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Concentrations of PCB congeners were measured in indoor/outdoor pairs of 120 residences in two communities. More than 270 passive samplers equipped with polyurethane foam disks (PAS-PUF) were deployed and collected in the urban/industrial community of East Chicago, Indiana and rural Columbus Junction, Iowa. The sampling protocol included transport and storage of pre-cleaned and exposed PUF disks to and from the laboratory in Iowa City. The potential exposure to PCBs during transport and shipping was found to contribute no more than 10% of the PCBs measured in samples, although the sealed polyethylene bags were insufficient protection from ambient air over longer time periods. The samples were extracted and analyzed for the full suite of 209 polychlorinated biphenyls (PCBs) and are reported as a set of 158 individual or coeluting compounds. The quality control measures included laboratory and travel blanks, injection of surrogate standards in every sample, and analysis of certified PCBs in standard reference materials. Although we hypothesized that homes in East Chicago would have higher PCB concentrations than in rural Columbus Junction, this was not the case: the communities had no significant difference in either indoor or outdoor PCB concentrations (0.62 ± 0.65 ng m -3 and 1.3 ± 1.6 ng m-3 for outdoor air respectively and 1.9 ± 1.4 ng m-3 and 1.9 ± 4.4 ng m -3 for indoor air respectively). In both communities, indoor air was higher in concentration, with indoor/outdoor ratios averaging 3. The samples from the two communities do exhibit statistically different congener distributions, however, with higher molecular weight congeners more enriched in East Chicago.

We use convolutional neural networks to recover images optically down-sampled by \\(6.7\\times\\) using coherent aperture synthesis over a 16 camera array. Where conventional ptychography relies on scanning and oversampling, here we apply decompressive neural estimation to recover full resolution image from a single snapshot, although as shown in simulation multiple snapshots can be used to improve SNR. In place training on experimental measurements eliminates the need to directly calibrate the measurement system. We also present simulations of diverse array camera sampling strategies to explore how snapshot compressive systems might be optimized.

While characterization of coherent wavefields is essential to laser, x-ray and electron imaging, sensors measure the squared magnitude of the field, rather than the field itself. Holography or phase retrieval must be used to characterize the field. The need for a reference severely restricts the utility of holography. Phase retrieval, in contrast, is theoretically consistent with sensors that directly measure coherent or partially coherent fields with no prior assumptions. Unfortunately, phase retrieval has not yet been successfully implemented for large-scale fields. Here we show that both holography and phase retrieval are capable of quantum-limited coherent signal estimation and we describe phase retrieval strategies that approach the quantum limit for >1 megapixel fields. These strategies rely on group testing using networks of interferometers, such as might be constructed using emerging integrated photonic, plasmonic and/or metamaterial devices. Phase-sensitive sensor planes using such devices could eliminate the need both for lenses and reference signals, creating a path to large aperture diffraction limited laser imaging.

Coherent illumination reflected by a remote target may be secondarily scattered by intermediate objects or materials. Here we show that phase retrieval on remotely observed images of such scattered fields enables imaging of the illuminated object at resolution proportional to \\(\\lambda R_s/A_s\\), where \\(R_s\\) is the range between the scatterer and the target and \\(A_s\\) is the diameter of the observed scatter. This resolution may exceed the resolution of directly viewing the target by the factor \\(R_cA_s/R_sA_c\\), where \\(R_c\\) is the range between the observer and the target and \\(A_c\\) is the observing aperture. Here we use this technique to demonstrate \\(\\approx 32\\times\\) resolution improvement relative to direct imaging.

The goal of multiframe image restoration is to process a sequence of blurred imagery of a static object or scene with the purpose of recovering a single deblurred image. The imaging problems discussed in this chapter involve the detection and processing of electromagnetic fields after reflection or emission from a remote object or scene. The applications considered are all examples of planar incoherent imaging, wherein the object or scene is characterized by its incoherent reflectance or emission function. Multiframe image restoration is concerned with the improvement of imagery acquired in the presence of varying degradations. The degradations can arise from a variety of factors; the common examples include undersampling of the image data, uncontrolled platform or scene motion, system aberrations and instabilities, and wave propagation through atmospheric turbulence. In a typical application, a sequence of images (frames) is recorded about a static object or scene, and a single restored image is extracted through analog or digital signal processing.

How does time pressure influence exploration and decision-making? We investigated this question with several four-armed bandit tasks manipulating (within subjects) expected reward, uncertainty, and time pressure (limited vs. unlimited). With limited time, people have less opportunity to perform costly computations, thus shifting the cost-benefit balance of different exploration strategies. Through behavioral, reinforcement learning (RL), reaction time (RT), and evidence accumulation analyses, we show that time pressure changes how people explore and respond to uncertainty. Specifically, participants reduced their uncertainty-directed exploration under time pressure, were less value-directed, and repeated choices more often. Since our analyses relate uncertainty to slower responses and dampened evidence accumulation (i.e., drift rates), this demonstrates a resource-rational shift towards simpler, lower-cost strategies under time pressure. These results shed light on how people adapt their exploration and decision-making strategies to externally imposed cognitive constraints.

Background Emotion regulation (ER) is a key process underlying posttraumatic stress disorder (PTSD), yet, little is known about how ER changes with PTSD treatment. Understanding these effects may shed light on treatment processes. Methods We recently completed a non-inferiority design randomised controlled trial demonstrating that a breathing-based yoga practice (Sudarshan kriya yoga; SKY) was not clinically inferior to cognitive processing therapy (CPT) across symptoms of PTSD, depression, or negative affect. Here, in secondary exploratory analyses (intent-to-treat N  = 85; per protocol N  = 59), we examined whether self-reported ER (Difficulties in Emotion Regulation Scale; DERS) and physiological ER (heart rate variability; HRV) improved with treatment for clinically significant PTSD symptoms among US Veterans. Results DERS-Total and all six subscales improved with small-to-moderate effect sizes ( d  = .24–.66) following CPT or SKY, with no differences between treatment groups. Following SKY (but not CPT), HR max–min (average difference between maximum and minimum beats per minute), LF/HF (low-to-high frequency) ratio, and normalised HF-HRV (high frequency power) improved (moved towards a healthier profile; d  = .42–.55). Conclusions To our knowledge, this is the first study to demonstrate that a breathing-based yoga (SKY) improved both voluntary/intentional and automatic/physiological ER. In contrast, trauma-focused therapy (CPT) only reliably improved self-reported ER. Findings have implications for PTSD treatment and interventions for emotional disorders more broadly. Trial registration Secondary analyses of ClinicalTrials.gov NCT02366403 .

The re-emergence of scarlet fever poses a new global public health threat. The capacity of North-East Asian serotype M12 ( emm 12) Streptococcus pyogenes (group A Streptococcus , GAS) to cause scarlet fever has been linked epidemiologically to the presence of novel prophages, including prophage ΦHKU.vir encoding the secreted superantigens SSA and SpeC and the DNase Spd1. Here, we report the molecular characterization of ΦHKU.vir-encoded exotoxins. We demonstrate that streptolysin O (SLO)-induced glutathione efflux from host cellular stores is a previously unappreciated GAS virulence mechanism that promotes SSA release and activity, representing the first description of a thiol-activated bacterial superantigen. Spd1 is required for resistance to neutrophil killing. Investigating single, double and triple isogenic knockout mutants of the ΦHKU.vir-encoded exotoxins, we find that SpeC and Spd1 act synergistically to facilitate nasopharyngeal colonization in a mouse model. These results offer insight into the pathogenesis of scarlet fever-causing GAS mediated by prophage ΦHKU.vir exotoxins. The pathogenesis of Streptococcus pyogenes (GAS) causing scarlet fever has been associated with the presence of prophages, such as ΦHKU.vir, and their products. Here, the authors characterize the exotoxins SpeC and Spd1 of ΦHKU.vir and show these to act synergistically to facilitate nasopharyngeal colonization in mice.

Breaking waves on the ocean surface generate air bubbles that scavenge organic matter from the surrounding sea water. When injected into the atmosphere, these bubbles burst, yielding sea spray aerosols enriched in organic matter, relative to the sea water. Downwind of plankton blooms, the organic carbon content of sea spray aerosol is weakly correlated with satellite-derived measurements of chlorophyll a levels, a measure of phytoplankton biomass. This correlation has been used in large-scale models to calculate the organic enrichment in sea spray aerosol. Here, we assess the relationship between the organic carbon content of sea water and freshly emitted sea spray aerosol in the presence and absence of plankton blooms in the North Atlantic Ocean and the coastal waters of California. The organic carbon content of freshly emitted sea spray aerosol was similar in all regions sampled, despite significant differences in seawater chlorophyll a levels. The proportion of freshly emitted aerosols that served as cloud condensation nuclei at a given supersaturation was also similar across sampling sites. The large reservoir of organic carbon in surface sea water remained relatively constant across the regions sampled, and independent of variations in chlorophyll a concentrations. We suggest that this reservoir is responsible for the organic carbon enrichment of freshly emitted sea spray aerosol, overwhelming any influence of local biological activity as measured by chlorophyll a levels. Breaking waves on the ocean surface generate air bubbles that yield sea spray aerosols when released to the atmosphere. Measurements of sea spray aerosols in the North Atlantic Ocean and the coastal waters of California suggest that the surface water organic carbon reservoir is responsible for the organic carbon enrichment of freshly emitted sea spray aerosol.

Radiocarbon (14C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.