Terror threat perception and its consequences in contemporary Britain

The terrorist attacks of 9/11, and subsequent terrorist acts around the world, have alerted social psychologists to the need to examine the antecedents and consequences of terrorist threat perception. In these two studies we examined the predictive power of demographic factors (age, sex, location), individual values and normative influences on threat perception and the consequences of this perception for behavioural change and close relationships. In study 1 (N = 100) gender, benevolence values and normative influences were all correlates of threat perception, whilst sense of personal threat was correlated with increased contact with friends and family. In study 2 (N = 240) age, sex, location, and the values of Openness to Change and Hedonism, all predicted threat perception, which in turn predicted behavioural change and relationship contact. Such findings point to the important role social psychologists should play in understanding responses to these new terrorist threats

Development of an aeroelastic stability boundary for a rotor in autorotation

<p>For the present study, a mathematical model AMRA was created to simulate the aeroelastic behaviour of a rotor during autorotation. Our model: Aeroelastic Model of a Rotor in Autorotation (AMRA) captures transverse bending and teeter, torsional twist and lag-wise motion of the rotor blade and hence it is used to investigate couplings between blade flapping, torsion and rotor speed. Lagrange’s method was used for the modelling of blade flapping and chord-wise bending. Torsional twist of the rotor blade was modelled with the aid of finite element method (FEM), and blade transverse bending could also be modelled in FEM. The model can switch between using a full FEM model for bending and torsion, or a FEM model for torsion and simple blade teeter, depending on the complexity that the user requires.</p> <p>The AMRA model was verified against experimental data obtained during a CAA sponsored flight test programme of the G-UNIV autogyro. Published results of modal analysis of helicopter rotor blades and other data published in open literature were used to validate the FEM model of the rotor blade. The first torsional natural frequency of the ’McCutcheon’ rotor blades was measured with the aid of high-speed camera and used for validation of the FEM model of blade torsional twist. As a further verification of the modelling method, Aérospatiale Puma helicopter rotor blade data were compared on a Southwell plot showing comparison between experimental results and AMRA estimation.</p> <p>The aeromechanical behaviour of the rotor during both axial flight and forward flight in autorotation was investigated. A significant part of the research was focused on investigation of the effect of different values of torsional and flexural stiffness, and the relative positions of blade shear centre/elastic axis and centre of mass of the blade on stability during the autorotation.</p> <p>The results obtained with the aid of the model demonstrate the interesting, and unique, characteristics of the autorotative regime - with instabilities possible in bending and torsion, but also in rotorspeed. Coupled rotor speed/flap/twist oscillations (flutter and divergence) occur if the torsional stiffness of the blade is lower than a critical value, or if the blade centre of mass is significantly aft of the blade twisting axis, as is the case in helicopter pitch-flap flutter. The instability shown here, however, is specific to the autogyro, or autorotating rotor, as it is coupled with rotorspeed, and so differs from both helicopter rotor flutter and fixed-wing flutter. The coupling with rotorspeed allows a combined flutter and divergence instability, where the rotor begins to flutter in rotorspeed, teeter angle and torsional twist and, once the rotorspeed had dropped below a critical value, then moves into divergence in flap and rotorspeed. It was found that the aeroelastic behaviour of a rotor in autorotation is significantly affected by the strong coupling of blade bending stiffness and teeter angle with rotorspeed, and the strong coupling between blade aeroelastic twist and rotor torque.</p&gt

A study of stainless steel as a material of construction for a molten salt reactor

The aim of this work was to investigate the corrosion of stainless steel within a molten salt, with the possibility that it could be used as a construction material within a molten salt fuelled nuclear reactor. Four different metal compositions were used; stainless steel 316L, stainless steel 304L, LDX2101 and iron, and these were tested in two different molten salts, LiCl-KCl-NaCl and KCl-NaCl at 600 and 750°C. Stainless steel 316L was tested for one day, one, three, four and six weeks. The samples were analysed using SEM/EDX and XRD. It was found that in general, a lithium containing spinel formed on the surface of the stainless steel, LiCrO2, with a large percentage coverage. As immersion time increased the bulk also showed signs of attack. The three week test showed the formation of five different corrosion products and analysis suggests they are a combination of numerous mixed oxides. The three week test was subsequently repeated and showed the formation of a lithium containing spinel as observed in the one week test. Further testing investigated the role of lithium in the formation of the protective layer, a LiCrO2 layer formed on stainless steel 316L in the presence of a ternary salt, whereas mixed oxides were generally observed in the binary salt. Again an anomalous result was obtained in the three week binary test, where a tabular crystal containing sodium iron and oxide was formed. Finally compositional changes were examined, and the subsequent effect they had on the corrosion layer. It was found that increasing the chromium content does not necessarily increase the surface coverage and it is likely that other elements aid in the formation of the protective layer. From the results obtained in this work it is possible that with extensive research a stainless steel, which has been specifically designed, could be utilised within a molten salt reactor

Using Semantic Ambiguity Instruction to Improve Third Graders\u27 Metalinguistic Awareness and Reading Comprehension: An Experimental Study

An experiment examined whether metalinguistic awareness involving the detection of semantic ambiguity can be taught and whether this instruction improves students\u27 reading comprehension. Lower socioeconomic status third graders (M age = 8 years, 7 months) from a variety of cultural backgrounds (N = 46) were randomly assigned to treatment and control groups. Those receiving metalinguistic ambiguity instruction learned to analyze multiple meanings of words and sentences in isolation, in riddles, and in text taken from the Amelia Bedelia series (Parish, 1979, 988). The control group received a book-reading and discussion treatment to provide special attention and to rule out Hawthorne effects. Results showed that metalinguistic ambiguity instruction was effective in teaching students to identify multiple meanings of homonyms and ambiguous sentences and to detect inconsistencies in text. Moreover, this training enhanced students\u27 reading com prehension on a paragraph-completion task but not on a multiple-choice passage-recall task, possibly because the two tests differ in the array of linguistic or cognitive correlates influencing performance. Comprehension monitoring was not found to mediate the relationship between ambiguity instruction and reading comprehension. Results carry implications for the use of language-based methods to improve reading comprehension in the classroom

The Architectural Dynamics of Encapsulated Botnet Detection (EDM)

Botnet is one of the numerous attacks ravaging the networking environment. Its approach is said to be brutal and dangerous to network infrastructures as well as client systems. Since the introduction of botnet, different design methods have been employed to solve the divergent approach but the method of taking over servers and client systems is unabated. To solve this, we first identify Mpack, ICEpack and Fiesta as enhanced IRC tool. The analysis of its role in data exchange using OSI model was carried out. This further gave the needed proposal to the development of a High level architecture representing the structural mechanism and the defensive mechanism within network server so as to control the botnet trend. Finally, the architecture was designed to respond in a proactive state when scanning and synergizing the double data verification modules in an encapsulation manner within server system

Preventing Advanced Persistent Threats in Complex Control Networks

An Advanced Persistent Threat (APT) is an emerging attack against Industrial Control and Automation Systems, that is executed over a long period of time and is difficult to detect. In this context, graph theory can be applied to model the interaction among nodes and the complex attacks affecting them, as well as to design recovery techniques that ensure the survivability of the network. Accordingly, we leverage a decision model to study how a set of hierarchically selected nodes can collaborate to detect an APT within the network, concerning the presence of changes in its topology. Moreover, we implement a response service based on redundant links that dynamically uses a secret sharing scheme and applies a flexible routing protocol depending on the severity of the attack. The ultimate goal is twofold: ensuring the reachability between nodes despite the changes and preventing the path followed by messages from being discovered.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Malware in the Future? Forecasting of Analyst Detection of Cyber Events

There have been extensive efforts in government, academia, and industry to anticipate, forecast, and mitigate cyber attacks. A common approach is time-series forecasting of cyber attacks based on data from network telescopes, honeypots, and automated intrusion detection/prevention systems. This research has uncovered key insights such as systematicity in cyber attacks. Here, we propose an alternate perspective of this problem by performing forecasting of attacks that are analyst-detected and -verified occurrences of malware. We call these instances of malware cyber event data. Specifically, our dataset was analyst-detected incidents from a large operational Computer Security Service Provider (CSSP) for the U.S. Department of Defense, which rarely relies only on automated systems. Our data set consists of weekly counts of cyber events over approximately seven years. Since all cyber events were validated by analysts, our dataset is unlikely to have false positives which are often endemic in other sources of data. Further, the higher-quality data could be used for a number for resource allocation, estimation of security resources, and the development of effective risk-management strategies. We used a Bayesian State Space Model for forecasting and found that events one week ahead could be predicted. To quantify bursts, we used a Markov model. Our findings of systematicity in analyst-detected cyber attacks are consistent with previous work using other sources. The advanced information provided by a forecast may help with threat awareness by providing a probable value and range for future cyber events one week ahead. Other potential applications for cyber event forecasting include proactive allocation of resources and capabilities for cyber defense (e.g., analyst staffing and sensor configuration) in CSSPs. Enhanced threat awareness may improve cybersecurity.Comment: Revised version resubmitted to journa