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In this paper, we study a distributionally robust optimization (DRO) problem with affine decision rules. In particular, we construct an ambiguity set based on a new family of Wasserstein metrics, shortfall–Wasserstein metrics, which apply normalized utility-based shortfall risk measures to summarize the transportation cost random variables. In this paper, we demonstrate that the multi-dimensional shortfall–Wasserstein ball can be affinely projected onto a one-dimensional one. A noteworthy result of this reformulation is that our program benefits from finite sample guarantee without a dependence on the dimension of the nominal distribution. This distributionally robust optimization problem also has computational tractability, and we provide a dual formulation and verify the strong duality that enables a direct and concise reformulation of this problem. Our results offer a new DRO framework that can be applied in numerous contexts such as regression and portfolio optimization.

Yanmeizhi Wu,1 Jun Han,1 Kazakova Elena Vladimirovna,1 Shumei Zhang,2 Wenhua Lv,2 Yan Zhang,3 Esma Jamaspishvili,1 Jingxue Sun,1 Qingxiao Fang,1 Jingjing Meng,1 Hong Qiao1 1Department of Endocrinology, No.2 Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, People’s Republic of China; 2Department of Epigenetics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, People’s Republic of China; 3Department of Bioinformatics and Computational Epigenetics, College of Life and Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang Province, People’s Republic of ChinaCorrespondence: Hong QiaoDepartment of Endocrinology, No.2 Affiliated Hospital of Harbin Medical University, No. 148 Baojian Road, Nangang District, Harbin, Heilongjiang Province, People’s Republic of ChinaTel +86 13945677355Email qhong0823@163.comIntroduction: PTC is not generally considered a lethal disease, but prone to recurrence as the prognosis. Hashimoto’s thyroiditis (HT) is an important factor that affects the prognosis of papillary thyroid carcinoma (PTC). It is crucial to find biomarkers to identify the combination of HT with PTC and to predict the prognosis.Methods: RNASeq data from the Cancer Genome Atlas (TCGA) database was used to screen differentially expressed genes (DEGs) of PTC with HT via the edgeR package of R software version 3.3.0. Also, the DEGs were applied to the DAVID web-based tool to determine the enrichment of gene functions via Gene Ontology (GO) analysis and to identify associated pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. By constructing protein interaction networks within Cytoscape software, we screened candidate genes and explored possible relationships with the clinical phenotype of PTC. Finally, additional thyroid tissue samples were collected to verify the results above.Results: After analyzing the RNA-Seq data of PTC patients from the Cancer Genomic Atlas, 497 differentially expressed PTC genes were found to be associated with HT, of which protein tyrosine phosphatase receptor type C (PTPRC), KIT, and COL1A1 were associated with tumor size and lymph node metastasis (p < 0.05). Verification of these results with another 30 thyroid tissues of clinical PTC patients revealed that the expression level of PTPRC in the PTC with HT group was higher than that in the PTC without HT group (p < 0.05) and the ROC curve showed a good discrimination (area under the curve = 0.846). However, the correlation with the clinical phenotype was not statistically significant (p > 0.05).Discussion: These data suggest that upregulation of PTPRC enhances the incidence of HT associated with PTC and is also predictive of a poor prognosis.Keywords: papillary thyroid carcinoma, Hashimoto’s thyroiditis, PTPRC, biomarker, prognosis

Ventricular septal defect (VSD) is one of the most common types of congenital heart disease. To find more and more molecular alteration is conducive to explore the mechanism and biomarker in VSD. Herein we devised a predictive strategy to uncover novel lncRNA of VSD integrating DNA methylation, gene expression and lncRNA expression of early embryo and VSD by profiles from GEO database. In totally, 175 lncRNAs, 7290 genes and 3002 DNA methylation genes were obtained by logistic regression analysis associated with embryonic development. Moreover, 7304 DMGs were significant differential methylated by Wilcoxon rank test and Student’s test in VSD. We constructed the lncRNA-mRNA co-expression network in embryo (LMCNe). Then, a reconstructed co-expression weighted network (RCWN) was built integrated LMCNe and the DNA methylation associated network (DMAN) based on the correlation of the DNA methylation level and protein interaction network between embryonic development and VSD. We extracted top 10 lncRNAs with higher score performing DRaWR from the weight network, which as potential VSD related lncRNAs. Six lncRNAs showed a high level of expression in the heart tissue recorded in the NONOCOND database. Furthermore, associated lncRNA genes DCAF8L1, NIT1, SH2D7 and DOCK9-AS2 in validated samples showed a prominently association with VSD. These outcomes provide a reference for lncRNA involved in VSD initialization and a new insight for studies of VSD-associated lncRNAs.Author SummaryVentricular septal defect (VSD) is one of the most common types of congenital heart disease and has a high mortality rate in infants. Many molecular markers have proved effective as biomarker in VSD like DNA methylation and lncRNA. lncRNA is a type of non-coding RNA which has important effect in regulation gene expression and disease occurrence. VSD is an embryonic stage developmental disease. Therefore we hypothesized that lncRNA which was associated with DNA methylation and mRNA in early embryonic development may also affect the occurrence of VSD. So in this work, from the perspective of embryonic development, we devised a predictive strategy to uncovering novel lncRNA of VSD. In our result, four lncRNA associated genes were found differential expressed in VSD and normal samples by qPCR validation. The identification of lncRNA associated with ventricular septal defect is beneficial to further study the mechanism of VSD from the molecular level and also provides a good molecular marker for clinical therapeutic and diagnosis. At the same time, it also provides a new insight for the researches of lncRNA associated with VSD.

A method of utilizing active resistance network to calibrate the temperature channel of data-acquisition unit is proposed in this paper. This method changes gate-source voltage by micro-controller so as to simulate the resistance. Compares resistance value measured by data-acquisition unit with the simulated resistances to calibrate the performance of the data-acquisition unit. Take DT50 data-acquisition unit in CAWS600 AWS for an example. By software commands, output current and A/D sample duration time of the data-acquisition unit temperature channel are changed to resolve the problem of parameters mismatch, then this data-acquisition unit is calibrated effectively. The experiment result shows this approach provide a reliable means to calibrate AWS data-acquisition unit.