Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased Type I and Type II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in online supplemental materials.

This manuscript aims to contribute to the next phase of mechanisms of behavior change (MOBC) science on alcohol or other drug use. Specifically, we encourage the transition from a basic science orientation (i.e., knowledge generation) to a translational science orientation (i.e., knowledge application or Translational MOBC Science). To inform that transition, we examine MOBC science and implementation science and consider how these two research areas can intersect to capitalize on the goals, strengths, and key methodologies of each. First, we define MOBC science and implementation science and offer a brief historical rationale for these two areas of clinical research. Second, we summarize similarities in rationale and discuss two scenarios where one draws from the other-MOBC science on implementation strategy outcomes and implementation science on MOBC. We then focus on the latter scenario, and briefly review the MOBC knowledge base to consider its readiness for knowledge translation. Finally, we provide a series of research recommendations to facilitate the translation of MOBC science. These recommendations include: (1) identifying and targeting MOBC that are well suited for implementation, (2) use of MOBC research results to inform broader health behavior change theory, and (3) triangulation of a more diverse set of research methodologies to build a translational MOBC knowledge base. Ultimately, it is important for gains borne from MOBC science to affect direct patient care, while basic MOBC research continues to be developed and refined over time. Potential implications of these developments include greater clinical significance for MOBC science, an efficient feedback loop between clinical research methodologies, a multi-level approach to understanding behavioral change, and reduced or eliminated siloes between MOBC science and implementation science.

The ARIANNA hexagonal radio array (HRA) is an experiment in its pilot phase designed to detect cosmogenic neutrinos of energies above 1016 eV. The most neutrino-like background stems from the radio emission of air showers. This article reports on dedicated efforts of simulating and detecting the signals of cosmic rays. A description of the fully radio self-triggered data-set, the properties of the detected air shower signals in the frequency range of 100–500 MHz and the consequences for neutrino detection are given. 38 air shower signals are identified by their distinct waveform characteristics, are in good agreement with simulations and their signals provide evidence that neutrino-induced radio signals will be distinguishable with high efficiency in ARIANNA. The cosmic ray flux at a mean energy of 6.5−1.0+1.2×1017 eV is measured to be 1.1−0.7+1.0×10−16 eV−1 km−2 sr−1 yr−1 and one five-fold coincident event is used to illustrate the capabilities of the ARIANNA detector to reconstruct arrival direction and energy of air showers.

Autoimmune polyendocrine syndrome type 1 (APS1) is a monogenic disorder that features multiple autoimmune disease manifestations. It is caused by mutations in the Autoimmune regulator (AIRE) gene, which promote thymic display of thousands of peripheral tissue antigens in a process critical for establishing central immune tolerance. We here used proteome arrays to perform a comprehensive study of autoimmune targets in APS1. Interrogation of established autoantigens revealed highly reliable detection of autoantibodies, and by exploring the full panel of more than 9000 proteins we further identified MAGEB2 and PDILT as novel major autoantigens in APS1. Our proteome-wide assessment revealed a marked enrichment for tissue-specific immune targets, mirroring AIRE's selectiveness for this category of genes. Our findings also suggest that only a very limited portion of the proteome becomes targeted by the immune system in APS1, which contrasts the broad defect of thymic presentation associated with AIRE-deficiency and raises novel questions what other factors are needed for break of tolerance.

Ongoing experimental efforts in Antarctica seek to detect ultra-high energy neutrinos by measurement of radio-frequency (RF) Askaryan radiation generated by the collision of a neutrino with an ice molecule. An array of RF antennas, deployed either in-ice or in-air, is used to infer the properties of the neutrino. To evaluate their experimental sensitivity, such experiments require a refractive index model for ray tracing radio-wave trajectories from a putative in-ice neutrino interaction point to the receiving antennas; this gives the degree of signal absorption or ray bending from source to receiver. The gradient in the density profile over the upper 200 meters of Antarctic ice, coupled with Fermat's least-time principle, implies ray "bending" and the existence of "forbidden" zones for predominantly horizontal signal propagation at shallow depths. After re-deriving the formulas describing such shadowing, we report on experimental results that, somewhat unexpectedly, demonstrate the existence of electromagnetic wave transport modes from nominally shadowed regions. The fact that this shadow-signal propagation is observed both at South Pole and the Ross Ice Shelf in Antarctica suggests that the effect may be a generic property of polar ice, with potentially important implications for experiments seeking to detect neutrinos.

The measurement of ultra-high energy (UHE) neutrinos (E > 1016 eV) opens a new field of astronomy with the potential to reveal the sources of ultra-high energy cosmic rays especially if combined with observations in the electromagnetic spectrum and gravitational waves. The ARIANNA pilot detector explores the detection of UHE neutrinos with a surface array of independent radio detector stations in Antarctica which allows for a cost-effective instrumentation of large volumes. Twelve stations are currently operating successfully at the Moore's Bay site (Ross Ice Shelf) in Antarctica and at the South Pole. We will review the current state of ARIANNA and its main results. We report on a newly developed wind generator that successfully operates in the harsh Antarctic conditions and powers the station for a substantial time during the dark winter months. The robust ARIANNA surface architecture, combined with environmentally friendly solar and wind power generators, can be installed at any deep ice location on the planet and operated autonomously. We report on the detector capabilities to determine the neutrino direction by reconstructing the signal arrival direction of a 800 m deep calibration pulser, and the reconstruction of the signal polarization using the more abundant cosmic-ray air showers. Finally, we describe a large-scale design – ARIA – that capitalizes on the successful experience of the ARIANNA operation and is designed sensitive enough to discover the first UHE neutrino.

Ultra high energy neutrinos (Eν > 1016.5eV) are efficiently measured via radio signals following a neutrino interaction in ice. An antenna placed1(15 m) below the ice surface will measure two signals for the vast majority of events (90% at Eν=1018 eV): a direct pulse and a second delayed pulse from a reflection off the ice surface. This allows for a unique identification of neutrinos against backgrounds arriving from above. Furthermore, the time delay between the direct and reflected signal (D'n'R) correlates with the distance to the neutrino interaction vertex, a crucial quantity to determine the neutrino energy. In a simulation study, we derive the relation between time delay and distance and study the corresponding experimental uncertainties in estimating neutrino energies. We find that the resulting contribution to the energy resolution is well below the natural limit set by the unknown inelasticity in the initial neutrino interaction. We present an in-situ measurement that proves the experimental feasibility of this technique. Continuous monitoring of the local snow accumulation in the vicinity of the transmit and receive antennas using this technique provide a precision of (1 mm) in surface elevation, which is much better than that needed to apply the D'n'R technique to neutrinos.

The ARIANNA experiment is an Askaryan detector designed to record radio signals induced by neutrino interactions in the Antarctic ice. Because of the low neutrino flux at high energies (Eν > 1016 eV), the physics output is limited by statistics. Hence, an increase in sensitivity significantly improves the interpretation of data and offers the ability to probe new parameter spaces. The amplitudes of the trigger threshold are limited by the rate of triggering on unavoidable thermal noise fluctuations. We present a real-time thermal noise rejection algorithm that enables the trigger thresholds to be lowered, which increases the sensitivity to neutrinos by up to a factor of two (depending on energy) compared to the current ARIANNA capabilities. A deep learning discriminator, based on a Convolutional Neural Network (CNN), is implemented to identify and remove thermal events in real time. We describe a CNN trained on MC data that runs on the current ARIANNA microcomputer and retains 95% of the neutrino signal at a thermal noise rejection factor of 105, compared to a template matching procedure which reaches only 102 for the same signal efficiency. Then the results are verified in a lab measurement by feeding in generated neutrino-like signal pulses and thermal noise directly into the ARIANNA data acquisition system. Lastly, the same CNN is used to classify cosmic-rays events to make sure they are not rejected. The network classified 102 out of 104 cosmic-ray events as signal.

The sources of ultra-high energy (UHE) cosmic rays, which can have energies up to 1020 eV, remain a mystery. UHE neutrinos may provide important clues to understanding the nature of cosmic-ray sources. ARIANNA aims to detect UHE neutrinos via radio (Askaryan) emission from particle showers when a neutrino interacts with ice, which is an efficient method for neutrinos with energies between 1016 eV and 1020 eV. The ARIANNA radio detectors are located in Antarctic ice just beneath the surface. Neutrino observation requires that radio pulses propagate to the antennas at the surface with minimum distortion by the ice and firn medium. Using the residual hole from the South Pole Ice Core Project, radio pulses were emitted from a transmitter located up to 1.7 km below the snow surface. By measuring these signals with an ARIANNA surface station, the angular and polarization reconstruction abilities are quantified, which are required to measure the direction of the neutrino. After deconvolving the raw signals for the detector response and attenuation from propagation through the ice, the signal pulses show no significant distortion and agree with a reference measurement of the emitter made in an anechoic chamber. Furthermore, the signal pulses reveal no significant birefringence for our tested geometry of mostly vertical ice propagation. The origin of the transmitted radio pulse was measured with an angular resolution of 0.37◦ indicating that the neutrino direction can be determined with good precision if the polarization of the radio-pulse can be well determined. In the present study we obtained a resolution of the polarization vector of 2.7◦. Neither measurement show a significant offset relative to expectation.

The ARIANNA detector is designed to detect neutrinos with energies above 1017 eV. Due to the similarities in generated radio signals, cosmic rays are often used as test beams for neutrino detectors. Some ARIANNA detector stations are equipped with antennas capable of detecting air showers. Since the radio emission properties of air showers are well understood, and the polarization of the radio signal can be predicted from the arrival direction, cosmic rays can be used as a proxy to assess the reconstruction capabilities of the ARIANNA neutrino detector. We report on dedicated efforts of reconstructing the polarization of cosmic-ray radio pulses. After correcting for difference in hardware, the two stations used in this study showed similar performance in terms of event rate and agreed with simulation. Subselecting high quality cosmic rays, the polarizations of these cosmic rays were reconstructed with a resolution of 2.5° (68% containment), which agrees with the expected value obtained from simulation. A large fraction of this resolution originates from uncertainties in the predicted polarization because of the contribution of the subdominant Askaryan effect in addition to the dominant geomagnetic emission. Subselecting events with a zenith angle greater than 70° removes most influence of the Askaryan emission, and, with limited statistics, we found the polarization uncertainty is reduced to 1.3° (68% containment).