The Mountain West Clinical & Translational Research Infrastructure Network (MW CTR-IN), hosted at the University of Nevada, Las Vegas, and supported by the National Institute of General Medical Sciences at the National Institutes of Health, began as a partnership among 13 major U.S. public universities across 7 MW Institutional Development Award (IDeA) States, stretched across 1/3rd of the U.S. land mass and encompassed almost 1/3rd of all IDeA States. The mission of the MW CTR-IN is to build and enhance infrastructure capacity to increase CTR in the MW region. This case study describes the Clinical Pilot Projects Program (CP3) processes and tools used to support this objective through its selection of applications to fund, supporting applicants and funded investigators, and providing guidance and oversight during the funding period. The MW CTR-IN has funded 152 single-investigator pilot projects, 7 multisite pilot projects, 13 developmental team grant projects, and 14 community-engaged projects. These projects have also led to over $92M in extramural grant funding, 308 presentations, and 1,124 peer-reviewed publications. The methodologies and expertise we gained can assist other CTR networks in developing efficient pilot project programs that have been evaluated and demonstrated to improve CTR initiatives, especially through the use of a custom portal.

This paper considers the reflection unidentifiability problem in confirmatory factor analysis (CFA) and the associated implications for Bayesian estimation. We note a direct analogy between the multimodality in CFA models that is due to all possible column sign changes in the matrix of loadings and the multimodality in finite mixture models that is due to all possible relabelings of the mixture components. Drawing on this analogy, we derive and present a simple approach for dealing with reflection in variance in Bayesian factor analysis. We recommend fitting Bayesian factor analysis models without rotational constraints on the loadings—allowing Markov chain Monte Carlo algorithms to explore the full posterior distribution—and then using a relabeling algorithm to pick a factor solution that corresponds to one mode. We demonstrate our approach on the case of a bifactor model; however, the relabeling algorithm is straightforward to generalize for handling multimodalities due to sign invariance in the likelihood in other factor analysis models.

We discuss the applicability of quasilinear-type approximations for a turbulent system with a large range of spatial and temporal scales. We consider a paradigm fluid system of rotating convection with vertical and horizontal temperature gradients. In particular, the interaction of rotation with the horizontal temperature gradient drives a ‘thermal wind’ shear flow whose strength is controlled by the horizontal temperature gradient. Varying this parameter therefore systematically alters the ordering of the shearing time scale, the convective time scale and the correlation time scale. We demonstrate that quasilinear-type approximations work well when the shearing time scale or the correlation time scale is sufficiently short. In all cases, the generalised quasilinear approximation systematically outperforms the quasilinear approximation. We discuss the consequences for statistical theories of turbulence interacting with mean gradients.

People who inject drugs are at risk of acute bacterial and fungal injecting-related infections. There is evidence that incidence of hospitalizations for injecting-related infections are increasing in several countries, but little is known at an individual level. We aimed to examine injecting-related infections in a linked longitudinal cohort of people who inject drugs in Melbourne, Australia. A retrospective descriptive analysis was conducted to estimate the prevalence and incidence of injecting-related infections using administrative emergency department and hospital separation datasets linked to the SuperMIX cohort, from 2008 to 2018. Over the study period, 33% (95%CI: 31–36%) of participants presented to emergency department with any injecting-related infections and 27% (95%CI: 25–30%) were admitted to hospital. Of 1,044 emergency department presentations and 740 hospital separations, skin and soft tissue infections were most common, 88% and 76%, respectively. From 2008 to 2018, there was a substantial increase in emergency department presentations and hospital separations with any injecting-related infections, 48 to 135 per 1,000 person-years, and 18 to 102 per 1,000 person-years, respectively. The results emphasize that injecting-related infections are increasing, and that new models of care are needed to help prevent and facilitate early detection of superficial infection to avoid potentially life-threatening severe infections.

We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bi-static radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also allow studies of (a) the relative contributions of coherent (such as discrete internal conducting layers with sub-centimeter transverse scale) vs incoherent (e.g. bulk volumetric) scattering, (b) the magnitude of internal layer reflection coefficients, (c) limits on signal propagation velocity asymmetries (‘birefringence’) and (d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that (1) attenuation lengths approach 1 km in our band, (2) after averaging 10 000 echo triggers, reflected signals observable over the thermal floor (to depths of ~1500 m) are consistent with being entirely coherent, (3) internal layer reflectivities are ≈–60$\to$–70 dB, (4) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to South Pole and (5) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.

We tested the effectiveness of 23 disinfectants used in healthcare facilities against isolates from the 4 major clades of Candida auris. Sporicidal disinfectants were consistently effective, whereas quaternary-ammonium disinfectants had limited activity. Quaternary-ammonium–alcohol and hydrogen-peroxide–based disinfectants varied in effectiveness against C. auris.

Separation or “perfect prediction” is a common problem in discrete choice models that, in practice, leads to inflated point estimates and standard errors. Standard statistical packages do not provide clear advice on how to correct these problems. Furthermore, separation can go completely undiagnosed in fitting advanced models that optimize a user-supplied log-likelihood rather than relying on pre-programmed estimation procedures. In this paper, we both describe the problems that separation can cause and address the issue of detecting it in empirical models of strategic interaction. We then consider several solutions based on penalized maximum likelihood estimation. Using Monte Carlo experiments and a replication study, we demonstrate that when separation is detected in the data, the penalized methods we consider are superior to ordinary maximum likelihood estimators.

People who possess greater mathematical skills (i.e., numeracy) are generally more accurate in interpreting numerical data than less numerate people. However, recent evidence has suggested that more numerate people may use their numerical skills to interpret data only if their initial interpretation conflicts with their worldview. That is, if an initial, intuitive (but incorrect) interpretation of data appears to disconfirm one’s beliefs, then numerical skills are used to further process the data and reach the correct interpretation, whereas numerical skills are not used in situations where an initial incorrect interpretation of the data appears to confirm one’s beliefs (i.e., motivated numeracy). In the present study, participants were presented with several data problems, some with correct answers confirming their political views and other disconfirming their views. The difficulty of these problems was manipulated to examine how numeracy would influence the rate of correct responses on easier vs. more difficult problems. Results indicated that participants were more likely to answer problems correctly if the correct answer confirmed rather than disconfirmed their political views, and this response pattern did not depend on problem difficulty or numerical skill. Although more numerate participants were more accurate overall, this was true both for problems in which the correct answer confirmed and disconfirmed participants’ political views.

Over the last 25 years, radiowave detection of neutrino-generated signals, using cold polar ice as the neutrino target, has emerged as perhaps the most promising technique for detection of extragalactic ultra-high energy neutrinos (corresponding to neutrino energies in excess of 0.01 Joules, or 1017 electron volts). During the summer of 2021 and in tandem with the initial deployment of the Radio Neutrino Observatory in Greenland (RNO-G), we conducted radioglaciological measurements at Summit Station, Greenland to refine our understanding of the ice target. We report the result of one such measurement, the radio-frequency electric field attenuation length $L_\alpha$. We find an approximately linear dependence of $L_\alpha$ on frequency with the best fit of the average field attenuation for the upper 1500 m of ice: $\langle L_\alpha \rangle = ( ( 1154 \pm 121) - ( 0.81 \pm 0.14) \, ( \nu /{\rm MHz}) ) \,{\rm m}$ for frequencies ν ∈ [145 − 350] MHz.