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 $100\%$ 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