35 research outputs found
Two Dimensional Adiabatic Flows onto a Black Hole: I. Fluid Accretion
When gas accretes onto a black hole, at a rate either much less than or much
greater than the Eddington rate, it is likely to do so in an "adiabatic" or
radiatively inefficient manner. Under fluid (as opposed to MHD) conditions, the
disk should become convective and evolve toward a state of marginal
instability. The resulting disk structure is "gyrentropic," with convection
proceeding along common surfaces of constant angular momentum, Bernoulli
function and entropy, called "gyrentropes." We present a family of
two-dimensional, self-similar models which describes the time-averaged disk
structure. We then suppose that there is a self-similar, Newtonian torque and
that the Prandtl number is large. This torque drives inflow and meridional
circulation and the resulting flow is computed. Convective transport will
become ineffectual near the disk surface. It is conjectured that this will lead
to a large increase of entropy across a "thermal front" which we identify as
the effective disk surface and the base of an outflow. The conservation of
mass, momentum and energy across this thermal front permits a matching of the
disk models to self-similar outflow solutions. We then demonstrate that
self-similar disk solutions can be matched smoothly onto relativistic flows at
small radius and thin disks at large radius. This model of adiabatic accretion
is contrasted with some alternative models that have been discussed recently.
The disk models developed in this paper should be useful for interpreting
numerical, fluid dynamical simulations. Related principles to those described
here may govern the behaviour of astrophysically relevant, magnetohydrodynamic
disk models.Comment: 21 pages, 9 figures, submitted to Monthly Notices of the Royal
Astronomical Societ
Functional annotations of diabetes nephropathy susceptibility loci through analysis of genome-wide renal gene expression in rat models of diabetes mellitus
<p>Abstract</p> <p>Background</p> <p>Hyperglycaemia in diabetes mellitus (DM) alters gene expression regulation in various organs and contributes to long term vascular and renal complications. We aimed to generate novel renal genome-wide gene transcription data in rat models of diabetes in order to test the responsiveness to hyperglycaemia and renal structural changes of positional candidate genes at selected diabetic nephropathy (DN) susceptibility loci.</p> <p>Methods</p> <p>Both Affymetrix and Illumina technologies were used to identify significant quantitative changes in the abundance of over 15,000 transcripts in kidney of models of spontaneous (genetically determined) mild hyperglycaemia and insulin resistance (Goto-Kakizaki-GK) and experimentally induced severe hyperglycaemia (Wistar-Kyoto-WKY rats injected with streptozotocin [STZ]).</p> <p>Results</p> <p>Different patterns of transcription regulation in the two rat models of diabetes likely underlie the roles of genetic variants and hyperglycaemia severity. The impact of prolonged hyperglycaemia on gene expression changes was more profound in STZ-WKY rats than in GK rats and involved largely different sets of genes. These included genes already tested in genetic studies of DN and a large number of protein coding sequences of unknown function which can be considered as functional and, when they map to DN loci, positional candidates for DN. Further expression analysis of rat orthologs of human DN positional candidate genes provided functional annotations of known and novel genes that are responsive to hyperglycaemia and may contribute to renal functional and/or structural alterations.</p> <p>Conclusion</p> <p>Combining transcriptomics in animal models and comparative genomics provides important information to improve functional annotations of disease susceptibility loci in humans and experimental support for testing candidate genes in human genetics.</p
Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry
Gradient tantalum-doped hematite homojunction photoanode improves both photocurrents and turn-on voltage for solar water splitting
Hematite has a great potential as a photoanode for photoelectrochemical (PEC) water splitting by converting solar energy into hydrogen fuels, but the solar-to-hydrogen conversion efficiency of state-of-the-art hematite photoelectrodes are still far below the values required for practical hydrogen production. Here, we report a core-shell formation of gradient tantalum-doped hematite homojunction nanorods by combination of hydrothermal regrowth strategy and hybrid microwave annealing, which enhances the photocurrent density and reduces the turn-on voltage simultaneously. The unusual bi-functional effects originate from the passivation of the surface states and intrinsic built-in electric field by the homojunction formation. The additional driving force provided by the field can effectively suppress charge???carrier recombination both in the bulk and on the surface of hematite, especially at lower potentials. Moreover, the synthesized homojunction shows a remarkable synergy with NiFe(OH)x cocatalyst with significant additional improvements of photocurrent density and cathodic shift of turn-on voltage. The work has nicely demonstrated multiple collaborative strategies of gradient doping, homojunction formation, and cocatalyst modification, and the concept could shed light on designing and constructing the efficient nanostructures of semiconductor photoelectrodes in the field of solar energy conversion. ?? 2020, The Author(s)
Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry
To face global competition, and also reduce environmental and climate impact, industry-wide changes are needed, especially regarding energy use, which is closely related to global warming. Energy efficiency is therefore an essential task for the future as it has a significant impact on both business profits and the environment. For the analysis of possible changes in industrial production processes, and to choose what changes should be made, various modelling tools can be used as a decision support. This paper uses two types of energy analysis tool: Discrete Event Simulation (DES) and Energy Systems Optimisation (ESO). The aim of this study is to describe how a DES and an ESO tool can be combined. A comprehensive five-step approach is proposed for reducing system costs and making a more robust production system. A case study representing a new investment in part of a Swedish iron foundry is also included to illustrate the method's use. The method described in this paper is based on the use of the DES program QUEST and the ESO tool reMIND. The method combination itself is generic, i.e. other similar programs can be used as well with some adjustments and adaptations. The results from the case study show that when different boundary conditions are used the result obtained from the simulation tools is not optimum, in other words, the result shows only a feasible solution and not the best way to run the factory. It is therefore important to use the optimisation tool in such cases in order to obtain the optimum operating strategy. By using the optimisation tool a substantial amount of resources can be saved. The results also show that the combination of optimisation and simulation tools is useful to provide very detailed information about how the system works and to predict system behaviour as well as to minimise the system cost.funding agencies|Swedish Energy Agency (SEA)||</p
Developing new understanding of photoelectrochemical water splitting via in-situ techniques: A review on recent progress
Accuracy of a GFR Estimating Equation Over Time in People With a Wide Range of Kidney Function
BACKGROUND: Change in glomerular filtration rate (GFR) is important for clinical decision making. GFR estimates from serum creatinine provide an unbiased but imprecise estimate of GFR at single time points. However, the accuracy of estimated GFR over time is not well known. STUDY DESIGN: Longitudinal study of diagnostic test accuracy SETTINGS AND PARTICIPANTS: Four clinical trials with longitudinal measures of GFR and serum creatinine on the same day, including subjects with and without kidney disease, with a wide range of kidney function, diverse racial backgrounds and varied clinical characteristics. INDEX TEST: GFR estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. REFERENCE TEST: GFR measured using urinary clearance of (125)I-iothalamate RESULTS: Data included 19,735 GFR measurements in 3531 subjects over mean follow up of 2.6 years. Mean at baseline for measured and estimated GFR and error (measured GFR – estimated GFR) were 73.1 (95% CI, 71.6 to 74.5), 72.7 (95% CI, 71.5 to 74.0) and 0.14 (95% CI, −0.35 to 0.63) ml/min/1.73 m(2), respectively. The mean rate of change in measured and estimated GFR and error was −2.3 (95% CI, −2.4 to −2.1), −2.2 (95% CI, −2.4 to −2.1) and −0.09 (95% CI, −0.24 to 0.05) ml/min/1.73 m(2) per year (p <.001, p <.001, and p = 0.2 respectively). The variability (ie, SD) among subjects in rate of change in measured GFR, estimated GFR and error was 4.3, 3.4 and 3.3 ml/min/1.73 m(2) per year, respectively. Only 15% of subjects had a rate of change in error of more than 3 ml/min/1.73 m(2) per year, and only 2% had a rate of change in error larger than 5% per year. LIMITATIONS: Subject characteristics were not available over time. CONCLUSION: Accuracy of GFR estimates did not change over time. Clinicians should interpret changes in estimated GFR over time as reflecting changes in measured GFR rather than changes in errors in the GFR estimates in most individuals