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At least 289 records · Page 16

Dynamic load balancing with enhanced shared-memory parallelism for particle-in-cell codes

Furthering our understanding of many of today’s interesting problems in plasma physics – including plasma based acceleration and magnetic reconnection with pair production due to quantum electrodynamic effects – requires large-scale kinetic simulations using particle-in-cell (PIC) codes. However, these simulations are extremely demanding, requiring that contemporary PIC codes be designed to efficiently use a new fleet of exascale computing architectures. To this end, the key issue of parallel load balance across computational nodes must be addressed. We discuss the implementation of dynamic load balancing by dividing the simulation space into many small, self-contained regions or ‘‘tiles,’’ along with shared-memory (e.g., OpenMP) parallelism both over many tiles and within single tiles. The load balancing algorithm can be used with three different topologies, including two space-filling curves. Here, we tested this implementation in the code Osiris and show low overhead and improved scalability with OpenMP thread number on simulations with both uniform load and severe load imbalance. Compared to other load-balancing techniques, our algorithm gives order-of-magnitude improvement in parallel scalability for simulations with severe load imbalance issues.

97 MATHEMATICS AND COMPUTING↗

Produced water sharing: Improved economics and reduced community impact – A Pennsylvania case study

Here, hydraulic fracturing for oil and gas extraction from unconventional reservoirs is water intensive. Between water sourced for fracturing purposes and water present in rock formations, operators often produce a greater volume of water than oil or gas. Historically, this surplus of produced water has mainly been disposed of via deep injection wells. Rising disposal costs, seasonally limited water availability, and concerns over induced seismicity have incentivized produced water recycling practices, where an operator uses produced water for hydraulic fracturing operations. The logistical challenges associated with produced water recycling have also encouraged operators to adopt ad-hoc water exchange practices, in which competing operators will exchange produced water for mutual cost savings. In this paper, we investigate the potential benefit from systematic produced water exchange among operators in Northeastern Pennsylvania. We leverage PARETO, a free and open-source modeling framework for produced water management optimization, to quantify the benefits of water exchange practices. In an example drawn from FracFocus data, we find that the adoption of systematic water sharing could improve produced water recycling rates from 49.2% to 99%, decreasing operating and trucking costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Extending the Shared Socioeconomic Pathways for sub-national impacts, adaptation, and vulnerability studies

The exploration of alternative socioeconomic futures is an important aspect of understanding the potential consequences of climate change. While socioeconomic scenarios are common and, at times essential, tools for the impact, adaptation and vulnerability and integrated assessment modeling research communities, their approaches to scenario development have historically been quite distinct. However, increasing convergence of impact, adaptation and vulnerability and integrated assessment modeling research in terms of scales of analysis suggests there may be value in the development of a common framework for socioeconomic scenarios. The Shared Socioeconomic Pathways represents an opportunity for the development of such a common framework. However, the scales at which these global storylines have been developed are largely incommensurate with the sub-national scales at which impact, adaptation and vulnerability, and increasingly integrated assessment modeling, studies are conducted. Our objective for this study was to develop sub-national and sectoral extensions of the global SSP storylines in order to identify future socioeconomic challenges for adaptation for the U.S. Southeast. A set of nested qualitative socioeconomic storyline elements, integrated storylines, and accompanying quantitative indicators were developed through an application of the Factor-Actor-Sector framework. Finally, in addition to revealing challenges and opportunities associated with the use of the SSPs as a basis for more refined scenario development, this study generated sub-national storyline elements and storylines that can subsequently be used to explore the implications of alternative subnational socioeconomic futures for the assessment of climate change impacts and adaptation.

54 ENVIRONMENTAL SCIENCES↗

Future air pollution in the Shared Socio-economic Pathways

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high, central, and low pollution control ambitions over the 21 st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. We provide an overview of pollutant emission trajectories under the SSP scenarios. Pollutant emissions in these scenarios cover a wider range than the scenarios used in previous international climate model comparisons. Furthermore, the SSP scenarios provide the opportunity to access a more comprehensive range of future global and regional air quality outcomes.

54 ENVIRONMENTAL SCIENCES↗

The Shared Socio-economic Pathways: Trajectories for human development and global environmental change

This Special Issue presents the Shared Socio-economic Pathways (SSPs), a set of 5 storylines on possible trajectories for human development and global environmental change during the 21st century. The information presented in the Special Issue has been developed over the last few years as a joint community effort and includes both qualitative narratives and results of quantitative model analysis. The SSPs form part of a larger set of community scenarios for analysis of climate change. Such community scenarios form a key tool for analysis of analysis of global environmental change and sustainable development problems. They allow exploration of different futures with and without response strategies. They also form a key tool to link across different disciplines and scales. They allow the same scenarios to be used in research on driving forces of climate change, the physical climate system, climate impacts and adaptation and mitigation strategies. Such scenarios can also link research across different research areas (e.g. climate change and biodiversity analysis) or be used across different scales (global, regional and local scales). Finally, they also have a key function as a consistent data source (population projections, climate projections and insights into land and energy development, for instance).

Van Vuuren, Detlef↗

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Message Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.

dynamic simulation↗

Structural basis for inhibition of coagulation factor VIII reveals a shared antigenic hotspot on the C1 domain

Hemophilia A arises from dysfunctional or deficient coagulation factor (F)VIII and leads to inefficient fibrin clot formation and uncontrolled bleeding events. The development of antibody inhibitors is a clinical complication in hemophilia A patients receiving FVIII replacement therapy. LE2E9 is an anti-C1 domain inhibitor previously isolated from a mild/moderate hemophilia A patient and disrupts FVIII interactions with von Willebrand factor and FIXa, though the intermolecular contacts that underpin LE2E9-mediated FVIII neutralization are undefined. To determine the structure of the complex between FVIII and LE2E9 and characterize its mechanism of inhibition. FVIII was bound to the antigen binding fragment (Fab) of NB2E9, a recombinant construct of LE2E9, and its structure was determined by cryogenic electron microscopy. Here, this report communicates the 3.46 Å structure of FVIII bound to NB2E9, with its epitope comprising FVIII residues S2040 to Y2043, K2065 to W2070, and R2150 to H2155. Structural analysis reveals that the LE2E9 epitope overlaps with portions of the epitope for 2A9, a murine-derived inhibitor, suggesting that these residues represent a shared antigenic region on the C1 domain between FVIII –/– mice and hemophilia A patients. Furthermore, the FVIII:NB2E9 structure elucidates the orientation of the LE2E9 glycan, illustrating how the glycan sterically blocks interactions between the FVIII C1 domain and the von Willebrand factor D' domain. A putative model of the FVIIIa:FIXa complex suggests potential clashing between the NB2E9 glycan and FIXa light chain. These results describe an antigenic “hotspot” on the FVIII C1 domain and provide a structural basis for engineering FVIII replacement therapeutics with reduced antigenicity.

60 APPLIED LIFE SCIENCES↗

Structure of an E3:E2~Ub Complex Reveals an Allosteric Mechanism Shared among RING/U-box Ligases

Despite the widespread importance of RING/U-box E3 ubiquitin ligases in ubiquitin (Ub) signaling, the mechanismby which this class of enzymes facilitates Ub transfer remains enigmatic. Here, we present a structural model for a RING/U-box E3:E2~Ub complex poised for Ub transfer. The model and additional analyses reveal that E3 binding biases dynamic E2~Ub ensembles toward closed conformations with enhanced reactivity for substrate lysines. We identify a key hydrogen bond between a highly conserved E3 side chain and an E2 backbone carbonyl, observed in all structures of active RING/ U-Box E3/E2 pairs, as the linchpin for allosteric activation of E2~Ub. The conformational biasing mechanism is generalizable across diverse E2s and RING/U-box E3s, but is not shared by HECT-type E3s. The results provide a structural model for a RING/ U-box E3:E2~Ub ligase complex and identify the long sought-after source of allostery for RING/UBox activation of E2~Ub conjugates.

Environmental Molecular Sciences Laboratory↗

A GEM readout with radial zigzag strips and linear charge-sharing response

Here, we study the position sensitivity of radial zigzag strips intended to read out large GEM detectors for tracking at future experiments. Zigzag strips can cover a readout area with fewer strips than regular straight strips while maintaining good spatial resolution. Consequently, they can reduce the number of required electronic channels and related cost for large-area GEM detector systems. A non-linear relation between incident particle position and hit position measured from charge sharing among zigzag strips was observed in a previous study. We significantly reduce this non-linearity by improving the interleaving of adjacent physical zigzag strips. Zigzag readout structures are implemented on PCBs and on a flexible foil and are tested using a 10 cm × 10 cm triple-GEM detector scanned with a strongly collimated X-ray gun on a 2D motorized stage. Lastly, angular resolutions of 60–84 μrad are achieved with a 1.37 mrad angular strip pitch at a radius of 784 mm. On a linear scale this corresponds to resolutions below 100 μm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A quantitative model of application slow-down in multi-resource shared systems

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job is characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.

97 MATHEMATICS AND COMPUTING↗

Optimal assignment for the single-household shared autonomous vehicle problem

Autonomous vehicles have the potential to transform the way people are transported. While driverless technology may mean fewer vehicles are required to transport people to and from their daily activities, such changes may result in increased congestion or total miles traveled. In this study, we solve the single-household shared autonomous vehicle problem to identify cost-optimal routings of vehicles throughout the day. Such a tool will be useful for consumers seeking to minimize cost and for regulators seeking to understand and predict how people may behave in different scenarios. Here, we provide a thorough literature review and construct a mixed-integer linear program to minimize the daily travel cost of a household attending a given set of activities. Since solution time is a determinant for applicability of such a model, we present the model in a component-wise fashion. This approach allows us to understand which features most affect the problem complexity and solution time. We note that modeling carpooling is the feature that most increases time to find an optimal solution, and we therefore propose a novel modeling technique for carpooling two people. We illustrate the performance of our model by comparing it with other models from the literature and note that our model can solve significantly larger problem instances and in a time that is short enough to facilitate real-time scheduling. We also highlight the utility of our model for regulators, who can use it to analyze quickly produced optimal routes under different cost/tax scenarios.

33 ADVANCED PROPULSION SYSTEMS↗

Joint Optimization of Multimodal Transit Frequency and Shared Autonomous Vehicle Fleet Size with Hybrid Metaheuristic and Nonlinear Programming

Shared autonomous vehicles (SAVs) bring competition to traditional transit services but redesigning multimodal transit network can utilize SAVs as feeders to enhance service efficiency and coverage. This paper presents an optimization framework for the joint multimodal transit frequency and SAV fleet size problem, a variant of the transit network frequency setting problem. The objective is to maximize total transit ridership (including SAV-fed trips and subtracting boarding rejections) across multiple time periods under budget constraints, considering endogenous mode choice (transit, point-to-point SAVs, driving) and route selection, while allowing for strategic route removal by setting frequencies to zero. Due to the problem’s non-linear, non-convex nature and the computational challenges of large-scale networks, we develop a hybrid solution approach that combines a metaheuristic approach (particle swarm optimization) with nonlinear programming for local solution refinement. To ensure computational tractability, the framework integrates analytical approximation models for SAV waiting times based on fleet utilization, multimodal network assignment for route choice, and multinomial logit mode choice behavior, bypassing the need for computationally intensive simulations within the main optimization loop. Applied to the Chicago metropolitan area’s multimodal network, our method illustrates a 33.3% increase in transit ridership through optimized transit route frequencies and SAV integration, particularly enhancing off-peak service accessibility and strategically reallocating resources.

Ng, Max↗

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↗

Environmental Contributions to Proton Sharing in Protein Low-Barrier Hydrogen Bonds

Hydrogen bonds (H-bonds) are central to biomolecular structure and dynamics. Although H-bonds are typically characterized by well-defined proton positions, proton delocalization has been proposed to play a role in facilitating enzyme catalysis and allostery in some systems. Experimentally locating protons is difficult, hampering the study of proton mobility in H-bonds. We used neutron crystallography, atomic resolution X-ray bond length analysis, and large quantum mechanics/molecular mechanics-Born–Oppenheimer molecular dynamics (QM/MM-BOMD) simulations to comprehensively characterize the shared proton/deuteron in a Glu–Asp low-barrier hydrogen bond (LBHB) in the bacterial protein YajL that is a conventional H-bond in the homologous disease-associated human protein DJ-1. X-ray bond length analysis of protiated and perdeuterated DJ-1 and YajL shows no significant effect of deuteron substitution on these carboxylic acid-carboxylate H-bonds but does reveal an effect at the active site glutamic acid near a cysteine thiolate. Residues in an H-bonded network that might favor LBHB formation in YajL were interrogated by the mutation of homologous residues in DJ-1. A distal DJ-1 substitution increases proton delocalization in the Glu–Asp H-bond, demonstrating that mutations within extended H-bond networks can modulate proton transfer barriers in carboxylic acid-carboxylate H-bonds. In addition, proton mobility in the H-bond is correlated with dimer-spanning motions in the QM/MM-BOMD simulations of YajL and DJ-1. Our results show that proton delocalization can be tuned using combined bioinformatic, structural, and computational information, opening the possibility of using engineered proton delocalization as a probe of H-bonding environments and as a tool to test hypotheses about LBHB function.

Lin, Jiusheng [University of Nebraska, Lincoln, NE↗

LiMo 8 O 10 : Polar Crystal Structure with Infinite Edge-Sharing Molybdenum Octahedra

Here, polycrystalline LiMo 8 O 10 was prepared in a sealed Mo crucible at 1380 °C for 48 h using the conventional high-temperature solid-state method. The polar tetragonal crystal structure (space group I4 1 md) is confirmed based on the Rietveld refinement of powder neutron diffraction and 7 Li/ 6 Li solid-state NMR. The crystal structure features infinite chains of Mo 4 O 5 (i.e., Mo 2 Mo 4/2 O 6/2 O 6/3 ) as a repeat unit containing edge-sharing Mo 6 octahedra with strong Mo–Mo metal bonding along the chain. X-ray absorption near-edge spectroscopy of the Mo-L 3 edge is consistent with the formal Mo valence/configuration. Magnetic measurements reveal that LiMo 8 O 10 is paramagnetic down to 1.8 K. Temperature-dependent resistivity [ρ(T)] measurement indicates a semiconducting behavior that can be fitted with Mott’s variable range hopping conduction mechanism in the temperature range of 215 and 45 K. The ρ(T) curve exhibits an exponential increase below 5 K with a large ratio of ρ 1.8 /ρ 300 = 435. LiMo 8 O 10 shows a negative field-dependent magnetoresistance between 2 and 25 K. Heat capacity measurement fitted with the modified Debye model yields the Debye temperature of 365 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing

Ocean metaproteomics is an emerging field enabling discoveries about marine microbial communities and their impact on global biogeochemical processes. Recent ocean metaproteomic studies have provided insight into microbial nutrient transport, colimitation of carbon fixation, the metabolism of microbial biofilms, and dynamics of carbon flux in marine ecosystems. Future methodological developments could provide new capabilities such as characterizing long-term ecosystem changes, biogeochemical reaction rates, and in situ stoichiometries. Yet challenges remain for ocean metaproteomics due to the great biological diversity that produces highly complex mass spectra, as well as the difficulty in obtaining and working with environmental samples. This review summarizes the progress and challenges facing ocean metaproteomic scientists and proposes best practices for data sharing of ocean metaproteomic data sets, including the data types and metadata needed to enable intercomparisons of protein distributions and annotations that could foster global ocean metaproteomic capabilities.

54 ENVIRONMENTAL SCIENCES↗

Task Sharing of Proton Incorporation in Vertically Aligned Nanocomposite Triple Conductors: Growth, Structure, and Surface Exchange Kinetics

As protonic ceramic electrolysis cells emerge for efficient H 2 production, there is a need to develop air electrode materials enabling fast, durable steam splitting and proton incorporation. Single-phase triple conductors may fail to satisfy the myriad performance/stability requirements, and their critical charge-carriers (holes, oxygen vacancies, and protons) are in competition, limiting their concentrations. Instead, we propose task-sharing, vertically aligned nanocomposites (VANs), comprising a proton conductor (BaZr 0.9 Y 0.1 O 3-δ ) and a redox-active mixed ionic electronic conductor (Ce 0.9 Pr 0.1 O 2-δ ), that may enable rapid proton surface exchange at the solid–gas interface and transport along the solid–solid heterointerfaces. We grew VANs by pulsed laser deposition and investigated the interplay between their processing conditions, structure, and proton and oxygen surface exchange kinetics. We varied the substrate temperature, laser repetition rate, laser fluence, and processing oxygen pressure. The crystallinity and phases were characterized by grazing-incidence X-ray diffraction, and the strain and structural order as a function of depth were evaluated by angle-dependent synchrotron X-ray pair distribution function analysis. To evaluate the potential for interdiffusion, the formation energies of substitutional defects were simulated with density functional theory. Corresponding structural analysis and elemental mapping were performed by scanning/transmission electron microscopy, energy-dispersive X-ray spectroscopy, and electron energy-loss spectroscopy, indicating distinct nanoscale compositional regions with a hierarchical structure embedded in individual VANs columns and minimal interdiffusion across a bilayer film. Proton and oxygen surface exchange coefficients (k H , k O ) and polarization resistances were evaluated by electrical and optical relaxations and impedance spectroscopy of VAN-incorporated protonic ceramic electrochemical cells, respectively, at 400–500 °C, demonstrating values comparable to some of the best-known triple and mixed conductors.

36 MATERIALS SCIENCE↗