Dynamic analysis of Flip-Chip Self-Alignment

Self-alignment of soldered electronic components such as flip-chips (FC), ball grid arrays (BGA) and optoelectronic devices during solder reflow is important as it ensures good alignment between components and substrates. Two uncoupled analytical models are presented which provide estimates of the dynamic time scales of both the chip and the solder in the self-alignment process. These predicted time scales can be used to decide whether a coupled dynamic analysis is required for the analysis of the chip motion. In this paper, we will show that for flip-chips, the alignment dynamics can be described accurately only when the chip motion is coupled with the solder motion because the two have similar time-scale values. To study this coupled phenomenon, a dynamic modeling method has been developed. The modeling results show that the uncoupled and coupled calculations result in significantly different predictions. The calculations based on the coupled model predict much faster rates of alignment than those predicted using the uncoupled approach.

Emergent self-organisation of wireless sensor networks

This paper describes a protocol for dynamically configuring wireless sensor nodes into logical clusters. The concept is to be able to inject an overlay configuration into an ad-hoc network of sensor nodes or similar devices, and have the network configure itself organically. The devices are arbitrarily deployed and have initially have no information whatsoever concerning physical location, topology, density or neighbourhood. The Emergent Cluster Overlay (ECO) protocol is totally self-configuring and has several novel features, including nodes self-determining their mobility based on patterns of neighbour discovery, and that the target cluster size is specified externally (by the sensor network application) and is not directly coupled to radio communication range or node packing density. Cluster head nodes are automatically assigned as part of the cluster configuration process, at no additional cost. ECO is ideally suited to applications of wireless sensor networks in which localized groups of sensors act cooperatively to provide a service. This includes situations where service dilution is used (dynamically identifying redundant nodes to conserve their resources).

In vitro-in vivo correlations of self-emulsifying drug delivery systems combining the dynamic lipolysis model and neuro-fuzzy networks

The aim of the current study was to evaluate the potential of the dynamic lipolysis model to simulate the absorption of a poorly soluble model drug compound, probucol, from three lipid-based formulations and to predict the in vitro-in vivo correlation (IVIVC) using neuro-fuzzy networks. An oil solution and two self-micro and nano-emulsifying drug delivery systems were tested in the lipolysis model. The release of probucol to the aqueous (micellar) phase was monitored during the progress of lipolysis. These release profiles compared with plasma profiles obtained in a previous bioavailability study conducted in mini-pigs at the same conditions. The release rate and extent of release from the oil formulation were found to be significantly lower than from SMEDDS and SNEDDS. The rank order of probucol released (SMEDDS approximately SNEDDS > oil formulation) was similar to the rank order of bioavailability from the in vivo study. The employed neuro-fuzzy model (AFM-IVIVC) achieved significantly high prediction ability for different data formations (correlation greater than 0.91 and prediction error close to zero), without employing complex configurations. These preliminary results suggest that the dynamic lipolysis model combined with the AFM-IVIVC can be a useful tool in the prediction of the in vivo behavior of lipid-based formulations.

To fit in or stand out? The interaction between mortality salience, dissent and self esteem on social projection

Social projection (SP) refers to our tendency to assume that others think the same as we do, but the effect can also be used to detect the extent to which participants want to see themselves as similar to others. Simon et al (1997) found that participants informed that they were deviant increased their SP but those told that they were conformist reduced theirs. This compensatory function supports Brewer’s optimal distinctiveness which states that a balance must be struck between competing desires to feel similar and unique. In line with terror management theory, the effect was particularly apparent under conditions of mortality salience (MS). So far SP has only been examined on measures that target personal identity so this experiment developed a measure to target social identity as well. Participants were provided with either minority or majority dissent feedback, in MS or control conditions, and their SP on items relevant to personal and social identity were recorded. Results showed that group feedback only impacted upon participants SP on social identity measures and interacted with MS and self-esteem; those with high self-esteem had higher SP scores following minority dissent under conditions of mortality salience, indicating an attempt to assert their individuality. On SP measures targeting personal identity, MS and self-esteem interacted; the death prime increased SP scores for those with low self-esteem but decreased it for those with high self-esteem. Findings are interpreted in terms of TMT and optimal distinctiveness theory and their applications.