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We examine the market response to quarterly earnings announcements made during trading and nontrading hours on the NYSE and the NASDAQ. For nontrading-hours announcements, the opening trade on the NYSE impounds most of the price response, whereas for trading-hours announcements, the response is spread evenly over the first several post-announcement trades. In contrast, the first post-announcement trade on the NASDAQ impounds most of the price response regardless of announcement time. These results suggest that the different trading environments on the two exchanges (e.g., specialist versus dealer market, call auction versus continuous trading, etc.) may differ in their ability to impound information.

Although supermarkets for groceries have existed for nearly a century, financial supermarkets are a much more recent innovation. We find that investors rely on mutual fund supermarkets to buy highly differentiable funds from small, specialized fund families. Investors' use of supermarkets is consistent with efforts to reduce search costs while obtaining the benefits of product focus at the fund origination level. The results thus demonstrate the growing importance of distribution in the context of intangible goods. Consistent with arguments by Black, Ciccotello, and Skipper (2002), the findings suggest that brand in financial services is increasingly driven by closeness to the customer. [PUBLICATION ABSTRACT]

How does increased noise trading affect market liquidity and trading costs? We use The Wall Street Journal's \"Investment Dartboard\" column, which stimulates noise trading, as a natural experiment to evaluate models of the bid-ask spread. We find that substantial increases in trading volume and significant but temporary abnormal returns occur when analysts recommend stocks in this column, especially when recommendations come from analysts with successful contest track records. We also find an increase in liquidity and a decrease in the adverse selection component of the bid-ask spread.

Replication has become the gold standard for assessing statistical results from genome-wide association studies. Unfortunately this replication requirement may cause real genetic effects to be missed. A real result can fail to replicate for numerous reasons including inadequate sample size or variability in phenotype definitions across independent samples. In genome-wide association studies the allele frequencies of polymorphisms may differ due to sampling error or population differences. We hypothesize that some statistically significant independent genetic effects may fail to replicate in an independent dataset when allele frequencies differ and the functional polymorphism interacts with one or more other functional polymorphisms. To test this hypothesis, we designed a simulation study in which case-control status was determined by two interacting polymorphisms with heritabilities ranging from 0.025 to 0.4 with replication sample sizes ranging from 400 to 1600 individuals. We show that the power to replicate the statistically significant independent main effect of one polymorphism can drop dramatically with a change of allele frequency of less than 0.1 at a second interacting polymorphism. We also show that differences in allele frequency can result in a reversal of allelic effects where a protective allele becomes a risk factor in replication studies. These results suggest that failure to replicate an independent genetic effect may provide important clues about the complexity of the underlying genetic architecture. We recommend that polymorphisms that fail to replicate be checked for interactions with other polymorphisms, particularly when samples are collected from groups with distinct ethnic backgrounds or different geographic regions.

•Functional connectivity (FC) analysis has been widely applied in clinical populations.•Intrinsic FC networks are found in virtually all brains.•FC suggests that disorders and diseases are less ‘focal’ than previously believed.•Widespread FC changes are found in non-communicative patients.•Challenging barriers must be overcome to enable further clinical applications. Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

The Late Triassic Carnian Pluvial Episode (CPE) saw a dramatic increase in global humidity and temperature that has been linked to the large-scale volcanism of the Wrangellia large igneous province. The climatic changes coincide with a major biological turnover on land that included the ascent of the dinosaurs and the origin of modern conifers. However, linking the disparate cause and effects of the CPE has yet to be achieved because of the lack of a detailed terrestrial record of these events. Here, we present a multidisciplinary record of volcanism and environmental change from an expanded Carnian lake succession of the Jiyuan Basin, North China. New U–Pb zircon dating, high-resolution chemostratigraphy, and palynological and sedimentological data reveal that terrestrial conditions in the region were in remarkable lockstep with the large-scale volcanism. Using the sedimentary mercury record as a proxy for eruptions reveals four discrete episodes during the CPE interval (ca. 234.0 to 232.4 Ma). Each eruptive phase correlated with large, negative C isotope excursions and major climatic changes to more humid conditions (marked by increased importance of hygrophytic plants), lake expansion, and eutrophication. Our results show that large igneous province eruptions can occur in multiple, discrete pulses, rather than showing a simple acme-and-decline history, and demonstrate their powerful ability to alter the global C cycle, cause climate change, and drive macroevolution, at least in the Triassic.

Major ecological realignments are already occurring in response to climate change. To be successful, conservation strategies now need to account for geographical patterns in traits sensitive to climate change, as well as climate threats to species-level diversity. As part of an effort to provide such information, we conducted a climate vulnerability assessment that included all anadromous Pacific salmon and steelhead (Oncorhynchus spp.) population units listed under the U.S. Endangered Species Act. Using an expert-based scoring system, we ranked 20 attributes for the 28 listed units and 5 additional units. Attributes captured biological sensitivity, or the strength of linkages between each listing unit and the present climate; climate exposure, or the magnitude of projected change in local environmental conditions; and adaptive capacity, or the ability to modify phenotypes to cope with new climatic conditions. Each listing unit was then assigned one of four vulnerability categories. Units ranked most vulnerable overall were Chinook (O. tshawytscha) in the California Central Valley, coho (O. kisutch) in California and southern Oregon, sockeye (O. nerka) in the Snake River Basin, and spring-run Chinook in the interior Columbia and Willamette River Basins. We identified units with similar vulnerability profiles using a hierarchical cluster analysis. Life history characteristics, especially freshwater and estuary residence times, interplayed with gradations in exposure from south to north and from coastal to interior regions to generate landscape-level patterns within each species. Nearly all listing units faced high exposures to projected increases in stream temperature, sea surface temperature, and ocean acidification, but other aspects of exposure peaked in particular regions. Anthropogenic factors, especially migration barriers, habitat degradation, and hatchery influence, have reduced the adaptive capacity of most steelhead and salmon populations. Enhancing adaptive capacity is essential to mitigate for the increasing threat of climate change. Collectively, these results provide a framework to support recovery planning that considers climate impacts on the majority of West Coast anadromous salmonids.

Despite the success of antiretroviral therapy (ART) to halt viral replication and slow disease progression, this treatment is not curative and there remains an urgent need to develop approaches to clear the latent HIV reservoir. The human IL-15 superagonist N-803 (formerly ALT-803) is a promising anti-cancer biologic with potent immunostimulatory properties that has been extended into the field of HIV as a potential \"shock and kill\" therapeutic for HIV cure. However, the ability of N-803 to reactivate latent virus and modulate anti-viral immunity in vivo under the cover of ART remains undefined. Here, we show that in ART-suppressed, simian-human immunodeficiency virus (SHIV)SF162P3-infected rhesus macaques, subcutaneous administration of N-803 activates and mobilizes both NK cells and SHIV-specific CD8+ T cells from the peripheral blood to lymph node B cell follicles, a sanctuary site for latent virus that normally excludes such effector cells. We observed minimal activation of memory CD4+ T cells and no increase in viral RNA content in lymph node resident CD4+ T cells post N-803 administration. Accordingly, we found no difference in the number or magnitude of plasma viremia timepoints between treated and untreated animals during the N-803 administration period, and no difference in the size of the viral DNA cell-associated reservoir post N-803 treatment. These results substantiate N-803 as a potent immunotherapeutic candidate capable of activating and directing effector CD8+ T and NK cells to the B cell follicle during full ART suppression, and suggest N-803 must be paired with a bona fide latency reversing agent in vivo to facilitate immune-mediated modulation of the latent viral reservoir.

Computer vision is a tool that could provide livestock producers with digital body measures and records that are important for animal health and production, namely body height and length, and chest girth. However, to build these tools, the scarcity of labeled training data sets with uniform images (pose, lighting) that also represent real-world livestock can be a challenge. Collecting images in a standard way, with manual image labeling is the gold standard to create such training data, but the time and cost can be prohibitive. We introduce the PreciseEdge image segmentation algorithm to address these issues by employing a standard image collection protocol with a semi-automated image labeling method, and a highly precise image segmentation for automated body measurement extraction directly from each image. These elements, from image collection to extraction are designed to work together to yield values highly correlated to real-world body measurements. PreciseEdge adds a brief preprocessing step inspired by chromakey to a modified GrabCut procedure to generate image masks for data extraction (body measurements) directly from the images. Three hundred RGB (red, green, blue) image samples were collected uniformly per the African Goat Improvement Network Image Collection Protocol (AGIN-ICP), which prescribes camera distance, poses, a blue backdrop, and a custom AGIN-ICP calibration sign. Images were taken in natural settings outdoors and in barns under high and low light, using a Ricoh digital camera producing JPG images (converted to PNG prior to processing). The rear and side AGIN-ICP poses were used for this study. PreciseEdge and GrabCut image segmentation methods were compared for differences in user input required to segment the images. The initial bounding box image output was captured for visual comparison. Automated digital body measurements extracted were compared to manual measures for each method. Both methods allow additional optional refinement (mouse strokes) to aid the segmentation algorithm. These optional mouse strokes were captured automatically and compared. Stroke count distributions for both methods were not normally distributed per Kolmogorov-Smirnov tests. Non-parametric Wilcoxon tests showed the distributions were different (p< 0.001) and the GrabCut stroke count was significantly higher (p = 5.115 e -49 ), with a mean of 577.08 (std 248.45) versus 221.57 (std 149.45) with PreciseEdge. Digital body measures were highly correlated to manual height, length, and girth measures, (0.931, 0.943, 0.893) for PreciseEdge and (0.936, 0. 944, 0.869) for GrabCut (Pearson correlation coefficient). PreciseEdge image segmentation allowed for masks yielding accurate digital body measurements highly correlated to manual, real-world measurements with over 38% less user input for an efficient, reliable, non-invasive alternative to livestock hand-held direct measuring tools.