A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error Bound

In this work, we develop a simple algorithm for semi-supervised regression. The key idea is to use the top eigenfunctions of integral operator derived from both labeled and unlabeled examples as the basis functions and learn the prediction function by a simple linear regression. We show that under appropriate assumptions about the integral operator, this approach is able to achieve an improved regression error bound better than existing bounds of supervised learning. We also verify the effectiveness of the proposed algorithm by an empirical study.Comment: Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012

The complete mitochondrial genomes of two ghost moths, Thitarodes renzhiensis and Thitarodes yunnanensis: the ancestral gene arrangement in Lepidoptera

BACKGROUND: Lepidoptera encompasses more than 160,000 described species that have been classified into 45–48 superfamilies. The previously determined Lepidoptera mitochondrial genomes (mitogenomes) are limited to six superfamilies of the lineage Ditrysia. Compared with the ancestral insect gene order, these mitogenomes all contain a tRNA rearrangement. To gain new insights into Lepidoptera mitogenome evolution, we sequenced the mitogenomes of two ghost moths that belong to the non-ditrysian lineage Hepialoidea and conducted a comparative mitogenomic analysis across Lepidoptera. RESULTS: The mitogenomes of Thitarodes renzhiensis and T. yunnanensis are 16,173 bp and 15,816 bp long with an A + T content of 81.28 % and 82.34 %, respectively. Both mitogenomes include 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and the A + T-rich region. Different tandem repeats in the A + T-rich region mainly account for the size difference between the two mitogenomes. All the protein-coding genes start with typical mitochondrial initiation codons, except for cox1 (CGA) and nad1 (TTG) in both mitogenomes. The anticodon of trnS(AGN) in T. renzhiensis and T. yunnanensis is UCU instead of the mostly used GCU in other sequenced Lepidoptera mitogenomes. The 1,584-bp sequence from rrnS to nad2 was also determined for an unspecified ghost moth (Thitarodes sp.), which has no repetitive sequence in the A + T-rich region. All three Thitarodes species possess the ancestral gene order with trnI-trnQ-trnM located between the A + T-rich region and nad2, which is different from the gene order trnM-trnI-trnQ in all previously sequenced Lepidoptera species. The formerly identified conserved elements of Lepidoptera mitogenomes (i.e. the motif ‘ATAGA’ and poly-T stretch in the A + T-rich region and the long intergenic spacer upstream of nad2) are absent in the Thitarodes mitogenomes. CONCLUSION: The mitogenomes of T. renzhiensis and T. yunnanensis exhibit unusual features compared with the previously determined Lepidoptera mitogenomes. Their ancestral gene order indicates that the tRNA rearrangement event(s) likely occurred after Hepialoidea diverged from other lepidopteran lineages. Characterization of the two ghost moth mitogenomes has enriched our knowledge of Lepidoptera mitogenomes and contributed to our understanding of the mechanisms underlying mitogenome evolution, especially gene rearrangements

Practical formula to calculate tension of vertical cable with hinged-fixed conditions based on vibration method

Vertical cables are widely used in the tied-arch bridges and suspension bridges as the vital components to transfer load. It is very important to accurately estimate the cable tensions in the cable supported bridges during both construction and in-service stages. Vibration method is the most widely used method for in-situ measurement of cable tensions. But for the cables with hinged-fixed boundary conditions, no analytical formulas can be used to describe the relationship between the frequencies and the cable tension. According to the general solution of the vibration equation and based on its numerical computational results, practical formula to calculate tensions of vertical cables by multiple natural frequencies satisfying hinged-fixed boundary conditions is proposed in this paper. The expression of the practical formula is the same as the solution derived from an axially loaded beam with simple supported ends and can use the first 10 order frequencies to calculate the cable tension conveniently and accurately. Error analysis showed that when using the fundamental frequency to estimate cable force, the estimated tension errors of the cables with its dimensionless parameter ξ≥ 2.8 are less than 2 %. It contained nearly all of the vertical cables used in bridge engineering. In addition, with multiple natural frequencies being measured, bending stiffness of the cable can be identified by using the formulas presented in this paper with an iterative method. At last, the practical formula in this paper is verified to have high precision with several numerical examples, and can be conveniently applied to field test for cable-supported bridges

Integrated analysis of long non-coding RNAs and mRNAs associated with glaucoma in vitro

IntroductionIn recent years, the biological functions and important roles of long non-coding RNAs (lncRNAs) have been widely reported in many diseases. Although glaucoma is the leading cause of blindness worldwide, the specific mechanisms of lncRNAs in the pathogenesis and progression of glaucoma remain unclear. Our research aims to elucidate the differentially expressed lncRNAs and mRNAs in glaucoma and to provide a basis for further exploration of the specific mechanism of action of lncRNAs in the progression of glaucoma.MethodsWe performed RNA sequencing on samples from a pressurized model of R28 cells and performed bioinformatics analyses on the sequencing results. The expression consistency of lncRNAs in clinical samples from patients with glaucoma or cataracts was detected using real-time quantitative polymerase chain reaction (RT-qPCR).ResultsRNA sequencing results showed that lncRNAs in cluster 5 were upregulated with increasing stress after typing all significantly altered lncRNAs using k-means in a cellular stress model. KEGG analysis indicated that they were associated with neurodegenerative diseases. Differentially expressed lncRNAs were verified by RT-qPCR, and the lncRNA expression levels of AC120246.2 and XLOC_006247 were significantly higher in the aqueous humor (AH) of patients with glaucoma than in those with cataracts. For LOC102551819, there was almost no expression in the AH and trabecular meshwork in patients with glaucoma but high expression was observed in the iris. ConclusionOur research proposes potential diagnostic or intervention targets for clinical applications as well as a theoretical basis for more in-depth research on the function of lncRNAs in glaucoma