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Survey researchers have carefully modified their data collection operations for various reasons, including the rising costs of data collection and the ongoing Coronavirus disease (COVID-19) pandemic, both of which have made in-person interviewing difficult. For large national surveys that require household (HH) screening to determine survey eligibility, cost-efficient screening methods that do not include in-person visits need additional evaluation and testing. A new study, known as the American Family Health Study (AFHS), recently initiated data collection with a national probability sample, using a sequential mixed-mode mail/web protocol for push-to-web US HH screening (targeting persons aged 18–49 years). To better understand optimal approaches for this type of national screening effort, we embedded two randomized experiments in the AFHS data collection. The first tested the use of bilingual respondent materials where mailed invitations to the screener were sent in both English and Spanish to 50 percent of addresses with a high predicted likelihood of having a Spanish speaker and 10 percent of all other addresses. We found that the bilingual approach did not increase the response rate of high-likelihood Spanish-speaking addresses, but consistent with prior work, it increased the proportion of eligible Hispanic respondents identified among completed screeners, especially among addresses predicted to have a high likelihood of having Spanish speakers. The second tested a form of nonresponse follow-up, where a subsample of active sampled HHs that had not yet responded to the screening invitations was sent a priority mailing with a $5 incentive, adding to the $2 incentive provided for all sampled HHs in the initial screening invitation. We found this approach to be quite valuable for increasing the screening survey response rate.

Supplemental material, sj-docx-1-smr-10.1177_00491241221099550 for The Additional Effects of Adaptive Survey Design Beyond Post-Survey Adjustment: An Experimental Evaluation by Shiyu Zhang and James Wagner in Sociological Methods & Research

Supplemental material, sj-docx-1-smr-10.1177_00491241221099550 for The Additional Effects of Adaptive Survey Design Beyond Post-Survey Adjustment: An Experimental Evaluation by Shiyu Zhang and James Wagner in Sociological Methods & Research

Supplemental Material, sj-docx-1-smr-10.1177_00491241211031270 for Applying Responsive Survey Design to Small-Scale Surveys: Campus Surveys of Sexual Misconduct by William G. Axinn, James Wagner, Mick Couper and Scott Crawford in Sociological Methods & Research

Responsive survey designs introduce protocol changes to survey operations based on accumulating paradata. Case-level predictions, including response propensity, can be used to tailor data collection features in pursuit of cost or quality goals. Unfortunately, predictions based only on partial data from the current round of data collection can be biased, leading to ineffective tailoring. Bayesian approaches can provide protection against this bias. Prior beliefs, which are generated from data external to the current survey implementation, contribute information that may be lacking from the partial current data. Those priors are then updated with the accumulating paradata. The elicitation of the prior beliefs, then, is an important characteristic of these approaches. While historical data for the same or a similar survey may be the most natural source for generating priors, eliciting prior beliefs from experienced survey managers may be a reasonable choice for new surveys, or when historical data are not available. Here, we fielded a questionnaire to survey managers, asking about expected attempt-level response rates for different subgroups of cases, and developed prior distributions for attempt-level response propensity model coefficients based on the mean and standard error of their responses. Then, using respondent data from a real survey, we compared the predictions of response propensity when the expert knowledge is incorporated into a prior to those based on a standard method that considers accumulating paradata only, as well as a method that incorporates historical survey data, methods, data, analyses, Vol 14, No 2 (2020)

Supplemental Material, Supplemental_Material_Online_Harkema_09172019 for Influx, Persistence, and Recall of Eosinophils and GATA-3+ Innate Lymphoid Cells in the Nasal Mucosa of Mice Exposed and Reexposed to the Gaseous Air Pollutant Ozone by Jack R. Harkema, Elyse A. Eldridge, Ryan P. Lewandowski and James G. Wagner in Toxicologic Pathology

Supplemental material, appendix_1 for Defining Learning Communities in Undergraduate Medical Education: A National Study by Robert Shochet, Amy Fleming, James Wagner, Jorie Colbert-Getz, Monica Bhutiani, Kevin Moynahan and Meg Keeley in Journal of Medical Education and Curricular Development

Effects of airborne biological particulate matter (BioPM; from livestock farms) on the pulmonary airways are not well studied. The aim of the present study was to investigate whether fine (

Synthetic biology and metabolic engineering seek to re-engineer microbes into living foundries for the production of high value chemicals. Through a design-build-test cycle paradigm, massive libraries of genetically engineered microbes can be constructed and tested for metabolite overproduction and secretion. However, library generation capacity outpaces the rate of high-throughput testing and screening. Well plate assays are flexible but with limited throughput, whereas droplet microfluidic techniques are ultrahigh-throughput but require a custom assay for each target. Here we present RNA-aptamers-in-droplets (RAPID), a method that greatly expands the generality of ultrahigh-throughput microfluidic screening. Using aptamers, we transduce extracellular product titer into fluorescence, allowing ultrahigh-throughput screening of millions of variants. We demonstrate the RAPID approach by enhancing production of tyrosine and secretion of a recombinant protein in Saccharomyces cerevisiae by up to 28- and 3-fold, respectively. Aptamers-in-droplets affords a general approach for evolving microbes to synthesize and secrete value-added chemicals.Screening libraries of genetically engineered microbes for secreted products is limited by the available assay throughput. Here the authors combine aptamer-based fluorescent detection with droplet microfluidics to achieve high throughput screening of yeast strains engineered for enhanced tyrosine or streptavidin production.

Surveys are a critical resource for social, economic, and health research. The ability to efficiently collect these data and develop accurate post-survey adjustments depends upon reliable data about effort required to recruit sampled units. Level-of-effort paradata are data generated by interviewers during the process of collecting data in surveys. These data are often used as predictors in nonresponse adjustment models or to guide data collection efforts. However, recent research has found that these data may include measurement errors, which would lead to inaccurate decisions in the field or reduced effectiveness for adjustment purposes (Biemer, et al., 2013; West and Little, 2013). In order to assess whether errors occur in level-of-effort paradata, we introduce a new source of validation data for call records -- Global Positioning System (GPS) data generated by smartphones carried by interviewers. We examine the quality of the GPS data and then use the GPS data to characterize interviewer travel within sampled area segments. We also link the GPS data with the interviewer-reported call records in order to identify potential errors in the call records. Given the lack of a gold standard, we perform a sensitivity analysis under various assumptions to see how this would change our conclusions., Survey Research Methods, Vol 11, No 3 (2017): Special Issue: Uses of Geographic Information Systems Tools in Survey Data Collection and Analysis

Calculation of the deposition fractions in different regions of the respiratory system. Figure S1. Size distribution of the mass based concentration of CeO2 nanoparticles for four experiments based on the SMPS collected data. (DOCX 57 kb)

Technical report TR06-10. Background: Accurately quantifying the signature information of chemical shifts provides a foundation for accurate and complete sequential resonance assignment in protein NMR spectroscopy. A nearly complete assignment is a prerequisite for three dimensional protein structure calculation. Methods: A number of filtering steps are applied to construct two training datasets using known protein NMR data for learning scoring schemes to quantify the signature information. The scoring schemes are learned through a naive Bayesian method to use both intra-residue and inter-residue chemical shifts and to use the intermediate neural network output from the secondary structure predictor PsiPred. Results: Two training datasets ALL and HOMO for scoring scheme learning were carefully constructed. Based on these two datasets, a total of 16 scoring schemes were proposed and examined. An extensive simulation study was set up to validate these scoring schemes and the one that performed the best was implemented into a web server, which is publicly accessible. Conclusions: Through the extensive simulation study we found that the currently known protein NMR data is quite evenly distributed in terms of protein homology, and therefore homology removal in training dataset construction wouldn't gain a lot in the overall performance of the resultant scoring schemes. Also, we conclude that in general a naive Bayesian learning is better than a trivial distribution assumption. We believe this conclusion holds not just in our care but also for similar applications where the training data size is large. Another conclusion is that in applications where PsiPred prediction results are used as intermediate input, using its intermediate neural network output could be a better choice than using its the final prediction result. | TRID-ID TR06-10

In 2005, persistent online worlds — sometimes saddled with the unwieldy acronym MMORPGs, for “massively multiplayer online role playing games,” or somewhat less clumsily, MMOs — made the leap from niche entertainment to global mainstream medium. On a popularity metric, Worlds of Warcraft became the first game to surpass a million U.S. subscribers, while gaining a global audience over 4.5 million and counting (with a third of that from mainland China.) On an innovation scale, Second Life suggested the potential for MMOs to also be a development platform for commercial, educational, and research projects. As broadband and high end PCs saturate the international market, it’s time to consider MMOs as the likeliest candidate for the Internet’s next generation, supplanting the two dimensional, semi–interactive portal of the Web for an immersive, three–dimensional, fully interactive Metaverse of data. But a new medium requires new guidelines for understanding it, and it is here that many questions loom. What happens as users continue to employ MMOs for purposes beyond gaming or light socializing, when they become the first true meeting space for the world, where cultural, commercial, and political intercourse is conducted in real time in an immersive setting that feels real, even hyperreal? When they have a direct, measurable impact on real world news? And who will do the reporting to understand this profound shift? Unlike the Web revolution of the ’90s, documenting the emergence of online worlds is something that will be conducted from the inside, immersed within the media itself. Some tentative guidelines are therefore proposed, a new kind of journalistic ethics for a world where reality and identity are mutable and anonymity is both hazard and godsend. Based on nearly three years as Second Life’s official embedded journalist, the author suggests several principles, with the object to preserve a separation between real life identity and virtual being, while sustaining the fantastic, otherworldly nature of online worlds. Paradoxically, it’s argued, maintaining the illusion increases the value of online worlds as a journalistic tool, enabling a direct, intimate form of communication with diverse people throughout the world. At the same time, it enables us to see these worlds as model and microcosm for the socioeconomic realm of the world at large. In either case, these worlds can help us understand the conflicts and values of our own material world — and for good and ill, begin to shape them. To emphasize how crucial the need to understand this next dramatic shift for the Internet, the author offers five likely futures in which online worlds directly impact national and international politics and the global economy — a time when MMOs help decide the outcomes of real–world elections and influence long–established jurisprudence, while authoritarian government attempt to repress them, and they become the next theater for terrorist and counterterrorist infiltration.

Mathematical representation of the model. (DOCX 79 kb)

Individual organ concentrations of CeO2 nanoparticles for all experiments. (DOCX 39 kb)

Additional file 3: The influence of the ability of NPs to induce superoxide generation as measured in an acellular EPR assay on the different biomarkers of effects.

Concentrations found in feces in the pilot study. Error bars representing one standard deviation on the means. (DOCX 37 kb)

Mathematical representation of the model. (DOCX 79 kb)

Concentrations found in feces in the pilot study. Error bars representing one standard deviation on the means. (DOCX 37 kb)

Additional file 3: The influence of the ability of NPs to induce superoxide generation as measured in an acellular EPR assay on the different biomarkers of effects.

Individual organ concentrations of CeO2 nanoparticles for all experiments. (DOCX 39 kb)

Time history of nanoparticles in the individual organs for all experiments. (DOCX 122 kb)