1,194 research outputs found
Identification-based Diagnosis of Rainfall ÂżStream Flow Data: the Tinderry Catchment
System identification tools, such as transfer function (TF) model structure identification, recursive estimation, time-varying parameter (TVP) estimation and assessment of data information, are used to evaluate the quality of rainfall-stream flow data from the Tinderry catchment (ACT, Australia) and the timevarying behaviour of the rainfall-stream flow dynamics. For the catchment, given the wide range and the abrupt changes of the single input-single output transfer functions describing different periods or events, we conclude that further investigation of (i) local rainfall effects, (ii) time-varying time delays (travelling time), (iii) time-varying residence times related to the base flow and (iv) occurrence of negative residues is needed. Periods with high and low data information content, for further use in effective parameter estimation procedures, are clearly indicated by the analysis
Metabolic profiling predicts response to anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis
<p>Objective: Anti–tumor necrosis factor (anti-TNF) therapies are highly effective in rheumatoid arthritis (RA) and psoriatic arthritis (PsA), but a significant number of patients exhibit only a partial or no therapeutic response. Inflammation alters local and systemic metabolism, and TNF plays a role in this. We undertook this study to determine if the patient's metabolic fingerprint prior to therapy could predict responses to anti-TNF agents.</p>
<p>Methods: Urine was collected from 16 RA patients and 20 PsA patients before and during therapy with infliximab or etanercept. Urine metabolic profiles were assessed using nuclear magnetic resonance spectroscopy. Discriminating metabolites were identified, and the relationship between metabolic profiles and clinical outcomes was assessed.</p>
<p>Results: Baseline urine metabolic profiles discriminated between RA patients who did or did not have a good response to anti-TNF therapy according to European League Against Rheumatism criteria, with a sensitivity of 88.9% and a specificity of 85.7%, with several metabolites contributing (in particular histamine, glutamine, xanthurenic acid, and ethanolamine). There was a correlation between baseline metabolic profiles and the magnitude of change in the Disease Activity Score in 28 joints from baseline to 12 months in RA patients (P = 0.04). In both RA and PsA, urinary metabolic profiles changed between baseline and 12 weeks of anti-TNF therapy. Within the responders, urinary metabolite changes distinguished between etanercept and infliximab treatment.</p>
<p>Conclusion: The clear relationship between urine metabolic profiles of RA patients at baseline and their response to anti-TNF therapy may allow development of novel approaches to the optimization of therapy. Differences in metabolic profiles during treatment with infliximab and etanercept in RA and PsA may reflect distinct mechanisms of action.</p>
A Universal Vertical Stellar Density Distribution Law for the Galaxy
We reduced the observational logarithmic space densities in the vertical
direction up to 8 kpc from the galactic plane, for stars with absolute
magnitudes (5,6], (6,7] and [5,10] in the fields #0952+5245 and SA114, to a
single exponential density law. One of three parameters in the quadratic
expression of the density law corresponds to the local space density for stars
with absolute magnitudes in question. There is no need of any definition for
scaleheights or population types. We confirm with the arguments of non-discrete
thin and thick discs for our Galaxy and propose a single structure up to
several kiloparsecs from the galactic plane. The logarithmic space densities
evaluated by this law for the ELAIS field fit to the observational ones.
Whereas, there are considerable offsets for the logarithmic space densities
produced by two sets of classical galactic model parameters from the
observational ones, for the same field.Comment: 9 pages, 1 figure and 10 tables, accepted for publication in
Astrophysics & Space Scienc
An improved instrumental variable method for industrial robot model identification
Abstract Industrial robots are electro-mechanical systems with double integrator behaviour, necessitating operation and model identification under closed-loop control conditions. The Inverse Dynamic Identification Model (IDIM) is a mechanical model based on Newton’s laws that has the advantage of being linear with respect to the parameters. Existing Instrumental Variable (IDIM-IV) estimation provides a robust solution to this estimation problem and the paper introduces an improved IDIM-PIV method that takes account of the additive noise characteristics by adding prefilters that provide lower variance estimates of the IDIM parameters. Inspired by the prefiltering approach used in optimal Refined Instrumental Variable (RIV) estimation, the IDIM-PIV method identifies the nonlinear physical model of the robot, as well as the noise model resulting from the feedback control system. It also has the advantage of providing a systematic prefiltering process, in contrast to that required for the previous IDIM-IV method. The issue of an unknown controller is also considered and resolved using existing parametric identification. The evaluation of the new estimation algorithms on a six degrees-of-freedom rigid robot shows that they improve statistical efficiency, with the controller either known or identified as an intrinsic part of the IDIM-PIV algorithm
Identification of continuous-time models with slowly time-varying parameters
The off-line estimation of the parameters of continuous-time, linear, time-invariant transfer function models can be achieved straightforwardly using linear prefilters on the measured input and output of the system. The on-line estimation of continuous-time models with time-varying parameters is less straightforward because it requires the updating of the continuous-time prefilter parameters. This paper shows how such on-line estimation is possible by using recursive instrumental variable approaches. The proposed methods are presented in detail and also evaluated on a numerical example using both single experiment and Monte Carlo simulation analysis. In addition, the proposed recursive algorithms are tested using data from two real-life systems
Electronics Letters
The optimal refined instrumental variable method for the estimation of the Box-Jenkins (BJ) model is modified so that it functions as an optimal filter and state-estimation algorithm. In contrast to the previously developed minimal and non-minimal state-space (NMSS) forms for an Auto-Regressive Moving Average with eXogenous variables (ARMAX) model, the new algorithm requires the introduction of a novel extended NMSS form. This facilitates representation of the more general noise component of the BJ model. The approach can be used for adaptive filtering and state variable feedback control
EUV Spectra of the Full Solar Disk: Analysis and Results of the Cosmic Hot Interstellar Plasma Spectrometer (CHIPS)
We analyze EUV spectra of the full solar disk from the Cosmic Hot
Interstellar Plasma Spectrometer (CHIPS) spanning a period of two years. The
observations were obtained via a fortuitous off-axis light path in the 140 --
270 Angstrom passband. The general appearance of the spectra remained
relatively stable over the two-year time period, but did show significant
variations of up to 25% between two sets of Fe lines that show peak emission at
1 MK and 2 MK. The variations occur at a measured period of 27.2 days and are
caused by regions of hotter and cooler plasma rotating into, and out of, the
field of view. The CHIANTI spectral code is employed to determine plasma
temperatures, densities, and emission measures. A set of five isothermal
plasmas fit the full disk spectra well. A 1 -- 2 MK plasma of Fe contributes
85% of the total emission in the CHIPS passband. The standard Differential
Emission Measures (DEMs) supplied with the CHIANTI package do not fit the CHIPS
spectra well as they over-predict emission at temperatures below log(T) = 6.0
and above log(T) = 6.3. The results are important for cross-calibrating TIMED,
SORCE, SOHO/EIT, and CDS/GIS, as well as the recently launched Solar Dynamics
Observatory.Comment: 27 Pages, 13 Figure
The Influences of Diesel Particulate Filter Installation on Air Pollutant Emissions for Used Vehicles
Three kinds of diesel particulate filters (DPFs) were installed on used diesel-powered vehicles to investigate their influences on air pollutant emissions. The air pollutant emissions were measured before, after and running for specific distances to assess the deterioration effect. The emission measurement was performed on a chassis dynamometer. The results show that emissions of smoke, CO and HC are all reduced after DPF installation. After 20000 km driving, the emission concentrations of the above 3 criteria air pollutants do not increase in comparison with that right after installation. When DPFs are installed, the emissions of PAHs (polycyclic aromatic hydrocarbons) are reduced by 85.6-89.4% and 69.0-89.2% for heavy-duty diesel vehicles (HDVs) and light-duty diesel vehicles (LDVs), respectively. After driving 20000 km for HDVs and 2500 km for LDVs, PAH emissions do not increase in comparison with that right after installation, indicating that the DPFs do not deteriorate after driving for the test mileages. The lower molecular weight PAHs predominates in the exhaust both before and after DPF installation. The results also show the reduction rate is higher for higher molecular weight PAHs due to their tendency to adsorb on particulate
Signatures of the slow solar wind streams from active regions in the inner corona
Some of local sources of the slow solar wind can be associated with
spectroscopically detected plasma outflows at edges of active regions
accompanied with specific signatures in the inner corona. The EUV telescopes
(e.g. SPIRIT/CORONAS-F, TESIS/CORONAS-Photon and SWAP/PROBA2) sometimes
observed extended ray-like structures seen at the limb above active regions in
1MK iron emission lines and described as "coronal rays". To verify the
relationship between coronal rays and plasma outflows, we analyze an isolated
active region (AR) adjacent to small coronal hole (CH) observed by different
EUV instruments in the end of July - beginning of August 2009. On August 1 EIS
revealed in the AR two compact outflows with the Doppler velocities V =10-30
km/s accompanied with fan loops diverging from their regions. At the limb the
ARCH interface region produced coronal rays observed by EUVI/STEREO-A on July
31 as well as by TESIS on August 7. The rays were co-aligned with open magnetic
field lines expanded to the streamer stalks. Using the DEM analysis, it was
found that the fan loops diverged from the outflow regions had the dominant
temperature of ~1 MK, which is similar to that of the outgoing plasma streams.
Parameters of the solar wind measured by STEREO-B, ACE, WIND, STEREO-A were
conformed with identification of the ARCH as a source region at the
Wang-Sheeley-Arge map of derived coronal holes for CR 2086. The results of the
study support the suggestion that coronal rays can represent signatures of
outflows from ARs propagating in the inner corona along open field lines into
the heliosphere.Comment: Accepted for publication in Solar Physics; 31 Pages; 13 Figure
Nucleon mass and sigma term from lattice QCD with two light fermion flavors
We analyze Nf=2 nucleon mass data with respect to their dependence on the
pion mass down to mpi = 157 MeV and compare it with predictions from covariant
baryon chiral perturbation theory (BChPT). A novel feature of our approach is
that we fit the nucleon mass data simultaneously with the directly obtained
pion-nucleon sigma-term. Our lattice data below mpi = 435 MeV is well described
by O(p^4) BChPT and we find sigma=37(8)(6) MeV for the sigma-term at the
physical point. Using the nucleon mass to set the scale we obtain a Sommer
parameter of r_0=0.501(10)(11) fm.Comment: 26 pages, 11 figures, 5 tables. Version to appear in NPB with a few
more details on the fit parameter
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