AND Protocols Using Only Uniform Shuffles

Secure multi-party computation using a deck of playing cards has been a subject of research since the "five-card trick" introduced by den Boer in 1989. One of the main problems in card-based cryptography is to design committed-format protocols to compute a Boolean AND operation subject to different runtime and shuffle restrictions by using as few cards as possible. In this paper, we introduce two AND protocols that use only uniform shuffles. The first one requires four cards and is a restart-free Las Vegas protocol with finite expected runtime. The second one requires five cards and always terminates in finite time.Comment: This paper has appeared at CSR 201

Building interpretable models for polypharmacy prediction in older chronic patients based on drug prescription records

© 2018 Kocbek et al. Background. Multimorbidity presents an increasingly common problem in older population, and is tightly related to polypharmacy, i.e., concurrent use of multiple medications by one individual. Detecting polypharmacy from drug prescription records is not only related to multimorbidity, but can also point at incorrect use of medicines. In this work, we build models for predicting polypharmacy from drug prescription records for newly diagnosed chronic patients. We evaluate the models' performance with a strong focus on interpretability of the results. Methods. A centrally collected nationwide dataset of prescription records was used to perform electronic phenotyping of patients for the following two chronic conditions: Type 2 diabetes mellitus (T2D) and cardiovascular disease (CVD). In addition, a hospital discharge dataset was linked to the prescription records. A regularized regression model was built for 11 different experimental scenarios on two datasets, and complexity of the model was controlled with a maximum number of dimensions (MND) parameter. Performance and interpretability of the model were evaluated with AUC, AUPRC, calibration plots, and interpretation by a medical doctor. Results. For the CVD model, AUC and AUPRC values of 0.900 (95% [0.898-0.901]) and 0.640 (0.635-0.645) were reached, respectively, while for the T2D model the values were 0.808 (0.803-0.812) and 0.732 (0.725-0.739). Reducing complexity of the model by 65% and 48% for CVD and T2D, resulted in 3% and 4% lower AUC, and 4% and 5% lower AUPRC values, respectively. Calibration plots for our models showed that we can achieve moderate calibration with reducing the models' complexity without significant loss of predictive performance. Discussion. In this study, we found that it is possible to use drug prescription data to build a model for polypharmacy prediction in older population. In addition, the study showed that it is possible to find a balance between good performance and interpretability of the model, and achieve acceptable calibration at the same time

Secure Grouping Protocol Using a Deck of Cards

We consider a problem, which we call secure grouping, of dividing a number of parties into some subsets (groups) in the following manner: Each party has to know the other members of his/her group, while he/she may not know anything about how the remaining parties are divided (except for certain public predetermined constraints, such as the number of parties in each group). In this paper, we construct an information-theoretically secure protocol using a deck of physical cards to solve the problem, which is jointly executable by the parties themselves without a trusted third party. Despite the non-triviality and the potential usefulness of the secure grouping, our proposed protocol is fairly simple to describe and execute. Our protocol is based on algebraic properties of conjugate permutations. A key ingredient of our protocol is our new techniques to apply multiplication and inverse operations to hidden permutations (i.e., those encoded by using face-down cards), which would be of independent interest and would have various potential applications

ALAD and APOE polymorphisms are associated with lead and mercury levels in Italian pregnant women and their newborns with adequate nutritional status of zinc and selenium

The impacts of single-nucleotide polymorphisms (SNPs) in ALAD and VDR genes on Pb health effects and/or kinetics are inconclusive at low exposure levels, while studies including APOE SNPs are rare. In this study, we examined the associations of ALAD, VDR and APOE SNPs with exposure biomarkers of Pb and other trace elements (TEs) in Italian pregnant women (N = 873, aged 18–44 years) and their newborns (N = 619) with low-level mixed-element exposure through diet, the environment or endogenously. DNA from maternal peripheral venous blood (mB), sampled during the second and third trimesters, was genotyped for ALAD (rs1800435, rs1805313, rs1139488, rs818708), VDR (rs2228570, rs1544410, rs7975232, rs731236) and APOE (rs429358, rs7421) using TaqMan SNP assays. Personal and lifestyle data and TE levels (mB, maternal plasma, hair and mixed umbilical cord blood [CB]) from the PHIME project were used. Multiple linear regression models, controlling for confounding variables, were performed to test the associations between SNPs and TEs. The geometric means of mB-Pb, mB-Hg, mB-As and mB-Cd (11.0 ng/g, 2.16 ng/g, 1.38 ng/g and 0.31 ng/g, respectively) indicated low exposure levels, whereas maternal plasma Zn and Se (0.72 μg/mL and 78.6 ng/g, respectively) indicated adequate micronutritional status. Variant alleles of ALAD rs1800435 and rs1805313 were negatively associated with mB-Pb levels, whereas a positive association was observed for rs1139488. None of the VDR SNPs or their haplotypes had any association with Pb levels. Regarding APOE, the ϵ4 allele was associated with lower mB-Hg and CB-Hg, while a positive association was found with the ϵ2 allele and CB-Pb when the model included only newborn girls. The observed associations indicate possible modification effects of ALAD and APOE SNPs on Pb or Hg kinetics in women and their newborns with low exposure to non-essential TEs, as well as an adequate nutritional status of Zn and Se

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website (https://osf.io/mhg94/).</p&gt

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts

Roles of cyberbullying, sleep, and physical activity in mediating the effects of social media use on mental health and wellbeing among young people in England: a secondary analysis of longitudinal data

BACKGROUND: There is growing concern about the potential associations between social media use and mental health and wellbeing in young people. We explored associations between the frequency of social media use and later mental health and wellbeing in adolescents, and how these effects might be mediated. METHODS: We did secondary analyses of publicly available data from the Our Futures study, a nationally representative, longitudinal study of 12 866 young people from age 13 years to 16 years in England. The exposure considered was the frequency of social media use (from weekly or less to very frequent [multiple times daily]) at wave 1 (participants aged 13-14 years) through wave 3 of the study (participants aged 15-16 years). Outcomes were mental health at wave 2 (with high 12-item General Health Questionnaire [GHQ12] scores [≥3] indicating psychological distress), and wellbeing at wave 3 (life satisfaction, feeling life is worthwhile, happiness, and anxiety, rated from 1 to 10 by participants). Analyses were adjusted for a minimal sufficient confounding structure, and were done separately for boys and girls. Cyberbullying, sleep adequacy, and physical activity were assessed as potential mediators of the effects. FINDINGS: Very frequent use of social media increased from wave 1 to wave 3: from 34·4% (95% CI 32·4-36·4) to 61·9% (60·3-63·6) in boys, and 51·4% (49·5-53·3) to 75·4% (73·8-76·9) in girls. Very frequent social media use in wave 1 predicted a high GHQ12 score at wave 2 among girls (adjusted odds ratio [OR] 1·31 [95% CI 1·06-1·63], p=0·014; N=4429) and boys (1·67 [1·24-2·26], p=0·0009; N=4379). Persistent very frequent social media use across waves 1 and 2 predicted lower wellbeing among girls only (adjusted ORs 0·86 [0·74-0·99], N=3753, p=0·039 for life satisfaction; 0·80 [0·70-0·92], N=3831, p=0·0013 for happiness; 1·28 [1·11-1·48], N=3745, p=0·0007 for anxiety). Adjustment for cyberbullying, sleep, and physical activity attenuated the associations of social media use with GHQ12 high score (proportion mediated 58·2%), life satisfaction (80·1%), happiness (47·7%), and anxiety (32·4%) in girls, such that these associations (except for anxiety) were no longer significant; however, the association with GHQ12 high score among boys remained significant, being mediated only 12·1% by these factors. INTERPRETATION: Mental health harms related to very frequent social media use in girls might be due to a combination of exposure to cyberbullying or displacement of sleep or physical activity, whereas other mechanisms appear to be operative in boys. Interventions to promote mental health should include efforts to prevent or increase resilience to cyberbullying and ensure adequate sleep and physical activity in young people. FUNDING: None