Hangzhou Regional Center (HRC) for Small Hydro Power has hosted 70 international training workshops or seminars on small hydropower (SHP) and rural electrification (RE) which embraced thousands of engineers, department heads, decision-makers and ministers from over 100 countries and regions. The training programs are highly appreciated and widely welcome by the associated UN organizations and developing Countries. HRC serves as an important means of international cooperation on SHP and RE in China, as one of the first centers that undertake the foreign-aid trainings. Source
Small hydropower (SHP) is internationally well known clean renewable energy, and quite rich in China. China already had a history of 100 years in SHP development. At the initial stage of SHP development, electricaland mechanical equipment were nonstandard production, so the technical key and applied research is to combine local actual situation, for example, to obtain raw material locally to build earth dam, rockfill dam, concrete penstock. With the reform of national finance system, electric power system reform, that the protection of the ecological environment and scientific development becomes the increasingly high demand, there are still problems to be solved in process of SHP development. One of key problems is that the development of diversion type hydropower stations is carried out without considering the ecological water flow, which leads to water reducing or dehydration of local rivers in the dry season. Source
Less than a cubic metre, Proba-1 is the first in ESA's series of satellites aimed at flight-testing new space technologies. It was launched in October 2001 as an experimental mission but is still going strong after 14 years in orbit, having since been reassigned to ESA's Earth observation team. Proba-1's main hyperspectral CHRIS imager is supplemented by this experimental HRC high-resolution camera, acquiring black and white 5 m-resolution images. Other innovations included what were then novel gallium-arsenide solar cells, the use of startrackers for attitude control, one of the first lithium-ion batteries – now the longest such item operating in orbit – and one of ESA's first ERC32 microprocessors to run Proba-1's agile computer. Towering 348 m above its surroundings, the monolithic Uluru was formed from compressed layers of sandstone when this part of Australia was a shallow sea, layers that were subsequently tilted and uplifted. The lines seen cutting across its top come from horizontal sandstone layering. This image was acquired by HRC on 8 September 2015. Explore further: Small but agile Proba-1 reaches 10 years in orbit
Using the ROSAT All-Sky Survey18, the region around the host galaxy, PGC 043234, was searched for point sources. No sources were found. Points in the vicinity of the host galaxy were examined to derive a background count rate of 0.002 counts s−1. Assuming the Milky Way column density N along this line of sight, and taking a typical Seyfert X-ray spectral index of Γ = 1.7, this count rate translates into L ≈ 4.8 × 1040 erg s−1. This limit is orders of magnitude below a Seyfert or quasar luminosity. Swift16 monitors transient and variable sources via co-aligned X-ray (XRT, 0.3–10 keV) and ultraviolet–optical (UVOT, 170–650 nm) telescopes. High-cadence monitoring of ASASSN-14li with UVOT has continued in six bands: V, B, U, UVW1, UVM2, and UVW2 (central wavelength λ = 550 nm, 440 nm, 350 nm, 260 nm, 220 nm and 190 nm). All observations were processed using the latest HEASOFT (http://heasarc.gsfc.nasa.gov/docs/software/lheasoft/) suite and calibrations. Individual optical/ultraviolet exposures were astrometrically corrected and sub-exposures in each filter were summed. Source fluxes were then extracted from an aperture of 3″ radius, and background fluxes were extracted from a source-free region to the east of ASASSN-14li owing to the presence of a (blue) star lying 10 arcsec to the South, using UVOTMAGHIST, a routine within HEASOFT. To estimate the host contamination, we have measured the host flux in 3″ aperture (matched to the aperture used for the UVOT photometry) in pre-outburst Sloan Digital Sky Survey (SDSS29), 2 Micron All-Sky Survey (2MASS30), and GALEX31 images. We took extra care to deblend the GALEX data, where the large point spread function (PSF) resulted in contamination from the star about 10″ to the South. We estimated the uncertainty in each host flux by varying the inclusion aperture from 2″ to 4″. We then fitted the host photometry to synthetic galaxy templates using the Fitting and Assessment of Synthetic Templates (FAST32) code. We employed stellar templates from the33catalogue, and allowed the star-formation history, extinction law, and initial mass function to vary over the full range of parameters allowed by the software. All best-fit models had stellar masses of about 109.2M , low ongoing star-formation rates (at most about 10−1.5M yr−1), and modest line-of-sight extinction (A ≲ 0.4 mag). We integrated the resulting galaxy template spectra over each UVOT filter bandpass to estimate the host count rate. For the uncertainty in this value, we adopt either the root-mean-square spread of the resulting galaxy template models, or 10% of the inferred count rate, whichever value was larger. We then subtracted these values from our measured (coincidence-loss corrected) photometry of the host plus transient, to isolate the component that is due to TDE. For reference, our inferred count rates for each UVOT filter are 5.7 ± 0.6 s−1 for V, 9.4 ± 0.9 s−1 for B, 4.0 ± 0.4 s−1 for U, 0.83 ± 0.08 s−1 for UVW1, 0.29 ± 0.03 s−1 for UVM2, and 0.49 ± 0.05 s−1 for UVW2. Figure 1 shows the host-subtracted optical and ultraviolet light curves ASASSN-14li. The UVM2 filter provides the most robust trace of the mass accretion rate in a TDE like ASASSN-14li; it has negligible transmission at optical wavelengths34, 35. Fits to the UVM2 light curve with a power law of the form f(t) = f × (t + t )α with a fixed index of α = −5/3 imply a disruption date of t = 56,980 ± 3 (mjd). This model achieves a fair characterization of the data; high fluxes between days 80 and 100 (in the units of Fig. 1) result in a poor statistical fit (χ2/ν = 1.7, where ν = 54 degrees of freedom). If the light curve is fitted with a variable index, a value of −2.6 ± 0.3 is measured (90% confidence). This model achieves an improved fit (χ2/ν = 1.4, for ν = 53 degrees of freedom), but it does not tightly constrain the disruption date, placing t in the mjd 56,855–56,920 range. That disruption window is adjacent to an interval wherein the ASASSN monitoring did not detect the source15, making it less plausible than the fit with α = −5/3. The optical bands appear to have a shallower decay curve than the ultraviolet bands. Recent theory11 predicts that optical light produced via thermal disk emission should show a decay consistent with t−5/12; this might also be due to reprocessing7. The V-band data are consistent with this prediction, though the data are of modest quality and a broad range of decays are permitted. The Swift XRT17 is a charge-coupled device. In such cameras, photon pile-up occurs when two or more photons land within a single detection box during a single frame time. This causes flux distortions and spectral distortions to bright sources. Such distortions are effectively avoided by extracting events from an annular region, rather than from a circle at the centre of the telescope PSF. We therefore extracted source spectra from annuli with an inner radius of 12 arcsec (5 pixels), and an outer radius of 50 arcsec. Background flux was measured in an annular region extending from 140 arcsec to 210 arcsec. Standard redistribution matrices were used; an ancillary response file was created with the xrtmkarf tool (a routine within HEASOFT) using a vignetting corrected exposure map. The source spectra were rebinned to have 20 counts per bin with grppha. In all spectral fits, we adopted a lower spectral bound of 0.3 keV (36 Å). The upper bound on spectral fits varied depending on the boundary of the last bin with at least 20 counts; this was generally around 1 keV (12 Å). The XRT spectra were fitted with a model consisting of absorption in the Milky Way of a blackbody emitted at the redshift of the TDE, that is, pha(zashift(bbodyrad)), where N ≡ 4 × 1020 cm−2 and z ≡ 0.0206. The evolution of the best-fit temperature of this blackbody component is displayed in Fig. 3. The blackbody temperature values measured from the Swift XRT are slightly higher (kT ≈ 7–10 eV) than those measured with XMM-Newton and Chandra. If an outflow component with fiducial parameters is included in the spectral model anyway, the XRT temperatures are then in complete agreement with those measured using XMM-Newton and Chandra. Luminosity values inferred for the band over which the high-resolution spectra are actually fitted, and for a broader band, are listed in Table 1. Taking the broader values as a proxy for a true bolometric fit, the highest implied soft X-ray luminosity is measured in the last XMM-Newton monitoring observation, giving L ≈ 3.2 × 1044 erg s−1. The Eddington luminosity for standard hydrogen-rich accretion is L = 1.3 × 1038 erg s−1 (M/M ). This implies a black-hole mass of M ≈ 2.5 × 106M . Blackbody continua imply size scales, and, if we assume that optically thick blackbody emission can only originate at radii larger than the innermost stable circular orbit (ISCO), also masses. For a non-spinning Schwarzschild black hole, r = 6GM/c2. The blackbody emission measured in fits to the time-averaged XMM-Newton ‘long stare’ gives an emitting area of 3.7 × 1025 cm2; implying r = 1.7 × 1012 cm for a spherical geometry. The actual geometry may be more disk-like, but the inner flow may be a thick disk that is better represented by a spherical geometry. If the black hole powering ASASSN-14li is not spinning, this size implies a black-hole mass of M ≈1.9 × 106M . We also estimated the mass of the black hole at the heart of ASASSN-14li by fitting the host-subtracted light curves (see Fig. 1) using the Monte Carlo software TDEFit7. This software assumes that emission is produced within an elliptical accretion disk where the mass accretion rate follows the fallback rate36 onto the black hole with a viscous delay26. This emission is then partly reprocessed into the ultraviolet/optical part of the spectrum by an optically thick layer21. Super-Eddington accretion is treated by presuming that a fitted fraction of the Eddington excess is converted into light that is reprocessed by the same optically thick layer. This excess can be produced either with an unbound wind9, 37, or with the energy deposited by shocks in the circularization process13, 22. The software performs a maximum-likelihood analysis to determine the combinations of parameters that reproduce the observed light curves. We utilize the ASASSN, UVOT and XRT data in our light-curve fitting; the most likely models produce good fits to all bands simultaneously. Within the context of this TDE model, a black-hole mass of (0.4–1.2) × 106M (1σ) is derived. Table 1 lists the observation identification number, start time, and duration of all of the XMM-Newton and Chandra observations considered in our work. The XMM-Newton data were reduced using the standard Science Analysis System (SAS version 13.5.0) tools and the latest calibration files. The rgsproc routine was used to generate spectral files from the source, background spectral files, and instrument response files. The spectra from the RGS1 and RGS2 units were fitted jointly. Prior to fitting models, all XMM-Newton spectra were binned by a factor of five for clarity and sensitivity. The Chandra data were reduced using the standard Chandra Interactive Analysis of Observations (CIAO version 4.7) suite, and the latest associated calibration files. Instrument response files were constructed using the fullgarf and mkgrmf routines. The first-order spectra from each observation were combined using the tool add grating orders, and spectra from each observation were then added using add grating spectra. The spectra were analysed using the SPEX suite version 2.06 (ref. 20). The fitting procedure minimized a χ2 statistic. The spectra are most sensitive in the 18–35 Å band, and all fits were restricted to this range. Within SPEX, absorption from the interstellar medium in the Milky Way was modelled using the model ‘hot’; a separate ‘hot’ component was included to allow for interstellar medium (ISM) absorption within PGC 043234 at its known redshift (using the reds component in SPEX). The photoionized outflow was modelled using the pion component within the SPEX suite. pion20 includes numerous lines from intermediate charge states that are lacking in similar astrophysics packages. The fits explored in this analysis varied the gas column density (N ), the gas ionization parameter (ξ, where ξ = L/nr2, and L is luminosity, n is the hydrogen number density and r is the distance between the ionizing source and absorbing gas), the root-mean-square velocity of the gas (v ), and the bulk shift of the gas relative to the source, in the source frame (v ). Spectra from segments within the ‘long stare’ made with XMM-Newton were made by using the SAS tool tabgtigen to create good time interval files to isolate periods within the light curves of the RGS data. The Chandra/LETG spectra were dispersed onto the HRC, which has a relatively high instrumental background. Fitting the spectra only in the 18–35 Å band served to limit the contributions of the background. Nevertheless, the Chandra spectra are less sensitive than the best XMM-Newton spectra of ASASSN-14li (see Fig. 2). Prior to fitting, spectra from the two exposures were added and then binned by a factor of three. Figure 2 includes plots of the Δχ2 goodness-of-fit statistic as a function of wavelength, before and after including pion to model the ionized absorption. There is weak evidence of emission lines in the spectra, perhaps with a P Cygni profile (see below). The best-fit models for the high-resolution spectra predict one absorption line at 34.5 Å (H-like C vi) that is not observed; small variations to abundances could resolve this disparity. Blueshifts as small as 200 km s−1 are measured in the XMM-Newton/RGS using the pion model. According to the XMM-Newton User’s Handbook, available through the mission website, http://xmm.esac.esa.int/external/xmm_user_support/documentation/index.shtml, the absolute accuracy of the first-order wavelength scale is 6 mÅ. At 18 Å this corresponds to a velocity of 100 km s−1; at 35 Å, this corresponds to a velocity of 51 km s−1. The model predicts numerous lines across the 18–35 Å band that are clearly detected; especially with this leverage, the small shifts we have measured with XMM-Newton are robust. In particular, the difference in blueshift between the low- and high-flux phases of the ‘long stare’, −360 ± 50 km s−1 versus − −1, is greater than the absolute calibration uncertainties. Differences observed in the outflow velocities between XMM-Newton observations are as large, or larger, and also robust. The lower sensitivity of the Chandra spectra is evident in the relatively poor constraints achieved on the column density of the ionized X-ray outflow N (see Table 1). Similarly, the relatively high outflow velocity measured in the Chandra spectra should be viewed with a degree of caution. The outflow velocity changes from about 500 km s−1 to just −130 ± 130 km s−1, for instance, when the binning factor is increased from three to five. We have found no reports in the literature of a systematic wavelength offset between contemporaneous high-resolution spectra obtained with XMM-Newton and Chandra. The small number of high-resolution spectra complicates efforts to discern trends. The velocity width of the absorbing gas is fairly constant over time, but there is a general trend towards higher blue-shifts. There is no clear trend in column density or ionization parameter with time. There is no a priori constraint on the density of the absorbing gas. Taking the maximum radius implied by variability within XMM-Newton ‘long stare’, r ≤ 3 × 1015 cm, and manipulating the ionization parameter equation (ξ = Ln−1r−2, where L is the luminosity, n is the number density and r is the absorbing radius), we can derive an estimate of the density: n ≈ 2 × 109 cm−3. Even assuming a uniformly filled sphere out to a radius of r = 3 × 1015 cm, a total mass of M ≈ 4 × 1032 g is implied, or approximately 0.2M . The true gas mass within r is likely to be orders of magnitude lower, owing to clumping and a very low volume filling factor. Using the measured value of N and assuming n ≈ 2 × 109 cm−3, N = nΔr gives a value of Δr ≈ 6.5 × 1012 cm. The filling factor can be estimated using Δr/r ≈ 0.002. The total mass enclosed out to a distance r is then reduced accordingly, down to 4 × 10−4M , assuming a uniform density within r. This is a small value, plausible either for a clumpy wind or gas within a filament executing an elliptical orbit. Formally, the mass outflow rate in ASASSN-14li can be adapted from the case where the density is known, and written as: where µ is the mean atomic weight (µ = 1.23 is typical), m is the mass of the proton, Ω is the covering factor (0 ≤ Ω ≤ 4π), L is the ionizing luminosity, v is the outflow velocity, C is the line-of-sight global (volume) filling factor and ξ is the ionization parameter. Using the values obtained in fits to the XMM-Newton ‘long stare’ (see Table 1), for instance, Ω C g s−1.Taking the value of C derived above, an outflow rate of Ω g s−1 results. The kinetic power in the outflow is given by ; using the same values assumed to estimate the mass outflow rate, L ≈ 3.3 × 1035 erg s−1. We synthesized a plausible wind emission spectrum by coupling the pion and hyd models within SPEX. The hyd code enables spectra to be constructed based on the output of hydrodynamical simulations. As inputs, the hyd code requires the electron temperature and ion concentrations for a gas; these were taken from our fits with pion. We included the resulting emission component in experimental fits to the XMM-Newton ‘long stare’. The best-fit model gives an emission measure of (1.0 ± 0.3) × 1064 cm−3, a redshift (relative to the host) of km s−1, and an ionization parameter of logξ = 4.3 ± 0.1. According to an F-test, the emission component is only required at the 3σ level; however, it has some compelling properties. Combined with the blueshifted absorption spectrum, the redshifted emission gives P Cygni profiles. For the gas density of n ≈ 2 × 109 cm−3 derived previously, the emission measure gives a radius of about 1015 cm, comparable to the size scale inferred from absorption variability. The strongest lines predicted by the emission model include He-like O vii, and H-like charge states of C, N and O. This model does not account for other emission line-like features in the spectra, which are more likely to be artefacts from spectral binning, or calibration or modelling errors. Emission features in the O K-edge region may be real, but caution is warranted. Other features are more easily discounted given that they differ between the RGS1 and RGS2 spectra. All of the data reduction and spectroscopic fitting routines and packages used in this work are publicly available. The light-curve modelling package, TDEFit7, is proprietary at this time owing to ongoing code development; a public release is planned within the coming year.
News Article | November 24, 2015
Ducati Corse, the racing division of Italian motorcycle manufacturer Ducati, announced the return of Casey Stoner, a former two-time MotoGP world champion, under its banner. Stoner won his first MotoGP championship with Ducati Corse back in 2007. He then proceeded to take another in 2011 with Honda Racing Corporation (HRC), the racing technology development arm of the Honda Motor Company. Stoner retired a year after, in 2012, but decide once again to take the track this year. However, during the Suzuka 8 Hours, which is an annual endurance race held at the Suzuka Circuit in Japan, the 30-year-old Australian racer crashed his bike due to a throttle mechanical issue. HRC issued an official apology to Stoner. "A malfunction was discovered related to the throttle cable," writes HRC. "HRC would like to apologise to Casey Stoner and thank him for the effort he made in attending the Suzuka 8 Hour event." After noting of his great journey with the HRC, Stoner confirmed that he will once again be on a Ducati motorbike for 2016. "For 2016 I am very excited to announce that I will again be joining the Ducati team," Stoner comments on his return. "I have so many great memories working with the people and the brand of Ducati and the opportunity to work with them again is something very special." Note that Ducati has not won any championships after Stoner's win on a Ducati Desmosedici GP almost nine years ago. In total, Casey Stoner won 23 races for Ducati from 2007 until 2010. Given the racer's achievements, Ducati's CEO Claudio Domenicali spoke of his delight with Casey Stoner's return. "Stoner has always remained in the hearts of all the Ducatisti and I am really pleased that he has decided to come back to our family," Domenicali comments. "Casey has an extraordinary talent and with his experience he will be able to make an important contribution for Gigi and the two Andreas in the development of the Desmosedici MotoGP bike." Aside from becoming Ducati's brand ambassador, Casey Stoner is also scheduled to star on World Ducati Week's 2016 edition which will run from July 1 to July 3 next year. Moreover, Stoner will be part of several of the Ducati team's MotoGP tests also scheduled for 2016.