Impact of virtual atmospherics and functional qualities on the online gambler's experience

This study empirically tests a stimulus–organism–response (S–O–R) structural model that proposes that an online casino's atmospheric cues and functional qualities influence individuals' affective and cognitive responses, which in turn impact consumer behavioural intentions. Using self-reported data from a primarily US-based sample, analysed elements of the online gambling site stimulus included high and low task-relevant cues, financial trust, and gambling value. Demographic characteristics were found to moderate the relationship between the stimulus and internal satisfaction, with demographic group differences found among all stimulus constructs. Results emphasise the significant role that atmospherics and functional qualities play in generating positive behaviours from online gamblers, with additional implications in marketplace competitiveness and in responsible gambling practices.     

Irish Archaeological Data: Toward a Framework

The EU co-funded project Advanced Research Infrastructure for Archaeological Dataset Networking in Europe (ARIADNE) aims to integrate data and services across Europe for the archaeological research community. The Discovery Programme has investigated data holdings and management practices in Irish archaeology, focusing on what information is available in physical and digital forms, approaches to preservation and accessibility, and the challenges and opportunities around dataset networking with Irish archaeological data. While significant work will be required to enable the accessibility expected by researchers now and in future, there is also an opportunity to approach the challenges of digital preservation as a community.     

Modeling and multiobjective optimization of traction performance for autonomous wheeled mobile robot in rough terrain

Application of terrain-vehicle mechanics for determination and prediction of mobility performance of autonomous wheeled mobile robot(AWMR) in rough terrain is a new research area currently receiving much attention for both terrestrial and planetary missions due to its significant role in design,evaluation,optimization,and motion control of AWMRs.In this paper,decoupled closed form terramechanics considering important wheel-terrain parameters is applied to model and predict traction.Numerical analysis of traction performance in terms of drawbar pull,tractive efficiency,and driving torque is carried out for wheels of different radii,widths,and lug heights,under different wheel slips.Effects of normal forces on wheels are analyzed.Results presented in figures are discussed and used to draw some conclusions.Furthermore,a multiobjective optimization(MOO) method for achieving optimal mobility is presented.The MOO problem is formulated based on five independent variables including wheel radius r,width b,lug height h,wheel slip s,and wheel rotation angle θ with three objectives to maximize drawbar pull and tractive efficiency while minimizing the dynamic traction ratio.Genetic algorithm in MATLAB is used to obtain optimized wheel design and traction control parameters such as drawbar pull,tractive efficiency,and dynamic traction ratio required for good mobility performance.Comparison of MOO results with experimental results shows a good agreement.A method to apply the MOO results for online traction and mobility prediction and control is discussed.     

Development of a high pressure automated lag time apparatus for experimental studies and statistical analyses of nucleation and growth of gas hydrates

Nucleation in a supercooled or a supersaturated medium is a stochastic event, and hence statistical analyses are required for the understanding and prediction of such events. The development of reliable statistical methods for quantifying nucleation probability is highly desirable for applications where control of nucleation is required. The nucleation of gas hydrates in supercooled conditions is one such application. We describe the design and development of a high pressure automated lag time apparatus (HP-ALTA) for the statistical study of gas hydrate nucleation and growth at elevated gas pressures. The apparatus allows a small volume (≈150 μl) of water to be cooled at a controlled rate in a pressurized gas atmosphere, and the temperature of gas hydrate nucleation, T(f), to be detected. The instrument then raises the sample temperature under controlled conditions to facilitate dissociation of the gas hydrate before repeating the cooling-nucleation cycle again. This process of forming and dissociating gas hydrates can be automatically repeated for a statistically significant (>100) number of nucleation events. The HP-ALTA can be operated in two modes, one for the detection of hydrate in the bulk of the sample, under a stirring action, and the other for the detection of the formation of hydrate films across the water-gas interface of a quiescent sample. The technique can be applied to the study of several parameters, such as gas pressure, cooling rate and gas composition, on the gas hydrate nucleation probability distribution for supercooled water samples.     

Ketamine effects on the urogenital system--changes in the urinary bladder and sperm motility

Different doses of ketamine (10 mg/kg, 20 mg/kg, 30 mg/kg, 40 mg/kg, 50 mg/kg, and 60 mg/kg) were injected i.p. (I.P.), respectively, to male ICR mice to determine the optimal dosage for chronic administration. At and above 40 mg/kg I.P. injection, mice had almost no hindlimb movement during swimming test. Subsequently, 30 mg/kg was used as the dose for the study in the toxicity of long-term ketamine administration on urinary bladder and sperm motility. The treatment group were subdivided into two (n = 10 each group); one received daily ketamine treatment i.p. for 3 months and another group for 6 months. Corresponding number of mice in control groups (n = 5 each group) received saline injection instead of ketamine. Terminal dUTP nick and labeling (TUNEL) study and Sirius red staining were carried out on the sectioned slides of the urinary bladders to study the degree of apoptosis in both epithelium and muscular layers of the urinary bladder and the relative thickness of the muscular layers in this organ was also computed. Apoptosis in the bladder epithelium was observed initially in the 3-month ketamine treated mice and the number of apoptotic cells was significantly different (P < 0.05) between the 3-month and 6-month ketamine treated mice and the control. The relative thickness of muscular layers in the bladder wall also decreased significantly (P < 0.05) when the 6-month treated mice and the control were compared. Sirius red staining revealed increase of collagen in the urinary bladder of the treated mice, most evidently 6 months after ketamine treatment. In addition, the sperm motility was studied and there was a statistically significant difference between the control and ketamine treated groups in the percentages of sperms which were motile (P < 0.05). This suggested that the chronic administration of ketamine affected the genital system as well.     

Features modeling with an α-stable distribution: Application to pattern recognition based on continuous belief functions

The aim of this paper is to show the interest in fitting features with an α-stable distribution to classify imperfect data. The supervised pattern recognition is thus based on the theory of continuous belief functions, which is a way to consider imprecision and uncertainty of data. The distributions of features are supposed to be unimodal and estimated by a single Gaussian and α-stable model. Experimental results are first obtained from synthetic data by combining two features of one dimension and by considering a vector of two features. Mass functions are calculated from plausibility functions by using the generalized Bayes theorem. The same study is applied to the automatic classification of three types of sea floor (rock, silt and sand) with features acquired by a mono-beam echo-sounder. We evaluate the quality of the α-stable model and the Gaussian model by analyzing qualitative results, using a Kolmogorov–Smirnov test (K–S test), and quantitative results with classification rates. The performances of the belief classifier are compared with a Bayesian approach.     

Static virtualization of C source code

Many existing systems are written in C and are not re‐entrant or thread safe. Sometimes these systems are required in a context for which they were not first designed, possibly meaning they now need to be re‐entrant. This article introduces a program that filters C source code, modifying shared resources (the global variables) to make the code re‐entrant: ‘virtualizing’ the code. The code is then compiled as normal. This approach allows programmatic virtualization with little cost at runtime. Copyright © 2007 John Wiley & Sons, Ltd.     

Achieving accurate and context‐sensitive timing for code optimization

Key computational kernels must run near their peak efficiency for most high‐performance computing (HPC) applications. Getting this level of efficiency has always required extensive tuning of the kernel on a particular platform of interest. The success or failure of an optimization is usually measured by invoking a timer. Understanding how to build reliable and context‐sensitive timers is one of the most neglected areas in HPC, and this results in a host of HPC software that looks good when reported in the papers, but delivers only a fraction of the reported performance when used by actual HPC applications. In this paper, we motivate the importance of timer design and then discuss the techniques and methodologies we have developed in order to accurately time HPC kernel routines for our well‐known empirical tuning framework, ATLAS. Copyright © 2008 John Wiley & Sons, Ltd.