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At least 847 records · Page 47

Model Scripts for "Old-Aged Groundwater Contributes to Mountain Hillslope Hydrologic Dynamics"

The partitioning of water inputs between deep and shallow groundwater flow paths is a fundamental processes, yet is challenging to observe. Numerical models provide a valuable tool to further develop insights on these groundwater mixing processes. This repository contains scripts to run the ParFlow-CLM and EcoSLIM integrated hydrologic models along the Pumphouse Hillslope in the East River Watershed and associated python scripts to process model outputs. Files includes input decks for the associated models, python scripts, and text and css files to support the model runs and processing. The 2-D hillslope model simulates from 2000 to 2021 using transient forcing conditions from the publicly available NLDAS-2 dataset. We develop an ensemble of models with variable hydrogeologic and soil parameters. Model outputs from the ensemble of runs are compared to to water level observations at the PLM1 and PLM6 wells published at (https://data.ess-dive.lbl.gov/view/doi:10.15485/1866836) and groundwater mean ages published at (https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1960042. The model results are used to evaluate hillslope water mass-balance transience and mixing dynamics between groundwater flow paths with young (<10 year) and old (>10 year) ages.

54 ENVIRONMENTAL SCIENCES↗

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 2. Evaluating Controls on Flow Persistence in an Urbanized Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in an urbanized catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, distributed temperature sensing (DTS), continuous self-potential (SP) monitoring, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Field_Application subfolder contains the ATS XML input scripts, data files, output data for the SP site. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. The flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.m can only be used with COMSOL with MATLAB) is executed using the ATS output data to simulate the potential field. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) DTS Contains collated DTS data including raw Stokes and anti-Stokes measurement (provided as .h5 file). It also includes DTS processing.ipynb, a Jupyter notebook for calibrating the DTS data using dts_calibration Python package. cooler_calibration.csv is the DTS calibration CSV used in the calibration sequence. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion. 6) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 7) SP Contains the SP data collected in field at the SP sites (provided as CSV files). 8) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). Note: Code files (.ipynb, .py, .xml) can be opened in any standard code editor, .exo file can be viewed using Paraview, .h5 files can be opened using HDFView software and h5py Python package, and .resipy file can be opened with the open-source ResIPy software.

ATS↗

Practical galaxy morphology tools from deep supervised representation learning

Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning.

79 ASTRONOMY AND ASTROPHYSICS↗

Commissioning of the Mu2e tracker DAQ, planning for the Vertical Slice Test and pre-pattern recognition studies

The primary objective of the Mu2e experiment at Fermilab is to search for the neutrino-less coherent $\mu \rightarrow e$ conversion in the field of an aluminum nucleus ($\mu^- \text{Al} \rightarrow e^- \text{Al}$). The signature of this process is a monochromatic Conversion Electron (CE) with an energy of approximately 104.97 MeV \cite{bartoszek2015mu2e}. Within the Standard Model (SM), the branching ratio for this process, including neutrino masses and oscillation, is expected to be less than $\mathcal{O}(10^{-50})$. This value is far beyond current experimental capabilities. However, models of physics beyond the SM predict much higher relative rates, approaching an observable level. The SINDRUM II experiment set an upper limit on muon conversion at $7 \times 10^{-13}$ (90\% CL) on Au target \cite{SINDRUMII:2006dvw}, and the Mu2e collaboration aims to improve this limit by four orders of magnitude. Observing this process would provide a clear evidence of physics beyond the Standard Model. A brief discussion of the theoretical and experimental aspects is provided in Chapter \ref{intr}. Mu2e adopts a sophisticated experimental setup to achieve its goals, further described in Chapter \ref{mu2echapter}. The central part of the Mu2e detector is the tracker, that consists of 18 tracking stations. The tracker must provide excellent momentum resolution, approximately 1 MeV/c, to distinguish the monochromatic CE signal from the background. To minimize the energy losses, a straw tube tracker will be used \cite{bobbb}. Chapter \ref{chaptertrk} provides an overview of the straw tracker design and its working principles. This Thesis presents a comprehensive study of the Mu2e tracker, covering complementary aspects from initial commissioning to optimization and first steps of the calibration processes. My work at Fermilab has been focused on the complete Data Acquisition (DAQ) testing from both hardware and software perspectives. I was involved in the commissioning of the Mu2e DAQ system and the Vertical Slice Test (VST) of the tracker. The VST encompasses the entire testing chain, from the straws to the readout, and to processed data on disk. I was also focused on the offline analysis, especially on pre-pattern recognition studies, to explore the best methods for identifying $\delta$-electrons during the data taking. Chapter \ref{commissioning} details the commissioning of the tracker DAQ system, emphasizing the importance of understanding of the readout process before the data acquisition. This includes validating the readout logic and firmware through Monte Carlo simulations to confirm functionality and buffering, monitoring the quality of the data from the tracker preamplifiers and front-end electronics, and assessing overall DAQ performance to ensure reliability during future calibration and data-taking. Chapter \ref{planning} discusses the initial steps towards the tracker calibration. The ultimate goal is to perform a time calibration of the first assembled station of the tracker using cosmic muons, aiming for a longitudinal hit position resolution better than 4 cm. This involves determining the signal propagation times and channel-to-channel delays. I performed a Monte Carlo study to determine the impact of the station orientation on the quality of the calibration, in particular on the cosmic track reconstruction, focusing on potential biases that could arise. These studies provide essential insights into the operation, optimization, and calibration of the Mu2e tracker system. Given the high data volume expected during Mu2e operations, estimated at approximately 7 PBytes per year, optimizing memory usage and minimizing CPU consumption are critical. A significant challenge lies in effectively flagging $\delta$-electron hits, which are the primary source of hits in the tracker, without compromising the efficiency of CE hit detection and track reconstruction. A detailed study of pre-pattern recognition and a thorough comparison of two $\delta$-electron flagging algorithms is provided in Chapter \ref{delta}. In Chapter \ref{conclusions}, the findings are concisely summarized, offering a comprehensive synthesis of the research and emphasizing the key insights derived from this study.

43 PARTICLE ACCELERATORS↗

Structure and Dynamics of Coronal Plasma

Brief summaries of the four published papers produced within the present performance period of NASA Grant NAGW-4081 are presented. The full text of the papers are appended to the report. The first paper titled "Coronal Structures Observed in X-rays and H-alpa Structures" was published in the Kofu Symposium proceedings. The study analyzes cool and hot behavior of two x-ray events, a small flare and a surge. It was found that a large H-alpha surge appears in x-rays as a very weak event, while a weak H-alpha feature corresponds to the brightest x-ray emission on the disk at the time of the observation. Calculations of the heating necessary to produce these signatures, and implications for the driving and heating mechanisms of flares vs. surges are presented. The second paper "Differential Magnetic Field Shear in an Active Region" has been published in The Astrophysical Journal. The study compared the three dimensional extrapolation of magnetic fields with the observed coronal structure in an active region. Based on the fit between observed coronal structure throughout the volume of the region and the calculated magnetic field configurations, the authors propose a differential magnetic field shear model for this active region. The decreasing field shear in the outer portions of the AR may indicate a continual relaxation of the magnetic field with time, corresponding to a net transport of helicity outward. The third paper "Difficulties in Observing Coronal Structure" has been published in the journal Solar Physics. This paper discusses the evidence that the temperature and density structure of the corona are far more complicated than had previously been thought. The discussion is based on five studies carried out by the group on coronal plasma properties, showing that any one x-ray instrument does see all of the plasma present in the corona, that hot and cool material may appear to be co-spatial at a given location in the corona, and that simple magnetic field extrapolations provide only a poor fit to the observed structure. The fourth paper "Analysis and Comparison of Loop Structures Imaged with NIXT and Yohkoh/SXT" has been published in Astronomy and Astrophysics. This paper analyzes and compares a variety of coronal loops, deriving loop pressure and emission measure from loop models. They are able to determine the volume filling factor in the corona, which is found to be in the range 0.001 to 0.01 for compact loops, and of order 1 for large structures. The small values suggest highly filamented structures, especially at lower temperatures.

Golub, Leon↗

Hybrid Quantum–Classical Graph Transformers for Efficient Sentiment Analysis

Quantum Machine Learning (QML) offers a promising paradigm that leverages quantum computing principles to develop efficient and expressive models for learning from complex and structured data. Recent advances in natural language processing (NLP) and artificial intelligence (AI) have demonstrated capabilities in understanding, generating, and reasoning over linguistic and multimodal information. In this work, we present the Quantum Graph Transformer (QGT), a hybrid quantum–classical architecture that extends graph transformer capabilities through quantum self-attention. The QGT models variable-length sentences as token graphs, where both the embedding encoding and the self-attention mechanisms are implemented using parameterized quantum circuits (PQCs), enabling efficient contextual learning with significantly fewer trainable parameters. We train QGT using both fully connected and 𝑘 -nearest-neighbor graph structures and evaluate it on five benchmark sentiment-classification datasets. Experimental results show that QGT consistently achieves higher or comparable accuracy to existing quantum NLP models and outperforms a Classical Graph Transformer (CGT) baseline with identical architecture, achieving 29.4 × fewer parameters while requiring 3–5 × fewer samples to reach comparable performance. These findings highlight the potential of graph-based quantum models as scalable and data-efficient architectures for natural language understanding.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Discovery of the First Leaking Double-Shell Tank - Hanford Tank 241-AY-102

Full text - Long Abstract. A routine video inspection of the annulus region of double-shell tank 241-A Y-102 in August of 2012 indicated the presence material in the annulus space between the primary and secondary liners. A comparison was made to previous inspections performed in 2006 and 2007. which indicated that a change had occurred. The material was observed at two locations on the floor of the annulus and one location at the top of the annulus region where the primary and secondary top knuckles meet (RPP-ASMT-53793). Subsequent inspections were performed. leading to additional material observed on the floor of the annulus space in a region that had not previously been inspected (WRPS-PER-2012-1363). The annulus Continuous Air Monitor (CAM) was still operational and was not indicating elevated radiation levels in the annulus region. When the camera from the inspections was recovered. it also did not indicate increased radiation above minimum contamination levels (WRPS-PER-2012-1363). A formal leak assessment team was established August 10, 2012 to review tank 241-AY-102 construction and operating histories and to determine whether the material observed in the annulus had resulted from a leak in the primary tank. The team consisted of individuals from Engineering. Base Operations and Environmental Protection. As this was a first-of-its-kind task. a method for obtaining a sample of the material in the annulus was needed. The consistency of the material was unknown.and the location of a majority of the material was not conducive to using the sampling devices that were currently available at Hanford. A subcontractor was tasked with the development fabrication.and testing of a sampling device that would be able to obtain multiple samples from the material on the annulus floor. as well as the material originating from a refractory air-slot near the floor of the annulus space. This sampler would need to be able to collect and dispense the material it collected into a sample jar retrieval device for transportation of the material to the 222-S laboratory on the Hanford site for analysis. The subcontractor agency fabricated a remote underground sampler by modifying off-the-shelf robotics and parts. Limited testing of the sampler was conducted using a mock-up of the tank annulus and one simulated material type -a salt block. The mock-up testing indicated that the sampler would be able to maneuver within the confined space and that the device worked with full functionality. A total of six weeks had passed from initiation to implementation of the new sampler in the 241-AY-102 tank annulus. Initial sample material was obtained from the annulus floor using the Off-Riser Sampler System that has been used at Hanford tor years to obtain material from the primary tanks. This could be used at the location near Riser 83 since the material was collected directly from the annulus floor and not from a location on the wall or behind a pipe, as was needed from the two locations near Riser 90. After obtaining a small sample of the material on the annulus floor.this sampler sustained terminal damage due to conduit pipes it had to transverse in order to collect and recover material from this location. Several issues were also encountered during deployment of the new sampler into the annulus near Riser 90. These included: Difficulty fitting the sampler down the 12-inch riser into the annulus due to a small tolerance in the size of the sampler; Failure of sampler components and functions during deployment including the camera. pneumatics.and bearing seals; Delays in the field due to supporting equipment issues including cables. cameras. and scaffolding; and, Low recovery of sample material obtained for analysis. The complications that occurred during deployment and use of the new sampler during the sampling event ultimately resulted in lower recovery of material from these locations in the annulus than was obtained using the Off-Riser Sampler System and limited the analyses that could be performed for determining the origin of the material. Following completion of the sample analyses and the assessment of its construction history and use. there was a consensus among the leak assessment team members that two of the three materials sampled from the annulus floor region were the result of waste leaking from a breach in the primary tank. The probable leak cause was identified as corrosion at high temperatures in a tank whose containment margins had been reduced due to construction difficulties (RPP-ASMT-53793). A formal Lessons Learned was created concerning designing equipment tor unique purposes under time constraints. This document was published in OPEXShare on May 20. 2013. It highlighted some of the issues that arose with the subcontractor sampler development and provided recommendations to prevent a recurrence should this task need to be performed again in the future. The document can be found at http://msa.hanford.gov/opex/lesson.cfm/2013/5/20/3481/AY-102-Annulus-Sampler-Designing-Equipment-for-Unique-Purposes-under-Time-Constraints/.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Examining Weathering of Magnesite in an Arid Environment: Implications For Jezero Crater

Introduction:Orbiter data indicatethe presence of carbonates in severallocations on the surface of Mars[1],but Jezero crater, landing site of the Perseverancerover,is the only known location where carbonatesap-pear coincident with evidence of fluvialand lacustrineactivity [2].On Earth, carbonates in close proximity to these paleoenvironments mayindicatethe presence of past microbial life,like stromatolites[3], that could re-sult inbiosignatures [2]. However,in other cases,car-bonates can also form throughthe alteration of mafic materialwiththe introductionof carbonic acid[4].Hy-drated magnesites have also been found in evaporative environments along lake shores, and in playas[5,6,7].Correctly interpreting past carbonates on Mars is there-fore critical in the search for past signs of life. In Jezero crater,both thenorthernand western fans haveMg-rich carbonates intermixed with olivine-rich material[8].According to CRISM data, magnesite(MgCO3), along with hydromagnesite(Mg5(CO3)4(OH)2•4H2O), arepotential candidatesfor these Mg-carbonates [2]. Considering the spatial con-text with olivine,there aremultiplepotential explana-tions for the presence ofMg-carbonatesin this locationincludingin-situformation via alterationof olivine-rich materialwith carbonic acid,transportationfrom farther up in the watershed, or precipitation of lacustrine car-bonates[2]. The formation of hydromagnesite rather than magnesite is favored when Mg2+saturated solutions have a high CO32-/HCO3-ratio, which, on Earth, is thought to be caused byinflow of groundwater [4]. Additionally, Mg-carbonates tend to precipitate under high pH condi-tions and are unstable at lower pH conditions [5]. Hy-dromagnesite is stable at atmospheric CO2pressure and temperature conditions common to most Earth surface environments [9]. However, it is subject to transfor-mation to magnesite after dehydration and concomitant brucite formation or dissolution and reprecipitation [10].Previousresearch suggests that hydrated car-bonates, including hydromagnesite, can formas weath-ering productsof mafic minerals in the presenceof H2O and CO2in subfreezing temperatures and would not de-hydrate under Martian atmospheric conditions [11,12].It is critical to understand the formation conditions of Mg-carbonatesbecause of the different implications for the past history of Martian environments. Therefore, in this work we are investigating the weathering of Mg-carbonatesin arid environments to helpbetter understand Mg-carbonates in Jezero crater. Study Area:The Ala-Mar Mines(East and West)near Ely, NVare the site ofmultiple magnesitedepositsfound within a calcareous tuff formationthat overlies Tertiary aged volcanic rocks.Here,magnesiteis formed via the alteration of the calcareous tuff and occurs innodules, veins,and lenses[13]. Previous work suggests magnesite deposits are associated with faults [13]. Within the West Mine, magnesite can be found in two maincontexts: (1) relatively circular zones of cauli-flower-like material found within (2) a more massivelensthat is heavily fractured on the surface.Methods.Samplesof both the cauliflower texture and more massive materialwere collectedat Ala Mar West Mine. Both samples were thenpowdered, sieved and analyzed with an inXitu Terra Portable XRD. The program QualX was used to identify potential mineral phases [14].Both samples were also optically inspected using 10x and 20x hand lenses.Figure 1. XRD patterns for the cauliflower magnesite (top) and massive magnesite (bottom). Ongoing and future work on the samples discussed above includes scanning electron microscopy (SEM), electron microprobe analysis (EMPA), and near-infra-red spectroscopy to determine whether hydromagnesite is present. Separation and analysis of the clay-size frac-tionby XRD will helpto better identify any phyllosili-cate phases present. Results and Discussion:Both textures are a white to light tan with a porcelain luster on weathered sur-faces, along with minor iron staining in some areas. Likewise, both textures are white with a porcelain luster on fresh surfaces. When broken apart, the massive mag-nesite shows macroscopic crystals, unlike the cauli-flower magnesite. XRD analysis shows that both samples have high concentrationsof magnesite with lesser amounts of thecarbonatemineral huntite(Mg3Ca(CO3)4; Figure1).The more massive samplecontainsa serpentine-groupmineral,with lizardite being apotential candidate. The cauliflower sample has several minor peaks that may correspond to hydromagnesite(Figure 1), although more work is needed to confirm this.Additionally, thecauliflower deposits closely resemble hydromagnesite deposits found in southwestern Turkey, formed via mi-crobialites[15].As such, it is likely that moreaqueous alterationor weatheringis occurring at the locations where the cauliflower magnesite is present. However, additional field work will need to be conducted to con-firm this hypothesis. Conclusions and Future Work:Future work will include field mapping of fault locations andadditional samplingof the different magnesite types as well as of the calcareous tuffmaterial.We will also look specifi-cally for potential weathering products of magnesite in this arid location, which may yield important insight into the Mg-carbonates located in Jezero crater. XRD analyses on aPANalytical XRDusing non-ambient stages will be used to investigate the stability of hydro-magnesiteat different humiditiesand temperatures, which has implications for samples to bereturned to Earth in the future. Additionally, thermal and evolved gas analysis of magnesite and hydromagnesite will be compared to results from Gale Craterto help interpret the mineralogy inthat location[16]. The results of this research will further ourunderstanding of carbonate for-mationin volcanic settingsandtheirweathering pro-cessesin arid environments. Acknowledgments:We acknowledge funding for this research from Jacobs Technology at the Johnson Space Center.We would also like to thank Ngoc Luu, Christopher Adcock, Richard Allanson, and the rest of the UNLV Soil Science Teamfor their continued sup-portwith troubleshooting and otherlab work. References:[1] Ehlmann, B.L., and Edwards, C.S. (2014) Annual Review of Earth and Planetary Sci., 42, 291–315. [2] Horgan, B.H.N., et al. (2020) Icarus, 339, 113526. [3] Bosak, T., et al. (2013) Annual Review of Earth and Planetary Sci, 41, 21–44. [4] Pohl, W.L. (1989) Gebriider Borntraege, 28, 1-13. [5] Müller, G., et al. (1972) Die Naturwissenschaften, 59, 158–164. [6] Walter, M.R., et al. (1973) Journal of Sedimentary Pe-trology, 43, 1021–1030. [7] Braithwaite, C.J.R., and Zedef, V. (1994) Sedimentary Geology, 92, 1–5. [8] Goudge, T.A., et al. (2015) JGR: Planets, 120, 775–808. [9] Langmuir, D. (1965) Journal of Geology, 73, 730–754. [10] Zhang, P., et al. (2000) Applied Geo-chem., 286, 1748–1753. [11] Calvin, W.M., et al. (1994) JGR, 99, 14659-14675. [12]Russell, M.J., et al. (1999) Journal of the Geological Society of London, v. 156, p. 869–888. [13] Faust, G.T., and Callaghan, E. (1948) GSA Bulletin, 59, 11–74. [14] Altomare, A., et al. (2015) J. of Applied Crystallography, 48, 598–603. [15] Zedef, V.,et al. (2000) Economic Geology, 95, 429–445. [16] Leshin, L.A. et al., (2013) Science, 341, 1–9

A W Provow↗

Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization

Objective: The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interoperability across different institutions due to coding differences. We propose a Multiview Incomplete Knowledge Graph Integration (MIKGI) algorithm to integrate information from multiple sources with partially overlapping EHR concept codes to enable translations between healthcare systems. Methods: The MIKGI algorithm combines knowledge graph information from (i) embeddings trained from the co-occurrence patterns of medical codes within each EHR system and (ii) semantic embeddings of the textual strings of all medical codes obtained from the Self-Aligning Pretrained BERT (SAPBERT) algorithm. Due to the heterogeneity in the coding across healthcare systems, each EHR source provides partial coverage of the available codes. MIKGI synthesizes the incomplete knowledge graphs derived from these multi-source embeddings by minimizing a spherical loss function that combines the pairwise directional similarities of embeddings computed from all available sources. MIKGI outputs harmonized semantic embedding vectors for all EHR codes, which improves the quality of the embeddings and enables direct assessment of both similarity and relatedness between any pair of codes from multiple healthcare systems. Results: With EHR co-occurrence data from Veteran Affairs (VA) healthcare and Mass General Brigham (MGB), MIKGI algorithm produces high quality embeddings for a variety of downstream tasks including detecting known similar or related entity pairs and mapping VA local codes to the relevant EHR codes used at MGB. Based on the cosine similarity of the MIKGI trained embeddings, the AUC was 0.918 for detecting similar entity pairs and 0.809 for detecting related pairs. For cross-institutional medical code mapping, the top 1 and top 5 accuracy were 91.0% and 97.5% when mapping medication codes at VA to RxNorm medication codes at MGB; 59.1% and 75.8% when mapping VA local laboratory codes to LOINC hierarchy. When trained with 500 labels, the lab code mapping attained top 1 and 5 accuracy at 77.7% and 87.9%. MIKGI also attained best performance in selecting VA local lab codes for desired laboratory tests and COVID-19 related features for COVID EHR studies. Compared to existing methods, MIKGI attained the most robust performance with accuracy the highest or near the highest across all tasks. Conclusions: The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.

Zhou, Doudou↗

Accelerated Lifetime Testing of Main Shaft Seals for Tidal Turbine Rotors

This document will briefly discuss the observations and results from an NREL conducted accelerated lifetime testing of the main shaft seal for the Verdant Power fifth generation Gen5 underwater Tidal Energy Converter (TEC) turbine, which successfully performed at the RITE project in 2020-2021. In order to evaluate a 5-year Service Interval ( SI) for this component, testing at NREL operated the main shaft seal nearly continuously for over 135 (text says 130 days on page 5 and 125 days on page 7 and 137 days on page 11) days at a rotational velocity of 160 rpm while the test stand recorded water pressure, barrier fluid pressure, temperature, and number of cycles., representing ~ 40% of the SI. An additional separate test was conducted to measure the aging behavior of the rubber drive rings. The water pressure reservoir was held constant as 29 psi. Barrier fluid pressure remained relatively constant throughout the duration of the test but was seen to sink to as low as 10.1 psi. No barrier fluid leakage was observed throughout the test. A sudden failure occurred within the seal after the power to test machine was interrupted for a scheduled building maintenance procedure. Upon restarting, the main shaft seal lost all ability to prevent water ingress. The exact cause is not known but is believed to be either a seal assembly issue or a change in the alignment of the seal components during or following the power outage. Following seal disassembly, significant wear was seen on one of the graphite sealing rings. Based on these results it is recommended that a follow-on TEAMER be conducted to rectify protocol and assembly issues to further evaluate SI of this component. The support and participation of Verdant Power Inc, Dovetail Solutions LLC and Garlock Manufacturing Inc were instrumental in understanding the results. NREL thanks them for their significant effort.

13 HYDRO ENERGY↗

Integration of performance assessments and 3116 basis documents within the Savannah River Site liquid waste facilities - 15375

The end of the Cold War has left a legacy of over 136 million liters (36 million gallons) of radioactive waste in the aging waste tanks at the Department of Energy's Savannah River Site (SRS). A robust program is in place to remove waste from these tanks, treat the waste to separate it into a relatively small volume of high-level waste and a large volume of low-level waste, and to actively dispose of the low-level waste on-site. This process allows the US Department of Energy (DOE) to move forward with closure of the cleaned waste tanks and associated ancillary structures. To support performance-based, risk decision making for closure and disposal activities, three individual performance assessments (PAs) have been developed - salt-stone Disposal Facility, F-Tank Farm and H-Tank Farm. In addition, three Waste Determinations (WDs) have been made by the Secretary of Energy, in consultation with the Nuclear Regulatory Commission (NRC), under the authority of Section 3116 of the Ronald W. Reagan National Defense Authorization Act for Fiscal Year 2005 (NDAA Section 3116). To support these waste determination decisions, individual '3116 Basis Documents' were developed that describe the assumptions and conditions under which the criteria outlined in NDAA Section 3116 are met. The development of each of the PAs represented a long and arduous effort that involved the development of both deterministic and probabilistic conceptual models of the facilities, the development of assumptions and associated ranges, uncertainty and sensitivity analyses, model data collection and analyses, writing of the actual performance assessment, internal and external peer reviews, and ultimately approval by DOE. Similarly, the development of the 3116 Basis Documents represents similar time and financial commitments. At the end of these efforts, after years of preparation and millions of dollars in investment, we have thousands of pages of highly technical text, tables of data and hundreds of graphs and charts all contained in a series of thick binders that fit neatly on the shelf of a bookcase. We were done - right? Actually, we were just getting started. Performance Assessments and 3116 Basis Documents are living documents that shape day-to-day and long-term decision making in the operation of a low-level waste disposal facility (e.g., salt-stone Disposal Facility) or in area closure activities (e.g., F-Tank Farm or H-Tank Farm). Although these documents do not contain specifically described requirements per se, they do utilize specific assumptions that, if changed significantly, could result in no longer being able to demonstrate that there is reasonable assurance that the required performance objectives or the criteria from NDAA Section 3116 can be met. Savannah River Remediation LLC (SRR), the contractor responsible for Liquid Waste operations at SRS, has not only developed the PAs and 3116 Basis Documents to support this work and shepherded these documents through the DOE approval process, but has also developed the processes and procedures to ensure the successful implementation and integration of these documents into day-to-day decision making within the associated facilities. This paper describes these processes, including the Un-reviewed Waste Management Question process and the PA Maintenance process, and provides specific examples of their successful implementation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Deep PDF parsing to extract features for detecting embedded malware.

The number of PDF files with embedded malicious code has risen significantly in the past few years. This is due to the portability of the file format, the ways Adobe Reader recovers from corrupt PDF files, the addition of many multimedia and scripting extensions to the file format, and many format properties the malware author may use to disguise the presence of malware. Current research focuses on executable, MS Office, and HTML formats. In this paper, several features and properties of PDF Files are identified. Features are extracted using an instrumented open source PDF viewer. The feature descriptions of benign and malicious PDFs can be used to construct a machine learning model for detecting possible malware in future PDF files. The detection rate of PDF malware by current antivirus software is very low. A PDF file is easy to edit and manipulate because it is a text format, providing a low barrier to malware authors. Analyzing PDF files for malware is nonetheless difficult because of (a) the complexity of the formatting language, (b) the parsing idiosyncrasies in Adobe Reader, and (c) undocumented correction techniques employed in Adobe Reader. In May 2011, Esparza demonstrated that PDF malware could be hidden from 42 of 43 antivirus packages by combining multiple obfuscation techniques [4]. One reason current antivirus software fails is the ease of varying byte sequences in PDF malware, thereby rendering conventional signature-based virus detection useless. The compression and encryption functions produce sequences of bytes that are each functions of multiple input bytes. As a result, padding the malware payload with some whitespace before compression/encryption can change many of the bytes in the final payload. In this study we analyzed a corpus of 2591 benign and 87 malicious PDF files. While this corpus is admittedly small, it allowed us to test a system for collecting indicators of embedded PDF malware. We will call these indicators features throughout the rest of this report. The features are extracted using an instrumented PDF viewer, and are the inputs to a prediction model that scores the likelihood of a PDF file containing malware. The prediction model is constructed from a sample of labeled data by a machine learning algorithm (specifically, decision tree ensemble learning). Preliminary experiments show that the model is able to detect half of the PDF malware in the corpus with zero false alarms. We conclude the report with suggestions for extending this work to detect a greater variety of PDF malware.

99 GENERAL AND MISCELLANEOUS↗

Tracking DO 2 with Compensatory Reserve during Whole Blood Resuscitation in Baboons

Background Hemorrhagic shock can be mitigated by timely and accurate resuscitation designed to restore adequate delivery of oxygen (DO 2 ) by increasing cardiac output (CO). However, standard care of using systolic blood pressure (SBP) as a guide for resuscitation has proven ineffective and can be associated with increased morbidity. We have developed a novel vital sign called the compensatory reserve (CRM) generated from analysis of arterial pulse waveform feature changes that has been validated in experimental and clinical models of hemorrhage. We tested the hypothesis that thresholds of DO 2 could be accurately defined by CRM while avoiding over resuscitation during whole blood resuscitation following a 25% hemorrhage in non‐human primates. Methods To accomplish this, adult male baboons (n=12) were exposed to a progressive controlled hemorrhage that resulted in an average (± SD) maximal reduction of 601 ± 18 ml of their estimated circulating blood volume of 1,262 ± 64 ml based on body weight. Values of DO 2 were calculated as the product of CO times O 2 carrying capacity of hemoglobin (i.e., Hb content × 1.34). Results Average (± SD) CRM increased from 6 ± 5 % at the end of hemorrhage to 70 ± 7 % at the end of resuscitation. DO 2 of 12.1, 10.3, and 7.0 ml O 2 ·kg −1 ·min −1 were calculated at 0% (baseline), 12.5% and 25% blood loss. By linear regression, CRM values of 6% (decompensation), 35%, and 68% corresponded to calculated DO 2 values of 6.0, 9.2, and 12.1 ml O 2 ·kg −1 ·min −1 during resuscitation. As such, return of CRM to baseline during resuscitation with only ~ 450 ml provided adequate DO 2 (12.5 ml O 2 ·kg −1 ·min −1 ) while total blood volume replacement (~600 ml) resulted in over resuscitation as indicated by an average increase in SBP (+17 mmHg) and CO (+0.1 L/min) over baseline values. Conclusion Consistent with our hypothesis, thresholds of DO 2 were associated with specific CRM values. A target resuscitation CRM value of 70% minimized the requirement for whole blood, while avoiding over resuscitation. Furthermore, CRM at 0% provided a noninvasive metric for determining critical DO 2 at approximately 5.4 ml O 2 ·kg −1 ·min −1 . Support or Funding Information This research was supported in part by appointment of Ms. Koons to the Postgraduate Research Fellowship Program at the US Army Institute of Surgical Research administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and USAMRMC. Study funding was provided by a grant from the US Army Combat Casualty Care Research Program (D‐009‐2014‐USAISR). Linearregression of the relationship between DO 2 and compensatory reserve during whole blood resuscitation in baboons. Data are expressed as mean ± SE. image Linearregression of the relationship between DO 2 and compensatory reserve during whole blood resuscitation in baboons. Data are expressed as mean ± SE. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Koons, Natalie Jane↗

In-Lab Rapid Analytical Detection of Lunar Volatiles By Universal Gas Analyzer With Comparison to GC-MS System

Introduction: The curation of permanently shadowed regions (PSRs) [1] on the lunar surface is centered around studies based upon the observed volatiles from the LCROSS mission [2]. The rapid detection of important volatile gases and vapors present in planetary bodies and Astromaterials by a standalone analytical device is an area of intense research interest in our group and Planetary Exploration & Astromaterials Research Laboratory (PEARL) facility and this work is relevant to the future preparation of viable lunar simulants for testing curation efforts down the road. The groundbreaking results obtained from the LCROSS Mission [2] open the requirements for the direct detection of volatiles present in regolith materials collected from the lunar surface. The mass spectrometry of volatile chemicals is a general technique that utilizes a set of instruments that creates charged ions from a gaseous chemical species and measures the intensities vs. mass-to-charge ratio (m/z) [3]. In this context, we discuss in-lab experimental results and procedures for rapid qualitative analysis of main LCROSS volatiles (water, H2S, NH3, CO2, and CH3OH) by a Universal Gas Analyzer (UGA) instrument. Additionally, the instrument performance was evaluated by measuring the isotopic abundance ratio of atmospheric Ar-40 to Ar-36 present in room air since, argon is a relevant gas in planetary studies as it can provide an insight and reference point to isotope studies [4]. Additional, cross comparisons were attempted and made between the two instruments to develop a robust analytical technique by comparing mass spectral data for H2S headspace samples with a Trace-1310/ ISQ 7000 (ThermoFisher Scientific.) GC-MS system. Background: The benchtop UGA System is equipped with an SRS UGA 300 quadrupole mass spectrometer designed and built by Stanford Research Systems [5]. This system can be configured for several types of gaseous chemical analysis. The inlet line continuously samples gases at low flow rates (several milliliters per minute) through a capillary limiting the intake pressure making the instrument ideal for online analysis of select gases and/or room atmosphere. Moreover, in our current UGA system, a change in composition at the inlet can be detected in about 200 milliseconds and a complete spectrum is acquired (for a range of 1-100 amu) in under 45 sec with masses measured at rates up to 25 msec per point [5]. This system provides a quick upstream analytical data that we can then compare to results obtained by our GC-MS system. Sample Preparation: Small volume (2-4 mL) of analyte sample was taken in a 10 mL glass vial and sealed with a crimped cap and purged with pure Ar or N2 gas to displace air from the top. The headspace sample was scanned by the UGA instrument at analog, histogram, and pressure vs. time modes. The isotopic abundance ratio for 40Ar-to-36Ar was estimated by measuring partial pressure vs. time scans and setting the mass at 40 and 36 respectively. Results and Discussions: In this work, we have investigated the applicability of the UGA system by qualitative analysis of a series of LCROSS volatiles measured individually. Fig. 1 demonstrates a set of vertically offset spectra for the partial pressures measured as a function of mass-to-charge (m/z) ratios. The average acquisition time for each spectrum was less than a minute suggesting that the UGA system is ideal for quick analysis of geochemical volatiles. For the cross-comparison, we analyzed an H2S headspace sample by a Trace-1310/ISQ-7000 system and compared mass spectral data with previously measured UGA histogram scan data (Fig. 2). In both cases, major peak positions are the same, however, the intensities of fragment ions ([1H132S]+ and [32S]+) are higher for UGA suggesting that the fragment ionization process is stronger in UGA compared to that of GC-MS. To investigate how the integrated area under each chromatogram varies with the headspace sample volume, a set of five H2S headspace samples with increasing volumes was analyzed by the GC-MS system (Fig. 3, inset). A small volume (e.g., 200 to 1000 µL) of H2S/H2O vapor was withdrawn from a 20 mL stock sample vial containing ~5 mL of 0.4% H2S in water by a gas-tight syringe and added to another 20 mL vial filled with argon and analyzed by the GC-MS system. Finally, the UGA detector sensitivity was evaluated by calculating the atmospheric 40Ar-to-36Ar isotopic abundance ratio in room air by running a partial pressure vs. time scan with setting the atomic mass at 40, and 36. Fig. 4(a) shows a ~25 min duration “P vs. time” scan for 40Ar (plot for 36Ar is not shown). The partial pressure values (~100 points) were corrected by subtracting the corresponding background pressure value for 37Ar and utilized to calculate 40Ar-to-36Ar isotopic abundance ratios as shown by Fig. 4b. The average isotopic abundance ratio is ~306 with a 2*STDEV ~13. This abundance ratio is significantly close to the previously reported value of 298.56 [6] and the ratio obtained by our GC-MS system (303 for a UHP grade Ar sample). Conclusions: Our study strongly evidenced that the benchtop UGA system is a valuable analytical tool for the detection of major LCROSS volatiles. The rapid scanning capability, the inexpensiveness of the whole system, and impressive detection sensitivity prove its worthiness as an essential device for advanced geochemical applications. Moreover, cross comparisons with the GC-MS provide important bridges into advanced curatorial efforts into the future. References: [1] Bickel, V.T., et al. (2021) Nat Commun 12, 5607. [2] Colaprete, A., et al. (2010) Science, 330, 463-468. [3] Glavin, D. P. et al. (2012) 2012 IEEE Aerospace Conference, 1-11. [4] Willett, C. D., et al. (2022) Geochimica et Cosmochimica Acta 329, 119-134. [5] Operation Manual and Programming Reference. (2018) Universal gas Analyzers, Stanford Research Systems. [6] Lee, J. Y., et al. (2006) Geochimica et Cosmochimica Acta 70, 4507–4512. Notes: (4 figures are attached with text as shown by the attached file)

Curation↗

Epi Archive: Automated Synthesis of Global Notifiable Disease Data

ObjectiveLANL has built software that automatically collects global notifiable disease data, synthesizes the data, and makes it available to humans and computers within the Biosurveillance Ecosystem (BSVE) as a novel data stream. These data have many applications including improving the prediction and early warning of disease events.IntroductionMost countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health.While most nations likely store incident data in a machine-readable format, governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues1.A survey conducted by LANL of notifiable disease data reporting in over fifty countries identified only a few websites that report data in a machine-readable format. The majority (>70%) produce reports as PDF files on a regular basis. The bulk of the PDF reports present data in a structured tabular format, while some report in natural language.The structure and format of PDF reports change often; this adds to the complexity of identifying and parsing the desired data. Not all websites publish in English, and it is common to find typos and clerical errors.LANL has developed a tool, Epi Archive, to collect global notifiable disease data automatically and continuously and make it uniform and readily accessible.MethodsWe conducted a survey of the national notifiable disease reporting systems notating how the data are reported and in what formats. We determined the minimal metadata that is required to contextualize incident counts properly, as well as optional metadata that is commonly found.The development of software to regularly ingest notifiable disease data and make it available involves three or four main steps: scraping, detecting, parsing and persisting.Scraping: we examine website design and determine reporting mechanisms for each country/website, as well as what varies across the reporting mechanisms. We then designed and wrote code to automate the downloading of the data for each country. We store all artifacts presented as files (PDF, XLSX, etc.) in their original form, along with appropriate metadata for parsing and data provenance.Detecting: This step is required when parsing structured non-machine-readable data such as tabular data in PDF files. We combined the Nurminen methodology of PDF table detection with in-house heuristics to find the desired data within PDF reports2.Parsing: We determined what to extract from each dataset and parsed these data into uniform data structures, correctly accommodating the variations in metadata (e.g., time interval definitions) and the various human languages.Persisting: We store the data in the Epi Archive database and make it available on the internet and through the BSVE. The data is persisted into a structured and normalized SQL database.ResultsThe Epi Archive tool currently contains national and/or subnational notifiable disease data from twenty nations. When a user accesses the Epi Archive site, they are prompted with four fields: country, subregion, disease of interest, and date duration. Upon form submission, a time series is generated from the users’ specifications. The generated graph can then be downloaded into a CSV file if a user is interested in performing personal analysis. Additionally, the data from Epi Archive can be reached through a REST API (Representational State Transfer Application Programming Interface).ConclusionsLANL, as part of a currently funded DTRA effort, is automatically and continually collecting global notifiable disease data. While 20 nations are in production, more are being brought online in the near future. These data are already being utilized and will have many applications including improving the prediction and early warning of disease events.References[1] van Panhuis WG, Paul P, Emerson C, et al. A systematic review of barriers to data sharing in public health. BMC Public Health. 2014. 14:1144. doi:10.1186/1471-2458-14-1144[2] Nurminen, Anssi. "Algorithmic extraction of data in tables in PDF documents." (2013).

Khalsa, Hari S.↗

Search for the rare decay D + → D 0 e + ν e

Using a data set with an integrated luminosity of $2.93\text{ }\text{ }{\mathrm{fb}}^{{-}1}$ collected at $\sqrt{s}=3.773\text{ }\mathrm{GeV}$ with the BESIII detector operating at the BEPCII storage rings, we search for the rare decay ${D}^{+}{\rightarrow}{D}^{0}{e}^{+}{{\nu}}_{e}$. No signal events are observed. We set the upper limit on the branching fraction for ${D}^{+}{\rightarrow}{D}^{0}{e}^{+}{{\nu}}_{e}$ to be $1.0\times{}1{0}^{{-}4}$ at the 90% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

AI Model Benchmarking for Nonproliferation Applications: Steel Thread Benchmarking Task Force Technical Report (Rev. 2)

Steel Thread is a NA-22 venture that seeks to build trustworthy, reliable AI models that can be used in a wide variety of nonproliferation tasks. A key aspect of building these models is developing appropriate benchmarks and evaluation methods, which will enable the venture to identify and adapt models to provide the most value in the nonproliferation domain. Benchmarks must be relevant to key tasks in this domain, such as question answering, information retrieval, document summarization and classification, consensus analysis, and image and data analysis. This report 1) provides an overview of benchmark design, evaluation, and challenges; 2) reviews a variety of open benchmarks, with a focus on language models and tasks; and 3) identifies benchmarks that are most relevant to Steel Thread. This report is intended to serve as a basis for further efforts to classify and evaluate benchmarks and their correlation with success on nonproliferation-specific tasks. The Steel Thread venture has defined benchmarks to be a particular combination of a dataset (or datasets) and a metric (or metrics) conceptualized as representing one or more specific tasks or sets of abilities for a specific modality. It is adopted by a research community as a shared framework for comparing methods.1 It includes 1) Data: Labeled (a designated subset not used for training, which could be all the data), 2) Metric: A way to quantify performance, 3) Task/Ability: What the benchmark is testing, 4) Protocol: A structured and repeatable evaluation process, 5) Baseline/Reference Model: For comparison; could be statistical, rule-based, SME-derived, or another model, and 6) Maintenance Plan: to update with new information over time; important for long-term utility. For further clarity, the definition includes what a benchmark, in this context, is not. It is not a corpus of training data, specific to a model (it is intended to apply to a range of models), a universal evaluation of performance, a guarantee that the ‘top’ model on the leaderboard will be the best fit for every specific use case, an all-encompassing proof of a model’s universal quality, nor is it a one-size-fits-all measure of success. It does not cover every real-world constraint (like operational, ethical, or cost considerations), a systems integration test, or a unit test. This definition was inspired by and resulted from discussions within the Steel Thread Benchmarking Task Force. This group was formed to define what we would mean as a benchmark within Steel Thread but persisted as the need to develop a thorough understanding of the large and expanding existing benchmarking space. This technical report is a result of the group’s divide and conquer approach to exploring this space. The release of benchmarks might not be progressing as quickly as model development, but it is moving very fast, as many benchmarks quickly become saturated, when state-of-the-art models score so close to the benchmark’s ceiling that their results are virtually indistinguishable. At that point, the test no longer differentiates between new systems, so researchers usually stop reporting scores as the benchmark no longer informs about improvements from the next generation of models. In the OpenAI announcement of GPT-5, they reported results on six flagship public benchmarks (AIME 2025, SWE-bench Verified, Aider Polyglot, MMMU, HealthBench Hard, GPQA) but the full system-card covers roughly thirty-five separate evaluations, comprising hundreds of test task items in total. There have been some efforts to summarize benchmarks in specific fields, like for text-to-image generation, but these surveys have had a narrow methodology scope. Therefore, a comprehensive survey of all benchmarks or even all benchmarks that could be relevant to Steel Thread is outside of the scope of this report. We chose some specific benchmarks to investigate in detail.

97 MATHEMATICS AND COMPUTING↗

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗