Search NASA⌕ Search

SEARCH · Search NASA

Results for “Social Isolation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Influence of Mild Chronic Stress and Social Isolation on Acute Ozone-Induced Alterations in Stress Biomarkers and Brain-Region-Specific Gene Expression in Male Wistar–Kyoto Rats

Individuals with psychosocial stress often experience an exaggerated response to air pollutants. Ozone (O 3 ) exposure has been associated with the activation of the neuroendocrine stress-response system. We hypothesized that preexistent mild chronic stress plus social isolation (CS), or social isolation (SI) alone, would exacerbate the acute effects of O 3 exposure on the circulating adrenal-derived stress hormones, and the expression of the genes regulating glucocorticoid stress signaling via an altered stress adaptation in a brain-region-specific manner. Male Wistar–Kyoto rats (5 weeks old) were socially isolated, plus were subjected to either CS (noise, confinement, fear, uncomfortable living, hectic activity, and single housing), SI (single housing only, restricted handling and no enrichment) or no stress (NS; double housing, frequent handling and enrichment provided) for 8 weeks. The rats were then exposed to either air or O 3 (0.8 ppm for 4 h), and the samples were collected immediately after. The indicators of sympathetic and hypothalamic–pituitary axis (HPA) activation (i.e., epinephrine, corticosterone, and lymphopenia) increased with O 3 exposure, but there were no effects from CS or SI, except for the depletion of serum BDNF. CS and SI revealed small changes in brain-region-specific glucocorticoid-signaling-associated markers of gene expression in the air-exposed rats (hypothalamic Nr3c1, Nr3c2 Hsp90aa1, Hspa4 and Cnr1 inhibition in SI; hippocampal HSP90aa1 increase in SI; and inhibition of the bed nucleus of the stria terminalis (BNST) Cnr1 in CS). Gene expression across all brain regions was altered by O 3 , reflective of glucocorticoid signaling effects, such as Fkbp5 in NS, CS and SI. The SI effects on Fkbp5 were greatest for SI in BNST. O 3 increased Cnr2 expression in the hypothalamus and olfactory bulbs of the NS and SI groups. O 3 , in all stress conditions, generally inhibited the expression of Nr3c1 in all brain regions, Nr3c2 in the hippocampus and hypothalamus and Bdnf in the hippocampus. SI, in general, showed slightly greater O 3 -induced changes when compared to NS and CS. Serum metabolomics revealed increased sphingomyelins in the air-exposed SI and O 3 -exposed NS, with underlying SI dampening some of the O 3 -induced changes. These results suggest a potential link between preexistent SI and acute O 3 -induced increases in the circulating adrenal-derived stress hormones and brain-region-specific gene expression changes in glucocorticoid signaling, which may partly underlie the stress dynamic in those with long-term SI.

gene expression↗

Social Vulnerability and Beacon Hill Resilience Hub Network [Slides]

Improving community resilience to climate change impacts is a core goal of the Beacon Hill stakeholder task force. Developing a network of resilience hubs in the community is a strategy the task force is pursuing to build this resilience. This technical assistance aims to assist the task force in their resilience hub network planning by: identifying hazards that the resilience hubs may address; providing background information on social vulnerability and climate impacts; identifying populations in Beacon Hill who are at risk to disproportionate climate impacts due to social isolation and physical vulnerability characteristics (e.g., lack of transportation or internet); and identifying the potential role of resilience hubs that align with best practices for reducing social vulnerability to climate impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States

To increase situational awareness and support evidence-based policymaking, we formulated a mathematical model for coronavirus disease transmission within a regional population. This compartmental model accounts for quarantine, self-isolation, social distancing, a nonexponentially distributed incubation period, asymptomatic persons, and mild and severe forms of symptomatic disease. We used Bayesian inference to calibrate region-specific models for consistency with daily reports of confirmed cases in the 15 most populous metropolitan statistical areas in the United States. We also quantified uncertainty in parameter estimates and forecasts. This online learning approach enables early identification of new trends despite considerable variability in case reporting.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular and Epidemiological Investigation of Fluconazole-resistant Candida parapsilosis —Georgia, United States, 2021

Abstract Background Reports of fluconazole-resistant Candida parapsilosis bloodstream infections are increasing. We describe a cluster of fluconazole-resistant C parapsilosis bloodstream infections identified in 2021 on routine surveillance by the Georgia Emerging Infections Program in conjunction with the Centers for Disease Control and Prevention. Methods Whole-genome sequencing was used to analyze C parapsilosis bloodstream infections isolates. Epidemiological data were obtained from medical records. A social network analysis was conducted using Georgia Hospital Discharge Data. Results Twenty fluconazole-resistant isolates were identified in 2021, representing the largest proportion (34%) of fluconazole-resistant C parapsilosis bloodstream infections identified in Georgia since surveillance began in 2008. All resistant isolates were closely genetically related and contained the Y132F mutation in the ERG11 gene. Patients with fluconazole-resistant isolates were more likely to have resided at long-term acute care hospitals compared with patients with susceptible isolates (P = .01). There was a trend toward increased mechanical ventilation and prior azole use in patients with fluconazole-resistant isolates. Social network analysis revealed that patients with fluconazole-resistant isolates interfaced with a distinct set of healthcare facilities centered around 2 long-term acute care hospitals compared with patients with susceptible isolates. Conclusions Whole-genome sequencing results showing that fluconazole-resistant C parapsilosis isolates from Georgia surveillance demonstrated low genetic diversity compared with susceptible isolates and their association with a facility network centered around 2 long-term acute care hospitals suggests clonal spread of fluconazole-resistant C parapsilosis. Further studies are needed to better understand the sudden emergence and transmission of fluconazole-resistant C parapsilosis.

Misas, Elizabeth (ORCID:0000000162437716)↗

Distributed Energy Resources as an Equity Asset: Lessons Learned from Deployments in Disadvantaged Communities

For an Energy System to be truly equitable, it should provide affordable and reliable energy services to disadvantaged and underserved populations. Disadvantaged communities often face a combination of economic, social, health, and environmental burdens and may be geographically isolated (e.g., rural communities), which systematically limits their opportunity to fully participate in aspects of economic, social, and civic life.

24 POWER TRANSMISSION AND DISTRIBUTION↗

“Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study

Background: The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation. Health-related misinformation threatens adherence to public health messaging, and monitoring its spread on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts. Objective: The aim of this study is to use Twitter data to explore methods to characterize and classify four COVID-19 conspiracy theories and to provide context for each of these conspiracy theories through the first 5 months of the pandemic. Methods: We began with a corpus of COVID-19 tweets (approximately 120 million) spanning late January to early May 2020. We first filtered tweets using regular expressions (n=1.8 million) and used random forest classification models to identify tweets related to four conspiracy theories. Our classified data sets were then used in downstream sentiment analysis and dynamic topic modeling to characterize the linguistic features of COVID-19 conspiracy theories as they evolve over time. Results: Analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. Random forest classifier metrics varied across the four conspiracy theories considered (F1 scores between 0.347 and 0.857); this performance increased as the given conspiracy theory was more narrowly defined. We showed that misinformation tweets demonstrate more negative sentiment when compared to non-misinformation tweets and that theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events. Conclusions: Although we focus here on health-related misinformation, this combination of approaches is not specific to public health and is valuable for characterizing misinformation in general, which is an important first step in creating targeted messaging to counteract its spread. Initial messaging should aim to preempt generalized misinformation before it becomes widespread, while later messaging will

5g↗

ReNCAT: The Resilient Node Cluster Analysis Tool

ReNCAT is a software application that suggests microgrid portfolios that reduce the impact of large-scale disruptions to power, as measured by the Social Burden Metric. ReNCAT examines a power distribution network to identify regions that can be isolated into microgrids that enable critical services to be provided even if the remainder of the study area is left without power. ReNCAT operates on a simplified representation of the power grid, one that aggregates and approximates loads and conductors. Microgrids are formed within the power network by setting switch states to split or join portions of the grid. ReNCAT identifies candidate microgrid portfolios with varying tradeoffs between cost and service availability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Social-ecological interactions in a disaster context: Puerto Rican farmer households’ food security after Hurricane Maria

Islands are uniquely vulnerable to extreme weather events and food insecurity, and have additional response challenges due to their limited landmasses and economies, isolation, colonial legacies, and high dependence of food imports. Domestic farmers have a key role in producing food for island communities like Puerto Rico, which can safeguard food security when food importation may be challenging. Nevertheless, in the context of disaster, farmers themselves may be vulnerable to food insecurity and unable to contribute to domestic markets. This paper examines Puerto Rican farmers households’ food security in the aftermath of 2017’s Hurricane Maria using a social-ecological lens. Survey data from 405 farmers gathered eight months after Maria, coupled with biophysical data from the hurricane’s impacts (winds, rains, and landslides), were analyzed. Overall, 69% of farmers experienced at least one month of food insecurity in the aftermath of Hurricane Maria, and 38% reported persistent food insecurity (three months or more). A multinomial logistic regression suggests that biophysical impacts, but especially social factors, such as age and constraint access to external sources of support, are linked with persistent food insecurity. This suggests that the biophysical impacts of the hurricane interact with existing infrastructure and social resources to affect farmer vulnerability and the food environment in different ways. Thus, strengthening adaptive capacity in multiple domains can help farmers and vulnerable populations better navigate the disruptions faced during disasters to alleviate food insecurity.

54 ENVIRONMENTAL SCIENCES↗

Leveraging SETS resilience capabilities for safe-to-fail infrastructure under climate change

As the rehabilitation of infrastructure is outpaced by changes in the profile, frequency, and intensity of extreme weather events, infrastructure’s service disruptions and failures become increasingly likely. Safe-to-fail approaches for infrastructure planning and design improve the capacity of cities to adapt for uncertain climate futures by identifying social, ecological, and technological systems (SETS) capabilities to prepare for potential failure scenarios. In this work, we argue for transforming infrastructure planning and design to effectively utilize safe-to-fail approaches by navigating the opportunities and trade-offs of SETS resilience capabilities. From a technological vantage point, traditional infrastructure planning approaches account for social and ecological domains as external design conditions rather than embedded system characteristics. Safe-to-fail approaches directly challenge the isolation of the technological domain by necessitating a recognition that SETS domains are interconnected and interdependent in infrastructure systems, as such risks and system capabilities for resilience must be managed cohesively.

54 ENVIRONMENTAL SCIENCES↗

Past Approaches for Spent Nuclear Fuel, Transuranic, and High-Level Waste Disposal in the United States—Part 2: Siting Process, Staged Development, and Public Preferences

This report presents pertinent aspects of the ~50-year United States experience in siting a mined geologic disposal repository for spent nuclear fuel (SNF), transuranic (TRU) waste, and high-level radioactive waste (HLW) as related to site selection and the staged process for site investigations as specified in the Nuclear Waste Policy Act of 1982 and generic and site-specific regulations of the US Department of Energy (DOE), US Environmental Protection Agency (EPA), and US Nuclear Regulatory Commission (NRC). The roles of the Environmental Impact Statement and guidance in international consensus standards by the International Atomic Energy Agency are also mentioned. The focus is on siting and developing the Waste Isolation Pilot Plant, an operating repository for TRU waste from atomic energy defense activities, and the proposed Yucca Mountain repository for commercial SNF and HLW. In the social dimension, the role of institutional stakeholders is described. Past national surveys related to waste management options for storage and disposal provide insight on public preferences of other stakeholders. The descriptions are intended to help other countries more fully understand the stages adopted for siting and developing repositories in the United States.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Generating Mixed Patterns of Residential Segregation: An Evolutionary Approach

The Schelling model of residential segregation has demonstrated that even the slightest preference for neighbors of the same race can be amplified into community-wide segregation. However, these models are unable to simulate mixed, coexisting patterns of segregation and integration, which have been seen to exist in cities. Using evolutionary model discovery we demonstrate how including social factors beyond racial bias when modeling relocation behavior enables the emergence of strongly mixed patterns. Our results indicate that the emergence of mixed patterns is better explained by multiple factors influencing the decision to relocate; the most important being the interaction of nonlinear, rapidly diminishing racial bias with a recent, historical tendency to move. Additionally, preference for less isolated neighborhoods or preference for neighborhoods with longer residing neighbors may produce weaker mixed patterns. Finally, this work highlights the importance of exploring the influence of multiple hypothesized factors of decision making, and their interactions, within agent rules, when studying emergent outcomes generated by agent-based models of complex social systems.

97 MATHEMATICS AND COMPUTING↗

Setting the Baseline: The Current Understanding of Equity in Land-Based Wind Energy Development and Operation

As discussions about economic equity and environmental justice have become more prevalent in recent years, the related concepts of "energy justice" or "energy equity" have received increasing attention from policymakers, industry, nonprofits, and academics. According to the Initiative for Energy Justice (2019), energy justice is defined as "The goal of achieving equity in both the social and economic participation in the energy system, while also remediating social, economic, and health burdens on those disproportionately harmed by the energy system" The state of equity as it applies specifically to wind energy, however, remains relatively unexplored and isolated to academia. As a result, the National Renewable Energy Laboratory's Wind Energy Equity Engagement Series aims to better understand equity in wind energy through engagement with experts and communities, including representation in decision-making around new developments, potential impacts to communities near wind energy installations, and community-level distribution of the benefits and burdens of wind energy. This report covers the first three phases of the series.

17 WIND ENERGY↗

Power System Modeling for the Study of High Penetration of Distributed Photovoltaic Energy

Many conventional power systems are evolving due to the growth of renewable energy and distributed energy resources (DERs). Modeling the interplay of transmission and distribution systems is critical to analyze how DERs impact a system’s conventional operation and which electric infrastructure improvements are needed to achieve a balance between centralized generation and DERs. This article describes the process, tools, and resources used to model electric power systems with a centralized infrastructure in an isolated context and limited access to actual utility data. Photovoltaic systems installed on residential rooftops were the main design option. This work broadened the typical power system modeling to include planning and social considerations. This integrative engineering-social method allows for interdisciplinary teams to work in the development of a model as part of broader design goals for a renewable-dominant energy system. The Puerto Rico electric power system was used as a case study to demonstrate the process. The integrative engineering-social perspective in developing the model and the actions to manage data limitations are aspects that could be followed in other locations with aggressive renewable energy goals and where utility data are not readily available.

Cuello-Polo, Gustavo↗

A population data-driven workflow for COVID-19 modeling and learning

CityCOVID is a detailed agent-based model that represents the behaviors and social interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 million distinct places, including households, schools, workplaces, and hospitals, as determined by individual hourly activity schedules and dynamic behaviors such as isolating because of symptom onset. Disease progression dynamics incorporated within each agent track transitions between possible COVID-19 disease states, based on heterogeneous agent attributes, exposure through colocation, and effects of protective behaviors of individuals on viral transmissibility. Throughout the COVID-19 epidemic, CityCOVID model outputs have been provided to city, county, and state stakeholders in response to evolving decision-making priorities, while incorporating emerging information on SARS-CoV-2 epidemiology. Here we demonstrate our efforts in integrating our high-performance epidemiological simulation model with large-scale machine learning to develop a generalizable, flexible, and performant analytical platform for planning and crisis response.

97 MATHEMATICS AND COMPUTING↗

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗

A comprehensive review on the loss of wellbore integrity due to cement failure and available remedial methods

With the recent abrupt fluctuations in oil pricing and the need of complying with environmental and social requirements, nowadays it is an urgent call for the oil and gas industry to produce the hydrocarbon without any loss as well as in a safe manner. Cements are placed in the annular space of casing to provide zonal isolation in between wellbore and surface during the operational life cycle of the well or even after the abandonment. But this is not what happens most of the time. Cement degrades or loses its integrity through debonding either from the casing or formation and generates cracks or fractures due to varied reasons throughout the life of the well. Multiple causes contribute to the loss of wellbore integrity – either by physical, mechanical, or chemical processes. These failures lead to sustained casing pressure (SCP) and contamination of surrounding environment. To combat this issue or to restore the well integrity, multiple remedial actions have also been either implemented in the industry or proposed based on experimental research to prevent the damage or to seal the leakage in the cement sheath. Here, this paper will provide an extensive review of the underlying reasons of cement failure and the available remedial actions to minimize the loss of well integrity issue. These information are not only useful to know about the different corrective options available for us to implement in industry but also it will provide us a knowledge base regarding how we can enhance the performance of the exiting systems to battle the cement integrity problem more efficiently.

02 PETROLEUM↗

Distributed Renewables for Arctic Energy: A Case Study

Alaska is a vast state that stretches into the Arctic Circle. Roughly 140,000 people in the state are dependent on isolated electric grids, traditionally burning expensive fossil fuels. This has negative impacts on air quality and climate. As the climate warms, fuel supply chains and traditional ways of life are threatened. Renewable electric sources offer a clean, resilient alternative with less volatile costs, but there are a variety of technical, social, economic, and political challenges to developing renewable energy systems in remote Arctic communities. Examples include harsh operating conditions, lack of local technical and managerial capacity, complex funding mechanisms, and glacial permitting processes. In this study, we interview one group of communities that are interested in adding renewable energy to their systems to understand the needs and challenges they face, and then another group that has successfully installed renewable energy, to understand how they overcame such challenges and the lessons they learned. Notable results include the importance of local buy-in, education, and technical involvement, procuring external funding sources, inter-community collaboration, installing bespoke systems, and working with reliable equipment suppliers. The goal of this report is to orient and inspire Arctic communities that want to begin their renewable transition, by providing helpful examples and points of contact.

17 WIND ENERGY↗