Information retrieval evaluation in knowledge acquisition tasks

The Cranfield Paradigm is a widely adopted and the de-facto standard approach to the evaluation of IR systems. However, this approach does not inherently support situations in which the user is acquiring knowledge (is learning) during an information seeking session consisting of the submission of a sequence of queries into an information retrieval system. More specifically, during a situation in which the retrieval of a particular document at the beginning of a session can be considered not relevant (due to the user's lack of knowledge), while it can be considered relevant at a later point in the session (once the user acquired all required prerequisite knowledge). In this position paper, we reflect on the limitations of the Cranfield Paradigm in the context of knowledge acquisition tasks and propose several alternatives. These alternatives are based on the notion of evaluating a session consisting of a sequence of individual queries created to address a specific information need as part of a knowledge acquisition task

Murine Features of Neurogenesis in the Human Hippocampus across the Lifespan from 0 to 100 Years

BACKGROUND: Essentially all knowledge about adult hippocampal neurogenesis in humans still comes from one seminal study by Eriksson et al. in 1998, although several others have provided suggestive findings. But only little information has been available in how far the situation in animal models would reflect the conditions in the adult and aging human brain. We therefore here mapped numerous features associated with adult neurogenesis in rodents in samples from human hippocampus across the entire lifespan. Such data would not offer proof of adult neurogenesis in humans, because it is based on the assumption that humans and rodents share marker expression patterns in adult neurogenesis. Nevertheless, together the data provide valuable information at least about the presence of markers, for which a link to adult neurogenesis might more reasonably be assumed than for others, in the adult human brain and their change with increasing age. METHODS AND FINDINGS: In rodents, doublecortin (DCX) is transiently expressed during adult neurogenesis and within the neurogenic niche of the dentate gyrus can serve as a valuable marker. We validated DCX as marker of granule cell development in fetal human tissue and used DCX expression as seed to examine the dentate gyrus for additional neurogenesis-associated features across the lifespan. We studied 54 individuals and detected DCX expression between birth and 100 years of age. Caveats for post-mortem analyses of human tissues apply but all samples were free of signs of ischemia and activated caspase-3. Fourteen markers related to adult hippocampal neurogenesis in rodents were assessed in DCX-positive cells. Total numbers of DCX expressing cells declined exponentially with increasing age, and co-expression of DCX with the other markers decreased. This argued against a non-specific re-appearance of immature markers in specimen from old brains. Early postnatally all 14 markers were co-expressed in DCX-positive cells. Until 30 to 40 years of age, for example, an overlap of DCX with Ki67, Mcm2, Sox2, Nestin, Prox1, PSA-NCAM, Calretinin, NeuN, and others was detected, and some key markers (Nestin, Sox2, Prox1) remained co-expressed into oldest age. CONCLUSIONS: Our data suggest that in the adult human hippocampus neurogenesis-associated features that have been identified in rodents show patterns, as well as qualitative and quantitative age-related changes, that are similar to the course of adult hippocampal neurogenesis in rodents. Consequently, although further validation as well as the application of independent methodology (e.g. electron microscopy and cell culture work) is desirable, our data will help to devise the framework for specific research on cellular plasticity in the aging human hippocampus

Integrating Knowledge Graphs for Analysing Academia and Industry Dynamics

Academia and industry are constantly engaged in a joint effort for producing scientific knowledge that will shape the society of the future. Analysing the knowledge flow between them and understanding how they influence each other is a critical task for researchers, governments, funding bodies, investors, and companies. However, current corpora are unfit to support large-scale analysis of the knowledge flow between academia and industry since they lack of a good characterization of research topics and industrial sectors. In this short paper, we introduce the Academia/Industry DynAmics (AIDA) Knowledge Graph, which characterizes 14M papers and 8M patents according to the research topics drawn from the Computer Science Ontology. 4M papers and 5M patents are also classified according to the type of the author's affiliations (academy, industry, or collaborative) and 66 industrial sectors (e.g., automotive, financial, energy, electronics) obtained from DBpedia. AIDA was generated by an automatic pipeline that integrates several knowledge graphs and bibliographic corpora, including Microsoft Academic Graph, Dimensions, English DBpedia, the Computer Science Ontology, and the Global Research Identifier Database

Human hippocampal neurogenesis drops sharply in children to undetectable levels in adults.

New neurons continue to be generated in the subgranular zone of the dentate gyrus of the adult mammalian hippocampus. This process has been linked to learning and memory, stress and exercise, and is thought to be altered in neurological disease. In humans, some studies have suggested that hundreds of new neurons are added to the adult dentate gyrus every day, whereas other studies find many fewer putative new neurons. Despite these discrepancies, it is generally believed that the adult human hippocampus continues to generate new neurons. Here we show that a defined population of progenitor cells does not coalesce in the subgranular zone during human fetal or postnatal development. We also find that the number of proliferating progenitors and young neurons in the dentate gyrus declines sharply during the first year of life and only a few isolated young neurons are observed by 7 and 13 years of age. In adult patients with epilepsy and healthy adults (18-77 years; n = 17 post-mortem samples from controls; n = 12 surgical resection samples from patients with epilepsy), young neurons were not detected in the dentate gyrus. In the monkey (Macaca mulatta) hippocampus, proliferation of neurons in the subgranular zone was found in early postnatal life, but this diminished during juvenile development as neurogenesis decreased. We conclude that recruitment of young neurons to the primate hippocampus decreases rapidly during the first years of life, and that neurogenesis in the dentate gyrus does not continue, or is extremely rare, in adult humans. The early decline in hippocampal neurogenesis raises questions about how the function of the dentate gyrus differs between humans and other species in which adult hippocampal neurogenesis is preserved

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered

FEBUKO and MODMEP: Field measurements and modelling of aerosol and cloud multiphase processes

An overview of the two FEBUKO aerosol–cloud interaction field experiments in the Thüringer Wald (Germany) in October 2001 and 2002 and the corresponding modelling project MODMEP is given. Experimentally, a variety of measurement methods were deployed to probe the gas phase, particles and cloud droplets at three sites upwind, downwind and within an orographic cloud with special emphasis on the budgets and interconversions of organic gas and particle phase constituents. Out of a total of 14 sampling periods within 30 cloud events three events (EI, EII and EIII) are selected for detailed analysis. At various occasions an impact of the cloud process on particle chemical composition such as on the organic compounds content, sulphate and nitrate and also on particle size distributions and particle mass is observed. Moreover, direct phase transfer of polar organic compound from the gas phase is found to be very important for the understanding of cloudwater composition. For the modelling side, a main result of the MODMEP project is the development of a cloud model, which combines a complex multiphase chemistry with detailed microphysics. Both components are described in a fine-resolved particle/drop spectrum. New numerical methods are developed for an efficient solution of the entire complex model. A further development of the CAPRAM mechanism has lead to a more detailed description of tropospheric aqueous phase organic chemistry. In parallel, effective tools for the reduction of highly complex reaction schemes are provided. Techniques are provided and tested which allow the description of complex multiphase chemistry and of detailed microphysics in multidimensional chemistry-transport models

The Role of Additive Neurogenesis and Synaptic Plasticity in a Hippocampal Memory Model with Grid-Cell Like Input

Recently, we presented a study of adult neurogenesis in a simplified hippocampal memory model. The network was required to encode and decode memory patterns despite changing input statistics. We showed that additive neurogenesis was a more effective adaptation strategy compared to neuronal turnover and conventional synaptic plasticity as it allowed the network to respond to changes in the input statistics while preserving representations of earlier environments. Here we extend our model to include realistic, spatially driven input firing patterns in the form of grid cells in the entorhinal cortex. We compare network performance across a sequence of spatial environments using three distinct adaptation strategies: conventional synaptic plasticity, where the network is of fixed size but the connectivity is plastic; neuronal turnover, where the network is of fixed size but units in the network may die and be replaced; and additive neurogenesis, where the network starts out with fewer initial units but grows over time. We confirm that additive neurogenesis is a superior adaptation strategy when using realistic, spatially structured input patterns. We then show that a more biologically plausible neurogenesis rule that incorporates cell death and enhanced plasticity of new granule cells has an overall performance significantly better than any one of the three individual strategies operating alone. This adaptation rule can be tailored to maximise performance of the network when operating as either a short- or long-term memory store. We also examine the time course of adult neurogenesis over the lifetime of an animal raised under different hypothetical rearing conditions. These growth profiles have several distinct features that form a theoretical prediction that could be tested experimentally. Finally, we show that place cells can emerge and refine in a realistic manner in our model as a direct result of the sparsification performed by the dentate gyrus layer