Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

Conscientiousness, Career Success, and Longevity: A Lifespan Analysis

Markers of executive functioning, such as prudent planning for the future and impulse control, are related to conscientiousness and may be central to both occupational success and health outcomes. The aim of the study was to examine relations among conscientiousness, career success, and mortality risk across a 65-year period. Using data derived from 693 male participants in the Terman Life Cycle Study, we examined associations among childhood personality, midlife objective career success, and lifelong mortality risk through 2006. Conscientiousness and career success each predicted lower mortality risk (N = 693, relative hazard (rh) = 0.82 [95% confidence interval = 0.74, 0.91] and rh = 0.80 [0.71, 0.91], respectively), with both shared and unique variance. Importantly, childhood personality moderated the success–longevity link; conscientiousness was most relevant for least successful individuals. Conscientiousness and career success predicted longevity, but not in a straightforward manner. Findings highlight the importance of lifespan processes

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

Delta-9 tetrahydrocannabinol (THC) inhibits lytic replication of gamma oncogenic herpesviruses in vitro

BACKGROUND: The major psychoactive cannabinoid compound of marijuana, delta-9 tetrahydrocannabinol (THC), has been shown to modulate immune responses and lymphocyte function. After primary infection the viral DNA genome of gamma herpesviruses persists in lymphoid cell nuclei in a latent episomal circular form. In response to extracellular signals, the latent virus can be activated, which leads to production of infectious virus progeny. Therefore, we evaluated the potential effects of THC on gamma herpesvirus replication. METHODS: Tissue cultures infected with various gamma herpesviruses were cultured in the presence of increasing concentrations of THC and the amount of viral DNA or infectious virus yield was compared to those of control cultures. The effect of THC on Kaposi's Sarcoma Associated Herpesvirus (KSHV) and Epstein-Barr virus (EBV) replication was measured by the Gardella method and replication of herpesvirus saimiri (HVS) of monkeys, murine gamma herpesvirus 68 (MHV 68), and herpes simplex type 1 (HSV-1) was measured by yield reduction assays. Inhibition of the immediate early ORF 50 gene promoter activity was measured by the dual luciferase method. RESULTS: Micromolar concentrations of THC inhibit KSHV and EBV reactivation in virus infected/immortalized B cells. THC also strongly inhibits lytic replication of MHV 68 and HVS in vitro. Importantly, concentrations of THC that inhibit virus replication of gamma herpesviruses have no effect on cell growth or HSV-1 replication, indicating selectivity. THC was shown to selectively inhibit the immediate early ORF 50 gene promoter of KSHV and MHV 68. CONCLUSIONS: THC specifically targets viral and/or cellular mechanisms required for replication and possibly shared by these gamma herpesviruses, and the endocannabinoid system is possibly involved in regulating gamma herpesvirus latency and lytic replication. The immediate early gene ORF 50 promoter activity was specifically inhibited by THC. These studies may also provide the foundation for the development of antiviral strategies utilizing non-psychoactive derivatives of THC

Why Human Health and Health Ethics Must Be Central to Climate Change Deliberations

Jerome Singh argues that health ethics principles must be afforded equal status to economics principles in climate change deliberations, and that the health community must play more of a leadership role

Animal-related factors associated with moderate-to-severe diarrhea in children younger than five years in western Kenya: A matched case-control study

Background Diarrheal disease remains among the leading causes of global mortality in children younger than 5 years. Exposure to domestic animals may be a risk factor for diarrheal disease. The objectives of this study were to identify animal-related exposures associated with cases of moderate-to-severe diarrhea (MSD) in children in rural western Kenya, and to identify the major zoonotic enteric pathogens present in domestic animals residing in the homesteads of case and control children. Methodology/Principal findings We characterized animal-related exposures in a subset of case and control children (n = 73 pairs matched on age, sex and location) with reported animal presence at home enrolled in the Global Enteric Multicenter Study in western Kenya, and analysed these for an association with MSD. We identified potentially zoonotic enteric pathogens in pooled fecal specimens collected from domestic animals resident at children’s homesteads. Variables that were associated with decreased risk of MSD were washing hands after animal contact (matched odds ratio [MOR] = 0.2; 95% CI 0.08–0.7), and presence of adult sheep that were not confined in a pen overnight (MOR = 0.1; 0.02–0.5). Variables that were associated with increased risk of MSD were increasing number of sheep owned (MOR = 1.2; 1.0–1.5), frequent observation of fresh rodent excreta (feces/urine) outside the house (MOR = 7.5; 1.5–37.2), and participation of the child in providing water to chickens (MOR = 3.8; 1.2–12.2). Of 691 pooled specimens collected from 2,174 domestic animals, 159 pools (23%) tested positive for one or more potentially zoonotic enteric pathogens (Campylobacter jejuni, C. coli, non-typhoidal Salmonella, diarrheagenic E. coli, Giardia, Cryptosporidium, or rotavirus). We did not find any association between the presence of particular pathogens in household animals, and MSD in children. Conclusions and significance Public health agencies should continue to promote frequent hand washing, including after animal contact, to reduce the risk of MSD. Future studies should address specific causal relations of MSD with sheep and chicken husbandry practices, and with the presence of rodents

Should we welcome robot teachers?

Abstract Current uses of robots in classrooms are reviewed and used to characterise four scenarios: (s1) Robot as Classroom Teacher; (s2) Robot as Companion and Peer; (s3) Robot as Care-eliciting Companion; and (s4) Telepresence Robot Teacher. The main ethical concerns associated with robot teachers are identified as: privacy; attachment, deception, and loss of human contact; and control and accountability. These are discussed in terms of the four identified scenarios. It is argued that classroom robots are likely to impact children’s’ privacy, especially when they masquerade as their friends and companions, when sensors are used to measure children’s responses, and when records are kept. Social robots designed to appear as if they understand and care for humans necessarily involve some deception (itself a complex notion), and could increase the risk of reduced human contact. Children could form attachments to robot companions (s2 and s3), or robot teachers (s1) and this could have a deleterious effect on their social development. There are also concerns about the ability, and use of robots to control or make decisions about children’s behaviour in the classroom. It is concluded that there are good reasons not to welcome fully fledged robot teachers (s1), and that robot companions (s2 and 3) should be given a cautious welcome at best. The limited circumstances in which robots could be used in the classroom to improve the human condition by offering otherwise unavailable educational experiences are discussed

Patients' views on responsibility for the management of musculoskeletal disorders – A qualitative study

<p>Abstract</p> <p>Background</p> <p>Musculoskeletal disorders are very common and almost inevitable in an individual's lifetime. Enabling self-management and allowing the individual to take responsibility for care is stated as desired in the management of these disorders, but this may be asking more than people can generally manage. A willingness among people to take responsibility for musculoskeletal disorders and not place responsibility out of their hands or on employers but to be shared with medical professionals has been shown. The aim of the present study was to describe how people with musculoskeletal disorders think and reason regarding responsibility for prevention, treatment and management of the disorder.</p> <p>Methods</p> <p>Individual interviews with a strategic sample of 20 individuals with musculoskeletal disorders were performed. The interviews were tape-recorded, transcribed verbatim and analysed according to qualitative content analysis.</p> <p>Results</p> <p>From the interviews an overarching theme was identified: own responsibility needs to be met. The analysis revealed six interrelated categories: Taking on responsibility, Ambiguity about responsibility, Collaborating responsibility, Complying with recommendations, Disclaiming responsibility, and Responsibility irrelevant. These categories described different thoughts and reasoning regarding the responsibility for managing musculoskeletal disorders. Generally the responsibility for prevention of musculoskeletal disorders was described to lie primarily on society/authorities as they have knowledge of what to prevent and how to prevent it. When musculoskeletal disorders have occurred, health care should provide fast accessibility, diagnosis, prognosis and support for recovery. For long-term management, the individuals themselves are responsible for making the most out of life despite disorders.</p> <p>Conclusion</p> <p>No matter what the expressions of responsibility for musculoskeletal disorders are, own responsibility needs to be met by society, health care, employers and family in an appropriate way, with as much or as little of the "right type" of support needed, based on the individual's expectations.</p

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

The Cluster Variation Method for Efficient Linkage Analysis on Extended Pedigrees

BACKGROUND: Computing exact multipoint LOD scores for extended pedigrees rapidly becomes infeasible as the number of markers and untyped individuals increase. When markers are excluded from the computation, significant power may be lost. Therefore accurate approximate methods which take into account all markers are desirable. METHODS: We present a novel method for efficient estimation of LOD scores on extended pedigrees. Our approach is based on the Cluster Variation Method, which deterministically estimates likelihoods by performing exact computations on tractable subsets of variables (clusters) of a Bayesian network. First a distribution over inheritances on the marker loci is approximated with the Cluster Variation Method. Then this distribution is used to estimate the LOD score for each location of the trait locus. RESULTS: First we demonstrate that significant power may be lost if markers are ignored in the multi-point analysis. On a set of pedigrees where exact computation is possible we compare the estimates of the LOD scores obtained with our method to the exact LOD scores. Secondly, we compare our method to a state of the art MCMC sampler. When both methods are given equal computation time, our method is more efficient. Finally, we show that CVM scales to large problem instances. CONCLUSION: We conclude that the Cluster Variation Method is as accurate as MCMC and generally is more efficient. Our method is a promising alternative to approaches based on MCMC sampling