A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China

There are two typical subprocesses in bank production—deposit generation and loan generation. Aiming to open the black box of input-output production of banks and provide comprehensive and accurate assessment on the efficiency of each stage, this paper proposes a two-stage network model with bad outputs and supper efficiency (US-NSBM). Empirical comparisons show that the US-NSBM may be promising and practical for taking the nonperforming loans into account and being able to rank all samples. Applying it to measure the efficiency of Chinese commercial banks from 2008 to 2012, this paper explores the characteristics of overall and divisional efficiency, as well as the determinants of them. Some interesting results are discovered. The polarization of efficiency occurs in the bank level and deposit generation, yet does not in the loan generation. Five hypotheses work as expected in the bank level, but not all of them are supported in the stage level. Our results extend and complement some earlier empirical publications in the bank level

Adaptive trajectories sampling for solving PDEs with deep learning methods

In this paper, we propose a new adaptive technique, named adaptive trajectories sampling (ATS), which is used to select training points for the numerical solution of partial differential equations (PDEs) with deep learning methods. The key feature of the ATS is that all training points are adaptively selected from trajectories that are generated according to a PDE-related stochastic process. We incorporate the ATS into three known deep learning solvers for PDEs, namely the adaptive derivative-free-loss method (ATS-DFLM), the adaptive physics-informed neural network method (ATS-PINN), and the adaptive temporal-difference method for forward-backward stochastic differential equations (ATS-FBSTD). Our numerical experiments demonstrate that the ATS remarkably improves the computational accuracy and efficiency of the original deep learning solvers for the PDEs. In particular, for some specific high-dimensional PDEs, the ATS can even improve the accuracy of the PINN by two orders of magnitude.Comment: 18 pages, 12 figures, 42 reference

Ultra-precise Micro-motion Stage for Optical Scanning Test

This study aims at the application of optical sensing technology in a 2D flexible hinge test stage. Optical fiber sensor which is manufactured taking advantage of the various unique properties of optical fiber, such as good electric insulation properties, resistance of electromagnetic disturbance, sparkless property and availability in flammable and explosive environment, has lots of good properties, such as high accuracy and wide dynamic range, repeatable, etc. and is applied in 2D flexible hinge stage driven by PZT. Several micro-bending structures are designed utilizing the characteristics of the flexible hinge stage. And through experiments, the optimal micro-bending tooth structure and the scope of displacement sensor trip under this optimal micro-bending tooth structure are derived. These experiments demonstrate that the application of optical fiber displacement sensor in 2D flexible hinge stage driven by PZT substantially broadens the dynamic testing range and improves the sensitivity of this apparatus. Driving accuracy and positioning stability are enhanced as well

General power-law temporal scaling for unequal-size microbubble coalescence

We systematically study the effects of liquid viscosity, liquid density, and surface tension on global microbubble coalescence using lattice Boltzmann simulation. The liquid-gas system is characterized by Ohnesorge number Oh ≡ ηh/√ρhσrF with ηh, ρh, σ, and rF being viscosity and density of liquid, surface tension, and the radius of the larger parent bubble, respectively. This study focuses on the microbubble coalescence without oscillation in an Oh range between 0.5 and 1.0. The global coalescence time is defined as the time period from initially two parent bubbles touching to finally one child bubble when its half-vertical axis reaches above 99% of the bubble radius. Comprehensive graphics processing unit parallelization, convergence check, and validation are carried out to ensure the physical accuracy and computational efficiency. From 138 simulations of 23 cases, we derive and validate a general power-law temporal scaling T ∗ = A0γ−n, that correlates the normalized global coalescence time (T ∗) with size inequality (γ ) of initial parent bubbles. We found that the prefactor A0 is linear to Oh in the full considered Oh range, whereas the power index n is linear to Oh when Oh 0.66. The physical insights of the coalescence behavior are explored. Such a general temporal scaling of global microbubble coalescence on size inequality may provide useful guidance for the design, development, and optimization of microfluidic systems for various applications

The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: bioinformatics towards translational applications

The 2018 International Conference on Intelligent Biology and Medicine (ICIBM 2018) was held on June 10–12, 2018, in Los Angeles, California, USA. The conference consisted of a total of eleven scientific sessions, four tutorials, one poster session, four keynote talks and four eminent scholar talks, which covered a wild range of aspects of bioinformatics, medical informatics, systems biology and intelligent computing. Here, we summarize nine research articles selected for publishing in BMC Bioinformatics

A Recombination Hotspot in a Schizophrenia-Associated Region of GABRB2

Background: Schizophrenia is a major disorder with complex genetic mechanisms. Earlier, population genetic studies revealed the occurrence of strong positive selection in the GABRB2 gene encoding the β2 subunit of GABAA receptors, within a segment of 3,551 bp harboring twenty-nine single nucleotide polymorphisms (SNPs) and containing schizophrenia-associated SNPs and haplotypes. Methodology/Principal Findings:In the present study, the possible occurrence of recombination in this 'S1-S29' segment was assessed. The occurrence of hotspot recombination was indicated by high resolution recombination rate estimation, haplotype diversity, abundance of rare haplotypes, recurrent mutations and torsos in haplotype networks, and experimental haplotyping of somatic and sperm DNA. The sub-segment distribution of relative recombination strength, measured by the ratio of haplotype diversity (Hd) over mutation rate (θ), was indicative of a human specific Alu-Yi6 insertion serving as a central recombining sequence facilitating homologous recombination. Local anomalous DNA conformation attributable to the Alu-Yi6 element, as suggested by enhanced DNase I sensitivity and obstruction to DNA sequencing, could be a contributing factor of the increased sequence diversity. Linkage disequilibrium (LD) analysis yielded prominent low LD points that supported ongoing recombination. LD contrast revealed significant dissimilarity between control and schizophrenic cohorts. Among the large array of inferred haplotypes, H26 and H73 were identified to be protective, and H19 and H81 risk-conferring, toward the development of schizophrenia. Conclusions/Significance: The co-occurrence of hotspot recombination and positive selection in the S1-S29 segment of GABRB2 has provided a plausible contribution to the molecular genetics mechanisms for schizophrenia. The present findings therefore suggest that genome regions characterized by the co-occurrence of positive selection and hotspot recombination, two interacting factors both affecting genetic diversity, merit close scrutiny with respect to the etiology of common complex disorders. © 2010 Ng et al