The diffuse neutrino flux from FR-II radio galaxies and blazars: A source property based estimate

Water and ice Cherenkov telescopes of the present and future aim for the detection of a neutrino signal from extraterrestrial sources at energies E>PeV. Some of the most promising extragalactic sources are Active Galactic Nuclei (AGN). In this paper, the neutrino flux from two kinds of AGN sources will be estimated assuming photohadronic interactions in the jet of the AGN. The first analyzed sample contains FR-II radio galaxies while the second AGN type examined are blazars. The result is highly dependent on the proton's index of the energy spectrum. To normalize the spectrum, the connection between neutrino and disk luminosity will be used by applying the jet-disk symbiosis model from Falcke and Biermann (1995). The maximum proton energy and thus, also the maximum neutrino energy of the source is connected to its disk luminosity, which was shown by Lovelace (1976) and was confirmed by Falcke et al. (1995).Comment: 24 pages, 14 figures, to be published in Astroparticle Physic

A novel real-time computational framework for detecting catheters and rigid guidewires in cardiac catheterization procedures

Purpose: Catheters and guidewires are used extensively in cardiac catheterization procedures such as heart arrhythmia treatment (ablation), angioplasty and congenital heart disease treatment. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications, for example, motion compensation, co-registration between 2D and 3D imaging modalities and 3D object reconstruction. Methods: For the generalized framework, a multiscale vessel enhancement filter is first used to enhance the visibility of wire-like structures in the X-ray images. After applying adaptive binarization method, the centerlines of wire-like objects were extracted. Finally, the catheters and guidewires were detected as a smooth path which is reconstructed from centerlines of target wire-like objects. In order to classify electrode catheters which are mainly used in electrophysiology procedures, additional steps were proposed. First, a blob detection method, which is embedded in vessel enhancement filter with no additional computational cost, localizes electrode positions on catheters. Then the type of electrode catheters can be recognized by detecting the number of electrodes and also the shape created by a series of electrodes. Furthermore, for detecting guiding catheters or guidewires, a localized machine learning algorithm is added into the framework to distinguish between target wire objects and other wire-like artifacts. The proposed framework were tested on total 10,624 images which are from 102 image sequences acquired from 63 clinical cases. Results: Detection errors for the coronary sinus (CS) catheter, lasso catheter ring and lasso catheter body are 0.56 ± 0.28 mm, 0.64 ± 0.36 mm and 0.66 ± 0.32 mm, respectively, as well as success rates of 91.4%, 86.3% and 84.8% were achieved. Detection errors for guidewires and guiding catheters are 0.62 ± 0.48 mm and success rates are 83.5%. Conclusion: The proposed computational framework do not require any user interaction or prior models and it can detect multiple catheters or guidewires simultaneously and in real-time. The accuracy of the proposed framework is sub-mm and the methods are robust toward low-dose X-ray fluoroscopic images, which are mainly used during procedures to maintain low radiation dose

The Effect of Speed Limits and Traffic Signal Control on Emissions

Traffic signals strongly influence traffic in cities - in terms of delay but also in terms of the emissions emitted by traffic. This work analyzes the effect of different traffic control strategies on emissions like NOx and PMx. Simulations of an inner-city arterial show that reducing the speed limit leads to a lower production of NOx and PMx, but to an increase in delay. The impact of the traffic signal control on the emissions is less distinct: A carefully designed co-ordination reduces emissions, while a simple actuated control cannot improve traffic flow and therefore increases pollutant production

A mountain ridge model for quantifying oblique mountain wave propagation and distribution

Following the current understanding of gravity waves (GWs) and especially mountain waves (MWs), they have high potential of horizontal propagation from their source. This horizontal propagation and therefore the transport of energy is usually not well represented in MW parameterizations of numerical weather prediction and general circulation models. The lack thereof possibly leads to shortcomings in the model's prediction as e.g. the cold pole bias in the Southern Hemisphere and the polar vortex breaking down too late. In this study we present a mountain wave model (MWM) for quantification of the horizontal propagation of orographic gravity waves. This model determines MW source location and associates their parameters from a fit of idealized Gaussian shaped mountains to topography data. Propagation and refraction of these MWs in the atmosphere is modeled using the ray-tracer GROGRAT. Ray-tracing each MW individually allows for an estimation of momentum transport due to both vertical and horizontal propagation. This study presents the MWM itself and gives validations of MW induced temperature perturbations to ECMWF IFS numerical weather prediction data and estimations of gravity wave momentum flux (GWMF) compared to HIRDLS satellite observations. The MWM is capable of reproducing the general features and amplitudes of both of these data sets and, in addition, is used to explain some observational features by investigating MW parameters along their trajectories.</p

Real-time malware process detection and automated process killing

Perimeter-based detection is no longer sufficient for mitigating the threat posed by malicious software. This is evident as antivirus (AV) products are replaced by endpoint detection and response (EDR) products, the latter allowing visibility into live machine activity rather than relying on the AV to filter out malicious artefacts. This paper argues that detecting malware in real-time on an endpoint necessitates an automated response due to the rapid and destructive nature of some malware. The proposed model uses statistical filtering on top of a machine learning dynamic behavioural malware detection model in order to detect individual malicious processes on the fly and kill those which are deemed malicious. In an experiment to measure the tangible impact of this system, we find that fast-acting ransomware is prevented from corrupting 92% of files with a false positive rate of 14%. Whilst the false-positive rate currently remains too high to adopt this approach as-is, these initial results demonstrate the need for a detection model that is able to act within seconds of the malware execution beginning; a timescale that has not been addressed by previous work

The behavioural effects of feeding lean meat vs whole rabbit carcasses to zoo jaguars Panthera onca

The challenge of carnivore feeding in zoos is to stimulate natural feeding behaviour without using live prey animals. The objective of this study was to investigate how two different feed types (lean beef and whole rabbits) affect the behaviour of zoo jaguars Panthera onca for the first six hours after feed presentation. Three socially housed jaguars at Parken Zoo, Sweden, were offered either lean beef or whole rabbits for 10 consecutive feeding days. Their behaviour during and after feeding was videorecorded and then compared between the two feed types. When analysing the frequency of different behaviours for six hours after feeding, results confirm that feeding behaviour occurred significantly more frequently when whole rabbits were fed, particularly during the first hour after feed presentation. However, even though feeding time increased by more than 300%, this represents a change of less than 1% in terms of the overall proportion of a 24-hour budget. Future studies might investigate the effect of feeding jaguars larger carcasses than rabbits, including with more hours of observation