Special report: Competing on knowledge

Traditionally, the UK has been regarded as good at innovation - with many inventions and scientific breakthroughs. So, can this nation rest easy? No. Based on extensive research by the Advanced Institute of Management Research (AIM), it would appear that the agenda for keeping Britain competitive is a demanding one. Six AIM authors report on what the UK needs to know. And do. © 2008 London Business School.

Understanding university academics' internal and external knowledge interactions in different disciplines: evidence from university in South Korea

Most of the literature on the role of universities in innovation assumes that academics¡¯ knowledge interacts only with industry and knowledge transfer occurs only or mainly in the technological and scientific fields. We question these assumptions, suggesting academics¡¯ internal and external knowledge interact across disciplines. Using national survey data, this paper tries to show the heterogeneity of university teachers¡¯ knowledge interactions across wider disciplines. Also, this paper explores the patterns of university academics¡¯ internal knowledge interactions with other academics within academia and the university academics¡¯ external knowledge interactions with industry, such as small and medium enterprises (SMEs) and major Korean firms, Chaebols. We found that there are heterogeneities of academics¡¯ knowledge interactions across the disciplines.

Intelligence in Scientific Computing

Combining numerical techniques with ideas from symbolic computation and with methods incorporating knowledge of science and mathematics leads to a new category of intelligent computational tools for scientists and engineers. These tools autonomously prepare simulation experiments from high-level specifications of physical models. For computationally intensive experiments, they automatically design special-purpose numerical engines optimized to perform the necessary computations. They actively monitor numerical and physical experiments. They interpret experimental data and formulate numerical results in qualitative terms. They enable their human users to control computational experiments in terms of high-level behavioral descriptions.

Information Fusion and Hierarchical Knowledge Discovery by ARTMAP Neural Networks

Mapping novel terrain from sparse, complex data often requires the resolution of conflicting information from sensors working at different times, locations, and scales, and from experts with different goals and situations. Information fusion methods help resolve inconsistencies in order to distinguish correct from incorrect answers, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods developed here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an objects class is car, vehicle, or man-made. Underlying relationships among objects are assumed to be unknown to the automated system of the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchial knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples.

Self-Organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System

Classifying novel terrain or objects front sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods described here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among objects are assumed to be unknown to the automated system or the human user. The ARTMAP information fusion system used distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchical knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships.

Self-Organizing Information Fusion and Hierarchical Knowledge Discovery: A New Framework Using Artmap Neural Networks

Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors woring at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when eveidence variously suggests that and object's class is car, truck, or airplane. The methods described her address a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among classes are assumed to be unknown to the autonomated system or the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierachical knowlege structures. The fusion system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples, but is not limited to image domain.

Broadening public input into science policy decision making: can the democratic model for science communication influence scientific, innovation and technological trajectories?

This PhD thesis investigates the potential use of science communication models to engage a broader swathe of actors in decision making in relation to scientific and technological innovation in order to address possible democratic deficits in science and technology policy-making. A four-pronged research approach has been employed to examine different representations of the public(s) and different modes of engagement. The first case study investigates whether patient-groups could represent an alternative needs-driven approach to biomedical and health sciences R & D. This is followed by enquiry into the potential for Science Shops to represent a bottom-up approach to promote research and development of local relevance. The barriers and opportunities for the involvement of scientific researchers in science communication are next investigated via a national survey which is comparable to a similar survey conducted in the UK. The final case study investigates to what extent opposition or support regarding nanotechnology (as an emerging technology) is reflected amongst the YouTube user community and the findings are considered in the context of how support or opposition to new or emerging technologies can be addressed using conflict resolution based approaches to manage potential conflict trajectories. The research indicates that the majority of communication exercises of relevance to science policy and planning take the form of a one-way flow of information with little or no facility for public feedback. This thesis proposes that a more bottom-up approach to research and technology would help broaden acceptability and accountability for decisions made relating to new or existing technological trajectories. This approach could be better integrated with and complementary to government, institutional, e.g. university, and research funding agencies activities and help ensure that public needs and issues are better addressed directly by the research community. Such approaches could also facilitate empowerment of societal stakeholders regarding scientific literacy and agenda-setting. One-way information relays could be adapted to facilitate feedback from representative groups e.g. Non-governmental organisations or Civil Society Organisations (such as patient groups) in order to enhance the functioning and socio-economic relevance of knowledge-based societies to the betterment of human livelihoods.

Reexamining the science of marine protected areas: Linking knowledge to action

Marine protected areas (MPAs) are often implemented to conserve or restore species, fisheries, habitats, ecosystems, and ecological functions and services; buffer against the ecological effects of climate change; and alleviate poverty in coastal communities. Scientific research provides valuable insights into the social and ecological impacts of MPAs, as well as the factors that shape these impacts, providing useful guidance or "rules of thumb" for science-based MPA policy. Both ecological and social factors foster effective MPAs, including substantial coverage of representative habitats and oceanographic conditions; diverse size and spacing; protection of habitat bottlenecks; participatory decisionmaking arrangements; bounded and contextually appropriate resource use rights; active and accountable monitoring and enforcement systems; and accessible conflict resolution mechanisms. For MPAs to realize their full potential as a tool for ocean governance, further advances in policy-relevant MPA science are required. These research frontiers include MPA impacts on nontarget and wide-ranging species and habitats; impacts beyond MPA boundaries, on ecosystem services, and on resource-dependent human populations, as well as potential scale mismatches of ecosystem service flows. Explicitly treating MPAs as "policy experiments" and employing the tools of impact evaluation holds particular promise as a way for policy-relevant science to inform and advance science-based MPA policy. © 2011 Wiley Periodicals, Inc.

Muscle Logic: New Knowledge Resource for Anatomy Enables Comprehensive Searches of the Literature on the Feeding Muscles of Mammals.

BACKGROUND: In recent years large bibliographic databases have made much of the published literature of biology available for searches. However, the capabilities of the search engines integrated into these databases for text-based bibliographic searches are limited. To enable searches that deliver the results expected by comparative anatomists, an underlying logical structure known as an ontology is required. DEVELOPMENT AND TESTING OF THE ONTOLOGY: Here we present the Mammalian Feeding Muscle Ontology (MFMO), a multi-species ontology focused on anatomical structures that participate in feeding and other oral/pharyngeal behaviors. A unique feature of the MFMO is that a simple, computable, definition of each muscle, which includes its attachments and innervation, is true across mammals. This construction mirrors the logical foundation of comparative anatomy and permits searches using language familiar to biologists. Further, it provides a template for muscles that will be useful in extending any anatomy ontology. The MFMO is developed to support the Feeding Experiments End-User Database Project (FEED, https://feedexp.org/), a publicly-available, online repository for physiological data collected from in vivo studies of feeding (e.g., mastication, biting, swallowing) in mammals. Currently the MFMO is integrated into FEED and also into two literature-specific implementations of Textpresso, a text-mining system that facilitates powerful searches of a corpus of scientific publications. We evaluate the MFMO by asking questions that test the ability of the ontology to return appropriate answers (competency questions). We compare the results of queries of the MFMO to results from similar searches in PubMed and Google Scholar. RESULTS AND SIGNIFICANCE: Our tests demonstrate that the MFMO is competent to answer queries formed in the common language of comparative anatomy, but PubMed and Google Scholar are not. Overall, our results show that by incorporating anatomical ontologies into searches, an expanded and anatomically comprehensive set of results can be obtained. The broader scientific and publishing communities should consider taking up the challenge of semantically enabled search capabilities.

A blackboard architecture for a hybrid CBR system for scientific software

This paper describes the use of a blackboard architecture for building a hybrid case based reasoning (CBR) system. The Smartfire fire field modelling package has been built using this architecture and includes a CBR component. It allows the integration into the system of qualitative spatial reasoning knowledge from domain experts. The system can be used for the automatic set-up of fire field models. This enables fire safety practitioners who are not expert in modelling techniques to use a fire modelling tool. The paper discusses the integrating powers of the architecture, which is based on a common knowledge representation comprising a metric diagram and place vocabulary and mechanisms for adaptation and conflict resolution built on the Blackboard.

Towards Cloud-Based Knowledge Capturing Based on Natural Language Processing

Paper presented at the Cloud Forward Conference 2015, October 6th-8th, Pisa

Contribution to the knowledge of the genus "Cladonia" in Macaronesia

Sixteen species of the genus Cladonia are reported from Macaronesia from the Canary Islands. Three species are new to canarian flora and, two of them new to Macaronesia. The chemical variation of the taxa is reported. A phytogeographic distribution of the taxa with data on their habitat and ecology are presented.

Determination of relevant Indicators for Environmental monitoring: A Strategy for Europe (DIESE) Final Scientific Report

The DIESE program (Determination of relevant Indicators for Environmental monitoring: A Strategy for Europe) brought together seven French and British research teams, a private company and the agencies responsible for the management of water bodies of the two countries (ONEMA and the Environmental Agency) in a joint effort to document the ecotoxicological effects related to the presence of chemicals in the environment. To contribute to a better understanding and management of the environment, the program has expanded its efforts to (1) use existing knowledge, or new information acquired during the research program, to identify important biological problems affecting the wildlife, (2) increase our understanding of toxicological mechanisms involved and thus be able to identify the causes of the identified dysfunctions and (3) to hone our expertise and vigilance system in order to better monitor changes in the environment and make appropriate diagnoses.

Outposts of Empire: Scientific Discovery and Colonial Displacement in Gaskell's Wives and Daughters

This article offers a fresh consideration of Elizabeth Gaskell's unfinished Wives and Daughters (1864–6), in terms of what this metropolitan novelist knew about contemporary scientific debates and imperial exploration of Africa, and how her familiarity with these discourses was incorporated into her imaginative work. Her focus for these two related themes is the naturalist Roger Hamley, whose character and exploits are meant to parallel those of the young Charles Darwin. Roger's direct involvement in the historical Geoffroy–Cuvier debate allows Gaskell to offer a sophisticated examination of how discussions about evolutionary biology (about which she learned from personal acquaintances and printed sources) contributed to political and social change in the era of the first Reform Bill. Roger's subsequent journey to Abyssinia to gather specimens allows Gaskell to form a link between science and imperial exploration, which demonstrates how, when carried to its conclusion, the development of classificatory knowledge systems was never innocent; rather, it facilitated colonial exploitation and intervention, which allowed for the ‘opening up of Africa’. Gaskell's pronouncements about science in the novel are far more explicit than her brief references to empire; the article ponders why this should be so, and offers some suggestions about how her reliance on imaginative and discursive constructs concerning the ‘Dark Continent’ may be interpreted as tacit complicity with the imperial project, or at least an interest in its more imaginative aspects.

Analysis of the reading and comprehension control in scientific texts in high school students

Students' learning process can be negatively affected when their reading and comprehension control is not appropriated. This research focuses on the analysis of how a group of students from high school evaluate their reading comprehension in manipulated scientific texts. An analysis tool was designed to determine the students' degree of comprehension control when reading a scientific short text with an added contradiction. The results have revealed that the students from 1st and 3rd ESO do not properly self-evaluated their reading comprehension. A different behavior has been observed in 1st Bachillerato, where appropriate evaluation and regulation seem to be more frequent. Moreover, no significant differences have been found regarding the type of text, year or gender. Finally, as identified by previous research, the correlations between the students' comprehension control and their school marks have shown to have a weak relationship and inversely proportional to the students' age.