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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.

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.