Aerodynamic investigations of ventilated brake discs.

The heat dissipation and performance of a ventilated brake disc strongly depends on the aerodynamic characteristics of the flow through the rotor passages. The aim of this investigation was to provide an improved understanding of ventilated brake rotor flow phenomena, with a view to improving heat dissipation, as well as providing a measurement data set for validation of computational fluid dynamics methods. The flow fields at the exit of four different brake rotor geometries, rotated in free air, were measured using a five-hole pressure probe and a hot-wire anemometry system. The principal measurements were taken using two-component hot-wire techniques and were used to determine mean and unsteady flow characteristics at the exit of the brake rotors. Using phase-locked data processing, it was possible to reveal the spatial and temporal flow variation within individual rotor passages. The effects of disc geometry and rotational speed on the mean flow, passage turbulence intensity, and mass flow were determined. The rotor exit jet and wake flow were clearly observed as characterized by the passage geometry as well as definite regions of high and low turbulence. The aerodynamic flow characteristics were found to be reasonably independent of rotational speed but highly dependent upon rotor geometry

Automatic Dataset Labelling and Feature Selection for Intrusion Detection Systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Correctly labelled datasets are commonly required. Three particular scenarios are highlighted, which showcase this need. When using supervised Intrusion Detection Systems (IDSs), these systems need labelled datasets to be trained. Also, the real nature of the analysed datasets must be known when evaluating the efficiency of the IDSs when detecting intrusions. Another scenario is the use of feature selection that works only if the processed datasets are labelled. In normal conditions, collecting labelled datasets from real networks is impossible. Currently, datasets are mainly labelled by implementing off-line forensic analysis, which is impractical because it does not allow real-time implementation. We have developed a novel approach to automatically generate labelled network traffic datasets using an unsupervised anomaly based IDS. The resulting labelled datasets are subsets of the original unlabelled datasets. The labelled dataset is then processed using a Genetic Algorithm (GA) based approach, which performs the task of feature selection. The GA has been implemented to automatically provide the set of metrics that generate the most appropriate intrusion detection results

Trimers, molecules and polarons in imbalanced atomic Fermi gases

We consider the ground state of a single "spin-down" impurity atom interacting attractively with a "spin-up" atomic Fermi gas. By constructing variational wave functions for polarons, molecules and trimers, we perform a detailed study of the transitions between each of these dressed bound states as a function of mass ratio $r=m_\uparrow/m_\downarrow$ and interaction strength. We find that the presence of a Fermi sea enhances the stability of the $p$-wave trimer, which can be viewed as a Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) molecule that has bound an additional majority atom. For sufficiently large $r$, we find that the transitions lie outside the region of phase separation in imbalanced Fermi gases and should thus be observable in experiment, unlike the well-studied equal-mass case.Comment: 5 pages, 2 figure

Evaporative depolarization and spin transport in a unitary trapped Fermi gas

We consider a partially spin-polarized atomic Fermi gas in a high-aspect-ratio trap, with a flux of predominantly spin-up atoms exiting the center of the trap. We argue that such a scenario can be produced by evaporative cooling, and we find that it can result in a substantially non-equilibrium polarization pattern for typical experimental parameters. We offer this as a possible explanation for the quantitative discrepancies in recent experiments on spin-imbalanced unitary Fermi gases.Comment: 6 pages, 3 figures; published versio

Adding Contextual Information to Intrusion Detection Systems Using Fuzzy Cognitive Maps

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In the last few years there has been considerable increase in the efficiency of Intrusion Detection Systems (IDSs). However, networks are still the victim of attacks. As the complexity of these attacks keeps increasing, new and more robust detection mechanisms need to be developed. The next generation of IDSs should be designed incorporating reasoning engines supported by contextual information about the network, cognitive information and situational awareness to improve their detection results. In this paper, we propose the use of a Fuzzy Cognitive Map (FCM) in conjunction with an IDS to incorporate contextual information into the detection process. We have evaluated the use of FCMs to adjust the Basic Probability Assignment (BPA) values defined prior to the data fusion process, which is crucial for the IDS that we have developed. The experimental results that we present verify that FCMs can improve the efficiency of our IDS by reducing the number of false alarms, while not affecting the number of correct detections

Using the Pattern-of-Life in Networks to Improve the Effectiveness of Intrusion Detection Systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.As the complexity of cyber-attacks keeps increasing, new and more robust detection mechanisms need to be developed. The next generation of Intrusion Detection Systems (IDSs) should be able to adapt their detection characteristics based not only on the measureable network traffic, but also on the available high- level information related to the protected network to improve their detection results. We make use of the Pattern-of-Life (PoL) of a network as the main source of high-level information, which is correlated with the time of the day and the usage of the network resources. We propose the use of a Fuzzy Cognitive Map (FCM) to incorporate the PoL into the detection process. The main aim of this work is to evidence the improved the detection performance of an IDS using an FCM to leverage on network related contextual information. The results that we present verify that the proposed method improves the effectiveness of our IDS by reducing the total number of false alarms; providing an improvement of 9.68% when all the considered metrics are combined and a peak improvement of up to 35.64%, depending on particular metric combination

Heparan Sulfate: A Ubiquitous Glycosaminoglycan with Multiple Roles in Immunity

Heparan sulfate (HS) is a highly acidic linear polysaccharide with a very variable structure. It is ubiquitously expressed on cell surfaces and in the extracellular matrix and basement membrane of mammalian tissues. Synthesized attached to various core proteins to form HS-proteoglycans, HS is capable of interacting with various polypeptides and exerting diverse functions. In fact, a bioinformatics analysis of mammalian proteins that express a heparin/HS-binding motif and are associated with the immune system identified 235 candidate proteins, the majority having an intracellular location. This simple analysis suggests that HS may, in fact, interact with many more components of the immune system than previously realized. Numerous studies have also directly demonstrated that HS plays multiple prominent functional roles in the immune system that are briefly reviewed in this article. In particular, the molecule has been shown to regulate leukocyte development, leukocyte migration, immune activation, and inflammatory processes

A Data Fusion Technique to Detect Wireless Network Virtual Jamming Attacks

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Wireless communications are potentially exposed to jamming due to the openness of the medium and, in particular, to virtual jamming, which allows more energy-efficient attacks. In this paper we tackle the problem of virtual jamming attacks on IEEE 802.11 networks and present a data fusion solution for the detection of a type of virtual jamming attack (namely, NAV attacks), based on the real-time monitoring of a set of metrics. The detection performance is evaluated in a number of real scenarios

Phase separation and collapse in Bose-Fermi mixtures with a Feshbach resonance

We consider a mixture of single-component bosonic and fermionic atoms with an interspecies interaction that is varied using a Feshbach resonance. By performing a mean-field analysis of a two-channel model, which describes both narrow and broad Feshbach resonances, we find an unexpectedly rich phase diagram at zero temperature: Bose-condensed and non-Bose-condensed phases form a variety of phase-separated states that are accompanied by both critical and tricritical points. We discuss the implications of our results for the experimentally observed collapse of Bose-Fermi mixtures on the attractive side of the Feshbach resonance, and we make predictions for future experiments on Bose-Fermi mixtures close to a Feshbach resonance.Comment: 7 pages, 3 figures. Extended versio

Observation of quantum depletion in a nonequilibrium exciton-polariton condensate

The property of superfluidity, first discovered in liquid 4He, is closely related to Bose-Einstein condensation (BEC) of interacting bosons. However, even at zero temperature, when one would expect the whole bosonic quantum liquid to become condensed, a fraction of it is excited into higher momentum states via interparticle interactions and quantum fluctuations -- the phenomenon of quantum depletion. Quantum depletion of weakly interacting atomic BECs in thermal equilibrium is well understood theoretically but is difficult to measure. This is even more challenging in driven-dissipative systems such as exciton-polariton condensates(photons coupled to electron-hole pairs in a semiconductor), since their nonequilibrium nature is predicted to suppress quantum depletion. Here, we observe quantum depletion of an optically trapped high-density exciton-polariton condensate by directly detecting the spectral branch of elementary excitations populated by this process. Analysis of the population of this branch in momentum space shows that quantum depletion of an exciton-polariton condensate can closely follow or strongly deviate from the equilibrium Bogoliubov theory, depending on the fraction of matter (exciton) in an exciton-polariton. Our results reveal the effects of exciton-polariton interactions beyond the mean-field description and call for a deeper understanding of the relationship between equilibrium and nonequilibrium BECs.Comment: 18 pages, 5 figures, with supplementary informatio