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Chemical Characterization and Antimicrobial Activity of Green Propolis from the Brazilian Caatinga Biome

Green propolis, particularly from the unique flora of the Brazilian Caatinga biome, has gained significant interest due to its diverse chemical composition and biological activities. This study focuses on the chemical characterization and antimicrobial evaluation of Caatinga green propolis. Twelve compounds were isolated through different chromatographic techniques, including flavanones (naringenin, 7-O-methyleriodictyol, sakuranetin), flavones (hispidulin, cirsimaritin), flavonols (quercetin, quercetin-3-methyl ether, kaempferol, 6-methoxykaempferol, viscosine, penduletin), and one chalcone (kukulkanin B). Using liquid chromatography–quadrupole time-of-flight tandem mass spectrometry (LC-QToF-MS), a total of 55 compounds excluding reference standards were tentatively identified, which include flavonoids, phenolic acids derivatives, and alkaloids, with flavonols, flavanones, and flavones being predominant. Antimicrobial testing against pathogens revealed that the crude extract exhibited low inhibitory activity, against Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE) (IC50: 148.4 and 120.98 µg/mL, respectively). Although the isolated compounds showed limited individual activity, a fraction containing sakuranetin and penduletin (Fraction 8) exhibited moderated activity against Cryptococcus neoformans (IC50: 47.86 µg/mL), while a fraction containing quercetin and hispidulin showed moderated activity against VRE (IC50: 16.99 µg/mL). These findings highlight the potential application of Caatinga green propolis as an antimicrobial agent, particularly against resistant bacterial strains, and underscore the importance of synergistic interactions between compounds in enhancing biological effects.

Aldana-Mejía, Jennyfer A. (ORCID:0000000307361899)↗

Myths of German Graphite in World War II, with Original Translations

We re-examine the common narrative that a 1941 experimental error by physicists Walther Bothe and Peter Jensen led Germany to abandon graphite as a reactor moderator during World War II. We first detail the history of both German and American graphite experiments, noting that the Americans faced similar setbacks but succeeded only at the end of a costly 18-month graphite purification program. We then use Monte Carlo N-Particle simulations to reconstruct Bothe's 1941 experiment. We find the thermal absorption cross section of Bothe's Siemens electrographite to be 12.2 mb, in contrast to his reported 7.9 mb. This discrepancy arises because the neutrons in Bothe's experiment did not reach thermal equilibrium, leading to an underestimation of neutron absorption. Additionally, despite misconceptions that the Germans were unaware of boron impurities, we share evidence that Wilhelm Hanle accurately measured boron and cadmium impurities in the electrographite. To support our findings, we provide 9 excerpted and 3 complete English translations of classified wartime reports by Heisenberg, Joos, Bothe, Jensen, Höcker, Hanle, and Kremer. Our work aims to illuminate the rational constraints behind Germany's decision to forgo graphite moderation.

Park, Patrick J.↗

MSD CoP Webinar: AI and Extreme Events - Overcoming Data Challenges for Improved Characterization of Climate Extremes

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Artificial Intelligence (AI) models require large volumes of data for training and testing. Data requirements present challenges for using AI to explore extreme events with limited observational data. This webinar will showcase two innovative methods developed by part of the European Climate Intelligence (CLINT) project to overcome data challenges and harness AI to improve our understanding of climate extremes. Dr. Ascenso will present his research on data augmentation methods to improve estimates of tropical cyclones using satellite data. His presentation will review established methods for data augmentation and explore opportunities and challenges for using generative AI to generate images of extreme, life-threatening tropical cyclones. Next, Dr. Plesiat will present his research on deep learning techniques to overcome limited observational data sets. His presentation will illustrate deep learning methods to develop AI reconstructions of four climate indices across Europe. Presenters : Dr. Guido Ascenso (post-doctoral researcher, Politecnico di Milano); Dr. Étienne Plésiat (German Climate Computing Centre - DKRZ) Moderator(s): Stefano Galelli (MSD CoP WG Co-Lead), David Gold (MSD CoP WG Co-Lead), Jillian Sturtevant (MSD CoP WG Communications Officer), Matteo Giuliani (Politecnico di Milano, MSD CoP WG Member, Moderator and Organizer) This webinar was held on: October 11, 2024 from 11AM - 1PM ET

AI↗

MSD CoP Webinar: Representing Climate Impacts in Scenaros

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Scenarios of future emissions and land use have been most commonly produced without accounting for the effects that climate impacts linked to those emissions and land use changes may have. The questions of how important such impacts could be, at the regional or global scale, has become an increasingly cogent one. Using the Global Change Analysis Model (GCAM), we implement climate impacts on water supply, agricultural productivity, and energy demand driven by climatic impact drivers whose evolution over the 21st century is representative of a climate consistent with GCAM's reference scenario and compare the output to the reference at both regional and global scales. We show that the impacts from the version of GCAM that uses GDP as an exogenous input are not sufficient to bend emission pathways at the global scale. However, we see effects emerge at the regional scale in terms of emissions, among other metrics linked to water, land and energy. We expect the impacts to become more significant at an aggregate, global scale in a forthcoming version of the model with endogenous GDP. Meanwhile, we document the mechanisms that drive the difference at regional scales which could still be significant in their impacts for individual economies and populations. Presenters: Dr. Claudia Tebaldi (Joint Global Change Research Institute, Pacific Northwest National Laboratory) Moderator(s): Jennifer Morris (MSD CoP SSG member), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 5, 2024 from 1 PM - 2:15 PM ET

Climate Scenarios↗

MSD CoP Webinar: Accounting for distributive justice in model-based decision support

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Model-based analyses play an ever-increasing role in informing policy and decision-making. However, many large-scale societal challenges unavoidably involve questions about the fair distribution of positive and negative consequences. How are the costs of the energy transition distributed over households and businesses? How are flood risks redistributed under different flood risk management plans? How are the impacts of climate change and climate mitigation distributed over different parts of the world?These kinds of questions play an important role when deliberating public policy, and the lack, in many cases, of clear answers becomes an obstacle to decision-making. At recent COPs, for example, wicked questions about loss and damages and the phase-out versus phase-down of coal became obstacles to global climate action, illustrating the misalignment of the direction of scientific research and decision-makers' information needs. In this talk, I'll explore advances that are being made that enable analysts to start providing grounded model-based answers to questions of distributive justice, as well as argue that analysts should embrace and explicate the normative nature of their work instead of hiding behind the purported neutrality of science. Presenters: Dr. Jan Kwakkel (Delft University of Technology) Moderator(s): Rebecca Saari (MSD CoP Working Group Co-Chair; Univ. of Waterloo), Matt Sparks (Univ. of Waterloo); Sarah Fletcher (MSD CoP Working Group Co-Chair; Stanford University), Juan Moreno-Cruz (Univ. of Waterloo), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 13, 2024 from 1 PM - 2:15 PM ET

Kwakkel, Jan H.↗

Computational Modeling of Molten Salt Infiltration and Oxidation in Nuclear Graphite

Graphite is utilized as a moderator and reflector in advanced nuclear reactor designs due to its high thermal conductivity, neutron moderation properties, and resistance to radiation damage. However, its longterm performance and reliability are challenged by degradation mechanisms such as molten salt infiltration in molten salt reactors (MSRs) and oxidation in gas-cooled reactors (GCRs). These mechanisms can compromise the structural integrity and operational lifetime of graphite components, necessitating a more detailed assessment of their physical behavior. This report focuses on the development of computational models for molten salt infiltration and oxidation of graphite to aid the design and performance analysis of graphite components. For molten salt infiltration, a computational framework is developed that couples incompressible Navier-Stokes and phase-field model to simulate the penetration of molten salt into graphite?s interconnected pore structure. Initial model verification is performed using two-phase flows in two dimensions, demonstrating the models ability to capture fundamental physical behavior and agree with analytical solution. This framework is then applied to a realistic IG110 nuclear graphite , where a computed tomography extracted pore geometry is used to analyse the infiltration behavior of FLiNaK molten salt. This model provides insights into how the microstructure and other relevant parameters influence the transport pathways of molten salt into graphite, potentially offering a means to rapidly evaluate a graphite grade?s resistance to infiltration. For oxidation, the report details pore-scale mass and heat transport models, describing the diffusion of gases, reaction kinetics, and thermal effects. Additionally, this report highlights inconsistencies in the existing volume-averaged macroscopic model, particularly in upscaling of reaction kinetics and flux terms, and surface to volume transformations. These inconsistencies suggest that current formulations may not accurately capture the experimentally observed graphite oxidation process, highlighting the need for improved model development. This work advances the development of physics-based computational models for graphite degradation, contributing to improved predictive models for next-generation nuclear reactor designs. Future efforts will focus on refining the infiltration model to address non-physical behaviors and enhance its robustness. Additionally, for oxidation, further studies will employ the principles of volume averaging to rigorously derive the upscaled equations, potentially in collaboration with subject matter experts.

Computational Modeling of Molten Salt Infiltration↗

A Bottom-Up Cost Estimation Tool for Nuclear Microreactors

The rising interest in nuclear microreactors has highlighted the need for comprehensive technoeconomic assessments. However, the scarcity of publicly available designs and cost data has posed significant challenges. To address this issue, the Microreactor Optimization Using Simulation and Economics (MOUSE) tool is developed. MOUSE is a tool that integrates nuclear microreactor design with reactor economics. The design calculations encompass core simulations using the OpenMC Monte Carlo Particle Transport Code [romano2015], along with simplified balance of plant calculations. On the economic side, MOUSE provides detailed bottom-up cost estimates, calculating both the total capital cost and the levelized cost of energy for first-of-a-kind and nth-of-a-kind microreactors. The cost estimation correlations are developed using data from the MARVEL project and additional literature sources. MOUSE has released as an open-source tool on GitHub (MOUSE Tool). By combining design calculations with cost equations, MOUSE enables users to evaluate the impact of various technological consideration, advanced moderators, design changes, material/fuel changes, and geometry modifications—as well as economic parameters like interest rates and construction duration. This comprehensive framework can guide stakeholders towards technological solutions that enhance microreactor competitiveness. Additionally, powered by the WATTS toolkit [romano2022], MOUSE supports optimization studies, parametric analyses, and uncertainty calculations/propagation. Currently, preconceptual designs of three microreactor types are included in MOUSE: a liquid metal thermal microreactor (LTMR), gas cooled TRISO-fueled microreactor (GCMR) and heat-pipe TRISO fueled microreactor (HPMR). To showcase its ability, MOUSE was used to conduct detailed bottom-up cost estimates for the first of a kind (FOAK) and Nth of a kind (NOAK) of the following microreactors • A 20MWt LTMR that is built on the ongoing MARVEL demonstration at Idaho National Laboratory (INL) • A 15 MWt GCMR that was designed to be more representative of the typical commercial microreactor • A 7 MWt HPMR that was built on previous work (Choi 2024) The The reader should note that these three designs and corresponding cost estimates are examples to demonstrate the MOUSE capability. The designs are pre-conceptual, the reactor designs were not optimized, and the cost estimates were developed with incomplete information. Additionally, stakeholders might be interested in a variety of designs that may differ from the examples provided in this report. The MOUSE tool can also be used to study how design choices affect economics. To demonstrate its capability, MOUSE was used conduct parametric studies such as examining the economic impact of the reflector's material and thickness, the moderator's booster material and dimensions, fuel composition and enrichment, core size, and power level. Several insights were gained from these parametric studies.

Hanna, Botros↗

Stream Temperature Responses to Summer Urban Rain Events Along the Savannah River

The hydrological urban heat island (HUHI) is a recent facet of the urban heat island (UHI), describing thermal enhancement of bodies of water in response to urbanization. Although the forefront of this work has been studied for large Metropolitan areas, this effect on developing cities is currently unknown. To locally measure and quantify HUHI effects in a developing city, we utilized Multi-Radar Multi Sensor (MRMS) radar-derived rainfall data to estimate rainfall in the Augusta Metropolitan Area (AMA) and the Savannah Metropolitan Area (SMA), two developing communities adjacent to the Savannah River. We analyzed mean temperature trends of two stream gauges measuring temperature at, and downstream of the central AMA and the SMA. Results show overall peak stream temperatures within AMA are reached within a 2hr timeframe with surge temperatures between 1-2 K, perhaps assisted by the presence of the Augusta Shoals further upstream. The SMA appears to have little HUHI effects due to urban greening and impacts to coastal meteorology. It is suggested that Moderate rainfall events (10-25mm of rainfall) have a significant correlation (~0.1 correlation coefficient with a significance level of 0.05) between stream temperature and rainfall, indicating potential warmer runoff input into the Savannah River. Although results seem promising, further research into moderate rainfall events are needed to determine the extent of the HUHI for AMA.

Wermter, Joseph E. [Savannah River National Labora↗

Experimental and Computational Study of Weld Drop-Through Hydraulic Effects in Multi-Layer Concentric Pipes Servicing Cryogenic Liquid Hydrogen

The Cryogenic Moderator System (CMS) at the Oak Ridge National Laboratory (ORNL)-Spallation Neutron Source (SNS) supplies liquid hydrogen, through vacuum insulated transfer lines to the moderators. The welding process used to make the transfer lines produces weld drop-through, which can constrict the flow of hydrogen and/or cause thermal bridges between adjacent layers. To ensure proper operation of the CMS it is therefore necessary to conduct a flow test to verify the pressure drop caused by the welds. Measurements in as-built piping sections intended to provide liquid hydrogen service to the SNS-CMS system were performed to test the effect of weld penetrations into the fluid flow area focusing on pressure drop effects. The reference test sections were designed using prototypical piping dimensions, materials and expected penetration welds. A numerical study using Computational Fluid Dynamics (CFD) tools in the transfer lines provided a conversion factor from the pressure drop measured in the lines with water to the expected pressure drop using liquid cryogenic hydrogen. The results show evidence of a maximum pressure drop modification in water of 78 KPa in the tested parts, which scales to liquid hydrogen as PHydrogen = 5.2 KPa. The maximum measured equivalent blockage area percentage was found in the as-built TDM transfer line spool 2 with a value of 31%. The measured values obtained in the as-built transfer lines provided accurate values to estimate the expected total pressure drop in the CMS system providing operational limits for the current recirculatory capacity. The effect of the weld drop-through in hydrogen evacuation capacity scenarios was better evaluated as a result of this study.

Dominguez-Ontiveros, Elvis [ORNL] (ORCID:000000018↗

Low-Income Energy Affordability Data - LEAD Tool - 2022 Update

The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11. The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below. For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.

AMI↗

Effect of impurities on hydrogen defect stability and migration barrier in yttrium dihydride crystal

The impurity or alloying atoms in YH 2 can alter the local electronic structure and so the hydrogen defect stability, as well as the H migration barrier energy. Thus, DFT calculations were employed to determine the effect of foreign elements from alkali and alkaline earth metals to transition metals and one critical impurity element, O, on H vacancy stability and retention characteristics in YH2. Results revealed that alloying elements act as hydrogen vacancy sinks by reducing the vacancy formation energy at neighboring sites. The implantation of non-magnetic foreign elements (s1, s2, and d10 valence electrons) in hydrogen energy landscape was calculated to be minor; while the hydrogen vacancy formation energy was reduced from 1.37 eV to 1.00 eV, the migration energy barrier of hydrogen was increased from 0.87 eV to 1.15 eV for non-magnetic foreign elements. The migration energy barrier monotonically decreased with increasing d-shell occupancy, reaching as low as 0.4 eV for Cr, Mo(d4), and Fe (d4). Alloying with late transition metals (d8 and d9) moderately impacted the hydrogen vacancy formation. Finally, it was found to be O addition into the YH 2- lattice did not alter the energy landscape of hydrogen vacancies. Since alloyed YH 2 has not been studied extensively, this study provides an atomistic understanding how alloying elements and impurities trap vacancies and affects hydrogen mobility YH 2 . Meanwhile, the main findings of this study may serve as guidelines for introducing alloying elements in ZrH 2 as well.

08 HYDROGEN↗

Enhanced power density in zero-vacuum-gap thermophotovoltaic devices

Thermophotovoltaic (TPV) devices, which convert infrared thermal radiation from a hot emitter into electricity, hold great promise for applications in energy storage and waste heat recovery. While recent advancements have developed TPV devices with high efficiency, much less attention has been focused on improving the power density. Current TPV methods face challenges in significantly boosting the power density using emitters at very high temperatures (>2000 °C) or using complex, costly architectures such as near-field TPV. Here, we present the first experimental demonstration of a novel far-field TPV concept called “zero-vacuum-gap TPV” that eliminates the vacuum or gas-filled gap in conventional designs. By incorporating a high-index, infrared-transparent, and thermally insulating fused quartz spacer, we achieved a two-fold increase in power density compared to the far-field counterpart under identical conditions. Notably, in our experiment, the zero-vacuum-gap far-field design transforms a less-optimized, low-power-density far-field device into one with one of the highest power densities reported at moderate temperatures (700–1100 °C). Moreover, our measurements using a graphite emitter surpass the blackbody limit for gap-integrated far-field devices and match the performance of near-field TPV devices with an ultrathin 200-nm gap. Our findings suggest that zero-vacuum-gap TPV offers potential for cost-effective, scalable manufacturing using current technologies. Additionally, our modelling predicts that further power enhancements over one order of magnitude are possible with other spacer materials.

14 SOLAR ENERGY↗

Investigation of High-Temperature Compatibility of Select Oxides with Yttrium Hydride for Micro and Space Reactor Applications

Yttrium hydride is a promising material for a high-temperature neutron moderator in advanced micro and space reactors due to its high hydrogen density and relative thermal stability compared to other metal hydrides. However, yttrium hydride desorbs hydrogen rapidly at temperatures above 800°C, which is below the operational temperature range of some reactor designs. A hydrogen barrier coating of oxide on the hydride surface may inhibit hydrogen loss at 800°C and beyond, but the high-temperature compatibility between yttrium hydride and many oxides is currently unknown. The high-temperature compatibility of Al 2 O 3 , MgO, and Y 2 O 3 with YH 1.92 was examined by subjecting mixed oxide–hydride pellets to a 1200°C heat treatment then using a combination of diffractometry, microscopy, and spectroscopy to determine changes in the pellet composition as a result. Yttrium scavenged oxygen from both Al 2 O 3 and MgO to form Y 2 O 3 , resulting in significant loss of YH 1.92 . Yttrium reacted with reduced aluminum to form YAl 2 and several other compounds. Reduced magnesium volatilized above 1091°C and vacated the pellet. Only Y 2 O 3 did not appreciably react with YH 1.92 . Of the three oxides tested, only Y 2 O 3 was compatible with YH 1.92 at 1200°C based on the experimental criteria.

compatibility↗

Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin

This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4) “MTBS_fire”. The ERA meteorological fields and the data processing scritps are in (5) “ERA_Var_CR”. All the scripts for figure development are in the format of *ncl and in the folder (6) “paper_scripts”. See the file ending in “flmd.csv” for a list of all files contained in this data package and descriptions for each. Tabular column headers and units are described in the data dictionary file ending in “dd.csv”.

54 ENVIRONMENTAL SCIENCES↗

Proceedings for the Workshop on Applied Nuclear Data Activities 2025

The 2025 Workshop for Applied Nuclear Data Activities (WANDA) covered four topic areas in nuclear data: Nuclear Data and Deterrence, Nuclear Data Prioritization for Fusion, High-Assay Low-Enriched Uranium and Novel Moderators for Advanced Reactors, and Data Preservation and Data Workflows. The intention of this workshop is to connect different communities that are invested in nuclear data and have their own unique sets of needs for the purposes of sharing information, fostering collaboration in areas of shared interest, and leveraging synergistic capabilities. The attendance of federal program managers at these workshops is essential in creating awareness of the needs of their respective communities and in providing information to better guide funding investments. In each of these topical sessions, a general description of the nuclear data needs and/or capabilities was presented, along with discussions of existing capabilities that could be leveraged, potential synergistic needs or resources, and challenges that must be overcome for the application space to progress. There are many synergistic nuclear data needs among these application spaces. The discussion largely focused on increasing the accuracy of the nuclear data and better quantifying the data uncertainties that have the greatest impact on applications. The full-day session on data processing and data workflows was by nature intended to be synergistic and applicable to all technical sessions at WANDA. A notable common theme that was highlighted across all sessions was the need for accelerated delivery of nuclear data products across complex and time-consuming workflows.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TEX-Chlorine: Highly Enriched Uranium with Chloride Absorbers to Provide Validation Benchmarks for Y-12 Electrorefining Facility

This report documents the final benchmark of the TEX-Chlorine (IER-499) Thermal Epithermal eXperiments (TEX) with highly enriched uranium with chlorine absorbers and high-density polyethylene reflectors and moderators. TEX-Chlorine is a variation of the TEX-HEU baseline assembly with the addition of sodium chloride absorber plates. This evaluation contains three experimental configurations that were performed on Comet at NCERC between July and August 2024. The three configurations, which were acceptable as benchmark cases, spanned from thermal (first two configurations) to fast (third configuration). All three cases were reviewed and accepted by the ICSBEP TRG in April 2025 and was submitted to the ICSBEP in August 2025 after receiving subgroup approval.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Influence of Demographic Variables on the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA)

Building on our prior research with a national survey sample of 5385 US participants, the Pooled Rideshare Acceptance Model (PRAM) was built upon two factor analyses. This exploratory study extends the PRAM framework using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) to examine how 16 demographic variables influence and interact with the acceptance of Pooled Rideshare (PR), filling a gap in understanding user segmentation and personalization. Using a national sample of 5385 US participants, this methodological approach allowed for the evaluation of how PRAM variables such as safety, privacy, service experience, and environmental impact vary across diverse groups, including gender, generation, driver’s license, rideshare experience, education level, employment status, household size, number of children, income, vehicle ownership, and typical commuting practices. Factors such as convenience, comfort, and passenger safety did not show significant differences across the moderators, suggesting their universal importance across all demographics. Furthermore, geographical differences did not significantly impact the relationships within the model, suggesting consistent relationships across different regions. The findings highlight the need to move beyond a “one size fits all” approach, demonstrating that tailored strategies may be crucial for enhancing the adoption and satisfaction of PR services among various demographic groups. The analyses provide valuable insight for policymakers and rideshare companies looking to optimize their services and increase user engagement in PR.

moderator↗

Agent-Based Model of Combined Community- and Jail-Based Take-Home Naloxone Distribution

Importance Opioid-related overdose accounts for almost 80 000 deaths annually across the US. People who use drugs leaving jails are at particularly high risk for opioid-related overdose and may benefit from take-home naloxone (THN) distribution. Objective To estimate the population impact of THN distribution at jail release to reverse opioid-related overdose among people with opioid use disorders. Design, Setting, and Participants This study developed the agent-based Justice-Community Circulation Model (JCCM) to model a synthetic population of individuals with and without a history of opioid use. Epidemiological data from 2014 to 2020 for Cook County, Illinois, were used to identify parameters pertinent to the synthetic population. Twenty-seven experimental scenarios were examined to capture diverse strategies of THN distribution and use. Sensitivity analysis was performed to identify critical mediating and moderating variables associated with population impact and a proxy metric for cost-effectiveness (ie, the direct costs of THN kits distributed per death averted). Data were analyzed between February 2022 and March 2024. Intervention Modeled interventions included 3 THN distribution channels: community facilities and practitioners; jail, at release; and social network or peers of persons released from jail. Main Outcomes and Measures The primary outcome was the percentage of opioid-related overdose deaths averted with THN in the modeled population relative to a baseline scenario with no intervention. Results Take-home naloxone distribution at jail release had the highest median (IQR) percentage of averted deaths at 11.70% (6.57%-15.75%). The probability of bystander presence at an opioid overdose showed the greatest proportional contribution (27.15%) to the variance in deaths averted in persons released from jail. The estimated costs of distributed THN kits were less than $\$$15 000 per averted death in all 27 scenarios. Conclusions and Relevance This study found that THN distribution at jail release is an economical and feasible approach to substantially reducing opioid-related overdose mortality. Training and preparation of proficient and willing bystanders are central factors in reaching the full potential of this intervention.

Tatara, Eric [Argonne National Laboratory (ANL), A↗