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Recommender systems are the engine of online advertising. Not only do they suggest movies, music, or romantic partners, but they also are used to select which advertisements to show to users. This paper reviews the basics of recommender system methodology and then looks at the emerging arena of active recommender systems. [ABSTRACT FROM AUTHOR]

Understanding museum activism Drawing on Ann Rigney's[8] work in the field of memory activism, in this Special Issue we think about activism in museums, and associated forms of education, in three forms: museum activism, museums I in i activism, and museums I of i activism. Museum activism can be viewed as the practice undertaken by museums to influence and alter future practice, engaging with social needs. Museum as Muck is a vital form of activism within UK museums both for the care and space it provides for its members and for the direct interventions they undertake with museum workers and students. This echoes the values-led calls for museum activism outlined above. museums I in i activism refers to occasions where museum sites become places of or utilized in other forms of activism. [Extracted from the article]

Turkey's 2019 acquisition of Russian S-400 missile batteries is puzzling. Despite repeated threats of sanctions by the United States, North Atlantic Treaty Organization ally Turkey purchased a multi-billion-dollar Russian air defense system that remains nonoperational, fails to cover Turkey's air defense gap, and led to Turkey's costly expulsion from the F-35 program. We argue unexpected domestic constraints created by the ruling Justice and Development Party (AKP)'s symbolic diplomacy raised the political costs of backing away from the deal. Collecting data from media reports and interviews, we analyze how Turkey's AKP wielded the S-400 as a weapons system legitimating an identity narrative of Turkey as regional counterhegemon, facilitating the cultivation of coalitions with multiple, often competing, constituencies. We demonstrate via process tracing how the inherent ambiguity of symbols allowed nationalist constituencies key to the AKP's hold on power to amplify the S-400 as symbolic of Turkey's sovereignty, trapping Turkish officials in a costly policy corner. In unpacking Turkey's S-400 purchase, the article contributes to the literature on symbolic diplomacy, audience costs, weapons procurement, and deterrence failure. [ABSTRACT FROM AUTHOR]

Sometimes the Joint Statistical Meetings (JSM) is frustrating to attend, because multiple sessions on the same topic are scheduled at the same time. This article uses seeded latent Dirichlet allocation and a scheduling optimization algorithm to very significantly reduce overlapping content in the original schedule for the 2020 JSM program. Specifically, a measure based on total variation distance that ranges from 0 (random scheduling) to 1 (no overlapping content) finds that the original schedule had a score of 0.058, whereas our proposed schedule achieved a score of 0.371. This is a huge improvement that would (i) increase participant satisfaction as measured by the post-JSM satisfaction survey, and (ii) save the American Statistical Association significant money by obviating the need for the traditional in-person meeting of the 47 program chairs and other organizers. The methodology developed in this work immediately applies to future JSMs and is easily modified to improve scheduling for any other scientific conference that has parallel sessions. [ABSTRACT FROM AUTHOR]

Cities, like the people that live in them, are subject to the attention economy. Familiar social media platforms aggregate users' tastes and reconstitute them as advertising and curated content. In this paper, I show that American cities are induced by state governments to adopt the attention-grabbing tactics of social media influencers. This is particularly evident in cultural planning as it relates to economic development. While this is a global phenomenon, I have chosen to focus on the Capital Region of New York State, a region approximately 240 kilometres north of New York City. I have chosen the Capital Region because New York's nine-year-old system of Regional Economic Development Councils highlights the competitive and often capricious environment that urbanists increasingly find themselves in. Through an analysis of planning documents, reported events and secondary sources I demonstrate how small to medium cities in Upstate New York are competing to be the purveyors of authentic urban living. I then discuss how authenticity and social media interact to create desires for consumption of identity performance. Finally, I compare the city authentic branding regime with the 'Bilbao effect' and show how the former can summon the effects of the latter without a 'star' architect. [ABSTRACT FROM AUTHOR]

Agent-based models (ABMs) are popular in many research communities, but few statisticians have contributed to their theoretical development. They are models like any other models we study, but in general, we are still learning how to fit ABMs to data and how to make quantified statements of uncertainty about the outputs of an ABM. ABM validation is also an underdeveloped area that is ripe for new statistical developments. In what follows, we lay out the research space and encourage statisticians to address the many research issues in the ABM ambit. [ABSTRACT FROM AUTHOR]

Policy-makers should perform a cost-benefit analysis before initiating a war. This article describes a methodology for such assessment, and applies it post hoc to five military actions undertaken by the United States between 1950 and 2000 (the Korean War, the Vietnam War, the invasion of Grenada, the invasion of Panama, and the First Gulf War). The analysis identifies three broad categories of value: human capital, economic outcomes, and national influence. Different stakeholders (politicians, generals, industry, etc.) may assign different weights to these three categories, so this analysis tabulates each separately, and then, as may sometimes be necessary, monetizes them for unified comparison. [ABSTRACT FROM AUTHOR]

This study identifies pediatric cancer clusters in Florida for the years 2000–2015. Unlike previous publications on pediatric cancers in Florida, it draws upon an Environmental Protection Agency dataset on carcinogenic air pollution, the National Air Toxics Assessment, as well as more customary demographic variables (age, sex, race). The focus is upon the three most widely seen pediatric cancer types in the USA: brain tumors, leukemia, and lymphomas. The covariates are used in a Poisson regression to predict cancer incidence. The adjusted cluster analysis quantifies the role of each covariate. Using Florida Association of Pediatric Tumor Programs data for 2000–2015, we find statistically significant pediatric cancer clusters, but we cannot associate air pollution with the cancer incidence. for this article are available online. [ABSTRACT FROM AUTHOR]

Traffic flow count data in networks arise in many applications, such as automobile or aviation transportation, certain directed social network contexts, and Internet studies. Using an example of Internet browser traffic flow through site-segments of an international news website, we present Bayesian analyses of two linked classes of models which, in tandem, allow fast, scalable, and interpretable Bayesian inference. We first develop flexible state-space models for streaming count data, able to adaptively characterize and quantify network dynamics efficiently in real-time. We then use these models as emulators of more structured, time-varying gravity models that allow formal dissection of network dynamics. This yields interpretable inferences on traffic flow characteristics, and on dynamics in interactions among network nodes. Bayesian monitoring theory defines a strategy for sequential model assessment and adaptation in cases when network flow data deviate from model-based predictions. Exploratory and sequential monitoring analyses of evolving traffic on a network of web site-segments in e-commerce demonstrate the utility of this coupled Bayesian emulation approach to analysis of streaming network count data. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

The heat pump is a tool for extracting low temperature heat from the environment (e.g. from the shallow geosphere) and supplying it for space heating at a higher temperature. It is noteworthy that so much of the pioneering work that allowed the development of this tool was associated with Scottish scientists and engineers. William Cullen’s experimentation led to an understanding of the transfer of latent heat (which takes place at the evaporator of the heat pump). William Rankine and the Stirling brothers worked on the thermodynamic cycles that lie at the heart of many heat pumps and low temperature heat engines. William Thomson (Lord Kelvin) first proposed the use of the heat pump for space heating and, with James David Forbes, worked on an understanding of the behaviour of heat in the ground. [ABSTRACT FROM AUTHOR]

The dominant microbial components of fluids from wells in pristine and water-injected, high-temperature, Western Siberian oil fields, were analyzed by PCR-DGGE. Particular emphasis was placed on sulphate-reducing organisms, due to their ecological and industrial importance. Bacterial phylotypes obtained from the non-water-injected Stolbovoye oil field were more diverse than those from the Samotlor field, which is subject to secondary oil recovery by reinjection of recycled production water. The majority of phylotypes from both sites were related to Firmicutes. The low similarity to their closest relatives indicates unique bacterial communities in deep underground production waters and crude oil. Archaeal phylotypes detected only in the Samotlor samples were represented by Methanosarcinales and Methanobacteriales. [ABSTRACT FROM PUBLISHER]

Dr T. G. N. 'Graeme' Haldane was a visionary proponent of a national, rational electricity strategy. He was a pioneer of the National Grid and displayed a keen, early interest in nuclear power and renewable energy sources. It appears that he was the first engineer in Britain (and, possibly, internationally) to construct, monitor and document the performance of a heat pump system for space heating. He built his experimental heat pump system at the Foswell Estate, Auchterarder, Perthshire, Scotland. The environmental heat source that he used was the estate's water supply, which is likely to have been derived from groundwater springs in the estate grounds. In this case, Haldane's heat pump can be described as Britain's earliest ground-source heat pump. [ABSTRACT FROM AUTHOR]

Multiple systems estimation (MSE) is becoming an increasingly common approach for exploratory study of underreported events in the field of quantitative human rights. In this context, it is used to estimate the number of people who died as a result of political unrest when it is believed that many of those who died or disappeared were never reported. MSE relies upon several assumptions, each of which may be slightly or significantly violated in particular applications. This article outlines the evolution of the application of MSE to human rights research through the use of three case studies: Guatemala, Peru, and Colombia. Each of these cases presents distinct challenges to the MSE method. Motivated by these applications, we describe new methodology for assessing the impact of violated assumptions in MSE. Our approach uses simulations to explore the cumulative magnitude of errors introduced by violation of the model assumptions at each stage in the analysis. [ABSTRACT FROM AUTHOR]

Background: No standardized educational curriculum exists for pediatric sedation practitioners. We sought to describe the curriculum and implementation of a pediatric sedation provider course and assess learner satisfaction with the course curriculum.Description: The course content was determined by formulating a needs assessment using published sedation guidelines, reports of sedation related adverse events, and a survey of sedation practitioners. Students provided feedback regarding satisfaction with the course immediately following the course and 6 months later.Evaluation: The course consisted of 5 didactic lectures, 1 small-group session, 6 simulation scenarios, a course syllabus, and a written examination. The course was conducted over 1 day at 3 different locations. Sixty-nine students completed the course and were uniformly satisfied with the course curriculum.Conclusions: A standardized pediatric sedation provider course was developed for sedation practitioners and consisted of a series of lectures and simulation scenarios. Overall satisfaction with the course was positive. [ABSTRACT FROM AUTHOR]

Objective. Biomarkers for preterm labor (PTL) and delivery can be discovered through the analysis of the transcriptome (transcriptomics) and protein composition (proteomics). Characterization of the global changes in low-molecular weight compounds which constitute the 'metabolic network' of cells (metabolome) is now possible by using a 'metabolomics' approach. Metabolomic profiling has special advantages over transcriptomics and proteomics since the metabolic network is downstream from gene expression and protein synthesis, and thus more closely reflects cell activity at a functional level. This study was conducted to determine if metabolomic profiling of the amniotic fluid can identify women with spontaneous PTL at risk for preterm delivery, regardless of the presence or absence of intraamniotic infection/inflammation (IAI). Study Design. Two retrospective cross-sectional studies were conducted, including three groups of pregnant women with spontaneous PTL and intact membranes: (1) PTL who delivered at term; (2) PTL without IAI who delivered preterm; and (3) PTL with IAI who delivered preterm. The first was an exploratory study that included 16, 19, and 20 patients in groups 1, 2, and 3, respectively. The second study included 40, 33, and 40 patients in groups 1, 2, and 3, respectively. Amniotic fluid metabolic profiling was performed by combining chemical separation (with gas and liquid chromatography) and mass spectrometry. Compounds were identified using authentic standards. The data were analyzed using discriminant analysis for the first study and Random Forest for the second. Results. (1) In the first study, metabolomic profiling of the amniotic fluid was able to identify patients as belonging to the correct clinical group with an overall 96.3% (53/55) accuracy; 15 of 16 patients with PTL who delivered at term were correctly classified; all patients with PTL without IAI who delivered preterm neonates were correctly identified as such (19/19), while 19/20 patients with PTL and IAI were correctly classified. (2) In the second study, metabolomic profiling was able to identify patients as belonging to the correct clinical group with an accuracy of 88.5% (100/113); 39 of 40 patients with PTL who delivered at term were correctly classified; 29 of 33 patients with PTL without IAI who delivered preterm neonates were correctly classified. Among patients with PTL and IAI, 32/40 were correctly classified. The metabolites responsible for the classification of patients in different clinical groups were identified. A preliminary draft of the human amniotic fluid metabolome was generated and found to contain products of the intermediate metabolism of mammalian cells and xenobiotic compounds (e.g. bacterial products and Salicylamide). Conclusion. Among patients with spontaneous PTL with intact membranes, metabolic profiling of the amniotic fluid can be used to assess the risk of preterm delivery in the presence or absence of infection/inflammation. [ABSTRACT FROM AUTHOR]

Applications in counterterrorism and corporate competition have led to the development of new methods for the analysis of decision making when there are intelligent opponents and uncertain outcomes. This field represents a combination of statistical risk analysis and game theory, and is sometimes called adversarial risk analysis. In this article, we describe several formulations of adversarial risk problems, and provide a framework that extends traditional risk analysis tools, such as influence diagrams and probabilistic reasoning, to adversarial problems. We also discuss the research challenges that arise when dealing with these models, illustrate the ideas with examples from business, and point out relevance to national defense. [ABSTRACT FROM AUTHOR]

The ever-growing number of high-dimensional, superlarge databases requires effective analysis techniques to mine interesting information from the data. Development of new-wave methodologies for high-dimensional nonparametric regression has exploded over the last decade in an effort to meet these analysis demands. This article reports on an extensive simulation experiment that compares the performance of ten different, commonly-used regression techniques: linear regression, stepwise linear regression, additive models (AM), projection pursuit regression (PPR), recursive partitioning regression (RPR), multivariate adaptive regression splines (MARS), alternating conditional expectations (ACE), additivity and variance stabilization (AVAS), locally weighted regression (LOESS), and neural networks. Each regression technique was used to analyze multiple datasets each having a unique embedded structure; the accuracy of each technique was determined by its ability to correctly identify the embedded structure averaged over all the datasets. Datasets used in the experiment were constructed so as to have particular properties which varied across the datasets in order to determine each technique's accuracy within various environments. The dataset properties which were varied include dimension of the data, the true dimension of the embedded structure, the sample size, the amount of noise, and the complexity of the embedded structure. Analyses of the results show that all of these properties affect the accuracy of each regression technique under investigation. A mapping from data characteristics to the most effective regression technique(s) is suggested. [ABSTRACT FROM AUTHOR]

This article reports an exploratory analysis of human-rights data compiled for 74 countries during 1982-1983. The information is combined with social, demographic, and economic indexes, then subjected to the scrutiny of CART, nearest-neighbor clustering, and other classification and clustering algorithms. Human-rights data separate most nations into one of seven categories; these categories can also be accurately predicted from widely available social and economic indexes. The results suggest that one need monitor only a small number of human-rights indexes to capture most of the original information, thus reducing the cost and complexity of human-rights assessment. Also, the analysis discovers socioeconomic indexes associated with certain patterns of human-rights violation, and this may enable a better understanding of climates that foster compliance with the International Bill of Rights. [ABSTRACT FROM AUTHOR]

This paper describes mathematical models for network evolution when ties (edges) are directed and the node set is fixed. Each of these models implies a specific type of departure from the standard null binomial model. We provide statistical tests that, in keeping with these models, are sensitive to particular types of departures from the null. Each model (and associated test) discussed follows directly from one or more socio-cognitive theories about how individuals alter the colleagues with whom they are likely to interact. The models include triad completion models, degree variance models, polarization and balkanization models, the Holland-Leinhardt models, metric models, and the constructural model. We find that many of these models, in their basic form, tend asymptotically towards an equilibrium distribution centered at the completely connected network (i.e., all individuals are equally likely to interact with all other individuals); a fact that can inhibit the development of satisfactory tests. [ABSTRACT FROM AUTHOR]

Various theoretical concerns often require researchers to answer questions of the form does co-member- ship in a group predict other ties between those individuals. Data appropriate for answering such a question often is referred to as network data Network data exhibits row-column dependencies that often invalidate traditional statistical methods for doing group comparisons such as analysis of variance and the Kruskal-Wallis Procedure. Because of the positive dependence within rows/columns the significance probabilities of such traditional methods may be exaggerated. This paper uses restricted-randomization to develop exact permutation tests for network data where co-membership in coups can be specified a priori. This enables the nonparametric estimation of the significance of standard statistics for group- difference tests and ordered-alternative tests where the group orderings have been prespecified. These methods are demonstrated by examining three different data sets: Sampson's Monastery data, Carley's Tutor Selection data, and Humana's Human Rights data. [ABSTRACT FROM AUTHOR]

The article focuses on the comments and encouragement of the discussants of the periodical "The American Statistician" who helped to build the statistical field. Jay Kadane shared themes with Steve Fienberg, wherein both pointed to the origin of capture-recapture modeling in census adjustment. Fienberg review the history behind the methodology and the development of the log-linear models. Fritz Scheuren has more field experiences in creating human rights statistics.

The article discusses the decision by the journal to post at the "Statistics and Public Policy" website a series of papers which study data from the Florida Pediatric Cancer Studies from multiple perspectives.

Presents a letter to the editor commenting on the article "A History of the Metropolis-Hastings Algorithm," by D.B. Hitchcock, which appeared in the 57th volume of the periodical "The American Statistician".