Video Game Evaluation Based on Player Decision Cycles

In this thesis we describe a three pronged framework that captures the important aspects of player engagement in a video game. The focus of the framework is the Player Decision Cycle, which refers to the overlapping decisions that players make during game play. These various decisions must be made many times, but each type of decision has to be made at different rates. These decisions interact to produce the pacing of the gameplay experience. To illustrate the framework we have designed and implemented two prototype RPGs. These two RPGs are Dragon Mist and Radium Seas. These games exemplify adherence to the Player Decision Cycle framework presented in this thesis

Vegetation structure influences predation rates of early nests in subarctic breeding waders

Ground-nesting species are vulnerable to a wide range of predators and often experience very high levels of nest predation. Strategies to reduce nest vulnerability can include concealing nests in vegetation and/or nesting in locations in which nests and eggs are camouflaged and less easy for predators to locate. These strategies could have important implications for the distribution of ground-nesting species and the success rates of nests in areas with differing vegetation structure. However, the factors influencing the success of nest concealment and camouflage strategies in ground-nesting species are complex. Here we explore the effects of local vegetation structure and extent of nest concealment on nest predation rates in a range of ground-nesting, sympatric wader species with differing nest concealment strategies (open-nest species: Oystercatcher Haematopus ostralegus, Golden Plover Pluvialis apricaria and Whimbrel Numenius phaeopus; concealed-nest species: Black-tailed Godwit Limosa limosa, Redshank Tringa totanus and Snipe Gallinago gallinago) in south Iceland, in landscapes that comprise substantial variability in vegetation structure at a range of scales. We monitored 469 nests of these six wader species in 2015 and 2016 and ~40% of these nests were predated. Nest predation rates were similar for open-nest and concealed-nest species and did not vary with vegetation structure in the surrounding landscape, but nest-concealing species were ~10% more likely to have nests predated when they were poorly concealed, and the frequency of poorly concealed nests was higher in colder conditions at the start of the breeding season. For concealed-nest species, the reduced capacity to hide nests in colder conditions is likely to reflect low rates of vegetation growth in such conditions. The ongoing trend for warmer springs at subarctic latitudes could result in more rapid vegetation growth, with consequent increases in the success rates of early nests of concealed-nest species. Temperature-related effects on nest concealment from predators could thus be an important mechanism through which climate change affecting vegetation could have population-level impacts on breeding birds at higher latitudes

Differential Impact of Blood Pressure Control Targets on Epicardial Coronary Flow After Transcatheter Aortic Valve Replacement

Background: The cause for the association between increased cardiovascular mortality rates and lower blood pressure (BP) after aortic valve replacement (AVR) is unclear. This study aims to assess how the epicardial coronary flow (ECF) after AVR varies as BP levels are changed in the presence of a right coronary lesion. Methods: The hemodynamics of a 3D printed aortic root model with a SAPIEN 3 26 deployed were evaluated in an in vitro left heart simulator under a range of varying systolic blood pressure (SBP) and diastolic blood pressure (DBP). ECF and the flow ratio index were calculated. Flow index value 0.9 for SBP ≥130 mmHg. However, at an SBP of 120 mmHg, the flow ratio was 0.63 (p ≤ 0.0055). With decreasing DBP, no BP condition yielded a flow ratio index that was less than 0.91. Conclusions: Reducing BP to the current recommended levels assigned for the general population after AVR in the presence of coronary artery disease may require reconsideration of levels and treatment priority. Additional studies are needed to fully understand the changes in ECF dynamics after AVR in the presence and absence of coronary artery disease

The association between serum biomarkers and disease outcome in influenza A(H1N1)pdm09 virus infection: results of two international observational cohort studies

BACKGROUND Prospective studies establishing the temporal relationship between the degree of inflammation and human influenza disease progression are scarce. To assess predictors of disease progression among patients with influenza A(H1N1)pdm09 infection, 25 inflammatory biomarkers measured at enrollment were analyzed in two international observational cohort studies. METHODS Among patients with RT-PCR-confirmed influenza A(H1N1)pdm09 virus infection, odds ratios (ORs) estimated by logistic regression were used to summarize the associations of biomarkers measured at enrollment with worsened disease outcome or death after 14 days of follow-up for those seeking outpatient care (FLU 002) or after 60 days for those hospitalized with influenza complications (FLU 003). Biomarkers that were significantly associated with progression in both studies (p<0.05) or only in one (p<0.002 after Bonferroni correction) were identified. RESULTS In FLU 002 28/528 (5.3%) outpatients had influenza A(H1N1)pdm09 virus infection that progressed to a study endpoint of complications, hospitalization or death, whereas in FLU 003 28/170 (16.5%) inpatients enrolled from the general ward and 21/39 (53.8%) inpatients enrolled directly from the ICU experienced disease progression. Higher levels of 12 of the 25 markers were significantly associated with subsequent disease progression. Of these, 7 markers (IL-6, CD163, IL-10, LBP, IL-2, MCP-1, and IP-10), all with ORs for the 3(rd) versus 1(st) tertile of 2.5 or greater, were significant (p<0.05) in both outpatients and inpatients. In contrast, five markers (sICAM-1, IL-8, TNF-α, D-dimer, and sVCAM-1), all with ORs for the 3(rd) versus 1(st) tertile greater than 3.2, were significantly (p≤.002) associated with disease progression among hospitalized patients only. CONCLUSIONS In patients presenting with varying severities of influenza A(H1N1)pdm09 virus infection, a baseline elevation in several biomarkers associated with inflammation, coagulation, or immune function strongly predicted a higher risk of disease progression. It is conceivable that interventions designed to abrogate these baseline elevations might affect disease outcome

Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security

Principal component analysis of summertime ground site measurements in the Athabasca oil sands with a focus on analytically unresolved intermediate-volatility organic compounds

In this paper, measurements of air pollutants made at a ground site near Fort McKay in the Athabasca oil sands region as part of a multi-platform campaign in the summer of 2013 are presented. The observations included measurements of selected volatile organic compounds (VOCs) by a gas chromatograph–ion trap mass spectrometer (GC-ITMS). This instrument observed a large, analytically unresolved hydrocarbon peak (with a retention index between 1100 and 1700) associated with intermediate-volatility organic compounds (IVOCs). However, the activities or processes that contribute to the release of these IVOCs in the oil sands region remain unclear. Principal component analysis (PCA) with varimax rotation was applied to elucidate major source types impacting the sampling site in the summer of 2013. The analysis included 28 variables, including concentrations of total odd nitrogen (NOy), carbon dioxide (CO2), methane (CH4), ammonia (NH3), carbon monoxide (CO), sulfur dioxide (SO2), total reduced-sulfur compounds (TRSs), speciated monoterpenes (including α- and β-pinene and limonene), particle volume calculated from measured size distributions of particles less than 10 and 1&thinsp;µm in diameter (PM10−1 and PM1), particle-surface-bound polycyclic aromatic hydrocarbons (pPAHs), and aerosol mass spectrometer composition measurements, including refractory black carbon (rBC) and organic aerosol components. The PCA was complemented by bivariate polar plots showing the joint wind speed and direction dependence of air pollutant concentrations to illustrate the spatial distribution of sources in the area. Using the 95&thinsp;% cumulative percentage of variance criterion, 10 components were identified and categorized by source type. These included emissions by wet tailing ponds, vegetation, open pit mining operations, upgrader facilities, and surface dust. Three components correlated with IVOCs, with the largest associated with surface mining and likely caused by the unearthing and processing of raw bitumen.</p

Geochemical recovery of the Torna-Marcal river system after the Ajka red mud spill, Hungary

The failure of the Ajka red mud depository in October 2010 led to the largest single release of red mud into the surface water environment. This study provides a comparative assessment of stream sediment quality in the Torna-Marcal-Rába catchment between post-disaster surveys (2010) and follow up surveys at an identical suite of 21 locations in 2013. The signature of red mud apparent in initial surveys with high Al, As, Cr, Na, V was only apparent at a small number of sample stations in recent surveys. These constitute 20 km reach of affected sediments in the immediate aftermath of the spill. Concentrations of red mud-derived contaminants are predominately associated with fine fractions of the red mud (<8 μm). This enhances transport out of the system of red mud-derived contaminants and, along with extensive remedial efforts, has substantially limited the within-channel inventory of potentially ecotoxic metals and metalloids

Massage Therapy for Osteoarthritis of the Knee: A Randomized Dose-Finding Trial

In a previous trial of massage for osteoarthritis (OA) of the knee, we demonstrated feasibility, safety and possible efficacy, with benefits that persisted at least 8 weeks beyond treatment termination.We performed a RCT to identify the optimal dose of massage within an 8-week treatment regimen and to further examine durability of response. Participants were 125 adults with OA of the knee, randomized to one of four 8-week regimens of a standardized Swedish massage regimen (30 or 60 min weekly or biweekly) or to a Usual Care control. Outcomes included the Western Ontario and McMaster Universities Arthritis Index (WOMAC), visual analog pain scale, range of motion, and time to walk 50 feet, assessed at baseline, 8-, 16-, and 24-weeks.WOMAC Global scores improved significantly (24.0 points, 95% CI ranged from 15.3-32.7) in the 60-minute massage groups compared to Usual Care (6.3 points, 95% CI 0.1-12.8) at the primary endpoint of 8-weeks. WOMAC subscales of pain and functionality, as well as the visual analog pain scale also demonstrated significant improvements in the 60-minute doses compared to usual care. No significant differences were seen in range of motion at 8-weeks, and no significant effects were seen in any outcome measure at 24-weeks compared to usual care. A dose-response curve based on WOMAC Global scores shows increasing effect with greater total time of massage, but with a plateau at the 60-minute/week dose.Given the superior convenience of a once-weekly protocol, cost savings, and consistency with a typical real-world massage protocol, the 60-minute once weekly dose was determined to be optimal, establishing a standard for future trials.ClinicalTrials.gov NCT00970008

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery