Molecular environments of 51 Planck cold clumps in Orion complex

A mapping survey towards 51 Planck cold clumps projected on Orion complex was performed with J=1-0 lines of $^{12}$CO and $^{13}$CO at the 13.7 m telescope of Purple Mountain Observatory. The mean column densities of the Planck gas clumps range from 0.5 to 9.5$\times10^{21}$ cm$^{-2}$, with an average value of (2.9$\pm$1.9)$\times10^{21}$ cm$^{-2}$. While the mean excitation temperatures of these clumps range from 7.4 to 21.1 K, with an average value of 12.1$\pm$3.0 K. The averaged three-dimensional velocity dispersion $\sigma_{3D}$ in these molecular clumps is 0.66$\pm$0.24 km s$^{-1}$. Most of the clumps have $\sigma_{NT}$ larger than or comparable with $\sigma_{Therm}$. The H$_{2}$ column density of the molecular clumps calculated from molecular lines correlates with the aperture flux at 857 GHz of the dust emission. Through analyzing the distributions of the physical parameters, we suggest turbulent flows can shape the clump structure and dominate their density distribution in large scale, but not affect in small scale due to the local fluctuations. Eighty two dense cores are identified in the molecular clumps. The dense cores have an averaged radius and LTE mass of 0.34$\pm$0.14 pc and 38$_{-30}^{+5}$ M_{\sun}, respectively. And structures of low column density cores are more affected by turbulence, while those of high column density cores are more concerned by other factors, especially by gravity. The correlation of the velocity dispersion versus core size is very weak for the dense cores. The dense cores are found most likely gravitationally bounded rather than pressure confined. The relationship between $M_{vir}$ and $M_{LTE}$ can be well fitted with a power law. The core mass function here is much more flatten than the stellar initial mass function. The lognormal behavior of the core mass distribution is most likely determined by the internal turbulence.Comment: Accepted to The Astrophysical Journal Supplement Series (ApJS

Uniform Infall toward the Cometary H II Region in the G34.26+0.15 Complex?

Gas accretion is a key process in star formation. However, the gas infall detections in high-mass star forming regions with high-spatial resolution observations are rare. Here we report the detection of gas infall towards a cometary ultracompact H{\sc ii} region "C" in G34.26+0.15 complex. The hot core associated with "C" has a mass of $\sim$76 M_{\sun} and a volume density of 1.1$\times10^{8}$ cm$^{-3}$. The HCN (3--2), HCO$^{+}$ (1--0) lines observed by single-dishes and the CN (2--1) lines observed by the SMA show redshifted absorption features, indicating gas infall. We found a linear relationship between the line width and optical depth of the CN (2--1) lines. Those transitions with larger optical depth and line width have larger absorption area. However, the infall velocities measured from different lines seem to be constant, indicating the gas infall is uniform. We also investigated the evolution of gas infall in high-mass star forming regions. At stages prior to hot core phase, the typical infall velocity and mass infall rate are $\sim$ 1 km s$^{-1}$ and $\sim10^{-4}$ M_{\sun}\cdotyr$^{-1}$, respectively. While in more evolved regions, the infall velocity and mass infall rates can reach as high as serval km s$^{-1}$ and $\sim10^{-3}-10^{-2}$ M_{\sun}\cdotyr$^{-1}$, respectively. Accelerated infall has been detected towards some hypercompact H{\sc ii} and ultracompact H{\sc ii} regions. However, the acceleration phenomenon becomes inapparent in more evolved ultracompact H{\sc ii} regions (e.g. G34.26+0.15)

Molecular gas and triggered star formation surrounding Wolf-Rayet stars

The environments surrounding nine Wolf-Rayet stars were studied in molecular emission. Expanding shells were detected surrounding these WR stars (see left panels of Figure 1). The average masses and radii of the molecular cores surrounding these WR stars anti-correlate with the WR stellar wind velocities (middle panels of Figure 1), indicating the WR stars has great impact on their environments. The number density of Young Stellar Objects (YSOs) is enhanced in the molecular shells at $\sim$5 arcmin from the central WR star (lower-right panel of Figure 1). Through detailed studies of the molecular shells and YSOs, we find strong evidences of triggered star formation in the fragmented molecular shells (\cite[Liu et al. 2010]{liu_etal12}Comment: 1 page, IAUS29

Competitive accretion in the protocluster G10.6-0.4?

We present the results of high spatial resolution observations at 1.1 mm waveband, with the Submillimetre Array (SMA), towards the protocluster G10.6-0.4. The 1.1 mm continuum emission reveals seven dense cores, towards which infall motions are all detected with the red-shifted absorption dips in HCN (3--2) line. This is the first time that infall is seen towards multiple sources in a protocluster. We also identified four infrared point sources in this region, which are most likely Class 0/I protostars. Two jet-like structures are also identified from Spitzer/IRAC image. The dense core located in the centre has much larger mass than the off-centre cores. The clump is in overall collapse and the infall motion is supersonic. The standard deviation of core velocities and the velocity differences between the cores and the cloud/clump are all larger than the thermal velocity dispersion. The picture of G10.6-0.4 seems to favor the "competitive accretion" model but needs to be tested by further observations.Comment: 9 pages, 9 figures, 2 tables, Submitted to MNRA

A new approach to the solution of Maxwell's equations for low frequency and high-resolution biomedical problems

High spatial resolution studies of the interaction of the human body with electromagnetic waves of low frequency presents a difficult computational problem. As these studies typically require at least $10^4$ points per wavelength, a huge number of time steps would be needed to be able to use the finite difference time domain method (FDTD). In this paper, a new technique is described, which allows the FDTD method to be efficiently applied over a very large frequency range, including low frequencies. In the method, no alterations to the properties of either the source or the transmission media are required. The method is essentially frequency independent and has been verified against analytical solutions within the frequency range 50 Hertz to 1 Gigahertz. As an example of the lower frequency range, the method has been applied to the simulation of electromagnetic field behavior in the human body exposed to the pulsed magnetic field gradients of a magnetic resonance image (MRI) system

The telosome/shelterin complex and its functions

The telosome/shelterin protein complex bound to telomeres is essential for maintenance of telomere structure and telomere signaling functions

A simulation data-driven design approach for rapid product optimization

Traditional design optimization is an iterative process of design, simulation, and redesign, which requires extensive calculations and analysis. The designer needs to adjust and evaluate the design parameters manually and continually based on the simulation results until a satisfactory design is obtained. However, the expensive computational costs and large resource consumption of complex products hinder the wide application of simulation in industry. It is not an easy task to search the optimal design solution intelligently and efficiently. Therefore, a simulation data-driven design approach which combines dynamic simulation data mining and design optimization is proposed to achieve this purpose in this study. The dynamic simulation data mining algorithm—on-line sequential extreme learning machine with adaptive weights (WadaptiveOS-ELM)—is adopted to train the dynamic prediction model to effectively evaluate the merits of new design solutions in the optimization process. Meanwhile, the prediction model is updated incrementally by combining new “good” data set to reduce the modeling cost and improve the prediction accuracy. Furthermore, the improved heuristic optimization algorithm—adaptive and weighted center particle swarm optimization (AWCPSO)—is introduced to guide the design change direction intelligently to improve the search efficiency. In this way, the optimal design solution can be searched automatically with less actual simulation iterations and higher optimization efficiency, and thus supporting the rapid product optimization effectively. The experimental results demonstrate the feasibility and effectiveness of the proposed approach