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Cropland and Land-Clearing Emission Factors From Firex-AQ

The Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign is a NOAA/NASA interagency intensive study of North American fires that took place from July to September 2019. Agricultural fires were sampled on 7 flights from August 21st to September 3rd, 2019. We present emission factors for gas-phase and aerosol-phase species for the different fuel types identified during the campaign. We discuss the dependence of these emission factors on both fuel type and burning characteristics such as modified combustion efficiency (MCE). We analyze 73 fires encompassing four different agricultural fuels (corn, rice, soybean, wheat) and four different types of land-clearing fuels (grass, slash, pile, shrub). Approximately half of all sampled fires were burning corn agricultural residue. We report emission factors for 118 VOCs, where two thirds of emissions are made up of species with lifetimes against oxidation by OH of less than 12 hours (near-field impacts) and the remainder have longer-lifetimes (far-field impacts). We also include an additional 9 aerosol species, 12 halogenated species, 5 sulfur-containing species, and 22 nitrogen-containing species, including NH3 and NOx. There is a statistically significant difference in MCE between agricultural and land-clearing fires that accounts for some of the differences in emission factors across these fuels. VOCs generally have a strong negative correlation with MCE but with different slopes across fuel types. There is a significant positive relationship between MCE and three gas-phase (NO, NO2, SO2) and two aerosol-phase (pCl, pNH4) species. Many emission factors show additional dependence factors beyond MCE that could be related to fuel composition, fire temperature, soil moisture, or other possible differences in burning conditions. Therefore, important differences in emission factors may result when averaging together different types of agricultural and land-clearing fuels in compilations for use in modeling efforts.

biomass burning↗

DOE OSTI2023

A Review of Factors Affecting the Susceptibility of Juvenile Salmonids to Avian Predation

Abstract We reviewed studies of piscivorous colonial waterbird predation on juvenile salmonids to synthesize current knowledge of factors affecting fish susceptibility to avian predators. Specifically, we examined peer-reviewed publications and reports from academic, governmental, and nongovernmental agencies to identify commonalities and differences in susceptibility of salmonids to avian predation, with a focus on mark–recovery studies in the Columbia River basin. Factors hypothesized to influence salmonid susceptibility to avian predation were grouped into four general categories: (1) salmonid species and populations, (2) environmental factors, (3) prey density, predator density, and migration timing, and (4) prey characteristics. Our review focused on predation by Caspian terns Hydroprogne caspia, double-crested cormorants Nannopterum auritum, and gull species Larus spp. as these are the most well-studied avian predators of salmonids. Results indicated that predator–prey interactions varied across salmonid species and populations and species of avian predator. Inferences across studies supported multiple hypotheses regarding predator–prey dynamics, including environmental factors that influence prey exposure to predators (e.g., river flows, turbidity, alternative prey), variation in predator and prey abundances, predator characteristics (e.g., foraging behavior, colony location), and prey characteristics (e.g., fish length, condition). Mark–recovery studies of avian predation on fish populations have greatly improved our understanding of the factors affecting fish susceptibility to avian predation, the relative contributions of abiotic and biotic factors to predation susceptibility, and the extent to which avian predation affects fish survival and the viability of prey populations. Future studies that jointly model predation and survival and the factors affecting those processes will further broaden our understanding of predator–prey dynamics and directly evaluate the effects of predation on prey population dynamics.

Hostetter, Nathan J. (ORCID:0000000160752157)↗

DOE OSTI2022

Empirical relationships between environmental factors and soil organic carbon produce comparable prediction accuracy as the Machine Learning

Accurate representation of environmental controllers of soil organic carbon (SOC) stocks in Earth System Model (ESM) land models could reduce uncertainties in future carbon-climate feedback projections. Using empirical relationships between environmental factors and SOC stocks to evaluate land models can help modelers understand prediction biases beyond what can be achieved with the observed SOC stocks alone. In this study, we used 31 observed environmental factors, field SOC observations (n = 6,213) from the continental US, and two Machine Learning approaches [Random Forest (RF) and Generalized Additive Modeling (GAM)] to (1) select important environmental predictors of SOC stocks, (2) derive empirical relationships between environmental factors and SOC stocks, and (3) use the derived relationships to predict SOC stocks and compare the prediction accuracy of simpler model developed with the machine learning predictions. Out of the 31 environmental factors we investigated, 12 were identified as important predictors of SOC stocks by the RF approach. In contrast, the GAM approach identified six (of those 12) environmental factors as important controllers of SOC stocks: potential evapotranspiration, normalized difference vegetation index, soil drainage condition, precipitation, elevation, and net primary productivity. The GAM approach showed minimal SOC predictive importance of the remaining six environmental factors identified by the RF approach. Our derived empirical relations produced comparable prediction accuracy as the GAM and RF approach using only a subset of environmental factors. The empirical relationships we derived using the GAM approach can serve as important benchmarks to evaluate environmental control representations of SOC stocks in ESMs, which could reduce uncertainty in predicting future carbon-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The three-point form factor of Tr ϕ 3 to six loops

We study the three-point form factor of the length-three half-BPS operator (Tr ϕ 3 ) in planar $\mathcal{N}$ = 4 Super-Yang-Mills theory, using analyticity and integrability methods. We find that the functions describing the form factor in perturbation theory live in the same restrictive space of multiple polylogarithms as the one describing the form factor of the stress-tensor operator (Tr ϕ 2 ). Furthermore, we find that the leading-order data in the collinear limit provided by the form factor operator product expansion (FFOPE) is enough to fix the form factor uniquely, at least through six loops. We perform various tests of our results using the subleading FFOPE corrections. We also analyze the form factor in the Regge limit where two Mandelstam invariants are large; we obtain a compact representation for the form factor in this limit which is valid to all orders in the coupling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2018

High expression of fibroblast growth factor-21 in liposarcoma patients indicated better prognosis and less recurrence

Liposarcoma is the most common soft tissue malignancy. We investigated the relationship between the expression of fibroblast growth factor −21 protein and recurrence in the liposarcoma tissues from 40 patients. The patients were divided into two groups (low/no- and high-expressing) for further survival analysis according to fibroblast growth factor −21 expression in their tumor tissue. Immunohistochemical staining showed that fibroblast growth factor −21 protein was located in the cytoplasm. The fibroblast growth factor −21 protein was significantly less expressed in liposarcoma than in normal tissue (p < 0.05). Fibroblast growth factor −21 protein expression was related to gender, but not age, cell differentiation or tumor size. The patients in the low/no fibroblast growth factor 21 expression group were more likely to relapse and die in a shorter period of time. The patients in the high-expression group had a better prognosis and less recurrence. fibroblast growth factor −21 has the potential to act both as a biomarker for liposarcoma prognosis as well as a marker for the response to therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Identifying key factors of the seawater intrusion model of Dagu river basin, Jiaozhou Bay

Highlights: • The key factors of seawater intrusion model is identified by mutual entropy analysis. • Precipitation rate and groundwater pumping are the key factors for seawater intrusion. • The hydraulic conductivity of zone 1 has significant influence on seawater intrusion. Seawater intrusion is a complex groundwater - seawater interaction process, and it is influenced by many factors from ground surface to underground, from groundwater to seawater. Generally, for seawater intrusion model, some model parameters and boundary conditions are always specified by model users’ personal experiences or literature's reference value. The defective model would damage the groundwater management for controlling and preventing seawater intrusion when making decisions are based on this model. In order to improve the reliability of seawater intrusion model, the influences of model inputs on output should be identified prior at optimizing model inputs. Dagu river basin, Jiaozhou Bay is one of the most serious areas of seawater intrusion in China, and it is chosen as the study area in this study. The seawater intrusion model of Dagu river basin is built based on a general program SEAWAT4. The key influence factors of model output are analyzed by two sensitivity analysis methods, i.e., stepwise regression and mutual entropy. The results demonstrated that the most important influence factors which have largest sensitivities to groundwater Cl{sup -} concentration are the precipitation rate and groundwater pumping in agriculture area. In addition, the hydraulic conductivity of zone 1 has a non-negligible influence on seawater intrusion process. Stepwise regression analysis is capable of identifying most important influence factor, and it can’t handle complicated nonlinear input-output relationship. Mutual entropy analysis is reliable for identifying the influence factors for complex seawater intrusion model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

E-scooter safety: How attitudinal factors influence risky behavior among shared e-scooter riders

In recent years, e-scooter usage for short-distance trips has grown rapidly. This surge in e-scooter use, combined with the high exposure of e-scooter riders to accident risk, has sparked concerns regarding e-scooter safety. Despite some studies focusing on e-scooter safety, little is known about how attitudinal factors lead e-scooter riders to engage in risky riding behaviors. In this paper, we developed a survey-based empirical model to identify the attitudinal factors influencing engagement in risky behaviors among e-scooter users. We used survey data collected from 420 shared e-scooter users in Chicago in 2022. The survey showed that 47.7% of respondents had experienced at least one collision or fall-off while riding e-scooters. We employed the Partial Least Squares Structural Equation Model (PLS-SEM) to examine the relationships between latent attitudinal factors and risky behavior engagement. Moreover, we conducted Permutation Multi-group Analysis (PMGA) to assess the moderating effect of socio-demographic factors within the estimated model. The findings suggest that riders’ unsafe riding attitude and riding confidence are the most influential factors shaping their risky behavior engagement. In addition, accident experience, infrastructure suitability, perceived enjoyment, traffic risk perception, and operational risk perception are among the other significant predictors. Among socio-demographic factors, gender, age, education, and car use frequency significantly influence riders’ engagement in risky behaviors. The results highlight the importance of infrastructure suitability and accident experience in analyzing e-scooter users’ riding behavior. The developed model advances our understanding of factors contributing to e-scooter riders’ risky behavior engagement. The findings offer valuable insights for policymakers and e-scooter vendors aiming to mitigate e-scooter users’ accident risk. Specifically, we recommend three safety countermeasures: (1) safety training programs to encourage a safer attitude, (2) practice-based initiatives to enhance riding confidence, and (3) infrastructure improvements, especially the expansion of bike lanes.

E-scooter↗

DOE OSTI2021

Prime factorization using quantum variational imaginary time evolution

The road to computing on quantum devices has been accelerated by the promises that come from using Shor’s algorithm to reduce the complexity of prime factorization. However, this promise hast not yet been realized due to noisy qubits and lack of robust error correction schemes. Here we explore a promising, alternative method for prime factorization that uses well-established techniques from variational imaginary time evolution. We create a Hamiltonian whose ground state encodes the solution to the problem and use variational techniques to evolve a state iteratively towards these prime factors. We show that the number of circuits evaluated in each iteration scales as $O(n^{5}d)$ , where n is the bit-length of the number to be factorized and d is the depth of the circuit. We use a single layer of entangling gates to factorize 36 numbers represented using 7, 8, and 9-qubit Hamiltonians. We also verify the method’s performance by implementing it on the IBMQ Lima hardware to factorize 55, 65, 77 and 91 which are greater than the largest number (21) to have been factorized on IBMQ hardware.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Factorized QED and QCD contribution to deeply inelastic scattering

We present the first calculation of next-to-leading order (NLO) factorized QED and QCD contributions to the short-distance hard coefficients of inclusive lepton-hadron deep inelastic scattering (DIS) in a joint QED and QCD factorization approach. Unlike the traditional radiative correction approach to handle the collision-induced QED contributions to DIS, QED radiation from all charged leptons and quarks are treated equally, and their collinear sensitivities are systematically factorized into corresponding universal lepton and parton distribution functions. We demonstrate that the NLO factorized short-distance QED contribution is completely infrared safe and calculable without the need of any parameters other than the standard factorization scale in the same way as the factorized short-distance QCD contribution. We discuss the potential impact of this joint factorization approach on the extraction of partonic information from lepton-hadron DIS.

Deep inelastic scattering↗

DOE OSTI2017

Extraction of the neutron electric form factor from measurements of inclusive double spin asymmetries

Background: Measurements of the neutron charge form factor, G$n\atop{E}$, are challenging because the neutron has no net charge. Additionally, measurements of the neutron form factors must use nuclear targets which require accurately accounting for nuclear effects. Extracting G$n\atop{E}$ with different targets and techniques provides an important test of our handling of these effects. Purpose: The goal of the measurement was to use an inclusive asymmetry measurement technique to extract the neutron charge form factor at a four-momentum transfer of 1 (GeV/c) 2 . This technique has very different systematic uncertainties than traditional exclusive measurements and thus serves as an independent check of whether nuclear effects have been taken into account correctly. Method: The inclusive quasielastic reaction 3 $→\atop{He}$ ($→\atop{e}$, e') was measured at Jefferson Laboratory. The neutron electric form factor, G$n\atop{E}$, was extracted at Q 2 = 0.98 ( GeV/c) 2 from ratios of electron-polarization asymmetries measured for two orthogonal target spin orientations. This Q 2 is high enough that the sensitivity to G$n\atop{E}$ is not overwhelmed by the neutron magnetic contribution, and yet low enough that explicit neutron detection is not required to suppress pion production. Results: The neutron electric form factor, G$n\atop{E}$, was determined to be 0.0414 ± 0.0077 ( stat ) ± 0.0022 ( syst ), providing the first high-precision inclusive extraction of the neutron's charge form factor. In conclusion: The use of the inclusive quasielastic 3 $→\atop{He}$ ($→\atop{e}$, e') with a four-momentum transfer near 1 (GeV/c) 2 has been used to provide a unique measurement of G$n\atop{E}$. This new result provides a systematically independent validation of the exclusive extraction technique results and implies that the nuclear corrections are understood. This is contrary to the proton form factor where asymmetry and differential cross section measurements have been shown to have large systematic differences.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Effect of Coaxial Electrode Geometry on the Electric Field Enhancement Factor for a High Voltage Vacuum Gap

We present an experimental analysis of the change in the electric field enhancement factor with varying gap size and penetration depth (P.D) of cathode into anode for a coaxial vacuum gap, diagnosed using Fowler–Nordheim analysis and optical imaging via scanning electron microscope (SEM) and time integrated Digital single lens reflex camera (DSLR). Data were collected on the Coaxial Gap Breakdown Machine (240 A, 25 kV, 150 ns, 0.1 Hz). Experiments using five different gap sizes at nine different P.Ds are compared over runs comprising 50 shots for each case. The results show a strong link between enhancement factor and gap size, with P.D and surface topology. For large gap sizes, 150, 330, and 700 μm, the average enhancement factor value increases with increasing P.D. For smaller gap sizes, 50 and 100 μm, the average enhancement factor decreases with P.D. SEM imaging before and after plasma formation for each gap size allows for quantifying surface finish, microprotrusion growth, average blast diameter, and an estimation of the surface area breakdowns occupy. Time integrated DSLR imaging analysis of the gap at each shot allows for a determination of the distribution of breakdowns about the circumference of the gap for each case tested. Here, the Fowler–Nordheim analysis allows for a quantitative analysis of the surface roughness of all gap sizes tested. Results show that for large gap sizes, the gap geometry and increasing area of breakdown is the main cause for increasing average enhancement factor. For small gap sizes, the dominant driving factor for small average enhancement factors—that subsequently decrease with P.D—is significant changes in surface topology due to an increased number of breakdowns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Experimental Study on the Effect of Localized Blockages on the Friction Factor of a 61-Pin Wire-Wrapped Bundle

Abstract The thermal-hydraulic behavior of the flow in rod bundles has motivated numerous experimental and computational investigations. Previous studies have identified potential for accumulation of debris within the small subchannels of typical wire-wrapped assemblies with subsequent total or partial blockage of subchannel coolant flow. A test campaign was conducted to study the effects of localized blockages on the bundle averaged friction factor of a tightly packed wire-wrapped rod bundle. Blockages were installed within the bundle, and fluid pressure drop was measured across one wire pitch for a Reynolds number range of 500–17,200. The Darcy–Weisbach friction factor of the perturbed rod bundle geometry was compared with that of the unblocked bundle, as well as with the predictions of a well-established friction factor correlation. Differing effects based on blockage size and location for various flow regimes were studied. A number of conclusions can be made about the effects of the blockages on the friction factor, such as an increasing effect of the blockage on friction factor with an increase in Reynolds number, a change in flow behavior in the turbulent transition flow regime near Reynolds number 3000, differences in effect on friction factor for different types of subchannel blockage, and a nonlinear trend in friction factor variation with flow area impeded for edge subchannels. To this end, all data and quantified uncertainty produced in this study are made available for comparison and validation of advanced computational tools.

Engineering↗

DOE OSTI2023

Virulence factors and antimicrobial resistance profiles of Campylobacter isolates recovered from consecutively reused broiler litter

ABSTRACT Campylobacterinfections are a leading cause of bacterial diarrhea in humans globally. Infections are due to consumption of contaminated food products and are highly associated with chicken meat, with chickens being an important reservoir forCampylobacter. Here, we characterized the genetic diversity ofCampylobacter jejuni(C. jejuni) andCampylobacter coli(C. coli) detected in broiler chicken litter over three consecutive flocks and determined their antimicrobial resistance (ARM) and virulence factor (VF) profiles.Campylobacterwas detected in 9.38% (27/288) of litter samples collected. Antimicrobial susceptibility testing and whole genome sequencing were performed onC. jejuni(n= 39) andC. coli(n= 5) isolates.Campylobactervirulence factors differed within and across broiler houses but were explained by the broiler flock cohort raised on litter,Campylobacterspecies andCampylobactermultilocus sequence type (MLST). Virulence factors involved in the ability to invade and colonize host tissues and evade host defenses were present inC. jejuniisolates (ST-464) from flock cohorts 1 and 2 but absent inC. jejuniisolates (ST-48) from flock cohort 3.C. jejuniisolates from house three harbored a significantly higher proportion of virulence genes with functions related to glycosylation and immune evasion thanC. jejuniisolates from houses 1 and 2 (P< 0.01). AllC. jejuniisolates were susceptible to all antibiotics tested whileC. coli(n= 4) were resistant to tetracycline and harbored the tetracycline resistant ribosomal protection protein (TetO). Our results suggest that house environment and broiler management practices imposed selective pressures on virulence factors and antimicrobial resistance genes ofCampylobacter. IMPORTANCE Campylobacteris a leading cause of foodborne illness in the United States due to consumption of contaminated or mishandled food products, often associated with chicken meat.Campylobacteris common in the microbiota of avian and mammalian gut; however, acquisition of antimicrobial resistance genes (ARGs) and virulence factors (VFs) may result in strains that pose significant threat to public health. Although there are studies investigating the genetic diversity ofCampylobacterstrains isolated from post-harvest chicken samples, there are limited data on the genome characteristics of isolates recovered from preharvest broiler production. Here, we show thatCampylobacter jejuniandCampylobacter colidiffer in their carriage of antimicrobial resistance and virulence factors may also differ in their ability to persist in litter during consecutive grow-out of broiler flocks. We found that presence/absence of virulence factors needed for evasion of host defense mechanisms and gut colonization played an integral role in differentiatingCampylobacterstrains.

Microbiology↗

DOE OSTI2023

NREM sleep as a novel protective cognitive reserve factor in the face of Alzheimer's disease pathology

Alzheimer’s disease (AD) pathology impairs cognitive function. Yet some individuals with high amounts of AD pathology suffer marked memory impairment, while others with the same degree of pathology burden show little impairment. Why is this? One proposed explanation is cognitive reserve i.e., factors that confer resilience against, or compensation for the effects of AD pathology. Deep NREM slow wave sleep (SWS) is recognized to enhance functions of learning and memory in healthy older adults. However, that the quality of NREM SWS (NREM slow wave activity, SWA) represents a novel cognitive reserve factor in older adults with AD pathology, thereby providing compensation against memory dysfunction otherwise caused by high AD pathology burden, remains unknown. Here, we tested this hypothesis in cognitively normal older adults (N = 62) by combining 11 C-PiB (Pittsburgh compound B) positron emission tomography (PET) scanning for the quantification of β-amyloid (Aβ) with sleep electroencephalography (EEG) recordings to quantify NREM SWA and a hippocampal-dependent face-name learning task. We demonstrated that NREM SWA significantly moderates the effect of Aβ status on memory function. Specifically, NREM SWA selectively supported superior memory function in individuals suffering high Aβ burden, i.e., those most in need of cognitive reserve (B = 2.694, p = 0.019). In contrast, those without significant Aβ pathological burden, and thus without the same need for cognitive reserve, did not similarly benefit from the presence of NREM SWA (B = -0.115, p = 0.876). This interaction between NREM SWA and Aβ status predicting memory function was significant after correcting for age, sex, Body Mass Index, gray matter atrophy, and previously identified cognitive reserve factors, such as education and physical activity (p = 0.042). These findings indicate that NREM SWA is a novel cognitive reserve factor providing resilience against the memory impairment otherwise caused by high AD pathology burden. Furthermore, this cognitive reserve function of NREM SWA remained significant when accounting both for covariates, and factors previously linked to resilience, suggesting that sleep might be an independent cognitive reserve resource. Beyond such mechanistic insights are potential therapeutic implications. Unlike many other cognitive reserve factors (e.g., years of education, prior job complexity), sleep is a modifiable factor. As such, it represents an intervention possibility that may aid the preservation of cognitive function in the face of AD pathology, both present moment and longitudinally.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Weak Dispersion of Exciton Landé Factor with Band Gap Energy in Lead Halide Perovskites: Approximate Compensation of the Electron and Hole Dependences

The optical properties of lead halide perovskite semiconductors in vicinity of the bandgap are controlled by excitons, so that investigation of their fundamental properties is of critical importance. The exciton Landé or g-factor g X is the key parameter, determining the exciton Zeeman spin splitting in magnetic fields. The exciton, electron, and hole carrier g-factors provide information on the band structure, including its anisotropy, and the parameters contributing to the electron and hole effective masses. Here, g X is measured by reflectivity in magnetic fields up to 60 T for lead halide perovskite crystals. The materials band gap energies at a liquid helium temperature vary widely across the visible spectral range from 1.520 up to 3.213 eV in hybrid organic–inorganic and fully inorganic perovskites with different cations and halogens: FA 0.9 Cs 0.1 PbI 2.8 Br 0.2 , MAPbI 3 , FAPbBr 3 , CsPbBr 3 , and MAPb(Br 0.05 Cl 0.95 ) 3 . The exciton g-factors are found to be nearly constant, ranging from +2.3 to +2.7. Thus, the strong dependences of the electron and hole g-factors on the bandgap roughly compensate each other when combining to the exciton g-factor. The same is true for the anisotropies of the carrier g-factors, resulting in a nearly isotropic exciton g-factor. The experimental data are compared favorably with model calculation results.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗

DOE OSTI2025

Factorized QED Contribution to Lepton-Hadron DIS

We present the first calculation of next-to-leading order (NLO) factorized QED contributions to the short-distance hard coefficients of inclusive lepton-hadron deep inelastic scattering (DIS) in a joint QCD and QED factorization approach. We demonstrate how the joint factorization consistently factorize all perturbative collinear sensitivities of partonic scattering in both QCD and QED into corresponding universal hadron and lepton distribution functions without the need of any parameters other than the standard factorization scale. We discuss the necessary modification to DGLAP-type evolution of the parton and lepton distribution functions in this joint factorization approach. We also discuss the potential impact of this joint factorization approach on the extraction of partonic information from lepton-hadron DIS.

Qiu, Jianwei↗

DOE OSTI2024

Factorized visual representations in the primate visual system and deep neural networks

Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many different types of information, and optimizing for classification of object identity alone does not constrain how other information may be encoded in visual representations. Information about different scene parameters may be discarded altogether (‘invariance’), represented in non-interfering subspaces of population activity (‘factorization’) or encoded in an entangled fashion. In this work, we provide evidence that factorization is a normative principle of biological visual representations. In the monkey ventral visual hierarchy, we found that factorization of object pose and background information from object identity increased in higher-level regions and strongly contributed to improving object identity decoding performance. We then conducted a large-scale analysis of factorization of individual scene parameters – lighting, background, camera viewpoint, and object pose – in a diverse library of DNN models of the visual system. Models which best matched neural, fMRI, and behavioral data from both monkeys and humans across 12 datasets tended to be those which factorized scene parameters most strongly. Notably, invariance to these parameters was not as consistently associated with matches to neural and behavioral data, suggesting that maintaining non-class information in factorized activity subspaces is often preferred to dropping it altogether. Thus, we propose that factorization of visual scene information is a widely used strategy in brains and DNN models thereof.

59 BASIC BIOLOGICAL SCIENCES↗