Master batch approach for developing PVDF/EVA/CNT nanocomposites with co-continuous morphology and improved electrical conductivity

Conducting polymer composites constituted by co-continuous poly (vinylidene fluoride) (PVDF)/ ethylene- vinyl acetate copolymer (EVA) blends with multiwalled carbon nanotube (CNT) were prepared by melt mixing using different procedures. The effect of the master batch approach on the conductivity, morphology, mechanical, thermal and rheological properties of PVDF/EVA/CNT nanocomposites was compared with that based on one step mixing strategy. The selective extraction experiments revealed that CNT was preferentially localized in the EVA phase in all situations, even when PVDF@CNT master batch was employed. Nanocomposites prepared with EVA@CNT master batch displayed higher conductivity, whose value reached around 10⁻¹ S m⁻¹ with the addition of 0.56 vol% of CNT. The better electrical performance was attributed to the better distribution of the filler, as indicated by transmission electron microscopy and rheological behavior. The electrical and rheological behavior were also investigated as a function of the CNT content.     

The teacher's responsibility in whole‐class debriefing of mathematical activity

Abstract

Prompted by recent moves in the United Kingdom to guide teachers’ practices in whole‐class, direct interactive teaching, in this article, we offer an opportunity for North American mathematics educators to reflect on possibilities for whole‐class teaching of mathematics. We focus particularly on the plenary aspect of lessons—what might be considered the debriefing of mathematical activity—and specifically on the teacher's responsibility during those sessions, both to his or her students and to the authenticity of the discipline of mathematics. Drawing on data from a Grade‐3 classroom and invoking complexity science as a theoretical lens to explore the classroom as a complex learning system, we present implications for teaching in whole‐class debriefings of mathematical activity.     

Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data

In this study we implemented a comprehensive analysis to validate the MODIS and GOES satellite active fire detection products (MOD14 and WFABBA, respectively) and characterize their major sources of omission and commission errors which have important implications for a large community of fire data users. Our analyses were primarily based on the use of 30 m resolution ASTER and ETM+ imagery as our validation data. We found that at the 50% true positive detection probability mark, WFABBA requires four times more active fire area than is necessary for MOD14 to achieve the same probability of detection, despite the 16× factor separating the nominal spatial resolutions of the two products. Approximately 75% and 95% of all fires sampled were omitted by the MOD14 and WFABBA instantaneous products, respectively; whereas an omission error of 38% was obtained for WFABBA when considering the 30-minute interval of the GOES data. Commission errors for MOD14 and WFABBA were found to be similar and highly dependent on the vegetation conditions of the areas imaged, with the larger commission errors (approximately 35%) estimated over regions of active deforestation. Nonetheless, the vast majority (> 80%) of the commission errors were indeed associated with recent burning activity where scars could be visually confirmed in the higher resolution data. Differences in thermal dynamics of vegetated and non-vegetated areas were found to produce a reduction of approximately 50% in the commission errors estimated towards the hours of maximum fire activity (i.e., early-afternoon hours) which coincided with the MODIS/Aqua overpass. Lastly, we demonstrate the potential use of temporal metrics applied to the mid-infrared bands of MODIS and GOES data to reduce the commission errors found with the validation analyses.     

Batch process modelling with mixtures of Gaussian processes

In recent years Gaussian processes have attracted a significant amount of interest with the particular focus being that of process modelling. This has primarily been a consequence of their good predictive performance and inherent analytical properties. Gaussian processes are a member of the family of non-parametric Bayesian regression models and can be derived from the perspective of neural networks. Their behaviour is controlled through the structure of the covariance function. However, when applied to batch processes, whose data exhibits different variance structures throughout the duration of the batch, a single Gaussian process may not be appropriate for the accurate modelling of its behaviour. Furthermore there are issues with respect to the computational costs of Gaussian processes. The implementation of a Gaussian process model requires the repeated computation of a matrix inverse whose order is the cubic of the number of training data points. This renders the algorithm impractical when dealing with large data sets. To address these two issues, a mixture model of Gaussian processes is proposed. The resulting prediction is attained as a weighted sum of the outputs from each Gaussian process component, with the weights determined by a Gaussian kernel gating network. The model is implemented through a Bayesian approach utilising Markov chain Monte Carlo algorithms. The proposed methodology is applied to data from a bench-mark batch simulation polymerization process, methyl methacrylate (MMA), and the results are compared with those from a single Gaussian process to illustrate the advantages of the proposed mixture model approach.     

Schema mapping and query translation in heterogeneous P2P XML databases

Peers in a peer-to-peer data management system often have heterogeneous schemas and no mediated global schema. To translate queries across peers, we assume each peer provides correspondences between its schema and a small number of other peer schemas. We focus on query reformulation in the presence of heterogeneous XML schemas, including data–metadata conflicts. We develop an algorithm for inferring precise mapping rules from informal schema correspondences. We define the semantics of query answering in this setting and develop query translation algorithm. Our translation handles an expressive fragment of XQuery and works both along and against the direction of mapping rules. We describe the HePToX heterogeneous P2P XML data management system which incorporates our results. We report the results of extensive experiments on HePToX on both synthetic and real datasets. We demonstrate our system utility and scalability on different P2P distributions.     

Achieving Diagnosis by Consensus

This paper provides an analysis of the collaborative work conducted at a multidisciplinary medical team meeting, where a patient’s definitive diagnosis is agreed, by consensus. The features that distinguish this process of diagnostic work by consensus are examined in depth. The current use of technology to support this collaborative activity is described, and experienced deficiencies are identified. Emphasis is placed on the visual and perceptual difficulty for individual specialities in making interpretations, and on how, through collaboration in discussion, definitive diagnosis is actually achieved. The challenge for providing adequate support for the multidisciplinary team at their meeting is outlined, given the multifaceted nature of the setting, i.e. patient management, educational, organizational and social functions, that need to be satisfied.

Understanding online customer repurchasing intention and the mediating role of trust – an empirical investigation in two developed countries

Although e-commerce adoption and customers’ initial purchasing behavior have been well studied in the literature, repeat purchase intention and its antecedents remain understudied. This study proposes a model to understand the extent to which trust mediates the effects of vendor-specific factors on customers’ intention to repurchase from an online vendor. The model was tested and validated in two different country settings. We found that trust fully mediates the relationships between perceived reputation, perceived capability of order fulfillment, and repurchasing intention, and partially mediates the relationship between perceived website quality and repurchasing intention in both countries. Moreover, multi-group analysis reveals no significant between-country differences of the model with regards to the antecedents and outcomes of trust, except the effect of reputation on trust. Academic and practical implications and future research are discussed.     

Automated High Throughput Screening of Fluorescent Imaging Plate Reader (FLIPR) Assays Using Assay Platform™ Integrated with Activity Base for ‘on the fly’ Compound Reconfirmation

Advances in the field of automation have meant hitherto complex manual cell-based assays can now be automated. These improvements have brought significant enhancements in throughput, data fidelity and consistency, and allowed a reallocation of constrained resources.Building upon these improvements, we have linked our automated cell-based screening system, Assay Platform™, to Activity Base (IDBS), a software package designed to automate the analysis of HTS data. Customisation of this package has resulted in software that can identify ‘active’ compounds and re-pick them ‘on the fly’ from the original compound plates for triplicate re-testing without operator intervention.Based on an operator initially defining ‘normal’ parameters for assay activity in Activity Base, combined with an automated quality control software module that checks data fidelity, wells containing ‘active’ compounds can be re-picked and re-tested at the end of an automated screening run. Automating cell-based assays has significantly improved productivity, and, with the synergism of Activity Base, has given us greater power to complete each screening run and report ‘active’ compounds to Chemistry more rapidly. This article presents our approach to the automation of cell-based Fluorescent Imaging Plate Reader (FLIPR) screening together with automated active re-test confirmation using Activity Base.