Exposing Fake Images with Forensic Similarity Graphs

We propose new image forgery detection and localization algorithms by recasting these problems as graph-based community detection problems. To do this, we introduce a novel abstract, graph-based representation of an image, which we call the Forensic Similarity Graph, that captures key forensic relationships among regions in the image. In this representation, small image patches are represented by graph vertices with edges assigned according to the forensic similarity between patches. Localized tampering introduces unique structure into this graph, which aligns with a concept called ``community structure'' in graph-theory literature. In the Forensic Similarity Graph, communities correspond to the tampered and unaltered regions in the image. As a result, forgery detection is performed by identifying whether multiple communities exist, and forgery localization is performed by partitioning these communities. We present two community detection techniques, adapted from literature, to detect and localize image forgeries. We experimentally show that our proposed community detection methods outperform existing state-of-the-art forgery detection and localization methods, which do not capture such community structure.Comment: 16 pages, under review at IEEE Journal of Selected Topics in Signal Processin

Joint Demosaicing and Denoising with Double Deep Image Priors

Demosaicing and denoising of RAW images are crucial steps in the processing pipeline of modern digital cameras. As only a third of the color information required to produce a digital image is captured by the camera sensor, the process of demosaicing is inherently ill-posed. The presence of noise further exacerbates this problem. Performing these two steps sequentially may distort the content of the captured RAW images and accumulate errors from one step to another. Recent deep neural-network-based approaches have shown the effectiveness of joint demosaicing and denoising to mitigate such challenges. However, these methods typically require a large number of training samples and do not generalize well to different types and intensities of noise. In this paper, we propose a novel joint demosaicing and denoising method, dubbed JDD-DoubleDIP, which operates directly on a single RAW image without requiring any training data. We validate the effectiveness of our method on two popular datasets -- Kodak and McMaster -- with various noises and noise intensities. The experimental results show that our method consistently outperforms other compared methods in terms of PSNR, SSIM, and qualitative visual perception

Tregs self-organize into a computing ecosystem and implement a sophisticated optimization algorithm for mediating immune response

Regulatory T cells (Tregs) play a crucial role in mediating immune response. Yet an algorithmic understanding of the role of Tregs in adaptive immunity remains lacking. Here, we present a biophysically realistic model of Treg-mediated self-tolerance in which Tregs bind to self-antigens and locally inhibit the proliferation of nearby activated T cells. By exploiting a duality between ecological dynamics and constrained optimization, we show that Tregs tile the potential antigen space while simultaneously minimizing the overlap between Treg activation profiles. We find that for sufficiently high Treg diversity, Treg-mediated self-tolerance is robust to fluctuations in self-antigen concentrations but lowering the Treg diversity results in a sharp transition-related to the Gardner transition in perceptrons-to a regime where changes in self-antigen concentrations can result in an autoimmune response. We propose an experimental test of this transition in immune-deficient mice and discuss potential implications for autoimmune diseases

Tregs self-organize into a "computing ecosystem" and implement a sophisticated optimization algorithm for mediating immune response

Regulatory T cells (Tregs) play a crucial role in mediating immune response. Yet an algorithmic understanding of the role of Tregs in adaptive immunity remains lacking. Here, we present a biophysically realistic model of Treg mediated self-tolerance in which Tregs bind to self-antigens and locally inhibit the proliferation of nearby activated T cells. By exploiting a duality between ecological dynamics and constrained optimization, we show that Tregs tile the potential antigen space while simultaneously minimizing the overlap between Treg activation profiles. We find that for sufficiently high Treg diversity, Treg mediated self-tolerance is robust to fluctuations in self-antigen concentrations but lowering the Treg diversity results in a sharp transition -- related to the Gardner transition in perceptrons -- to a regime where changes in self-antigen concentrations can result in an auto-immune response. We propose a novel experimental test of this transition in immune-deficient mice and discuss potential implications for autoimmune diseases.Comment: 8 pages, 4 figures + Appendix; Accepted at PNA

Numerical investigation of conjugated heat transfer in a channel with a moving depositing front

This article presents numerical simulations of conjugated heat transfer in a fouled channel with a moving depositing front. The depositing front separating the fluid and the deposit layer is captured using the level-set method. Fluid flow is modeled by the incompressible Navier–Stokes equations. Numerical solution is performed on a fixed mesh using the finite volume method. The effects of Reynolds number and thermal conductivity ratio between the deposit layer and the fluid on local Nusselt number as well as length-averaged Nusselt number are investigated. It is found that heat transfer performance, represented by the local and length-averaged Nusselt number reduces significantly in a fouled channel compared with that in a clean channel. Heat transfer performance decreases with the growth of the deposit layer. Increases in Reynolds, Prandtl numbers both enhance heat transfer. Besides, heat transfer is enhanced when the thermal conductivity ratio between the deposit layer and the fluid is lower than 20 but it decreases when the thermal conductivity ratio is larger than 2

The zooarchaeological application of quantifying cranial shape differences in wild boar and domestic pigs (Sus scrofa) using 3D geometric morphometrics

Peer reviewedPublisher PD

Epidural Hematoma Following Cervical Spine Surgery.

STUDY DESIGN: A multicentered retrospective case series. OBJECTIVE: To determine the incidence and circumstances surrounding the development of a symptomatic postoperative epidural hematoma in the cervical spine. METHODS: Patients who underwent cervical spine surgery between January 1, 2005, and December 31, 2011, at 23 institutions were reviewed, and all patients who developed an epidural hematoma were identified. RESULTS: A total of 16 582 cervical spine surgeries were identified, and 15 patients developed a postoperative epidural hematoma, for a total incidence of 0.090%. Substantial variation between institutions was noted, with 11 sites reporting no epidural hematomas, and 1 site reporting an incidence of 0.76%. All patients initially presented with a neurologic deficit. Nine patients had complete resolution of the neurologic deficit after hematoma evacuation; however 2 of the 3 patients (66%) who had a delay in the diagnosis of the epidural hematoma had residual neurologic deficits compared to only 4 of the 12 patients (33%) who had no delay in the diagnosis or treatment (P = .53). Additionally, the patients who experienced a postoperative epidural hematoma did not experience any significant improvement in health-related quality-of-life metrics as a result of the index procedure at final follow-up evaluation. CONCLUSION: This is the largest series to date to analyze the incidence of an epidural hematoma following cervical spine surgery, and this study suggest that an epidural hematoma occurs in approximately 1 out of 1000 cervical spine surgeries. Prompt diagnosis and treatment may improve the chance of making a complete neurologic recovery, but patients who develop this complication do not show improvements in the health-related quality-of-life measurements

Origin of volatiles in the Main Belt

We propose a scenario for the formation of the Main Belt in which asteroids incorporated icy particles formed in the outer Solar Nebula. We calculate the composition of icy planetesimals formed beyond a heliocentric distance of 5 AU in the nebula by assuming that the abundances of all elements, in particular that of oxygen, are solar. As a result, we show that ices formed in the outer Solar Nebula are composed of a mix of clathrate hydrates, hydrates formed above 50 K and pure condensates produced at lower temperatures. We then consider the inward migration of solids initially produced in the outer Solar Nebula and show that a significant fraction may have drifted to the current position of the Main Belt without encountering temperature and pressure conditions high enough to vaporize the ices they contain. We propose that, through the detection and identification of initially buried ices revealed by recent impacts on the surfaces of asteroids, it could be possible to infer the thermodynamic conditions that were present within the Solar Nebula during the accretion of these bodies, and during the inward migration of icy planetesimals. We also investigate the potential influence that the incorporation of ices in asteroids may have on their porosities and densities. In particular, we show how the presence of ices reduces the value of the bulk density of a given body, and consequently modifies its macro-porosity from that which would be expected from a given taxonomic type.Comment: Accepted for publication in MNRA