Resource Allocation using Virtual Clusters

In this report we demonstrate the utility of resource allocations that use virtual machine technology for sharing parallel computing resources among competing users. We formalize the resource allocation problem with a number of underlying assumptions, determine its complexity, propose several heuristic algorithms to find near-optimal solutions, and evaluate these algorithms in simulation. We find that among our algorithms one is very efficient and also leads to the best resource allocations. We then describe how our approach can be made more general by removing several of the underlying assumptions

A decade into Facebook: where is psychiatry in the digital age?

Social networking sites are a part of everyday life for over a billion people worldwide. They show no sign of declining popularity, with social media use increasing at 3 times the rate of other Internet use. Despite this proliferation, mental healthcare has yet to embrace this unprecedented resource. We argue that social networking site data should become a high priority for psychiatry research and mental healthcare delivery. We illustrate our views using the world’s largest social networking site, Facebook, which currently has over 1 billion daily users (1 in 7 people worldwide). Facebook users can create personal profiles, socialize, express feelings, and share content, which Facebook stores as time-stamped digital records dating back to when the user first joined. Evidence suggests that 92% of adolescents go online daily and disclose considerably more about themselves online than offline. Thus, working with Facebook data could further our understanding of the onset and early years of mental illness, a crucial period of interpersonal development. Furthermore, a diminishing ‘digital divide’ has allowed for a broader sociodemographic to access Facebook, including homeless youth, young veterans, immigrants, patients with mental health problems, and seniors, enabling greater contact with traditionally harder-to-reach populations

Exploring the utility of Acxiom’s Research Opinion Poll data for use in social science research

Acxiom’s Research Opinion Poll (ROP), a voluntary survey designed to capture detailed information about household consumption and expenditure across Great Britain, has the potential to provide information valuable for social science research. This paper provides a review of the ROP, indicating that the survey in undertaken through a number of channels which enable Acxiom to generate over one million household responses a year. The ROP micro data collected are used in the construction of many of Acxiom’s aggregate products including its geo-demographic classification system called ‘PersonicX’. The ROP is found to compare favourably in areas such as sample size, geographic detail, consistency and data quality and accuracy when compared against government datasets including the 2001 Census, the Living Costs and Food Survey, the Labour Force Survey, the British Household Panel Survey, the General Lifestyle Survey and the English Housing Survey

Using item response theory to develop measures of acquisitive and protective self-monitoring from the original self-monitoring scale

For the past 40 years, the conventional univariate model of self-monitoring has reigned as the dominant interpretative paradigm in the literature. However, recent findings associated with an alternative bivariate model challenge the conventional paradigm. In this study, item response theory is used to develop measures of the bivariate model of acquisitive and protective self-monitoring using original Self-Monitoring Scale (SMS) items, and data from two large, nonstudent samples (Ns = 13,563 and 709). Results indicate that the new acquisitive (six-item) and protective (seven-item) self-monitoring scales are reliable, unbiased in terms of gender and age, and demonstrate theoretically consistent relations to measures of personality traits and cognitive ability. Additionally, by virtue of using original SMS items, previously collected responses can be reanalyzed in accordance with the alternative bivariate model. Recommendations for the reanalysis of archival SMS data, as well as directions for future research, are provided

Personality and intrinsic motivational factors in end-user programming

We explore the factors that determine whether individuals are likely to experience intrinsic motivation in end-user programming (EUP). We report two experiments: one that tests whether there are reliable psychometric constructs that describe different aspects of intrinsic motivation, and one that tests whether these constructs are successful in predicting individuals' own self-reported intrinsic motivation after using a popular EUP product. We conclude that there are identifiable and distinct motivational factors in EUP, and that these are associated with particular psychometric personality traits. We offer several suggestions for future research that could apply these findings to improve uptake and quality of user experience for educational and general-purpose EUP applications

Psychological targeting as an effective approach to digital mass persuasion

People are exposed to persuasive communication across many different contexts: governments, companies, and political parties use persuasive appeals to encourage people to eat healthier, purchase a particular product, or vote for a specific candidate. Laboratory studies show that such persuasive appeals are more effective in influencing behavior when they are tailored to individuals’ unique psychological characteristics. Yet, the investigation of large-scale psychological persuasion in the real world has been hindered by the questionnaire-based nature of psychological assessment. Recent research, however, shows that people’s psychological characteristics can be accurately predicted from their digital footprints, such as their Facebook Likes or Tweets. Capitalizing on this new form of psychological assessment from digital footprints, we test the effects of psychological persuasion on people’s actual behavior in an ecologically valid setting. In three field experiments that reached over 3.5 million individuals with psychologically-tailored advertising, we find that matching the content of persuasive appeals to individuals’ psychological characteristics significantly altered their behavior as measured by clicks and purchases. Persuasive appeals that were matched to people’s extraversion or openness-to-experience level resulted in up to 40% more clicks and up to 50% more purchases than their mismatching or un-personalized counterparts. Our findings suggest that the application of psychological targeting makes it possible to influence the behavior of large groups of people by tailoring persuasive appeals to the psychological needs of the target audiences. We discuss both the potential benefits of this method for helping individuals make better decisions and the potential pitfalls related to manipulation and privacy

A computer adaptive measure of delay discounting

Delay discounting has been linked to important behavioral, health, and social outcomes, including academic achievement, social functioning and substance use, but thoroughly measuring delay discounting is tedious and time consuming. We develop and consistently validate an efficient and psychometrically sound computer adaptive measure of discounting. First, we develop a binary search–type algorithm to measure discounting using a large international data set of 4,190 participants. Using six independent samples ($N$ = 1,550), we then present evidence of concurrent validity with two standard measures of discounting and a measure of discounting real rewards, convergent validity with addictive behavior, impulsivity, personality, survival probability; and divergent validity with time perspective, life satisfaction, age and gender. The new measure is considerably shorter than standard questionnaires, includes a range of time delays, can be applied to multiple reward magnitudes, shows excellent concurrent, convergent, divergent, and discriminant validity—by showing more sensitivity to effects of smoking behavior on discounting.Nehru Trust for Cambridge University, Cambridge Overseas Trus

A Review of Energy-for-water Data in Energy-water Nexus Publications

Published literature on the energy-water nexus continues to increase, yet much of the supporting data, particularly regarding energy-for-water, remains obscure or inaccessible. We perform a systematic review of literature that describes the primary energy and electricity demands for drinking water and wastewater systems in urban environments. This review provides an analysis of the underlying data and other properties of over 170 published studies by systematically creating metadata on each study. Over 45% of the evaluated studies utilized primary data sources (data collected directly from utilities), potentially enabling large-scale data sharing and a more comprehensive understanding of global water-related energy demand. The most prevalent geographic scale of the existing literature was at the individual city scale (39%), limiting comparisons between utilities. Additionally, energy-for-water studies span 34 different countries with 11 countries having at least 4 published studies. The analyzed literature often considered greenhouse gas emissions of energy demand as an important input for life cycle analysis, highlighting the broader impact of the energy-water nexus. As a result of the review, we identify several common practices for filling data gaps, discover that research and data are primarily concentrated in three countries (Australia, China, and the United States), and offer suggestions for the future of the energy-water nexus, specifically regarding energy-for-water

Age trends in musical preferences in adulthood: 1. Conceptualization and empirical investigation

This article aims to fill some gaps in theory and research on age trends in musical preferences in adulthood by presenting a conceptual model that describes three classes of determinants that can affect those trends. The Music Preferences in Adulthood Model (MPAM) posits that some psychological determinants that are extrinsic to the music (individual differences and social influences), and some that are intrinsic to the music (the perceived inner properties of the music), affect age differences in musical preferences in adulthood. We first present the MPAM, which aims to explain age trends in musical preferences in adulthood, and to identify which variables may be the most important determinants of those trends. We then validate a new test of musical preferences that assesses musical genres and clips in parallel. Finally, with a sample of 4,002 adults, we examine age trends in musical preferences for genres and clips, using our newly developed test. Our results confirm the presence of robust age trends in musical preferences, and provide a basis for the investigation of the extrinsic and intrinsic psychological determinants of musical preferences, in line with the MPAM framework.This research was supported by the Cambridge Commonwealth Trust and the Social Sciences and Humanities Research Council of Canada granted to the first author