STL Energy Project, Spring 2020

STL Multifamily Housing Building Energy Efficiency Through Building Communication. A collaboration between Washington University in St. Louis Sustainability Exchange and the City of St. Louis to promote Building Energy Awareness that will reduce GHG Emissions and combat Climate Change. Mentors & Client: Ray Ehrhard and Rajiv Ravulapati. Community Partners: Rachel Pressley (Lindell Park Apartments) and Stephanie Blockton (House at Westminister

Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis

Many subproblems in automated skin lesion diagnosis (ASLD) canbe unified under a single generalization of assigning a label, from an predefinedset, to each pixel in an image. We first formalize this generalizationand then present two probabilistic models capable of solving it. The firstmodel is based on independent pixel labeling using maximum a-posteriori(MAP) estimation. The second model is based on conditional randomfields (CRFs), where dependencies between pixels are defined using agraph structure. Furthermore, we demonstrate how supervised learningand an appropriate training set can be used to automatically determineall model parameters. We evaluate both models\u27 ability to segment achallenging dataset consisting of 116 images and compare our results to5 previously published methods

Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis

Many subproblems in automated skin lesion diagnosis (ASLD) can be unified under a single generalization of assigning a label, from an predefined set, to each pixel in an image. We first formalize this generalization and then present two probabilistic models capable of solving it. The first model is based on independent pixel labeling using maximum a-posteriori (MAP) estimation. The second model is based on conditional random fields (CRFs), where dependencies between pixels are defined using a graph structure. Furthermore, we demonstrate how supervised learning and an appropriate training set can be used to automatically determine all model parameters. We evaluate both models' ability to segment a challenging dataset consisting of 116 images and compare our results to 5 previously published methods

High Resolution Spectroscopy during Eclipse of the Young Substellar Eclipsing Binary 2MASS 0535-0546. I. Primary Spectrum: Cool Spots versus Opacity Uncertainties

We present high-resolution Keck optical spectra of the very young substellar eclipsing binary 2MASS J05352184-0546085, obtained during eclipse of the lower-mass (secondary) brown dwarf. The observations yield the spectrum of the higher-mass (primary) brown dwarf alone, with negligible (~1.6%) contamination by the secondary. We perform a simultaneous fine-analysis of the TiO-epsilon band and the red lobe of the KI doublet, using state-of-the-art PHOENIX Dusty and Cond synthetic spectra. Comparing the effective temperature and surface gravity derived from these fits to the {\it empirically} determined surface gravity of the primary (logg=3.5) then allows us to test the model spectra as well as probe the prevailing photospheric conditions. We find that: (1) fits to TiO-epsilon alone imply Teff=2500 \pm 50K; (2) at this Teff, fits to KI imply logg=3.0, 0.5 dex lower than the true value; and (3) at the true logg, KI fits yield Teff=2650 \pm 50K, ~150K higher than from TiO-epsilon alone. On the one hand, these are the trends expected in the presence of cool spots covering a large fraction of the primary's surface (as theorized previously to explain the observed Teff reversal between the primary and secondary). Specifically, our results can be reproduced by an unspotted stellar photosphere with Teff=2700K and (empirical) logg=3.5, coupled with axisymmetric cool spots that are 15% cooler (2300K), have an effective logg=3.0 (0.5 dex lower than photospheric), and cover 70% of the surface. On the other hand, the trends in our analysis can also be reproduced by model opacity errors: there are lacks in the synthetic TiO-epsilon opacities, at least for higher-gravity field dwarfs. Stringently discriminating between the two possibilities requires combining the present results with an equivalent analysis of the secondary (predicted to be relatively unspotted compared to the primary).Comment: To appear in ApJ. 11 pages, 5 figure

Exploiting the variability and heritability of leaf angle in sorghum to design optimal canopies for different target environments

In cereal crops, average leaf angle of the canopy affects the total amount of radiation that is intercepted and how effectively light is distributed through the canopy. Selecting for more erect leaves in maize and rice has allowed higher density plantings and has been associated with significant productivity gains in those crops. The effects of leaf angle on crop productivity depend on how it influences within-canopy light distribution and the plants’ efficiency in using that light to produce biomass. Canopy light distribution is influenced by agronomic interventions such as growing at different locations, sowing on different dates, using different plant densities (leaf area index). For sorghum, which may be grown across a large range of latitudes and plant population densities, the effects of leaf angle manipulations have not previously been studied. We used the APSIM-DCaPST sorghum model to simulate the effects of more erectophile canopies on yield for two locations with different latitudes and planting dates, assuming low-and high- intensity agronomies. The simulations showed that more erect leaves would result in yield benefits in most years at both of those locations. Contrary to the situation in maize, the simulated yield gains were greatest in the low-yielding rather than the high-yielding years. Interestingly also, the simulated productivity gains in erectophile sorghum canopies were not due to enhanced light penetration as suggested in maize, but rather through effects on extent of radiation interception and its implications for early crop growth and crop water balance through the crop life cycle

Multimodal LLMs for health grounded in individual-specific data

Foundation large language models (LLMs) have shown an impressive ability to solve tasks across a wide range of fields including health. To effectively solve personalized health tasks, LLMs need the ability to ingest a diversity of data modalities that are relevant to an individual's health status. In this paper, we take a step towards creating multimodal LLMs for health that are grounded in individual-specific data by developing a framework (HeLM: Health Large Language Model for Multimodal Understanding) that enables LLMs to use high-dimensional clinical modalities to estimate underlying disease risk. HeLM encodes complex data modalities by learning an encoder that maps them into the LLM's token embedding space and for simple modalities like tabular data by serializing the data into text. Using data from the UK Biobank, we show that HeLM can effectively use demographic and clinical features in addition to high-dimensional time-series data to estimate disease risk. For example, HeLM achieves an AUROC of 0.75 for asthma prediction when combining tabular and spirogram data modalities compared with 0.49 when only using tabular data. Overall, we find that HeLM outperforms or performs at parity with classical machine learning approaches across a selection of eight binary traits. Furthermore, we investigate the downstream uses of this model such as its generalizability to out-of-distribution traits and its ability to power conversations around individual health and wellness

Development and management of systemic lupus erythematosus in an HIV-infected man with hepatitis C and B co-infection following interferon therapy: a case report

<p>Abstract</p> <p>Introduction</p> <p>The association of human immunodeficiency virus and immune dysfunction leading to development of autoimmune markers is well described, but human immunodeficiency virus infection is relatively protective for the development of systemic lupus erythematosus. In contrast, development of systemic lupus erythematosus with hepatitis C and with interferon therapy is well described in a number of case reports. We here describe the first case of systemic lupus erythematosus developing in a man infected with human immunodeficiency virus, hepatitis C and hepatitis B co-infection where the onset seems to have been temporally related to interferon therapy.</p> <p>Case presentation</p> <p>We report the occurrence of systemic lupus erythematosus complicating interferon-α therapy for hepatitis C in a 47-year-old asplenic male with haemophilia co-infected with human immunodeficiency virus and hepatitis B. He presented with a truncal rash, abdominal pains and headache and later developed grade IV lupus nephritis requiring haemodialysis, mycophenolate mofetil and steroid therapy. We were able to successfully withdraw dialysis and mycophenolate while maintaining stable renal function.</p> <p>Conclusion</p> <p>Interferon-α is critical in antiviral immunity against hepatitis C but also acts as a pathogenic mediator for systemic lupus erythematosus, a condition associated with activation of plasmacytoid dendritic cells that are depleted in human immunodeficiency virus infection. The occurrence of auto-antibodies and lupus-like features in the coinfections with hepatitis C require careful assessment. Immunosuppressant therapy for lupus risks exacerbating underlying infections in patients with concurrent human immunodeficiency virus, hepatitis B and C.</p

Zircon U-Pb Geochronology Links the End-Triassic Extinction with the Central Atlantic Magmatic Province

The end-Triassic extinction is characterized by major losses in both terrestrial and marine diversity, setting the stage for dinosaurs to dominate Earth for the next 136 million years. Despite the approximate coincidence between this extinction and flood basalt volcanism, existing geochronologic dates have insufficient resolution to confirm eruptive rates required to induce major climate perturbations. Here, we present new zircon uranium-lead (U-Pb) geochronologic constraints on the age and duration of flood basalt volcanism within the Central Atlantic Magmatic Province. This chronology demonstrates synchroneity between the earliest volcanism and extinction, tests and corroborates the existing astrochronologic time scale, and shows that the release of magma and associated atmospheric flux occurred in four pulses over about 600,000 years, indicating expansive volcanism even as the biologic recovery was under way