Regularization of descriptor systems

Implicit dynamic-algebraic equations, known in control theory as descriptor systems, arise naturally in many applications. Such systems may not be regular (often referred to as singular). In that case the equations may not have unique solutions for consistent initial conditions and arbitrary inputs and the system may not be controllable or observable. Many control systems can be regularized by proportional and/or derivative feedback.We present an overview of mathematical theory and numerical techniques for regularizing descriptor systems using feedback controls. The aim is to provide stable numerical techniques for analyzing and constructing regular control and state estimation systems and for ensuring that these systems are robust. State and output feedback designs for regularizing linear time-invariant systems are described, including methods for disturbance decoupling and mixed output problems. Extensions of these techniques to time-varying linear and nonlinear systems are discussed in the final section.

The equivalent-weights particle filter in a high-dimensional system

In general, particle filters need large numbers of model runs in order to avoid filter degeneracy in high-dimensional systems. The recently proposed, fully nonlinear equivalent-weights particle filter overcomes this requirement by replacing the standard model transition density with two different proposal transition densities. The first proposal density is used to relax all particles towards the high-probability regions of state space as defined by the observations. The crucial second proposal density is then used to ensure that the majority of particles have equivalent weights at observation time. Here, the performance of the scheme in a high, 65 500 dimensional, simplified ocean model is explored. The success of the equivalent-weights particle filter in matching the true model state is shown using the mean of just 32 particles in twin experiments. It is of particular significance that this remains true even as the number and spatial variability of the observations are changed. The results from rank histograms are less easy to interpret and can be influenced considerably by the parameter values used. This article also explores the sensitivity of the performance of the scheme to the chosen parameter values and the effect of using different model error parameters in the truth compared with the ensemble model runs.

Solvothermal synthesis of one-dimensional chalcogenides containing group 13 elements

The solvothermal synthesis and characterisation of [C6H16N2][GaS2]2 (1), [C6H16N2][Ga2Se3(Se2)] (2), and mixed-metal phases with composition [C6H16N2][Ga2–xInxSe3(Se2)] (0 < x < 2)(3–5), is described. These materials have been characterised by single-crystal and powder X-ray diffraction, thermogravimetric analysis and UV/Vis diffuse reflectance spectroscopy. The materials contain one-dimensional anionic chains. In 1, these chains consist of edge-linked GaS4 tetrahedra, whilst in 2–5, the chains contain perselenide (Se2)2– units and comprise alternating four-membered [M2Se2] and five-membered [M2Se3] rings (where M = Ga, In). Compounds 3–5 represent the first examples of ternary mixed-metal [M2Se3(Se2)]2– chains.

Modelling the rheology of anisotropic particles adsorbed on a two-dimensional fluid interface

We present a general approach based on nonequilibrium thermodynamics for bridging the gap between a well-defined microscopic model and the macroscopic rheology of particle-stabilised interfaces. Our approach is illustrated by starting with a microscopic model of hard ellipsoids confined to a planar surface, which is intended to simply represent a particle-stabilised fluid–fluid interface. More complex microscopic models can be readily handled using the methods outlined in this paper. From the aforementioned microscopic starting point, we obtain the macroscopic, constitutive equations using a combination of systematic coarse-graining, computer experiments and Hamiltonian dynamics. Exemplary numerical solutions of the constitutive equations are given for a variety of experimentally relevant flow situations to explore the rheological behaviour of our model. In particular, we calculate the shear and dilatational moduli of the interface over a wide range of surface coverages, ranging from the dilute isotropic regime, to the concentrated nematic regime.

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

A simple and versatile 2-dimensional platform to study plant germination and growth under controlled humidity

We describe a simple, inexpensive, but remarkably versatile and controlled growth environment for the observation of plant germination and seedling root growth on a flat, horizontal surface over periods of weeks. The setup provides to each plant a controlled humidity (between 56% and 91% RH), and contact with both nutrients and atmosphere. The flat and horizontal geometry of the surface supporting the roots eliminates the gravitropic bias on their development and facilitates the imaging of the entire root system. Experiments can be setup under sterile conditions and then transferred to a non-sterile environment. The system can be assembled in 1-2 minutes, costs approximately 8.78$ per plant, is almost entirely reusable (0.43$ per experiment in disposables), and is easily scalable to a variety of plants. We demonstrate the performance of the system by germinating, growing, and imaging Wheat (Triticum aestivum), Corn (Zea mays), and Wisconsin Fast Plants (Brassica rapa). Germination rates were close to those expected for optimal conditions.

Hydrothermal synthesis of [C6H16N2][In2Se3(Se2)]: a new one-dimensional indium selenide

A new organically templated indium selenide, [C6H16N2][In2Se3(Se2)], has been prepared hydrothermally from the reaction of indium, selenium and trans-1,4-diaminocyclohexane in water at 170 °C. This material was characterised by single-crystal and powder X-ray diffraction, thermogravimetric analysis, UV–vis diffuse reflectance spectroscopy, FT-IR and elemental analysis. The compound crystallises in the monoclinic space group C2/c (a=12.0221(16) Å, b=11.2498(15) Å, c=12.8470(17) Å, β=110.514(6)°). The crystal structure of [C6H16N2][In2Se3(Se2)] contains anionic chains of stoichiometry [In2Se3(Se2)]2−, which are aligned parallel to the [1 0 1] direction, and separated by diprotonated trans-1,4-diaminocyclohexane cations. The [In2Se3(Se2)]2− chains, which consist of alternating four-membered [In2Se2] and five-membered [In2Se3] rings, contain perselenide (Se2)2− units. UV–vis diffuse reflectance spectroscopy indicates that [C6H16N2][In2Se3(Se2)] has a band gap of 2.23(1) eV

Na5(Ga4S)(GaS4)3·6H2O: a three-dimensional thiogallate containing a novel octahedral building block

The new thiogallate Na5(Ga4S)(GaS4)3·6H2O has been prepared solvothermally, using 3,5-dimethyl pyridine as a solvent, and characterised by powder and single crystal X-ray diffraction. This material, which exhibits a three-dimensional crystal structure, crystallises in the cubic space group View the MathML sourceF4¯3c (a = 17.557(4) Å). The crystal structure contains octahedral building blocks [Ga4S (GaS4)6]20−, linked into a three-dimensional network with a perovskite-type topology, and sodium hydrate clusters, [Na5(H2O)6]5+, filling the cavities in the [Ga4S(GaS4)6/2]5− framework. UV–Vis diffuse reflectance measurements indicate that this material is a wide band gap semiconductor, with a band gap of ca. 4.4 eV.

Synthesis, characterisation and magnetic properties of a one-dimensional Iron(II) coordination polymer

A new iron(II) coordination polymer, [FeCl2(NC7H9)2(N2C12H12)], has been synthesized under solvothermal conditions and structurally characterized by single-crystal X-ray diffraction. This material crystallizes in the monoclinic space group C2/c, with a = 11.2850(6), b = 13.8925(7), c = 17.0988(9) Å and β = 94.300(3)º (Z = 4). The crystal structure consists of neutral zig-zag chains, in which the iron(II) ions are octahedrally coordinated. The infinite polymer chains are packed into a three-dimensional structure through C–H···Cl interactions. Magnetic susceptibility measurements reveal the existence of weak antiferromagnetic interactions between the iron(II) ions. The effective magnetic moment, μ eff = 5.33 μ B , is consistent with a high-spin iron(II) configuration.

Human neural stem cell-derived cultures in three- dimensional substrates form spontaneously functional neuronal networks

Differentiated human neural stem cells were cultured in an inert three-dimensional (3D) scaffold and, unlike two-dimensional (2D) but otherwise comparable monolayer cultures, formed spontaneously active, functional neuronal networks that responded reproducibly and predictably to conventional pharmacological treatments to reveal functional, glutamatergic synapses. Immunocytochemical and electron microscopy analysis revealed a neuronal and glial population, where markers of neuronal maturity were observed in the former. Oligonucleotide microarray analysis revealed substantial differences in gene expression conferred by culturing in a 3D vs a 2D environment. Notable and numerous differences were seen in genes coding for neuronal function, the extracellular matrix and cytoskeleton. In addition to producing functional networks, differentiated human neural stem cells grown in inert scaffolds offer several significant advantages over conventional 2D monolayers. These advantages include cost savings and improved physiological relevance, which make them better suited for use in the pharmacological and toxicological assays required for development of stem cell-based treatments and the reduction of animal use in medical research.

Three dimensional analysis of cardiovascular development in mouse embryos using X-ray microcomputed tomography

Micro-computed tomography (μCT) has been successfully used to study the cardiovascular system of mouse embryos in situ. With the use of barium as a suitable contrast agent, blood vessels have been imaged and analysed quantitatively such as blood volume and vessel sizes on embryos of ages 14.5 to 16.5 days old. The advantage of using this imaging modality is that it has provided three dimensional information whilst leaving samples intact for further study.

Zero-Dimensional Units of Ligand-Bridged Gallium-Sulfide Supertetrahedra

The synthesis and characterization of the first anions containing two gallium-sulfide supertetrahedra linked via an organic moiety are described.

Three-dimensional gallium sulphide open framework

The synthesis and crystal structure of four gallium sulphide open frameworks, built from supertetrahedral clusters, are described. The structures of [C4NH12]6[Ga10S18][C4NH12]6[Ga10S18](1) and [C4NH12]12[Ga20S35.5(S3)0.5O](2) contain supertetrahedral T3 clusters, while in the isostructural compounds [C4NH12]16[Ga10S18M4Ga16S33][C4NH12]16[Ga10S18M4Ga16S33] (M=CoM=Co(3), Zn (4)), T3 and T4 clusters alternate. These materials exhibit three-dimensional frameworks, with topologies consisting of two interpenetrating diamond lattices, and contain over 50% of solvent accessible void space. UV–Vis diffuse reflectance measurements indicate that these compounds are semiconducting, with band gaps over the range 3.4–4.1 eV.

A five-dimensional model of attributes: some precursors of executive coach selection

The purpose of this study was to specify a set of attributes, identified as important precursors to coach selection. Executive coaching has grown exponentially, but there have been few studies as to the efficacy of coaching, including the factors that influence a manager's choice of coach. This study sought to identify these factors. The 45-item, online survey produced 267 useable responses. Results of the principal component analysis suggested a five-factor solution, with women showing a statistically significant preference over men for coaches who have the Ability to Develop Critical Thinking and Action, the Ability to Forge the Coaching Partnership and Coach Experience and Qualifications. The impact of coachee age was not significant in selecting executive coaches. The findings show a statistically significant relationship between coach attributes and the intention to continue with coaching. The implications of these findings for the selection of coaches, and for the coaching profession are discussed.

Aspects of particle filtering in high-dimensional spaces

Nonlinear data assimilation is high on the agenda in all fields of the geosciences as with ever increasing model resolution and inclusion of more physical (biological etc.) processes, and more complex observation operators the data-assimilation problem becomes more and more nonlinear. The suitability of particle filters to solve the nonlinear data assimilation problem in high-dimensional geophysical problems will be discussed. Several existing and new schemes will be presented and it is shown that at least one of them, the Equivalent-Weights Particle Filter, does indeed beat the curse of dimensionality and provides a way forward to solve the problem of nonlinear data assimilation in high-dimensional systems.