Calculation, comparison to simulations, and dependence on survey geometry

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-C-l estimates of tomographic cosmic shear power spectra. Using two existing publicly available codes in combination, we calculate the full covariance matrix, including mode-coupling contributions arising from both partial sky coverage and non-linear structure growth. For three different sky masks, we compare the theoretical covariance matrix to that estimated from publicly available N-body weak lensing simulations, finding good agreement. We find that as a more extreme sky cut is applied, a corresponding increase in both Gaussian off-diagonal covariance and non-Gaussian super-sample covariance is observed in both theory and simulations, in accordance with expectations. Studying the different contributions to the covariance in detail, we find that the Gaussian covariance dominates along the main diagonal and the closest off-diagonals, but farther away from the main diagonal the super-sample covariance is dominant. Forming mock constraints in parameters that describe matter clustering and dark energy, we find that neglecting non-Gaussian contributions to the covariance can lead to underestimating the true size of confidence regions by up to 70 per cent. The dominant non-Gaussian covariance component is the super-sample covariance, but neglecting the smaller connected non-Gaussian covariance can still lead to the underestimation of uncertainties by 10-20 per cent. A real cosmological analysis will require marginalisation over many nuisance parameters, which will decrease the relative importance of all cosmological contributions to the covariance, so these values should be taken as upper limits on the importance of each component.Peer reviewe

The Older Population of Texas.

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A hybrid semantic approach to building dynamic maps of research communities

In the last ten years, ontology-based recommender systems have been shown to be effective tools for predicting user preferences and suggesting items. There are however some issues associated with the ontologies adopted by these approaches, such as: 1) their crafting is not a cheap process, being time consuming and calling for specialist expertise; 2) they may not represent accurately the viewpoint of the targeted user community; 3) they tend to provide rather static models, which fail to keep track of evolving user perspectives. To address these issues, we propose Klink UM, an approach for extracting emergent semantics from user feedbacks, with the aim of tailoring the ontology to the users and improving the recommendations accuracy. Klink UM uses statistical and machine learning techniques for finding hierarchical and similarity relationships between keywords associated with rated items and can be used for: 1) building a conceptual taxonomy from scratch, 2) enriching and correcting an existing ontology, 3) providing a numerical estimate of the intensity of semantic relationships according to the users. The evaluation shows that Klink UM performs well with respect to handcrafted ontologies and can significantly increase the accuracy of suggestions in content-based recommender systems

Agency and structure in a sociotechnical transition: Hydrogen fuel cells, conjunctural knowledge and structuration in Europe

Despite each level of the multilevel perspective of sociotechnical transitions reflecting a different degree of structuration, structuration perspectives have been little used to help explain sociotechnical change and stasis. Here we show how ‘strong structuration’ can be used to theorise the role of agency in sociotechnical systems in a way that brings together psychological and sociological perspectives. Strong structuration gives weight not only to actors’ practices, but also to their experiences. Practices and structures are viewed as mutually influencing, as in Giddens’ original conception, but the role of situated, subjective experience is also explicitly acknowledged. Applying this perspective, we show how individual attitudes and beliefs in relation to a niche energy technology are influenced by experience of national economic and innovation policy environments, with in turn implications for expectations of action by self and others. The overall aim is to illustrate a framework that connects individual psychology to practice, with implications for sociotechnical structure. For this purpose we draw on case study data of European R&D stakeholder opinion of stationary hydrogen fuel cell applications for heat and power, focusing particularly on the contrasting situations of the UK, Germany and Spain. © 2017 Elsevier Lt

Identifying diachronic topic-based research communities by clustering shared research trajectories

Communities of academic authors are usually identified by means of standard community detection algorithms, which exploit ‘static’ relations, such as co-authorship or citation networks. In contrast with these approaches, here we focus on diachronic topic-based communities –i.e., communities of people who appear to work on semantically related topics at the same time. These communities are interesting because their analysis allows us to make sense of the dynamics of the research world –e.g., migration of researchers from one topic to another, new communities being spawn by older ones, communities splitting, merging, ceasing to exist, etc. To this purpose, we are interested in developing clustering methods that are able to handle correctly the dynamic aspects of topic-based community formation, prioritizing the relationship between researchers who appear to follow the same research trajectories. We thus present a novel approach called Temporal Semantic Topic-Based Clustering (TST), which exploits a novel metric for clustering researchers according to their research trajectories, defined as distributions of semantic topics over time. The approach has been evaluated through an empirical study involving 25 experts from the Semantic Web and Human-Computer Interaction areas. The evaluation shows that TST exhibits a performance comparable to the one achieved by human experts

Public opinion on energy crops in the landscape: considerations for the expansion of renewable energy from biomass

Public attitudes were assessed towards two dedicated biomass crops – Miscanthus and Short Rotation Coppice (SRC), particularly regarding their visual impacts in the landscape. Results are based on responses to photographic and computer-generated images as the crops are still relatively scarce in the landscape. A questionnaire survey indicated little public concern about potential landscape aesthetics but more concern about attendant built infrastructure. Focus group meetings and interviews indicated support for biomass end uses that bring direct benefits to local communities. Questions arise as to how well the imagery used was able to portray the true nature of these tall, dense, perennial plants but based on the responses obtained and given the caveat that there was limited personal experience of the crops, it appears unlikely that wide-scale planting of biomass crops will give rise to substantial public concern in relation to their visual impact in the landscape

Examining user comments for deliberative democracy: a corpus-driven analysis of the climate change debate online

The public perception of climate change is characterized by heterogeneity, even polarization. Deliberative discussion is regarded by some as key to overcoming polarization and engaging various publics with the complex issue of climate change. In this context, online engagement with news stories is seen as a space for a new “deliberative democratic potential” to emerge. This article examines aspects of deliberation in user comment threads in response to articles on climate change taken from the Guardian. “Deliberation” is understood through the concepts “reciprocity”, “topicality”, and “argumentation”. We demonstrate how corpus analysis can be used to examine the ways in which online debates around climate change may create or deny opportunities for multiple voices and deliberation. Results show that whilst some aspects of online discourse discourage alternative viewpoints and demonstrate “incivility”, user comments also show potential for engaging in dialog, and for high levels of interaction

Searching for converging research using field to field citations

We define converging research as the emergence of an interdisciplinary research area from fields that did not show interdisciplinary connections before. This paper presents a process to search for converging research using journal subject categories as a proxy for fields and citations to measure interdisciplinary connections, as well as an application of this search. The search consists of two phases: a quantitative phase in which pairs of citing and cited fields are located that show a significant change in number of citations, followed by a qualitative phase in which thematic focus is sought in publications associated with located pairs. Applying this search on publications from the Web of Science published between 1995 and 2005, 38 candidate converging pairs were located, 27 of which showed thematic focus, and 20 also showed a similar focus in the other, reciprocal pair

Candida soluble cell wall β-glucan facilitates ovalbumin-induced allergic airway inflammation in mice: Possible role of antigen-presenting cells

<p>Abstract</p> <p>Background</p> <p>Although fungi have been implicated as initiating/deteriorating factors for allergic asthma, their contributing components have not been fully elucidated. We previously isolated soluble β-glucan from <it>Candida albicans </it>(CSBG) (Ohno et al., 2007). In the present study, the effects of CSBG exposure on airway immunopathology in the presence or absence of other immunogenic allergen was investigated <it>in vivo</it>, and their cellular mechanisms were analyzed both <it>in vivo </it>and <it>in vitro</it>.</p> <p>Methods</p> <p><it>In vivo</it>, ICR mice were divided into 4 experimental groups: vehicle, CSBG (25 μg/animal), ovalbumin (OVA: 2 μg/animal), and CSBG + OVA were repeatedly administered intratracheally. The bronchoalveolar lavage cellular profile, lung histology, levels of cytokines and chemokines in the lung homogenates, the expression pattern of antigen-presenting cell (APC)-related molecules in the lung digests, and serum immunoglobulin values were studied. <it>In vitro</it>, the impacts of CSBG (0–12.5 μg/ml) on the phenotype and function of immune cells such as splenocytes and bone marrow-derived dendritic cells (BMDCs) were evaluated in terms of cell proliferation, the surface expression of APC-related molecules, and OVA-mediated T-cell proliferating activity.</p> <p>Results</p> <p><it>In vivo</it>, repeated pulmonary exposure to CSBG induced neutrophilic airway inflammation in the absence of OVA, and markedly exacerbated OVA-related eosinophilic airway inflammation with mucus metaplasia in mice, which was concomitant with the amplified lung expression of Th2 cytokines and IL-17A and chemokines related to allergic response. Exposure to CSBG plus OVA increased the number of cells bearing MHC class II with or without CD80 in the lung compared to that of others. <it>In vitro</it>, CSBG significantly augmented splenocyte proliferation in the presence or absence of OVA. Further, CSBG increased the expression of APC-related molecules such as CD80, CD86, and DEC205 on BMDCs and amplified OVA-mediated T-cell proliferation through BMDCs.</p> <p>Conclusion</p> <p>CSBG potentiates allergic airway inflammation with maladaptive Th immunity, and this potentiation was associated with the enhanced activation of APCs including DC.</p