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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Alzheimer's disease and alpha-synuclein pathology in the olfactory bulbs of infants, children, teens and adults ≤ 40 years in Metropolitan Mexico City. APOE4 carriers at higher risk of suicide accelerate their olfactory bulb pathology

Highlights: • Air pollution targets olfactory bulbs in young city dwellers. • Olfactory bulb hyperphosphorylated tau and Lewy neurites are present in Mexico City toddlers. • APOE4 carriers accelerate their OB pathology and have 4.7 times higher suicide odds v APOE3. • Olfactory testing may aid in identifying young persons at high risk for neurodegenerative disease. • Early neuroprotective interventions in PM{sub 2.5} and CDNP's exposed individuals ≤ 20 years are critical. There is growing evidence that air pollution is a risk factor for a number of neurodegenerative diseases, most notably Alzheimer's (AD) and Parkinson's (PD). It is generally assumed that the pathology of these diseases arises only later in life and commonly begins within olfactory eloquent pathways prior to the onset of the classical clinical symptoms. The present study demonstrates that chronic exposure to high levels of air pollution results in AD- and PD-related pathology within the olfactory bulbs of children and relatively young adults ages 11 months to 40 years. The olfactory bulbs (OBs) of 179 residents of highly polluted Metropolitan Mexico City (MMC) were evaluated for AD- and alpha-synuclein-related pathology. Even in toddlers, hyperphosphorylated tau (hTau) and Lewy neurites (LN) were identified in the OBs. By the second decade, 84% of the bulbs exhibited hTau (48/57), 68% LNs and vascular amyloid (39/57) and 36% (21/57) diffuse amyloid plaques. OB active endothelial phagocytosis of red blood cell fragments containing combustion-derived nanoparticles (CDNPs) and the neurovascular unit damage were associated with myelinated and unmyelinated axonal damage. OB hTau neurites were associated mostly with pretangle stages 1a and 1b in subjects ≤ 20 years of age, strongly suggesting olfactory deficits could potentially be an early guide of AD pretangle subcortical and cortical hTau. APOE4 versus APOE3 carriers were 6–13 times more likely to exhibit OB vascular amyloid, neuronal amyloid accumulation, alpha-synuclein aggregates, hTau neurofibrillary tangles, and neurites. Remarkably, APOE4 carriers were 4.57 times more likely than non-carriers to die by suicide. The present findings, along with previous data that over a third of clinically healthy MMC teens and young adults exhibit low scores on an odor identification test, support the concept that olfactory testing may aid in identifying young people at high risk for neurodegenerative diseases. Moreover, results strongly support early neuroprotective interventions in fine particulate matter (PM{sub 2.5}) and CDNP's exposed individuals ≤ 20 years of age, and the critical need for air pollution control.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A novel application of terrestrial LIDAR to characterize elevation change at human grave surfaces in support of narrowing down possible unmarked grave locations

Unmarked graves are difficult to locate once the ground surface no longer shows visible evidence of disturbance, posing significant challenges to missing person investigations. This research evaluates the use of terrestrial LIDAR point data for measuring localized elevation change at human grave surfaces. Three differently sized human graves, one control-pit, and surrounding undisturbed ground, were scanned four times between February 2013 and November 2014 using a tripod-mounted terrestrial laser scanner. All the disturbed surfaces exhibited measurable and localized elevation change, allowing for separation of disturbed and undisturbed ground. In conclusion, this study is the first to quantify elevation changes to human graves over time and demonstrates that terrestrial LIDAR may contribute to multi-modal data collection approach to improve unmarked grave detection.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Assessing Single-Source Reproducibility of Human Head Hair Peptide Profiling from Different Regions of the Scalp

Neither microscopical hair comparisons nor mitochondrial DNA sequencing alone, or together, constitutes a basis for personal identification. Due to these limitations, a complementary technique to compare questioned and known hair shafts was investigated. Recently, scientists from Lawrence Livermore National Laboratory's Forensic Science Center and other collaborators developed a peptide profiling technique, which can infer non-synonymous single nucleotide polymorphisms (SNPs) preserved in hair shaft proteins as single amino acid polymorphisms (SAPs). In this study, peptide profiling was evaluated to determine if it can meet forensic expectations when samples are in limited quantities with the possibility that hair samples collected from different areas of a single donor’s scalp (i.e., single source) might not exhibit the same SAP profile. The average dissimilarity, percent differences in SAP profiles within each source, ranged from 0% difference to 29%. This pilot study suggests that more work is needed before peptide profiling of hair can be considered for forensic comparisons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Meeting sustainable aviation fuel policy targets through first generation corn biorefineries

This paper investigates options to produce low carbon and renewable aviation fuel through existing commercial first generation biorefineries, which could be strategic given the rapid growth of the electric vehicle market for personal mobility. We evaluate the environmental impact of retrofitting a first generation biorefinery to produce aviation fuel through chemical process simulation. The analysis investigates the potential for reducing greenhouse gas (GHG) emissions and displacing fossil fuel (petroleum-based jet kerosene) in the aviation fuel industry through using corn feedstocks in dry grind biorefineries to convert sugars to 1,4-dimethylcyclooctane (DMCO), which qualifies as renewable jet-A fuel blend and is infrastructure compatible. Further, the average life cycle GHG emissions for a baseline case and a scenario with carbon capture and storage (CCS) of fermentative CO 2 are 36 and 5g CO 2 e/MJ DMCO, respectively. Investment in CCS at the biorefinery and adoption of crop best management practices on farms are essential for mitigating the risks of induced land use change GHG emissions for existing corn biorefineries. DMCO as a low-carbon aviation fuel could be a strategic fuel product for retrofitting existing corn dry grind facilities. For aviation fuel supply, corn dry grind facilities could displace about 12% of jet fuel demand in the near term, which would meet sustainable aviation fuel policy targets. We conclude that corn-to-DMCO shows promise for near-term low-carbon fuel markets in the aviation industry and as a bridge to developing biomass-based jet fuel in the future.

09 BIOMASS FUELS↗
DOE OSTI2022

Induced seismicity red-light thresholds for enhanced geothermal prospects in the Netherlands

Prospects for geothermal energy in the Netherlands have renewed concerns around induced earthquakes. Risks from induced earthquakes are managed by traffic light protocols (TLPs), where the red-light is chosen as the stop-point before exceeding a tolerance to risk. Here, we simulate post-shut-in earthquake scenarios based on realistic information for the Netherlands. We focus on three risk metrics: aggregates like nuisance and damage impacts and also local personal risk (LPR) – a likelihood of building collapse fatality for an individual. Our results show that the severity of these risks varies spatially by orders of magnitude. Prior induced seismicity (e.g., the 2012 Huizinge event) provides a reference baseline to calibrate the Dutch earthquake risk tolerances. We find that these calibrated risk tolerances are similar to those observed in North America, suggesting an underlying sociological ‘license to operate.’ Furthermore, the use of calibrated risk tolerances results in nuisance concerns completely eclipsing the other two metrics. We compare our results to a hypothetical Groningen geothermal operation and find that our approach sets red-light thresholds approximately one magnitude unit below the ML 3.6 Huizinge event. Overall, our results provide a first-order recommendation for red-light thresholds and proactive management of Dutch enhanced geothermal induced seismicity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Accelerating demand for residential solar photovoltaics: Can simple framing strategies increase consumer interest?

Household adoption of energy-efficient and renewable energy technologies has the potential to significantly reduce emissions from electricity generation. High upfront costs, however, are often a barrier to adoption, even when costs may be offset by future energy savings. Through a series of randomized experiments, we examine whether framing strategies grounded in behavioral economics and psychology can be used to increase the financial appeal of such products. Using mock ads for residential solar photovoltaics (PV), we test four frames: gain/loss framing, temporal framing, varied savings amounts, and simple vs. detailed savings calculations. Overall, we find that reframing the financial benefits of PV does not greatly influence the appeal of solar or the likelihood to respond to the mock ads. Instead, underlying consumer motivations and predispositions (i.e., perceived social support, consumer innovativeness, and personal pro-environmental norms) are the primary factors driving interest in adopting solar. Our findings suggest that tailoring messages to targeted consumer segments may be more effective than attempts to market the financial benefits of PV to broad audiences. Furthermore, the results also contribute to behavioral economics and psychology research by identifying contexts under which the gain/loss framing bias and the present/future framing bias may not apply.

14 SOLAR ENERGY↗
DOE OSTI2020

Synergistic enhancement of nanocellulose foam with dual in situ mineralization and crosslinking reaction

Cellulose nanocrystals (CNCs) foams have recently gained research interests because they are renewable, abundant, biodegradable and exhibit high surface area. However, the application of CNCs-based foams is still challenging, which is attributed to its lack of effective entanglements between the CNCs particles, thus lowering foam properties. In this study, a synergistic enhancement strategy was proposed, based on the in situ mineralization with hydroxyapatite (HAP) layer onto the CNCs surface, followed by a chemical crosslinking reaction. The physical and chemical structures of the composites were analyzed with SEM, STEM, XRD, FTIR, and TGA. By controlling the amount of coated HAP and the crosslinker, it is possible to manufacture a series of CNCs-based foams that are lightweight (50–75 mg/cm 3 ), highly porous (~90%) with high water absorption (>1300%) and outstanding mechanical strength properties (as high as 1.37 MPa). Moreover, our study further indicated that these CNCs/HAP materials could increase the proliferation of rat osteoblast cells. The method developed in this study presents a novel approach to design improved networked CNCs foam, which has the potential to be used in thermal-retardant material, wastewater treatment, tissue engineering, and personal care applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Human Choice and CCS Deployment: What have we learned from the social sciences about CCS?

It is my pleasure to present this Virtual Special Issue of key social science papers that have been published in the International Journal of Greenhouse Gas Control (IJGCC). These papers show that the social science research community has significantly advanced the state-of-the-art from vague discussions about the “acceptance of CCS” to a body of deeply insightful and actionable knowledge about how CCS is likely to be framed and how framing will impact the ultimate deployment of CCS as a means of mitigating anthropogenic climate change. The papers assembled here shed light on core issues such as how do humans make decisions about a new technology like CCS that they have no direct personal experience with and what is it is about “new” technologies that we find unsettling. These papers also speak to what are the best, and for that matter the worst, ways of presenting inherently highly technical information to lay audiences, including insights about the substance of the information, the form in which the information is delivered, and who delivers it. An extended editorial about this virtual special issue is freely available on ScienceDirect. I hope you find the papers contained in this Virtual Issue to be as informative and insightful as I do.

carbon dioxide capture and storage↗
DOE OSTI2016

An optimization approach to design monitoring schemes for CO 2 leakage detection

This paper demonstrates an approach to identify optimal monitoring designs that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. This research is part of the National Risk Assessment Partnership (NRAP), a DOE project tasked with conducting risk and uncertainty analysis in the areas of reservoir performance, natural leakage pathways, wellbore integrity, groundwater protection, monitoring, and systems level modeling. Our approach applies a simulated annealing algorithm that searches the solution space by iteratively mutating potential monitoring designs. An example application is provided to demonstrate the effectiveness and efficiency of this method compared to an exhaustive search of the entire solution space. We took into account uncertainty by evaluating the performance of potential monitoring designs across a set of simulated leakage realization. A flexible two-tiered signature was implemented to infer that CO 2 leakage had occurred. This approach was ~50 times faster than an exhaustive search. A user-friendly tool, MDLD, is being developed for use on personal computers to make this method available to stakeholders, regulators, and researchers.

03 NATURAL GAS↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗
DOE OSTI2022

Deep learning-accelerated 3D carbon storage reservoir pressure forecasting based on data assimilation using surface displacement from InSAR

Fast forecasting of the reservoir pressure distribution during geologic carbon storage (GCS) by assimilating monitoring data is a challenging problem. Due to high drilling cost, GCS projects usually have spatially sparse measurements from few wells, leading to high uncertainties in reservoir pressure prediction. To address this challenge, we use low-cost Interferometric Synthetic-Aperture Radar (InSAR) data as monitoring data to infer reservoir pressure build up. We develop a deep learning-accelerated workflow to assimilate surface displacement maps interpreted from InSAR and to forecast dynamic reservoir pressure. Employing an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates three-dimensional (3D) geologic properties and predicts reservoir pressure with quantified uncertainties. We use a synthetic commercial-scale GCS model with bimodally distributed permeability and porosity to demonstrate the efficacy of the workflow. A two-step CNN-PCA approach is employed to parameterize the bimodal fields. The computational efficiency of the workflow is boosted by two residual U-Net based surrogate models for surface displacement and reservoir pressure predictions, respectively. The workflow can complete data assimilation and reservoir pressure forecasting in half an hour on a personal computer.

25 ENERGY STORAGE↗
DOE OSTI2018

The fill density of automotive cryo-compressed hydrogen vessels

Cryo-compressed hydrogen storage promises to deliver highest system storage density leading to fundamental cost and safety advantages. Yet, cryogenic vessels are complex systems, continuously drifting in thermodynamic space depending on use patterns, insulation performance, vessel characteristics, liquid hydrogen pump performance, and para-H 2 to ortho-H 2 conversion. This paper reflects a comprehensive evaluation of all factors affecting cryogenic vessel fill density, in an effort to evaluate system performance vs. operational parameters over a broad range of conditions. The results validate previous experiments and models indicating that cryogenic vessels have maximum fill density of all available storage technologies, and fill density is most sensitive to daily driving distance and insulation performance. It is lastly predicted that para-H 2 to ortho-H 2 conversion will affect most automobiles, increasing fill density by up to 5.3%. In a future world dominated by cryogenic H 2 fueled vehicles, para-H 2 to ortho-H 2 conversion inside the vessel will be the closest contact an average person will have with quantum mechanics outside of consumer electronics.

08 HYDROGEN↗
DOE OSTI2018

Empirical profiling of cold hydrogen plumes formed from venting of LH 2 storage vessels

Liquid hydrogen (LH 2 ) storage is viewed as a viable approach to assure sufficient hydrogen capacity at commercial fuelling stations. Presently, LH 2 is produced at remote facilities and then transported to the end-use site by road vehicles (i.e., LH 2 tanker trucks). Venting of hydrogen to depressurize the transport storage tank is a routine part of the LH 2 delivery and site transfer process. The behavior of cold hydrogen plumes has not been well characterized because of the sparsity of empirical field data, which can lead to overly conservative safety requirements. Committee members of the National Fire Protection Association (NFPA) Standard 2 [1] formed the Hydrogen Storage Safety Task Group, which consists of hydrogen producers, safety experts, and computational fluid dynamics modellers, has identified the lack of understanding of hydrogen dispersion during LH 2 venting of storage vessels as a critical gap for establishing safety distances at LH 2 facilities, especially commercial hydrogen fuelling stations. To address this need, the National Renewable Energy Laboratory Sensor Laboratory, in collaboration with the NFPA Hydrogen Storage Task Group, developed a prototype Cold Hydrogen Plume Analyzer to empirically characterize the hydrogen plume formed during LH 2 storage tank venting. The prototype analyzer was field deployed during an actual LH 2 venting process. Critical findings included: hydrogen above the lower flammable limit (LFL) was detected as much as 2 m lower than the release point, which is not predicted by existing models; personal monitors detected hydrogen at ground level, although at levels below the LFL; a small but inconsistent correlation was found between oxygen depletion and the hydrogen concentration; a negligible to non-existent correlation was found between in-situ temperature measurements and the hydrogen concentration. The prototype analyzer is being upgraded for enhanced metrological capabilities, including improved real-time spatial and temporal profiling of hydrogen plumes and tracking of prevailing weather conditions. Additional deployments are planned to monitor plume behavior under different wind, humidity, and temperature conditions. The data will be shared with the Hydrogen Storage Task Group and ultimately will be used support theoretical models and code requirements prescribed in NFPA 2.

08 HYDROGEN↗
DOE OSTI2015

Effect of twist on transverse impact response of ballistic fiber yarns

A Hopkinson bar was employed to conduct transverse impact testing of twisted Kevlar KM2 fiber yarns at the same impact speed. The speed of Euler transverse wave generated by the impact was measured utilizing a high speed digital camera. The study included fiber yarns twisted by different amounts. The Euler transverse wave speed was observed to increase with increasing amount of twist of the fiber yarn, within the range of this investigation. As a result, the higher transverse wave speeds in the more twisted fiber yarns indicate better ballistic performance in soft body armors for personal protection.

42 ENGINEERING↗
DOE OSTI2021

Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track

Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine. We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing. We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests

Female reproductive disorders (FRDs) are common health conditions that may present with significant symptoms. Diet and environment are potential areas for FRD interventions. We utilized a knowledge graph (KG) method to predict factors associated with common FRDs (for example, endometriosis, ovarian cyst, and uterine fibroids). We harmonized survey data from the Personalized Environment and Genes Study (PEGS) on internal and external environmental exposures and health conditions with biomedical ontology content. We merged the harmonized data and ontologies with supplemental nutrient and agricultural chemical data to create a KG. We analyzed the KG by embedding edges and applying a random forest for edge prediction to identify variables potentially associated with FRDs. We also conducted logistic regression analysis for comparison. Across 9765 PEGS respondents, the KG analysis resulted in 8535 significant or suggestive predicted links between FRDs and chemicals, phenotypes, and diseases. Amongst these links, 32 were exact matches when compared with the logistic regression results, including comorbidities, medications, foods, and occupational exposures. Mechanistic underpinnings of predicted links documented in the literature may support some of our findings. Our KG methods are useful for predicting possible associations in large, survey-based datasets with added information on directionality and magnitude of effect from logistic regression. These results should not be construed as causal but can support hypothesis generation. This investigation enabled the generation of hypotheses on a variety of potential links between FRDs and exposures. Future investigations should prospectively evaluate the variables hypothesized to impact FRDs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2010

A Population-Based Study of Subsequent Primary Malignancies After Endometrial Cancer: Genetic, Environmental, and Treatment-Related Associations

Purpose: To examine the risk of subsequent primary malignancies (SPMs) in women diagnosed with endometrial cancer. Methods and Materials: The National Cancer Institute's Survival, Epidemiology, and End Results database was used to determine the risk of SPM after endometrial cancer in 69,739 women diagnosed between 1973 and 2005. Standardized incidence ratios were calculated (observed/expected [O/E]) for SPM sites. Results: Median follow-up was 11.2 years, representing 757,567 person-years of follow-up. The risk of SPM was significantly increased for small intestine (O/E = 1.48; 99% confidence interval [CI], 1.03-2.05), colon (O/E = 1.16; CI, 1.09-1.24), vagina (O/E = 2.71; CI, 1.86-3.8), and urinary bladder (O/E = 1.41; CI, 1.25-1.59) SPMs and decreased for oral cavity and pharynx (O/E = 0.75; CI, 0.6-0.93), lung and bronchus (O/E = 0.78; CI, 0.72-0.84), and esophagus (O/E = 0.58; CI, 0.37-0.86) SPMs. Patients receiving external-beam radiotherapy for endometrial cancer had an increased risk of colon (p < 0.001), bladder (p < 0.001), vagina (p = 0.04), and soft-tissue (p = 0.014) SPMs. Patients treated with brachytherapy had an increased risk of bladder SPM (p = 0.006). A positive bidirectional association with endometrial cancer was observed for colorectal cancer, with a negative bidirectional association for oropharyngeal and lung cancers. Conclusions: Genetic, environmental, and treatment-related factors influence SPM risk. Genetic factors may contribute to the increased risk of colorectal cancer. Smoking's negative effect on endometrial cancer risk factors might explain the decreased risk of lung and oropharyngeal cancer. Patients treated with radiotherapy likely have a small but significantly increased risk of bladder, vagina, colon, and soft-tissue SPM.

62 RADIOLOGY AND NUCLEAR MEDICINE↗