Harnessing The Collective Wisdom: Fusion Learning Using Decision Sequences From Diverse Sources

Learning from the collective wisdom of crowds enhances the transparency of scientific findings by incorporating diverse perspectives into the decision-making process. Synthesizing such collective wisdom is related to the statistical notion of fusion learning from multiple data sources or studies. However, fusing inferences from diverse sources is challenging since cross-source heterogeneity and potential data-sharing complicate statistical inference. Moreover, studies may rely on disparate designs, employ widely different modeling techniques for inferences, and prevailing data privacy norms may forbid sharing even summary statistics across the studies for an overall analysis. In this paper, we propose an Integrative Ranking and Thresholding (IRT) framework for fusion learning in multiple testing. IRT operates under the setting where from each study a triplet is available: the vector of binary accept-reject decisions on the tested hypotheses, the study-specific False Discovery Rate (FDR) level and the hypotheses tested by the study. Under this setting, IRT constructs an aggregated, nonparametric, and discriminatory measure of evidence against each null hypotheses, which facilitates ranking the hypotheses in the order of their likelihood of being rejected. We show that IRT guarantees an overall FDR control under arbitrary dependence between the evidence measures as long as the studies control their respective FDR at the desired levels. Furthermore, IRT synthesizes inferences from diverse studies irrespective of the underlying multiple testing algorithms employed by them. While the proofs of our theoretical statements are elementary, IRT is extremely flexible, and a comprehensive numerical study demonstrates that it is a powerful framework for pooling inferences.Comment: 29 pages and 10 figures. Under review at a journa

Information entropy-based intention prediction of aerial targets under uncertain and incomplete information

© 2020 by authors. To improve the effectiveness of air combat decision-making systems, target intention has been extensively studied. In general, aerial target intention is composed of attack, surveillance, penetration, feint, defense, reconnaissance, cover and electronic interference and it is related to the state of a target in air combat. Predicting the target intention is helpful to know the target actions in advance. Thus, intention prediction has contributed to lay a solid foundation for air combat decision-making. In this work, an intention prediction method is developed, which combines the advantages of the long short-term memory (LSTM) networks and decision tree. The future state information of a target is predicted based on LSTM networks from real-time series data, and the decision tree technology is utilized to extract rules from uncertain and incomplete priori knowledge. Then, the target intention is obtained from the predicted data by applying the built decision tree. With a simulation example, the results show that the proposed method is effective and feasible for state prediction and intention recognition of aerial targets under uncertain and incomplete information. Furthermore, the proposed method can make contributions in providing direction and aids for subsequent attack decision-makin

Analysis of miRNAs and their target genes associated with lipid metabolism in duck liver

Citation: He, J. et al. Analysis of miRNAs and their target genes associated with lipid metabolism in duck liver. Sci. Rep. 6, 27418; doi: 10.1038/srep27418 (2016).Fat character is an important index in duck culture that linked to local flavor, feed cost and fat intake for costumers. Since the regulation networks in duck lipid metabolism had not been reported very clearly, we aimed to explore the potential miRNA-mRNA pairs and their regulatory roles in duck lipid metabolism. Here, Cherry-Valley ducks were selected and treated with/without 5% oil added in feed for 2 weeks, and then fat content determination was performed on. The data showed that the fat contents and the fatty acid ratios of C17:1 and C18:2 were up-regulated in livers of oil-added ducks, while the C12:0 ratio was down-regulated. Then 21 differential miRNAs, including 10 novel miRNAs, were obtain from the livers by sequencing, and 73 target genes involved in lipid metabolic processes of these miRNAs were found, which constituted 316 miRNA-mRNA pairs. Two miRNA-mRNA pairs including one novel miRNA and one known miRNA, N-miR-16020-FASN and gga-miR-144-ELOVL6, were selected to validate the miRNA-mRNA negative relation. And the results showed that N-mir-16020 and gga-miR-144 could respectively bind the 3?-UTRs of FASN and ELOVL6 to control their expressions. This study provides new sights and useful information for future research on regulation network in duck lipid metabolism

Rubber Toughened and Nanoparticle Reinforced Epoxy Composites

Epoxy resins have achieved acceptance as adhesives, coatings, and potting compounds, but their main application is as matrix to produce reinforced composites. However, their usefulness in this field still limited due to their brittle nature. Some studies have been done to increase the toughness of epoxy composites, of which the most successful one is the modification of the polymer matrix with a second toughening phase. Resin Transfer Molding (RTM) is one of the most important technologies to manufacture fiber reinforced composites. In the last decade it has experimented new impulse, due to its favorable application to produce large surface composites with good technical properties and at relative low cost. This research work focuses on the development of novel modified epoxy matrices, with enhanced mechanical and thermal properties, suitable to be processed by resin transfer molding technology, to manufacture Glass Fiber Reinforced Composites (GFRC’s) with improved performance in comparison to the commercially available ones. In the first stage of the project, a neat epoxy resin (EP) was modified using two different nano-sized ceramics: silicium dioxide (SiO2) and zirconium dioxide (ZrO2); and micro-sized particles of silicone rubber (SR) as second filler. Series of nanocomposites and hybrid modified epoxy resins were obtained by systematic variation of filler contents. The rheology and curing process of the modified epoxy resins were determined in order to define their aptness to be processed by RTM. The resulting matrices were extensively characterized qualitatively and quantitatively to precise the effect of each filler on the polymer properties. It was shown that the nanoparticles confer better mechanical properties to the epoxy resin, including modulus and toughness. It was possible to improve simultaneously the tensile modulus and toughness of the epoxy matrix in more than 30 % and 50 % respectively, only by using 8 vol.-% nano-SiO2 as filler. A similar performance was obtained by nanocomposites containing zirconia. The epoxy matrix modified with 8 vol.-% ZrO2 recorded tensile modulus and toughness improved up to 36% and 45% respectively regarding EP. On the other hand, the addition of silicone rubber to EP and nanocomposites results in a superior toughness but has a slightly negative effect on modulus and strength. The addition of 3 vol.-% SR to the neat epoxy and nanocomposites increases their toughness between 1.5 and 2.5 fold; but implies also a reduction in their tensile modulus and strength in range 5-10%. Therefore, when the right proportion of nanoceramic and rubber were added to the epoxy resin, hybrid epoxy matrices with fracture toughness 3 fold higher than EP but also with up to 20% improved modulus were obtained. Widespread investigations were carried out to define the structural mechanisms responsible for these improvements. It was stated, that each type of filler induces specific energy dissipating mechanisms during the mechanical loading and fracture processes, which are closely related to their nature, morphology and of course to their bonding with the epoxy matrix. When both nanoceramic and silicone rubber are involved in the epoxy formulation, a superposition of their corresponding energy release mechanisms is generated, which provides the matrix with an unusual properties balance. From the modified matrices glass fiber reinforced RTM-plates were produced. The structure of the obtained composites was microscopically analyzed to determine their impregnation quality. In all cases composites with no structural defects (i.e. voids, delaminations) and good superficial finish were reached. The composites were also properly characterized. As expected the final performance of the GFRCs is strongly determined by the matrix properties. Thus, the enhancement reached by epoxy matrices is translated into better GFRC´s macroscopical properties. Composites with up to 15% enhanced strength and toughness improved up to 50%, were obtained from the modified epoxy matrices

Constitutive Equation and Hot Compression Deformation Behavior of Homogenized Al–7.5Zn–1.5Mg–0.2Cu–0.2Zr Alloy

The deformation behavior of homogenized Al–7.5Zn–1.5Mg–0.2Cu–0.2Zr alloy has been studied by a set of isothermal hot compression tests, which were carried out over the temperature ranging from 350 °C to 450 °C and the strain rate ranging from 0.001 s−1 to 10 s−1 on Gleeble-3500 thermal simulation machine. The associated microstructure was studied using electron back scattered diffraction (EBSD) and transmission electron microscopy (TEM). The results showed that the flow stress is sensitive to strain rate and deformation temperature. The shape of true stress-strain curves obtained at a low strain rate (≤0.1 s−1) conditions shows the characteristic of dynamic recrystallization (DRX). Two Arrhenius-typed constitutive equation without and with strain compensation were established based on the true stress-strain curves. Constitutive equation with strain compensation has more precise predictability. The main softening mechanism of the studied alloy is dynamic recovery (DRV) accompanied with DRX, particularly at deformation conditions, with low Zener-Holloman parameters

Magnetic damping forces in figure-eight-shaped null-flux coil suspension systems

This paper discusses magnetic damping forces in figure-eight-shaped null-flux coil suspension systems, focusing on the Holloman maglev rocket system. The paper also discusses simulating the damping plate, which is attached to the superconducting magnet by two short-circuited loop coils in the guideway. Closed-form formulas for the magnetic damping coefficient as functions of heave-and-sway displacements are derived by using a dynamic circuit model. These formulas are useful for dynamic stability studies