Neurological Disorders and Publication Abstracts Follow Elements of Social Network Patterns when Indexed Using Ontology Tree-Based Key Term Search

Disorders of the Central Nervous System (CNS) are worldwide causes of morbidity and mortality. In order to further investigate the nature of the CNS research, we generate from an initial reference a controlled vocabulary of CNS disorder-related terms and ontological tree structure for this vocabulary, and then apply the vocabulary in an analysis of the past ten years of abstracts (N = 10,488) from a major neuroscience journal. Using literal search methodology with our terminology tree, we find over 5,200 relationships between abstracts and clinical diagnostic topics. After generating a network graph of these document-topic relationships, we find that this network graph contains characteristics of document-author and other human social networks, including evidence of scale-free and power law-like node distributions. However, we also found qualitative evidence for Z-normal-type (albeit logarithmically skewed) distributions within disorder popularity. Lastly, we discuss potential consumer-centered as well as clinic-centered uses for our ontology and search methodology

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The present and future of QCD

This White Paper presents an overview of the current status and future perspective of QCD research, based on the community inputs and scientific conclusions from the 2022 Hot and Cold QCD Town Meeting. We present the progress made in the last decade toward a deep understanding of both the fundamental structure of the sub-atomic matter of nucleon and nucleus in cold QCD, and the hot QCD matter in heavy ion collisions. We identify key questions of QCD research and plausible paths to obtaining answers to those questions in the near future, hence defining priorities of our research over the coming decades

A Collaborative agent architecture with human-agent communication model

Designing a virtual agent architecture that comprises collaboration between the agents and human users remains a challenging issue due to differences in beliefs, ways of reasoning and the abilities used to achieve the common goal. Allowing the agent and human to communicate verbally and non-verbally while achieving the collaborative task, further increases the difficulty of the challenge. In this paper, we present an overview of existing research involving collaborative agents in virtual environments and extend our Multi-Agent Collaborative VIrtuaL Learning Environment (MACVILLE) agent architecture to handle two-way human-agent collaboration. A scenario is provided.19 page(s

SeMatching: using semantics to perform pair matching processes

Proceedings of: Second World Summit on the Knowledge Society (WSKS 2009), Chania, Crete, Greece, September 16-18, 2009.The importance of the human factor in 21st century organizations means that the competent development of professionals has become a key aspect. In this environment, mentoring has emerged as a common and efficient practice for the development of knowledge workers. Following the surge of concepts such as eMentoring, advancements of the Internet and its evolution towards a Semantic Web, such developments present novel opportunities for the improvement of the different characteristics of mentoring. Basing itself on such advancements, this paper presents SeMatching, a semantics-based platform which utilizes different personal and professional information to carry out pair matching of mentors and mentees.Publicad