The elaborated intrusion theory of desire : a 10-year retrospective and implications for addiction treatments

Introduction: Ten years after the publication of Elaborated Intrusion (EI) Theory, there is now substantial research into its key predictions. The distinction between intrusive thoughts, which are driven by automatic processes, and their elaboration, involving controlled processing, is well established. Desires for both addictive substances and other desired targets are typically marked by imagery, especially when they are intense. Attention training strategies such as body scanning reduce intrusive thoughts, while concurrent tasks that introduce competing sensory information interfere with elaboration, especially if they compete for the same limited-capacity working memory resources. Conclusion: EI Theory has spawned new assessment instruments that are performing strongly and offer the ability to more clearly delineate craving from correlated processes. It has also inspired new approaches to treatment. In particular, training people to use vivid sensory imagery for functional goals holds promise as an intervention for substance misuse, since it is likely to both sustain motivation and moderate craving.

Ultraviolet bands of mercury bromide

The ultraviolet bands of mercury bromide have been excited in uncondensed discharge and photographed with a quartz Littrow spectrograph. The class II system, lying between\lambda 2900 å to 2700 å, suggested byWieland as due to the triatomic molecule, has been studied in detail and ascribed to the diatomic molecule. The bands in the regionlambda 2900 å to 2770å have been analysed into two systems which may form the two components of a2 II –2 \sigma electronic transition with a2 II interval equal to 969·4 cm–1.Another system most probably due to2 \sigma–2 \sigma has been observed in the region\lambda 2770 to 2720.

Free convection heat transfer to mercury in vertical annuli

Data on free convection heat transfer to water and mercury are collected using a test rig in vertical annuli of three radii ratios, the walls of which are maintained at uniform temperatures. A theoretical analysis of the boundary layer equations has been attempted using local similarity transformation and double boundary layer approach. Correlations derived from the present theoretical analysis are compared with the analysis and the experimental data available in literature for non-metallic fluids and also with the present experimental data on water and mercury. Generalised correlations are set up for expressing the ratio of heat transferred by convection to the heat transferred by pure conduction and Nusselt's number, in terms of Grashof, Rayleigh and Prandtl numbers, based on the theoretical analysis and the present data on mercury and water. The present generalised correlations agree with the reported and present data for non-metallic fluids and liquid metals with an average deviation of 9% and maximum deviation of ± 13.7%.

Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

Large scale surveys suggest limited mercury availability in tropical north Queensland (Australia)

Little is known about the threat of mercury (Hg) to consumers in food webs of Australia's wet-dry tropics. This is despite high concentrations in similar biomes elsewhere and a recent history of gold mining that could lead to a high degree of exposure for biota. We analysed Hg in water, sediments, invertebrates and fishes in rivers and estuaries of north Queensland, Australia to determine its availability and biomagnification in food webs. Concentrations in water and sediments were low relative to other regions of Hg concern, with only four of 138 water samples and five of 60 sediment samples above detection limits of 0.1 mu g L-1 and 01 mu g g(-1), respectively. Concentrations of Hg in fishes and invertebrates from riverine and wetland food webs were well below international consumption guidelines, including those in piscivorous fishes, likely due to low baseline concentrations and limited rates of biomagnification (average slope of log Hg vs. delta N-15 = 0.08). A large fish species of recreational, commercial, and cultural importance (the barramundi, Lates calcarifer), had low concentrations that were below consumption guidelines. Observed variation in Hg concentrations in this species was primarily explained by age and foraging location (floodplain vs. coastal), with floodplain feeders having higher Hg concentrations than those foraging at sea. These analyses suggest that there is a limited threat of Hg exposure for fish-eating consumers in this region. (C) 2011 Published by Elsevier B.V.

Intrusion warning and assessment method for site safety enhancement

Intrusion (unauthorized stepping-into/staying-in a hazardous area), as a common type of near-miss, is the prime cause of the majority of incidents on construction sites including fall from heights, and striking against or being struck by moving objects. Accidents often occur because workers take shortcuts moving about the site without fully perceiving the potential dangers. A number of researches have been devoted to developing methods to prevent such behaviors mainly based on the theory of Behavior-Based Safety (BBS), which aims to cultivate safety behaviors among workers in accordance with safety regulations. In current BBS practice, trained observers and safety supervisors are responsible for safety behavior inspections following safety plans and operation regulations. The observation process is time-consuming and its effectiveness depends largely on the observer’s safety knowledge and experience, which often results in omissions or bias. This paper presents a reformed safety behavior modification approach by integrating a location-based technology with BBS. Firstly, a detailed background is provided, covering current intrusion problems on site, existing use of BBS for behavior improvement, difficulties in achieving widespread adoption and potential technologies for location tracking and in-time feedback. Then, a conceptual framework of positioning technology-enhanced BBS is developed, followed by details of the corresponding on-line supporting system, Real Time Location System (RTLS) and Virtual Construction System (VCS). The application of the system is then demonstrated and tested in a construction site in Hong Kong. Final comments are made concerning further research direction and prospects for wider adoption.

Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

A method of fraud & intrusion detection for e-payment systems in mobile

The need for paying with mobile devices has urged the development of payment systems for mobile electronic commerce. In this paper we have considered two important abuses in electronic payments systems for detection. The fraud, which is an intentional deception accomplished to secure an unfair gain, and an intrusion which are any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. Most of the available fraud and intrusion detection systems for e-payments are specific to the systems where they have been incorporated. This paper proposes a generic model called as Activity-Event-Symptoms(AES) model for detecting fraud and intrusion attacks which appears during payment process in the mobile commerce environment. The AES model is designed to identify the symptoms of fraud and intrusions by observing various events/transactions occurs during mobile commerce activity. The symptoms identification is followed by computing the suspicion factors for event attributes, and the certainty factor for a fraud and intrusion is generated using these suspicion factors. We have tested the proposed system by conducting various case studies, on the in-house established mobile commerce environment over wired and wire-less networks test bed.

Optimal sleep-wake scheduling for quickest intrusion detection using sensor networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Usefulness of DARPA dataset for intrusion detection system evaluation

The MIT Lincoln Laboratory IDS evaluation methodology is a practical solution in terms of evaluating the performance of Intrusion Detection Systems, which has contributed tremendously to the research progress in that field. The DARPA IDS evaluation dataset has been criticized and considered by many as a very outdated dataset, unable to accommodate the latest trend in attacks. Then naturally the question arises as to whether the detection systems have improved beyond detecting these old level of attacks. If not, is it worth thinking of this dataset as obsolete? The paper presented here tries to provide supporting facts for the use of the DARPA IDS evaluation dataset. The two commonly used signature-based IDSs, Snort and Cisco IDS, and two anomaly detectors, the PHAD and the ALAD, are made use of for this evaluation purpose and the results support the usefulness of DARPA dataset for IDS evaluation.