2,854 research outputs found
STME Hydrogen Mixer Study
The hydrogen mixer for the Space Transportation Main Engine is used to mix cold hydrogen bypass flow with warm hydrogen coolant chamber gas, which is then fed to the injectors. It is very important to have a uniform fuel temperature at the injectors in order to minimize mixture ratio problems due to the fuel density variations. In addition, the fuel at the injector has certain total pressure requirements. In order to achieve these objectives, the hydrogen mixer must provide a thoroughly mixed fluid with a minimum pressure loss. The AEROVISC computational fluid dynamics (CFD) code was used to analyze the STME hydrogen mixer, and proved to be an effective tool in optimizing the mixer design. AEROVISC, which solves the Reynolds Stress-Averaged Navier-Stokes equations in primitive variable form, was used to assess the effectiveness of different mixer designs. Through a parametric study of mixer design variables, an optimal design was selected which minimized mixed fuel temperature variation and fuel mixer pressure loss. The use of CFD in the design process of the STME hydrogen mixer was effective in achieving an optimal mixer design while reducing the amount of hardware testing
Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach
The half-life is defined as the number of periods required for the impulse response to a unit shock to a time series to dissipate by half. It is widely used as a measure of persistence, especially in international economics to quantify the degree of mean reversion of the deviation from an international parity condition. Several studies have proposed bias-corrected point and interval estimation methods. However, they have found that the confidence intervals are rather uninformative with their upper bound being either extremely large or infinite. This is largely due to the distribution of the half-life estimator being heavily skewed and multi-modal. In this paper, we propose a bias-corrected bootstrap procedure for the estimation of half-life, adopting the highest density region (HDR) approach to point and interval estimation. Our Monte Carlo simulation results reveal that the bias-corrected bootstrap HDR method provides an accurate point estimator, as well as tight confidence intervals with superior coverage properties to those of its alternatives. As an application, the proposed method is employed for half-life estimation of the real exchange rates of seventeen industrialized countries. The results indicate much faster rates of mean-reversion than those reported in previous studies.Autoregressive Model, Bias-correction, Bootstrapping, Confidence interval, Half-life, Highest density region.
Attendee-Sourcing: Exploring The Design Space of Community-Informed Conference Scheduling
Constructing a good conference schedule for a large multi-track conference
needs to take into account the preferences and constraints of organizers,
authors, and attendees. Creating a schedule which has fewer conflicts for
authors and attendees, and thematically coherent sessions is a challenging
task.
Cobi introduced an alternative approach to conference scheduling by engaging
the community to play an active role in the planning process. The current Cobi
pipeline consists of committee-sourcing and author-sourcing to plan a
conference schedule. We further explore the design space of community-sourcing
by introducing attendee-sourcing -- a process that collects input from
conference attendees and encodes them as preferences and constraints for
creating sessions and schedule. For CHI 2014, a large multi-track conference in
human-computer interaction with more than 3,000 attendees and 1,000 authors, we
collected attendees' preferences by making available all the accepted papers at
the conference on a paper recommendation tool we built called Confer, for a
period of 45 days before announcing the conference program (sessions and
schedule). We compare the preferences marked on Confer with the preferences
collected from Cobi's author-sourcing approach. We show that attendee-sourcing
can provide insights beyond what can be discovered by author-sourcing. For CHI
2014, the results show value in the method and attendees' participation. It
produces data that provides more alternatives in scheduling and complements
data collected from other methods for creating coherent sessions and reducing
conflicts.Comment: HCOMP 201
Appropriate Methodologies to Better Measure Consumer Preferences for Postal Services
This report summarises work undertaken testing the use of stated preference discrete choice experiments to measure consumer preferences for postal services. It discusses the importance of understanding and quantifying consumer priorities in the postal sector and presents different methods used for valuing non-market goods. We recommend the use of stated preference discrete choice experiments, and test the use of this approach in three member states. We provide the findings for these member states, as well as a “tool kit” for applying this methodology in other member states in future.Consumer preferences, postal services, discrete choice, two-sided market
Promoting environmental management in very small businesses through “Green Angels” in a local collaborative partnership: a case study from Brighton, England
This paper describes the results of the East Brighton Employment and Environment Centre (EBEEC), a 15 month URBAN project, promoting environmental management to very small businesses in east Brighton, England. Some 31 volunteers, termed `Green Angels`, were trained in waste minimisation at the University of Brighton, and provided practical support to local firms through site reviews and research. The EBEEC project provided information and support to some 600 SMEs in east Brighton, via newsletters, email, telephone helpline, seminars and other projects. The Project was managed by a collaborative partnership formed from regional as well as local organisations. The involvement of a University to train potential `Green Angels`, so as to support SMEs in an area designated for economic regeneration, was an innovative and successful method of providing environmental management support to small firms. To stimulate the uptake of environmental management, case study material based on Best Practice was produced and disseminated to local companies via an Internet Site. A CD-Rom containing the Green Angel training package has been produced to help other projects like this. The outcomes from this Project will inform the regional and potentially the national approach to providing environmental business support and advice via local collaborative partnerships containing Universities
Non-destructive characterisation of mesenchymal stem cell differentiation using LC-MS-based metabolite footprinting
Bone regeneration is a complex biological process where major cellular changes take place to support the osteogenic differentiation of mesenchymal bone progenitors. To characterise these biological changes and better understand the pathways regulating the formation of mature bone cells, the metabolic profile of mesenchymal stem cell (MSC) differentiation in vitro has been assessed non-invasively during osteogenic (OS) treatment using a footprinting technique. Liquid chromatography (LC)-mass spectrometry (MS)-based metabolite profiling of the culture medium was carried out in parallel to mineral deposition and alkaline phosphatase activity which are two hallmarks of osteogenesis in vitro. Metabolic profiles of spent culture media with a combination of univariate and multivariate analyses investigated concentration changes of extracellular metabolites and nutrients linked to the presence of MSCs in culture media. This non-invasive LC-MS-based analytical approach revealed significant metabolic changes between the media from control and OS-treated cells showing distinct effects of MSC differentiation on the environmental footprint of the cells in different conditions (control vs. OS treatment). A
subset of compounds was directly linked to the osteogenic time-course of differentiation, and represent interesting metabolite candidates as non-invasive biomarkers for characterising the differentiation of MSCs in a culture medium
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GABA-modulating bacteria of the human gut microbiota.
The gut microbiota affects many important host functions, including the immune response and the nervous system1. However, while substantial progress has been made in growing diverse microorganisms of the microbiota2, 23-65% of species residing in the human gut remain uncultured3,4, which is an obstacle for understanding their biological roles. A likely reason for this unculturability is the absence in artificial media of key growth factors that are provided by neighbouring bacteria in situ5,6. In the present study, we used co-culture to isolate KLE1738, which required the presence of Bacteroides fragilis to grow. Bioassay-driven purification of B. fragilis supernatant led to the isolation of the growth factor, which, surprisingly, is the major inhibitory neurotransmitter GABA (γ-aminobutyric acid). GABA was the only tested nutrient that supported the growth of KLE1738, and a genome analysis supported a GABA-dependent metabolism mechanism. Using growth of KLE1738 as an indicator, we isolated a variety of GABA-producing bacteria, and found that Bacteroides ssp. produced large quantities of GABA. Genome-based metabolic modelling of the human gut microbiota revealed multiple genera with the predicted capability to produce or consume GABA. A transcriptome analysis of human stool samples from healthy individuals showed that GABA-producing pathways are actively expressed by Bacteroides, Parabacteroides and Escherichia species. By coupling 16S ribosmal RNA sequencing with functional magentic resonance imaging in patients with major depressive disorder, a disease associated with an altered GABA-mediated response, we found that the relative abundance levels of faecal Bacteroides are negatively correlated with brain signatures associated with depression
How can we make the psychiatric workforce more family focused?
[Extract] Initially, the chapter outlines what we mean by family approaches and then overviews our conception of a continuum of family-focused care and expectations for psychiatric agencies and workers. A brief theoretical review of family-focused care is then outlined followed by information about barriers and enablers to family-focused practice. The chapter ends with reflections from multiple countries regarding the current state of family-focused practice and potential ways forward in each country
The Spatial Evolution of Stellar Structures in the LMC/SMC
We present an analysis of the spatial distribution of various stellar
populations within the Large and Small Magellanic Clouds. We use optically
selected stellar samples with mean ages between ~9 and ~1000 Myr, and existing
stellar cluster catalogues to investigate how stellar structures form and
evolve within the LMC/SMC. We use two statistical techniques to study the
evolution of structure within these galaxies, the -parameter and the
two-point correlation function (TPCF). In both galaxies we find the stars are
born with a high degree of substructure (i.e. are highly fractal) and that the
stellar distribution approaches that of the 'background' population on
timescales similar to the crossing times of the galaxy (~80/150 Myr for the
SMC/LMC respectively). By comparing our observations to simple models of
structural evolution we find that 'popping star clusters' do not significantly
influence structural evolution in these galaxies. Instead we argue that general
galactic dynamics are the main drivers, and that substructure will be erased in
approximately the crossing time, regardless of spatial scale, from small
clusters to whole galaxies. This can explain why many young Galactic clusters
have high degrees of substructure, while others are smooth and centrally
concentrated. We conclude with a general discussion on cluster 'infant
mortality', in an attempt to clarify the time/spatial scales involved.Comment: 6 pages, conference contribution to IAU Symposium 256, van Loon J.T.
& Oliviera J.M., ed
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