Evaluation of Digitally Encoded Layer‐by‐layer Coated Microparticles as Cell Carriers

To obtain more biologically relevant data there is a growing interest in the use of living cells for assaying the biological activity of unknown chemical compounds. Density ‘multiplex’ cell‐based assays, where different cell types are mixed in one well and simultaneously investigated upon exposure to a certain compound are beginning to emerge. To be able to identify the cells they should be attached to microscopic carriers that are encoded. This paper investigates how digitally encoded microparticles can be loaded with cells while keeping the digital code in the microcarriers readable. It turns out that coating the surface of the encoded microcarriers with polyelectrolytes using the layer‐by‐layer (LbL) approach provides the microcarriers with a ‘highly functional’ surface. The polyelectrolyte layer allows the growth of the cells, allows the orientation of the cell loaded microcarriers in a magnetic field, and does not hamper the reading of the code. It has further been shown that the cells growing on the polyelectrolyte layer can become transduced by adenoviral particles hosted by the polyelectrolyte layer. It is concluded that the digitally encoded microparticles are promising materials for use in biomedical and pharmaceutical in‐vitro research where cells are used as tools.     

Noise–Power Optimization of Incremental Data Converters

Incremental data converters (IDCs) are useful in instrumentation and measurement applications, where low-frequency analog signals need to be converted into digital form with high accuracy and low power dissipation. They are particularly well suited for applications where a single analog-digital converter is multiplexed between many channels. This paper proposes an exact design methodology for IDCs, which optimizes the signal-to-noise ratio of the converter under practical design constraints. The process also allows the designer to apportion the noise budget in an arbitrary manner between thermal and quantization noise. The design process is illustrated by an example which describes the optimization of a third-order multiplexed IDC.     

A Novel Ordered Nanopore Array Diode Laser

In this work, we have created a new type of structure, the nanopore active layer, for achieving quantization of carrier states in a semiconductor. The nanopore structure consists of a periodic two-dimensional array of localized energy barriers perturbing an otherwise conventional quantum well. This perturbation leads to the formation of intraband forbidden energy gaps which are observed experimentally.     

Photo-Fenton removal of water-soluble polymers

This paper presents the results of experiments carried out in a laboratory-scale photochemical reactor on the photodegradation of different polymers in aqueous solutions by the photo-Fenton process. Solutions of three polymers, polyethyleneglicol (PEG), polyacrylamide (PAM), and polyvinylpyrrolidone (PVP), were tested under different conditions. The reaction progress was evaluated by sampling and analyzing the total organic carbon concentration in solution (TOC) along the reaction time. The behavior of the different polymers is discussed, based on the evolution of the TOC–time curves. Under specific reaction conditions, the formation and coalescence of solid particles was visually observed. Solids formation occurred simultaneously to a sharp decrease in the TOC of the liquid phase. This may be favorable for the treatment of industrial wastewater containing polymers, since the photodegradation process can be coupled with solid separation systems, which may reduce the treatment cost.     

Implementation of adaptive critic-based neurocontrollers for turbogenerators in a multimachine power system

This paper presents the design and practical hardware implementation of optimal neurocontrollers that replace the conventional automatic voltage regulator (AVR) and the turbine governor of turbogenerators on multimachine power systems. The neurocontroller design uses a powerful technique of the adaptive critic design (ACD) family called dual heuristic programming (DHP). The DHP neurocontrollers' training and testing are implemented on the Innovative Integration M67 card consisting of the TMS320C6701 processor. The measured results show that the DHP neurocontrollers are robust and their performance does not degrade unlike the conventional controllers even when a power system stabilizer (PSS) is included, for changes in system operating conditions and configurations. This paper also shows that it is possible to design and implement optimal neurocontrollers for multiple turbogenerators in real time, without having to do continually online training of the neural networks, thus avoiding risks of instability.     

Robustness of classification rules that incorporate additional information

The discrimination problem for two normal populations with the same covariance matrix when additional information on the population is available is considered. A study of the robustness properties against training sample contamination of classification rules that incorporate this additional information is performed. These rules have received recently attention where their total misclassification probability (TMP) is proved to be lower than Fisher's linear discriminant rule. The results of a simulation study on the TMP which compares the behaviour of the new rules against Fisher's rule and some of its robustified versions under different types of contamination are presented. These results show that the rules that incorporate the additional information not only have lower TMP, but they also prevent against some types of contamination. In order to achieve prevention from all types of contamination a robustifed version of these rules is recommended.     

Power sector development in India with CO2 emission targets: Effects of regional grid integration and the role of clean technologies

The power sector in India at present comprises of five separate regional electricity grids having practically no integrated operation in between them. This study analyses the utility planning, environmental and economical effects of integrated power sector development at the national level in which the regional electric grids are developed and operated as one integrated system. It also examines the effects of selected CO₂ emission reduction targets in the power sector and the role of renewable power generation technologies in India. The study shows that the integrated development and operation of the power system at the national level would reduce the total cost including fuel cost by 4912 million $, total capacity addition by 2784 MW, while the emission of CO₂, SO₂ and NO_x would be reduced by 231.6 (1.9%), 0.8 (0.9%), 0.4 (1.2%) million tons, respectively, during the planning horizon. Furthermore, the study shows that the expected unserved energy, one of the indices of generation system reliability, would decrease to 26 GWh under integrated national power system from 5158 GWh. As different levels of CO₂ emission reduction targets were imposed, there is a switching of generation from conventional coal plants to gas fired plants, clean coal technologies and nuclear based plants. As a result the capacity expansion cost has increased. It was found that wind power plant is most attractive and economical in the Indian perspective among the renewable options considered (Solar, wind and biomass). Copyright © 2003 John Wiley & Sons, Ltd.     

An order-specific clustering algorithm for the determination of representative demand curves

Data clustering consists of a group of procedures used to collect similar entries or data points within a set into clusters. No existing clustering technique considers entries sequentially in time. In some cases, it is desirable to generate clusters that represent a segment of a time-ordered data set. For these purposes, an order-specific clustering algorithm is proposed. The proposed algorithm employs representative load curves to describe the clusters it generates. The capabilities of the order-specific clustering algorithm are demonstrated on a case study using electricity demand data for the province of Ontario, Canada. Two different applications of the clustering algorithm on this data set are given to demonstrate the effect of error threshold values on the formation of clusters. An analysis of the error for each of these clustering applications is presented.     

Life cycle of hydroprocessing catalysts and total catalyst management

Hydroprocessing catalysts based on Ni, Co, Mo and W are used in various refinery processing applications where several deactivation mechanisms become of importance (coke formation, active phase sintering, metals deposition, poisoning) in the catalyst's life cycle. The life cycle of commercial hydroprocessing catalysts is very complex and includes the catalyst production, sulfidation, use, oxidative regeneration followed by re-sulfidation and reuse or, if reuse is not possible, recycling or disposal. To understand the changes in catalyst properties taking place during a life cycle, the catalyst quality in the different stages can be best monitored by using advanced analytical techniques. The catalyst's life cycle is further complicated by numerous technical, environmental and organizational issues involved. In principle, different companies can be involved in each of the life cycle steps. Leading catalyst manufacturers, together with specialized firms, offer refineries a total catalyst management concept, starting with the purchase of the fresh catalyst and ending with its final recycling or disposal. Total catalyst management includes a broad range of services, ensuring optimal timing during the change-out process, reliable, smooth and safe operations, minimal downtime and maximum catalyst and unit performance.     

Influence of a lipid phase on steam jet agglomeration of maltodextrin powders

The contribution of an oil phase to the agglomeration mechanisms of food powders was evaluated. Maltodextrin (DE 10), palm oil stearin and two palm oil oleins (up to 25% dry mass) were used as food models. Granulation runs were carried out in a pilot plant steam jet agglomerator. The powders containing oleins were more cohesive than those with stearin and the presence of oil changed the agglomeration mechanisms. The size increase mechanism of pure maltodextrin powder was controlled by surface plasticization and agglomerates with suitable instant properties were obtained. Small amount of oil degenerated drastically the rate of dispersion in water of the powders and their agglomerates but the average size and the mechanical resistance of the agglomerates increased when the oil content of the powders increased. SEM micrographs of agglomerates indicated that higher lipid content in the powders produced compact granules, favoring sinkability but hindering their disintegration. Agglomeration enhanced considerably the flowability of the particles containing oil. The dispersion behavior of the powders with higher lipid content could be correlated with the Hausner Number. A pre-agglomeration step favored the blend of the more cohesive powders producing larger and more resistant agglomerates.