A fluorogenic peptide containing the processing site of human SARS corona virus S-protein: kinetic evaluation and NMR structure elucidation

Human severe acute respiratory syndrome coronavirus (hSARS-CoV) is the causative agent for SARS infection. Its surface glycoprotein (spike protein) is considered to be one of the prime targets for SARS therapeutics and intervention because its proteolytic maturation by a host protease is crucial for host-virus fusion. Using intramolecularly quenched fluorogenic (IQF) peptides based on hSARS-CoV spike protein (Abz-(755)Glu-Gln-Asp-Arg-Asn-Thr-Arg-Glu-Val-Phe-Ala-Gln(766)-Tyx-NH(2)) and in vitro studies, we show that besides furin, other PCs, like PC5 and PC7, might also be involved in this cleavage event. Through kinetic measurements with recombinant PCs, we observed that the peptide was cleaved efficiently by both furin and PC5, but very poorly by PC7. The cleavage could be blocked by a PC-inhibitor, alpha1-PDX, in a dose-dependent manner. Circular dichroism spectra indicated that this peptide possesses a high degree of sheet structure. Following cleavage by furin, the sheet content increased, possibly at the expense of turn and random structures. (1)H NMR spectra from 2D COSY and ROESY experiments under physiological buffer and pH conditions indicated that this peptide possesses a structure with a turn at its C-terminal segment, close to the cleavage site. The data suggest that the cleavable peptide bond is located within the most exposed domain; this is supported by the nearby turn structure. Several strong to weak NMR ROESY correlations were detected, and a 3D structure of the spike IQF peptide that contains the crucial cleavage site R(761) E has been proposed.     

Variance-penalized Markov decision processes: dynamic programming and reinforcement learning techniques

In control systems theory, the Markov decision process (MDP) is a widely used optimization model involving selection of the optimal action in each state visited by a discrete-event system driven by Markov chains. The classical MDP model is suitable for an agent/decision-maker interested in maximizing expected revenues, but does not account for minimizing variability in the revenues. An MDP model in which the agent can maximize the revenues while simultaneously controlling the variance in the revenues is proposed. This work is rooted in machine learning/neural network concepts, where updating is based on system feedback and step sizes. First, a Bellman equation for the problem is proposed. Thereafter, convergent dynamic programming and reinforcement learning techniques for solving the MDP are provided along with encouraging numerical results on a small MDP and a preventive maintenance problem.     

Electrochemical Pretreatment of Wastewater from Bulk Drug Manufacturing Industry

The present study involves the treatment of high strength Bulk Drug Industry Wastewater by electrochemical method. The treatability studies were carried out with four different electrodes made of mild steel, aluminum, carbon, and stainless steel. The treatment efficiencies for chemical oxygen demand (COD)/biochemical oxygen demand (BOD), color, and heavy metal removals were assessed at different electrolysis time. A comparative study for heavy metal removal between chemical precipitation using aluminum and electrocoagulation with aluminum electrode has shown electrocoagulation to be more effective. Carbon electrode has shown COD removal of 34.0% and high BOD5f/CODf ratio of 0.581 at 120-min exposure time. Among all electrodes, aluminum was found as the most efficient in removal of color, suspended solids, and heavy metals with the least energy consumption of 95.83?Wh?kg?1?CODr and anode efficiency of 5.76?kg?COD?A?1?m?2?h?1. After electrochemical treatment, certain increase in BOD/COD ratio attributed to increase in biodegradability of wastewater. The study reveals that the wastewater could be effectively pretreated by electrochemical method.     

Cooperative adaptive control for synchronization of second‐order systems with unknown nonlinearities

This paper studies synchronization to a desired trajectory for multi‐agent systems with second‐order integrator dynamics and unknown nonlinearities and disturbances. The agents can have different dynamics and the treatment is for directed graphs with fixed communication topologies. The command generator or leader node dynamics is also nonlinear and unknown. Cooperative tracking adaptive controllers are designed based on each node maintaining a neural network parametric approximator and suitably tuning it to guarantee stability and performance. A Lyapunov‐based proof shows the ultimate boundedness of the tracking error. A simulation example with nodes having second‐order Lagrangian dynamics verifies the performance of the cooperative tracking adaptive controller. Copyright © 2010 John Wiley & Sons, Ltd.     

BIST/Digital-Compatible Testing of RF Devices Using Distortion Model Fitting

Testing of Radio Frequency (RF) circuits for nonlinearity specifications generally requires the use of multiple test measurements thereby contributing to increased test cost. Prior RF test methods have suffered from significant test calibration effort (training for supervised learners) when using compact tests or from increased test time due to direct specification measurement. On the other hand, due to aggressive technology scaling, there are plenty of digital transistors available that can be used to simplify testing of Analog/Mixed-Signal (AMS) and RF devices. In this paper, an RF test methodology is developed that: (a) allows RF devices to be tested for several distortion specifications using distortion model fitting algorithms in test time comparable to what can be achieved using supervised learning techniques while retaining the accuracy of direct specification measurement, (b) allows multiple RF specifications to be determined concurrently from a single data acquisition and (c) allows digital-compatible testing/BIST to be performed using digital testers or on-chip built in self-test (BIST) circuitry. With regard to (a), a key benefit is that no training of supervised learning algorithm is necessary. The proposed method based on distortion model fitting is shown to give excellent results across common RF performance metrics while providing ~10× improvements in test time compared to previous methods.     

Effect of silica doping on the densification and grain growth in zinc oxide

The ability of silica (SiO₂) in controlling the densification and grain growth behavior of nano crystalline zinc oxide (ZnO) has been systematically studied. It has been observed that SiO₂ acts as a sintering inhibitor in the ZnO–SiO₂ system up to 4 wt.% limiting value beyond which densification behavior of the system remains almost unchanged, especially above 1100 °C. The addition of SiO₂ to ZnO retards grain growth which in turn results a finer ultimate grain size as compared to the undoped ZnO. However, stabilization in grain size occurs at ≥4 wt.% SiO₂ addition. It has been observed that SiO₂ incorporation changes the grain growth mechanism up to 4 wt.% addition, beyond which no remarkable changes was noticed. The grain growth (n) shows distinctly different slopes as a function of sintering time for the SiO₂ doped ZnO systems than undoped ZnO. The different slopes tend to indicate that different diffusion mechanisms and probably the formation of a secondary phase (Zn–Si–O) at the grain boundary control the densification and grain growth. The thermal expansion coefficient of the system has been found to decrease substantially beyond 4 wt.% SiO₂ addition to ZnO.     

Studies on Hg(II) ion retention properties of cross-linked graft copolymer of acrylic acid and its analytical application

The effects of different parameters such as time, concentration, pH and temperature, on metal ion retention properties of the polymer have been investigated. Metal ion adsorption kinetics, isotherms and thermodynamics have been studied. A plausible mechanism for mercury ion retention has been suggested. Mercuric ion has been isolated quantitatively from various synthetic mixture containing metal ions (Ni²⁺, Cd²⁺, Pb²⁺ and Zn²⁺).     

Photoelectrochemical performances of indium-doped CdS0.2Se0.8 thin film electrodes prepared by spray pyrolysis

Polycrystalline undoped and indium-doped CdS_0.2Se_0.8 thin films were deposited on FTO-coated glass substrates by spray pyrolysis. The cell configurations CdS_0.2Se_0.8/1 M (Na₂S + S + NaOH)/C and In:CdS_0.2Se_0.8/1 M (Na₂S + S + NaOH)/C were used to study a wide range of photoelectrochemical characteristics including capacitance–voltage in the dark, current–voltage characteristics in the dark and under illumination, photovoltaic power output and spectral response and to perform electrochemical impedance spectroscopy studies. The study reveals that the films exhibit n-type conductivity. Various PEC parameters such as the junction ideality factor under illumination, series and shunt resistances, fill factor and efficiency have been estimated for the PEC cells formed with CdS_0.2Se_0.8 and indium-doped CdS_0.2Se_0.8 thin films. The efficiency and fill factor of these PEC cells are found to be improved from 0.79% and 0.46 to 2.12% and 0.49, respectively, with indium doping in CdS_0.2Se_0.8 thin films. Electrochemical impedance spectroscopy studies show that doping of indium into CdS_0.2Se_0.8 thin film improves the performance of resulting PEC cells.     

Rheological studies of two component high build epoxy and polyurethane based high performance coatings

The work presented in this article involves the study of rheometric profile of several rheological additives in two-component (2K) high build epoxy zinc phosphate primer and two-component high build aliphatic polyurethane topcoat. Viscosity profile and thixotropic behavior at different shear rates have been determined for both the paints using Physica MCR 301 Rheometer of Anton Paar. The valuable information derived from these measurements led to better insight into the influence of these rheological additives on important paint properties like flow and leveling, sag control, in-can settling during storage, etc. Rheometric results were also compared with the results obtained during the actual application of these experimental coatings on mild steel panels. From the rheological study it was concluded that the thickeners based on surface-modified clay and organically modified castor oil derivative work well in epoxy zinc phosphate primer whereas polyurea-based thickener showed better results than other rheological additives in the case of the 2K polyurethane system. Measurement of low shear and high shear viscosity response of different thickeners helps in predicting storage and application behavior of these coatings which correlates well with the actual observation.