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At least 163 records · Page 9

Exaggerated Plurivory of Macrophomina phaseolina : Accounting for the Large Host Range Claim and the Shifting of Scientific Language

Macrophomina phaseolina is a plant pathogenic fungus that is frequently described as having a broad host range encompassing more than 500 species. We noticed that citations provided in support of this statement do not actually demonstrate such a broad host range. To elucidate the true documented host range of this fungus, we initiated a literature meta-analysis of 894 publications on M. phaseolina since 1913. We discovered that the first host range summaries did not require Koch's postulates or other experimental demonstrations of pathogenicity. Most of the available early host claims were based on tenuous associations between the fungus and symptoms, sometimes without reporting isolation or morphological examination in vitro. These statements apparently led to a pattern of increasingly exaggerated host range claims, without support from a primary reference, until the claim that M. phaseolina has 500 hosts became common in the early 2000s. At present, the scientific community typically requires Koch's postulates to characterize pathogenicity on a new host. Among all the available literature, we only found primary experimental evidence for M. phaseolina’s pathogenicity on 97 hosts; 74 hosts confirmed by Koch's postulates and 23 hosts with all steps from Koch's postulates completed except for recovery of the pathogen from symptomatic tissues. This study demonstrates how scientific concepts can change over time and necessitate changes to historic axioms. We propose that the hyperbole surrounding the host range of M. phaseolina has obscured an accurate depiction of its biology.

Plant Sciences↗

Real-time estimators for scattering observables: A full account of finite-volume errors for quantum simulation

The real-time correlators of quantum field theories can be directly probed through new approaches to simulation, such as quantum computing and tensor networks. This provides a new framework for computing scattering observables in lattice formulations of strongly interacting theories, such as lattice quantum chromodynamics. In this paper, we prove that the proposal of real-time estimators of scattering observables is universally applicable to all scattering observables of gapped quantum field theories. All finite-volume errors are exponentially suppressed, and the rate of this suppression is controlled by the regulator considered, namely, a displacement of the spectrum of the theory into the complex plane. A partial restoration of Lorentz symmetry by averaging over different boosts gives an additional suppression of finite volume errors. Our results also apply to the simulation of wave packet scattering, where a similar averaging is performed to construct the wave packets that regulate the finite volume effects. This result represents a necessary key step toward determining a broad class of scattering observables via quantum computing that are currently inaccessible via classical computing. Such observables are relevant for various applications, including hadron spectroscopy, hadron structure, and precision tests of the Standard Model. We also comment on potential applications of our results to traditional computational schemes.

Burbano, Ivan M. [University of California, Berkel↗

Design of Thermophotovoltaic Cells for Optimal System Efficiency, Accounting for Photon Reuse from Front and Back Contacts

We develop a model showing how reflection from both the front and back contacts of thermophotovoltaic (TPV) cells affects the system efficiency. From this foundation we determine the design rules for front grids for TPV cells, and assess the consequences of those rules on cell design and system performance. We show that these design rules are different and more complex than the corresponding design rules for solar photovoltaic (PV) cells, and can lead to substantially different grid design and system performance than if the simpler solar PV design rules were used.

14 SOLAR ENERGY↗

Accounting for herbaceous communities in process‐based models will advance our understanding of “grassy” ecosystems

Abstract Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process‐based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

59 BASIC BIOLOGICAL SCIENCES↗

Co-Optimization of Velocity and Charge-Depletion for Plug-In Hybrid Electric Vehicles: Accounting for Acceleration and Jerk Constraints

Abstract Recent advances in vehicle connectivity and automation technologies promote advanced control algorithms that co-optimize the longitudinal dynamics and powertrain operation of hybrid electric vehicles. Typically, a sequential optimization with the vehicle dynamics optimized followed by powertrain optimization is adopted to manage a number of complexities such as the inherent mixed-integer nature of the hybrid powertrain, the numerous state and control variables, the differing time scales of vehicle and powertrain subsystems, time-varying state constraints, and large horizon lengths. Instead, we solve the offline optimization problem in a centralize manner assuming exact knowledge of the lead vehicle's position over the entire trip by applying a discrete-time single shooting-based numerical approach, Discrete Mixed-Integer Shooting (DMIS), including a linearly increasing computational complexity to the problem horizon. In particular, the hierarchical problem structure is exploited to decompose the computationally intensive Hamiltonian minimization step into a set of low-dimensional optimizations. DMIS allows us to compute the direct fuel minimization problem including the vehicle and powertrain dynamics in a centralized manner to its full horizon while systematically tuning weighting factors that penalize passenger discomfort. For the first time, this study reveals that practically implemented sequential optimization exhibits similar fuel optimality as co-optimization when a certain level of passenger comfort is required.

Automation & Control Systems↗

Damage Modeling of Solid Oxide Fuel Cells Accounting for Redox Effects

This work applies a multiscale mechanistic damage model developed for brittle ceramics and implemented in commercial finite element (FE) packages via user subroutines to study progressive damage in solid oxide fuel cells (SOFC) subjected to thermomechanical loading under normal operating and shutdown conditions including redox effects. The damage model captures the micromechanics of stiffness reduction due to material porosity change and microcracking and integrates the as-obtained stiffness reduction law into a continuum damage mechanics (CDM) formulation for the evolution of microcracks up to fracture. The volumetric “swelling” that occurs during redox is treated in constitutive modeling similarly to thermal expansion, but swelling strains are irreversible. Furthermore, this damage model was first validated through predictions of strength and stress-strain response for the SOFC electrode materials. Next, it has been applied to predict the potential for degradation in a generic planar SOFC stack with large active area cells. Multicell stack models were simulated in both co-flow and counter-flow configurations. In addition, a constant temperature redox cycle was also simulated to capture overall cell electrode damage due to volumetric swelling of the nickel (Ni)-based anode in the anode-supported cells.

25 ENERGY STORAGE↗

Improved Beam Loss Accounting with Fast Data Acquisition (DAQ) Chassis

Identifying the source of beam loss events in the CE-BAF accelerator can be a challenging task. However, with our new prototype system, this task becomes more effi-cient. The system, developed in the fall of 2022, utilizes a dispersive beam position monitor (BPM) and the exist-ing switched electrode electronics BPM hardware. Previ-ously a commercial off-the-shelf data acquisition (DAQ) system was employed to capture BPM wire signals at a sample rate of 20 kS/s. The fast shutdown signal triggered the system, which disables the beam at the injector. Analysis of beam position and energy variation before a beam loss event was used to determine if the beam loss event was associated with an energy transient. The proto-type system, implemented using National Instruments hardware and LabVIEW® software, relied on a software trigger. Manual post-processing was required to ascertain whether the fault was due to an un-tripped cavity with a gradient or phase transient. This work focuses on deploying a Fast DAQ Chassis to monitor BPM hardware in real time and during beam loss events. This system was originally developed and in-stalled in CEBAF to monitor the time-domain RF control signals in the legacy analog RF systems. This technology was leveraged to also monitor BPM signals. As the new system employs a hardware trigger, developing tools to automatically identify faults linked to energy transients unrelated to cavity faults will be straightforward. This paper will discuss the project's initial updates, underlin-ing the crucial role of each member of our team in this achievement

Tiskumara, J.↗

Quantifying the Potential Atmospheric Leakage Risks Associated With the Geologic Storage of CO 2 in Saline Aquifers for Use in Voluntary Carbon Market Buffer Account Determination

Conference paper presented at 17th International Conference on Greenhouse Gas Control Technologies (GHGT-17), Calgary, Alberta, Canada, October 20–24, 2024. This paper presents the results of a detailed study into the potential atmospheric leakage risks associated with the geologic storage of CO 2 in saline aquifers. This study included a detailed literature review, a re-creation of existing CO 2 leakage models put forth by other authors and, lastly, the development of an enhanced model that can be utilized for assessing the potential losses to the atmosphere of stored CO 2 across a variety of potential project parameters. The results of this study indicate that, across broad ranges of input parameters for mechanisms that have the potential for CO 2 loss from the storage complex to the atmosphere, there is an extremely low risk of CO 2 leakage to the atmosphere, with the median leakage risk estimated to be 0.1% of total injected CO 2 . The risk of leakage from real-world storage projects is likely to be even lower than those estimated through this study.

01 COAL, LIGNITE, AND PEAT↗

A guide for deploying Deep Learning in LHC searches: How to achieve optimality and account for uncertainty

Deep learning tools can incorporate all of the available information into a search for new particles, thus making the best use of the available data. This paper reviews how to optimally integrate information with deep learning and explicitly describes the corresponding sources of uncertainty. Simple illustrative examples show how these concepts can be applied in practice.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Domestic Safeguards Material Control and Accountancy Considerations for Molten Salt Reactors

Molten salt reactors (MSRs) are a class of nuclear reactor designs with features and operational characteristics that vary significantly more than the class of light water reactors (LWRs). MSR design concepts can be broadly categorized as solid-fueled reactors with molten salt as the coolant, liquid-fueled reactors with fuel dissolved in molten salt coolant and liquid-fueled reactors with fuel dissolved in molten salt that is contained in distinct fuel tubes with a nonfissile coolant. Proposed MSR concepts include features that are specific to each design. MSR concepts vary widely across these design features, including the physical, chemical, and isotopic composition of fresh and irradiated fuel. Operational neutron energy spectrums and breeding ratios also vary significantly across design concepts. Some concepts are burner reactors designed to transmute the spent nuclear fuel from LWRs or pressurized heavy water reactors (PHWRs), while others are breeder reactors designed to breed fissile 233 U from naturally occurring fertile 232 Th. Some MSR concepts are designed to be a part of a once-through fuel cycle, while others involve chemical separation. Those that include plans to recycle the fuel differ by whether the chemical processing would be done onsite, as a process connected to the fuel salt itself, or offsite at a reprocessing facility similar to how LWR or PHWR spent fuel is reprocessed in some countries. Each overall design concept contains various aspects of each of these features to produce a unique facility

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Safeguards for the Lithium Fluoride Thorium Reactor: A Preliminary Nuclear Material Control and Accounting Assessment

This report was prepared by Oak Ridge National Laboratory (ORNL) for Flibe Energy Inc. (FEI), a US-based advanced reactor company founded in 2011 and headquartered in Huntsville, Alabama. FEI is developing the lithium-fluoride thorium reactor (LFTR), which is a modern two-fluid molten salt reactor (MSR) design operating on a thorium/ 233 U fuel cycle. FEI intends for LFTR to become a self-sustaining clean energy source that can create or breed its own fuel from thorium. Each LFTR is intended to breed enough fissile material to compensate for the amount it consumes. Consequently it would not require fissile replenishment during its operational lifetime. This self-sustaining nature would eliminate the need for uranium enrichment infrastructure to support LFTRs after the first generation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗