Modelling of content-aware indicators for effective determination of shot boundaries in compressed MPEG videos

In this paper, a content-aware approach is proposed to design multiple test conditions for shot cut detection, which are organized into a multiple phase decision tree for abrupt cut detection and a finite state machine for dissolve detection. In comparison with existing approaches, our algorithm is characterized with two categories of content difference indicators and testing. While the first category indicates the content changes that are directly used for shot cut detection, the second category indicates the contexts under which the content change occurs. As a result, indications of frame differences are tested with context awareness to make the detection of shot cuts adaptive to both content and context changes. Evaluations announced by TRECVID 2007 indicate that our proposed algorithm achieved comparable performance to those using machine learning approaches, yet using a simpler feature set and straightforward design strategies. This has validated the effectiveness of modelling of content-aware indicators for decision making, which also provides a good alternative to conventional approaches in this topic

Integer and half-integer flux-quantum transitions in a niobium/iron-pnictide loop

The recent discovery of iron-based superconductors challenges the existing paradigm of high-temperature superconductivity. Owing to their unusual multi-orbital band structure, magnetism, and electron correlation, theories propose a unique sign reversed s-wave pairing state, with the order parameter changing sign between the electron and hole Fermi pockets. However, because of the complex Fermi surface topology and material related issues, the predicted sign reversal remains unconfirmed. Here we report a novel phase-sensitive technique for probing unconventional pairing symmetry in the polycrystalline iron-pnictides. Through the observation of both integer and half-integer flux-quantum transitions in composite niobium/iron-pnictide loops, we provide the first phase-sensitive evidence of the sign change of the order parameter in NdFeAsO0.88F0.12, lending strong support for microscopic models predicting unconventional s-wave pairing symmetry. These findings have important implications on the mechanism of pnictide superconductivity, and lay the groundwork for future studies of new physics arising from the exotic order in the FeAs-based superconductors.Comment: 23 pages, including 4 figures and supplementary informatio

Image-to-Image Translation to Unfold the Reality of Artworks: an Empirical Analysis

State-of-the-art Computer Vision pipelines show poor performances on artworks and data coming from the artistic domain, thus limiting the applicability of current architectures to the automatic understanding of the cultural heritage. This is mainly due to the difference in texture and low-level feature distribution between artistic and real images, on which state-of-the-art approaches are usually trained. To enhance the applicability of pre-trained architectures on artistic data, we have recently proposed an unpaired domain translation approach which can translate artworks to photo-realistic visualizations. Our approach leverages semantically-aware memory banks of real patches, which are used to drive the generation of the translated image while improving its realism. In this paper, we provide additional analyses and experimental results which demonstrate the effectiveness of our approach. In particular, we evaluate the quality of generated results in the case of the translation of landscapes, portraits and of paintings coming from four different styles using automatic distance metrics. Also, we analyze the response of pre-trained architecture for classification, detection and segmentation both in terms of feature distribution and entropy of prediction, and show that our approach effectively reduces the domain shift of paintings. As an additional contribution, we also provide a qualitative analysis of the reduction of the domain shift for detection, segmentation and image captioning

Steam reforming on transition-metal carbides from density-functional theory

A screening study of the steam reforming reaction (CH_4 + H_2O -> CO + 3H_2) on early transition-metal carbides (TMC's) is performed by means of density-functional theory calculations. The set of considered surfaces includes the alpha-Mo_2C(100) surfaces, the low-index (111) and (100) surfaces of TiC, VC, and delta-MoC, and the oxygenated alpha-Mo_2C(100) and TMC(111) surfaces. It is found that carbides provide a wide spectrum of reactivities towards the steam reforming reaction, from too reactive via suitable to too inert. The reactivity is discussed in terms of the electronic structure of the clean surfaces. Two surfaces, the delta-MoC(100) and the oxygen passivated alpha-Mo_2C(100) surfaces, are identified as promising steam reforming catalysts. These findings suggest that carbides provide a playground for reactivity tuning, comparable to the one for pure metals.Comment: 6 pages, 4 figure

An Integrated Approach to Identifying Cis-Regulatory Modules in the Human Genome

In eukaryotic genomes, it is challenging to accurately determine target sites of transcription factors (TFs) by only using sequence information. Previous efforts were made to tackle this task by considering the fact that TF binding sites tend to be more conserved than other functional sites and the binding sites of several TFs are often clustered. Recently, ChIP-chip and ChIP-sequencing experiments have been accumulated to identify TF binding sites as well as survey the chromatin modification patterns at the regulatory elements such as promoters and enhancers. We propose here a hidden Markov model (HMM) to incorporate sequence motif information, TF-DNA interaction data and chromatin modification patterns to precisely identify cis-regulatory modules (CRMs). We conducted ChIP-chip experiments on four TFs, CREB, E2F1, MAX, and YY1 in 1% of the human genome. We then trained a hidden Markov model (HMM) to identify the labels of the CRMs by incorporating the sequence motifs recognized by these TFs and the ChIP-chip ratio. Chromatin modification data was used to predict the functional sites and to further remove false positives. Cross-validation showed that our integrated HMM had a performance superior to other existing methods on predicting CRMs. Incorporating histone signature information successfully penalized false prediction and improved the whole performance. The dataset we used and the software are available at http://nash.ucsd.edu/CIS/

Overexpression of hepatoma-derived growth factor in melanocytes does not lead to oncogenic transformation

<p>Abstract</p> <p>Background</p> <p>HDGF is a growth factor which is overexpressed in a wide range of tumors. Importantly, expression levels were identified as a prognostic marker in some types of cancer such as melanoma.</p> <p>Methods</p> <p>To investigate the presumed oncogenic/transforming capacity of HDGF, we generated transgenic mice overexpressing HDGF in melanocytes. These mice were bred with mice heterozygous for a defective copy of the Ink4a tumor suppressor gene and were exposed to UV light to increase the risk for tumor development both genetically and physiochemically. Mice were analyzed by immunohistochemistry and Western blotting. Furthermore, primary melanocytes were isolated from different strains created.</p> <p>Results</p> <p>Transgenic animals overexpressed HDGF in hair follicle melanocytes. Interestingly, primary melanocytes isolated from transgenic animals were not able to differentiate <it>in vitro </it>whereas cells isolated from wild type and HDGF-deficient animals were. Although, HDGF^-/-/Ink4a^+/-mice displayed an increased number of epidermoid cysts after exposure to UV light, no melanomas or premelanocytic alterations could be detected in this mouse model.</p> <p>Conclusions</p> <p>The results therefore provide no evidence that HDGF has a transforming capacity in tumor development. Our results in combination with previous findings point to a possible role in cell differentiation and suggest that HDGF promotes tumor progression after secondary upregulation and may represent another protein fitting into the concept of non-oncogene addiction of tumor tissue.</p

ChromaSig: A Probabilistic Approach to Finding Common Chromatin Signatures in the Human Genome

Computational methods to identify functional genomic elements using genetic information have been very successful in determining gene structure and in identifying a handful of cis-regulatory elements. But the vast majority of regulatory elements have yet to be discovered, and it has become increasingly apparent that their discovery will not come from using genetic information alone. Recently, high-throughput technologies have enabled the creation of information-rich epigenetic maps, most notably for histone modifications. However, tools that search for functional elements using this epigenetic information have been lacking. Here, we describe an unsupervised learning method called ChromaSig to find, in an unbiased fashion, commonly occurring chromatin signatures in both tiling microarray and sequencing data. Applying this algorithm to nine chromatin marks across a 1% sampling of the human genome in HeLa cells, we recover eight clusters of distinct chromatin signatures, five of which correspond to known patterns associated with transcriptional promoters and enhancers. Interestingly, we observe that the distinct chromatin signatures found at enhancers mark distinct functional classes of enhancers in terms of transcription factor and coactivator binding. In addition, we identify three clusters of novel chromatin signatures that contain evolutionarily conserved sequences and potential cis-regulatory elements. Applying ChromaSig to a panel of 21 chromatin marks mapped genomewide by ChIP-Seq reveals 16 classes of genomic elements marked by distinct chromatin signatures. Interestingly, four classes containing enrichment for repressive histone modifications appear to be locally heterochromatic sites and are enriched in quickly evolving regions of the genome. The utility of this approach in uncovering novel, functionally significant genomic elements will aid future efforts of genome annotation via chromatin modifications

Easy detection of chromatin binding proteins by the histone association assay

The Histone Association Assay provides an easy approach for detecting proteins that bind chromatin in vivo. This technique is based on a chromatin immunoprecipitation protocol using histone H3-specific antibodies to precipitate bulk chromatin from crosslinked whole cell extracts. Proteins that co-precipitate with chromatin are subsequently detected by conventional SDS-PAGE and Western blot analysis. Unlike techniques that separate chromatin and non-chromatin interacting proteins by centrifugation, this method can be used to delineate whether a protein is chromatin associated regardless of its innate solubility. Moreover, the relative amount of protein bound to DNA can be ascertained under quantitative conditions. Therefore, this technique may be utilized for analyzing the chromatin association of proteins involved in diverse cellular processes

Movement Protein Pns6 of Rice dwarf phytoreovirus Has Both ATPase and RNA Binding Activities

Cell-to-cell movement is essential for plant viruses to systemically infect host plants. Plant viruses encode movement proteins (MP) to facilitate such movement. Unlike the well-characterized MPs of DNA viruses and single-stranded RNA (ssRNA) viruses, knowledge of the functional mechanisms of MPs encoded by double-stranded RNA (dsRNA) viruses is very limited. In particular, many studied MPs of DNA and ssRNA viruses bind non-specifically ssRNAs, leading to models in which ribonucleoprotein complexes (RNPs) move from cell to cell. Thus, it will be of special interest to determine whether MPs of dsRNA viruses interact with genomic dsRNAs or their derivative sRNAs. To this end, we studied the biochemical functions of MP Pns6 of Rice dwarf phytoreovirus (RDV), a member of Phytoreovirus that contains a 12-segmented dsRNA genome. We report here that Pns6 binds both dsRNAs and ssRNAs. Intriguingly, Pns6 exhibits non-sequence specificity for dsRNA but shows preference for ssRNA sequences derived from the conserved genomic 5′- and 3′- terminal consensus sequences of RDV. Furthermore, Pns6 exhibits magnesium-dependent ATPase activities. Mutagenesis identified the RNA binding and ATPase activity sites of Pns6 at the N- and C-termini, respectively. Our results uncovered the novel property of a viral MP in differentially recognizing dsRNA and ssRNA and establish a biochemical basis to enable further studies on the mechanisms of dsRNA viral MP functions