Dynamic allocation for input redundant control systems

In this paper we address control systems with redundant actuators and characterize the concepts of weak and strong input redundancy. Based on this characterization, we propose a dynamic augmentation to a control scheme which performs the plant input allocation with the goal of employing each actuator in a suitable way, based on its magnitude and rate limits. The proposed theory is first developed for redundant plants without saturation and then extended to the case of magnitude saturation first and of magnitude and rate saturation next. Several simulation examples illustrate the proposed technique and show its advantages for practical application.     

A model of domain-polymorph component for heterogeneous system design

Heterogeneous systems mix different technical domains such as signal processing, analog and digital electronics, software, telecommunication protocols, etc. Heterogeneous systems are composed of subsystems that are designed using different models of computation (MoC). These MoCs are the laws that govern the interactions of the components of a subsystem. The design of heterogeneous systems includes the design of each part of the system according to its specific MoC, and the connection of the parts in order to build the model representing the system. Indeed, this model allows the MoCs that govern different parts of system to coexist and interact.To be able to use a component which is specified according to a given MoC, under other, different MoCs, we can use either a hierarchical or a non-hierarchical approach, or we can build domain-specific components (DSC). However, these solutions present several disadvantages. This paper presents a new model of component, called domain-polymorph component (DPC). Such a component is atomic and is able to execute its core behavior, specified under a given MoC, under different host MoCs. This approach is not a competitor to the approaches above but is complementary.     

Adaptive and optimal difference operators in image processing

Differential operators are essential in many image processing applications. Previous work has shown how to compute derivatives more accurately by examining the image locally, and by applying a difference operator which is optimal for each pixel neighborhood. The proposed technique avoids the explicit computation of fitting functions, and replaces the function fitting process by a function classification process using a filter bank of feature detection templates. Both the feature detectors and the optimal difference operators have a specific shape and an associated cost, defined by a rigid mathematical structure, which can be described by Gröbner bases. This paper introduces a cost criterion to select the operator of the best approximating function class and the most appropriate template size so that the difference operator can be locally adapted to the digitized function. We describe how to obtain discrete approximates for commonly used differential operators, and illustrate how image processing applications can benefit from the adaptive selection procedure for the operators by means of two example applications: tangent computation for digitized object boundaries and the Laplacian of Gaussian edge detector.     

Asymptotic properties of mixture-of-experts models

The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the number of experts in the model. Our purpose is to extend the existing results for simple mixture models (Liu and Shao, 2003 [8]) and mixtures of multilayer perceptrons (Olteanu and Rynkiewicz, 2008 [9]). In this paper we first study a simple example which embodies all the difficulties arising in such models. We find that in the most general case the LRTS diverges but, with additional assumptions, the behavior of such models can be totally explicated.     

Demonstration and characterization of biomolecular enrichment on microfluidic aptamer-functionalized surfaces

This paper demonstrates and systematically characterizes the enrichment of biomolecular compounds using aptamer-functionalized surfaces within a microfluidic device. The device consists of a microchamber packed with aptamer-functionalized microbeads and integrated with a microheater and temperature sensor to enable thermally controlled binding and release of biomolecules by the aptamer. We first present an equilibrium binding-based analytical model to understand the enrichment process. The characteristics of the aptamer-analyte binding and enrichment are then experimentally studied, using adenosine monophosphate (AMP) and a specific RNA aptamer as a model system. The temporal process of AMP binding to the aptamer is found to be primarily determined by the aptamer-AMP binding kinetics. The temporal process of aptamer-AMP dissociation at varying temperatures is also obtained and observed to occur relatively rapidly (<2 s). The specificity of the enrichment is next confirmed by performing selective enrichment of AMP from a sample containing biomolecular impurities. Finally, we investigate the enrichment of AMP by either discrete or continuous introduction of a dilute sample into the microchamber, demonstrating enrichment factors ranging from 566 to 686×, which agree with predictions of the analytical model.     

Extended HALS algorithm for nonnegative Tucker decomposition and its applications for multiway analysis and classification

Analysis of high dimensional data in modern applications, such as neuroscience, text mining, spectral analysis, chemometrices naturally requires tensor decomposition methods. The Tucker decompositions allow us to extract hidden factors (component matrices) with different dimension in each mode, and investigate interactions among various modalities. The alternating least squares (ALS) algorithms have been confirmed effective and efficient in most of tensor decompositions, especially Tucker with orthogonality constraints. However, for nonnegative Tucker decomposition (NTD), standard ALS algorithms suffer from unstable convergence properties, demand high computational cost for large scale problems due to matrix inverse, and often return suboptimal solutions. Moreover they are quite sensitive with respect to noise, and can be relatively slow in the special case when data are nearly collinear. In this paper, we propose a new algorithm for nonnegative Tucker decomposition based on constrained minimization of a set of local cost functions and hierarchical alternating least squares (HALS). The developed NTD-HALS algorithm sequentially updates components, hence avoids matrix inverse, and is suitable for large-scale problems. The proposed algorithm is also regularized with additional constraint terms such as sparseness, orthogonality, smoothness, and especially discriminant. Extensive experiments confirm the validity and higher performance of the developed algorithm in comparison with other existing algorithms.     

Synthesis and Characterization of Superparamagnetic NiBaO<Subscript>2</Subscript> Nano-Oxide Using Novel Precursor Complex [Ba(H<Subscript>2</Subscript>O)<Subscript>8</Subscript>][Ni(dipic)<Subscript>2</Subscript>]

In this paper, for the first time, synthesis of [Ba(H₂O)₈][Ni(dipic)₂] complex and preparation of NiBaO₂ nano-oxide are reported through thermal decomposition under surfactant free condition. This novel complex was characterized by Fourier transform infrared spectroscopy (FT-IR), ultra violet–visible spectroscopy, conductivity measurement and elemental analysis. Formation of novel nanoparticles was supported by FT-IR and energy-dispersive X-ray spectroscopy and the orthorhombic structure of nanocrystals was confirmed by powder X-ray diffraction analysis. In addition, size distribution as well as uniform morphology of prepared nano-oxide were recorded by dynamic light scattering analysis and field-emission scanning electron microscopy, respectively. Magnetic features measured by vibrating sample magnetometer, illustrate superparamagnetic behavior of the oxide.     

An Eco-Friendly Ultrasound-Assisted Synthesis of Novel Fluorinated Pyridinium Salts-Based Hydrazones and Antimicrobial and Antitumor Screening

The present work reports an efficient synthesis of fluorinated pyridinium salts-based hydrazones under both conventional and eco-friendly ultrasound procedures. The synthetic approach first involves the preparation of halogenated pyridinium salts through the condensation of isonicotinic acid hydrazide (1) with p-fluorobenzaldehyde (2) followed by the nucleophilic alkylation of the resulting N-(4-fluorobenzylidene)isonicotinohydrazide (3) with a different alkyl iodide. The iodide counteranion of 5–10 was subjected to an anion exchange metathesis reaction in the presence of an excess of the appropriate metal salts to afford a new series of fluorinated pyridinium salts tethering a hydrazone linkage 11–40. Ultrasound irradiation led to higher yields in considerably less time than the conventional methods. The newly synthesized ILs were well-characterized with FT-IR, ¹H NMR, ¹³C NMR, ¹¹B, ¹⁹F, ³¹P and mass spectral analyses. The ILs were also screened for their antimicrobial and antitumor activities. Within the series, the salts tethering fluorinated counter anions 11–13, 21–23, 31–33 and 36–38 were found to be more potent against all bacterial and fungal strains at MIC 4–8 µg/mL. The in vitro antiproliferative activity was also investigated against four tumor cell lines (human ductal breast epithelial tumor T47D, human breast adenocarcinoma MCF-7, human epithelial carcinoma HeLa and human epithelial colorectal adenocarcinoma Caco-2) using the MTT assay, which revealed that promising antitumor activity was exhibited by compounds 5, 12 and 14.     

Use of a selective extractant-impregnated resin for removal of Pb(II) ion from waters and wastewaters: Kinetics,equilibrium and thermodynamic study

Adsorption of Pb(II) ion by a novel extractant-impregnated resin, EIR, was studied as a function of various experimental parameters using batch adsorption experiments. The new EIR was prepared by impregnating gallocyanine (GCN) onto Amberlite XAD-16 resin beads. The EIR was characterized by nitrogen analysis and SEM micrographs. The new EIR showed excellent selectivity factor values (α) for Pb(II) adsorption respect to other metal ions. The effects of some chemical and physical variables were evaluated and the optimum conditions were found for Pb(II) removal from aqueous solutions. The equilibrium adsorption isotherm was fitted with the Langmuir adsorption model. The maximum adsorption capacity (q_max) of EIR for Pb(II) ions was found to be 367.92 mg g⁻¹. The kinetic studies showed that the intra-particle diffusion is the rate-controlling step. Also, the intra-particle diffusion coefficients, D_ip values, were of the order of 10⁻¹² m² s⁻¹. The values of enthalpy (ΔH°) were positive, which confirms the endothermic nature of adsorption process. Also, the positive entropy changes (ΔS°) were showed that the randomness increased along with the adsorption process. In addition, the obtained negative values of Gibbs free energy (ΔG°) indicated feasible and spontaneous nature of the adsorption process at different temperatures. The new adsorbent was very stable so that it can be successfully used for many consecutive cycles without significant loss in its adsorption capacity.