Envelope Expansion with Core Collapse. III. Similarity Isothermal Shocks in a Magnetofluid

We explore MHD solutions for envelope expansions with core collapse (EECC) with isothermal MHD shocks in a quasi-spherical symmetry and outline potential astrophysical applications of such magnetized shock flows. MHD shock solutions are classified into three classes according to the downstream characteristics near the core. Class I solutions are those characterized by free-fall collapses towards the core downstream of an MHD shock, while Class II solutions are those characterized by Larson-Penston (LP) type near the core downstream of an MHD shock. Class III solutions are novel, sharing both features of Class I and II solutions with the presence of a sufficiently strong magnetic field as a prerequisite. Various MHD processes may occur within the regime of these isothermal MHD shock similarity solutions, such as sub-magnetosonic oscillations, free-fall core collapses, radial contractions and expansions. We can also construct families of twin MHD shock solutions as well as an `isothermal MHD shock' separating two magnetofluid regions of two different yet constant temperatures. The versatile behaviours of such MHD shock solutions may be utilized to model a wide range of astrophysical problems, including star formation in magnetized molecular clouds, MHD link between the asymptotic giant branch phase to the proto-planetary nebula phase with a hot central magnetized white dwarf, relativistic MHD pulsar winds in supernova remnants, radio afterglows of soft gamma-ray repeaters and so forth.Comment: 21 pages, 33 figures, accepted by MNRA

Effects of continuous LED lighting on reducing nitrate content and enhancing edible quality of lettuce during pre-harvest stage

Lettuce easily accumulates higher nitrate content during production, especially in hydroponic system, and higher ni trate content poses a threat to human health. Light condition (light quality, intensity and duration) significantly affects nitrate content in plants. Lighting -emitting diodes (LEDs) have showed the great potential for plant growth and development with the higher luminous efficiency and positive impact compared with other artificial light. The effects of combination of red (R)/ blue (B) or/and green (G), and white (W) LED lights on the plant growth, plant physiological 8th 45 International Symposium on Light in Horticulture changes, including chlorophyll fluorescence, nitrate contents and phytochemical concentration before harvest were investigated. The results showed that Pre-harvest continuous light exposure can effectively reduce nitrate accumulation and increase phytochemical concentrations in lettuce plants, and the reduction in nitrate content is dependent on the spectral composition and light intensity of the applied light sources and continuous light duration. Lettuce plants grown under the continuous combined red, green and blue LED light (RGB) with a PPFD at 200 μmol·m-2·s -(RGB-200) and RB-200 treatments exhibited a remarkable decrease of nitrate contents at 24 h compared to other LED light treatments. Moreover, continuous LED light at 24 h significantly enhanced the DPPH free-radical scavenging activity and increase phenolic compound concentrations. In this study, we suggest that a period of continuous LED light (RGB-200 or RB -200) exposure is needed in order to decrease nitrate concentrations and enhance lettuce quality. The period of 24 h continuous LED light exposure appears to be the best, and this period should not exceed 48 h

Ultrasonic-assisted extraction and evaluation of biological activities of flavonoids from Flemingia philippinensis Merr et Rolfe

Purpose: To develop a simple and rapid method for extracting total flavonoids from the roots of Flemingia philippinensis and to investigate the antioxidant and anti-tumor activities of the extracts of the materials from various locations in China.Methods: The total flavonoids in F. philippinensis were obtained by ultrasonic-assisted conventional solvent extraction method, and the extraction conditions were optimized by single factor and orthogonal test. 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging and anti-tumor activities, using 3-(4,5- dimethylthiazol-2-yl)- 2,5-diphenyltetrazolium bromide (MTT) assay, of the extract were evaluated. The contents of flemiphilippinin A, auriculasin, 5,7,3',4'-tetrahydroxy-6,8 –diprenylisoflavone and dorsmanins I were also determined.Results: Optimal extraction conditions were as follows: extraction time, 40 min; methanol concentration, 85 %; and solvent to solid ratio, 40 mL/g; and number of extraction, once. Total flavonoid content varied greatly (3.7 - 14.35 %) among the 19 samples collected from different origins in China. Flemiphilippin A, 5,7,3',4'- tetrahydroxy-6,8 -diprenylisoflavone, auriculasin and dorsmanins I showed varying DPPH radical scavenging activities with effective half maximal concentration (EC50) of 18.36, 23.59, 57.25 and 63.54 μg/mL, respectively.  Flemiphilippinin A (5 μg/mL) also exhibited some level of antitumor activity against human hepatocellular carcinoma cell (BEL-7402), human lung epithelial (A-549) and human ileocecal adenocarcinoma cell (HCT-8) with inhibition of 91.13 ± 1.6, 91.22 ± 3.23, and 79.77 ± 3.57 %, respectively.Conclusion: Total flavonoids can be extracted efficiently from F.  philippinensis by ultrasonic-assisted extraction method. Flemiphilippinin A has a potential for use in medicine as an antioxidant and antitumor drug

Conditional Graphical Lasso for Multi-label Image Classification

© 2016 IEEE. Multi-label image classification aims to predict multiple labels for a single image which contains diverse content. By utilizing label correlations, various techniques have been developed to improve classification performance. However, current existing methods either neglect image features when exploiting label correlations or lack the ability to learn image-dependent conditional label structures. In this paper, we develop conditional graphical Lasso (CGL) to handle these challenges. CGL provides a unified Bayesian framework for structure and parameter learning conditioned on image features. We formulate the multi-label prediction as CGL inference problem, which is solved by a mean field variational approach. Meanwhile, CGL learning is efficient due to a tailored proximal gradient procedure by applying the maximum a posterior (MAP) methodology. CGL performs competitively for multi-label image classification on benchmark datasets MULAN scene, PASCAL VOC 2007 and PASCAL VOC 2012, compared with the state-of-the-art multi-label classification algorithms