Data and process requirements for product recall coordination

When an organisation becomes aware that one of its products may pose a safety risk to customers, it must take appropriate action as soon as possible or it can be held liable. The ability to automatically trace potentially dangerous goods through the supply chain would thus help organisations fulfill their legal obligations in a timely and effective manner. Furthermore, product recall legislation requires manufacturers to separately notify various government agencies, the health department and the public about recall incidents. This duplication of effort and paperwork can introduce errors and data inconsistencies. In this paper, we examine traceability and notification requirements in the product recall domain from two perspectives: the activities carried out during the manufacturing and recall processes and the data collected during the enactment of these processes. We then propose a workflow-based coordination framework to support these data and process requirements.

Minimising wave drag for free surface flow past a two-dimensional stern

Free surface flow past a two-dimensional semi-infinite curved plate is considered, with emphasis given to solving for the shape of the resulting wave train that appears downstream on the surface of the fluid. This flow configuration can be interpreted as applying near the stern of a wide blunt ship. For steady flow in a fluid of finite depth, we apply the Wiener-Hopf technique to solve a linearised problem, valid for small perturbations of the uniform stream. Weakly nonlinear results found using a forced KdV equation are also presented, as are numerical solutions to the fully nonlinear problem, computed using a conformal mapping and a boundary integral technique. By considering different families of shapes for the semi-infinite plate, it is shown how the amplitude of the waves can be minimised. For plates that increase in height as a function of the direction of flow, reach a local maximum, and then point slightly downwards at the point at which the free surface detaches, it appears the downstream wavetrain can be eliminated entirely.

Value-adding to cellulosic ethanol: Lignin polymers

Lignocellulosic waste materials are the most promising feedstock for generation of a renewable, carbon-neutral substitute for existing liquid fuels. The development of value-added products from lignin will greatly improve the economics of producing liquid fuels from biomass. This review gives an outline of lignin chemistry, describes the current processes of lignocellulosic biomass fractionation and the lignin products obtained through these processes, then outlines current and potential value-added applications of these products, in particular as components of polymer composites. Research highlights The use of lignocellulosic biomass to produce platform chemicals and industrial products enhances the sustainability of natural resources and improves environmental quality by reducing greenhouse and toxic emissions. In addition, the development of lignin based products improves the economics producing liquid transportation fuel from lignocellulosic feedstock. Value adding can be achieved by converting lignin to functionally equivalent products that rely in its intrinsic properties. This review outlines lignin chemistry and some potential high value products that can be made from lignin. Keywords: Lignocellulose materials; Lignin chemistry; Application

Poly[di-mu-aqua-bis(mu-2-amino-4-nitrobenzoato)dicaesium]

In the structure of title compound [Cs2(C7H5N2O4)2(H2O)2]n the asymmetric unit comprises two independent and different Cs centres, one nine-coordinate, the other seven coordinate, with both having irregular stereochemistry. The CsO9 coordination comprises oxygen donors from three bridging water molecules, one of which is doubly bridging, three from carboxylate groups, and three from nitro groups, of which two are bidentate chelate bridging. The CsO6N coordination comprises the two bridging water molecules, one amine N donor, one carboxyl O donor and four O donors from nitro groups (two from the chelate bridges). The extension of the dimeric unit gives a two-dimensional polymeric structure which is stabilized by both intra- and intermolecular amine N-H...O and water O-H...O hydrogen bonds to carboxyl O acceptors, as well as inter-ring pi-pi interactions [minimum ring centroid separation, 3.4172(15)A].

Functional heterogeneity as a two-dimensional concept : empirical evidence for new venture teams

Previous research on entrepreneurial teams has failed to settle the controversy over whether team heterogeneity helps or hinders new venture performance. Reconciling this inconsistency, this paper suggests a new conceptual approach to disentangle differential effects of team heterogeneity by modeling two separate heterogeneity dimensions, namely knowledge scope and knowledge disparity. Analyzing unique data on functional experiences of the members of 337 start-up teams, we find support for our contention of team heterogeneity as a two-dimensional concept. Results suggest that knowledge disparity negatively relates to both start-ups’ entrepreneurial and innovative performance. In contrast, we find knowledge scope to positively affect entrepreneurial performance, while it shows an inverse U-shaped relationship to innovative start-up performance.

Evaluation of texture and geometry for dimensional facial expression recognition

Facial expression recognition (FER) algorithms mainly focus on classification into a small discrete set of emotions or representation of emotions using facial action units (AUs). Dimensional representation of emotions as continuous values in an arousal-valence space is relatively less investigated. It is not fully known whether fusion of geometric and texture features will result in better dimensional representation of spontaneous emotions. Moreover, the performance of many previously proposed approaches to dimensional representation has not been evaluated thoroughly on publicly available databases. To address these limitations, this paper presents an evaluation framework for dimensional representation of spontaneous facial expressions using texture and geometric features. SIFT, Gabor and LBP features are extracted around facial fiducial points and fused with FAP distance features. The CFS algorithm is adopted for discriminative texture feature selection. Experimental results evaluated on the publicly accessible NVIE database demonstrate that fusion of texture and geometry does not lead to a much better performance than using texture alone, but does result in a significant performance improvement over geometry alone. LBP features perform the best when fused with geometric features. Distributions of arousal and valence for different emotions obtained via the feature extraction process are compared with those obtained from subjective ground truth values assigned by viewers. Predicted valence is found to have a more similar distribution to ground truth than arousal in terms of covariance or Bhattacharya distance, but it shows a greater distance between the means.