RSK tableaux and the weak order on fully commutative permutations

For each fully commutative permutation, we construct a "boolean core," which is the maximal boolean permutation in its principal order ideal under the right weak order. We partition the set of fully commutative permutations into the recently defined crowded and uncrowded elements, distinguished by whether or not their RSK insertion tableaux satisfy a sparsity condition. We show that a fully commutative element is uncrowded exactly when it shares the RSK insertion tableau with its boolean core. We present the dynamics of the right weak order on fully commutative permutations, with particular interest in when they change from uncrowded to crowded. In particular, we use consecutive permutation patterns and descents to characterize the minimal crowded elements under the right weak order.Comment: 20 pages, 2 figure

Runs and RSK tableaux of boolean permutations

We define and construct the "canonical reduced word" of a boolean permutation, and show that the RSK tableaux for that permutation can be read off directly from this reduced word. We also describe those tableaux that can correspond to boolean permutations, and enumerate them. In addition, we generalize a result of Mazorchuk and Tenner, showing that the "run" statistic influences the shape of the RSK tableau of arbitrary permutations, not just of those that are boolean.Comment: 18 pages, 3 figure

What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community. In this work, we present the first free-form multiple-choice OpenQA dataset for solving medical problems, MedQA, collected from the professional medical board exams. It covers three languages: English, simplified Chinese, and traditional Chinese, and contains 12,723, 34,251, and 14,123 questions for the three languages, respectively. We implement both rule-based and popular neural methods by sequentially combining a document retriever and a machine comprehension model. Through experiments, we find that even the current best method can only achieve 36.7\%, 42.0\%, and 70.1\% of test accuracy on the English, traditional Chinese, and simplified Chinese questions, respectively. We expect MedQA to present great challenges to existing OpenQA systems and hope that it can serve as a platform to promote much stronger OpenQA models from the NLP community in the future.Comment: Submitted to AAAI 202

γδ T Cells Provide an Early Source of Interferon γ in Tumor Immunity

Interferon (IFN)-γ is necessary for tumor immunity, however, its initial cellular source is unknown. Because γδ T cells primarily produce this cytokine upon activation, we hypothesized that they would provide an important early source of IFN-γ in tumor immunosurveillance. To address this hypothesis, we first demonstrated that γδ T cell–deficient mice had a significantly higher incidence of tumor development after challenge with a chemical carcinogen methylcholanthrene (MCA) or inoculation with the melanoma cell line B16. In wild-type mice, γδ T cells were recruited to the site of tumor as early as day 3 after inoculation, followed by αβ T cells at day 5. We then used bone marrow chimeras and fetal liver reconstitutions to create mice with an intact γδ T cell repertoire but one that was specifically deficient in the capacity to produce IFN-γ. Such mice had a higher incidence of tumor development, induced either with MCA or by inoculation of B16 melanoma cells, compared with mice with IFN-γ–competent γδ T cells. Moreover, genetic deficiency of γδ T cells resulted in impaired IFN-γ production by tumor antigen-triggered αβ T cell upon immunization with tumor lysate. These results demonstrate that γδ T cells can play a necessary role in tumor immunity through provision of an early source of IFN-γ that in turn may regulate the function of tumor-triggered αβ T cells

Riverine Carbon Cycling Over The Past Century in the Mid‐Atlantic Region of the United States

The lateral transport and degassing of carbon in riverine ecosystems is difficult to quantify on large spatial and long temporal scales due to the relatively poor representation of carbon processes in many models. Here, we coupled a scale‐adaptive hydrological model with the Dynamic Land Ecosystem Model to simulate key riverine carbon processes across the Chesapeake and Delaware Bay Watersheds from 1900 to 2015. Our results suggest that throughout this time period riverine CO2 degassing and lateral dissolved inorganic carbon fluxes to the coastal ocean contribute nearly equally to the total riverine carbon outputs (mean ± standard deviation: 886 ± 177 Gg C∙yr−1 and 883 ± 268 Gg C∙yr−1, respectively). Following in order of decreasing importance are the lateral dissolved organic carbon flux to the coastal ocean (293 ± 81 Gg C∙yr−1), carbon burial (118 ± 32 Gg C∙yr−1), and lateral particulate organic carbon flux (105 ± 35 Gg C∙yr−1). In the early 2000s, carbon export to the coastal ocean from both the Chesapeake and Delaware Bay watersheds was only 15%–20% higher than it was in the early 1900s (decade), but it showed a twofold increase in standard deviation. Climate variability (changes in temperature and precipitation) explains most (225 Gg C∙yr−1) of the increase since 1900, followed by changes in atmospheric CO2 (82 Gg C∙yr−1), atmospheric nitrogen deposition (44 Gg C∙yr−1), and applications of nitrogen fertilizer and manure (27 Gg C∙yr−1); in contrast, land conversion has resulted in a 188 Gg C∙yr−1 decrease in carbon export

Impacts of Multiple Environmental Changes on Long‐Term Nitrogen Loading From the Chesapeake Bay Watershed

Excessive nutrient inputs from land, particularly nitrogen (N), have been found to increase the occurrence of hypoxia and harmful algal blooms in coastal ecosystems. To identify the main contributors of increased N loading and evaluate the efficacy of water pollution control policies, it is essential to quantify and attribute the long‐term changes in riverine N export. Here, we use a state‐of‐the‐art terrestrial–aquatic interface model to examine how multiple environmental factors may have affected N export from the Chesapeake Bay watershed since 1900. These factors include changes in climate, carbon dioxide, land use, and N inputs (i.e., atmospheric N deposition, animal manure, synthetic N fertilizer use, and wastewater discharge). Our results estimated that ammonium (NH4+) and nitrate (NO3−) export increased substantially (66% for NH4+ and 123% for NO3−) from the 1900s to the 1990s and then declined (32% for NH4+ and 14% for NO3−) since 2000. The temporal trend of dissolved organic nitrogen (DON) export paralleled that of dissolved inorganic N, while particulate organic nitrogen export was relatively constant during 1900–2015. Precipitation was the primary driver of interannual variability in N export to the Bay. Wastewater discharge explained most of the long‐term change in riverine NH4+ and DON fluxes from 1900 to 2015. The changes in atmospheric deposition, wastewater, and synthetic fertilizer were responsible for the trend of riverine NO3−. In light of our model‐based attribution analysis, terrestrial non‐point source nutrient management will play an important role in achieving water quality goals

Impacts of Multiple Environmental Changes on Long‐Term Nitrogen Loading From the Chesapeake Bay Watershed

Excessive nutrient inputs from land, particularly nitrogen (N), have been found to increase the occurrence of hypoxia and harmful algal blooms in coastal ecosystems. To identify the main contributors of increased N loading and evaluate the efficacy of water pollution control policies, it is essential to quantify and attribute the long‐term changes in riverine N export. Here, we use a state‐of‐the‐art terrestrial–aquatic interface model to examine how multiple environmental factors may have affected N export from the Chesapeake Bay watershed since 1900. These factors include changes in climate, carbon dioxide, land use, and N inputs (i.e., atmospheric N deposition, animal manure, synthetic N fertilizer use, and wastewater discharge). Our results estimated that ammonium (NH4+) and nitrate (NO3−) export increased substantially (66% for NH4+ and 123% for NO3−) from the 1900s to the 1990s and then declined (32% for NH4+ and 14% for NO3−) since 2000. The temporal trend of dissolved organic nitrogen (DON) export paralleled that of dissolved inorganic N, while particulate organic nitrogen export was relatively constant during 1900–2015. Precipitation was the primary driver of interannual variability in N export to the Bay. Wastewater discharge explained most of the long‐term change in riverine NH4+ and DON fluxes from 1900 to 2015. The changes in atmospheric deposition, wastewater, and synthetic fertilizer were responsible for the trend of riverine NO3−. In light of our model‐based attribution analysis, terrestrial non‐point source nutrient management will play an important role in achieving water quality goals

Prevalence and Clinical Features of Inflammatory Bowel Diseases Associated With Monogenic Variants, Identified by Whole-Exome Sequencing in 1000 Children at a Single Center

BACKGROUND & AIMS: A proportion of infants and young children with inflammatory bowel diseases (IBDs) have subtypes associated with a single gene variant (monogenic IBD). We aimed to determine the prevalence of monogenic disease in a cohort of pediatric patients with IBD. METHODS: We performed whole-exome sequencing analyses of blood samples from an unselected cohort of 1005 children with IBD, aged 0-18 years (median age at diagnosis, 11.96 years) at a single center in Canada and their family members (2305 samples total). Variants believed to cause IBD were validated using Sanger sequencing. Biopsies from patients were analyzed by immunofluorescence and histochemical analyses. RESULTS: We identified 40 rare variants associated with 21 monogenic genes among 31 of the 1005 children with IBD (including 5 variants in XIAP, 3 in DOCK8, and 2 each in FOXP3, GUCY2C, and LRBA). These variants occurred in 7.8% of children younger than 6 years and 2.3% of children aged 6-18 years. Of the 17 patients with monogenic Crohn\u27s disease, 35% had abdominal pain, 24% had nonbloody loose stool, 18% had vomiting, 18% had weight loss, and 5% had intermittent bloody loose stool. The 14 patients with monogenic ulcerative colitis or IBD-unclassified received their diagnosis at a younger age, and their most predominant feature was bloody loose stool (78%). Features associated with monogenic IBD, compared to cases of IBD not associated with a single variant, were age of onset younger than 2 years (odds ratio [OR], 6.30; P = .020), family history of autoimmune disease (OR, 5.12; P = .002), extra-intestinal manifestations (OR, 15.36; P \u3c .0001), and surgery (OR, 3.42; P = .042). Seventeen patients had variants in genes that could be corrected with allogeneic hematopoietic stem cell transplantation. CONCLUSIONS: In whole-exome sequencing analyses of more than 1000 children with IBD at a single center, we found that 3% had rare variants in genes previously associated with pediatric IBD. These were associated with different IBD phenotypes, and 1% of the patients had variants that could be potentially corrected with allogeneic hematopoietic stem cell transplantation. Monogenic IBD is rare, but should be considered in analysis of all patients with pediatric onset of IBD

Linking Student Performance in Massachusetts Elementary Schools with the “Greenness” of School Surroundings Using Remote Sensing

Various studies have reported the physical and mental health benefits from exposure to “green” neighborhoods, such as proximity to neighborhoods with trees and vegetation. However, no studies have explicitly assessed the association between exposure to “green” surroundings and cognitive function in terms of student academic performance. This study investigated the association between the “greenness” of the area surrounding a Massachusetts public elementary school and the academic achievement of the school’s student body based on standardized tests with an ecological setting. Researchers used the composite school-based performance scores generated by the Massachusetts Comprehensive Assessment System (MCAS) to measure the percentage of 3rd-grade students (the first year of standardized testing for 8–9 years-old children in public school), who scored “Above Proficient” (AP) in English and Mathematics tests (Note: Individual student scores are not publically available). The MCAS results are comparable year to year thanks to an equating process. Researchers included test results from 2006 through 2012 in 905 public schools and adjusted for differences between schools in the final analysis according to race, gender, English as a second language (proxy for ethnicity and language facility), parent income, student-teacher ratio, and school attendance. Surrounding greenness of each school was measured using satellite images converted into the Normalized Difference Vegetation Index (NDVI) in March, July and October of each year according to a 250-meter, 500-meter, 1,000-meter, and 2000-meter circular buffer around each school. Spatial Generalized Linear Mixed Models (GLMMs) estimated the impacts of surrounding greenness on school-based performance. Overall the study results supported a relationship between the “greenness” of the school area and the school-wide academic performance. Interestingly, the results showed a consistently positive significant association between the greenness of the school in the Spring (when most Massachusetts students take the MCAS tests) and school-wide performance on both English and Math tests, even after adjustment for socio-economic factors and urban residency