Emerging wildlife pathogens often display geographic variability due to landscape heterogeneity. Modeling approaches capable of learning complex, non-linear spatial dynamics of diseases are needed to rigorously assess and mitigate the effects of pathogens on wildlife health and biodiversity. We propose a novel machine learning (ML)-guided approach that leverages prior physical knowledge of ecological systems, using partial differential equations. We present our approach, taking advantage of the universal function approximation property of neural networks for flexible representation of the underlying dynamics of the geographic spread and growth of wildlife diseases. We demonstrate the benefits of our approach by comparing its forecasting power with commonly used methods and highlighting the obtained insights on disease dynamics. Additionally, we show the theoretical guarantees for the approximation error of our model. We illustrate the implementation of our ML-guided approach using data from white-nose syndrome (WNS) outbreaks in bat populations across the US. WNS is an infectious fungal disease responsible for significant declines in bat populations. Our results on WNS are useful for disease surveillance and bat conservation efforts. Our methods can be broadly used to assess the effects of environmental and anthropogenic drivers impacting wildlife health and biodiversity.

By some accounts, the location of America's capital was decided at a secret dinner party that Thomas Jefferson held in 1790 at his New York City residence. There, through the age-old practice of logrolling, James Madison and Alexander Hamilton hatched a plan to build the nation's capital in Virginia. “Madison agreed to permit the core provision of Hamilton's fiscal program to pass; and in return, Hamilton agreed to use his influence to assure that the permanent residence of the national capital would be on the Potomac River” (Ellis 2001, 49).

Japan's government remains firmly committed to a large scale nuclear power program despite sustained resistance from local communities. Recognizing the concerns of many citizens about nuclear power and its health and property risks, the government instituted tactics to smooth the path for its nation-wide energy agenda undertaken in cooperation with private utilities. The responsible government office, the Agency for Natural Resources and Energy (ANRE, or Shigen enerugi cho), honed a wide variety of strategies designed to quell resistance to nuclear power plant siting. Despite innovative and expensive programs such as awards ceremonies for cooperative local government officials, pro-nuclear curricula for local schools, and extensive subsidies for host communities, the time necessary for siting new plans continues to increase and some plans have been defeated. Local communities and anti-nuclear activists remain resistant to central government inducements and will no doubt seek to block future siting attempts.

Glufosinate serves as both a primary herbicide option and a complement to glyphosate and other postemergence (POST) herbicides for managing herbicide-resistant weed species. Enhancing broadleaf weed control with glufosinate through effective mixtures may mitigate further herbicide resistance evolution in soybean and other glufosinate-resistant cropping systems. Two field experiments were conducted in 2020 and 2021 across locations in Wisconsin (Arlington, Brooklyn, Janesville, and Lancaster) and one location in Illinois (Macomb) to evaluate the impact of POST glufosinate mixed with PPO-inhibitors (flumiclorac-pentyl, fluthiacet-methyl, fomesafen, and lactofen, WSSA Group 14), bentazon (Group 6), and 2,4-D (Group 4) on waterhemp control, soybean phytotoxicity, and yield. The experiments were established in a randomized complete block design with four replications. The first experiment focused on soybean phytotoxicity 14 days after treatment (DAT) and yield in the absence of weed competition. All treatments received a preemergence herbicide, with postemergence herbicide applications occurring between the V3-V6 soybean growth stages, depending on the site-year. The second experiment evaluated the impact of herbicide treatments on waterhemp control 14 DAT and on soybean yield. Lactofen, applied alone or with glufosinate, presented the highest phytotoxicity to soybean 14 DAT, but this injury did not translate into yield loss. Mixing glufosinate with 2,4-D, bentazon, and PPO-inhibitor herbicides did not increase waterhemp control, nor did it affect soybean yield compared to when glufosinate was applied solely but may be an effective practice to reduce selection pressure for glufosinate-resistant waterhemp.

Surfactant transport is central to a diverse range of natural phenomena with numerous practical applications in physics and engineering. Surprisingly, this process remains relatively poorly understood at the molecular scale. Here, we use non-equilibrium molecular dynamics (NEMD) simulations to study the spreading of sodium dodecyl sulphate on a thin film of liquid water. The molecular form of the control volume is extended to a coordinate system moving with the liquid–vapour interface to track surfactant spreading. We use this to compare the NEMD results to the continuum description of surfactant transport on an interface. By including the molecular details in the continuum model, we establish that the transport equation preserves substantial accuracy in capturing the underlying physics. Moreover, the relative importance of the different mechanisms involved in the transport process is identified. Consequently, we derive a novel exact molecular equation for surfactant transport along a deforming surface. Close agreement between the two conceptually different approaches, i.e. NEMD simulations and the numerical solution of the continuum equation, is found as measured by the surfactant concentration profiles, and the time dependence of the so-called spreading length. The current study focuses on a relatively simple specific solvent–surfactant system, and the observed agreement with the continuum model may not arise for more complicated industrially relevant surfactants and anti-foaming agents. In such cases, the continuum approach may fail to predict accompanying phase transitions, which can still be captured through the NEMD framework.

Objectives/Goals: Osteosarcoma (OS) is the most common primary bone malignancy in humans and dogs. >40% of children and >90% of dogs succumb to metastatic disease. We hypothesize MYC overexpression in metastatic canine and human OS contributes to an immunosuppressive tumor environment by driving tumor-associated macrophage influx and T lymphocyte exclusion. Methods/Study Population: To characterize the role of oncogenic MYC signaling in the canine metastatic tumor immune microenvironment (TIME), 42 archived FFPE lung metastatic canine OS samples were evaluated for MYC copy number variation (CNV), mRNA, and protein expression via ddPCR, nanostring analysis, and immunohistochemistry (IHC). Seven samples also underwent GeoMX spatial profiling to more specifically evaluate T cell and macrophage transcriptional profiles based on MYC status. To determine the role of MYC target modulation as a potential therapeutic option, canine and human OS cell lines were treated with a novel MYC inhibitor (MYCi975) and assessed for effects on survival, proliferation, and cytokine profiles. Results/Anticipated Results: We demonstrate that copy number gains are not a key driver of MYC hyperactivity in canine metastatic OS. However, stratification based on MYC protein expression demonstrates that “MYC-high” tumors are associated with downregulation of cytotoxic effector T-cell associated transcripts and upregulation of tumor-associated macrophage (TAM) and extracellular matrix remodeling transcripts. We also report that MYCi975 treatment of canine and human OS cell lines results in significant inhibition of OS cell survival and proliferation at concentrations that are pharmacologically achievable in mice. Furthermore, we demonstrate MYC inhibition by MYCi975 is associated with reduced pro-inflammatory cytokine secretion in OS cell culture models. Discussion/Significance of Impact: While MYC overactivity in metastatic canine OS may not be genomically driven, other mechanisms that lead to increased MYC protein expression are associated with transcriptomic profiles supportive of local immunosuppression. Pharmacologic targeting of MYC may serve as a strategy to bolster immunotherapeutic options in metastatic OS treatment.

Objectives/Goals: To explore the caregivers’ lived experiences related to facilitators of and barriers to effective primary care or neurology follow-up for children discharged from the pediatric emergency department (PED) with headaches. Methods/Study Population: We used the descriptive phenomenology qualitative study design to ascertain caregivers’ lived experiences with making follow-up appointments after their child’s PED visit. We conducted semi-structured interviews with caregivers of children with headaches from 4 large urban PEDs over HIPAA-compliant Zoom conferencing platform. A facilitator/co-facilitator team (JH and SL) guided all interviews, and the audio of which was transcribed using the TRINT software. Conventional content analysis was performed by two coders (JH and AS) to generate new themes, and coding disputes were resolved by team members using Atlas TI (version 24). Results/Anticipated Results: We interviewed a total of 11 caregivers (9 mothers, 1 grandmother, and 1 father). Among interviewees, 45% identified as White non-Hispanic, 45% Hispanic, 9% as African-American, and 37% were publicly insured. Participants described similar experiences in obtaining follow-up care that included long waits to obtain neurology appointments. Participants also described opportunities to overcome wait times that included offering alternative healthcare provider types as well as telehealth options. Last, participants described desired action while awaiting neurology appointments such as obtaining testing and setting treatment plans. Discussion/Significance of Impact: Caregivers perceived time to appointment as too long and identified practical solutions to ease frustrations while waiting. Future research should explore sharing caregiver experiences with primary care providers, PED physicians, and neurologists while developing plans to implement caregiver-informed interventions.

Over the last decade, the USA experienced an unprecedented opioid crisis. While there are myriad causes for this crisis, here we examine how social capital shapes the public’s demand for opioids and the government’s responses to the crisis. First, we posit that communities with higher levels of social capital are associated with lower rates of opioid use/abuse. Second, we posit that higher levels of social capital will be associated with a more robust public response in providing necessary resources to address substance abuse resulting in lower rates of drug-related deaths. Using county-level data from the USA, we find support for an indirect relationship where social capital is associated with higher levels of community support for drug treatment, which, in turn, is associated with lower drug-related deaths and deaths of despair.

We reviewed infection prevention policies using an adapted Equity Impact Assessment tool. Thirty-one percent of policies had substantial potential to impact marginalized groups and create or sustain inequities, and most lacked existing equity considerations. Systematic policy review for equity implications can result in actions to improve care and quality.

The compromise effect arises when being close to the “middle” of a choice set makes an option more appealing. The compromise effect poses conceptual and practical problems for economic research: by influencing choices, it can bias researchers’ inferences about preference parameters. To study this bias, we conduct an experiment with 550 participants who made choices over lotteries from multiple price lists (MPLs). Following prior work, we manipulate the compromise effect to influence choices by varying the middle options of each MPL. We then estimate risk preferences using a discrete-choice model without a compromise effect embedded in the model. As anticipated, the resulting risk preference parameter estimates are not robust, changing as the compromise effect is manipulated. To disentangle risk preference parameters from the compromise effect and to measure the strength of the compromise effect, we augment our discrete-choice model with additional parameters that represent a rising penalty for expressing an indifference point further from the middle of the ordered MPL. Using this method, we estimate an economically significant magnitude for the compromise effect and generate robust estimates of risk preference parameters that are no longer sensitive to compromise-effect manipulations.

The paper considers what can be inferred about experimental subjects’ time preferences for consumption from responses to laboratory tasks involving tradeoffs between sums of money at different dates, if subjects can reschedule consumption spending relative to income in external capital markets. It distinguishes three approaches identifiable in the literature: the straightforward view; the separation view; and the censored data view. It shows that none of these is fully satisfactory and discusses the resulting implications for intertemporal decision-making experiments.