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At least 1,531 records · Page 85

Phylogeny, morphology, virulence, ecology, and host range of Ordospora pajunii (Ordosporidae), a microsporidian symbiont of Daphnia spp.

ABSTRACT The impacts of microsporidia on host individuals are frequently subtle and can be context dependent. A key example of the latter comes from a recently discovered microsporidian symbiont of Daphnia , the net impact of which was found to shift from negative to positive based on environmental context. Given this, we hypothesized low baseline virulence of the microsporidian; here, we investigated the impact of infection on hosts in controlled conditions and the absence of other stressors. We also investigated its phylogenetic position, ecology, and host range. The genetic data indicate that the symbiont is Ordospora pajunii , a newly described microsporidian parasite of Daphnia . We show that O. pajunii infection damages the gut, causing infected epithelial cells to lose microvilli and then rupture. The prevalence of this microsporidian could be high (up to 100% in the lab and 77% of adults in the field). Its overall virulence was low in most cases, but some genotypes suffered reduced survival and/or reproduction. Susceptibility and virulence were strongly host-genotype dependent. We found that North American O. pajunii were able to infect multiple Daphnia species, including the European species Daphnia longispina , as well as Ceriodaphnia spp. Given the low, often undetectable virulence of this microsporidian and potentially far-reaching consequences of infections for the host when interacting with other pathogens or food, this Daphnia–O. pajunii symbiosis emerges as a valuable system for studying the mechanisms of context-dependent shifts between mutualism and parasitism, as well as for understanding how symbionts might alter host interactions with resources. IMPORTANCE The net outcome of symbiosis depends on the costs and benefits to each partner. Those can be context dependent, driving the potential for an interaction to change between parasitism and mutualism. Understanding the baseline fitness impact in an interaction can help us understand those shifts; for an organism that is generally parasitic, it should be easier for it to become a mutualist if its baseline virulence is relatively low. Recently, a microsporidian was found to become beneficial to its Daphnia hosts in certain ecological contexts, but little was known about the symbiont (including its species identity). Here, we identify it as the microsporidium Ordospora pajunii . Despite the parasitic nature of microsporidia, we found O. pajunii to be, at most, mildly virulent; this helps explain why it can shift toward mutualism in certain ecological contexts and helps establish O. pajunii is a valuable model for investigating shifts along the mutualism-parasitism continuum.

59 BASIC BIOLOGICAL SCIENCES↗

Superconducting Radio-frequency Cavity Fault Classification Using Machine Learning at Jefferson Laboratory

We report on the development of machine learning models for classifying C100 superconducting radiofrequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. Of the 418 SRF cavities in CEBAF, 96 are designed with a digital low-level RF system configured such that a cavity fault triggers recordings of RF signals for each of eight cavities in the cryomodule. Subject matter experts analyze the collected time-series data and identify which of the eight cavities faulted first and classify the type of fault. This information is used to find trends and strategically deploy mitigations to problematic cryomodules. However, manually labeling the data is laborious and time-consuming. By leveraging machine learning, near real-time - rather than postmortem - identification of the offending cavity and classification of the fault type has been implemented. We discuss the performance of the machine learning models during a recent physics run. We also discuss efforts for further insights into fault types through unsupervised learning techniques and present preliminary work on cavity and fault prediction using data collected prior to a failure event.

Tennant, C. D.↗

Evaluation of the Accuracy of Astroskin as a Behavioral Health Self-Monitoring System for Spaceflight

In space, there is a need to monitor astronauts' vital signs and assess their readiness to perform specific tasks during a mission. Currently, NASA does not have the capability to noninvasively monitor crew for extended periods of time. The Canadian Space Agency is working with the Psychophysiology Lab at NASA ARC to determine if the Astroskin could be used as a solution to this problem. Astroskin, a commercially available garment with built-in biosensors, can be comfortably worn under clothing or a spacesuit and relay information to the crewman's own mobile device. Data can also be sent wirelessly to the on-board Exploration Medical System. To determine if Astroskin meets requirements for health monitoring, it must first be validated in spaceflight analog environments. In the current study Astroskin data will be compared to traditional biomedical instrument measures of electrocardiography (ECG), respiration rate, and systolic blood pressure. The data will be recorded during Autogenic Feedback Training Exercise (AFTE), which is a type of physiological self-regulation training designed for astronauts. The data will also be recorded during simulations of the Orion spacecraft re-entry. The results to date suggest that Astroskin is a suitable ambulatory monitoring system that allows astronauts to self-diagnose and self-regulate adverse autonomic nervous system responses to sustained exposure to microgravity of spaceflight.

biomedical↗

Exploring the ARNTL and RORc Genes' Impact on Lipid Accumulation in the Liver via the Circadian Rhythm

The objective of our proposed experiment is to prove the significance of the upregulation of the ARNTL gene and down regulation of the RORc gene in space, highlighting their crucial roles in causing circadian rhythm misalignment during spaceflight, ultimately resulting in liver lipid accumulation. This experiment was created by thoroughly analyzing the genetic data (UseGalaxy) in OSD-245, Transcriptional analysis of liver from mice flown on the RR-6 mission (NASA GeneLab), and making a comparison between the Flight ISS Terminal and the Ground Control ISS Terminal groups. In our study, we intend to establish experimental groups of Mus musculus (lab mice), with 4 of these groups designated for space travel, while the remaining groups will serve as ground control samples on Earth. Both the space and ground conditions are categorized into four groups according to the genetic makeup of the mice. Within each condition, there will be a control group representing the wild type genes, and the experimental groups will involve knockout mice for ARNTL and RORc. We will then compare the lipid accumulation between the ground control mice and FLT mice to understand whether or not spaceflight causes lipid accumulation, due to a misaligned circadian rhythm. The experiment is anticipated to yield two main outcomes. Firstly, the upregulation of ARNTL is expected to rectify the circadian rhythm misalignment in space, consequently heightening lipid accumulation within the liver. Secondly, the downregulation of RORc is predicted to result in a diminished immune response in the liver, thereby facilitating lipid accumulation. Our space research is expected to aid in lipid buildup countermeasures, informing scientists regarding astronaut protection and providing insights into obesity and non-alcoholic fatty liver disease.

GL4HS↗

MEASUREMENT OF Fn 2 /Fp 2 FROM DEEP INELASTIC ELECTRON SCATTERING OFF A=3 MIRROR NUCLEI AT JEFFERSON LAB

This research is part of the Je?erson Lab MARATHON experiment (MeAsurement of the Fn 2 /Fp 2 , d/u RAtios and A = 3 EMC E?ect in Deep Inelastic Electron Scattering Off the Tritium and Helium MirrOr Nuclei). MARATHON is an experiment on electron deep inelastic scattering off the 3H, 3He mirror nuclei. It has extracted, from the measured deep inelastic scattering cross section ratio o? 3H and 3He, the ratio of the neutron to proton inelastic structure functions Fn 2 /Fp 2 . The extraction has taken advantage of the isospin symmetry of the A = 3 mirror nuclei within a novel technique, which avoids the theoretical uncertainties that are present in the SLAC experiments of the 1970s, which used hydrogen and deuterium targets. The experiment was performed using the upgraded 11 GeV beam of the Jefferson Lab electron accelerator, the Hall A Experimental Facility, and a newly designed cryogenic, high-pressure gas target system containing 3H and 3He cells. Electrons scattered o? the gas targets were detected in the two superconducting, high-resolution magnetic spectrometers of Hall A. The cross section data cover the four-momentum transfer squared range 2.0 < Q2 < 14.0 (GeV/c)2, and the Bjorken x scaling variable range 0.19 < x < 0.83. The experiment also measured, for calibration purposes, electron deep inelastic scattering off hydrogen and deuterium at selected kinematics.

Su, Tong↗

Integrating Crack Detection and Pipe Shape Optimization for Enhanced Sewage System Durability

Crack detection in underground reinforced concrete pipes has been essential in determining the state of stormwater infrastructure. Detection models have been implemented for detecting cracks and other defects in pipes using CCTV footage for stormwater drainage systems. In addition, Finite element models have been used to determine optimum shapes and pipe thickness for different boundary conditions such as header pipes in power plants. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint. This paper discusses the integration of both topics by using the cracks detected in underground pipes as boundary conditions for shape optimization of the pipes. A machine learning model has been developed which uses limited data for training and outlines the location of detected cracks. A shape optimization methodology is proposed in which ANSYS modules are used to analyze fluid flow and then optimize the shape of the pipe. The crack detection model developed has been applied to a crack detected in lab setting and machine learning model used has an accuracy of 98% using a random forest algorithm.

20 FOSSIL-FUELED POWER PLANTS↗

Infrared spectroscopic method for uranium isotopic analysis

A high performance infrared (HPIR) system was developed and demonstrated for the infrared absorption analysis of {sup 235}U and {sup 238}U isotopes in uranium hexafluoride gas samples. Sweeping the quantum cascade laser light source over the spectral range and sampling via a high-rate analog-to-digital converter provided 0.0005 cm-1 spectral resolution, which allowed for high-precision measurements of the isotopic peak shift. A data analysis method was developed using principal component analysis to predict the isotope weight % content of {sup 235}U. The HPIR precision, accuracy, and error were evaluated for a wide range of isotopic ratio samples (0.287 – 93.7 weight % {sup 235}U), and the results were compared to the International Target Values (ITVS) set forth by the International Atomic Energy Agency (IAEA) for non-destructive and destructive analytical techniques. The method meets or surpasses the IAEA ITVs for non-destructive analysis of samples with isotopic content of depleted to highly enriched. The results also demonstrated the capability of the HPIR system to correctly predict the {sup 235}U weight % content of a mislabeled sample whose isotopic distribution was validated by mass spectroscopic measurements. The HPIR measurement is nondestructive and, thus, allows for confirmatory analyses of the exact sample at a designated IAEA lab if higher-resolution or a certified analysis is needed. (author)

07 ISOTOPE AND RADIATION SOURCES↗

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗

Space Link Extension Protocol Emulation for High-Throughput, High-Latency Network Connections

New space missions require higher data rates and new protocols to meet these requirements. These high data rate space communication links push the limitations of not only the space communication links, but of the ground communication networks and protocols which forward user data to remote ground stations (GS) for transmission. The Consultative Committee for Space Data Systems, (CCSDS) Space Link Extension (SLE) standard protocol is one protocol that has been proposed for use by the NASA Space Network (SN) Ground Segment Sustainment (SGSS) program. New protocol implementations must be carefully tested to ensure that they provide the required functionality, especially because of the remote nature of spacecraft. The SLE protocol standard has been tested in the NASA Glenn Research Center's SCENIC Emulation Lab in order to observe its operation under realistic network delay conditions. More specifically, the delay between then NASA Integrated Services Network (NISN) and spacecraft has been emulated. The round trip time (RTT) delay for the continental NISN network has been shown to be up to 120ms; as such the SLE protocol was tested with network delays ranging from 0ms to 200ms. Both a base network condition and an SLE connection were tested with these RTT delays, and the reaction of both network tests to the delay conditions were recorded. Throughput for both of these links was set at 1.2Gbps. The results will show that, in the presence of realistic network delay, the SLE link throughput is significantly reduced while the base network throughput however remained at the 1.2Gbps specification. The decrease in SLE throughput has been attributed to the implementation's use of blocking calls. The decrease in throughput is not acceptable for high data rate links, as the link requires constant data a flow in order for spacecraft and ground radios to stay synchronized, unless significant data is queued a the ground station. In cases where queuing the data is not an option, such as during real time transmissions, the SLE implementation cannot support high data rate communication.

Computer Networking↗

Next Generation Noble Liquid Detectors

The research program here combines Generic and Directed R\&D for Liquid Noble Gas detectors for neutrino physics and dark matter. In neutrino physics and dark matter research, we are addressing some of the most fundamental questions in particle physics today by studying these tiny particles in the electron family. To study them, detectors must be large, high precision, and ideally have the ability to collect detailed information from both charge and light from neutrino and dark matter interactions. Precision detection combined with large scales can be challenging. Liquid Argon detectors mitigate some of these challenges given the nature of its interaction medium and it’s relatively inexpensive cost per ton. Significant progress has been made in the last 15 years in developing these kinds of detectors to be built and operated at large scales. However there are still challenges and new ideas in moving these detectors from ton scale to kiloton scale. To be able to get the most out of these kinds of detectors directed questions with respect to specific components running and colleting data in the detectors must be understood. As well, new ideas on how to best combine charge and light measurements may lead to new ways to learn new things with these detectors. Experimental test stands to conduct this work, as is done in this proposal, to accomplish both of these goals are critical to address both of these questions. In the test stand enabled under this grant at Yale University’s Wright lab, new developments in efficient small scale setups were developed, instrumentation developed for running and future experiments (the SBND experiment at Fermilab at present, the DUNE experiment in the future) were and will be tested, and new ideas for charge and light determination for new measurements are under study. The long term impact of this work in neutrino physcis is both for the short and long baseline programs originating at Fermi National Accelerator Laboratory. At long baselines, the US flagship DUNE experiment will measure neutrino properties through neutrino oscillations using a beam originating at Fermilab and a massive LArTPC detector sited about a mile underground at the Sanford Underground Research Facility in Lead, South Dakota. Studies here on the high voltage for thes detectors, and ongoing work on charge and light production and collection in the TPC are relevant for the design and data taking of this and other LArTPC detectors to enable them to best measure the neutrinos created at Fermilab that then pass through the detector in South Dakota. What we learn in these detectors may ultimately change the course of how we understand neutrino’s impact in the early universe. What we learn about how to improve this detection technology and develop new ideas in Lar detectors in general may impact both future neutrino experiments and dark matter experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

On extraction of twist-two Compton form factors from DVCS observables through harmonic analysis

We investigate the exercise of locally extracting the real and imaginary parts of the four twist-2 Compton form factors (CFFs) {$\mathcal{H,E,\tilde H,\tilde E}$} which arise in the deeply virtual Compton scattering (DVCS) process e + p → e + p + y. Neglecting dynamical higher-twist contributions, we find that there are a sufficient number of DVCS observables and degrees of freedom to extract all 8 leading quantities model-independently, exploiting the azimuthal dependence of the absolute cross sections across all possible beam and target polarizations at a common kinematical point in {Q, t,x b , y}. As an example, for typical JLab lab-frame kinematics, we simplify the reduced DVCS observables to their dominant terms, providing a sufficient number of equations for local determination of the twist-2 CFFs. We demonstrate the feasibility using harmonic fitting to both cross sections and beam spin asymmetries with both real and pseudo-data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Instabilities and phase transitions in architected metamaterials: a gradient-enhanced continuum approach

Architected metamaterials such as foams and lattices exhibit a wide range of properties governed by microstructural instabilities and emerging phase transitions. Their macroscopic response–including energy dissipation during impact, large recoverable deformations, morphing between configurations, and auxetic behavior–remains difficult to capture with conventional continuum models, which often rely on discrete approaches that limit scalability. In this work, we propose a nonlocal continuum formulation that captures both stable and unstable responses of elastic architected metamaterials. The framework extends anisotropic hyperelasticity by introducing nonlocal variables and internal length scales reflective of microstructural features. Local polyconvex free-energy models are systematically augmented with two families of non-(poly)convex energies, enabling both metastable and bistable responses. Implementation in a finite element framework enables solution using a hybrid monolithic–staggered strategy. Simulations capture densification fronts, forward and reverse transitions, hysteresis loops, imperfection sensitivity, and globally coordinated auxetic modes. Overall, this framework provides a robust foundation for accelerated modeling of instability-driven phenomena in architected metamaterials, while enabling extensions to anisotropic, dissipative, and active systems as well as integration with data-driven and machine learning approaches.

42 ENGINEERING↗

LLM-Based Adaptive Distribution Voltage Regulation Under Frequent Topology Changes: An In-Context MPC Framework

This paper proposes a large language model (LLM) based adaptive inverter control for distribution voltage regulation under frequent topology changes. We leverage the ability of the LLM to perform in-context learning and create a topology-adaptive surrogate model for power flow calculation. The surrogate model is then integrated with a long short-term memory-based load forecaster and a model predictive control (MPC) scheme to achieve the optimal inverter control that adapts to frequent topology changes. Unlike many existing works that assume fixed-topology grids or require the knowledge of all possible topologies when training a model, the proposed in-context MPC method tackles the distribution voltage control problem under various topologies and adapts to unknown topologies with limited data requirement for fine-tuning. The effectiveness of our method is demonstrated on a modified IEEE 123-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performance Study of CXL Memory Topology

This paper presents a comprehensive evaluation of the performance impact of various Compute Express Link (CXL) memory topologies, with a particular emphasis on CXL switches, in the context of High- Performance Computing (HPC) and Large Language Model (LLM) inference workloads. Our study unveils significant performance variations across different topologies, demonstrating that certain configurations yield superior performance for specific workloads. These findings underscore the critical importance of tailored topol- ogy selection in optimizing system performance. Additionally, we address the inherent challenges associated with integrating CXL switches, including overhead considerations and routing complex- ities. Our research highlights the necessity for thorough evalua- tion methodologies to fully leverage CXL technology’s potential in contemporary computing environments. These insights provide valuable guidance for system architects and data center operators in designing and optimizing CXL-based infrastructures for diverse workload requirements.

CXL, memory, Artificial Intelligence (AI), HPC↗

The Baby Universe is Fine and the CFT Knows It: On Holography for Closed Universes

Big bang/big crunch closed universes can be realized in AdS/CFT, even though they lack asymptotically AdS boundaries. With enough bulk entanglement, the bulk Hilbert space of a closed universe can be holographically encoded in the CFT. We clarify the relation of this encoding to observer-clone proposals and refute recent arguments about the breakdown of semiclassical physics in such spaces. In the limit of no bulk entanglement, the holographic encoding breaks down. The oft-cited one-dimensional nature of the closed universe Hilbert space represents the limitation of the external (CFT) Hilbert space to access the quantum information in the closed universe, similar to the limitations imposed on observers outside a perfectly isolated quantum lab. We advocate that the CFT nevertheless continues to determine the physical properties of the closed universe in this regime, showing how to interpret this relationship in terms of a final state projection in the closed universe. We provide a dictionary between the final state wavefunction and CFT data. We propose a model of the emergence of an arrow of time in the universe with a given initial or final state projection. Finally, we show that the conventional EFT in the closed universe, without any projection, can be recovered as a maximally ignorant description of the final state. This conventional EFT is encoded in CFT data, and it can be probed by computing coarse-grained observables. We provide an example of one such observable. Taken together, these results amount to a clean bill of health for baby universes born of AdS/CFT.

FOS: Physical sciences↗

A brief survey of constrained mechanics and variational problems in terms of differential forms

There has been considerable interest recently in constrained mechanics and variational problems. This is in part due to applied interests (such as 'non-holonomic mechanics in robotics') and in other part due to the fact that several schools of 'pure' mathematics have found that this classical subject is of importance for what they are trying to do. I have made various attempts at developing these subjects since my Lincoln lab days of the late 1950's. In this Chapter, I will sketch a Unified point of view, using Cartan's approach with differential forms. This has the advantage from the C-O-R viewpoint being developed in this Volume that the extension from 'smooth' to 'generalized' data is very systematic and algebraic. (I will only deal with the 'smooth' point of view in this Chapter; I will develop the 'generalized function' material at a later point.) The material presented briefly here about Variational Calculus and Constrained Mechanics can be found in more detail in my books, 'Differential Geometry and the Calculus of Variations', 'Lie Algebras and Quantum Mechanics', and 'Geometry, Physics and Systems'.

Hermann, Robert↗

Operational Parameters, Considerations, and Design Decisions for Resource-Constrained Ion Trap Mass Spectrometers

Mass spectrometers are increasingly finding applications in new and unique areas, often in situations where key operational resources (i.e. power, weight and size) are limited. One such example is the Mars Organic Molecule Analyzer (MOMA). This instrument is a joint venture between NASA and the European Space Agency (ESA) to develop an ion trap mass spectrometer for chemical analysis on Mars. The constraints on such an instrument are significant as are the performance requirements. While the ideal operating parameters for an ion trap are generally well characterized, methods to maintain analytical performance with limited power and system weight need to be investigated and tested. Methods Experiments have been performed on two custom ion trap mass spectrometers developed as prototypes for the MOMA instrument. This hardware consists of quadrupole ion trap electrodes that are 70% the size of common commercial instrumentation. The trapping RF voltage is created with a custom tank circuit that can be tuned over a range of RF frequencies and is driven using laboratory supplies and amplifiers. The entire instrument is controlled with custom Lab VIEW software that allows a high degree of flexibility in the definition of the scan function defining the ion trap experiment. Ions are typically generated via an internal electron ionization source, however, a laser desorption source is also in development for analysis of larger intact molecules. Preliminary Data The main goals in this work have been to reduce the power required to generate the radio frequency trapping field used in an ion trap mass spectrometer. Generally minimizing the power will also reduce the volume and mass of the electronics to support the instrument. In order to achieve optimum performance, commercial instruments typically utilize RF frequencies in the 1 MHz range. Without much concern for power usage, they simply generate the voltage required to access the mass range of interest. In order to reduce the required RF voltage (and power), operation of the ion trap at lower RF frequencies has been investigated. Surprisingly, the performance of the instrument has only been slightly degraded at RF frequencies all the way down to 500 kHz. Mass resolution is relatively stable to this point and depending on the resonant ejection point used, the peak intensity is also quite stable. To date only masses up to m/z 200 have been fully investigated, however, additional studies are planned to verify the performance with higher mass ions. The lower frequency and voltage should reduce the pseudo potential well depth, eventually affecting the trapping efficiency of the instrument -- effect that could manifest itself in significantly limiting the mass range of trapped ions. Other methods to reduce the RF power while maintaining analytical performance are also under investigation. This includes ion ejection at lower q(sub z) values to access a given mass with a lower RF voltage. The loss of mass resolution at lower q(sub eject) points has been measured and current work is underway to leverage scan speed and the use of non-linear resonances in order to counter this trend. The overall trap performance under this range of operating conditions will be presented with a goal of identifying what trade-offs are acceptable.

Danell, Ryan M.↗