Accurate and Fast Compressed Video Captioning

Existing video captioning approaches typically require to first sample video frames from a decoded video and then conduct a subsequent process (e.g., feature extraction and/or captioning model learning). In this pipeline, manual frame sampling may ignore key information in videos and thus degrade performance. Additionally, redundant information in the sampled frames may result in low efficiency in the inference of video captioning. Addressing this, we study video captioning from a different perspective in compressed domain, which brings multi-fold advantages over the existing pipeline: 1) Compared to raw images from the decoded video, the compressed video, consisting of I-frames, motion vectors and residuals, is highly distinguishable, which allows us to leverage the entire video for learning without manual sampling through a specialized model design; 2) The captioning model is more efficient in inference as smaller and less redundant information is processed. We propose a simple yet effective end-to-end transformer in the compressed domain for video captioning that enables learning from the compressed video for captioning. We show that even with a simple design, our method can achieve state-of-the-art performance on different benchmarks while running almost 2x faster than existing approaches. Code is available at https://github.com/acherstyx/CoCap

A Hessenberg-type algorithm for computing PageRank Problems

PageRank is a widespread model for analysing the relative relevance of nodes within large graphs arising in several applications. In the current paper, we present a cost-effective Hessenberg-type method built upon the Hessenberg process for the solution of difficult PageRank problems. The new method is very competitive with other popular algorithms in this field, such as Arnoldi-type methods, especially when the damping factor is close to 1 and the dimension of the search subspace is large. The convergence and the complexity of the proposed algorithm are investigated. Numerical experiments are reported to show the efficiency of the new solver for practical PageRank computations

Off-diagonal low-rank preconditioner for difficult PageRank problems

PageRank problem is the cornerstone of Google search engine and is usually stated as solving a huge linear system. Moreover, when the damping factor approaches 1, the spectrum properties of this system deteriorate rapidly and this system becomes difficult to solve. In this paper, we demonstrate that the coefficient matrix of this system can be transferred into a block form by partitioning its rows into special sets. In particular, the off-diagonal part of the block coefficient matrix can be compressed by a simple low-rank factorization, which can be beneficial for solving the PageRank problem. Hence, a matrix partition method is proposed to discover the special sets of rows for supporting the low rank factorization. Then a preconditioner based on the low-rank factorization is proposed for solving difficult PageRank problems. Numerical experiments are presented to support the discussions and to illustrate the effectiveness of the proposed methods. (C) 2018 Elsevier B.V. All rights reserved

Role played by port drains in a Maxwell fisheye lens

Maxwell fisheye lens was proposed to pinpoint super-resolution with the addition of wave drain and the interaction of multiple drains is theoretically predicted to improve subwavelength resolution further. In this paper we discuss the role played by port drains in optical absolute instruments, and verify by full-wave simulation that coupling nature for wave source and drain applies correctly in the picture of scanning imaging for absolute instrument. This work prospects for scanning near fields shaped from far-field wave propagation.Comment: to be submitted to JOSA

Origin of Immediate Damping of Coherent Oscillations in Photoinduced Charge Density Wave Transition

In stark contrast to the conventional charge density wave (CDW) materials, the one-dimensional CDW on the In/Si(111) surface exhibits immediate damping of the CDW oscillation during the photoinduced phase transition. Here, by successfully reproducing the experimentally observed photoinduced CDW transition on the In/Si(111) surface by performing real-time time-dependent density functional theory (rt-TDDFT) simulations, we demonstrate that photoexcitation promotes valence electrons from Si substrate to empty surface bands composed primarily of the covalent p-p bonding states of the long In-In bonds, generating interatomic forces to shorten the long bonds and in turn drives coherently the structural transition. We illustrate that after the structural transition, the component of these surface bands occurs a switch among different covalent In bonds, causing a rotation of the interatomic forces by about {\pi}/6 and thus quickly damping the oscillations in feature CDW modes. These findings provide a deeper understanding of photoinduced phase transitions.Comment: 11 pages,3 figure

A genetic variant in large tumor suppressor kinase 2 of Hippo signaling pathway contributes to prognosis of hepatocellular carcinoma

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Home enteral nutrition for patients with esophageal cancer undergoing esophagectomy: A systematic review and meta-analysis

IntroductionHome enteral nutrition (HEN) is a relatively new nutritional intervention that provides patients with EN support at home through jejunostomy or nasogastric feeding tubes. We conducted this systematic review and meta-analysis to explore the safety and effect of HEN compared with normal oral diet (NOD) in postoperative patients with esophageal cancer (EC).MethodsEMBASE, Medline, Web of Science, and the Cochrane Library were used to search articles in English-language journals. The intervention effect was expressed using risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcome measures, with 95% confidence intervals (95% CIs). The chi-square test and I-square test were used to test heterogeneity among studies.ResultsFour studies were eventually included in this meta-analysis. Compared with NOD, HEN has a favorable impact on postoperative body mass index (BMI) (weighted mean difference [WMD] = 0.70, 95% CI: 0.09–1.30, P = 0.02), lean body mass (LBM) (WMD = 0.76, 95% CI: 0.04–1.48, P = 0.04), and appendicular skeletal muscle mass index (ASMI) (WMD = 0.30, 95% CI: 0.02–0.58, P = 0.03). Physical function (WMD = 9.26, 95% CI: 8.00–10.53, P < 0.001), role function (WMD = 9.96, 95% CI: 8.11–11.82, P < 0.001), and social function (WMD = 8.51, 95% CI: 3.48–13.54, P = 0.001) of the HEN group were better than those of the NOD group at 3 months, and HEN could reduce the fatigue of patients (WMD = −12.73, 95% CI: −14.8 to −10.66, P < 0.001) and the incidence of postoperative pneumonia (RR = 0.53, 95% CI: 0.34–0.81, P = 0.004). There was no significant difference in albumin between HEN and NOD groups (WMD = 0.05, 95% CI: −0.03 to 0.13, P = 0.20).ConclusionHEN improved nutritional status and quality of life (QOL) in postoperative patients with EC and reduced fatigue and the incidence of postoperative pneumonia. All in all, the results of our meta-analysis support the use of HEN after esophagectomy