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At least 361 records · Page 20

Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning

Self-contrastive learning (SCL), a self-supervised learning method, has been shown to improve image and signal classifier accuracies and reduce the training time for neural communications receivers. In particular, prior work has shown that SCL applied as a pre-training step can improve simulated performance of OFDM in 3GPP TDL channel models by reducing the training time of the downstream classification task (demodulation and demapping). In this work a practical implementation demonstrating SCL pre-training using software defined radios (SDRs) is proposed.

Cooke, Corey [ORNL] (ORCID:0000000234263672)↗

4D Multimodal Co-attention Fusion Network with Latent Contrastive Alignment for Alzheimer’s Diagnosis

Multimodal neuroimaging provides complementary structural and functional insights into both human brain organization and disease-related dynamics. Recent studies demonstrate enhanced diagnostic sensitivity for Alzheimer’s disease (AD) through synergistic integration of neuroimaging data (e.g., sMRI, fMRI) with tabular data (e.g., behavioral and cognitive tests). However, the intrinsic heterogeneity across modalities (e.g., 4D spatiotemporal fMRI dynamics vs. 3D anatomical sMRI structure) presents critical challenges for discriminative feature fusion, often leading to information loss or biased fusion. To bridge this gap, we propose M2M-AlignNet: a multimodal co-attention network with latent alignment for early AD diagnosis using sMRI and fMRI. At the core of our approach is a multi-patch-to-multi-patch (M2M) contrastive loss function that quantifies and reduces representational discrepancies via weighted patch correspondence, explicitly aligning fMRI components across brain regions with their sMRI structural substrates without one-to-one constraints. Additionally, we propose a latent-as-query co-attention module to autonomously discover fusion patterns, circumventing modality prioritization biases while minimizing feature redundancy. We conduct extensive experiments to confirm the effectiveness of our method and highlight the correspondence between fMRI and sMRI as AD biomarkers.

Wei, Yuxiang [Georgia Institute of Technology]↗

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

Transgenic Mixed‐Linkage‐Glucan Enhancement Affects Root Characteristics and Decomposition in Soils of Contrasting Vegetation History

ABSTRACT Development of transgenic bioenergy sorghum [ Sorghum bicolor (L.) Moench] with increased contents of mixed‐linkage (1,3;1,4)‐β‐glucan (MLG) is an important step towards enhancing quality of bioenergy feedstocks. Since MLG‐enhancement leads to greater biomass digestibility, our overarching hypothesis is that root residues of MLG‐enhanced plants may be more readily decomposed in the soil, potentially creating new opportunities for optimizing soil carbon (C) sequestration, nutrient cycling, and overall agricultural sustainability. The study examined morphological, chemical, and enzymatic characteristics of fine and coarse roots of four bioenergy sorghum genotypes. Then, we incubated the roots within soils with contrasting vegetation histories while measuring C mineralization, microbial biomass C (MBC), and activity of hydrolytic enzymes and calculating vector length and vector angle enzymatic stoichiometry parameters. The results indicated that MLG‐enhancing transformations increased root total nitrogen (N) contents, decreased C/N ratios, and were associated with higher MLG concentrations in fine than in coarse roots. Incubations with transgenic roots led to 16%–38% higher MBC and 19%–41% lower microbial metabolic quotient (qCO 2 ). While enzyme activity differed markedly among the studied genotypes, it did not directly respond to MLG levels in root tissues. The increase in MBC without concurrent increases in C mineralization or hydrolytic enzyme activities in transgenic genotypes suggests that MLG enhancement promoted microbial anabolic retention of root‐derived C rather than stimulating catabolic decomposition. Enzymatic vector results indicated that these parameters reflect a variety of drivers behind microbial enzyme production, including availability of specific substrates, such as MLG here, and/or deficiency in specific nutrients, such as phosphorus (P). The study confirms the positive impacts from the roots of engineered MLG‐enhanced bioenergy plants on soil microbial activity and highlights the interactive influences on the MLG‐enhancement effects from root size and inherent soil properties.

Mahmoodabadi, Majid [Department of Plant, Soil, an↗

Contrasting coordination of non‐structural carbohydrates with leaf and root economic strategies of alpine coniferous forests

Non-structural carbohydrates (NSCs), as the labile fraction and dominant carbon currency, are essential mediators of plant adaptation to environments. However, whether and how NSC coordinates with plant economic strategy frameworks, particularly the well-recognized leaf economics spectrums (LES) and root economics space (RES), remains unclear. We examined the relationships between NSC and key plant economics traits in leaves and fine roots across 90 alpine coniferous populations on the Tibetan Plateau, China. We observed contrasting coordination of NSC with economics traits in leaves and roots. Leaf total NSC and soluble sugar aligned with the leaf economic spectrum, conveying a trade-off between growth and storage in leaves. However, NSC in roots was independent of the root economic spectrum, but highly coordinated with root foraging, with more starch and less sugar in forage-efficient, thinner roots. Further, NSC-trait coordination in leaves and roots was, respectively, driven by local temperature and precipitation. These findings highlight distinct roles of NSC in shaping the above- and belowground multidimensional economics trait space, and NSC-based carbon economics provides a mechanistic understanding of how plants adapt to heterogeneous habitats and respond to environmental changes.

54 ENVIRONMENTAL SCIENCES↗

Contrasting effects of bioenergy crops on biodiversity

Agriculture is driving biodiversity loss, and future bioenergy cropping systems have the potential to ameliorate or exacerbate these effects. Using a long-term experimental array of 10 bioenergy cropping systems, we quantified diversity of plants, invertebrates, vertebrates, and microbes in each crop. For many taxonomic groups, alternative annual cropping systems provided no biodiversity benefits when compared to corn (the business-as-usual bioenergy crop in the United States), and simple perennial grass–based systems provided only modest gains. In contrast, for most animal groups, richness in plant-diverse perennial systems was much higher than in annual crops or simple perennial systems. Microbial richness patterns were more eclectic, although some groups responded positively to plant diversity. Future agricultural landscapes incorporating plant-diverse perennial bioenergy cropping systems could be of high conservation value. However, increased use of annual crops will continue to have negative effects, and simple perennial grass systems may provide little improvement over annual crops.

09 BIOMASS FUELS↗

Algorithms for Forward and Inverse Problem Solutions in Phase Contrast Tomography

PhaseTorch is a python package that implements algorithms for forward and inverse problem solutions in X-ray phase contrast tomography (XPCT). XPCT is useful to reconstruct the 3D distribution of the refractive index decrement and absorption index of an imaged object. PhaseTorch implements algorithms for simulation, reconstruction, and analysis of XPCT data. PhaseTorch provides algorithms for simulation of XPCT data of an object with known refractive and absorption indices. It contains algorithms for reconstructing the projections of the absorption index and refractive index decrement.

Sridhar, Venkatesh↗

Multiple Environmental Influences on the Lightning of Cold-Based Continental Convection. Part II: Sensitivity Tests for Its Charge Structure and Land–Ocean Contrast

In Part I, an electrification scheme was described and a simulation of an observed cold-based storm from the U.S. Great Plains was validated with electrical observations. Most charge in the storm was separated by rebounding collisions of secondary ice originating from prior graupel–snow collisions. In this Part II, sensitivity tests are performed with the control simulation (Part I) and influences from environmental factors (aerosols, temperature, moisture, and shear) on lightning are elucidated. Environmental factors [e.g., convective available potential energy (CAPE)] controlling updraft speed are salient. When ascent is reduced by 30% and 70%, flashes become 70% fewer and disappear, respectively; faster ascent promotes positive cloud-to-ground (+CGs) flashes. Since cloud base is too cold (1°C) for coalescence, cloud condensation nucleus aerosol concentrations do not influence the lightning appreciably. The electrical response to varying concentrations of active ice nuclei is limited by most ice particles being secondary and less sensitive—a natural “buffer.” Imposing a maritime sounding suggests that the land–sea contrast in lightning for such storms is due to the vertical structure of environmental temperature and humidity. Weak CAPE, and both entrainment and condensate weight from a low cloud base, suppress ascent and charging. Maritime thermodynamic conditions reduce simulated flash rates by two orders of magnitude. Reducing aerosol loadings from continental to maritime only slightly reinforces this suppression. Last, a conceptual model is provided for how any simulated storm is either normal because graupel/hail is mostly positively charged or else is inverted/anomalous because graupel/hail is mostly negatively charged, with environmental factors controlling the charging. Impacts from microphysical processes, including three processes of secondary ice production, on lightning are analyzed.

54 ENVIRONMENTAL SCIENCES↗

Contrast analysis in two-beam laser interference lithography

Interference lithography enables large area, sub-µm, periodic patterning without photomasks or projection lithography tools. We show that optical contrast, which is the fundamental design variable of interference lithography, enforces coupled constraints on source coherence, beam pointing stability, field size, polarization state, and the intensity balance between beams. The analysis enables selection and alignment tolerance of components to meet a specific design requirement. In particular, the analysis reveals that grating beam splitters are significantly less sensitive to beam pointing and polarization misalignment than plate beam splitters.

Miller, David B. (ORCID:0000000207755284)↗

Anomalous contrast in broadband THz near-field imaging of gold microstructures

THz scattering-type scanning near-field microscopy (s-SNOM) has become a powerful technique for measuring carrier dynamics in nanoscale materials and structures. Changes in a material’s local THz reflection or transmission can be correlated to changes in electrical conductivity. Here, we perform tip-based THz nano-imaging of subwavelength gold nanostructures and demonstrate image contrast unrelated to any spatially varying material properties. We show that the specific physical configuration of the gold structures can have a strong influence on local excitations which can obscure the sample’s true dielectric response, even in cases where the relevant structures are far outside of the spatial region probed by the AFM tip.

47 OTHER INSTRUMENTATION↗

Data and scripts associated with "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams."

This data package is associated with the publication "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams." in review at Limnology and Oceanography (Roley et al. 2023). This study focuses on understanding ecosystem metabolism for the Hanford Reach of the Columbia River in Washington state, a free-flowing stretch with a substantial discharge. Large rivers have been overlooked compared to small and medium rivers due to the challenges associated with measurements. Our study presents novel ways to address these challenges and highlights that metabolism patterns in large rivers differ from those observed in small-medium rivers and requires the application of knowledge and tools beyond those implemented for smaller rivers.This data package includes the data and R scripts for the analyses described in Roley et al. 2023. It includes dissolved oxygen and temperature data from a dissolved oxygen HOBO sensor, light data collected from the National Solar Radiation Database (https://nsrdb.nrel.gov/) and hydrologic variables estimated from the MASS-1 model (Niehus et al.; 2014). It also includes metabolism estimates (gross primary production, ecosystem respiration, and net ecosystem production) estimated via streamMetabolizer (Appling et al.; 2018). All analyses in the paper can be replicated with these data and scripts.The data package is comprised of one main data folder. The folder includes (1) file-level metadata (flmd); (2) a data dictionary (dd) for each data file; (3) data files; and (4) R scripts for metabolism estimates and data analysis. All files are .R, .csv, or .pdf.

54 ENVIRONMENTAL SCIENCES↗

X-Ray Radiography and Phase-Contrast Imaging of the Engine Combustion Network Spray B Sprays and Injection

X-ray measurements of diesel sprays from two of the Engine Combustion Network (ECN) Spray B injectors are described. Measurements in these three-hole nozzles complement both visible light measurements of these sprays and previous x-ray measurements of the axial single-hole ECN Spray A injectors. Both axial and lateral motions of the injector needle valve were measured with x-ray phase contrast imaging. Additionally, the liquid mass distribution in room temperature sprays at elevated ambient pressure was determined with x-ray radiography. Measurements of both needle valve motion and spray distribution were performed at both the standard Spray A/B conditions and with selected variations of injection pressure, ambient density, and injection timing. The needle valve motion for the Spray B injectors is quite similar to that of the Spray A injectors, though little lateral motion is seen in either Spray B injector. Compared to the sprays from the Spray A injectors, the sprays from Spray B penetrate more slowly in the near-nozzle region, demonstrate a broader, more uniform distribution in the transverse direction, and are significantly more variable with respect to time. These differences demonstrate the importance of studies with multi-hole nozzles to provide insight into applied diesel combustion.

42 ENGINEERING↗

Development of an Ultrahigh-bandwidth Phase Contrast Imaging System for detection of electron scale turbulence and Gigahertz Radio-Frequency Waves

The study of waves and turbulence is vital to the development of future reactor-grade plasma devices developed in the quest for fusion energy. These fluctuations are responsible for moving heat and particles across the magnetic field, and a predictive understanding of them is needed to achieve the density and temperature required to sustain a plasma fusion reaction. While many techniques have been developed for measuring waves and fluctuations, every measurement method has limitations. There are relatively few techniques for measuring very high frequency fluctuations, such as radio frequency waves injected to heat the plasma, unstable waves driven by suprathermal particles, or short wavelength electrostatic waves driven by electron temperature or density gradients. The present project builds upon the proven phase contrast imaging (PCI) technique to extend the response of the diagnostic by orders of magnitude in frequency and almost a factor of ten in spatial resolution. PCI provides a measurement of electron density based on small angle scattering of a CO-2 laser beam by using optical techniques to render a phase shift as an intensity change on a detector. Due to the telecommunications revolution, technological development by manufacturers has focused on components in the near -infrared, so that high- quality lasers and detectors at 1.55 µm are readily available. Shifting PCI design to a new, shorter wavelength has numerous advantages and challenges. Similar detector performance is available with room-temperature arrays with GHz bandwidth, while the detector arrays for 10.6 µm required liquid nitrogen cooling and were therefore limited to a bandwidth of about 1 MHz. Shifting to a shorter wavelength reduces the angle at which the laser beam scatters off of plasma waves, allowing more such scattered components to pass through the aperture of the vacuum vessel port and be collected by the PCI, which increases the spatial resolution. Concomitant with these benefits, various questions of performance arise. At shorter laser wave- length, the sensitivity to mirror and lens quality is increased, the contribution of the laser to the overall system noise is increased, and the sensitivity to vibrations is increased. The custom optical components at the heart of the PCI technique were required to be properly scaled for the shorter wavelength, so fabrication technologies needed to be explored. This project was designed to show that a low noise, high response PCI system at 1.55 µm could be constructed and operated, and then to quantify potential issues to allow extrapolation to a full-size production system providing physics measurements on a large plasma device. The first stage, producing the custom optical component called a Phase Plate, was successfully achieved using two methods. First, an easily reproduced masking and coating technique was able to produce good phase plates with the required parameters. Second, a nanofabrication technique was found to produce extremely high quality phase plates at a competitive price. The PCI constructed with the new phase plates and 1.55 µm laser was found to provide excellent wavelength measurements with the theoretically expected response. The sensitivity to optical surface quality was found to be in line with previous measurements at 10.6 µm. The observed signal-to-noise ratio was similar to the theoretically expected value. The effect of vibrations on PCI was studied with the first measurement of the effect of beam motion on PCI response and comparison to theory, allowing for a quantitative prediction of the effect of vibrations on a production PCI system and the requirements for improved beam stabilization. PCI is an extremely cost-effective method to provide a low noise, absolutely calibrated measurement of plasma fluctuations across a wide spatial scale. This project has shown that a 1.55 µm PCI using modern techniques and components is less expensive than the 10.6 µm PCI of a few years ago, with the largest savings in phase plate fabrication and the infrared detector array.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transient Deformation in Additively Manufactured 316L Stainless Steel Lattices Characterized with in-situ X-ray Phase Contrast Imaging: The Complete Dataset for Three Geometrical Lattices

Metallic lattice structures are being considered for shock mitigation applications due to their superior mechanical properties, energy absorption capability and lightweight characteristics inherent of the additive manufacturing process. In this study, shock compression experiments coupled to x-ray phase contrast imaging (PCI) were conducted on 316L stainless steel lattices. Meso-scale simulations incorporating the as-built lattice structure characterized by computed tomography were used to simulate PCI radiographs in CTH for direct comparison to experimental data. The methodology presented here offers robust validation for constitutive properties to further our understanding of lattice compaction at application-relevant strain rates.

36 MATERIALS SCIENCE↗

Image processing workflow yielding high contrast synchrotron nanoscale computed tomography data from Ni-YSZ electrodes

The operating lifetime of Ni-YSZ fuel electrodes used in solid oxide electrolysis cells and fuel cells (SOECs and SOFCs) is limited by Ni redistribution, one of the primary degradation mechanisms that must be overcome to extend the longevity and maximize the performance of SOECs and SOFCs. To achieve this, 3D microstructural data is needed to relate both initial performance and performance loss over time to microstructural properties and their evolution throughout operation under various conditions. However, 3D microstructure data remains relatively scarce within the literature due to multiple challenges in acquiring and analyzing such data reliably. This work presents a workflow for acquiring and processing synchrotron X-ray nanoscale computed tomography (nano-CT) data from Ni-YSZ electrodes. Parameters for each step in the nano-CT workflow are described up to the final result (a 3D reconstruction), with particular emphasis on image alignment using freely available software. Following the results of a parametric sweep of the image alignment step, high contrast, low signal-to-noise 3D nano-CT data is obtained with relatively short compute times. While the exact methods best suited to samples with different microstructural qualities, or similar Ni-YSZ nano-CT data obtained from other sources may deviate from the solution found herein, this work also generalizes the decision points and evaluation of each step to provide a starting point to adapt this workflow to other datasets.

08 HYDROGEN↗

Contrasting Community Assembly Forces Drive Microbial Structural and Potential Functional Responses to Precipitation in an Incipient Soil System

Microbial communities in incipient soil systems serve as the only biotic force shaping landscape evolution. However, the underlying ecological forces shaping microbial community structure and function are inadequately understood. We used amplicon sequencing to determine microbial taxonomic assembly and metagenome sequencing to evaluate microbial functional assembly in incipient basaltic soil subjected to precipitation. Community composition was stratified with soil depth in the pre-precipitation samples, with surficial communities maintaining their distinct structure and diversity after precipitation, while the deeper soil samples appeared to become more uniform. The structural community assembly remained deterministic in pre- and post-precipitation periods, with homogenous selection being dominant. Metagenome analysis revealed that carbon and nitrogen functional potential was assembled stochastically. Sub-populations putatively involved in the nitrogen cycle and carbon fixation experienced counteracting assembly pressures at the deepest depths, suggesting the communities may functionally assemble to respond to short-term environmental fluctuations and impact the landscape-scale response to perturbations. We propose that contrasting assembly forces impact microbial structure and potential function in an incipient landscape; in situ landscape characteristics (here homogenous parent material) drive community structure assembly, while short-term environmental fluctuations (here precipitation) shape environmental variations that are random in the soil depth profile and drive stochastic sub-population functional dynamics.

16S amplicon sequencing↗

Control of hydrogen concentrations by microbial sulfate reduction in two contrasting anoxic coastal sediments

Introduction Molecular hydrogen is produced by the fermentation of organic matter and consumed by organisms including hydrogenotrophic methanogens and sulfate reducers in anoxic marine sediment. The thermodynamic feasibility of these metabolisms depends strongly on organic matter reactivity and hydrogen concentrations; low organic matter reactivity and high hydrogen concentrations can inhibit fermentation so when organic matter is poor, fermenters might form syntrophies with methanogens and/or sulfate reducers who alleviate thermodynamic stress by keeping hydrogen concentrations low and tightly controlled. However, it is unclear how these metabolisms effect porewater hydrogen concentrations in natural marine sediments of different organic matter reactivities. Methods We measured aqueous concentrations of hydrogen, sulfate, methane, dissolved inorganic carbon, and sulfide with high-depth-resolution and 16S rRNA gene assays in sediment cores with low carbon reactivity in White Oak River (WOR) estuary, North Carolina, and those with high carbon reactivity in Cape Lookout Bight (CLB), North Carolina. We calculated the Gibbs energies of sulfate reduction and hydrogenotrophic methanogenesis. Results Hydrogen concentrations were significantly higher in the sulfate reduction zone at CLB than WOR (mean: 0.716 vs. 0.437 nM H 2 ) with highly contrasting hydrogen profiles. At WOR, hydrogen was extremely low and invariant (range: 0.41–0.52 nM H 2 ) in the upper 15 cm. Deeper than 15 cm, hydrogen became more variable (range: 0.312–2.56 nM H 2 ) and increased until methane production began at ~30 cm. At CLB, hydrogen was highly variable in the upper 15 cm (range: 0.08–2.18 nM H 2 ). Ratios of inorganic carbon production to sulfate consumption show AOM drives sulfate reduction in WOR while degradation of organics drive sulfate reduction in CLB. Discussion We conclude more reactive organic matter increases hydrogen concentrations and their variability in anoxic marine sediments. In our AOM-dominated site, WOR, sulfate reducers have tight control on hydrogen via consortia with fermenters which leads to the lower observed variance due to interspecies hydrogen transfer. After sulfate depletion, hydrogen accumulates and becomes variable, supporting methanogenesis. This suggests that CLB’s more reactive organic matter allows fermentation to occur without tight metabolic coupling of fermenters to sulfate reducers, resulting in high and variable porewater hydrogen concentrations that prevent AOM from occurring through reverse hydrogenotrophic methanogenesis.

Microbiology↗