Expander Chunked Codes

Chunked codes are efficient random linear network coding (RLNC) schemes with low computational cost, where the input packets are encoded into small chunks (i.e., subsets of the coded packets). During the network transmission, RLNC is performed within each chunk. In this paper, we first introduce a simple transfer matrix model to characterize the transmission of chunks, and derive some basic properties of the model to facilitate the performance analysis. We then focus on the design of overlapped chunked codes, a class of chunked codes whose chunks are non-disjoint subsets of input packets, which are of special interest since they can be encoded with negligible computational cost and in a causal fashion. We propose expander chunked (EC) codes, the first class of overlapped chunked codes that have an analyzable performance,where the construction of the chunks makes use of regular graphs. Numerical and simulation results show that in some practical settings, EC codes can achieve rates within 91 to 97 percent of the optimum and outperform the state-of-the-art overlapped chunked codes significantly.Comment: 26 pages, 3 figures, submitted for journal publicatio

Synthesis Methods and Crystallization of MOFs

Metal-organic frameworks (MOFs) are a class of porous crystalline materials constructed of metal centres with organic linkers, creating one-, two-, or three-dimensional well-organized frameworks with very high surface areas. The study of MOFs has become one of the research hot spots in many fields, owing to the broad potential applications projected for these materials in various areas. It is well recognized that synthesis strategies dictate the structure and thus the properties and performance of the resulted MOFs. This chapter provides a comprehensive up-to-date overview on the modulated synthesis strategies for MOFs. The ability to control crystal morphology and size by a number of modulated synthesis methods is illustrated by the zirconium-terephthalate-based MOF, the UiO-66, and a number of other MOFs

ReSee: Responding through Seeing Fine-grained Visual Knowledge in Open-domain Dialogue

Incorporating visual knowledge into text-only dialogue systems has become a potential direction to imitate the way humans think, imagine, and communicate. However, existing multimodal dialogue systems are either confined by the scale and quality of available datasets or the coarse concept of visual knowledge. To address these issues, we provide a new paradigm of constructing multimodal dialogues as well as two datasets extended from text-only dialogues under such paradigm (ReSee-WoW, ReSee-DD). We propose to explicitly split the visual knowledge into finer granularity (``turn-level'' and ``entity-level''). To further boost the accuracy and diversity of augmented visual information, we retrieve them from the Internet or a large image dataset. To demonstrate the superiority and universality of the provided visual knowledge, we propose a simple but effective framework ReSee to add visual representation into vanilla dialogue models by modality concatenations. We also conduct extensive experiments and ablations w.r.t. different model configurations and visual knowledge settings. Empirical, encouraging results not only demonstrate the effectiveness of introducing visual knowledge at both entity and turn level but also verify the proposed model ReSee outperforms several state-of-the-art methods on automatic and human evaluations. By leveraging text and vision knowledge, ReSee can produce informative responses with real-world visual concepts.Comment: 15 pages, preprin

Non-Oscillatory Pattern Learning for Non-Stationary Signals

This paper proposes a novel non-oscillatory pattern (NOP) learning scheme for several oscillatory data analysis problems including signal decomposition, super-resolution, and signal sub-sampling. To the best of our knowledge, the proposed NOP is the first algorithm for these problems with fully non-stationary oscillatory data with close and crossover frequencies, and general oscillatory patterns. NOP is capable of handling complicated situations while existing algorithms fail; even in simple cases, e.g., stationary cases with trigonometric patterns, numerical examples show that NOP admits competitive or better performance in terms of accuracy and robustness than several state-of-the-art algorithms

5 Fluorouracil as firs t line treatment for low risk gestational trophoblastic neoplasia

Purpose: To investigate the efficacy and prognostic factors in response to 5-fluorouracil (5-FU) in lowrisk gestational trophoblastic neoplasia (GTN).Methods: This single-center retrospective study analyzed the hospital records of 204 LRGTN patients admitted to Department of Gynecology, Liaoning Cancer Hospital & Institute of China from 2002 to 2016 for retrieval of their clinical data, chemotherapy regimens, related side-effects, and evaluation of treatment efficacy and prognostic factors.Results: The median progression-free survival (PFS) was 55 months (3 - 190 months). The overall cure rate was 100 %, with no tumor-related deaths. When a single-agent regimen i.e. 5-FU, was selected for initiation of treatment for 132 patients while only 49 of them were treated with chemotherapy, the effective cure rate was 62.88 % (83/132); while the overall drug resistance r was 27.27 % (36/132). For patients with FIGO scores ≥ 4 points, the incidence of drug resistance was 71.43 % (5/7), while the incidence of III/IV myelosuppression was 10.61 % (14/132). A total of 38 patients (18.63 %) received surgical treatment in addition to chemotherapy. A comparison was made between two groups of patients with non-drug resistance, i.e., patients with unexpected GTN diagnosed postoperatively and those who received chemotherapy preoperatively. It was found that the number of courses of GTN chemotherapy for those who were unexpectedly diagnosed postoperatively was more than that for those who received chemotherapy preoperatively (p = 0.004).Conclusion: The single drug (5-FU) was effective in the management of low-risk (LR)-GTN. Treatment failure was related to drug resistance, high tumor score, and severe toxicity. Multi-agent regiments in combination with surgery, were an effective treatment method for GTN. For patients without metastasis and fertility requirements, surgery after chemotherapy significantly shortened the treatment cycle without increasing complications

Effect of β3-adrenoceptor on cardiac fibrosis in rat cardiac fibroblast cells and its potential mechanism

Purpose: To investigate the effect of β3-adrenoceptors (β3-AR) up-regulation on fibrosis in cardiac fibroblast cells in rats and its potential mechanism.Methods: Cardiac fibroblast cells (CFB) were isolated and identified from rats’ hearts. The β3-ARupregulated cardiac fibroblast cells were constructed by lentiviral transfection technology. Thereafter, Ang II was used to induce fibrosis in cardiac fibroblast cells, and subsequently, Western blot assay was performed to investigate fibrosis related marker proteins (TGF-β, Smad-2, p-Smad-2, Col-I and Col-III) in cardiac fibroblast cells.Results: β3-AR up-regulated cardiac fibroblast cells were successfully constructed. Furthermore, the results show that up-regulation of β3-AR increased the expressions of TGF-β, p-Smad-2, Col-I and Col- III proteins in Ang II treated cardiac fibroblast cells.Conclusion: The results suggest that up-regulation of β3-AR aggravates fibrosis of cardiac fibroblast cells. In other words, inhibition of β3-AR expressions in cardiac tissues would be beneficial for treating cardiac fibrosis and its related cardiac diseases.Keywords: Cardiac fibrosis, β3-AR, TGF/Smads, Col-I/III, Cardiac fibroblast cell