Research of the active reflector antenna using laser angle metrology system

Active reflector is one of the key technologies for constructing large telescopes, especially for the millimeter/sub-millimeter radio telescopes. This article introduces a new efficient laser angle metrology system for the active reflector antenna of the large radio telescopes, with a plenty of active reflector experiments mainly about the detecting precisions and the maintaining of the surface shape in real time, on the 65-meter radio telescope prototype constructed by Nanjing Institute of Astronomical Optics and Technology (NIAOT). The test results indicate that the accuracy of the surface shape segmenting and maintaining is up to micron dimension, and the time-response can be of the order of minutes. Therefore, it is proved to be workable for the sub-millimeter radio telescopes.Comment: 10 pages, 15 figure

Towards Understanding Astrophysical Effects of Nuclear Symmetry Energy

Determining the Equation of State (EOS) of dense neutron-rich nuclear matter is a shared goal of both nuclear physics and astrophysics. Except possible phase transitions, the density dependence of nuclear symmetry \esym is the most uncertain part of the EOS of neutron-rich nucleonic matter especially at supra-saturation densities. Much progresses have been made in recent years in predicting the symmetry energy and understanding why it is still very uncertain using various microscopic nuclear many-body theories and phenomenological models. Simultaneously, significant progresses have also been made in probing the symmetry energy in both terrestrial nuclear laboratories and astrophysical observatories. In light of the GW170817 event as well as ongoing or planned nuclear experiments and astrophysical observations probing the EOS of dense neutron-rich matter, we review recent progresses and identify new challenges to the best knowledge we have on several selected topics critical for understanding astrophysical effects of the nuclear symmetry energy.Comment: 77 pages. Invited Review Article, EPJA (2019) in pres

Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

Histological staining is a vital step used to diagnose various diseases and has been used for more than a century to provide contrast to tissue sections, rendering the tissue constituents visible for microscopic analysis by medical experts. However, this process is time-consuming, labor-intensive, expensive and destructive to the specimen. Recently, the ability to virtually-stain unlabeled tissue sections, entirely avoiding the histochemical staining step, has been demonstrated using tissue-stain specific deep neural networks. Here, we present a new deep learning-based framework which generates virtually-stained images using label-free tissue, where different stains are merged following a micro-structure map defined by the user. This approach uses a single deep neural network that receives two different sources of information at its input: (1) autofluorescence images of the label-free tissue sample, and (2) a digital staining matrix which represents the desired microscopic map of different stains to be virtually generated at the same tissue section. This digital staining matrix is also used to virtually blend existing stains, digitally synthesizing new histological stains. We trained and blindly tested this virtual-staining network using unlabeled kidney tissue sections to generate micro-structured combinations of Hematoxylin and Eosin (H&E), Jones silver stain, and Masson's Trichrome stain. Using a single network, this approach multiplexes virtual staining of label-free tissue with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created on the same tissue cross-section, which is currently not feasible with standard histochemical staining methods.Comment: 19 pages, 5 figures, 2 table

Metabolic profile, bioavailability and toxicokinetics of zearalenone-14-glucoside in rats after oral and intravenous administration by liquid chromatography high-resolution mass spectrometry and tandem mass spectrometry

Zearalenone-14-glucoside (ZEN-14G), a key modified mycotoxin, has attracted a great deal of attention due to the possible conversion to its free form of zearalenone (ZEN) exerting toxicity. In this study, the toxicokinetics of ZEN-14G were investigated in rats after oral and intravenous administration. The plasma concentrations of ZEN-14G and its major five metabolites were quantified using a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. The data were analyzed via non-compartmental analysis using software WinNonlin 6.3. The results indicated that ZEN-14G was rapidly hydrolyzed into ZEN in vivo. In addition, the major parameters of ZEN-14G following intravenous administration were: area under the plasma concentration-time curve (AUC), 1.80 h.ng/mL; the apparent volume of distribution (V-Z), 7.25 L/kg; and total body clearance (CL), 5.02 mL/h/kg, respectively. After oral administration, the typical parameters were: AUC, 0.16 h.ng/mL; V-Z, 6.24 mL/kg; and CL, 4.50 mL/h/kg, respectively. The absolute oral bioavailability of ZEN-14G in rats was about 9%, since low levels of ZEN-14G were detected in plasma, which might be attributed to its extensive metabolism. Therefore, liquid chromatography high-resolution mass spectrometry (LC-HRMS) was adopted to clarify the metabolic profile of ZEN-14G in rats' plasma. As a result, eight metabolites were identified in which ZEN-14-glucuronic acid (ZEN-14GlcA) had a large yield from the first time-point and continued accumulating after oral administration, indicating that ZEN-14-glucuronic acid could serve a potential biomarker of ZEN-14G. The obtained outcomes would prompt the accurate safety evaluation of ZEN-14G