Decentralized Sliding Mode Control for Output Tracking of Large-Scale Interconnected Systems

In this paper, a class of nonlinear interconnected systems with matched and unmatched uncertainties is considered. The isolated subsystem dynamics are described by linear systems and a nonlinear component. The matched uncertainties and unmatched unknown interconnection terms are assumed to be bounded by known functions. Based on sliding mode techniques, a state feedback decentralized control scheme is proposed such that the outputs of the controlled interconnected system track given desired signals uniformly ultimately. The desired reference signals are allowed to be time-varying. Using multiple transformations, the considered system is transferred to a new interconnected system with an appropriate structure to facilitate the sliding surface design and the design of a decentralized controller. A set of conditions is proposed to guarantee that the designed controller drives the tracking errors onto the sliding surface. The sliding motion exhibited by the error dynamics is uniformly ultimately bounded. The developed results are applied to a river quality control problem. Simulation results show that the proposed decentralized control strategy is effective and feasible

CNV analysis in Chinese children of mental retardation highlights a sex differentiation in parental contribution to de novo and inherited mutational burdens

Rare copy number variations (CNVs) are a known genetic etiology in neurodevelopmental disorders (NDD). Comprehensive CNV analysis was performed in 287 Chinese children with mental retardation and/or development delay (MR/DD) and their unaffected parents. When compared with 5,866 ancestry-matched controls, 11~12% more MR/DD children carried rare and large CNVs. The increased CNV burden in MR/DD was predominantly due to de novo CNVs, the majority of which (62%) arose in the paternal germline. We observed a 2~3 fold increase of large CNV burden in the mothers of affected children. By implementing an evidence-based review approach, pathogenic structural variants were identified in 14.3% patients and 2.4% parents, respectively. Pathogenic CNVs in parents were all carried by mothers. The maternal transmission bias of deleterious CNVs was further replicated in a published dataset. Our study confirms the pathogenic role of rare CNVs in MR/DD, and provides additional evidence to evaluate the dosage sensitivity of some candidate genes. It also supports a population model of MR/DD that spontaneous mutations in males’ germline are major contributor to the de novo mutational burden in offspring, with higher penetrance in male than female; unaffected carriers of causative mutations, mostly females, then contribute to the inherited mutational burden.published_or_final_versio

Identifying Topological Order by Entanglement Entropy

Topological phases are unique states of matter incorporating long-range quantum entanglement, hosting exotic excitations with fractional quantum statistics. We report a practical method to identify topological phases in arbitrary realistic models by accurately calculating the Topological Entanglement Entropy (TEE) using the Density Matrix Renormalization Group (DMRG). We argue that the DMRG algorithm naturally produces a minimally entangled state, from amongst the quasi-degenerate ground states in a topological phase. This proposal both explains the success of this method, and the absence of ground state degeneracy found in prior DMRG sightings of topological phases. We demonstrate the effectiveness of the calculational procedure by obtaining the TEE for several microscopic models, with an accuracy of order $10^{-3}$ when the circumference of the cylinder is around ten times the correlation length. As an example, we definitively show the ground state of the quantum $S=1/2$ antiferromagnet on the kagom\'e lattice is a topological spin liquid, and strongly constrain the full identification of this phase of matter.Comment: 20 pages, 6 figure

Gene-based multiple trait analysis for exome sequencing data

The common genetic variants identified through genome-wide association studies explain only a small proportion of the genetic risk for complex diseases. The advancement of next-generation sequencing technologies has enabled the detection of rare variants that are expected to contribute significantly to the missing heritability. Some genetic association studies provide multiple correlated traits for analysis. Multiple trait analysis has the potential to improve the power to detect pleiotropic genetic variants that influence multiple traits. We propose a gene-level association test for multiple traits that accounts for correlation among the traits. Gene- or region-level testing for association involves both common and rare variants. Statistical tests for common variants may have limited power for individual rare variants because of their low frequency and multiple testing issues. To address these concerns, we use the weighted-sum pooling method to test the joint association of multiple rare and common variants within a gene. The proposed method is applied to the Genetic Association Workshop 17 (GAW17) simulated mini-exome data to analyze multiple traits. Because of the nature of the GAW17 simulation model, increased power was not observed for multiple-trait analysis compared to single-trait analysis. However, multiple-trait analysis did not result in a substantial loss of power because of the testing of multiple traits. We conclude that this method would be useful for identifying pleiotropic genes

Prognostic and therapeutic significance of carbohydrate antigen 19-9 as tumor marker in patients with pancreatic cancer

In pancreatic cancer ( PC) accurate determination of treatment response by imaging often remains difficult. Various efforts have been undertaken to investigate new factors which may serve as more appropriate surrogate parameters of treatment efficacy. This review focuses on the role of carbohydrate antigen 19- 9 ( CA 19- 9) as a prognostic tumor marker in PC and summarizes its contribution to monitoring treatment efficacy. We undertook a Medline/ PubMed literature search to identify relevant trials that had analyzed the prognostic impact of CA 19- 9 in patients treated with surgery, chemoradiotherapy and chemotherapy for PC. Additionally, relevant abstract publications from scientific meetings were included. In advanced PC, pretreatment CA 19- 9 levels have a prognostic impact regarding overall survival. Also a CA 19- 9 decline under chemotherapy can provide prognostic information for median survival. A 20% reduction of CA 19- 9 baseline levels within the first 8 weeks of chemotherapy appears to be sufficient to define a prognostic relevant subgroup of patients ('CA 19- 9 responder'). It still remains to be defined whether the CA 19- 9 response is a more reliable method for evaluating treatment efficacy compared to conventional imaging. Copyright (c) 2006 S. Karger AG, Basel

Vector assembly of colloids on monolayer substrates

The key to spontaneous and directed assembly is to encode the desired assembly information to building blocks in a programmable and efficient way. In computer graphics, raster graphics encodes images on a single-pixel level, conferring fine details at the expense of large file sizes, whereas vector graphics encrypts shape information into vectors that allow small file sizes and operational transformations. Here, we adapt this raster/vector concept to a 2D colloidal system and realize 'vector assembly' by manipulating particles on a colloidal monolayer substrate with optical tweezers. In contrast to raster assembly that assigns optical tweezers to each particle, vector assembly requires a minimal number of optical tweezers that allow operations like chain elongation and shortening. This vector approach enables simple uniform particles to form a vast collection of colloidal arenes and colloidenes, the spontaneous dissociation of which is achieved with precision and stage-by-stage complexity by simply removing the optical tweezers

Realistic Standard Model Fermion Mass Relations in Generalized Minimal Supergravity (GmSUGRA)

Grand Unified Theories (GUTs) usually predict wrong Standard Model (SM) fermion mass relation m_e/m_{\mu} = m_d/m_s toward low energies. To solve this problem, we consider the Generalized Minimal Supergravity (GmSUGRA) models, which are GUTs with gravity mediated supersymmetry breaking and higher dimensional operators. Introducing non-renormalizable terms in the super- and K\"ahler potentials, we can obtain the correct SM fermion mass relations in the SU(5) model with GUT Higgs fields in the {\bf 24} and {\bf 75} representations, and in the SO(10) model. In the latter case the gauge symmetry is broken down to SU(3)_C X SU(2)_L X SU(2)_R X U(1)_{B-L}, to flipped SU(5)X U(1)_X, or to SU(3)_C X SU(2)_L X U(1)_1 X U(1)_2. Especially, for the first time we generate the realistic SM fermion mass relation in GUTs by considering the high-dimensional operators in the K\"ahler potential.Comment: JHEP style, 29 pages, no figure,references adde

Confined conversion of CuS nanowires to CuO nanotubes by annealing-induced diffusion in nanochannels

Copper oxide (CuO) nanotubes were successfully converted from CuS nanowires embedded in anodic aluminum oxide (AAO) template by annealing-induced diffusion in a confined tube-type space. The spreading of CuO and formation of CuO layer on the nanochannel surface of AAO, and the confinement offered by AAO nanochannels play a key role in the formation of CuO nanotubes