Provenance analysis for instagram photos

As a feasible device fingerprint, sensor pattern noise (SPN) has been proven to be effective in the provenance analysis of digital images. However, with the rise of social media, millions of images are being uploaded to and shared through social media sites every day. An image downloaded from social networks may have gone through a series of unknown image manipulations. Consequently, the trustworthiness of SPN has been challenged in the provenance analysis of the images downloaded from social media platforms. In this paper, we intend to investigate the effects of the pre-defined Instagram images filters on the SPN-based image provenance analysis. We identify two groups of filters that affect the SPN in quite different ways, with Group I consisting of the filters that severely attenuate the SPN and Group II consisting of the filters that well preserve the SPN in the images. We further propose a CNN-based classifier to perform filter-oriented image categorization, aiming to exclude the images manipulated by the filters in Group I and thus improve the reliability of the SPN-based provenance analysis. The results on about 20, 000 images and 18 filters are very promising, with an accuracy higher than 96% in differentiating the filters in Group I and Group II

Semantic bottleneck for computer vision tasks

This paper introduces a novel method for the representation of images that is semantic by nature, addressing the question of computation intelligibility in computer vision tasks. More specifically, our proposition is to introduce what we call a semantic bottleneck in the processing pipeline, which is a crossing point in which the representation of the image is entirely expressed with natural language , while retaining the efficiency of numerical representations. We show that our approach is able to generate semantic representations that give state-of-the-art results on semantic content-based image retrieval and also perform very well on image classification tasks. Intelligibility is evaluated through user centered experiments for failure detection

Tracking intracavernously injected adipose-derived stem cells to bone marrow.

The intracavernous (i.c.) injection of stem cells (SCs) has been shown to improve erectile function in various erectile dysfunction (ED) animal models. However, the tissue distribution of the injected cells remains unknown. In this study we tracked i.c.-injected adipose-derived stem cells (ADSCs) in various tissues. Rat paratesticular fat was processed for ADSC isolation and culture. The animals were then subject to cavernous nerve (CN) crush injury or sham operation, followed by i.c. injection of 1 million autologous or allogeneic ADSCs that were labeled with 5-ethynyl-2-deoxyuridine (EdU). Another group of rats received i.c. injection of EdU-labeled allogeneic penile smooth muscle cells (PSMCs). At 2 and 7 days post injection, penises and femoral bone marrow were processed for histological analyses. Whole femoral bone marrows were also analyzed for EdU-positive cells by flow cytometry. The results show that ADSCs exited the penis within days of i.c. injection and migrated preferentially to bone marrow. Allogenicity did not affect the bone marrow appearance of ADSCs at either 2 or 7 days, whereas CN injury reduced the number of ADSCs in bone marrow significantly at 7 but not 2 days. The significance of these results in relation to SC therapy for ED is discussed

Do individual investors trade Stocks as gambling? Evidence from repeated natural experiments

Session - Experimental FinanceMultiple natural experiments of large jackpot lotteries in Taiwan are used to document that some individual investors trade stocks as a form of gambling. Those investors substitute lottery gambling for stock trading. This substitution effect between lottery and stock is substantiated by the following five key findings. First, when the jackpot exceeds 500 million Taiwan dollars (about 15 million U.S. dollars), the number of shares traded by individual investors decreases by about 7% among stocks with high individual trading fraction, low market capitalization, high past returns, and high past turnover. Second, the reduction in individual trading is about 7% among stocks with lottery features, i.e. high return volatility and skewness. Third, the magnitude of the decline increases monotonically with the jackpot. Fourth, firm-level trading activity reacts negatively to large jackpots, and is statistically significant for a sizable number of firms. Finally, the aggregate trading activity by individual investors declines by about 5% on large jackpot days.postprintThe 46th Annual Meeting of the Western Finance Association (WFA), Santa Fe, N.M., 19-22 June 2011

Wilson ratio of Fermi gases in one dimension

We calculate the Wilson ratio of the one-dimensional Fermi gas with spin imbalance. The Wilson ratio of attractively interacting fermions is solely determined by the density stiffness and sound velocity of pairs and of excess fermions for the two-component Tomonaga-Luttinger liquid (TLL) phase. The ratio exhibits anomalous enhancement at the two critical points due to the sudden change in the density of states. Despite a breakdown of the quasiparticle description in one dimension, two important features of the Fermi liquid are retained, namely the specific heat is linearly proportional to temperature whereas the susceptibility is independent of temperature. In contrast to the phenomenological TLL parameter, the Wilson ratio provides a powerful parameter for testing universal quantum liquids of interacting fermions in one, two and three dimensions.Comment: 5+2 pages, 4+1 figures, Eq. (4) is proved, figures were refine