Electrical and Mechanical Behavior of Aerosol Jet–Printed Gold on Alumina Substrate for High-Temperature Applications

There is a growing interest in the development of microelectronics that can perform reliably and robustly at temperatures above 300 °C. Such devices require stable thermal properties, low thermal drift, and thermal cycling resistance. Conventional hybrid circuit technology demonstrates high-temperature packages, but the high costs and lead time are significant drawbacks. In contrast, additive manufacturing processes, including aerosol jet printing (AJP), offer cost and time benefits, as well as 3D structures and embedded features. However, the properties and reliability of additive packaging materials at extreme temperatures are not well known. Herein, the reliability at temperatures up to 750 °C in terms of electrical performance and mechanical strength of aerosol jet printed gold thick films onto ceramic substrates are assessed. Thermal coefficient of resistance of printed gold films is measured. The electrical resistance stability and leakage current of printed gold structures are also characterized during over 100 h of aging at temperatures up to 750 °C. Finally, the mechanical adhesion strength of the printed gold films is evaluated after aging for 100 h at temperatures up to 750 °C. The adhesion of the printed gold to the ceramic substrates remains high after aging, very stable resistances and minimal leakage currents have been observed.     

An Artificial Neural Network Classifier Design Based-on Variable Kernel and Non-Parametric Density Estimation

This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule) model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems. The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification problem.     

Approximate inference in Boltzmann machines

Inference in Boltzmann machines is NP-hard in general. As a result approximations are often necessary. We discuss first order mean field and second order Onsager truncations of the Plefka expansion of the Gibbs free energy. The Bethe free energy is introduced and rewritten as a Gibbs free energy. From there a convergent belief optimization algorithm is derived to minimize the Bethe free energy. An analytic expression for the linear response estimate of the covariances is found which is exact on Boltzmann trees. Finally, a number of theorems is proven concerning the Plefka expansion, relating the first order mean field and the second order Onsager approximation to the Bethe approximation. Experiments compare mean field approximation, Onsager approximation, belief propagation and belief optimization.     

Linear response algorithms for approximate inference in graphical models

Belief propagation (BP) on cyclic graphs is an efficient algorithm for computing approximate marginal probability distributions over single nodes and neighboring nodes in the graph. However, it does not prescribe a way to compute joint distributions over pairs of distant nodes in the graph. In this article, we propose two new algorithms for approximating these pairwise probabilities, based on the linear response theorem. The first is a propagation algorithm that is shown to converge if BP converges to a stable fixed point. The second algorithm is based on matrix inversion. Applying these ideas to gaussian random fields, we derive a propagation algorithm for computing the inverse of a matrix.     

Impact of N-Terminal Tags on De Novo Vimentin Intermediate Filament Assembly

Vimentin, a type III intermediate filament protein, is found in most cells along with microfilaments and microtubules. It has been shown that the head domain folds back to associate with the rod domain and this association is essential for filament assembly. The N-terminally tagged vimentin has been widely used to label the cytoskeleton in live cell imaging. Although there is previous evidence that EGFP tagged vimentin fails to form filaments but is able to integrate into a pre-existing network, no study has systematically investigated or established a molecular basis for this observation. To determine whether a tag would affect de novo filament assembly, we used vimentin fused at the N-terminus with two different sized tags, AcGFP (239 residues, 27 kDa) and 3 × FLAG (22 residues; 2.4 kDa) to assemble into filaments in two vimentin-deficient epithelial cells, MCF-7 and A431. We showed that regardless of tag size, N-terminally tagged vimentin aggregated into globules with a significant proportion co-aligning with β-catenin at cell–cell junctions. However, the tagged vimentin aggregates could form filaments upon adding untagged vimentin at a ratio of 1:1 or when introduced into cells containing pre-existing filaments. The resultant filament network containing a mixture of tagged and untagged vimentin was less stable compared to that formed by only untagged vimentin. The data suggest that placing a tag at the N-terminus may create steric hinderance in case of a large tag (AcGFP) or electrostatic repulsion in case of highly charged tag (3 × FLAG) perhaps inducing a conformational change, which deleteriously affects the association between head and rod domains. Taken together our results shows that a free N-terminus is essential for filament assembly as N-terminally tagged vimentin is not only incapable of forming filaments, but it also destabilises when integrated into a pre-existing network.     

Wireless link prediction and triggering using modified Ornstein–Uhlenbeck jump diffusion process

Through time domain observation, typical wireless signal strength values seems to exhibit some forms of mean-reverting and discontinuous “jumps” behaviour. Motivated by this fact, we propose a wireless link prediction and triggering (LPT) technique using a modified mean-reverting Ornstein–Uhlenbeck (OU) jump diffusion process. The proposed technique which we refer as OU-LPT is an integral component of wireless mesh network monitoring system developed by ICT FP7 CARrier grade wireless MEsh Network project. In particular, we demonstrate how this technique can be applied in the context of wireless mesh networks to support link switching or handover in the event of predicted link degradation or failure. The proposed technique has also been implemented and evaluated in a real-time experimental testbed. The results show that OU-LPT technique can significantly enhance the reliability of wireless links by reducing the rate of false triggers compared to a conventional linear prediction technique and therefore offers a new direction on how wireless link prediction, triggering and switching process can be conducted in the future.     

Amelioration in physicochemical properties and single cell performance of sulfonated poly(ether ether ketone) block copolymer composite membrane using sulfonated carbon nanotubes for intermediate humidity fuel cells

A composite membrane composed of a sulfonated diblock copolymer (SDBC) based on poly(ether ether ketone) blocks copolymerized with partially fluorinated poly(arylene ether sulfone) and sulfonated carbon nanotubes (SCNTs) was fabricated by simple solution casting. Addition of the SCNT filler enhanced the water absorption and proton conductivity of membranes because of the increased per‐cluster volume of sulfonic acid groups, at the same time reinforced the membranes' thermal and mechanical properties. The SDBC/SCNT‐1.5 membrane exhibited the most improved physicochemical properties among all materials. It obtained a proton conductivity of 10.1 mS/cm at 120°C under 20% relative humidity (RH) which was 2.6 times more improved than the pristine membrane (3.9 mS/cm). Moreover, the single cell performance of the SDBC/SCNT‐1.5 membrane at 60°C and 60% RH at ambient pressure exhibited a peak power density of 171 mW/cm² at a load current density of 378 mA/cm², while the pristine membrane exhibited 119 mW/cm² at a load current density of 294 mA/cm². Overall, the composite membrane exhibited very promising characteristics to be used as polymer electrolyte membrane in fuel cells operated at intermediate RH.     

Does power posing affect gerontechnology adoption among older adults?

Recognising the rise of an aging population and independent living among older adults, many governments and organisations have developed and promoted new technologies in the form of gerontechnologies to support the needs and enhance the well-being of older adults. However, the adoption of products using such technology remains modest among the aging population. This study introduces the notion of power in the form of power posing and examines its impact on new technology adoption, particularly gerontechnology, among older adults. Using an experimental approach on a sample of older adults exposed to an in-house near-field communication-enabled light system, the study finds that high-power poses have a greater and more positive impact on older adults’ perceived ease of use of, perceived usefulness of, and intentions to use gerontechnology than low-power poses. Implications, limitations, and future research directions are discussed.     

Design characteristics of a workload manager to aid drivers in safety–critical situations

Cognition, Technology & Work - The objective of this study was to evaluate a workload manager designed to supervise the presentation of in-vehicle information for two age groups of drivers...