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Digital gaming has broad appeal globally, with a reported 2.7 billion gamers worldwide. There is significant interest in using games to enhance learning, with ‘serious games’ being included in classrooms to engage adolescents’ learning across a range of domains. A systematic scoping review of serious games used for health promotion with adolescents was conducted to identify serious games, review the methods used to evaluate these games, and outline evidence available to support the efficacy of these games in improving knowledge, beliefs/attitudes and behaviours in the target groups. Player engagement/enjoyment was reported if assessed. A total of 21 studies were found to have met the inclusion criteria domains: ‘healthy lifestyle’ ‘sexual health’ and ‘substance use’. A heterogenous approach across studies to game design and development, duration of game play, use of a control group and measurement of outcome(s) was observed. Game efficacy was difficult to assess due to broad generalisations and lack of consistent evaluation methods. Several studies demonstrate serious games can be engaging and pedagogically effective as a learning device and behaviour-change agent. Several studies, however, had less rigorous evaluation and lacked longer-term follow up. The ability for developers to demonstrate positive short- and long-term impacts of serious games with high-quality evidence is essential to the ongoing acceptance and use of these serious games as part of the school curriculum.

Sarcoidosis is a systemic inflammatory disease of unknown etiology, which can affect almost any organ. Cardiac involvement determines the prognosis of the affected individuals. Its prevalence in patients with extracardiac sarcoidosis with the absence of cardiac symptoms remains unclear. Cardiac magnetic resonance (CMR) provides excellent diagnostic accuracy in the detection of heart involvement by sarcoidosis.We sought to determine the prevalence of cardiac sarcoidosis in asymptomatic individuals with newly diagnosed extracardiac sarcoidosis using CMR.We prospectively evaluated 55 consecutive patients including 23 women with newly diagnosed extracardiac sarcoidosis who underwent contrast-enhanced CMR and had no symptoms of heart disease. The mean (standard deviation) age of patients was 43 (11) years. The presence of myocardial late gadolinium enhancement (LGE) of non-ischemic etiology on CMR examination was considered diagnostic for cardiac sarcoidosis.In 3 (6%) patients, the LGE pattern consistent with cardiac sarcoidosis was detected. In all patients, preserved left ventricular systolic regional and global function was present, and in none of them, the elevation of blood biomarkers of myocardial injury or overload was found.Our study suggests that the prevalence of cardiac involvement in patients with newly diagnosed extracardiac sarcoidosis and no symptoms of heart disease is very low as assessed by CMR. However, CMR may be considered as part of routine evaluation of patients with extracardiac sarcoidosis due to its higher diagnostic yield in comparison with echocardiography and electrocardiography, respectively.

In this paper we address the problem of automatically discovering optimal tactics in a combat scenario in which two opposing sides control a number of fighting units. Our approach is based on the evolution of behaviour trees, combined with simulation-based evaluation of solutions to drive the evolution. Our behaviour trees use a small set of possible actions that can be assigned to a combat unit, along with standard behaviour tree constructs and a novel approach for selecting which action from the tree is performed. A set of test scenarios was designed for which an optimal strategy is known from the literature. These scenarios were used to explore and evaluate our approach. The results indicate that it is possible, from the small set of possible unit actions, for a complex strategy to emerge through evolution. Combat units with different capabilities were observed exhibiting coordinated team work and exploiting aspects of the environment.

BACKGROUND In this study, we examined nutrition‐related topics among adolescent students attending schools with different Indices of Community Socio‐Educational Advantage (ICSEA). METHOD Participating students (N = 206) from 5 schools in Western Australia completed a paper‐based questionnaire on nutrition‐related topics. Frequencies and independent chi‐square tests were used to identify differences between sexes and school ICSEA. RESULTS Of the participating students, 75% were interested in learning about 8 of 16 topics. We found statistically significant differences by sex (p

This article describes a set of proposed measures for characterizing areas within a virtual terrain in terms of their attributes and their relationships with other areas for incorporating game designers’ intent in gameplay requirement-based terrain generation. Examples of such gameplay elements include vantage point, strongholds, chokepoints and hidden areas. Our measures are constructed on characteristics of an isovist, that is, the volume of visible space at a local area and the connectivity of areas within the terrain. The calculation of these measures is detailed, in particular we introduce two new ways to accurately and efficiently calculate the 3D isovist volume. Unlike previous research that has mainly focused on aesthetic-based terrain generation, the proposed measures address a gap in gameplay requirement-based terrain generation – the need for a flexible mechanism to automatically parameterise specified areas and their associated relationships, capturing semantic knowledge relating to high level user intent associated with specific gameplay elements within the virtual terrain. We demonstrate applications of using the measures in an evolutionary process to automatically generate terrains that include specific gameplay elements as defined by a game designer. This is significant as this shows that the measures can characterize different gameplay elements and allow gameplay elements consistent with the designers’ intents to be generated and positioned in a virtual terrain without the need to specify low-level details at a model or logic level, hence leading to higher productivity and lower cost.

Fabry disease (FD) is a rare X-linked disorder of glycosphingolipid metabolism caused by pathogenic variants within the alpha-galactosidase A (GLA) gene, often leading to neurological manifestations including stroke. Multiple screening programs seeking GLA variants among stroke survivors lacked detailed phenotype description, making the interpretation of the detected variant’s pathogenicity difficult. Here, we describe detailed clinical characteristics of GLA variant carriers identified by a nationwide stroke screening program in the Czech Republic. A total of 23 individuals with 8 different GLA variants were included in the study. A comprehensive diagnostic workup was performed by a team of FD specialists. The investigation led to the suggestion of phenotype reclassification for the G325S mutation from late-onset to classical. A novel variant R30K was found and was classified as a variant of unknown significance (VUS). The typical manifestation in our FD patients was a stroke occurring in the posterior circulation with an accompanying pathological finding in the cerebrospinal fluid. Moreover, we confirmed that cornea verticillata is typically associated with classical variants. Our findings underline the importance of detailed phenotype description and data sharing in the correct identification of pathogenicity of gene variants detected by high-risk-population screening programs.

We present a software package for analysing body positions of a subject when they are lying or sleeping in their bed. The software is designed to interface to inexpensive sensors, such as the Microsoft Kinect, and is thus suitable for monitoring at the subjects own home, rather than a dedicated sleep lab. The system is invariant to bed clothing and levels of ambient lighting. Analysis time for a single night session is under five minutes, a significant improvement over the 30–60 min analysis time reported in the literature. Keywords: Lying position, Body position, Automated analysis

Bacground: Cardiac magnetic resonance imaging (MRI) represents the gold standard in noninvasive evaluation of myocardial tissue. However, some patients are unable to undergo cardiac MRI due to a variety of reasons. Aims: We sought to determine the diagnostic accuracy of routinely performed contrast‑enhanced computed tomography (CECT) compared with cardiac MRI in the evaluation of myocardial tissue. Methods: We retrospectively evaluated 96 consecutive patients (mean [SD] age, 51 [15] years; 41 women) who underwent both CECT and cardiac MRI within 30 days. All CECT scans that visualized the entire heart were analyzed, regardless of the indication for and protocol of the procedure. The presence of late gadolinium enhancement on cardiac MRI was compared with the finding of myocardial hypoattenuation on computed tomography scans. Results: With cardiac MRI as the gold standard, CECT revealed a per‑patient sensitivity of 66%, specificity of 89%, positive predictive value of 75%, negative predictive value of 84%, and accuracy of 81%. Per‑segment sensitivity was 54%; specificity, 98%; positive predictive value, 76%; negative predictive value, 94%; and accuracy, 92%. Conclusions: Our study suggests that routinely performed CECT has high specificity, but only moderate sensitivity, compared with cardiac MRI in the evaluation of myocardial tissue. This result supports the recommendation that all CECT scans that visualize the entire heart should be analyzed for myocardial tissue pathology.

The automatic generation of behavioural models for intelligent agents in military simulation and experimentation remains a challenge. Genetic Algorithms are a global optimization approach which is suitable for addressing complex problems where locating the global optimum is a difficult task. Unlike traditional optimisation techniques such as hill-climbing or derivatives-based methods, Genetic Algorithms are robust for addressing highly multi-modal and discontinuous search landscapes. In this paper, we outline a simheuristic GA-based approach for automatic generation of finite state machine based behavioural models of intelligent agents, where the aim is the identification of novel combat tactics. Rather than evolving states, the proposed approach evolves a sequence of transitions. We also discuss workable starting points for the use of Genetic Algorithms for such scenarios, shedding some light on the associated design and implementation difficulties. Keywords: Simheuristics, Genetic algorithms, Multiagent simulations, Stochastic combinatorial optimization, Finite state machines

BACKGROUND AND PURPOSE: Potential differences between primary progressive and relapsing remitting multiple sclerosis are the subject of ongoing controversial discussions. The aim of this work was to determine whether and how primary-progressive and relapsing-remitting multiple sclerosis subtypes differ regarding conventional MR imaging parameters, cerebral iron deposits, and their association with clinical status. MATERIALS AND METHODS: We analyzed 24 patients with primary-progressive MS, 80 with relapsing-remitting MS, and 20 healthy controls with 1.5T MR imaging for assessment of the conventional quantitative parameters: T2 lesion load, T1 lesion load, brain parenchymal fraction, and corpus callosum volume. Quantitative susceptibility mapping was performed to estimate iron concentration in the deep gray matter. RESULTS: Decreased susceptibility within the thalamus in relapsing-remitting MS compared with primary-progressive MS was the only significant MR imaging difference between these MS subtypes. In the relapsing-remitting MS subgroup, the Expanded Disability Status Scale score was positively associated with conventional parameters reflecting white matter lesions and brain atrophy and with iron in the putamen and caudate nucleus. A positive association with putaminal iron and the Expanded Disability Status Scale score was found in primary-progressive MS. CONCLUSIONS: Susceptibility in the thalamus might provide additional support for the differentiation between primary-progressive and relapsing-remitting MS. That the Expanded Disability Status Scale score was associated with conventional MR imaging parameters and iron concentrations in several deep gray matter regions in relapsing-remitting MS, while only a weak association with putaminal iron was observed in primary-progressive MS suggests different driving forces of disability in these MS subtypes.

Mark Brogan and Martin Masek teach and research in the School of Computer and Security Science at Edith Cowan University. Dr Brogan teaches and researches enterprise information management and digital recordkeeping. With Associate Professor Karen Murcia, Dr Masek coordinates research activity in ECU’s Research Centre for Transformational Games. 1 This paper describes outcomes from user acceptance testing of AE2 Commander 2 – a docugame released as alpha software in April 2011 by ECU’s Research Centre for Transformational Games. Docugames form a genre of serious games that employ digitised copy of historical sources as part of the game narrative. The design and development of AE2 Commander began in 2009, when the authors received an Ian MacLean Award 3 from the National Archives of Australia (NAA) to build an authentic role-play game based on the exploits of the World War I Australian submarine AE2. The design brief required the designers to develop a strategy for incorporating digitised copy of archival r...

Kasuistika dokumentuje klinický průběh, výsledky zobrazovacich vysetřeni a pitevni nalez nemocneho s metastatickým postiženim vsech srdecnich struktur jako prvni manifestaci plicniho adenokarcinomu.

In the last decade, there has been increasing evidence that comprehensive evaluation of the left atrium is of utmost importance. Numerous studies have clearly demonstrated the prognostic value of left atrial volume for long-term outcome. Furthermore, advances in catheter ablation procedures used for the treatment of drug-refractory atrial fibrillation require the need for detailed knowledge of left atrial and pulmonary venous morphology as well of atrial wall characteristics. This review article discusses the role of cardiac magnetic resonance and computed tomography in assessment of left atrial size, its normal and abnormal morphology, and function. Special interest is paid to the utility of these rapidly involving noninvasive imaging methods before and after atrial fibrillation ablation.

The addition of an exercise component to computer games is a method that attempts to increase exercise compliance among the population. Various attempts at such games have been made, both commercially and as research projects, but the set of studied game mechanics that are both entertaining and provide beneficial exercise are relatively small. In our work, a game mechanic was designed for a floor-based input controller (DDR Pad). Rather than the standard mechanic usually employed for this device, our approach allows the player to explore a virtual world, requiring exertive movements on the input device in order to progress. The exercise is motivated implicitly through the game goals and a mechanism exists to control the pace of the game by monitoring the player's heart rate. In our trials, we have found that the game is engaging for the participants. The game also provides a beneficial level of exercise, with the player's heart rate, on average, rising to a level that constitutes moderate exercise after three minutes and forty seconds, and increasing from thereon.

In this study, we introduce MC-TSAR, a Monte Carlo Tree Search algorithm for strategy selection in simultaneous multistage games. We evaluate the algorithm using a battle planning scenario in which replanning is possible. We show that the algorithm can be used to select a strategy that approximates a Nash equilibrium strategy, taking into account the possibility of switching strategies part way through the execution of the scenario in the light of new information on the progress of the battle.

Coevolutionary algorithms are a special kind of evolutionary algorithm with advantages in solving certain specific kinds of problems. In particular, competitive coevolutionary algorithms can be used to study problems in which two sides compete against each other and must choose a suitable strategy. Often these problems are multimodal -- there is more than one strong strategy for each side. In this paper, we introduce a scalable multimodal test problem for competitive coevolution, and use it to investigate the effectiveness of some common coevolutionary algorithm enhancement techniques.

In this paper, we report on an experimental study in which we investigated the use of feedback mechanisms in exergames. We based the study around the Dual Flow model for exergame design, using biophysical feedback to control exercise intensity, and player performance feedback to control gameplay challenge. We found good success in controlling exercise intensity to achieve an effective workout, while controlling gameplay challenge to improve enjoyment and attractiveness was problematic. We offer some possible reasons for this, suggesting the need for further investigation.

Threats to critical infrastructure are not passive. Trying to identify what is in fact ’critical’ is proving to be very difficult as threats constantly evolve. A major benefit of simulating the infrastructure is that security tests and risk modelling can be applied before infrastructure is built or its environment modified, allowing for lower cost design alterations to minimise vulnerabilities. By using the 3D environment of an existing Game Engine we can explore several possibilities for security analysis that existing tools, due to their global view of the problem, do not allow. Providing participants with a first-person view of the situation allows for more realistic role-play, whilst the networked gaming technology allows remote experts to interact in an intuitive environment and explore, identify and assess the critical components of the infrastructure.

The scanning and computerized processing of images hadits birth in 1956 at the National Bureau of Standards (NBS,nowNationalInstituteofStandardsandTechnology(NIST))[1].Image enhancementalgorithms weresome of the first tobe developed [2]. Half a century later, literally thousands ofimage processing algorithms have been published. Some ofthese have been specific to certain applications such as theenhancement of latent fingerprints, whilst others have beenmore generic in nature, applicable to all, yet master of none.The scope of these algorithms is fairly expansive, rangingfrom automatically extracting and delineating regions of in-terest such as in the case of segmentation, to improving theperceived quality of an image, by means of image enhance-ment. Since the early years of image processing, as in manysubfields of software design, there has been a portion of thedesign process dedicated to algorithm testing. Testing is theprocessofdeterminingwhetherornotaparticularalgorithmhassatisfieditsspecificationsrelatingtocriteriasuchasaccu-racy and robustness. A major limitation in the design of im-ageprocessingalgorithmsliesinthedifficultyindemonstrat-ingthatalgorithmsworktoanacceptablemeasureofperfor-mance. The purpose of algorithm testing is two-fold. Firstlyit provides either a qualitative or a quantitative method ofevaluating an algorithm. Secondly, it provides a comparativemeasure of the algorithm against similar algorithms, assum-ing similar criteria are used. One of the greatest caveats indesigning algorithms incorporating image processing is howtoconceivethecriteriausedtoanalyzetheresults.Dowede-signacriterionwhichmeasuressensitivity,robustness,orac-curacy? Performance evaluation in the broadest sense refersto a measure of some required behavior of an algorithm,whether it is achievable accuracy, robustness, or adaptabil-ity. It allows the intrinsic characteristics of an algorithm tobe emphasized, as well as the evaluation of its benefits andlimitations.More often than not though, such testing has been lim-ited in its scope. Part of this is attributable to the actual lackof formal process used in performance evaluation of im-age processing algorithms, from the establishment of testingregimes, to the design of metrics. Selection of an appropri-ate evaluation methodology is dependent on the objectiveof the task. For example, in the context of image enhance-ment, requirements are essentially different for screen-basedenhancementandenhancementwhichisembeddedwithinasubalgorithm. Screen-based enhancement is usually assessedinasubjectivemanner,whereaswhenanalgorithmisencap-sulated within a larger system, subjective evaluation is notavailable,andthealgorithmitselfmustdeterminethequalityof a processed image. Very few approaches to the evaluationofimageprocessingalgorithmscanbefoundintheliterature,although the concept has been around for decades. A signif-icant difficulty which arises in the evaluation of algorithmsis finding suitable metrics which provide an objective mea-sure of performance. A performance metric is a meaningfuland computable measure used for quantitatively evaluatingthe performance of any algorithm. Consider the process ofassessing image quality. There is no single quantitative met-ric which correlates well with image quality as perceived bythe human visual system. The process of analyzing failure isintrinsically coupled with the process of performance evalu-ation.Inordertoascertainwhetheranalgorithmfailsornot,youhavetodefinethecharacteristicsofsuccess.Failureanal-ysisistheprocessofdeterminingwhyanalgorithmfailsdur-ing testing. The knowledge generated is then fed back to thedesign process in order to engender refinements in the algo-rithm.Thisisadifficultprocessinapplicationssuchasimageenhancement primarily because there is usually no referenceimagewhichcanbeusedasan“ideal”image.Theassessmentofimagequalityplaysanimportantroleinapplicationssuchas consumer electronics. Metrics could be used to monitororoptimizeimagequalityindigitalcameras,benchmarkandevaluate image enhancement algorithms. There is no singlemetric that correlates well with image quality as perceivedby the human visual system. Selection of an appropriate

A threshold-based algorithm is presented for the extraction of the pectoral muscle edge in mediolateral oblique view mammograms. The minimum cross-entropy thresholding algorithm is applied to local areas around the pectoral muscle to determine a series of thresholds as a function of area size. Using a model image it is shown that art inflection point in this function corresponds to a threshold that will separate the pectoral muscle from the rest of the breast. Post processing is performed on mammograms to eliminate false positive points of inflection and a straight line is fitted to the detected pectoral boundary in order to smooth jaggedness caused by the non-uniform intensity of the pectoral muscle edge.