Disparate Flood Outcomes and Social Vulnerability as a Fair Housing Issue in Norfolk, Virginia

The purpose of this plan is to explore how social vulnerability and the disparate impacts of floods can be viewed as a fair housing infringement. This plan includes examining the current and past conditions of how flood risk management, housing development, and the natural environment have been operating in favor of or against socially vulnerable populations in Norfolk. These topics have been explored through stakeholder interviews, geographic analysis, and descriptive analysis. This project suggests an understanding of fair housing in which the equitable sharing of environmental risk and the benefits of its management, are integral to equal access in housing, inclusive neighborhoods, and full enjoyment of one\u27s residence. In doing so, new understandings are created as to how environmental hazards, such as flooding, can negatively impact fair housing. By casting the disproportionate flooding burden faced by socially vulnerable groups as a fair housing violation, we can begin to recognize and make reparations for this inequality

Application and Evaluation of a Snowmelt Runoff Model in the Tamor River Basin, Eastern Himalaya Using a Markov Chain Monte Carlo (MCMC) Data Assimilation Approach

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree-day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash-Sutcliffe metric approx. 0.84, annual volume bias <3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002-2006 period is estimated to be 29.7+/-2.9% (which includes 4.2+/-0.9% from snowfall that promptly melts), whereas 70.3+/-2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000-5500m range contributes the most to basin runoff, averaging 56.9+/-3.6% of all snowmelt input and 28.9+/-1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree-day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds

Communicating Results of a Dietary Exposure Study Following Consumption of Traditionally Smoked Salmon

One expectation of community-based participatory research (CBPR) is participant access to study results. However, reporting experimental data produced by studies involving biological measurements in the absence of clinical relevance can be challenging to scientists and participants. We applied best practices in data sharing to report the results of a study designed to explore polycyclic aromatic hydrocarbons (PAHs) absorption, metabolism, and excretion following consumption of traditionally-smoked salmon by members of the Confederated Tribes of the Umatilla Indian Reservation (CTUIR). A dietary exposure study was developed, wherein 9 Tribal members consumed 50 grams of traditionally-smoked salmon and provided repeated urine samples over 24 hours. During recruitment, participants requested access to their data following analysis. Disclosing data is an important element of community-based participatory research, and must be treated with the same rigor as that given to the data analysis. The field of data disclosure is relatively new, but when handled correctly can improve education within the community, reduce distrust and enhance environmental health literacy. Using the results from this study, we suggest mechanisms for sharing data with a Tribal community.This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Mary Ann Liebert, Inc., and can be found at: http://www.liebertpub.com/overview/environmental-justice/259

Documenting ---- in Bloomington-Normal: A Community Report on Intolerance, Segregation, Accessibility, Inclusion, and Progress, and Improvement

For the local chapter of Not In Our Town, we document intolerance, discrimination, segregation, disparities of access, and disparities in the criminal justice system in Bloomington-Normal, IL. Using archival material, secondary data, and primary data, we examine these issues from the mid-1990s to the present. We also assess the position of the organization in the community and provide strategies for future success. In sum, Bloomington-Normal was and is intolerant; discrimination did and does take place in this community; there are disparities of access and in the criminal justice system; we are segregated. The community is also less of these things than it used to be and is less of these things than other places. Fifteen undergraduate students in Sociology 300, twelve graduate students in Sociology 477, a teaching assistant, and an instructor conducted this study in spring 2017

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Resolvins suppress tumor growth and enhance cancer therapy

National Cancer Institute grants RO1 01CA170549-02 (to D. Panigrahy and C.N. Serhan), ROCA148633-01A4 (to D. Panigrahy), and GM095467 (to C.N. Serhan); the Stop and Shop Pediatric Brain Tumor Fund (to M.W. Kieran); the CJ Buckley Pediatric Brain Tumor Fund (to M.W. Kieran); Alex Lemonade Stand (to M.W. Kieran); Molly’s Magic Wand for Pediatric Brain Tumors (to M.W. Kieran); the Markoff Foundation Art-In-Giving Foundation (to M.W. Kieran); the Kamen Foundation (to M.W. Kieran); Jared Branfman Sunflowers for Life (to M.W.K.); and The Wellcome Trust program 086867/Z/08 (to M. Perretti)

Application and evaluation of a snowmelt runoff model in the Tamor River basin, Eastern Himalaya using a Markov Chain Monte Carlo (MCMC) data assimilation approach

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree-day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash-Sutcliffe metric ~0.84, annual volume bias\u3c3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002-2006 period is estimated to be 29.7±2.9% (which includes 4.2±0.9% from snowfall that promptly melts), whereas 70.3±2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000-5500m range contributes the most to basin runoff, averaging 56.9±3.6% of all snowmelt input and 28.9±1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree-day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds

Illuminating the Molecular Mechanisms of Tyrosine Kinase Inhibitor Resistance for the FGFR1 Gatekeeper Mutation: The Achilles’ Heel of Targeted Therapy

Human fibroblast growth factor receptors (FGFRs) 1–4 are a family of receptor tyrosine kinases that can serve as drivers of tumorigenesis. In particular, <i>FGFR1</i> gene amplification has been implicated in squamous cell lung and breast cancers. Tyrosine kinase inhibitors (TKIs) targeting FGFR1, including AZD4547 and E3810 (Lucitanib), are currently in early phase clinical trials. Unfortunately, drug resistance limits the long-term success of TKIs, with mutations at the “gatekeeper” residue leading to tumor progression. Here we show the first structural and kinetic characterization of the FGFR1 gatekeeper mutation, V561M FGFR1. The V561M mutation confers a 38-fold increase in autophosphorylation achieved at least in part by a network of interacting residues forming a hydrophobic spine to stabilize the active conformation. Moreover, kinetic assays established that the V561M mutation confers significant resistance to E3810, while retaining affinity for AZD4547. Structural analyses of these TKIs with wild type (WT) and gatekeeper mutant forms of FGFR1 offer clues to developing inhibitors that maintain potency against gatekeeper mutations. We show that AZD4547 affinity is preserved by V561M FGFR1 due to a flexible linker that allows multiple inhibitor binding modes. This is the first example of a TKI binding in distinct conformations to WT and gatekeeper mutant forms of FGFR, highlighting adaptable regions in both the inhibitor and binding pocket crucial for drug design. Exploiting inhibitor flexibility to overcome drug resistance has been a successful strategy for combatting diseases such as AIDS and may be an important approach for designing inhibitors effective against kinase gatekeeper mutations