Introduction: Cannabis use frequently co-occurs with gambling, and evidence indicates that both acute and chronic cannabis use may influence gambling behavior. The primary aim of the present study was to further contribute to the literature on this relationship by examining data collected from a Canadian national study of gambling.Methods: Respondents consisted of 10,054 Canadian gamblers recruited from Leger Opinion's (LEO) online panel. In this study, gamblers who used cannabis were compared with non-users across a number of gambling as well as demographic and mental health variables.Results: Of the total sample, 25.4 % reported past 12-month cannabis use. Among the 2,553 cannabis-users, 21.3 % reported daily use, and 69.9 % reported using once a month or more. A total of 56.2 % indicated they had used cannabis while gambling in the past 12 months. Bivariate analysis found significant differences between cannabis use and non-use on numerous demographic, mental health, and gambling-related variables. Individuals with greater problem gambling severity scores, more hours gambling, and a larger range of gambling activities were more likely to endorse using cannabis. Hierarchical logistic regression revealed that tobacco use, and having experienced significant child abuse were predictors of cannabis use. Non-use of cannabis was associated with older age, less engagement in online gambling, and being less likely to consume alcohol.Conclusion: The present findings both corroborate previous studies and expand upon the relationship between cannabis and gambling.

Objectives The purpose of this study is to provide an updated profile of gamblers and problem gamblers in Canada and to identify characteristics most strongly associated with problem gambling. Methods An assessment of gambling participation and problem gambling was included in the 2018 Canadian Community Health Survey and administered to 23,952 individuals 18 years and older. Descriptive statistics provided a demographic profile for each type of gambling involvement as well as category of gambler (non-gambler, non-problem gambler, at-risk gambler, problem gambler). A logistic regression identified characteristics that best distinguished problem from non-problem gamblers. Results Gambling participation and problem gambling both varied as a function of gender, income, educational attainment, and race/ethnicity. However, multivariate analysis identified electronic gambling machine (EGM) participation to be the primary predictor of problem gambling status, with race/ethnicity, presence of a mood disorder, male gender, casino table game participation, older age, a greater level of smoking, participation in speculative financial activity, instant lottery participation, lower household income, and lottery or raffle ticket participation providing additional predictive power. Provincial EGM density and EGM participation rates are also very strong predictors of provincial rates of at-risk and problem gambling. Conclusion Problem gambling has a biopsychosocial etiology, determined by personal vulnerability factors combined with the presence of riskier types of gambling such as EGMs. Effective prevention requires a multifaceted approach, but constraints on the availability and operation of EGMs would likely have the greatest single public health benefit.

This study analyzed the Responsible Gambling Check patron survey data from Canadian casinos and racinos collected from 2011-2019 (18,580 patrons and 75 venues). The results indicated increasing awareness and use over time of harm minimization tools among more frequent patrons. Despite these promising trends, it is concerning that a substantial percentage of gamblers are still unaware of the harm minimization tools available. Further, the actual impact of this awareness on responsible gambling behaviour is largely unknown. We suggest greater efforts are needed nation-wide to promote the awareness, utilization, and evaluation of these harm minimization tools.

Prior studies have identified self-regulatory strategies that are infrequently used by problem-gamblers, but which might be protective if used. However, guidelines with evidence-based safe gambling practices (SGPs) that prevent gambling-related harm are lacking. This study aimed to: 1) identify a parsimonious set of evidence-based SGPs that best predict non-harmful gambling amongst gamblers who are otherwise most susceptible to experiencing gambling harm; 2) examine how widely are they used; and 3) assess whether their use differs by gambler characteristics. A sample of 1,174 regular gamblers in Alberta Canada completed an online survey measuring uptake of 43 potential SGPs, gambling harms and numerous risk factors for harmful gambling. Elastic net regression identified a sub-sample of 577 gamblers most susceptible to gambling harm and therefore most likely to benefit from the uptake of SGPs. A second elastic net predicted gambling harm scores in the sub-sample, using the SGPs as candidate predictors. Nine SGPs best predicted non-harmful gambling amongst this sub-sample. The behaviour most strongly associated with increased harm was using credit to gamble. The behaviour most strongly associated with reduced harm was 'If I'm not having fun gambling, I stop'. These SGPs form the basis of evidence-based safe gambling guidelines which can be: 1) promoted to consumers, 2) form the basis of self-assessment tests, 3) used to measure safe gambling at a population level, and 4) inform supportive changes to policy and practice. The guidelines advise gamblers to: stop if they are not having fun, keep a household budget, keep a dedicated gambling budget, have a fixed amount they can spend, engage in other leisure activities, avoid gambling when upset or depressed, not use credit for gambling, avoid gambling to make money, and not think that strategies can help you win. These guidelines are a promising initiative to help reduce gambling-related harm.

The objective of the current study was to examine the possible temporal associations between alcohol misuse and problem gambling symptomatology from adolescence through to young adulthood. Parallel-process latent growth curve modeling was used to examine the trajectories of alcohol misuse and symptoms of problem gambling over time. Data were from a sample of adolescents recruited for the Leisure, Lifestyle, and Lifecycle Project in Alberta, Canada (n = 436), which included 4 assessments over 5 years. There was an average decline in problem gambling symptoms followed by an accelerating upward trend as the sample reached the legal age to gamble. There was significant variation in the rate of change in problem gambling symptoms over time; not all respondents followed the same trajectory. There was an average increase in alcohol misuse over time, with significant variability in baseline levels of use and the rate of change over time. The unconditional parallel process model indicated that higher baseline levels of alcohol misuse were associated with higher baseline levels of problem gambling symptoms. In addition, higher baseline levels of alcohol misuse were associated with steeper declines in problem gambling symptoms over time. However, these between-process correlations did not retain significance when covariates were added to the model, indicating that one behavior was not a risk factor for the other. The lack of mutual influence in the problem gambling symptomatology and alcohol misuse processes suggest that there are common risk factors underlying these two behaviors, supporting the notion of a syndrome model of addiction.

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

In this paper we consider the structure of dynamically evolving networks modelling information and activity moving across a large set of vertices. We adopt the communicability concept that generalizes that of centrality which is defined for static networks. We define the primary network structure within the whole as comprising of the most influential vertices (both as senders and receivers of dynamically sequenced activity). We present a methodology based on successive vertex knockouts, up to a very small fraction of the whole primary network,that can characterize the nature of the primary network as being either relatively robust and lattice-like (with redundancies built in) or relatively fragile and tree-like (with sensitivities and few redundancies). We apply these ideas to the analysis of evolving networks derived from fMRI scans of resting human brains. We show that the estimation of performance parameters via the structure tests of the corresponding primary networks is subject to less variability than that observed across a very large population of such scans. Hence the differences within the population are significant.

We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.

While much has been written about the need for governments and the gambling industry to act responsibly in their provision of gambling, only modest advances have been made to establish best practices in this area. Worldwide, few governments even approach what William Eadington, in Trends in gambling and responsible gaming in the US and elsewhere (2003, http://www.888betsoff.com/links/04presentations/Eadington.pdf), calls a stage-four level of responsible gambling stewardship, that is, the unconditional acceptance of strong measures to attenuate gambling-related harms. One of the cornerstones of a gambling regime oriented toward consumer safety and public interest is a commitment by government and the gambling industry to meet commendable standards for accountability and social responsibility. After studying the government's legislative framework for the operation and regulation of gambling in the province of Ontario (Canada), reviewing the province's gambling-related mission and public-policy statements, and interviewing key actors in the government's gambling administration, a template was developed for an optimally socially responsible and accountable gambling regime that operates in the public interest. The template, along with suggestions for improving accountability and social responsibility in the provision of gambling, is presented.

Traditional resource management has had as its main objective the optimisation of throughput, based on parameters such as CPU, memory, and network bandwidth. With the appearance of Grid Markets, new variables that determine economic expenditure, benefit and opportunity must be taken into account. The SORMA project aims to allow resource owners and consumers to exploit market mechanisms to sell and buy resources across the Grid. SORMA’s motivation is to achieve efficient resource utilisation by maximising revenue for resource providers, and minimising the cost of resource consumption within a market environment. An overriding factor in Grid markets is the need to ensure that desired Quality of Service levels meet the expectations of market participants. This paper explains the proposed use of an Economically Enhanced Resource Manager (EERM) for resource provisioning based on economic models. In particular, this paper describes techniques used by the EERM to support revenue maximisation across multiple Service Level Agreements.

A full assessment of para-­virtualization is important, because without knowledge about the various overheads, users can not understand whether using virtualization is a good idea or not. In this paper we are very interested in assessing the overheads of running various benchmarks on bare-­‐metal, as well as on para-­‐virtualization. The idea is to see what the overheads of para-­‐ virtualization are, as well as looking at the overheads of turning on monitoring and logging. The knowledge from assessing various benchmarks on these different systems will help a range of users understand the use of virtualization systems. In this paper we assess the overheads of using Xen, VMware, KVM and Citrix, see Table 1. These different virtualization systems are used extensively by cloud-­‐users. We are using various Netlib1 benchmarks, which have been developed by the University of Tennessee at Knoxville (UTK), and Oak Ridge National Laboratory (ORNL). In order to assess these virtualization systems, we run the benchmarks on bare-­‐metal, then on the para-­‐virtualization, and finally we turn on monitoring and logging. The later is important as users are interested in Service Level Agreements (SLAs) used by the Cloud providers, and the use of logging is a means of assessing the services bought and used from commercial providers. In this paper we assess the virtualization systems on three different systems. We use the Thamesblue supercomputer, the Hactar cluster and IBM JS20 blade server (see Table 2), which are all servers available at the University of Reading. A functional virtualization system is multi-­‐layered and is driven by the privileged components. Virtualization systems can host multiple guest operating systems, which run on its own domain, and the system schedules virtual CPUs and memory within each Virtual Machines (VM) to make the best use of the available resources. The guest-­‐operating system schedules each application accordingly. You can deploy virtualization as full virtualization or para-­‐virtualization. Full virtualization provides a total abstraction of the underlying physical system and creates a new virtual system, where the guest operating systems can run. No modifications are needed in the guest OS or application, e.g. the guest OS or application is not aware of the virtualized environment and runs normally. Para-­‐virualization requires user modification of the guest operating systems, which runs on the virtual machines, e.g. these guest operating systems are aware that they are running on a virtual machine, and provide near-­‐native performance. You can deploy both para-­‐virtualization and full virtualization across various virtualized systems. Para-­‐virtualization is an OS-­‐assisted virtualization; where some modifications are made in the guest operating system to enable better performance. In this kind of virtualization, the guest operating system is aware of the fact that it is running on the virtualized hardware and not on the bare hardware. In para-­‐virtualization, the device drivers in the guest operating system coordinate the device drivers of host operating system and reduce the performance overheads. The use of para-­‐virtualization [0] is intended to avoid the bottleneck associated with slow hardware interrupts that exist when full virtualization is employed. It has revealed [0] that para-­‐ virtualization does not impose significant performance overhead in high performance computing, and this in turn this has implications for the use of cloud computing for hosting HPC applications. The “apparent” improvement in virtualization has led us to formulate the hypothesis that certain classes of HPC applications should be able to execute in a cloud environment, with minimal performance degradation. In order to support this hypothesis, first it is necessary to define exactly what is meant by a “class” of application, and secondly it will be necessary to observe application performance, both within a virtual machine and when executing on bare hardware. A further potential complication is associated with the need for Cloud service providers to support Service Level Agreements (SLA), so that system utilisation can be audited.

Tycho was conceived in 2003 in response to a need by the GridRM [1] resource-monitoring project for a “light-weight”, scalable and easy to use wide-area distributed registry and messaging system. Since Tycho’s first release in 2006 a number of modifications have been made to the system to make it easier to use and more flexible. Since its inception, Tycho has been utilised across a number of application domains including widearea resource monitoring, distributed queries across archival databases, providing services for the nodes of a Cray supercomputer, and as a system for transferring multi-terabyte scientific datasets across the Internet. This paper provides an overview of the initial Tycho system, describes a number of applications that utilise Tycho, discusses a number of new utilities, and how the Tycho infrastructure has evolved in response to experience of building applications with it.

Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware or faulty system or application software. Monitoring systems such as GridRM provide the ability to connect to any number of different types of monitoring agents and provide different views of the system, based on a client's particular preferences. Web 2.0 technologies, and in particular 'mashups', are emerging as a promising technique for rapidly constructing rich user interfaces, that combine and present data in intuitive ways. This paper describes a Web 2.0 user interface that was created to expose resource data harvested by the GridRM resource monitoring system.

Economic mechanisms enhance technological solutions by setting the right incentives to reveal information about demand and supply accurately. Market or pricing mechanisms are ones that foster information exchange and can therefore attain efficient allocation. By assigning a value (also called utility) to their service requests, users can reveal their relative urgency or costs to the service. The implementation of theoretical sound models induce further complex challenges. The EU-funded project SORMA analyzes these challenges and provides a prototype as a proof-of-concept. In this paper the approach within the SORMA-project is described on both conceptual and technical level.

Resource monitoring in distributed systems isrequired to understand the ‘health’ of the overallsystem and to help identify particular problems, suchas dysfunctional hardware, a faulty system orapplication software. Desirable characteristics formonitoring systems are the ability to connect to anynumber of different types of monitoring agents and toprovide different views of the system, based on aclient’s particular preferences. This paper outlines anddiscusses the ongoing activities within the GridRMwide-area resource-monitoring project.

In any wide-area distributed system there is a need to communicate and interact with a range of networked devices and services ranging from computer-based ones (CPU, memory and disk), to network components (hubs, routers, gateways) and specialised data sources (embedded devices, sensors, data-feeds). In order for the ensemble of underlying technologies to provide an environment suitable for virtual organisations to flourish, the resources that comprise the fabric of the Grid must be monitored in a seamless manner that abstracts away from the underlying complexity. Furthermore, as various competing Grid middleware offerings are released and evolve, an independent overarching monitoring service should act as a corner stone that ties these systems together. GridRM is a standards-based approach that is independent of any given middleware and that can utilise legacy and emerging resource-monitoring technologies. The main objective of the project is to produce a standardised and extensible architecture that provides seamless mechanisms to interact with native monitoring agents across heterogeneous resources.