Online monitoring of the curing of adhesives with a miniaturised interdigital sensor using impedance spectroscopy

Monitoring adhesives during manufacturing and their lifetime has become increasingly important due to the variety of materials and applications. Impedance spectroscopy is a suitable method for online monitoring of the curing process. We present a miniaturised interdigital structure to monitor the curing process of the adhesives using impedance spectroscopy. Compared to other sensors, our sensor is ultrathin, so that it disappears in the adhesive joint. Therefore, it can remain in the joint and be used for lifetime monitoring. In addition it is suitable for thin adhesive layers due to its fine grid. We demonstrate that the impedance of the sensor embedded in the adhesive gives insight into the curing mechanisms. Therefore monitoring of a dispersion and an epoxy is shown. In addition, the curing cycles can be reliably controlled using this monitoring method. The permittivity of the adhesives is extracted from the impedance measurements, applying analytical models of the electrical field of the interdigital structure.     

Calculating adjusted R(2) measures for Poisson regression models

In regression models not only the parameter estimates and significances of explanatory variables are of interest, but also the degree to which variation in the dependent variable can be explained by covariates. In recent publications, an R(2) measure based on deviance was recommended for Poisson regression models, one of the most frequently used modelling tools in epidemiological studies. However, when sample size is small relative to the number of covariates in the model, simple R(2) measures may be seriously inflated and may need to be adjusted according to the number of covariates in the model. We present a SAS-macro that calculates adjustments for the R(2) measures in Poisson regression models based on log-likelihood and on sums of squares. The proposed measures are applied to real data sets and their performance is discussed.     

Model-sensitive sequential optimal designs

The increasing number of experimenters using computer-generated experimental designs creates an increasing need to have design procedures that are less sensitive to model misspecification. To address this problem, the notion of empirical models that have both important and potential terms is used. A two-stage design strategy for planning experiments in the face of model uncertainty is proposed. The advantage of this procedure resides in the rearrangement of active potential terms at the end of the first stage using marginal posterior probabilities of different candidate models. The two-stage procedure has better estimation efficiency than its one-stage alternatives available from the literature.     

In situ synthesised TiO2 ‐chitosan‐chondroitin 4–sulphate nanocomposites for bone implant applications

The artificial materials for bone implant applications are gaining more importance in the recent years. The series titania‐chitosan‐chondroitin 4–sulphate nanocomposites of three different concentrations (2:1:x, where x ‐ 0.125, 0.25, 0.5) have been synthesised by in situ sol–gel method and characterised by various techniques. The particle size of the nanocomposites ranges from 30–50 nm. The bioactivity, swelling nature, and the antimicrobial nature of the nanocomposites were investigated. The swelling ability and bioactivity of the composites is significantly greater and they possess high zone of inhibition against the microorganisms such as Staphylococcus aureus and Escherichia coli. The cell viability of the nanocomposites were evaluated by using MG‐63 and observed the composites possess high cell viability at low concentration. The excellent bioactivity and biocompatibility makes these nanocomposites a promising biomaterial for bone implant applications.Inspec keywords: titanium compounds, filled polymers, nanocomposites, bone, orthopaedics, biomedical materials, sol‐gel processing, nanofabrication, particle size, swelling, microorganisms, cellular biophysics, nanomedicine, prostheticsOther keywords: in situ synthesised TiO₂ ‐chitosan‐chondroitin 4‐sulphate nanocomposites, bone implant applications, artificial materials, in situ sol‐gel method, particle size, swelling nature, antimicrobial nature, microorganisms, Staphylococcus aureus, Escherichia coli, cell viability, MG‐63, biomaterial, size 30 nm to 50 nm, TiO₂      

Detection of temporary flooded areas with potential floodwater mosquito production using imaging radar

Temporarily flooded areas can produce enormous numbers of floodwater mosquitoes, causing tremendous nuisance to people living in the vicinity. The aim of this study is to develop a remote-sensing method for detecting temporary flooded areas that can produce floodwater mosquitoes. For this objective, synthetic aperture radar (SAR) imagery from the European Remote Sensing satellite (ERS-2) and the Environmental Satellite (Envisat) are chosen. The images cover both flooded and dry periods around Lake Färnebofjärden, located in the lowlands of the River Dalälven, central Sweden, during the vegetation season between 2000 and 2006. Unsupervised classification and principal component analysis (PCA) are tested as methods for detecting floodwater mosquito production sites. In the unsupervised classification experiment, four types of images are tested. The classification of a synthetic colour image gives the best result with an overall accuracy of 85.7% and a kappa value of 0.7, as well as a 46% detection rate of field-mapped flooded areas. PCA is performed on a data set of 16 time series radar images. The resulting principal component (PC) bands provide information about flooding probability as well as vegetation structures. Regular flooding increases the probability for an area to provide breeding sites for floodwater mosquitoes. Thus, this approach will be very useful in estimating the risk of floodwater mosquito establishment.     

Extensible Prototyping for pragmatic engineering of knowledge-based systems

Knowledge-based systems (KBSs) have been built and practically applied in various contexts for decades. Yet, they still challenge developers by their complexity: Apart from a sound knowledge base they likewise require comprehensive user interface (UI) and interaction design for supporting the task at hand optimally. However, current KBS-Engineering methodologies still mostly focus on knowledge base development, regarding UI/interaction design a more incidental, low priority task. Thus, the UI often is developed in a rather ad hoc manner, thereby neglecting the potential of experimental design and creating reusable solutions. The integration of (rapid) evolutionary prototyping activities with KBS Engineering offers the chance for incorporating UI/interaction design more prominently into the process while at the same time leveraging the overall development task; specifically, we propose Extensible Prototyping as a tailored prototyping approach and we suggest its integration with the Agile Process Model for knowledge-based systems in this paper. For practical support, we further introduce the customized prototyping and knowledge systems engineering tool ProKEt, and we report on practical experiences with applying both the approach and the tool.     

Summoning earth and fire: The energy development implications of Grameen Shakti (GS) in Bangladesh

Since its establishment in 1996, the nonprofit company Grameen Shakti (GS) has installed almost half a million solar home systems (SHS), 132,000 cookstoves, and 13,300 biogas plants among 3.1 million beneficiaries. They plan to ramp up their expansion so that by 2015, more than 1.5 million SHS are in place along with 100,000 biogas units and 5 million improved cookstoves. This article describes GS’s current activities, the contours of its programs, and likely reasons for its success. It also explores the remaining challenges facing GS and distils common lessons for other energy development assistance projects and programs around the world. After detailing research methods consisting primarily of research interviews and site visits, the article briefly explores the history of GS and summarizes its three most prominent programs. The article then identifies six distinct benefits to their programs—expansion of energy access, less deforestation and fewer greenhouse gas emissions, price savings, direct employment and income generation, improved public health, and better technology—before discussing challenges related to staff retention and organizational growth, living standards, technical obstacles, affordability, tension with other energy programs, political constraints, and awareness and cultural values.