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Facile and simple method is developed to synthesize silver-nanoparticle-decorated quercetin nanoparticles (QA NPs). Modification suggests that synergistic quercetin (Qe) improves the antibacterial effect of silver nanoparticles (Ag NPs). Characterization experiment indicates that QA NPs have a diameter of approximately 10 nm. QA NPs show highly effective antibacterial activities against drug-resistant Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). We explore antibacterial mechanisms using S. aureus and E. coli treated with QA NPs. Through morphological changes in E. coli and S. aureus, mechanisms are examined for bacterial damage caused by particulate matter from local dissociation of silver ion and Qe from QA NPs trapped inside membranes. Moreover, we note that gene expression profiling methods, such as RNA sequencing, can be used to predict discover mechanisms of toxicity of QA NPs. Gene ontology (GO) assay analyses demonstrate the molecular mechanism of the antibacterial effect of QA NPs. Regarding cellular component ontology, "cell wall organization or biogenesis" (GO: 0071554) and "cell wall macromolecule metabolic process" (GO: 0044036) are the most represented categories. The present study reports that transcriptome analysis of the mechanism offers novel insights into the molecular mechanism of antibacterial assays.

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Motivated by linear network coding, communication channels perform linear operation over finite fields, namely linear operator channels (LOCs), are studied in this paper. For such a channel, its output vector is a linear transform of its input vector, and the transformation matrix is randomly and independently generated. The transformation matrix is assumed to remain constant for every T input vectors and to be unknown to both the transmitter and the receiver.There are NO constraints on the distribution of the transformation matrix and the field size.Specifically, the optimality of subspace coding over LOCs is investigated. A lower bound on the maximum achievable rate of subspace coding is obtained and it is shown to be tight for some cases. The maximum achievable rate of constant-dimensional subspace coding is characterized and the loss of rate incurred by using constant-dimensional subspace coding is insignificant.The maximum achievable rate of channel training is close to the lower bound on the maximum achievable rate of subspace coding. Two coding approaches based on channel training are proposed and their performances are evaluated.Our first approach makes use of rank-metric codes and its optimality depends on the existence of maximum rank distance codes. Our second approach applies linear coding and it can achieve the maximum achievable rate of channel training. Our code designs require only the knowledge of the expectation of the rank of the transformation matrix.The second scheme can also be realized ratelessly without a priori knowledge of the channel statistics.

A universal lossless data compression code called the multilevel pattern matching code (MPM code) is introduced. In processing a finite-alphabet data string of length , the MPM code operates at (log log) levels sequentially. At each level, the MPM code detects matching patterns in the input data string (substrings of the data appearing in two or more nonoverlapping positions). The matching patterns detected at each level are of a fixed length which decreases by a constant factor from level to level, until this fixed length becomes one at the final level. The MPM code represents information about the matching patterns at each level as a string of tokens, with each token string encoded by an arithmetic encoder. From the concatenated encoded token strings, the decoder can reconstruct the data string via several rounds of parallel substitutions. A (1 log) maximal redundancy/sample upper bound is established for the MPM code with respect to any class of finite state sources of uniformly bounded complexity. We also show that the MPM code is of linear complexity in terms of time and space requirements. The results of some MPM code compression experiments are reported.

In this paper, it is shown that each Slepian-Wolf coding problem is related to a dual channel coding problem in the sense that the sphere packing exponents, random coding exponents, and correct decoding exponents in these two problems are mirror-symmetrical to each other. This mirror symmetry is interpreted as a manifestation of the linear codebook-level duality between Slepian-Wolf coding and channel coding. Furthermore, this duality, in conjunction with a systematic analysis of the expurgated exponents, reveals that nonlinear Slepian-Wolf codes can strictly outperform linear Slepian-Wolf codes in terms of rate-error tradeoff at high rates. The linear codebook-level duality is also established for general sources and channels.

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