3,189 research outputs found
Hunting for Extremely Faint Planetary Nebulae in the SDSS Spectroscopic Database
Using ~1,700,000 target- and sky-fiber spectra from the SDSS, we have carried
out a systematic search for Galactic planetary nebulae (PNe) via detections of
the [OIII] 4959, 5007 lines. Thanks to the excellent sensitivity of the SDSS
spectroscopic surveys, this is by far the deepest search for PNe ever taken,
reaching a surface brightness of the [OIII] 5007 line down to about 29.0
mag./arcsec^2. The search recovers 13 previously known PNe in the Galactic
Caps. In total, 44 new PN candidates are identified, including 7 candidates of
multiple detections and 37 candidates of single detection. The 7 candidates of
multiple detections are all extremely large (between 21' - 154') and faint,
located mostly in the low Galactic latitude region and with a kinematics
similar to disk stars. After checking their images in Ha and other bands, three
of them are probably HII regions, one is probably associated with a new
supernova remnant, another one is possibly a true PN, and the remaining two
could be either PNe or supernova remnants. Based on sky positions and
kinematics, 7 candidates of single detection probably belong to the halo
population. If confirmed, they will increase the number of known PNe in the
Galactic halo significantly. All the newly identified PN candidates are very
faint, with a surface brightness of the [OIII] 5007 line between 27.0 - 30.0
mag./arcsec^2, very challenging to be discovered with previous techniques and
thus may greatly increase the number of "missing" faint PNe. Our results
demonstrate the power of large scale fiber spectroscopy in hunting for
ultra-faint PNe and other types of emission line nebulae. Combining the large
spectral databases provided by the SDSS and other on-going projects (e.g. the
LAMOST Galactic surveys), it is possible to build a statistically meaningful
sample of ultra-faint, large, evolved PNe, thus improving the census of
Galactic PNe.Comment: 23 pages, 1 table and 16 figures. MNRAS accepted. High resolution
version and online-only material may be found at
http://kiaa.pku.edu.cn/DSSGAC/YL13_pne_sdss.pd
Network Utility Maximization under Maximum Delay Constraints and Throughput Requirements
We consider the problem of maximizing aggregate user utilities over a
multi-hop network, subject to link capacity constraints, maximum end-to-end
delay constraints, and user throughput requirements. A user's utility is a
concave function of the achieved throughput or the experienced maximum delay.
The problem is important for supporting real-time multimedia traffic, and is
uniquely challenging due to the need of simultaneously considering maximum
delay constraints and throughput requirements. We first show that it is
NP-complete either (i) to construct a feasible solution strictly meeting all
constraints, or (ii) to obtain an optimal solution after we relax maximum delay
constraints or throughput requirements up to constant ratios. We then develop a
polynomial-time approximation algorithm named PASS. The design of PASS
leverages a novel understanding between non-convex maximum-delay-aware problems
and their convex average-delay-aware counterparts, which can be of independent
interest and suggest a new avenue for solving maximum-delay-aware network
optimization problems. Under realistic conditions, PASS achieves constant or
problem-dependent approximation ratios, at the cost of violating maximum delay
constraints or throughput requirements by up to constant or problem-dependent
ratios. PASS is practically useful since the conditions for PASS are satisfied
in many popular application scenarios. We empirically evaluate PASS using
extensive simulations of supporting video-conferencing traffic across Amazon
EC2 datacenters. Compared to existing algorithms and a conceivable baseline,
PASS obtains up to improvement of utilities, by meeting the throughput
requirements but relaxing the maximum delay constraints that are acceptable for
practical video conferencing applications
Swine blood transcriptomics: Application and advancement
Improving swine feed efficiency (FE) by selection for low residual feed intake (RFI) is of practical interest. However, whether selection for low RFI compromises a pig’s immune response is not clear. In addition, current RFI-based selection for improving feed efficiency was expensive and time-consuming. Seeking alternative tools to facilitate selection, such as predictive biomarkers for RFI, is of great interest. The objectives of this thesis are as follows: (1) to investigate whether selection for low RFI compromise a pig’s immune response; (2) to develop candidate biomarkers applicable at early growth stage for predicting RFI at late growth stage; (3) to improve the annotation of the porcine blood transcriptome.
In Chapter 2, pigs of two lines divergently selected for RFI were injected with lipopolysaccharide (LPS). Transcriptomes of peripheral blood at baseline and multi-time points post injection were profiled by RNA-seq. LPS injection induced systemic inflammatory response in both RFI lines. However, no significant differences were detected in dynamics of body temperature, blood cell count and cytokine levels during the time course. Only a very small number of differentially expressed genes (DEGs) were detected between the lines over all time points, though ~ 50% of blood genes were differentially expressed post LPS injection compared to baseline for each line. The two lines were largely similar in most biological pathways and processes studied. Minor differences included a slightly lower level of inflammatory response in the low- versus high-RFI animals. Cross-species comparison showed that humans and pigs responded to LPS stimulation similarly at both the gene and pathway levels, though pigs are more tolerant to LPS than humans.
In Chapter 3, post-weaning blood transcriptomic differences between the two lines were studied by RNA-seq. DEGs between the lines significantly overlapped gene sets associated with human diseases, such as eating disorders, hyperphagia and mitochondrial disease. Genes functioning in the mitochondrion and proteasome, and signaling had lower and higher expression in the low-RFI group relative to the high-RFI group, respectively. Expression levels of five differentially expressed genes between the two groups were significantly associated with individual animal’s RFI values. These five genes were candidate biomarkers for predicting RFI.
Given limitations of current annotation of the porcine reference genome, a high-quality annotated transcriptome of porcine peripheral blood was built in the last study via a hybrid assembly strategy with a large amount of blood RNA-seq data from studies mentioned above and public databases.
Taken together, this work provides evidence that selection for low RFI did not significantly compromise pigs’ immune response to systemic inflammation, offers a few candidate biomarkers for predicting RFI to facilitate RFI-based selection, and significantly advances the structural and functional annotation of porcine blood transcriptome
Experimental Investigation of the Vibro-impact Capsule System
Dr. Yang Liu would like to acknowledge the financial support for the Small Research Grant (31841) by the Carnegie Trust for the Universities of Scotland. This work is also partially supported by the National Natural Science Foundation of China (Grant Nos. 11672257 and 11402224), the Natural Science Foundation of Jiangsu Province of China (Grant No. BK20161314).Peer reviewedPublisher PD
On the Min-Max-Delay Problem: NP-completeness, Algorithm, and Integrality Gap
We study a delay-sensitive information flow problem where a source streams
information to a sink over a directed graph G(V,E) at a fixed rate R possibly
using multiple paths to minimize the maximum end-to-end delay, denoted as the
Min-Max-Delay problem. Transmission over an edge incurs a constant delay within
the capacity. We prove that Min-Max-Delay is weakly NP-complete, and
demonstrate that it becomes strongly NP-complete if we require integer flow
solution. We propose an optimal pseudo-polynomial time algorithm for
Min-Max-Delay, with time complexity O(\log (Nd_{\max}) (N^5d_{\max}^{2.5})(\log
R+N^2d_{\max}\log(N^2d_{\max}))), where N = \max\{|V|,|E|\} and d_{\max} is the
maximum edge delay. Besides, we show that the integrality gap, which is defined
as the ratio of the maximum delay of an optimal integer flow to the maximum
delay of an optimal fractional flow, could be arbitrarily large
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