What Are the Consequences of Consequentiality?

We offer an empirical test of a theoretical result in the contingent valuation literature. Specifically, it has been argued from a theoretical point of view that survey participants who perceive a survey to be ``consequential'' will respond to questions truthfully regardless of the degree of perceived consequentiality. Using survey data from the Iowa Lakes Project, we test this supposition. Specifically, we employ a Bayesian treatment effect model in which the degree of perceived consequentiality, measured as an ordinal response, is permitted to have a structural impact on willingness to pay (WTP) for a hypothetical environmental improvement. We test the theory by determining if the WTP distributions are the same for each value of the ordinal response. In our survey data, a subsample of individuals were randomly assigned supporting information suggesting that their responses to the questionnaires were important and will have an impact on policy decisions. In conjunction with a Bayesian posterior simulator, we use this source of exogenous variation to identify the structural impacts of consequentiality perceptions on willingness to pay, while controlling for the potential of confounding on unobservables. We find evidence consistent with the ``knife-edge'' theoretical results, namely that the willingness to pay distributions are equal among those believing the survey to be at least minimally consequential, and different for those believing that the survey is irrelevant for policy purposes.nonmarket valuation

Controlling for observed and unobserved site characteristics in RUM models of recreation demand

Random Utility Maximization (RUM) models of recreation demand are typically plagued by limited information on environmental and other attributes characterizing the available sites in the choice set. To the extent that these unobserved site attributes are correlated with the observed characteristics and/or the key travel cost variable, the resulting parameter estimates and subsequent welfare calculations are likely to be biased. In this paper we develop a Bayesian approach to estimating a RUM model that incorporates a full set of alternative specific constants, insulating the key travel cost parameter from the influence of the unobserved site attributes. In contrast to estimation procedures recently outlined in Murdock (2006), the posterior simulator we propose (combining data augmentation and Gibbs sampling techniques) can be used in the more general mixed logit framework in which some parameters of the conditional utility function are random. Following a series of generated data experiments to illustrate the performance of the simulator, we apply the estimation procedures to data from the Iowa Lakes Project. In contrast to an earlier study using the same data (Egan et al. [7]), we find that, with the addition of a full set of alternative specific constants, water quality attributes no longer appear to influence the choice of where to recreate

Controlling for observed and unobserved site characteristics in RUM models of recreation demand

Recreation demand models are typically plagued by limited information on site attributes. If these unobserved site attributes are correlated with the observed characteristics and/or the travel cost variable, the resulting parameter estimates are likely to be biased. We develop a Bayesian approach to estimating a model that incorporates a full set of alternative-speci c constants, insulating the key travel cost parameter from the in uence of unobservables. The proposed posterior simulator can be used in the mixed logit framework in which some parameters of the conditional utility function are random. We apply the estimation procedures to data from the Iowa Lakes Project.Hatch Act and State of Iowa, the Iowa Department of Natural Resources and the U.S. Environmental Protection Agency's Science to Achieve Results (STAR) program.Grant R830818.http://ajae.oxfordjournals.org/hb201

Semiparametric Bayesian inference in smooth coefficient models

We describe procedures for Bayesian estimation and testing in cross-sectional, panel data and nonlinear smooth coefficient models. The smooth coefficient model is a generalization of the partially linear or additive model wherein coefficients on linear explanatory variables are treated as unknown functions of an observable covariate. In the approach we describe, points on the regression lines are regarded as unknown parameters and priors are placed on differences between adjacent points to introduce the potential for smoothing the curves. The algorithms we describe are quite simple to implement - for example, estimation, testing and smoothing parameter selection can be carried out analytically in the cross-sectional smooth coefficient model. We apply our methods using data from the National Longitudinal Survey of Youth (NLSY). Using the NLSY data we first explore the relationship between ability and log wages and flexibly model how returns to schooling vary with measured cognitive ability. We also examine a model of female labor supply and use this example to illustrate how the described techniques can been applied in nonlinear settings

Emergence of fractal geometries in the evolution of a metabolic enzyme

Fractals are patterns that are self-similar across multiple length-scales. Macroscopic fractals are common in nature; however, so far, molecular assembly into fractals is restricted to synthetic systems. Here we report the discovery of a natural protein, citrate synthase from the cyanobacterium Synechococcus elongatus, which self-assembles into Sierpiński triangles. Using cryo-electron microscopy, we reveal how the fractal assembles from a hexameric building block. Although different stimuli modulate the formation of fractal complexes and these complexes can regulate the enzymatic activity of citrate synthase in vitro, the fractal may not serve a physiological function in vivo. We use ancestral sequence reconstruction to retrace how the citrate synthase fractal evolved from non-fractal precursors, and the results suggest it may have emerged as a harmless evolutionary accident. Our findings expand the space of possible protein complexes and demonstrate that intricate and regulatable assemblies can evolve in a single substitution

Controlling for Observed and Unobserved Site Characteristics in RUM Models of Recreation Demand

Recreation demand models are typically plagued by limited information on site attributes. If these unobserved site attributes are correlated with the observed characteristics and/or the travel cost variable, the resulting parameter estimates are likely to be biased. We develop a Bayesian approach to estimating a model that incorporates a full set of alternative-speci c constants, insulating the key travel cost parameter from the in uence of unobservables. The proposed posterior simulator can be used in the mixed logit framework in which some parameters of the conditional utility function are random. We apply the estimation procedures to data from the Iowa Lakes Project.Hatch Act and State of Iowa, the Iowa Department of Natural Resources and the U.S. Environmental Protection Agency's Science to Achieve Results (STAR) program.Grant R830818.http://ajae.oxfordjournals.org/hb201

Decoding the Molecular Universe -- Workshop Report

On August 9-10, 2023, a workshop was convened at the Pacific Northwest National Laboratory (PNNL) in Richland, WA that brought together a group of internationally recognized experts in metabolomics, natural products discovery, chemical ecology, chemical and biological threat assessment, cheminformatics, computational chemistry, cloud computing, artificial intelligence, and novel technology development. These experts were invited to assess the value and feasibility of a grand-scale project to create new technologies that would allow the identification and quantification of all small molecules, or to decode the molecular universe. The Decoding the Molecular Universe project would extend and complement the success of the Human Genome Project by developing new capabilities and technologies to measure small molecules (defined as non-protein, non-polymer molecules less than 1500 Daltons) of any origin and generated in biological systems or produced abiotically. Workshop attendees 1) explored what new understanding of biological and environmental systems could be revealed through the lens of small molecules; 2) characterized the similarities in current needs and technical challenges between each science or mission area for unambiguous and comprehensive determination of the composition and quantities of small molecules of any sample; 3) determined the extent to which technologies or methods currently exist for unambiguously and comprehensively determining the small molecule composition of any sample and in a reasonable time; and 4) identified the attributes of the ideal technology or approach for universal small molecule measurement and identification. The workshop concluded with a discussion of how a project of this scale could be undertaken, possible thrusts for the project, early proof-of-principle applications, and similar efforts upon which the project could be modeled

Efficacy and moderators of efficacy of cognitive behavioural therapies with a trauma focus in children and adolescents: an individual participant data meta-analysis of randomised trials

Background: Existing clinical trials of cognitive behavioural therapies with a trauma focus (CBTs-TF) are underpowered to examine key variables that might moderate treatment effects. We aimed to determine the efficacy of CBTs-TF for young people, relative to passive and active control conditions, and elucidate putative individual-level and treatment-level moderators. Methods: This was an individual participant data meta-analysis of published and unpublished randomised studies in young people aged 6-18 years exposed to trauma. We included studies identified by the latest UK National Institute of Health and Care Excellence guidelines (completed on Jan 29, 2018) and updated their search. The search strategy included database searches restricted to publications between Jan 1, 2018, and Nov 12, 2019; grey literature search of trial registries ClinicalTrials.gov and ISRCTN; preprint archives PsyArXiv and bioRxiv; and use of social media and emails to key authors to identify any unpublished datasets. The primary outcome was post-traumatic stress symptoms after treatment (<1 month after the final session). Predominantly, one-stage random-effects models were fitted. This study is registered with PROSPERO, CRD42019151954. Findings: We identified 38 studies; 25 studies provided individual participant data, comprising 1686 young people (mean age 13·65 years [SD 3·01]), with 802 receiving CBTs-TF and 884 a control condition. The risk-of-bias assessment indicated five studies as low risk and 20 studies with some concerns. Participants who received CBTs-TF had lower mean post-traumatic stress symptoms after treatment than those who received the control conditions, after adjusting for post-traumatic stress symptoms before treatment (b=-13·17, 95% CI -17·84 to -8·50, p<0·001, τ2=103·72). Moderation analysis indicated that this effect of CBTs-TF on post-traumatic stress symptoms post-treatment increased by 0·15 units (b=-0·15, 95% CI -0·29 to -0·01, p=0·041, τ2=0·03) for each unit increase in pre-treatment post-traumatic stress symptoms. Interpretation: This is the first individual participant data meta-analysis of young people exposed to trauma. Our findings support CBTs-TF as the first-line treatment, irrespective of age, gender, trauma characteristics, or carer involvement in treatment, with particular benefits for those with higher initial distress

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London