What is the weakest topology in which feedback stability is robust?

Mathematical theorems in control theory are only of interest in so far as their assumptions relate to practical situations. The space of systems with transfer functions in ℋ∞, for example, has many advantages mathematically, but includes large classes of non-physical systems, and one must be careful in drawing inferences from results in that setting. Similarly, the graph topology has long been known to be the weakest, or coarsest, topology in which (1) feedback stability is a robust property (i.e. preserved in small neighbourhoods) and (2) the map from open-to-closed-loop transfer functions is continuous. However, it is not known whether continuity is a necessary part of this statement, or only required for the existing proofs. It is entirely possible that the answer depends on the underlying classes of systems used. The class of systems we concern ourselves with here is the set of systems that can be approximated, in the graph topology, by real rational transfer function matrices. That is, lumped parameter models, or those distributed systems for which it makes sense to use finite element methods. This is precisely the set of systems that have continuous frequency responses in the extended complex plane. For this class, we show that there is indeed a weaker topology; in which feedback stability is robust but for which the maps from open-to-closed-loop transfer functions are not necessarily continuous. © 2013 Copyright Taylor and Francis Group, LLC.

Trust-Level Risk Evaluation and Risk Control Guidance in the NHS East of England

In recent years, the healthcare sector has adopted the use of operational risk assessment tools to help understand the systems issues that lead to patient safety incidents. But although these problem-focused tools have improved the ability of healthcare organizations to identify hazards, they have not translated into measurable improvements in patient safety. One possible reason for this is a lack of support for the solution-focused process of risk control. This article describes a content analysis of the risk management strategies, policies, and procedures at all acute (i.e., hospital), mental health, and ambulance trusts (health service organizations) in the East of England area of the British National Health Service. The primary goal was to determine what organizational-level guidance exists to support risk control practice. A secondary goal was to examine the risk evaluation guidance provided by these trusts. With regard to risk control, we found an almost complete lack of useful guidance to promote good practice. With regard to risk evaluation, the trusts relied exclusively on risk matrices. A number of weaknesses were found in the use of this tool, especially related to the guidance for scoring an event's likelihood. We make a number of recommendations to address these concerns. The guidance assessed provides insufficient support for risk control and risk evaluation. This may present a significant barrier to the success of risk management approaches in improving patient safety. © 2013 Society for Risk Analysis.

Durability indicators of SCC towards performance-based specifications for the durability of SCC

The fundamental principle behind the development of SCC has been the nanoscale tailoring of cementitious matrices. Although self-compacting concrete (SCC) is currently used in many countries, there is a fundamental lack of the intrinsic durability of the material itself. The scope of the current paper is to present the outcomes of a research study on some principal indicators (porosity and capillary absorption) that define the durability of SCC, and how these are compared with the corresponding parameters of conventional concrete. Furthermore, this paper investigates the addition of industrial by-products, such as fly-ash or lime powder, to SCC mixtures and their effect on the durability indicators.

Combined effects of polyfluorinated and perfluorinated compounds on primary cultured hepatocytes from rare minnow (Gobiocypris rarus) using toxicogenomic analysis

Polyfluorinated and perfluorinated compounds (PFCs) are used in numerous commercial products and have been ubiquitously detected in the environment as well as in the blood of humans and wildlife. To assess the combined effects caused by PFCs in mixtures, gene expression profiles were generated using a custom cDNA microarray to detect changes in primary cultured hepatocytes of rare minnows exposed to six individual PFCs (perfluorooctanoic acid, perfluorononanoic acid, perfluorodecanoic acid, perfluorododecanoic acid, perfluorooctane sulfonate, and 8:2 fluorotelomer alcohol) and four formulations of the PFCs mixtures. Mixtures as well as individual compounds consistently regulated a particular gene set, which suggests that these conserved genes may play a central role in the toxicity mediated by PFCs. Specifically, a number of genes regulated by the mixtures were identified in this study, which were not affected by exposure to any single component. These genes are implicated in multiple biological functions and processes, including fatty acid metabolism and transport, xenobiotic metabolism, immune responses, and oxidative stress. More than 80% of the altered genes in the PFOA- and PFOS-dominant mixture groups were of the same gene set, while the gene expression profiles from single PFOA and PFOS exposures were not as similar. This work contributes to the development of toxicogenomic approaches in combined toxicity assessment and allows for comprehensive insights into the combined action of PFCs mixtures in multiple environmental matrices. (C) 2009 Elsevier B.V. All rights reserved.

Rapid quantification of total microcystins in cyanobacterial samples by periodate-permanganate oxidation and reversed-phase liquid chromatography

Microcystins (MCs) comprise a family of more than 80 related cyclic hepatotoxic heptapeptides. Oxidation of MCs causes cleavage of the chemically unique C-20 beta-amino acid (2S, 3S, 8S, 9S)-3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid (Adda) amino to form 2-methyl-3-methoxy-4-phenylbutanoic acid (MMPB), which has been exploited to enable analysis of the entire family. In the present study, the reaction conditions (e.g. concentration of the reactants. temperature and pH) used in the production of MMPB by oxidation of cyanobacterial samples with permanganate-periodate were optimized through a series of well-controlled batch experiments. The oxidation product (MMPB) was then directly analyzed by high-performance liquid chromatography with diode array detection. The results of this study provided insight into the influence of reaction conditions on the yield of MMPB. Specifically, the optimal conditions, including a high dose of permanganate (>= 50 mM) in saturated periodate solution at ambient temperature under alkaline conditions (pH similar to 9) over 1-4 h were proposed, as indicated by a MMPB yield of greater than 85%. The technique developed here was applied to determine the total concentration of MCs in cyanobacterial bloom samples, and indicated that the MMPB technique was a highly sensitive and accurate method of quantifying total MCs. Additionally, these results will aid in development of a highly effective analytical method for detection of MMPB as an oxidation product for evaluation of total MCs in a wide range of environmental sample matrices, including natural waters, soils (sediments) and animal tissues. (C) 2009 Elsevier B.V. All rights reserved.

Computational modelling and characterisation of nanoparticle-based tuneable photonic crystal sensors

Photonic crystals are materials that are used to control or manipulate the propagation of light through a medium for a desired application. Common fabrication methods to prepare photonic crystals are both costly and intricate. However, through a cost-effective laser-induced photochemical patterning, one-dimensional responsive and tuneable photonic crystals can easily be fabricated. These structures act as optical transducers and respond to external stimuli. These photonic crystals are generally made of a responsive hydrogel that can host metallic nanoparticles in the form of arrays. The hydrogel-based photonic crystal has the capability to alter its periodicity in situ but also recover its initial geometrical dimensions, thereby rendering it fully reversible and reusable. Such responsive photonic crystals have applications in various responsive and tuneable optical devices. In this study, we fabricated a pH-sensitive photonic crystal sensor through photochemical patterning and demonstrated computational simulations of the sensor through a finite element modelling technique in order to analyse its optical properties on varying the pattern and characteristics of the nanoparticle arrays within the responsive hydrogel matrix. Both simulations and experimental results show the wavelength tuneability of the sensor with good agreement. Various factors, including nanoparticle size and distribution within the hydrogel-based responsive matrices that directly affect the performance of the sensors, are also studied computationally. © 2014 The Royal Society of Chemistry.

A reversible infinite HMM using normalised random measures

Copyright 2014 by the author(s). We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected we define a prior over random walks on graphs that results in a reversible Markov chain. The resulting prior over infinite transition matrices is closely related to the hierarchical Dirichlet process but enforces reversibility. A reinforcement scheme has recently been proposed with similar properties, but the de Finetti measure is not well characterised. We take the alternative approach of explicitly constructing the mixing measure, which allows more straightforward and efficient inference at the cost of no longer having a closed form predictive distribution. We use our process to construct a reversible infinite HMM which we apply to two real datasets, one from epigenomics and one ion channel recording.

Nonylphenol and octylphenol in urban eutrophic lakes of the subtropical China

The paper studied two estrogenic pollutants, 4-nonylphenol (NP) and 4-tert-octylphenol (OP) in water, suspended particle (SP) and sediments in urban eutrophic lakes. The concentrations of NP ranged from 1.94 to 32.85 mu g/l, 0.876 to 31.13 mu g/l and 3.54 to 32.43 mu g/g dry weight (dw) in water, suspended particle (SP) and sediments, respectively, and that of OP from 0.027 to 1.44 mu g/l, 0.008 to 1.777 mu g/l and 0.058 to 1.245 mu g/g dw in water, suspended particle (SP) and sediments, respectively. An increasing trend in the concentration was noticed in all matrices close to the sewage inlets, which was found to be the major factor affecting the spatial distribution of alkylphenols (APs) in the lakes. Due to restoration of submerged macrophytes, which might accumulate APs, the contaminations of APs in the Little Moon Lake (LML) and the Little Lotus Lake (LLL) were lower than those in the Big, Moon Lake (BML) and the Bier Lotus Lake (BLL). A reasonable correlation of NP and OP was obtained among water, suspended particle and sediment. The possible environmental stress of APs concentration on aquatic organisms in Wuhan urban lakes was also discussed.

Synchronization of user-generated videos through trajectory correspondence and a refinement procedure

Temporal synchronization of multiple video recordings of the same dynamic event is a critical task in many computer vision applications e.g. novel view synthesis and 3D reconstruction. Typically this information is implied through the time-stamp information embedded in the video streams. User-generated videos shot using consumer grade equipment do not contain this information; hence, there is a need to temporally synchronize signals using the visual information itself. Previous work in this area has either assumed good quality data with relatively simple dynamic content or the availability of precise camera geometry. Our first contribution is a synchronization technique which tries to establish correspondence between feature trajectories across views in a novel way, and specifically targets the kind of complex content found in consumer generated sports recordings, without assuming precise knowledge of fundamental matrices or homographies. We evaluate performance using a number of real video recordings and show that our method is able to synchronize to within 1 sec, which is significantly better than previous approaches. Our second contribution is a robust and unsupervised view-invariant activity recognition descriptor that exploits recurrence plot theory on spatial tiles. The descriptor is individually shown to better characterize the activities from different views under occlusions than state-of-the-art approaches. We combine this descriptor with our proposed synchronization method and show that it can further refine the synchronization index. © 2013 ACM.

A solid-phase microextraction fiber coated with diglycidyloxycalix[4]arene yields very high extraction selectivity and sensitivity during the analysis of chlorobenzenes in soil

A novel fiber coated with novel sol-gel (5,11,17,23-tetra-tert-butyl-25,27-dihydroxy-26,28-diglycidyloxycalix[4]arene/hydroxy-terminated silicone oil; diglycidyloxy-C[4]/OH-TSO) was prepared for use with headspace solid-phase microextraction (HS-SPME) combined with gas chromatography (GC) and electron capture detection (ECD), which was applied in order to determine nine chlorobenzenes in soil matrices. Due to the improved fiber preparation, which increases the percentage of calixarene in the coating, the new calixarene fiber exhibits very high extraction selectivity and sensitivity to chlorine-substituted compounds. Various parameters affecting the extraction efficiency were optimized in order to maximize the sensitivity during the chlorobenzene analysis. Interferences from different soil matrices with different characteristics were investigated, and the amount extracted was strongly influenced by the matrix. Therefore, a standard addition protocol was performed on the real soil samples. The linear ranges of detection for the chlorobenzenes tested covered three orders of magnitude, and correlation coefficients > 0.9976 and relative standard deviations (RSD) < 8% were observed. The detection limits were found at sub-ng/g of soil levels, which were about an order of magnitude lower than those given by the commercial poly(dimethylsiloxane) (PDMS) coating for most of the compounds. The recoveries ranged from 64 to 109.6% for each analyte in the real kaleyard soil matrix when different concentration levels were determined over the linear range, which confirmed the reliability and feasibility of the HS-SPME/GC-ECD approach using the fiber coated with diglycidyloxy-C[4]/OH-TSO for the ultratrace analysis of chlorobenzenes in complex matrices.

Fixed-rank matrix factorizations and Riemannian low-rank optimization

Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and then exploit the Riemannian quotient geometry of the search space in the design of a class of gradient descent and trust-region algorithms. The proposed algorithms generalize our previous results on fixed-rank symmetric positive semidefinite matrices, apply to a broad range of applications, scale to high-dimensional problems, and confer a geometric basis to recent contributions on the learning of fixed-rank non-symmetric matrices. We make connections with existing algorithms in the context of low-rank matrix completion and discuss the usefulness of the proposed framework. Numerical experiments suggest that the proposed algorithms compete with state-of-the-art algorithms and that manifold optimization offers an effective and versatile framework for the design of machine learning algorithms that learn a fixed-rank matrix. © 2013 Springer-Verlag Berlin Heidelberg.

Structure, magnetization, and low-temperature spin dynamic behavior of zincblende Mn-rich Mn(Ga)As nanoclusters embedded in GaAs

We have fabricated a set of samples of zincblende Mn-rich Mn(Ga)As clusters embedded in GaAs matrices by annealing (Ga,Mn)As films with different nominal Mn content at 650 degrees C. For the samples with Mn content no more than 4.5%, the Curie temperature reaches nearly 360 K. However, when Mn content is higher than 5.4%, the samples exhibit a spin-glass-like behavior. We suggest that these different magnetic properties are caused by the competing result of dipolar and Ruderman-Kittel-Kasuya-Yosida interaction among clusters. The low-temperature spin dynamic behavior, especially the relaxation effect, shows the extreme creeping effect which is reflected by the time constant tau of similar to 10(11) s at 10 K. We explain this phenomenon by the hierarchical model based on the mean-field approach. We also explain the memory effect by the relationship between the correlation function and the susceptibility.

Memory effect in a system of zincblende Mn-rich Mn(Ga)As nanoclusters embedded in GaAs

Zincblende Mn-rich Mn(Ga)As nanoclusters embedded in GaAs matrices are fabricated by in situ postgrowth annealing diluted magnetic semiconductor (Ga,Mn)As films with Mn concentration ranging from 2.6% to 8% at 650 degrees C. Magnetization measurements show that memory effect and slow magnetic relaxation, the typical characteristics of the spin-glass-like phase, occur below the blocking temperature of 45 K in samples with high Mn concentration, while for samples with low Mn concentration, ferromagnetic order remains up to 360 K. The behavior of low-temperature spin dynamics can be explained by the hierarchical model. (c) 2007 American Institute of Physics.

A 16-term error model based on linear equations of voltage and current variables

Formulation of a 16-term error model, based on the four-port ABCD-matrix and voltage and current variables, is outlined. Matrices A, B, C, and D are each 2 x 2 submatrices of the complete 4 x 4 error matrix. The corresponding equations are linear in terms of the error parameters, which simplifies the calibration process. The parallelism with the network analyzer calibration procedures and the requirement of five two-port calibration measurements are stressed. Principles for robust choice of equations are presented. While the formulation is suitable for any network analyzer measurement, it is expected to be a useful alternative for the nonlinear y-parameter approach used in intrinsic semiconductor electrical and noise parameter measurements and parasitics' deembedding.

Amorphous silicon nanoparticles in compound films grown on cold substrates for high-efficiency photoluminescence

Silicon nanoparticles have been fabricated in both oxide and nitride matrices by using plasma-enhanced chemical vapour deposition, for which a low substrate temperature down to 50 degreesC turns out to be most favourable. High-rate deposition onto such a cold substrate results in the formation of nanoscaled silicon particles, which have revealed an amorphous nature under transmission electron microscope (TEM) examination. The particle size can be readily controlled below 3.0 nm, and the number density amounts to over 10(12) cm(-2), as calculated from the TEM micrographs. Strong photoluminescence in the whole visible light range has been observed in the as-deposited Si-in-SiOx and Si-in-SiNx thin films. Without altering the size or structure of the particles, a post-annealing at 300 degreesC for 2 min raised the photoluminescence efficiency to a level comparable to the achievements with nanocrystalline Si-in-SiO2 samples prepared at high temperature. This low-temperature procedure for fabricating light-emitting silicon structures opens up the possibility of manufacturing integrated silicon-based optoelectronics.