Distal dorsal forearm flap

Reinstatement and spontaneous recovery of previously extinguished nicotine-taking behavior were examined in rats. Male subjects were trained to self-administer nicotine (30 microg/kg per infusion, IV; one 60-min session per day for 3 weeks). Extinction sessions were then given for 5-10 days during which saline was substituted for nicotine. Subsequently, in the first set of tests for nicotine seeking, the reinstatement of lever presses that previously delivered nicotine was examined after priming injections of saline and nicotine (75, 150 and 300 microg/kg, SC; and 30 and 60 microg/kg, IV). In the second set of tests for nicotine-seeking, rats were tested after an additional 21-day drug-free period during which they were not exposed to the self-administration chambers (a test for the spontaneous recovery of drug seeking), and after priming injections of nicotine (150 and 300 microg/kg, SC). Reinstatement of extinguished food-reinforced behavior after exposure to nicotine was also determined. Priming injections of nicotine reinstated nicotine seeking regardless of the route of administration. In addition, previously extinguished nicotine seeking recovered spontaneously after a 21-day period during which rats were not exposed to the drug-taking environment. Nicotine also reinstated extinguished food-reinforced behavior in rats with a history of nicotine self-administration, but not in drug-naive rats. The present results extend previous work with opioid and stimulant drugs on reinstatement of drug seeking by the self-administered drug. It also appears that, as with other positive reinforcers, the mere passage of time is a sufficient condition for the spontaneous recovery of extinguished nicotine seeking.     

An analysis of fatal bicycle accidents in Victoria (Australia) with a special reference to nighttime accidents

This paper examines the fatal bicycle accidents which occurred in the period 1981-1984 in Victoria with particular emphasis on nighttime fatalities. The examination provides information on aspects of accident location, environment, problem type, time, and cyclist characteristics. The relationship between actual accidents and cyclists perceived collision danger is also investigated. The characteristics of fatal bicycle accidents are different to those of overall "casualty" accidents. A difference also exists between day and night, and between metropolitan and nonmetropolitan fatal accidents. In the metropolitan area, adult cyclists over 17 years were over-involved in fatal accidents. The proportion of cyclists involved in fatalities at night increases with increase in age. Almost 80% of nighttime accidents occurred on links on arterial roads, and the majority in the high speed limit zones (75 kph and over). A greater proportion of accidents was initiated by cyclists. In 90% of nighttime cyclist fatalities the cyclist was hit from the rear, compared with 40% in daytime. Inadequacy of bicycle and street lighting was found to be an important factor in nighttime fatalities.     

Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making

There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be designed to better fit each user's specific needs. Most studies to date, however, have looked at static visualizations. Studies considering interactive visualizations have only looked at a limited number of user characteristics, and consider either low‐level tasks (e.g., value retrieval), or high‐level tasks (in particular: discovery), but not both. This paper contributes to this line of work by looking at the impact of a large set of user characteristics on user performance with interactive visualizations, for both low and high‐level tasks. We focus on interactive visualizations that support decision making, exemplified by a visualization known as Value Charts. We include in the study two versions of ValueCharts that differ in terms of layout, to ascertain whether layout mediates the impact of individual differences and could be considered as a form of personalization. Our key findings are that (i) performance with low and high‐level tasks is affected by different user characteristics, and (ii) users with low visual working memory perform better with a horizontal layout. We discuss how these findings can inform the provision of personalized support to visualization processing.     

Are U.K. Citizens Satisfied With E-Government Services? Identifying and Testing Antecedents of Satisfaction

Citizens’ satisfaction is acknowledged as one of the most significant influences for e-government adoption and diffusion. This study examines the impact of information quality, system quality, trust, and cost on user satisfaction of e-government services. Using a survey, this study collected 1518 valid responses from e-government service adopters across the United Kingdom. Our empirical outcomes show the five factors identified in this study have a significant impact on U.K. citizens’ satisfaction with e-government services.     

DCT statistics-based digital dropout detection in degraded archived media

With the rapid development of visual digital media, the demand for better quality of service has increased the pressure on broadcasters to automate their error detection and restoration activities for preserving their archives. Digital dropout is one of the defects that affect archived visual materials and tends to occur in block by block basis (size of 8 × 8). It is well established that human visual system (HVS) is highly adapted to the statistics of its visual natural environment. Consequently, in this paper, we have formulated digital dropout detection as a classification problem which predicts block label based on statistical features. These statistical features are indicative of perceptual quality relevant to human visual perception, and allow pristine images to be distinguished from distorted ones. Here, the idea is to extract discriminant block statistical features based on discrete cosine transform (DCT) coefficients and determine an optimal neighborhood sampling strategy to enhance the discrimination ability of block representation. Since this spatial frame based approach is free from any motion computation dependency, it works perfectly in the presence of fast moving objects. Experiments are performed on video archives to evaluate the efficacy of the proposed technique.     

Toward an efficient and scalable feature selection approach for internet traffic classification

There is significant interest in the network management and industrial security community about the need to identify the “best” and most relevant features for network traffic in order to properly characterize user behaviour and predict future traffic. The ability to eliminate redundant features is an important Machine Learning (ML) task because it helps to identify the best features in order to improve the classification accuracy as well as to reduce the computational complexity related to the construction of the classifier. In practice, feature selection (FS) techniques can be used as a preprocessing step to eliminate irrelevant features and as a knowledge discovery tool to reveal the “best” features in many soft computing applications. In this paper, we investigate the advantages and disadvantages of such FS techniques with new proposed metrics (namely goodness, stability and similarity). We continue our efforts toward developing an integrated FS technique that is built on the key strengths of existing FS techniques. A novel way is proposed to identify efficiently and accurately the “best” features by first combining the results of some well-known FS techniques to find consistent features, and then use the proposed concept of support to select a smallest set of features and cover data optimality. The empirical study over ten high-dimensional network traffic data sets demonstrates significant gain in accuracy and improved run-time performance of a classifier compared to individual results produced by some well-known FS techniques.     

Assessing tropical cyclone impacts using object-based moderate spatial resolution image analysis: a case study in Bangladesh

The environmental and societal impacts of tropical cyclones could be reduced using a range of management initiatives. Remote sensing can be a cost effective, accurate, and potential tool for mapping the multiple impacts caused by tropical cyclones using high-to-moderate spatial resolution (5–30 m) satellite imagery to provide data on the following essential parameters – evacuation, relief, and management of natural resources. This study developed and evaluated an approach for assessing the impacts of tropical cyclones through object-based image analysis and moderate spatial resolution imagery. Pre- and post-cyclone maps of artificial and natural features are required for assessing the overall impacts in the landscape that could be acquired by mapping specific land cover types. We used the object-based approach to map land-cover types in pre- and post-cyclone Satellite Pour l’Observation de la Terre (SPOT) 5 image data and the post-classification comparison technique to identify changes in the particular features in the landscape. Cyclone Sidr (2007) was used to test the applicability of this approach in Sarankhola Upazila in Bangladesh. The object-based approach provided accurate results for classifying features from pre- and post-cyclone satellite images with an overall accuracy of 95.43% and 93.27%, respectively. Mapped changes identified the extent, type, and form of cyclone induced impacts. Our results indicate that 63.15% of the study area was significantly affected by cyclone Sidr. The majority of mapped damage was found in vegetation, cropped lands, settlements, and infrastructure. The damage results were verified through the high spatial resolution satellite imagery, reports and pictures that were taken after the cyclone. The methods developed may be used in future to assess the multiple impacts caused by tropical cyclones in Bangladesh and other similar environments for the purposes of tropical cyclone disaster management.     

Introducing the IA-64 architecture

Microprocessors continue on the relentless path to provide more performance. Every new innovation in computing-distributed computing on the Internet, data mining, Java programming, and multimedia data streams-requires more cycles and computing power. Even traditional applications such as databases and numerically intensive codes present increasing problem sizes that drive demand for higher performance. Design innovations, compiler technology, manufacturing process improvements, and integrated circuit advances have been driving exponential performance increases in microprocessors. To continue this growth in the future, Hewlett Packard and Intel architects examined barriers in contemporary designs and found that instruction-level parallelism (ILP) can be exploited for further performance increases. This article examines the motivation, operation, and benefits of the major features of IA-64. Intel's IA-64 manual provides a complete specification of the IA-64 architecture     

Artificial intelligence implementation in the APS process diagnostic

Thermal spray process is a technique of coating manufacturing implementing a wide variety of materials and processes. This technique is characterized by up to 150 processing parameters influencing the coating properties. The control of the coating quality is needed through the consideration of a robust methodology that takes into account the parameter interdependencies, the process variability and offers the ability to quantify the processing parameter-process response relationships. The aim of this work is to introduce a new approach based on artificial intelligence responding to these requirements. A detailed procedure is presented considering an artificial neural network (ANN) structure which encodes implicitly the physical phenomena governing the process. The implementation of such a structure was coupled to experimental results of an optic sensor controlling the powder particle fusion state before the coating formation. The optimization steps were discussed and the predicted results were compared to the experimental ones allowing the identification of the control factors.     

Electrical oscillation generation with current-induced resistivity switching in VO2 micro-channel devices

We report large amplitude modulation waveforms as large as ~ 10 V using vanadium dioxide micro-channel devices operating under current-controlled conditions. The self-sustained electrical oscillations were generated by controlling the applied current in the negative differential resistance region of the investigated devices. An appropriate value of internal capacitance was achieved as parasitic capacitance in the device structure to stabilize the electrical oscillations. This eliminates the need of an external pulsed source or any external passive component connected to the micro-channel devices. Amplitude and frequency of the oscillation were tuned by illuminating the device micro-channel with an external laser. An equivalent circuit model was developed to simulate the waveforms. A good agreement between experiment and simulation was verified.