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At least 109 records · Page 6

Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

genome-wide association study↗

S-QGPU: Shared quantum gate processing unit for distributed quantum computing

We propose a distributed quantum computing (DQC) architecture in which individual small-sized quantum computers are connected to a shared quantum gate processing unit (S-QGPU). The S-QGPU comprises a collection of hybrid two-qubit gate modules for remote gate operations. In contrast to conventional DQC systems, where each quantum computer is equipped with dedicated communication qubits, S-QGPU effectively pools the resources (e.g., the communication qubits) together for remote gate operations, and, thus, significantly reduces the cost of not only the local quantum computers but also the overall distributed system. Our preliminary analysis and simulation show that S-QGPU's shared resources for remote gate operations enable efficient resource utilization. When not all computing qubits (also called data qubits) in the system require simultaneous remote gate operations, S-QGPU-based DQC architecture demands fewer communication qubits, further decreasing the overall cost. Alternatively, with the same number of communication qubits, it can support a larger number of simultaneous remote gate operations more efficiently, especially when these operations occur in a burst mode.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fault Diagnosis of Double Pitch Time-Sharing Meshing Toothed Conveyor Chain Transmission System Based on Neural Network

With the rapid development of industry, the production and demand of automobiles have increased significantly. The generation of cars often requires tens of thousands of processes, consisting of hundreds of assembly lines to complete. Chain conveyors are widely used in the transportation of automobile assembly lines. The existing conveyor chains are roller chains. With the improvement of the requirements for conveyor reliability, synchronization, and environmental friendliness, the characteristics of roller conveyor chains restrict the further development of chain conveyors. It is urgent to study a new conveyor chain system to improve the synchronization, reliability, and environmental friendliness of chain conveyors on hundreds of assembly lines. In this paper, the mathematical modeling, meshing analysis, reliability, and environmental friendliness of the parameters of the components of the double pitch time-sharing meshing toothed conveyor chain system are studied. In addition, a novel fault diagnosis method of double pitch time-sharing meshing toothed conveyor chain transmission system based on neural network model is proposed in this paper.

Ding, Song↗

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Hunter, Christian B.↗

Integration of Electric Power Infrastructure into the Drinking Water Shared Risk Framework: Prototype Development

An existing shared risk framework designed for assessing and comparing threat-based risks to water utilities is being extended to incorporate electric power. An important differentiating characteristic of this framework is the use of a system-centric rather than an asset-centric approach. This approach allows anonymous sharing of results and enables comparison of assessments across different utilities within an infrastructure sector. By allowing utility owners to compare their assessments with others, they can improve their self-assessments and identification of "unknown unknowns". This document provides an approach for extension of the framework to electric power, including treatment of dependencies and interdependencies. The systems, threats, and mathematical description of associated risks used in a prototype framework are provided. The method is extensible so that additional infrastructure sectors can be incorporated. Preliminary results for a proof of concept calculation are provided.

42 ENGINEERING↗

Sharing the Sun: Community Solar Deployment and Subscriptions (as of June 2023) [Slides]

This presentation describes the community solar market as of the first half (H1) of 2023. The community solar market analysis presented here is based primarily on data collected through Sharing the Sun, an initiative of the National Community Solar Partnership (NCSP). Sharing the Sun data collection and analysis is conducted by the National Renewable Energy Laboratory (NREL) as part of its support for implementation of the NCSP.

14 SOLAR ENERGY↗

MAPSTER: Automated Geospatial Data Sharing – Version 1.4.0

The US Department of Energy’s (DOE) Oak Ridge National Laboratory (ORNL) developed MAPSTER which is a geospatial data management tool that aggregates, organizes, and shares data from dispersed sources such as unmanned aerial systems (UAS). Built specifically for use in environments where communications may be limited, MAPSTER utilizes two key technologies to effectively manage data in the field and enable easy data sharing with authorized partners: Observer and Checkpoint. Observer is a lightweight software package on an edge device, such as a laptop, that automatically detects newly processed UAS data and sends to a central server called Checkpoint. Checkpoint is a centralized server at ORNL that receives and manages data from all Observer instances. Even in a very low bandwidth environment, Observer can still send information about the UAS data product almost instantly as it generates its own metadata package on the size of KB (kilobytes). MAPSTER is not only for UAS data but for any geospatial data collected at the austere edge and dispersed sources.

97 MATHEMATICS AND COMPUTING↗

Inclusive Shared Solar Initiative (ISSI) (Final Technical Report)

Between 2020 and 2024, the Inclusive Shared Solar Initiative (ISSI) served as a forum for three states to navigate the design and development of LMI-accessible community solar projects. A collaboration between the National Association of State Energy Officials (NASEO) and National Energy Assistance Directors Association (NEADA), ISSI provided financial and technical assistance to teams of State Energy Offices and State LIHEAP Agencies in Minnesota, Wisconsin, and the District of Columbia. The key goals guiding ISSI were to develop four new community solar frameworks in three new states and create greater momentum among state governments, community solar developers, and the finance community in scaling and investing in community solar projects that are affordable and accessible to LIHEAP households. Ultimately, in addition to developing and launching four new shared solar projects serving LMI subscribers, the ISSI state partners pioneered community solar policy and program design strategies that increased protections for low-income consumers, reduced barriers to enrollment and project development, and fostered inter-program coordination.

14 SOLAR ENERGY↗

Benefit Analysis of Long-Duration Energy Storage in Power Systems with High Renewable Energy Shares

The integration of high shares of variable renewable energy raises challenges for the reliability and cost-effectiveness of power systems. The value of long-duration energy storage, which helps address variability in renewable energy supply across days and seasons, is poised to grow significantly as power systems shift to larger shares of variable generation such as wind and solar. This study explores the system-level services and associated benefits of long-duration energy storage on the 2050 Western Interconnection (WI). The operation of the future WI system with 85% renewable penetration is simulated using a two-stage production cost model. The impact of long duration energy storage on systemwide operations is examined for the 2050 WI system, using a range of round-trip efficiencies corresponding to four different energy storage technologies. The analysis projects the energy storage dispatch profile, system-wide production cost savings (from both diurnal and seasonal operation), and impacts on generation mix, and change in renewable generation curtailment.

25 ENERGY STORAGE↗

The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO 2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO 2 emissions. By 2150, CO 2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO 2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO 2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66% for the present day to roughly 68% to 85% by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (~5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5°C warming on the other.

54 ENVIRONMENTAL SCIENCES↗

Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways"

Datasets supporting findings and visualizations behind McManamay et al. (2024) Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways. Environmental Research Letters, DOI: 10.1088/1748-9326/ad2eec Using a spatial modeling experiment at high resolution (1-km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The numerical experiment, inputs and outputs are fully described in McManamay et al. (2024). The datasets summarize SELECT model simulations within urban areas and rural areas of the conterminous United States. For code to reproduce the results, please refer to https://github.com/IMMM-SFA/mcmanamay_etal_2024_erl Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions: Urban_Land_delta_UA_County.csv: Urban land area for original (default) population, updated population, and urban land delta (difference between the two) according to Shared Socioeconomic Pathways (SSPs) and year. Urban land is summarized for U.S. counties (FIPS code) and urban areas (GEOID) as unique areas within various counties. JO_Gao_pop_ufdelta.csv: Comparison of population differences and urban land differences between the origial (default) and updated population projections. City_Case_studies.csv: Differences in urban land areas arising from different population projections summarized for selected cities (Atlanta, Los Angeles, Houston, and New York) and their surrounding rural areas UA_county_FID.zip: Zipped folder of .tiff file depicting unique combination of urban areas and US counties used for summarizing urban land differences in urban and rural areas based on different population projections. ULD_clusters.zip: Zipped folder of .csv files depicting normalized changes in urban land delta (difference in urban land arising from population projections) and the respective Ward's hierarchical clusters, which group urban and rural areas based on similarities in temporal trends. Urban_Percent_change_2100.zip: Zipped folder of .csv files depicting percent changes in urban land area for year 2100 based on differences in the original (default) population and updated population. Each file is for SSPs and urban or rural areas.

Land↗

Extending Shared Socioeconomic Pathways to Future Water Supply In-frastructure Scenarios: A Case Study of San Antonio, TX

Datasets supporting findings and visualization behind Okoye and McManamay (2025) Extending Shared Socioeconomic Pathways to Future Water Supply Infrastructure Scenarios: A Case Study of San Antonio, TX. Environmental Research Communications, DOI: 10.57931/2563186 These datasets contains the results of a site selection analysis for municipal water supply planning across multiple Shared Socioeconomic Pathways (SSPs 1–5) and hard scenario classification of water systems in San Antonio, TX. It includes data at the resolution of individual surface water supply sources (COMIDs) and integrates a wide range of hydrologic, socioeconomic, infrastructural, and scenario-based planning variables. Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions: Dataset_SSP1_SSP4.xlsx - Contains data used for site selection optimization under SSP1 to SSP4. This dataset was generated based on multi-indicator computations (e.g., WAI, WQI, ERI, WTC, WIC), scenario demand projections, and resource and spatial constraints, excluding new reservoir values. Dataset_SSP5.xlsx - Used for site optimization under SSP5. Unlike Dataset_SSP1_SSP4, this dataset includes new reservoir features with updated calculations of WAI, WTC, and WIC to reflect the added infrastructure and supply potential. hard_classification.xlsx - Provides the scenario classification output for each site. Includes both the initial scenario classification based on Euclidean Distance and adjusted classifications based on 30% change reduction BAU.zip - Zipped folder of .shp files showing spatially optimized water supply sites per SSP under the Business-As-Usual (BAU) water demand strategy LowGW.zip - Zipped folder of .shp files showing optimized site selections under the Low Groundwater strategy

geospatial↗

Livewire Data Platform - A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

The Livewire Data Platform is a data storage and exchange platform. It provides: a platform, allowing data sharing and discovery by linking disparate data sources to a single website via application programming interfaces (APIs); a community, building partnerships and collaboration rather than competition; a system, allowing shared data to increase in size and complexity as EEMS evolves.

47 OTHER INSTRUMENTATION↗

IS BLOCKCHAIN A SUITABLE TECHNOLOGY FOR ENSURING THE INTEGRITY OF DATA SHARED BY LIGHTING AND OTHER BUILDING SYSTEMS?

Increasing amounts of data are available from lighting and other building systems. In commercial buildings, these data can be used to improve system and energy performance, detect and diagnose faults, and facilitate maintenance. Building data are not only of interest to owners and operators of the building systems, however. Owners and operators of similar buildings, manufacturers of building systems, utilities, and city agencies also have interesting use cases. Energy data can, for example, be used to verify the performance of energy-conservation measures, issue renewableenergy certificates, and financially settle grid services. Increased data sharing, however, significantly expands the cyber-attack surface, creating new challenges. In this work, blockchain is explored as an option for ensuring the integrity of data that are shared by lighting and other building systems. Blockchain fundamentals and variants are briefly reviewed, and value propositions relevant to building systems are discussed. A recently developed blockchain applicability framework (BAF) that builds upon and addresses the limitations of previous applicability models is also briefly reviewed. The BAF is used to assess the suitability of blockchain over other technologies or approaches for building-data applications, using emerging connected lighting systems as an example use case.

blockchain, connected lighting system, data integr↗

Overview of the 2021 SDP 3C Citation Context Classification Shared Task

This paper provides an overview of the 2021 3C Citation Context Classification shared task. The second edition of the shared task was organised as part of the 2nd Workshop on Scholarly Document Processing (SDP 2021). The task is composed of two subtasks: classifying citations based on their (Subtask A) purpose and (Subtask B) influence. As in the previous year, both tasks were hosted on Kaggle and used a portion of the new ACT dataset. A total of 22 teams participated in Subtask A, and 19 teams competed in Subtask B. All the participated systems were ranked based on their achieved macro f-score. The highest scores of 0.26973 and 0.60025 were reported for sub-task A and B, respectively.

Kunnath, Suchetha N.↗

Push-pull circuit with driving assisted by asymmetric charge sharing

A push-pull circuit for an opto-electronic device includes: an output node; a pull-up circuit that, in operation, controls a falling edge rate of an input signal to the opto-electronic device while sharing charge with the output node; and a pull-down circuit that, in operation, controls a rising edge rate of the input signal to the opto-electronic device while sharing charge with the output node.

Zhu, Zhubiao↗

Power Grid Planning with Higher Renewable Share

Power grid planning with a higher renewable share got worldwide attention since the declining cost of renewable energy technologies and greenhouse gas reduction goals continue to drive a transition to a cleaner power grid. Energy professionals from developing countries working to achieve renewable power goals want to learn about NREL's state-of-the-art research efforts in renewable power and power grid planning. Supporting these efforts, the United States Energy Association, Female Leaders in Energy initiative facilitates mid-career female energy professionals from South East Asia to learn from energy professionals from the USA. This presentation gives an overview of NREL scientific research studies on power grid planning with a high renewable share to mid-career female energy professionals.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

Panel Session 3: Prospects for Shared Solutions for Solving the WM Challenges for Small and Emerging Nuclear Countries

This panel focused on sharing WM solutions for small and emerging nuclear countries. As countries with substantial inventories of spent nuclear fuel pursue their national repository programs with varying degrees of progress, countries with only a few reactors and those at the beginning stages of their nuclear programs face a far different and substantial challenge toward developing a national solution. This session brought together a panel of experts from government and industry to explore shared solutions and next steps building off the recent progress made by international organizations and the recent efforts and lessons learned. Panelists with presentations: The Rationale for a Multinational Repository (Sean Tyson); Perspectives on the Future of the Multi-National Repository Concept (Alan Brownstein); Why Would any Country Accept Foreign Spent Nuclear Fuel? (Charles McCombie); Dual Track Strategy for Small Countries (Leon Kegel)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗