On-line estimation of kinetic parameters in anaerobic digestion using observer-based estimators and multiwavelength fluorometry.

Observer-based estimators (OBE) were used for estimation of state variables and kinetic parameters in an anaerobic digestion (AD) process. A simplified first-order model with time-varying kinetic parameters was used to design an OBE for kinetic parameter estimation. This approach was validated on a laboratory-scale anaerobic reactor equipped with a multiwavelength fluorometer for on-line measurements of COD and VFA concentrations in the reactor effluent. The proposed estimators provide continuous adjustment of kinetic parameters and can be used for predictions of state variables between samples acquisition and during sensor failure.     

Human alpha 2-macroglobulin is an osteogenic growth peptide-binding protein

The osteogenic growth peptide (OGP) is a 14mer mitogen of osteoblastic and fibroblastic cells. Physiologically, OGP is present in high abundance in human and other mammalian sera. Most of the serum OGP is complexed noncovalently to heat sensitive, high molecular weight OGP-binding proteins (OGPBPs). Changes in serum OGP levels that follow bone marrow ablation and the low doses of exogenous OGP required for the stimulation of bone formation suggest a regulatory role for the OGPBPs. In the present work, the OGP binding activity was monitored by competitive binding to [3-125I(Tyr10)]-sOGP and the corresponding complexes were demonstrated on nondenaturing cathodic polyacrylamide gel electrophoresis. We show that OGP binds to both native and activated human plasma alpha 2-macroglobulin (alpha 2M). alpha 2M was also immunoidentified in reduced and nonreduced SDS-polyacrylamide gel electrophoresis of OGP-affinity purified plasma-derived proteins. Immunoreactive OGP was detected in commercial preparations of both forms of alpha 2M; OGP was purified to homogeneity from the commercial preparation of activated alpha 2M. In MC3T3 E1 cells, native alpha 2M, at concentrations < 50 ng/mL, had a substantially increased mitogenic effect in the presence of synthetic, native-like, OGP (sOGP). Similar amounts of activated alpha 2M inhibited the sOGP proliferative effect. These results suggest that the native alpha 2M enhances the immediate availability of OGP to its target cells. Activated alpha 2M may participate in the removal of OGP from the system.     

Comparison of real‐time methods for maximizing power output in microbial fuel cells

Microbial fuel cells (MFCs) constitute a novel power generation technology that converts organic waste to electrical energy using microbially catalyzed electrochemical reactions. Since the power output of MFCs changes considerably with varying operating conditions, the online optimization of electrical load (i.e., external resistance) is extremely important for maintaining a stable MFC performance. The application of several real‐time optimization methods is presented, such as the perturbation and observation method, the gradient method, and the recently proposed multiunit method, for maximizing power output of MFCs by varying the external resistance. Experiments were carried out in two similar MFCs fed with acetate. Variations in substrate concentration and temperature were introduced to study the performance of each optimization method in the face of disturbances unknown to the algorithms. Experimental results were used to discuss advantages and limitations of each optimization method. © 2010 American Institute of Chemical Engineers AIChE J, 2010     

Inhibition of Strontium Sulfate Precipitation by Soluble Polymers

The inhibiting effects of vinyl sulfonate (MVS) and polyvinyl sulfonate (PVS) on the precipitation of strontium sulfate were investigated by absorbance measurements of the turbidity formed. The weights of precipitates retained after 3 h of ripening, by a 0.3 μm Millipore filter from unstirred or stirred solutions containing either PVS or MVS, were determined. The results are interpreted by the heterogeneous nucleation mechanism of crystal growth.     

Application of iron-based cathode catalysts in a microbial fuel cell

Catalysts for the oxygen reduction reaction (ORR) in a microbial fuel cell (MFC) were prepared by the impregnation on carbon black of Fe^II acetate (FeAc), Cl–Fe^III tetramethoxyphenyl porphyrin (ClFeTMPP), and Fe^II phthalocyanine (FePc). These materials were subsequently pyrolyzed at a high temperature. The ORR activity of all Fe-based catalysts was measured at pH 7 with a rotating disk electrode (RDE) and their performance for electricity production was then verified in a continuous flow MFC. Catalysts prepared with FeAc and pyrolyzed in NH₃ showed poor activity in RDE tests as well as a poor performance in a MFC. The ORR activity and fuel cell performance for catalysts prepared with ClFeTMPP and FePc and pyrolyzed in Ar were significantly higher and comparable for both precursors. The iron loading was optimized for FePc-based catalysts. With a constant catalyst load of 2 mg cm⁻² in a MFC, the highest power output (550–590 mW/m²) was observed when the Fe content was 0.5–0.8 wt%, corresponding to only 0.01–016 mg Fe/cm². A similar power output was observed using a Pt-based carbon cloth cathode containing 0.5 mg Pt/cm². Long-term stability of the Fe-based cathode (0.5 wt% Fe) was confirmed over 20 days of MFC testing.     

Asymptotically Optimal Quickest Change Detection in Distributed Sensor Systems

Abstract

In the standard formulation of the quickest change-point detection problem, a sequence of observations, whose distribution changes at some unknown point in time, is available to a decision maker, and the goal is to detect this change as quickly as possible, subject to false alarm constraints. In this paper, we study the quickest change detection problem in the setting where the information available for decision-making is distributed across a set of geographically separated sensors, and only a compressed version of observations in sensors may be used for final decision-making due to communication bandwidth constraints. We consider the minimax, uniform, and Bayesian versions of the optimization problem, and we present asymptotically optimal decentralized quickest change detection procedures for two scenarios. In the first scenario, the sensors send quantized versions of their observations to a fusion center where the change detection is performed based on all the sensor messages. In the second scenario, the sensors perform local change detection and send their final decisions to the fusion center for combining. We show that our decentralized procedures for the latter scenario have the same first-order asymptotic performance as the corresponding centralized procedures that have access to all of the sensor observations. We also present simulation results for examples involving Gaussian and Poisson observations. These examples show that although the procedures with local decisions are globally asymptotically optimal as the false alarm rate (or probability) goes to zero, they perform worse than the corresponding decentralized procedures with binary quantization at the sensors, unless the false alarm rate (or probability) is unreasonably small.     

Multihypothesis sequential probability ratio tests. II. Accurateasymptotic expansions for the expected sample size

For pt. I see ibid. vol.45, p.2448-61, 1999. We proved in pt.I that two specific constructions of multihypothesis sequential tests, which we refer to as multihypothesis sequential probability ratio tests (MSPRTs), are asymptotically optimal as the decision risks (or error probabilities) go to zero. The MSPRTs asymptotically minimize not only the expected sample size but also any positive moment of the stopping time distribution, under very general statistical models for the observations. In this paper, based on nonlinear renewal theory we find accurate asymptotic approximations (up to a vanishing term) for the expected sample size that take into account the “overshoot” over the boundaries of decision statistics. The approximations are derived for the scenario where the hypotheses are simple, the observations are independent and identically distributed (i.i.d.) according to one of the underlying distributions, and the decision risks go to zero. Simulation results for practical examples show that these approximations are fairly accurate not only for large but also for moderate sample sizes. The asymptotic results given here complete the analysis initiated by Baum and Veeravalli (1994), where first-order asymptotics were obtained for the expected sample size under a specific restriction on the Kullback-Leibler distances between the hypotheses     

Biocatalyzed hydrogen production in a continuous flow microbial fuel cell with a gas phase cathode

A single liquid chamber microbial fuel cell (MFC) with a gas-collection compartment was continuously operated under electrically assisted conditions for hydrogen production. Graphite felt was used for anode construction, while the cathode was made of Pd/Pt coated Toray carbon fiber paper with a catalyst loading of 0.5 mg cm⁻². To achieve hydrogen production, the MFC was connected to a power supply and operated at voltages in a range of 0.5–1.3 V. Either acetate or glucose was used as a source of carbon. At an acetate load of 1.67 g (L_A d)⁻¹, the volumetric rate of hydrogen production reached 0.98 L_STP (L_A d)⁻¹ when a voltage of 1.16 V was applied. This corresponded to a hydrogen yield of 2 mol (mol-acetate)⁻¹ with a 50% conversion efficiency. Throughout the experiment, MFC efficiency was adversely affected by the metabolic activity of methanogenic microorganisms, which competed with exoelectrogenic microorganisms for the carbon source and consumed part of the hydrogen produced at the cathode.     

Method for increasing the accuracy of wavefront reconstruction from a set of interferograms

A new approach to the wavefront (phase) reconstruction from interferograms is proposed based on the classical method of fringe tracing using a sample of interferograms with different numbers and orientations of interference fringes. Wavefronts reconstructed from individual interferograms are averaged, and the test surface quality is judged by the data obtained. Averaging the phase by several interferograms makes it possible to reduce the variance of the phase reconstruction error caused by random noise and inhomogeneities in aperture illumination and interference fringe distribution, as well as to reduce the effect of instability of external conditions.