Network analysis of 2-mode data

Network analysis is distinguished from traditional social science by the dyadic nature of the standard data set. Whereas in traditional social science we study monadic attributes of individuals, in network analysis we study dyadic attributes of pairs of individuals. These dyadic attributes (e.g. social relations) may be represented in matrix form by a square 1-mode matrix. In contrast, the data in traditional social science are represented as 2-mode matrices. However, network analysis is not completely divorced from traditional social science, and often has occasion to collect and analyze 2-mode matrices. Furthermore, some of the methods developed in network analysis have uses in analysing non-network data. This paper presents and discusses ways of applying and interpreting traditional network analytic techniques to 2-mode data, as well as developing new techniques. Three areas are covered in detail: displaying 2-mode data as networks, detecting clusters and measuring centrality.

A robust tri-state election algorithm for scalable applications

Existing election algorithms suffer limited scalability. This limit stems from the communication design which in turn stems from their fundamentally two-state behaviour. This paper presents a new election algorithm specifically designed to be highly scalable in broadcast networks whilst allowing any processing node to become coordinator with initially equal probability. To achieve this, careful attention has been paid to the communication design, and an additional state has been introduced. The design of the tri-state election algorithm has been motivated by the requirements analysis of a major research project to deliver robust scalable distributed applications, including load sharing, in hostile computing environments in which it is common for processing nodes to be rebooted frequently without notice. The new election algorithm is based in-part on a simple 'emergent' design. The science of emergence is of great relevance to developers of distributed applications because it describes how higher-level self-regulatory behaviour can arise from many participants following a small set of simple rules. The tri-state election algorithm is shown to have very low communication complexity in which the number of messages generated remains loosely-bounded regardless of scale for large systems; is highly scalable because nodes in the idle state do not transmit any messages; and because of its self-organising characteristics, is very stable.

Simultaneous monitoring of drug and solvent diffusion across a model membrane using ATR-FTIR spectroscopy

Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been used to simultaneously follow the diffusion of model drugs and solvent across polydimethylsiloxane (silicone) membrane. Three model drugs, cyanophenol (CNP), methyl nicotinate (MN) and butyl paraben (BP) were selected to cover a range of lipophilicities. Isostearyl isostearate (ISIS) was chosen as the solvent because its large molecular weight should facilitate observation of whether the drug molecules are able to diffuse through the membrane independently of the solvent. The diffusion of the three drugs and the solvent was successfully described by a Fickian model. The effects of parameters such as the absorption wavelength used to follow diffusion on the calculated diffusion coefficient were investigated. Absorption wavelength which affects the depth of penetration of the infrared radiation into the membrane did not significantly affect the calculated diffusion coefficient over the wavelength range tested. Each of the model drugs was observed to diffuse independently of the solvent across the membrane. The diffusion of a CNP-ISIS hydrogen bonded complex across the membrane was also monitored. The relative diffusion rates of the solute and solvent across the membrane can largely be accounted for by the molecular size of the permeant.

In vitro drug release studies of polymeric freeze-dried wafers and solvent-cast films using paracetamol as a model soluble drug

Drug dissolution and release characteristics from freeze-dried wafers and solvent-cast films prepared from sodium carboxymethylcellulose (CMC) have been investigated to determine the mechanisms of drug release from the two systems. The formulations were prepared by freeze-drying (wafers) or drying in air (films), the hydrated gel of the polymer containing paracetamol as a model soluble drug. Scanning electron microscopy (SEM) was used to examine differences between the physical structure of the wafers and films. Dissolution studies were performed using an exchange cell and drug release was measured by UV spectroscopy at 242 nm. The effects of drug loading, polymer content and amount of glycerol (films) on the release characteristics of paracetamol were investigated. The release profiles of paracetamol from the wafers and films were also compared. A digital camera was used to observe the times to complete hydration and dissolution of the wafers containing different amounts of CMC and how that impacts on drug release rates. Both formulations showed sustained type drug release that was modelled by the Korsmeyer–Peppas equation. Changes in the concentration of drug and glycerol (films) did not significantly alter the rate of drug release while increasing polymer content significantly decreased the rate of drug release from both formulations. The results show that the rate of paracetamol release was faster from the wafers than the corresponding films due to differences in their physical structures. The wafers which formed a porous network, hydrated faster than the more dense and continuous, (non-porous) sheet-like structure of the films.