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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A comprehensive guide to CAN IDS data and introduction of the ROAD dataset

Although ubiquitous in modern vehicles, Controller Area Networks (CANs) lack basic security properties and are easily exploitable. A rapidly growing field of CAN security research has emerged that seeks to detect intrusions or anomalies on CANs. Producing vehicular CAN data with a variety of intrusions is a difficult task for most researchers as it requires expensive assets and deep expertise. To illuminate this task, we introduce the first comprehensive guide to the existing open CAN intrusion detection system (IDS) datasets. We categorize attacks on CANs including fabrication (adding frames, e.g., flooding or targeting and ID), suspension (removing an ID’s frames), and masquerade attacks (spoofed frames sent in lieu of suspended ones). We provide a quality analysis of each dataset; an enumeration of each datasets’ attacks, benefits, and drawbacks; categorization as real vs. simulated CAN data and real vs. simulated attacks; whether the data is raw CAN data or signal-translated; number of vehicles/CANs; quantity in terms of time; and finally a suggested use case of each dataset. State-of-the-art public CAN IDS datasets are limited to real fabrication (simple message injection) attacks and simulated attacks often in synthetic data, lacking fidelity. In general, the physical effects of attacks on the vehicle are not verified in the available datasets. Only one dataset provides signal-translated data but is missing a corresponding “raw” binary version. This issue pigeon-holes CAN IDS research into testing on limited and often inappropriate data (usually with attacks that are too easily detectable to truly test the method). The scarcity of appropriate data has stymied comparability and reproducibility of results for researchers. As our primary contribution, we present the Real ORNL Automotive Dynamometer (ROAD) CAN IDS dataset, consisting of over 3.5 hours of one vehicle’s CAN data. ROAD contains ambient data recorded during a diverse set of activities, and attacks of increasing stealth with multiple variants and instances of real (i.e. non-simulated) fuzzing, fabrication, unique advanced attacks, and simulated masquerade attacks. To facilitate a benchmark for CAN IDS methods that require signal-translated inputs, we also provide the signal time series format for many of the CAN captures. Our contributions aim to facilitate appropriate benchmarking and needed comparability in the CAN IDS research field.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Anoxia begets anoxia: A positive feedback to the deoxygenation of temperate lakes

Abstract Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep‐water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time‐series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656‐lake dataset. Likewise, we found further support for these relationships by analyzing time‐series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake‐specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high‐phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Space processing float zone thermal analysis

Thermal analysis (BETA) computer program adaptations were prepared to analyze phase change histories in crystal specimens. The first program (BETA-CYL) treats right circular cylinder configurations and the second, more general, program (BETA-BOR) treats a generalized body-of-revolution configuration. A series of computer runs were made for silicon material to determine boundary conditions which produce flat solidification interfaces while, at the same time, minimizing peak temperatures in the molten zone. Flat solidification interfaces are a goal believed by some investigators to be required to produce high quality semiconductor materials. The thermal effects of convection in a molten zone were examined and found to be negligible in comparison to the conduction heat transfer of the melt.

Pogson, J. T.↗
NASA NTRS1935

Spinning characteristics of wings II : rectangular Clark Y biplane cellule: 25 percent stagger; 0 degree decalage; gap/chord 1.0

General methods of theoretical analysis of airplane spinning characteristics have been available for some time. Some of these methods of analysis might be used by designers to predict the spinning characteristics of proposed airplane designs if the necessary aerodynamic data were known. The present investigation, to determine the spinning characteristics of wings, is planned to include variations in airfoil sections, plan forms, and tip shapes of monoplane wings and variations in stagger, gap, and decalage for biplane cellules. The first series of tests, made on a rectangular Clark Y monoplane wing, are reported in reference 1. That report also gives an analysis of the data for predicting the probable effects of various important parameters on the spin for normal airplanes using such a wing. The present report is the second of the series. It gives the aerodynamic characteristics of a rectangular Clark Y biplane cellule in spinning attitudes and includes a discussion of the data, using the method of analysis given in reference 1.

Bamber, M J↗
NASA NTRS2005

X-Ray Emission from "Uranium" Stars

The project aims to secure XMM observations of two targets with extremely low abundances of the majority of heavy elements (e.g., log[Fe/H] $\sim$-4), but that show absorption lines of uranium. The presence of an r-process element such as uranium requires a binary star system in which the companion underwent a supernova explosion. A binary star system raises the distinct possibility of the existence of a compact object, most likely a neutron star, in the binary, assuming it survived the supernova blast. The presence of a compact object then suggests X-ray emission if sufficient matter accretes to the compact object. The observations were completed less than one year ago following a series of reobservations to correct for significant flaring that occurred during the original observations. The ROSAT all-sky survey was used to report on the initial assessment of X-ray emission from these objects; only upper limits were reported. These upper limits were used to justify the XMM observing time, but with the expectation that upper limits would merely be pushed lower. The data analysis hinges critically on the quality and degree of precision with which the background is handled. During the past year, I have spent some time learning the ins and outs of XMM data analysis. In the coming year, I can apply that learning to the analysis of the 'uranium' stars.

Schlegel, Eric↗
NASA NTRS2010

Terrestrial Hydrological Data from NASA's Hydrology Data and Information Services Center (HDISC): Products, Services, and Applications

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. The North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) have been generating a series of land surface states (soil moisture, snow, and temperature) and fluxes (evapotranspiration, radiation, and heat flux) variables. These data, hosted at and available from NASA s Hydrology Data and Information Services Center (HDISC), include the NLDAS hourly 1/8 degree products and the GLDAS 3-hourly 0.25 and 1.0 degree products. HDISC provides easy access and visualization and analysis capabilities for these products, thus reducing the time and resources spent by scientists on data management and facilitating hydrological research. Users can perform spatial and parameter subsetting, data format transformation, and data analysis operations without needing to first download the data. HDISC is continually being developed as a data and services portal that supports weather and climate forecasts, and water and energy cycle research.

Fang, Hongliang↗
DOE OSTI2020

Dynamic PRA-Based Estimation of PWR Coping Time Using a Surrogate Model for Accident Tolerant Fuel

In this study, we propose an interpolation-based response surface surrogate methodology to manage a large number of scenarios in dynamic probabilistic risk assessment. It adopts the shape Dynamic Time Warping algorithm to cluster the interpolation neighborhood from time series sample data. The interpolation method was adapted from Taylor Kriging to allow a reduced-order model of the Taylor series. In order to demonstrate its applicability to complex issues in risk assessment for nuclear engineering, an example risk response surface to estimate emergency core cooling system (ECCS) criteria for triplex silicon carbide (SiC) accident-tolerant fuel was constructed. The response surface was exploited to estimate the cumulative failure probability of the fuel cladding structure due to the uncertainties in operator actions and safety systems. The functional failures were assessed based on a combination of individual layer failures computed by coupling Risk Analysis Virtual Environment software with a pressurized water reactor 1000-MW(electric) RELAP5 model and the in-house fuel performance assessment module. Results showed that SiC cladding failure probability spiked less than 1 min after a large-break loss-of- coolant accident whenever the current ECCS criteria for Zircaloy-4 (Zr-4) cladding was used. However, it still provides an increased safety margin of three orders of magnitude compared to Zr-4. This positive margin could be utilized to relax active ECCS requirements by allowing deviations of up to 450 s in its actuation time. The proposed surrogate methodology generated a response surface of SiC cladding failure probability reasonably well, with a significant savings of computation time. This methodology is expected to be useful in the analysis of system response with complex uncertainty sources.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Complexity analysis of a CT injection experiment on BRB

In this work, we use Jensen–Shannon complexity and permutation entropy to analyze the magnetic field fluctuations of an astrophysically scaled plasma experiment. The experiment was intended to emulate an interplanetary coronal mass ejection event in the lab, recreating the major sections seen in satellite data. We also use a technique called “delay,” in which we use select elements, skipping one or more data points at a time, in our time series data to obtain Jensen–Shannon complexity as a function of frequency and investigate the frequency of maximized complexity. We then compare the delay frequencies to other frequencies in the plasma. We found that the frequencies for maximum complexity do not correspond to the frequencies investigated, implying that other physical mechanisms lead to an increase in complexity at these frequencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A Systems Biology Approach to Energy Flow in H 2 Producing Microbial Communities: Microbial Mats

This report describes the results of work conducted at NASA Ames Research Center, in collaboration with investigators at Lawrence Livermore National Laboratory, during the time period 12/15/2014 to 12/15/2017. The work was an extension of a collaboration with LLNL that began in 2008. Work this reporting period focused primarily on tasks related to microbial mats from both the Elkhorn Slough and Baja California field sites, including the analysis and publication of data produced prior to 12/15/2014. During this reporting period, in addition to the microbial mat work, we also conducted a series of experiments with a particular algal-bacterial association (C. sorokiniana and A. brasilense). A number of aspects of this well-characterized algal-bacterial association enabled us not only to further our understanding of interactions between these particular organisms, but to apply that knowledge and techniques to our collection of microorganisms isolated from microbial mats. Microbial mat experiments focused both on intact mat communities and on cultures of organisms isolated from the mats (the Microbial Mat Living Library). In a series of co-culture experiments, we documented both positive and negative interactions amongst heterotrophic and autotrophic isolates of microbial mat microorganisms. One particularly important and novel mat cyanobacterium (ESFC-1) was studied in detail. We developed techniques to pursue an investigation of functional redundancy (the idea that closely related organisms perform identical roles in a community) in cyanobacterial autotrophs in the Elkhorn Slough microbial mat. In those experiments, we documented numerous instances of increases in growth rate between co-cultures of two organisms (relative to their growth rate in isolation) performing what would seem to be identical functional roles. Simplified microbial mat communities consisting of organisms from the Microbial Mat Living Library were constructed and studied in laboratory experiments. The “constructed mats” were grown in standard laboratory glassware and plasticware, but cultures were also combined with artificial materials in an effort to re-create the three-dimensional structure of naturally occurring microbial mats. These constructed mats re-created a number of functions attributable to natural microbial mats (N-fixation, H2-production) and simplified their study using molecular ecological techniques due to the smaller number of microbial “species” present. Cyanobacteria which migrated in response to vertical variations in light intensity (irradiance) obtained characteristic positions in constructed mats that were similar to their positions in natural mats. A detailed investigation of nitrogen cycling in both the Baja California and Elkhorn Slough microbial mats was initiated during this reporting period. The nitrogen cycle in the microbial mats has not been studied in depth, despite the fact that nitrogen usually limits growth in marine environments. The organisms conducting nitrogen cycling in both microbial mats were studied using the genomes available from earlier work on these mats, as well as with a targeted approach using molecular ecological methods developed here. Quantitative measurements of rates of nitrogen transformations were made using stable isotopically labeled nitrogen. The processes quantified and examined using molecular ecological methods included: nitrogen fixation, ammonification, ammonium and nitrate assimilation, denitrification, anaerobic oxidation of ammonium, and dissimilatory nitrate reduction to ammonium. In a series of experiments designed to examine a potential application for microbial mats, we demonstrated that both Elkhorn Slough and Baja California microbial mats were very effective in removing large quantities of both nitrate and ammonium from waste streams containing these compounds at levels where they would be considered to be pollutants. Considerable effort was expended during this reporting period to analyze, and prepare for publication, metagenomes and metatranscriptomes collected from two experimental manipulations of microbial mats. The first, a diel study, was conducted in November 2011, while the second, an investigation of the effects of sulfate on community composition, was conducted during this reporting period. For the earlier study, reference-based and reference-free methods were used to assess microbial ecology and genetic partitioning in these complex microbial systems, and that work is available as a pre-print. Four metagenomes from the same experiment were published. In the second, longer (nearly 200 day) manipulation, rRNA iTag libraries for cDNA and DNA were analyzed to determine the effects of sulfate concentration on microbial mat community composition over the course of the experiment. Work on the algal-bacterial association (Chlorella sorokiniana and Azospirillum brasilense) focused initially on demonstrating the transfer of carbon and nitrogen between the partners, using stable isotopic labeling and the LLNL NanoSIMS. Subsequently, the potential role of diazotrophy (nitrogen fixation) by the bacterial partner in supporting the growth of the association was assessed in a series of experiments. It appears to be the case that, although the bacterial partner demonstrably increases the fitness of the algae under nitrogen limitation, and cells of C. sorokiniana receive nitrogen originally fixed from atmospheric nitrogen by A. brasilense, the amount of nitrogen obtained by diazotrophy is too small to explain the increase in fitness.

08 HYDROGEN↗
NASA NTRS1994

Modulations of stratospheric ozone by volcanic eruptions

We have used a time series of aerosol surface based on the measurements of Hofmann to investigate the modulation of total column ozone caused by the perturbation to gas phase chemistry by the reaction N2O5(gas) + H2O(aero) yields 2HNO3(gas) on the surface of stratospheric aerosols. We have tested a range of values for its reaction probability, gamma = 0.02, 0.13, and 0.26 which we compared to unperturbed homogeneous chemistry. Our analysis spans a period from Jan. 1974 to Oct. 1994. The results suggest that if lower values of gamma are the norm then we would expect larger ozone losses for highly enhanced aerosol content that for larger values of gamma. The ozone layer is more sensitive to the magnitude of the reaction probability under background conditions than during volcanically active periods. For most conditions, the conversion of NO2 to HNO3 is saturated for reaction probability in the range of laboratory measurements, but is only absolutely saturated following major volcanic eruptions when the heterogeneous loss dominates the losses of N2O5. The ozone loss due to this heterogeneous reaction increases with the increasing chlorine load. Total ozone losses calculated are comparable to ozone losses reported from TOMS and Dobson data.

Blanchette, Christian↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
DOE OSTI2026

Integrating very-high-resolution imagery, Sentinel-2 time-series data, and machine learning to map shrub fractional abundance across arid and semi-arid ecosystems in China

Shrub fractional abundance (SFA), the proportion of shrub cover per unit area, serves as a critical indicator of environmental aridity and ecosystem health in arid and semi-arid regions, particularly across the Mongolian steppe. However, large-scale SFA mapping in Mongolian steppe ecosystems remains challenging due to the small crown size of shrubs, their sparse distribution, and spectral overlap with coexisting low vegetation (e.g., grasses and herbs), which hinders accurate detection using coarser-resolution satellite data or traditional field surveys. To address these challenges, we developed a two-step approach that integrates very-high-resolution (VHR) imagery, time-series Sentinel-2 data, and deep learning techniques. First, we generated high-accuracy benchmark maps of individual shrub crowns from 0.5 m VHR imagery by combining manual segmentation with a hybrid deep learning framework (Dino V2 and convolutional neural networks). Second, we used these shrub crown maps as training data to build an XGBoost model for predicting SFA from 20 m Sentinel-2 time-series data, leveraging phenological information to improve estimation. We validated our approach across 70 sites (1km 2 each) in the Inner Mongolia Autonomous Region, which is representative of Mongolian steppe ecosystems. From VHR imagery, we mapped 1.31 million shrub crowns with an accuracy of R 2 = 0.92. Scaling up with Sentinel-2 data yielded regional SFA maps with an R 2 = 0.60. Further SHAP (SHapley Additive exPlanations) analysis on the developed XGBoost model revealed that phenological metrics (particularly observations in early-May, mid-July, and late-September), which distinguish shrub phenology from that of other land cover types (e.g., grasses and bare soil), were the most influential predictors of SFA. Finally, our regional SFA maps uncovered unimodal relationships between shrub distribution and climate variables, peaking at mean annual minimum temperatures near 0 °C and annual precipitation around 200 mm. Collectively, these findings demonstrate how the integration of multi-source remote sensing and machine learning can overcome historical limitations in SFA mapping, enabling accurate, spatially continuous assessments across vast Inner-Mongolian steppe ecosystems. Our framework has the potential to be applied to other steppe ecosystems and dryland ecosystems across the Mongolian steppe and beyond, offering a foundation for improved monitoring and ecological impact assessments in the face of global climate changes.

Arid and semi-arid landscapes↗
NASA NTRS1986

Uniformly high order accurate essentially non-oscillatory schemes 3

In this paper (a third in a series) the construction and the analysis of essentially non-oscillatory shock capturing methods for the approximation of hyperbolic conservation laws are presented. Also presented is a hierarchy of high order accurate schemes which generalizes Godunov's scheme and its second order accurate MUSCL extension to arbitrary order of accuracy. The design involves an essentially non-oscillatory piecewise polynomial reconstruction of the solution from its cell averages, time evolution through an approximate solution of the resulting initial value problem, and averaging of this approximate solution over each cell. The reconstruction algorithm is derived from a new interpolation technique that when applied to piecewise smooth data gives high-order accuracy whenever the function is smooth but avoids a Gibbs phenomenon at discontinuities. Unlike standard finite difference methods this procedure uses an adaptive stencil of grid points and consequently the resulting schemes are highly nonlinear.

Harten, A.↗
NASA NTRS2017

Informing Rodent Behavior in Space: Gene Expression and Hyper-Emotionality Following Prenatal Stress

As space exploration pushes our boundaries further away from Earth and for longer durations, we will inevitably require the use of multi-generational studies to continue our expansion. Space is a stressful environment not only due to the deleterious effect of spaceflight on physiology, but also due to confinement, limited social interactions, inherently dangerous circumstances, and many other stresses of an unknown environment. Stress can alter the brain chemistry, and these alterations can affect behavior at all stages of development, but it is especially pronounced during the perinatal period and can have longstanding effects, even into adulthood, which manifest through augmented brain function and psychopathology. This study investigated the nexus of brain chemistry and brain function by observing behavior of adult rats whose mothers were exposed to unpredictable variable prenatal stress (UVPS) while they were in the womb. The UVPS consisted of strobe light, tube restraint, and white noise, and was administered at unpredictable times of the day and also varied in length, both of which were measures taken to prevent habituation to the stressor. The offspring rats were then allowed to reach adulthood and at 90 days were subjected to a series of behavioral tests including novel object, startle response, and an unknown intruder to quantify the adult rats stress response and anxiety. Here we report these results of the behavioral analysis and correlate adult behavioral measures with the expression of genes involved in the hypothalamic-pituitary-adrenal axis, which modulates the animals stress response. We hypothesized that hyper-expression of genes involved in the HPA axis would correlate with the observed anxiety-like behaviors associated with early stress.

Moyer, E. L.↗
NASA NTRS1988

Reduction and analysis of photometric data on Comet Halley

The discovery that periodic variations in the brightness of Comet Halley were characterized by two unrelated frequencies implies that the nucleus is in a complex state of rotation. It either nutates as a result of the random addition of small torque perturbations accumulated over many perihelion passages, or the jet activity torques are so strong that it precesses wildly at each perihelion passage. To diagnose the state of nuclear rotation, researchers began a program to acquire photometric time series of the comet as it recedes from the sun. The intention is to observe the decay of the comet's atmosphere and then, when it is unemcumbered by the light of the coma, follow the light variation of the nucleus itself. The latter will be compared with preperihelion time series and the orientation of the nucleus at the time of Vega and Giotto flybys and an accurate rotational ephemeris constructed. Halley was observed on 38 nights during 1987 and approximately 21 nights in 1988. The comet moved from 5 AU to 8.5 AU during this time. The brightness of the coma was found to rapidly decrease in 1988 as the coma and cometary activity collapses. The magnitude in April 1988 was 19 mag (visual) and it is predicted that the nucleus itself will be the major contributor to the brightness in the 1988 and 1989 season.

Belton, Michael J. S.↗
DOE OSTI2026

Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem

Giant viruses play crucial ecological roles in aquatic ecosystems, yet their evolutionary dynamics in response to environmental changes, particularly in freshwater environments, are not well understood. We analyzed a 20-year time series (2000-2019) of 471 co-assembled metagenomes from Lake Mendota (USA) to reconstruct 1512 giant virus metagenome-assembled genomes, providing insights into viral genome evolution. Viruses in the order Imitervirales dominate the virome, remaining consistent across seasons and years. Our findings reveal gene duplication (23% of genes) and horizontal gene transfer (29% of genes) as key drivers of genomic innovation. A co-occurrence network analysis indicates increased virus-host interactions following the introduction of an invasive predatory zooplankton in 2009, highlighting potential hosts in Bigyra, Perkinsea, and Euglenozoa. While single nucleotide polymorphism analysis shows predominantly purifying selection in viral genes, there is a significant increase in positively selected genes post-invasion, particularly those related to infection. Comparative evolutionary analyses reveal that giant viruses exhibit genome-wide substitution rates similar to co-occurring bacteria but significantly slower than smaller dsDNA phages, suggesting both stability and adaptability. Our study demonstrates that freshwater giant viruses employ various evolutionary strategies to respond to environmental change. These results underscore their significant yet often underappreciated role in freshwater ecosystem dynamics.

Vasquez, Yumary M↗
DOE OSTI2021

Differences in c-Si Solar Cell Metallization and Susceptibility to Series Resistance Degradation

In this case study, we investigate a degradation mode occurring at the cell level in fielded multi-Si modules. Affected cells in the module show a progressive, series-resistance-related power degradation observed in module- and cell-level IV curves along with EL and PL imaging at the module, cell, and cell core sample scale. SEM and elemental analysis via EDS reveal a difference in the oxides in the silver paste used in screen printing of the finger contacts. This suggests that the cells were screen printed with different silver paste compositions and possibly firing conditions. One of these combinations leads to degradation of the contact at the interface between the cell and contact finger, causing severe series resistance across the cell that continues to progress over time.

acetic acid↗