Numerical Models of Viscous Accretion Flows Near Black Holes

We report on a numerical study of viscous fluid accretion onto a black hole. The flow is axisymmetric and uses a pseudo-Newtonian potential to model relativistic effects near the event horizon. The numerical method is a variant of the ZEUS code. As a test of our numerical scheme, we are able to reproduce results from earlier, similar work by Igumenshchev and Abramowicz and Stone et al. We consider models in which mass is injected onto the grid as well as models in which an initial equilibrium torus is accreted. In each model we measure three ``eigenvalues'' of the flow: the accretion rate of mass, angular momentum, and energy. We find that the eigenvalues are sensitive to r_{in}, the location of the inner radial boundary. Only when the flow is always supersonic on the inner boundary are the eigenvalues insensitive to small changes in r_{in}. We also report on the sensitivity of the results to other numerical parameters.Comment: 14 pages, 4 figures, 2 tables, to appear in v573 n2 pt1 ApJ July 10, 200

Non-vanishing boundary effects and quasi-first order phase transitions in high dimensional Ising models

In order to gain a better understanding of the Ising model in higher dimensions we have made a comparative study of how the boundary, open versus cyclic, of a d-dimensional simple lattice, for d=1,...,5, affects the behaviour of the specific heat C and its microcanonical relative, the entropy derivative -dS/dU. In dimensions 4 and 5 the boundary has a strong effect on the critical region of the model and for cyclic boundaries in dimension 5 we find that the model displays a quasi first order phase transition with a bimodal energy distribution. The latent heat decreases with increasing systems size but for all system sizes used in earlier papers the effect is clearly visible once a wide enough range of values for K is considered. Relations to recent rigorous results for high dimensional percolation and previous debates on simulation of Ising models and gauge fields are discussed.Comment: 12 pages, 27 figure

LR-CNN: Local-aware Region CNN for Vehicle Detection in Aerial Imagery

State-of-the-art object detection approaches such as Fast/Faster R-CNN, SSD, or YOLO have difficulties detecting dense, small targets with arbitrary orientation in large aerial images. The main reason is that using interpolation to align RoI features can result in a lack of accuracy or even loss of location information. We present the Local-aware Region Convolutional Neural Network (LR-CNN), a novel two-stage approach for vehicle detection in aerial imagery. We enhance translation invariance to detect dense vehicles and address the boundary quantization issue amongst dense vehicles by aggregating the high-precision RoIs' features. Moreover, we resample high-level semantic pooled features, making them regain location information from the features of a shallower convolutional block. This strengthens the local feature invariance for the resampled features and enables detecting vehicles in an arbitrary orientation. The local feature invariance enhances the learning ability of the focal loss function, and the focal loss further helps to focus on the hard examples. Taken together, our method better addresses the challenges of aerial imagery. We evaluate our approach on several challenging datasets (VEDAI, DOTA), demonstrating a significant improvement over state-of-the-art methods. We demonstrate the good generalization ability of our approach on the DLR 3K dataset.Comment: 8 page

On the Phase Structure of QCD in a Finite Volume

The chiral phase transition in QCD at finite chemical potential and temperature can be characterized for small chemical potential by its curvature and the transition temperature. The curvature is accessible to QCD lattice simulations, which are always performed at finite pion masses and in finite simulation volumes. We investigate the effect of a finite volume on the curvature of the chiral phase transition line. We use functional renormalization group methods with a two flavor quark-meson model to obtain the effective action in a finite volume, including both quark and meson fluctuation effects. Depending on the chosen boundary conditions and the pion mass, we find pronounced finite-volume effects. For periodic quark boundary conditions in spatial directions, we observe a decrease in the curvature in intermediate volume sizes, which we interpret in terms of finite-volume quark effects. Our results have implications for the phase structure of QCD in a finite volume, where the location of a possible critical endpoint might be shifted compared to the infinite-volume case.Comment: 11 pages, 3 figures, 4 tables; minor text corrections, one figure added, appendix added, references added, matches PLB versio

A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization

Existing Android malware detection approaches use a variety of features such as security sensitive APIs, system calls, control-flow structures and information flows in conjunction with Machine Learning classifiers to achieve accurate detection. Each of these feature sets provides a unique semantic perspective (or view) of apps' behaviours with inherent strengths and limitations. Meaning, some views are more amenable to detect certain attacks but may not be suitable to characterise several other attacks. Most of the existing malware detection approaches use only one (or a selected few) of the aforementioned feature sets which prevent them from detecting a vast majority of attacks. Addressing this limitation, we propose MKLDroid, a unified framework that systematically integrates multiple views of apps for performing comprehensive malware detection and malicious code localisation. The rationale is that, while a malware app can disguise itself in some views, disguising in every view while maintaining malicious intent will be much harder. MKLDroid uses a graph kernel to capture structural and contextual information from apps' dependency graphs and identify malice code patterns in each view. Subsequently, it employs Multiple Kernel Learning (MKL) to find a weighted combination of the views which yields the best detection accuracy. Besides multi-view learning, MKLDroid's unique and salient trait is its ability to locate fine-grained malice code portions in dependency graphs (e.g., methods/classes). Through our large-scale experiments on several datasets (incl. wild apps), we demonstrate that MKLDroid outperforms three state-of-the-art techniques consistently, in terms of accuracy while maintaining comparable efficiency. In our malicious code localisation experiments on a dataset of repackaged malware, MKLDroid was able to identify all the malice classes with 94% average recall

PADAMOT : project overview report

Background and relevance to radioactive waste management International consensus confirms that placing radioactive wastes and spent nuclear fuel deep underground in a geological repository is the generally preferred option for their long-term management and disposal. This strategy provides a number of advantages compared to leaving it on or near the Earth’s surface. These advantages come about because, for a well chosen site, the geosphere can provide: • a physical barrier that can negate or buffer against the effects of surface dominated natural disruptive processes such as deep weathering, glaciation, river and marine erosion or flooding, asteroid/comet impact and earthquake shaking etc. • long and slow groundwater return pathways from the facility to the biosphere along which retardation, dilution and dispersion processes may operate to reduce radionuclide concentration in the groundwater. • a stable, and benign geochemical environment to maximise the longevity of the engineered barriers such as the waste containers and backfill in the facility. • a natural radiation shield around the wastes. • a mechanically stable environment in which the facility can be constructed and will afterwards be protected. • an environment which reduces the likelihood of the repository being disturbed by inadvertent human intrusion such as land use changes, construction projects, drilling, quarrying and mining etc. • protection against the effects of deliberate human activities such as vandalism, terrorism and war etc. However, safety considerations for storing and disposing of long-lived radioactive wastes must take into account various scenarios that might affect the ability of the geosphere to provide the functionality listed above. Therefore, in order to provide confidence in the ability of a repository to perform within the deep geological setting at a particular site, a demonstration of geosphere “stability” needs to be made. Stability is defined here to be the capacity of a geological and hydrogeological system to minimise the impact of external influences on the repository environment, or at least to account for them in a manner that would allow their impacts to be evaluated and accounted for in any safety assessments. A repository should be sited where the deep geosphere is a stable host in which the engineered containment can continue to perform according to design and in which the surrounding hydrogeological, geomechanical and geochemical environment will continue to operate as a natural barrier to radionuclide movement towards the biosphere. However, over the long periods of time during which long-lived radioactive wastes will pose a hazard, environmental change at the surface has the potential to disrupt the stability of the geosphere and therefore the causes of environmental change and their potential consequences need to be evaluated. As noted above, environmental change can include processes such as deep weathering, glaciation, river and marine erosion. It can also lead to changes in groundwater boundary conditions through alternating recharge/discharge relationships. One of the key drivers for environmental change is climate variability. The question then arises, how can geosphere stability be assessed with respect to changes in climate? Key issues raised in connection with this are: • What evidence is there that 'going underground' eliminates the extreme conditions that storage on the surface would be subjected to in the long term? • How can the additional stability and safety of the deep geosphere be demonstrated with evidence from the natural system? As a corollary to this, the capacity of repository sites deep underground in stable rock masses to mitigate potential impacts of future climate change on groundwater conditions therefore needs to be tested and demonstrated. To date, generic scenarios for groundwater evolution relating to climate change are currently weakly constrained by data and process understanding. Hence, the possibility of site-specific changes of groundwater conditions in the future can only be assessed and demonstrated by studying groundwater evolution in the past. Stability of groundwater conditions in the past is an indication of future stability, though both the climatic and geological contexts must be taken into account in making such an assertion

Fluctuations as probe of the QCD phase transition and freeze-out in heavy ion collisions at LHC and RHIC

We discuss the relevance of higher order moments of net baryon number fluctuations for the analysis of freeze-out and critical conditions in heavy ion collisions at LHC and RHIC. Using properties of O(4) scaling functions, we discuss the generic structure of these higher moments at vanishing baryon chemical potential and apply chiral model calculations to explore their properties at non-zero baryon chemical potential. We show that the ratios of the sixth to second and eighth to second order moments of the net baryon number fluctuations change rapidly in the transition region of the QCD phase diagram. Already at vanishing baryon chemical potential they deviate considerably from the predictions of the hadron resonance gas model which reproduce the second to fourth order moments of the net proton number fluctuations at RHIC. We point out that the sixth order moments of baryon number and electric charge fluctuations remain negative at the chiral transition temperature. Thus, they offer the possibility to probe the proximity of the thermal freeze-out to the crossover line.Comment: 24 pages, 12 EPS files, revised version, to appear in EPJ

Cortical Dynamics of Boundary Segmentation and Reset: Persistence, Afterimages, and Residual Traces

Using a neural network model of boundary segmentation and reset, Francis, Grossberg, and Mingolla (1994) linked the percept of persistence to the duration of a boundary segmentation after stimulus offset. In particular, the model simulated the decrease of persistence duration with an increase in stimulus duration and luminance. Thc present article reveals further evidence for the neural mechanisms used by the theory. Simulations show that the model reset signals generate orientational afterimages, such as the MacKay effect, when the reset signals can be grouped by a subsequent boundary segmentation that generates illusory contours through them. Simulations also show that the same mechanisms explain properties of residual traces, which increase in duration with stimulus duration and luminance. The model hereby discloses previously unsuspected mechanistic links between data about persistence and afterimages, and helps to clarify the sometimes controversial issues surrounding distinctions between persistence, residual traces, and afterimages.Air Force Office of Scientific Research (F49620-92-J-0499); Office of Naval Research (N00014-91-J-4100, N00014-92-J-4015