Quantum invariants and the graph isomorphism problem

© 2019 authors. Published by the American Physical Society. Three graph invariants are introduced which may be measured from a quantum graph state and form examples of a framework under which other graph invariants can be constructed. Each invariant is based on distinguishing a different number of qubits. This is done by applying different measurements to the qubits to be distinguished. The performance of these invariants is evaluated and compared to classical invariants. We verify that the invariants can distinguish all nonisomorphic graphs with nine or fewer nodes. The invariants have also been applied to "classically hard" strongly regular graphs, successfully distinguishing all strongly regular graphs of up to 29 nodes, and preliminarily to weighted graphs. We have found that, although it is possible to prepare states with a polynomial number of operations, the average number of preparations required to distinguish nonisomorphic graph states scales exponentially with the number of nodes. We have so far been unable to find operators which reliably compare graphs and reduce the required number of preparations to feasible levels

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

Phylodynamics of HIV-1 Subtype B among the Men-Having-Sex-with-Men (MSM) Population in Hong Kong

The men-having-sex-with-men (MSM) population has become one of the major risk groups for HIV-1 infection in the Asia Pacific countries. Hong Kong is located in the centre of Asia and the transmission history of HIV-1 subtype B transmission among MSM remained unclear. The aim of this study was to investigate the transmission dynamics of HIV-1 subtype B virus in the Hong Kong MSM population. Samples of 125 HIV-1 subtype B infected MSM patients were recruited in this study. Through this study, the subtype B epidemic in the Hong Kong MSM population was identified spreading mainly among local Chinese who caught infection locally. On the other hand, HIV-1 subtype B infected Caucasian MSM caught infection mainly outside Hong Kong. The Bayesian phylogenetic analysis also indicated that 3 separate subtype B epidemics with divergence dates in the 1990s had occurred. The first and latest epidemics were comparatively small-scaled; spreading among the local Chinese MSM while sauna-visiting was found to be the major sex partner sourcing reservoir for the first subtype B epidemic. However, the second epidemic was spread in a large-scale among local Chinese MSM with a number of them having sourced their sex partners through the internet. The epidemic virus was estimated to have a divergence date in 1987 and the infected population in Hong Kong had a logistic growth throughout the past 20 years. Our study elucidated the evolutionary and demographic history of HIV-1 subtype B virus in Hong Kong MSM population. The understanding of transmission and growth model of the subtype B epidemic provides more information on the HIV-1 transmission among MSM population in other Asia Pacific high-income countries

Smoking status and common carotid artery intima-medial thickness among middle-aged men and women based on ultrasound measurement: a cohort study

BACKGROUND: Cigarette smoking is an established causal factor for atherosclerosis. However, the smoking effect on different echogenic components of carotid arterial wall measured by ultrasound is not well elucidated. METHODS: Middle-aged men and women who had IMT measurement ≥ 0.7 mm at baseline and follow-up were included (N = 413, age 40–60 years at baseline in 1995). Intima-media thickness of common carotid artery (CCA-IMT) and its components (echogenic and echolucent layers) were measured at baseline and in the follow-up examination 3 years later. IMT and its components were compared across current, former and never smokers. Individual growth models were used to examine how smoking status was related to the baseline and progression of overall IMT and IMT components. RESULTS: For both men and women, current smoking was associated with thicker echogenic layer than never smokers; former smokers exhibited thinner echogenic layer than current smokers after adjustment for cigarette pack-years. Among women, current smoking was also associated with a thinned echolucent layer that resulted in a non-significant overall association of current smoking with IMT for women. CONCLUSION: Cigarette smoking is associated with carotid artery morphological changes and the association is sex-dependent. The atherogenic effect of smoking appears to be partly reversible among former smokers. IMT measurement alone may not be adequate to detect carotid atherosclerosis associated with cigarette smoking among middle-age women

How does gender influence the recognition of cardiovascular risk and adherence to self-care recommendations? : a study in polish primary care

Background: Studies have shown a correlation between gender and an ability to change lifestyle to reduce the risk of disease. However, the results of these studies are ambiguous, especially where a healthy lifestyle is concerned. Additionally, health behaviors are strongly modified by culture and the environment. Psychological factors also substantially affect engagement with disease-related lifestyle interventions. This study aimed to examine whether there are differences between men and women in the frequency of health care behavior for the purpose of reducing cardiovascular risk (CVR), as well as cognitive appraisal of this type of risk. We also aimed to identify the psychological predictors of engaging in recommended behavior for reducing the risk of cardiovascular disease after providing information about this risk in men and women. Methods: A total of 134 consecutive eligible patients in a family practice entered a longitudinal study. At initial consultation, the individual’s CVR and associated health burden was examined, and preventive measures were recommended by the physician. Self-care behavior, cognitive appraisal of risk, and coping styles were then assessed using psychological questionnaires. Six months after the initial data collection, the frequency of subjects’ self-care behavior was examined. Results: We found an increase in health care behavior after providing information regarding the rate of CVR in both sexes; this increase was greater for women than for men. Women followed self-care guidelines more often than men, particularly for preventive measures and dietary advice. Women were more inclined to recognize their CVR as a challenge. Coping style, cognitive appraisal, age, level of health behaviors at baseline and CVR values accounted for 48% of the variance in adherence to self-care guidelines in women and it was 52% in men. In women, total risk of CVD values were most important, while in men, cognitive appraisal of harm/loss was most important. Conclusions: Different predictors of acquisition of health behavior are encountered in men and women. Our results suggest that gender-adjusted motivation models influencing the recognition process need to be considered to optimize compliance in patients with CVR

Modeling repeated ordinal responses using a family of power transformations: application to neonatal hypothermia data

BACKGROUND: For analyzing a repeated ordinal response, it is common to use a multivariate cumulative logit model. This model may fit poorly, especially when a nonsymmetric response is available. In these cases, alternative strategies should be utilized. METHODS: In this paper, we present a family of power transformations for the cumulative probabilities to model asymmetric departures from the random-intercept cumulative logit model. To illustrate this method, we analyze the data from an epidemiologic study to identify risk factors of hypothermia among newly born infants in some referral university hospitals in Tehran, Iran. RESULTS: For hypothermia data, using this family of transformations and comparing the goodness-of-fit statistics showed that a model with the cumulative complementary log-log link gives us a better fit compared to a model with the cumulative logit link. CONCLUSION: In some areas, using the ordinary cumulative logit link function does not lead to the best fit. So, other link functions should be evaluated to discover the best transformation for the cumulative probabilities

No evidence for association between polymorphisms in GRM3 and schizophrenia

BACKGROUND: Three studies have previously reported data that were interpreted by the authors as supportive of association between schizophrenia and polymorphisms in the gene encoding the metabotropic glutamate receptor GRM3. METHODS: In a bid to examine this hypothesis, we examined seven SNPs spanning GRM3 in a UK case-control sample (schizophrenic cases n = 674, controls n = 716). These included all SNPs previously reported to be associated, alone or in haplotypes, with schizophrenia in European or European American samples. RESULTS: Our data showed no evidence for association with single markers, or 2, 3, 4 and 5 marker haplotypes, nor did any specific haplotypes show evidence for association according to previously observed patterns. CONCLUSION: Examination of our own data and those of other groups leads us to conclude that at present, GRM3 should not be viewed as a gene for which there is replicated evidence for association with schizophrenia