Commercial phosphoric acid fuel cell system technology development

Reducing cost and increasing reliability were the technology drivers in both the electric utility and on-site integrated energy system applications. The longstanding barrier to the attainment of these goals was materials. Differences in approaches and their technological features, including electrodes, matrices, intercell cooling, bipolar/separator plates, electrolyte management, fuel selection, and system design philosophy were discussed

Advances in Microfluidics and Lab-on-a-Chip Technologies

Advances in molecular biology are enabling rapid and efficient analyses for effective intervention in domains such as biology research, infectious disease management, food safety, and biodefense. The emergence of microfluidics and nanotechnologies has enabled both new capabilities and instrument sizes practical for point-of-care. It has also introduced new functionality, enhanced sensitivity, and reduced the time and cost involved in conventional molecular diagnostic techniques. This chapter reviews the application of microfluidics for molecular diagnostics methods such as nucleic acid amplification, next-generation sequencing, high resolution melting analysis, cytogenetics, protein detection and analysis, and cell sorting. We also review microfluidic sample preparation platforms applied to molecular diagnostics and targeted to sample-in, answer-out capabilities

Improving Efficiency and Reliability of Building Systems Using Machine Learning and Automated Online Evaluation

A high percentage of newly-constructed commercial office buildings experience energy consumption that exceeds specifications and system failures after being put into use. This problem is even worse for older buildings. We present a new approach, 'predictive building energy optimization', which uses machine learning (ML) and automated online evaluation of historical and real-time building data to improve efficiency and reliability of building operations without requiring large amounts of additional capital investment. Our ML approach uses a predictive model to generate accurate energy demand forecasts and automated analyses that can guide optimization of building operations. In parallel, an automated online evaluation system monitors efficiency at multiple stages in the system workflow and provides building operators with continuous feedback. We implemented a prototype of this application in a large commercial building in Manhattan. Our predictive machine learning model applies Support Vector Regression (SVR) to the building's historical energy use and temperature and wet-bulb humidity data from the building's interior and exterior in order to model performance for each day. This predictive model closely approximates actual energy usage values, with some seasonal and occupant-specific variability, and the dependence of the data on day-of-the-week makes the model easily applicable to different types of buildings with minimal adjustment. In parallel, an automated online evaluator monitors the building's internal and external conditions, control actions and the results of those actions. Intelligent real-time data quality analysis components quickly detect anomalies and automatically transmit feedback to building management, who can then take necessary preventive or corrective actions. Our experiments show that this evaluator is responsive and effective in further ensuring reliable and energyefficient operation of building systems

Global and local (GloCal) knowledge logistics for innovation and competitiveness. ACES Working Papers, August 2010

The increasing engagement of firms within global knowledge and production networks and their ability to source knowledge globally as well as locally (GloCally), for the development of innovation capacities will shape the future of UK's knowledge resources and its role in the global economy. Practices such as off-shoring R&D activities are widely adopted, creating challenging, and not very well understood, issues related to cross-country and inter-firm knowledge and technology flows. We seek to address the internationalisation and networking of research and innovation activities, including the roles and strategies of enterprises, universities, research centres, governments in a cross-country and inter-sectoral way, to assess the impact and the implications for sustaining and enhancing the competitiveness of UK firms and other British knowledge producers and users

A Model for the Design and Development of a Science and Technology Park in Developing Countries

This paper presents an appropriate model for Science and Technology Parks (STPs) with a view to helping policy makers and STP managers implement and manage STPs. The authors reorganize and prioritize the Cabral-Dahab Science Park Management Paradigm. We identify three critical groups of actors (determinants, reactors and executors) and develop four sub-models from different trajectories of the groups of actors. We place more emphasis on the “determinants” as the most important actors in the establishment and management of STP. A critical evaluation of the sub-models reveals that the sub-model in which government, industry and university/research institutes are all jointly involved in decisive policy direction is the most appropriate for the developing country. The paper concludes that economies in transition should see STPs as having a distinctive organizational structure as a result of its myriads of collaborations and partnerships.Enterprise Development; Science and Technology Park; Model; Developing countries; Cabral-Dahab Paradigm; Determinants; Management

Biomechanics applied to computer-aided diagnosis: examples of orbital and maxillofacial surgeries

This paper introduces the methodology proposed by our group to model the biological soft tissues deformations and to couple these models with Computer-Assisted Surgical (CAS) applications. After designing CAS protocols that mainly focused on bony structures, the Computer Aided Medical Imaging group of Laboratory TIMC (CNRS, France) now tries to take into account the behaviour of soft tissues in the CAS context. For this, a methodology, originally published under the name of the Mesh-Matching method, has been proposed to elaborate patient specific models. Starting from an elaborate manually-built "generic" Finite Element (FE) model of a given anatomical structure, models adapted to the geometries of each new patient ("patient specific" FE models) are automatically generated through a non-linear elastic registration algorithm. This paper presents the general methodology of the Mesh-Matching method and illustrates this process with two clinical applications, namely the orbital and the maxillofacial computer-assisted surgeries

Building a Biorefinery Business - If it does not fit, make it fit - strategies for successful commercialization

Due to a combination of economic challenges as well as uncertain policy conditions in the United States and the European Union, the development of (advanced) biorefineries has been slower than anticipated. This has hampered the transition to a more sustainable and less carbon-intensive economy, namely the bioeconomy. In this thesis, the technological innovation system (TIS) approach is combined with the business model (BM) framework to analyze how biorefineries have addressed commercialization challenges and system weaknesses in practice. Hereby, a business-centered perspective is taken, using case study analysis and expert interviews as major means of empirical data collection. The analysis highlights a number of key strategies that have been applied: (1) cooperation, partnerships and networks play a major role for e.g. the mobilization of resources, market formation and knowledge development and diffusion; (2) a high degree of vertical integration, especially upstream, is found to overcome feedstock related challenges (3) product and market diversification into higher values is perceived as key to overcome dependence on oil prices and policy frameworks. Furthermore, prospects for lignocellulosic biorefineries are considered low due to unfavorable economics and lack of policy incentives. In addition to the empirical contribution, the study contributes with novel insights into the role of agency and individual actors as system builders within the TIS framework. The thesis thus suggests that both actor specific activities as well as policy measures are needed to overcome system weaknesses to achieve successful commercialization of biorefineries