovery. Second, Exon 5 mutations in <it>TOR1A </it>are rarely associated with non-generalized primary dystonia.</p

Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/

The C-Module-Binding Factor Supports Amplification of TRE5-A Retrotransposons in the Dictyostelium discoideum Genome ▿

Retrotransposable elements are molecular parasites that have invaded the genomes of virtually all organisms. Although retrotransposons encode essential proteins to mediate their amplification, they also require assistance by host cell-encoded machineries that perform functions such as DNA transcription and repair. The retrotransposon TRE5-A of the social amoeba Dictyostelium discoideum generates a notable amount of both sense and antisense RNAs, which are generated from element-internal promoters, located in the A module and the C module, respectively. We observed that TRE5-A retrotransposons depend on the C-module-binding factor (CbfA) to maintain high steady-state levels of TRE5-A transcripts and that CbfA supports the retrotransposition activity of TRE5-A elements. The carboxy-terminal domain of CbfA was found to be required and sufficient to mediate the accumulation of TRE5-A transcripts, but it did not support productive retrotransposition of TRE5-A. This result suggests different roles for CbfA protein domains in the regulation of TRE5-A retrotransposition frequency in D. discoideum cells. Although CbfA binds to the C module in vitro, the factor regulates neither C-module nor A-module promoter activity in vivo. We speculate that CbfA supports the amplification of TRE5-A retrotransposons by suppressing the expression of an as yet unidentified component of the cellular posttranscriptional gene silencing machinery