Semantic Image Segmentation via Deep Parsing Network

This paper addresses semantic image segmentation by incorporating rich information into Markov Random Field (MRF), including high-order relations and mixture of label contexts. Unlike previous works that optimized MRFs using iterative algorithm, we solve MRF by proposing a Convolutional Neural Network (CNN), namely Deep Parsing Network (DPN), which enables deterministic end-to-end computation in a single forward pass. Specifically, DPN extends a contemporary CNN architecture to model unary terms and additional layers are carefully devised to approximate the mean field algorithm (MF) for pairwise terms. It has several appealing properties. First, different from the recent works that combined CNN and MRF, where many iterations of MF were required for each training image during back-propagation, DPN is able to achieve high performance by approximating one iteration of MF. Second, DPN represents various types of pairwise terms, making many existing works as its special cases. Third, DPN makes MF easier to be parallelized and speeded up in Graphical Processing Unit (GPU). DPN is thoroughly evaluated on the PASCAL VOC 2012 dataset, where a single DPN model yields a new state-of-the-art segmentation accuracy.Comment: To appear in International Conference on Computer Vision (ICCV) 201

Deep Learning Markov Random Field for Semantic Segmentation

Semantic segmentation tasks can be well modeled by Markov Random Field (MRF). This paper addresses semantic segmentation by incorporating high-order relations and mixture of label contexts into MRF. Unlike previous works that optimized MRFs using iterative algorithm, we solve MRF by proposing a Convolutional Neural Network (CNN), namely Deep Parsing Network (DPN), which enables deterministic end-to-end computation in a single forward pass. Specifically, DPN extends a contemporary CNN to model unary terms and additional layers are devised to approximate the mean field (MF) algorithm for pairwise terms. It has several appealing properties. First, different from the recent works that required many iterations of MF during back-propagation, DPN is able to achieve high performance by approximating one iteration of MF. Second, DPN represents various types of pairwise terms, making many existing models as its special cases. Furthermore, pairwise terms in DPN provide a unified framework to encode rich contextual information in high-dimensional data, such as images and videos. Third, DPN makes MF easier to be parallelized and speeded up, thus enabling efficient inference. DPN is thoroughly evaluated on standard semantic image/video segmentation benchmarks, where a single DPN model yields state-of-the-art segmentation accuracies on PASCAL VOC 2012, Cityscapes dataset and CamVid dataset.Comment: To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017. Extended version of our previous ICCV 2015 paper (arXiv:1509.02634

Charm meson scattering cross sections by pion and rho meson

Using the local flavor SU(4) gauge invariance in the limit of vanishing vector meson masses, we extend our previous study of charm meson scattering cross sections by pion and rho meson, which is based only on the pseudoscalar-pseudoscalar-vector meson couplings, to include also contributions from the couplings among three vector mesons and among four particles. We find that diagrams with light meson exchanges usually dominate the cross sections. For the processes considered previously, the additional interactions lead only to diagrams involving charm meson exchanges and contact interactions, and the cross sections for these processes are thus not much affected. Nevertheless, these additional interactions introduce new processes with light meson exchanges and increase significantly the total scattering cross sections of charm mesons by pion and rho meson.Comment: 14 pages, revtex, 6 figures, added a figure on the effects of on-shell divergence, final version to appear in Nucl. Phys.

Re-evaluation of the carcinogenic significance of hepatitis B virus integration in hepatocarcinogenesis

To examine the role of hepatitis B virus (HBV) integration in hepatocarcinogenesis, a systematic comparative study of both tumor and their corresponding non-tumor derived tissue has been conducted in a cohort of 60 HBV associated hepatocellular carcinoma (HCC) patients. By using Alu-polymerase chain reaction (PCR) and ligation-mediated PCR, 233 viral-host junctions mapped across all human chromosomes at random, no difference between tumor and non-tumor tissue was observed, with the exception of fragile sites (P = 0.0070). HBV insertions in close proximity to cancer related genes such as hTERT were found in this study, however overall they were rare events. No direct correlation between chromosome aberrations and the number of HBV integration events was found using a sensitive array-based comparative genomic hybridization (aCGH) assay. However, a positive correlation was observed between the status of several tumor suppressor genes (TP53, RB1, CDNK2A and TP73) and the number of chromosome aberrations (r = 0.6625, P = 0.0003). Examination of the viral genome revealed that 43% of inserts were in the preC/C region and 57% were in the HBV X gene. Strikingly, approximately 24% of the integrations examined had a breakpoint in a short 15 nt viral genome region (1820-1834 nt). As a consequence, all of the confirmed X gene insertions were C-terminal truncated, losing their growth-suppressive domain. However, the same pattern of X gene C-terminal truncation was found in both tumor and non-tumor derived samples. Furthermore, the integrated viral sequences in both groups had a similar low frequency of C1653T, T1753V and A1762T/G1764A mutations. The frequency and patterns of HBV insertions were similar between tumor and their adjacent non-tumor samples indicating that the majority of HBV DNA integration events are not associated with hepatocarcinogenesis

Performance testing of a cross-flow membrane-based liquid desiccant dehumidification system

A membrane-based liquid desiccant dehumidification system is one of high energy efficient dehumidification approaches, which allows heat and moisture transfers between air stream and desiccant solution without carryover problem. The system performance is investigated experimentally with calcium chloride, and the impacts of main operating parameters on dehumidification effectiveness (i.e. sensible, latent and total effectiveness) are evaluated, which include dimensionless parameters (i.e. solution to air mass flow rate ratio m∗ and number of heat transfer units NTU) and solution properties (i.e. concentration Csol and inlet temperature Tsol,in). The sensible, latent and total effectiveness reach the maximum values of 0.49, 0.55, and 0.53 respectively at m∗= 3.5 and NTU = 12, and these effectiveness are not limited by m∗ and NTU when m∗ > 2 and NTU > 10. Both the latent and total effectiveness increase with Csol , while almost no variation is observed in the sensible effectiveness. All effectiveness can be improved by decreasing Tsol,in. The experimental data provide a full map of main design parameters for the membrane-based liquid desiccant air conditioning technology

Multi-Phase Transport Study of Relativistic Nuclear Collisions

A multi-phase transport model (AMPT) is developed for the study of hot and dense matter produced in relativistic nuclear collisions. This model includes both initial partonic and final hadronic scattering. Using the AMPT model, we study the momentum distributions of charged particles such as protons, antiprotons, pions, and kaons in central heavy ion collisions at Super Proton Synchrotron (SPS) and Relativistic Heavy Ion Collider (RHIC) energies. The results are consistent with experimental data at these energies. They indicate a significant nuclear shadowing but a relative weak jet quenching in the initial dense matter. Antiproton to proton ratio at mid-rapidity increases appreciably with energy, demonstrating the approach to a nearly baryon-anti-baryon symmetric matter in high energy collisions. Kaon to pion ratio is almost constant within the energy range studied here, providing strong evidence for strangeness equilibration in these reactions