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At least 847 records · Page 47

The Near-Gapless Penicillium fuscoglaucum Genome Enables the Discovery of Lifestyle Features as an Emerging Post-Harvest Phytopathogen

Penicillium spp. occupy many diverse biological niches that include plant pathogens, opportunistic human pathogens, saprophytes, indoor air contaminants, and those selected specifically for industrial applications to produce secondary metabolites and lifesaving antibiotics. Recent phylogenetic studies have established Penicillium fuscoglaucum as a synonym for Penicillium commune, which is an indoor air contaminant and toxin producer and can infect apple fruit during storage. During routine culturing on selective media in the lab, we obtained an isolate of P. fuscoglaucum Pf_T2 and sequenced its genome. The Pf_T2 genome is far superior to available genomic resources for the species. Our assembly exhibits a length of 35.1 Mb, a BUSCO score of 97.9% complete, and consists of five scaffolds/contigs representing the four expected chromosomes. It was determined that the Pf_T2 genome was colinear with a type specimen P. fuscoglaucum and contained a lineage-specific, intact cyclopiazonic acid (CPA) gene cluster. For comparison, a highly virulent postharvest apple pathogen, P. expansum strain TDL 12.1, was included and showed a similar growth pattern in culture to our Pf_T2 isolate but was far more aggressive in apple fruit than P. fuscoglaucum. The genome of Pf_T2 serves as a major improvement over existing resources, has superior annotation, and can inform forthcoming omics-based work and functional genetic studies to probe secondary metabolite production and disparities in aggressiveness during apple fruit decay.

59 BASIC BIOLOGICAL SCIENCES↗

Control of Carbon Assimilation and Partitioning by Jasmonate: An Accounting of Growth–Defense Tradeoffs

Plant growth is often constrained by the limited availability of resources in the microenvironment. Despite the continuous threat of attack from insect herbivores and pathogens, investment in defense represents a lost opportunity to expand photosynthetic capacity in leaves and absorption of nutrients and water by roots. To mitigate the metabolic expenditure on defense, plants have evolved inducible defense strategies. The plant hormone jasmonate (JA) is a key regulator of many inducible defenses. Synthesis of JA in response to perceived danger leads to the deployment of a variety of defensive structures and compounds, along with a potent inhibition of growth. Genetic studies have established an important role for JA in mediating tradeoffs between growth and defense. However, several gaps remain in understanding of how JA signaling inhibits growth, either through direct transcriptional control of JA-response genes or crosstalk with other signaling pathways. Here, we highlight recent progress in uncovering the role of JA in controlling growth-defense balance and its relationship to resource acquisition and allocation. We also discuss tradeoffs in the context of the ability of JA to promote increased leaf mass per area (LMA), which is a key indicator of leaf construction costs and leaf life span.

59 BASIC BIOLOGICAL SCIENCES↗

The COSMOS2015 Catalog: Exploring the 1 < z < 6 universe with half a million galaxies

We present the COSMOS2015{sup 24} catalog, which contains precise photometric redshifts and stellar masses for more than half a million objects over the 2deg{sup 2} COSMOS field. Including new YJHK{sub s} images from the UltraVISTA-DR2 survey, Y-band images from Subaru/Hyper-Suprime-Cam, and infrared data from the Spitzer Large Area Survey with the Hyper-Suprime-Cam Spitzer legacy program, this near-infrared-selected catalog is highly optimized for the study of galaxy evolution and environments in the early universe. To maximize catalog completeness for bluer objects and at higher redshifts, objects have been detected on a χ {sup 2} sum of the YJHK{sub s} and z {sup ++} images. The catalog contains ∼6×10{sup 5} objects in the 1.5 deg{sup 2} UltraVISTA-DR2 region and ∼1.5×10{sup 5} objects are detected in the “ultra-deep stripes” (0.62 deg{sup 2}) at K{sub s}⩽24.7 (3σ, 3″, AB magnitude). Through a comparison with the zCOSMOS-bright spectroscopic redshifts, we measure a photometric redshift precision of σ{sub Δz/(1+z{sub s)}} = 0.007 and a catastrophic failure fraction of η = 0.5%. At 3<z<6, using the unique database of spectroscopic redshifts in COSMOS, we find σ{sub Δz/(1+z{sub s)}} = 0.021 and η = 13.2%. The deepest regions reach a 90% completeness limit of 10{sup 10}M{sub ⊙} to z = 4. Detailed comparisons of the color distributions, number counts, and clustering show excellent agreement with the literature in the same mass ranges. COSMOS2015 represents a unique, publicly available, valuable resource with which to investigate the evolution of galaxies within their environment back to the earliest stages of the history of the universe. The COSMOS2015 catalog is distributed via anonymous ftp and through the usual astronomical archive systems (CDS, ESO Phase 3, IRSA).

79 ASTRONOMY AND ASTROPHYSICS↗

197 candidates and 104 validated planets in K2's first five fields

We present 197 planet candidates discovered using data from the first year of the NASA K2 mission (Campaigns 0–4), along with the results of an intensive program of photometric analyses, stellar spectroscopy, high-resolution imaging, and statistical validation. We distill these candidates into sets of 104 validated planets (57 in multi-planet systems), 30 false positives, and 63 remaining candidates. Our validated systems span a range of properties, with median values of R {sub P} = 2.3 R{sub ⊕}, P = 8.6 days, T{sub eff} = 5300 K, and Kp = 12.7 mag. Stellar spectroscopy provides precise stellar and planetary parameters for most of these systems. We show that K2 has increased by 30% the number of small planets known to orbit moderately bright stars (1–4 R {sub ⊕}, Kp = 9–13 mag). Of particular interest are 76 planets smaller than 2 R {sub ⊕}, 15 orbiting stars brighter than Kp = 11.5 mag, 5 receiving Earth-like irradiation levels, and several multi-planet systems—including 4 planets orbiting the M dwarf K2–72 near mean-motion resonances. By quantifying the likelihood that each candidate is a planet we demonstrate that our candidate sample has an overall false positive rate of 15%–30%, with rates substantially lower for small candidates (<2R{sub ⊕}) and larger for candidates with radii >8R{sub ⊕} and/or with P<3 days. Extrapolation of the current planetary yield suggests that K2 will discover between 500 and 1000 planets in its planned four-year mission, assuming sufficient follow-up resources are available. Efficient observing and analysis, together with an organized and coherent follow-up strategy, are essential for maximizing the efficacy of planet-validation efforts for K2, TESS, and future large-scale surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Some Issues in Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

The current tuning process of parameters in global climate models is often performed subjectively, or treated as an optimization procedure to minimize the difference between model fields and observations. The later approach may be generating a set of tunable parameters that approximate the observed climate but via an unrealistic balance of physical processes and/or compensating errors over different regions in the globe. In this study, we run the Weather Research and Forecasting (WRF) regional model constrained by the reanalysis data over the Southern Great Plains (SGP) where abundant observational data from various resources are available for calibration of the input parameters and validation of the model results. Our goal is to quantify the uncertainty ranges and identify the optimal values of five key input parameters in a new Kain-Frisch (KF) convective parameterization scheme incorporated in the WRF model. A stochastic sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA), is employed to efficiently sample the input parameters in KF scheme based on the skill score so that the algorithm progressively moves toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP show that the model bias for precipitation can be significantly reduced by using five optimal parameters identified by the MVFSA algorithm. The model performance is very sensitive to downdraft and entrainment related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreases as the ratio of downdraft to updraft flux increases. Larger CAPE consumption time results in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by only constraining precipitation generates positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25 km simulation, both the magnitude and spatial pattern of simulated precipitation are improved at 12-km spatial resolution. The optimal parameters identified from the SGP region have also improved the simulation of precipitation when moving model domain to another region with a different climate regime (i.e. North America monsoon region). These results suggest the improvement of precipitation simulation by using the optimal parameters remains when the model domain or spatial resolution is changed.

54 ENVIRONMENTAL SCIENCES↗

Offshore low-level jet observations and model representation using lidar buoy data off the California coast

Abstract. Low-level jets (LLJs) occur under a variety of atmospheric conditions and influence the available wind resource for wind energy projects. In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas administered by the Bureau of Ocean Energy Management: Humboldt and Morro Bay. The wind profile observations from the lidars and collocated near-surface meteorological stations (4–240 m) provide valuable year-long analyses of offshore LLJ characteristics at heights relevant to wind turbines. At Humboldt, LLJs were associated with flow reversals and north-northeasterly winds, directions that are more aligned with terrain influences than the predominant northerly flow. At Morro Bay, coastal LLJs were observed primarily during northerly flow as opposed to the predominant north-northwesterly flow. LLJs were observed more frequently in colder seasons within the lowest 250 m a.s.l. (above sea level), in contrast with the summertime occurrence of the higher-altitude California coastal jet influenced by the North Pacific High, which typically occurs at heights of 300–400 m. The lidar buoy observations also validate LLJ representation in atmospheric models that estimate potential energy yield of offshore wind farms. The European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) was unsuccessful at identifying all observed LLJs at both buoy locations within the lowest 200 m. An extension of the National Renewable Energy Laboratory (NREL) 20-year wind resource dataset for the Outer Continental Shelf off the coast of California (CA20-Ext) yielded marginally greater captures of observed LLJs using the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary layer (PBL) scheme than the 2023 National Offshore Wind dataset (NOW-23), which uses the Yonsei University (YSU) scheme. However, CA20-Ext also produced the most LLJ false alarms, which are instances when a model identified an LLJ but no LLJ was observed. CA20-Ext and NOW-23 exhibited a tendency to overestimate the duration of LLJ events and underestimate LLJ core heights.

17 WIND ENERGY↗

Combining multi-layered bitmap files using network specific hardware

Images and video can be produced by compositing or alpha blending a group of image layers or video layers. Increasing resolution or the number of layers results in increased computational demands. As such, the available computational resources limit the images and videos that can be produced. A computational architecture in which the image layers are packetized and streamed through processors can be easily scaled so to handle many image layers and high resolutions. The image layers are packetized to produce packet streams. The packets in the streams are received, placed in queues, and processed. For alpha blending, ingress queues receive the packetized image layers which are then z sorted and sent to egress queues. The egress queue packets are alpha blended to produce an output image or video.

97 MATHEMATICS AND COMPUTING↗

Appendix I3-1 to Wind HUI Initiative 1: AWST-WindNET-Phase 1 Final Report

This report is an appendix to the Hawaii WindHUI efforts to develop and operationalize short-term wind forecasting and wind ramp event forecasting capabilities. The report summarizes the WindNET Phase 1 efforts on the Big Island of Hawaii and includes descriptions of modeling methodologies, use of field validation data, results and recommendations. The objective of the WindNET project was to investigate the improvement that could be obtained in short-term wind power forecasting for wind generation facilities operating on the island grids operated by Hawaiian Electric Companies through the use of atmospheric sensors deployed at targeted locations. WindNET is envisioned as a multiphase project that will address the short-term wind forecasting issues of all of the wind generation facilities on the all of the Hawaiian Electric Companies' island grid systems. The first phase of the WindNET effort (referred to as WindNET-1) was focused on the wind generation facilities on the Big Island of Hawaii. With complex terrain and marine environment, emphasis was on improving the 0 to 6 hour forecasts of wind power ramps and periods of wind variability, with a particular interest in the intra-hour (0-1 hour) look-ahead period. The WindNET project was built upon a foundation that was constructed with the results from a previously completed observation targeting study for the Big Island that was conducted as part of a project supported by the National Renewable Energy Laboratory (NREL) and interactions with the western utilities. The observational targeting study provided guidance on which variables to measure and at what locations to get the most improvement in forecast performance at a target forecast site. The recommendations of the observation targeting study were based on the application two techniques: (1) an objective method called ensemble sensitivity analysis (ESA) (Ancell and Hakim, 2007; Torn and Hakim, 2008; Zack et al, 2010); and (2) a subjective method based on a diagnostic analysis of large ramp events. The analysis was completed for both the wind farm on the southern tip of the Big Island and on the northern tip of the island. The WindNET project was designed to also deploy sensors to validate the Big Island observational targeting study and enhance operator's understanding of predominate causes of wind variability conditions at the wind facilities. Compromises had to be made with the results from the observation targeting study to accommodate project resource limitations, availability of suitable sites, and other factors. To focus efforts, field sensor deployment activities focused on the wind facility on the southern point of Big Island.

14 SOLAR ENERGY↗

Calibration and Measurement Uncertainty Estimation of Radiometric Data: Preprint

Evaluating the performance of photovoltaic cells, modules, and arrays that form large solar deployments relies on accurate measurements of the available solar resource. Therefore, determining the accuracy of these solar radiation measurements provides a better understanding of investment risks. This paper provides guidelines and recommended procedures for estimating the uncertainty in calibrations and measurements by radiometers using methods that follow the International Bureau of Weights and Measures Guide to the Expression of Uncertainty (GUM). Standardized analysis based on these procedures ensures that the uncertainty quoted is well documented.

14 SOLAR ENERGY↗

Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

In much of the developed world, air-conditioning in buildings is the dominant driver of summer peak electricity demand. In the developing world a steadily increasing utilization of air-conditioning places additional strain on already-congested grids. This common thread represents a large and growing threat to the reliable delivery of electricity around the world, requiring capital-intensive expansion of capacity and draining available investment resources. Thermal energy storage (TES), in the form of ice or chilled water, may be one of the few technologies currently capable of mitigating this problem cost effectively and at scale. The installation of TES capacity allows a building to meet its on-peak air conditioning load without interruption using electricity purchased off-peak and operating with improved thermodynamic efficiency. In this way, TES has the potential to fundamentally alter consumption dynamics and reduce impacts of air conditioning. This investigation presents a simulation study of a large office building in four distinct geographical contexts: Miami, Lisbon, Shanghai, and Mumbai. The optimization tool DER-CAM (Distributed Energy Resources Customer Adoption Model) is applied to optimally size TES systems for each location. Summer load profiles are investigated to assess the effectiveness and consistency in reducing peak electricity demand. Additionally, annual energy requirements are used to determine system cost feasibility, payback periods and customer savings under local utility tariffs.

25 ENERGY STORAGE↗

National Geothermal Database

THE NGDS IS A USER-FRIENDLY, WEB-BASED APPLICATION TO SUPPORT FINDING, VISUALIZING, MAPPING, AND ACQUISITION OF DATA BY END-USERS. THIS APPLICATION ALLOWS USERS TO DISCOVER AND ACCESS RESOURCES MADE AVAILABLE ACROSS ALL NGDS NODES, AND TO SEARCH FOR DATA ACROSS THE SYSTEM BASED ON TOPIC, LOCATION, AND OR OTHER CRITERIA. STANDARDIZED METADATA DESCRIBING EACH DATASET PROVIDES THE USER WITH THE INFORMATION NECESSARY TO DETERMINE THE UTILITY OF THAT DATASET FOR THEIR PURPOSES. GEOGRAPHIC DATASETS CAN BE VISUALIZED THROUGH A MAP INTERFACE THAT ALLOWS USERS TO INSPECT THE DETAILS OF INDIVIDUAL DATA POINTS (E.G. WELLS, TEMPERATURE MEASUREMENTS, ETC.) FROM PROPERLY FORMATTED DATASETS. IN ADDITION TO VISUALIZATION WITHIN THE APPLICATION, THE INTERFACE PROVIDES THE INFORMATION NECESSARY FOR USERS TO ACCESS THE DATA FROM OTHER APPLICATIONS.

Source record↗

Muon Sources for Particle Physics - Accomplishments of the Muon Accelerator Program

The Muon Accelerator Program (MAP) completed a four-year study on the feasibility of muon colliders and on using stored muon beams for neutrinos. That study was broadly successful in its goals, establishing the feasibility of lepton colliders from the 125 GeV Higgs Factory to more than 10 TeV, as well as exploring using a μ storage ring (MSR) for neutrinos, and establishing that MSRs could provide factory-level intensities of νe (ν $\bar{e}$ ) and ν $\bar{μ}$ ) (ν μ ) beams. The key components of the collider and neutrino factory systems were identified. Feasible designs and detailed simulations of all of these components were obtained, including some initial hardware component tests, setting the stage for future implementation where resources are available and clearly associated physics goals become apparent

43 PARTICLE ACCELERATORS↗

High Performance Computing Based Parallel HIearchical Modal Association Clustering (HPAR HMAC)

For many applications, clustering is a crucial step in order to gain insight into the makeup of a dataset. The best approach to a given problem often depends on a variety of factors, such as the size of the dataset, time restrictions, and soft clustering requirements. The HMAC algorithm seeks to combine the strengths of 2 particular clustering approaches: model-based and linkage-based clustering. One particular weakness of HMAC is its computational complexity. HMAC is not practical for mega-scale data clustering. For high-definition imagery, a user would have to wait months or years for a result; for a 16-megapixel image, the estimated runtime skyrockets to over a decade! To improve the execution time of HMAC, it is reasonable to consider an multi-core implementation that utilizes available system resources. An existing imple-mentation (Ray and Cheng 2014) divides the dataset into N partitions - one for each thread prior to executing the HMAC algorithm. This implementation benefits from 2 types of optimization: parallelization and divide-and-conquer. By running each partition in parallel, the program is able to accelerate computation by utilizing more system resources. Although the parallel implementation provides considerable improvement over the serial HMAC, it still suffers from poor computational complexity, O(N2). Once the maximum number of cores on a system is exhausted, the program exhibits slower behavior. We now consider a modification to HMAC that involves a recursive partitioning scheme. Our modification aims to exploit divide-and-conquer benefits seen by the parallel HMAC implementation. At each level in the recursion tree, partitions are divided into 2 sub-partitions until a threshold size is reached. When the partition can no longer be divided without falling below threshold size, the base HMAC algorithm is applied. This results in a significant speedup over the parallel HMAC.

Patlolla, Dilip R↗

Continuous Membrane Assisted IBE Fermentation from AVAP® Cellulosic Sugars

An economically viable process for the production of butanol from the underutilized natural resources domestically available, economically sustainable biofuel at or below DOE target selling price; suitable for roll-out in multiple regions containing agricultural residues and underutilized forest residuals; and able to compete in the butanol market without subsidy

09 BIOMASS FUELS↗

NREL's Effort Toward Predicting Soiling

The aim of this works is sharing the research conducted by NREL in the past three years on photovoltaic soiling. Soiling is an issue affecting PV systems worldwide and causing reduction in performance and increase in O&M costs. NREL has been working closing with he community to (i) develop models to predict soiling, in order to help PV owners to better plan optimal cleaning schedules, and identify soiling trends from PV performance data, without the need of expensive soiling detectors, (ii) understand the abrasive effects of soiling and cleanings on PV glasses, (iii) investigate the effectiveness of different cleaning methods. The most important results and some of the resources made available by the NREL research team will be presented.

14 SOLAR ENERGY↗

BigPanDA: PanDA Workload Management System and its Applications beyond ATLAS

Modern experiments collect peta-scale volumes of data and utilize vast, geographically distributed computing infrastructure that serves thousands of scientists around the world. Requirements for rapid, near real-time data processing, fast analysis cycles and need to run massive detector simulations to support data analysis pose special premium on efficient use of available computational resources. A sophisticated Workload Management System (WMS) is needed to coordinate the distribution and processing of data and jobs in such environment. The ATLAS experiment at CERN uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. While PanDAcurrently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, it runs around 2 million jobs per day on hundreds of Grid sites and serving thousands of ATLAS users. In 2017 about 1.5 exabytes of data were processed with PanDA.In 2012 BigPanDA project project was started with aim to introduce new types of computing resources into ATLAS computing infrastructure, but also to offering PanDA features to different data-intensive applications for projects and experiments outside of ATLAS and High-Energy and Nuclear Physics. In this article we will present accomplishments and discuss possible directions for future work.

Svirin, Pavlo↗

Hydrogen's Expanding Role in the Energy System

Realizing the vision of H2@Scale will require research and investment in efficient hydrogen production methods and upgraded infrastructure. Advances in hydrogen production will allow new applications, such as steelmaking, biofuels production, and fuel cell electric vehicles, to thrive. H2@Scale is a U.S. Dept. of Energy (DOE) initiative that brings together stakeholders to advance affordable hydrogen production, transport, storage, and utilization in multiple energy sectors. H2@Scale will improve the resiliency and reliability of the energy supply chain, increase the competitiveness of U.S. manufacturing, create jobs, and reduce emissions, thereby improving environmental sustainability. Hydrogen has a unique ability to transfer energy across time and economic sectors. The electric grid was designed so that the generated load varies with changes in demand. However, wind and solar power technologies can only generate electricity when each resource is available, making it more difficult to balance the grid. Because hydrogen production can be a large-scale controllable load, it can help address that challenge. Hydrogen can serve as a clean feedstock for diverse applications within the transportation, process industries, and energy sectors. This article describes hydrogen production, application, and infrastructure opportunities. The first part of the article discusses hydrogen production and describes current costs and potential cost reductions that could be enabled by research and development (R&D). The second section discusses key applications that take advantage of hydrogen's chemical properties and its potential as an energy carrier. The final section of the article describes the current hydrogen infrastructure and how it must grow to meet the H2@Scale vision.

08 HYDROGEN↗

Cyber Threat Screening Using a Queuing-Based Game-Theoretic Approach

Dynamic and uncertain security environments, such as cyber systems, often involve strategic interactions among multiple decision-making agents. In this paper, we consider a cybersecurity setting where a system administrator (defender) has to screen malicious service requests of an attacker who seeks to exhaust available cyber resources and inconvenience users with normal requests. We propose a novel cyber-threat inspection model, based on Stackelberg games, that unies aspects of Threat Security Games with the Erlang-B queuing framework to provide equilibrium strategies for both the attacker and defender. In our proposed model, the defender seeks to determine the optimal number of inspection nodes required to maximize detection probability of malicious requests, while the attacker maximizes the probability of legitimate requests dropping out of the system. We derive analytical expressions of the equilibrium solutions of the proposed Stackelberg game under realistic assumptions on system observability and payoff structure of the players. A numerical case study is presented, and steps for further research are identified.

Cybersecurity, Stackelberg game, Erlang-B loss sys↗