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

Developmental differences in holistic interference of facial part recognition.

Research has shown that adults' recognition of a facial part can be disrupted if the part is learnt without a face context but tested in a whole face. This has been interpreted as the holistic interference effect. The present study investigated whether children of 6- and 9-10-year-olds would show a similar effect. Participants were asked to judge whether a probe part was the same as or different from a test part whereby the part was presented either in isolation or in a whole face. The results showed that while all the groups were susceptible to a holistic interference, the youngest group was most severely affected. Contrary to the view that piecemeal processing precedes holistic processing in the cognitive development, our findings demonstrate that holistic processing is already present at 6 years of age. It is the ability to inhibit the influence of holistic information on piecemeal processing that seems to require a longer period of development into at an older and adult age

Phyllanthus spp. Induces Selective Growth Inhibition of PC-3 and MeWo Human Cancer Cells through Modulation of Cell Cycle and Induction of Apoptosis

BACKGROUND: Phyllanthus is a traditional medicinal plant that has been used in the treatment of many diseases including hepatitis and diabetes. The main aim of the present work was to investigate the potential cytotoxic effects of aqueous and methanolic extracts of four Phyllanthus species (P.amarus, P.niruri, P.urinaria and P.watsonii) against skin melanoma and prostate cancer cells. METHODOLOGY/PRINCIPAL FINDINGS: Phyllanthus plant appears to possess cytotoxic properties with half-maximal inhibitory concentration (IC(50)) values of 150-300 µg/ml for aqueous extract and 50-150 µg/ml for methanolic extract that were determined using the MTS reduction assay. In comparison, the plant extracts did not show any significant cytotoxicity on normal human skin (CCD-1127Sk) and prostate (RWPE-1) cells. The extracts appeared to act by causing the formation of a clear "ladder" fragmentation of apoptotic DNA on agarose gel, displayed TUNEL-positive cells with an elevation of caspase-3 and -7 activities. The Lactate Dehydrogenase (LDH) level was lower than 15% in Phyllanthus treated-cancer cells. These indicate that Phyllanthus extracts have the ability to induce apoptosis with minimal necrotic effects. Furthermore, cell cycle analysis revealed that Phyllanthus induced a Go/G1-phase arrest on PC-3 cells and a S-phase arrest on MeWo cells and these were accompanied by accumulation of cells in the Sub-G1 (apoptosis) phase. The cytotoxic properties may be due to the presence of polyphenol compounds such as ellagitannins, gallotannins, flavonoids and phenolic acids found both in the water and methanol extract of the plants. CONCLUSIONS/SIGNIFICANCE: Phyllanthus plant exerts its growth inhibition effect in a selective manner towards cancer cells through the modulation of cell cycle and induction of apoptosis via caspases activation in melanoma and prostate cancer cells. Hence, Phyllanthus may be sourced for the development of a potent apoptosis-inducing anticancer agent

Modelling the impact of women’s education on fertility in Malawi

Many studies have suggested that there is an inverse relationship between education and number of children among women from sub-Saharan Africa countries, including Malawi. However, a crucial limitation of these analyses is that they do not control for the potential endogeneity of education. The aim of our study is to estimate the role of women’s education on their number of children in Malawi, accounting for the possible presence of endogeneity and for nonlinear effects of continuous observed confounders. Our analysis is based on micro data from the 2010 Malawi Demographic Health Survey, and uses a flexible instrumental variable regression approach. The results suggest that the relationship of interest is affected by endogeneity and exhibits an inverted U-shape among women living in rural areas of Malawi, whereas it exhibits an inverse (nonlinear) relationship for women living in urban areas

A probit- log- skew-normal mixture model for repeated measures data with excess zeros, with application to a cohort study of paediatric respiratory symptoms

<p>Abstract</p> <p>Background</p> <p>A zero-inflated continuous outcome is characterized by occurrence of "excess" zeros that more than a single distribution can explain, with the positive observations forming a skewed distribution. Mixture models are employed for regression analysis of zero-inflated data. Moreover, for repeated measures zero-inflated data the clustering structure should also be modeled for an adequate analysis.</p> <p>Methods</p> <p>Diary of Asthma and Viral Infections Study (DAVIS) was a one year (2004) cohort study conducted at McMaster University to monitor viral infection and respiratory symptoms in children aged 5-11 years with and without asthma. Respiratory symptoms were recorded daily using either an Internet or paper-based diary. Changes in symptoms were assessed by study staff and led to collection of nasal fluid specimens for virological testing. The study objectives included investigating the response of respiratory symptoms to respiratory viral infection in children with and without asthma over a one year period. Due to sparse data daily respiratory symptom scores were aggregated into weekly average scores. More than 70% of the weekly average scores were zero, with the positive scores forming a skewed distribution. We propose a random effects probit/log-skew-normal mixture model to analyze the DAVIS data. The model parameters were estimated using a maximum marginal likelihood approach. A simulation study was conducted to assess the performance of the proposed mixture model if the underlying distribution of the positive response is different from log-skew normal.</p> <p>Results</p> <p>Viral infection status was highly significant in both probit and log-skew normal model components respectively. The probability of being symptom free was much lower for the week a child was viral positive relative to the week she/he was viral negative. The severity of the symptoms was also greater for the week a child was viral positive. The probability of being symptom free was smaller for asthmatics relative to non-asthmatics throughout the year, whereas there was no difference in the <it>severity </it>of the symptoms between the two groups.</p> <p>Conclusions</p> <p>A positive association was observed between viral infection status and both the probability of experiencing any respiratory symptoms, and their severity during the year. For DAVIS data the random effects probit -log skew normal model fits significantly better than the random effects probit -log normal model, endorsing our parametric choice for the model. The simulation study indicates that our proposed model seems to be robust to misspecification of the distribution of the positive skewed response.</p

Linear-in-the-parameters oblique least squares (LOLS) provides more accurate estimates of density-dependent survival

Survival is a fundamental demographic component and the importance of its accurate estimation goes beyond the traditional estimation of life expectancy. The evolutionary stability of isomorphic biphasic life-cycles and the occurrence of its different ploidy phases at uneven abundances are hypothesized to be driven by differences in survival rates between haploids and diploids. We monitored Gracilaria chilensis, a commercially exploited red alga with an isomorphic biphasic life-cycle, having found density-dependent survival with competition and Allee effects. While estimating the linear-in-the-parameters survival function, all model I regression methods (i.e, vertical least squares) provided biased line-fits rendering them inappropriate for studies about ecology, evolution or population management. Hence, we developed an iterative two-step non-linear model II regression (i.e, oblique least squares), which provided improved line-fits and estimates of survival function parameters, while robust to the data aspects that usually turn the regression methods numerically unstable

Are the affluent prepared to pay for the planet? Explaining willingness to pay for public and quasi-private environmental goods in Switzerland

A large number of ‘environmental justice’ studies show that wealthier people are less affected by environmental burdens and also consume more resources than poorer people. Given this double inequity, we ask, to what extent are affluent people prepared to pay to protect the environment? The analyses are couched within the compensation/affluence hypothesis, which states that wealthier persons are able to spend more for environmental protection than their poorer counterparts. Further, we take into account various competing economic, psychological and sociological determinants of individuals’ willingness to pay (WTP) for both public environmental goods (e.g., general environmental protection) and quasi-private environmental goods (e.g., CO2-neutral cars). Such a comprehensive approach contrasts with most other studies in this field that focus on a limited number of determinants and goods. Multivariate analyses are based on a general population survey in Switzerland (N = 3,369). Although income has a positive and significant effect on WTP supporting the compensation hypothesis, determinants such as generalized interpersonal trust that is assumed to be positively associated with civic engagement and environmental concern prove to be equally important. Moreover, we demonstrate for the first time that time preferences can considerably influence survey-based WTP for environmental goods; since investments in the environment typically pay off in the distant future, persons with a high subjective discount rate are less likely to commit

Goal-directed and habitual control in the basal ganglia: implications for Parkinson's disease

Progressive loss of the ascending dopaminergic projection in the basal ganglia is a fundamental pathological feature of Parkinson's disease. Studies in animals and humans have identified spatially segregated functional territories in the basal ganglia for the control of goal-directed and habitual actions. In patients with Parkinson's disease the loss of dopamine is predominantly in the posterior putamen, a region of the basal ganglia associated with the control of habitual behaviour. These patients may therefore be forced into a progressive reliance on the goal-directed mode of action control that is mediated by comparatively preserved processing in the rostromedial striatum. Thus, many of their behavioural difficulties may reflect a loss of normal automatic control owing to distorting output signals from habitual control circuits, which impede the expression of goal-directed action. © 2010 Macmillan Publishers Limited. All rights reserved