Large-Scale Spectroscopic Mapping of the ρ\rho Ophiuchi Molecular Cloud Complex I. The C2_{2}H to N2_2H+^+ Ratio as a Signpost of Cloud Characteristics

We present 2.5-square-degree C$_{2}$H N=1-0 and N$_2$H$^+$ J=1-0 maps of the $\rho$ Ophiuchi molecular cloud complex. These are the first large-scale maps of the $\rho$ Ophiuchi molecular cloud complex with these two tracers. The C$_{2}$H emission is spatially more extended than the N$_2$H$^+$ emission. One faint N$_2$H$^+$ clump Oph-M and one C$_{2}$H ring Oph-RingSW are identified for the first time. The observed C$_{2}$H to N$_{2}$H$^{+}$ abundance ratio ([C$_{2}$H]/[N$_{2}$H$^{+}$]) varies between 5 and 110. We modeled the C$_{2}$H and N$_2$H$^+$ abundances with 1-D chemical models which show a clear decline of [C$_2$H]/[N$_2$H$^+$] with chemical age. Such an evolutionary trend is little affected by temperatures when they are below 40 K. At high density (n$_H$ $>$ 10$^5$ cm$^{-3}$), however, the time it takes for the abundance ratio to drop at least one order of magnitude becomes less than the dynamical time (e.g., turbulence crossing time $\rm \sim$10$^5$ years). The observed [C$_2$H]/[N$_2$H$^+$] difference between L1688 and L1689 can be explained by L1688 having chemically younger gas in relatively less dense regions. The observed [C$_{2}$H]/[N$_{2}$H$^{+}$] values are the results of time evolution, accelerated at higher densities. For the relative low density regions in L1688 where only C$_2$H emission was detected, the gas should be chemically younger.Comment: Accepted by ApJ, 45 pages, 10 figure

Signaling Network Assessment of Mutations and Copy Number Variations Predicts Breast Cancer Subtype-specific Drug Targets

Individual cancer cells carry a bewildering number of distinct genomic alterations i.e., copy number variations and mutations, making it a challenge to uncover genomic-driven mechanisms governing tumorigenesis. Here we performed exome-sequencing on several breast cancer cell lines which represent two subtypes, luminal and basal. We integrated this sequencing data, and functional RNAi screening data (i.e., for identifying genes which are essential for cell proliferation and survival), onto a human signaling network. Two subtype-specific networks were identified, which potentially represent core-signaling mechanisms underlying tumorigenesis. Within both networks, we found that genes were differentially affected in different cell lines; i.e., in some cell lines a gene was identified through RNAi screening whereas in others it was genomically altered. Interestingly, we found that highly connected network genes could be used to correctly classify breast tumors into subtypes based on genomic alterations. Further, the networks effectively predicted subtype-specific drug targets, which were experimentally validated.Comment: 4 figs, more related papers at http://www.cancer-systemsbiology.org, appears in Cell Reports, 201

Magnetic field control of the near-field radiative heat transfer in three-body planar systems

Recently, the application of an external magnetic field to actively control the near-field heat transfer has emerged as an appealing and promising technique. Existing studies have shown that an external static magnetic field tends to reduce the subwavelength radiative flux exchanged between two planar structures containing magneto-optical (MO) materials, but so far the nearfield thermomagnetic effects in systems with more such structures at different temperatures have not been reported. Here, we are focused on examining how the presence of an external magnetic field modifies the radiative energy transfer in a many-body configuration consisting of three MO n-doped semiconductors slabs, separated by subwavelength vacuum gaps. To exactly calculate the radiative flux transferred in such an anisotropic planar system, a general Green-function-based approach is offered, which allows one to investigate the radiative heat transfer in arbitrary manybody systems with planar geometry. We demonstrate that, under specific choices of the geometrical and thermal parameters, the applied magnetic field is able to either reduce or enhance the near-field energy transfer in three-element MO planar systems, depending on the interplay between the damped evanescent fields of the zero-field surface waves and the propagating hyperbolic modes induced by magnetic fields. Our study broadens the understanding concerning to the use of external fields to actively control the heat transfer in subwavelength regimes, and may be leveraged for potential applications in the realm of nanoscale thermal management.Comment: 18 pages, 7 figure

Deep Supervised Hashing using Symmetric Relative Entropy

By virtue of their simplicity and efficiency, hashing algorithms have achieved significant success on large-scale approximate nearest neighbor search. Recently, many deep neural network based hashing methods have been proposed to improve the search accuracy by simultaneously learning both the feature representation and the binary hash functions. Most deep hashing methods depend on supervised semantic label information for preserving the distance or similarity between local structures, which unfortunately ignores the global distribution of the learned hash codes. We propose a novel deep supervised hashing method that aims to minimize the information loss generated during the embedding process. Specifically, the information loss is measured by the Jensen-Shannon divergence to ensure that compact hash codes have a similar distribution with those from the original images. Experimental results show that our method outperforms current state-of-the-art approaches on two benchmark datasets