Creative collaboration between museums and well-known companies

The following thesis focuses on the collaboration between nonprofit art museums and large companies. For art museums, building a partnership with well-known corporations can help to increase the audience attendance, saving marketing and operating cost, as well as improve the reputation through social media and advertisement. It is essential for nonprofit art museums to know that the collaboration can be achieved through different ways including financial-sponsorship and creative partnership, as long as there is a common goal between the museum and the companies. Four case studies help to illustrate the findings which are San Francisco Museum of Modern Art, Philadelphia Museum of Art, Whitney Museum of American Art and Bank of America. From the studies, museums should also see some potential risks that will happen when building a cross-sector relationship, such as losing their artistic identity or cannot find the perfect partner. Nonprofit art museums should always be aware of the different trend in different industries in order serve the target community in the most efficient way.M.S., Arts Administration -- Drexel University, 201

Adaptive digital watermarking scheme based on support vector machines and optimized genetic algorithm

Digital watermarking is an effective solution to the problem of copyright protection, thus maintaining the security of digital products in the network. An improved scheme to increase the robustness of embedded information on the basis of discrete cosine transform (DCT) domain is proposed in this study. The embedding process consisted of two main procedures. Firstly, the embedding intensity with support vector machines (SVMs) was adaptively strengthened by training 1600 image blocks which are of different texture and luminance. Secondly, the embedding position with the optimized genetic algorithm (GA) was selected. To optimize GA, the best individual in the first place of each generation directly went into the next generation, and the best individual in the second position participated in the crossover and the mutation process. The transparency reaches 40.5 when GA’s generation number is 200. A case study was conducted on a 256 × 256 standard Lena image with the proposed method. After various attacks (such as cropping, JPEG compression, Gaussian low-pass filtering (3, 0. 5), histogram equalization, and contrast increasing (0.5, 0.6)) on the watermarked image, the extracted watermark was compared with the original one. Results demonstrate that the watermark can be effectively recovered after these attacks. Even though the algorithm is weak against rotation attacks, it provides high quality in imperceptibility and robustness and hence it is a successful candidate for implementing novel image watermarking scheme meeting real timelines

Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions

Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg)

Understanding Variation in Transcription Factor Binding by Modeling Transcription Factor Genome-Epigenome Interactions

Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg).</p

Adaptive robust blind watermarking scheme improved by entropy-based SVM and optimized quantum genetic algorithm

With the intensive study of machine learning in digital watermarking, its ability to balance the robustness and transparency of watermarking technology has attracted researchers’ attention. Therefore, quantum genetic algorithm, which serves as an intelligent optimized scheme combined with biological genetic mechanism and quantum computing, is widely used in various fields. In this study, an adaptive robust blind watermarking algorithm by means of optimized quantum genetics (OQGA) and entropy classification-based SVM (support vector machine) is proposed. The host image was divided into two parts according to the odd and even rows of the host image. One part was transformed by DCT (discrete cosine transform), and then the embedding intensity and position were separately trained by entropy-based SVM and OQGA; the other part was by DWT (discrete wavelet transform), in which the key fusion was achieved by an ergodic matrix to embed the watermark. Simulation results indicate the proposed algorithm ensures the watermark scheme transparency as well as having better resistance to common attacks such as lossy JPEG compression, image darken, Gaussian low-pass filtering, contrast decreasing, salt-pepper noise, and geometric attacks such as rotation and cropping. Received 22 May 2019 Revised 18 Aug 2019 Accepted 17 Sep 2019 Published 28 Oct 201

Clusterin confers gmcitabine resistance in pancreatic cancer

<p>Abstract</p> <p>Objective</p> <p>To measure clusterin expression in pancreatic cancer tissues and cell lines and to evaluate whether clusterin confers resistance to gmcitabine in pancreatic cancer cells.</p> <p>Methods</p> <p>Immunohistochemistry for clusterin was performed on 50 primary pancreatic cancer tissues and 25 matched backgrounds, and clusterin expression in 5 pancreatic cancer cell lines was quantified by Western blot and PT-PCR. The correlation between clusterin expression level and gmcitabine IC50 in pancreatic cancer cell lines was evaluated. The effect of an antisense oligonucleotide (ASO) against clusterin(OGX-011) on gmcitabine resistance was evaluated by MTT assays. Xenograft model was used to demonstrate tumor growth.</p> <p>Results</p> <p>Pancreatic cancer tissues expressed significantly higher levels of clusterin than did normal pancreatic tissues (<it>P </it>< 0.01). Clusterin expression levels were correlated with gmcitabine resistance in pancreatic cancer cell lines, and OGX-011 significantly decreased BxPc-3 cells resistance to gmcitabine (<it>P </it>< 0.01). <it>In vivo </it>systemic administration of AS clusterin and gmcitabine significantly decreased the s.c. BxPC-3 tumor volume compared with mismatch control ODN plus gmcitabine.</p> <p>Conclusion</p> <p>Our finding that clusterin expression was significantly higher in pancreatic cancer than in normal pancreatic tissues suggests that clusterin may confer gmcitabine resistance in pancreatic cancer cells.</p

Transcriptional Responses of Different Brain Cell Types to Oxygen Decline

Brain hypoxia is associated with a wide range of physiological and clinical conditions. Although oxygen is an essential constituent of maintaining brain functions, our understanding of how specific brain cell types globally respond and adapt to decreasing oxygen conditions is incomplete. In this study, we exposed mouse primary neurons, astrocytes, and microglia to normoxia and two hypoxic conditions and obtained genome-wide transcriptional profiles of the treated cells. Analysis of differentially expressed genes under conditions of reduced oxygen revealed a canonical hypoxic response shared among different brain cell types. In addition, we observed a higher sensitivity of neurons to oxygen decline, and dissected cell type-specific biological processes affected by hypoxia. Importantly, this study establishes novel gene modules associated with brain cells responding to oxygen deprivation and reveals a state of profound stress incurred by hypoxia

Lack of association between polymorphisms of MASP2 and susceptibility to SARS coronavirus infection

<p>Abstract</p> <p>Background</p> <p>The pathogenesis of severe acute respiratory disease syndrome (SARS) is not fully understood. One case-control study has reported an association between susceptibility to SARS and <it>mannan-binding lectin </it>(<it>MBL</it>) in China. As the downstream protein of <it>MBL</it>, variants of the <it>MBL</it>-associated serine protease-2 (<it>MASP2</it>) gene may be associated with SARS coronavirus (SARS-CoV) infection in the same population.</p> <p>Methods</p> <p>Thirty individuals with SARS were chosen for analysis of <it>MASP2 </it>polymorphisms by means of PCR direct sequencing. Tag single nucleotide polymorphisms (tagSNPs) were chosen using pairwise tagging algorithms. The frequencies of four tag SNPs (rs12711521, rs2261695, rs2273346 and rs7548659) were ascertained in 376 SARS patients and 523 control subjects, using the Beckman SNPstream Ultra High Throughput genotyping platform.</p> <p>Results</p> <p>There is no significant association between alleles or genotypes of the <it>MASP2 </it>tagSNP and susceptibility to SARS-CoV in both Beijing and Guangzhou populations. Diplotype (rs2273346 and rs12711521)were analyzed for association with susceptibility to SARS, no statistically significant evidence of association was observed. The Beijing and Guangzhou sample groups were homogeneous regarding demographic and genetic parameters, a joined analysis also showed no statistically significant evidence of association.</p> <p>Conclusion</p> <p>Our data do not suggest a role for <it>MASP2 </it>polymorphisms in SARS susceptibility in northern and southern China.</p

Discretization of the velocity space in solution of the Boltzmann equation

We point out an equivalence between the discrete velocity method of solving the Boltzmann equation, of which the lattice Boltzmann equation method is a special example, and the approximations to the Boltzmann equation by a Hermite polynomial expansion. Discretizing the Boltzmann equation with a BGK collision term at the velocities that correspond to the nodes of a Hermite quadrature is shown to be equivalent to truncating the Hermite expansion of the distribution function to the corresponding order. The truncated part of the distribution has no contribution to the moments of low orders and is negligible at small Mach numbers. Higher order approximations to the Boltzmann equation can be achieved by using more velocities in the quadrature