Qu-antitative analysis of diffraction by liquids using a pink-spectrum X-ray source
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Singh, Saransh↗
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High-speed quantitative X-ray multi-contrast imaging with deep learning based modulated pattern analysis
The advent of X-ray multi-contrast imaging methods, providing absorption, phase, and dark-field images, holds tremendous promise for complementary and non-destructive visualization of inner structures within materials and bio-samples. However, the low efficiency in measuring and analyzing X-ray modulated patterns has hindered their application in high-resolution in situ imaging. In this work, the Enhanced Scanning Pattern-based Imaging Neural Network (ESPINNet) is introduced as a powerful tool for achieving high-speed, high-resolution quantitative imaging. ESPINNet is faster than correlation-based speckle tracking methods such as XSVT and UMPA, and provides a balanced performance in terms of resolution and speed for data collection by using fewer scanning images. In comparison with our previously developed neural network, ESPINNet introduces the capability to generate dark-field images, further enhancing its versatility. By leveraging scanning patterns, ESPINNet significantly improves resolution and measurement precision. Furthermore, its adaptability to various modulation patterns, including those produced by sandpaper, coded masks, or gratings, ensures broad applicability. These features enable real-time 2D and 3D multi-contrast imaging, positioning ESPINNet as a transformative solution for applications in materials science and biomedical research, particularly for high-speed and in situ measurements.
X-ray at-wavelength metrology↗
Quantitative Evaluation of Reliability Improvement: Case Study on a Self-healing Distribution System
In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility’s historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.
Dong, Jiaojiao↗
CPES-QSM: A Quantitative Method Towards the Secure Operation of Cyber-Physical Energy Systems
Power systems are evolving into cyber-physical energy systems (CPES) mainly due to the integration of modern communication and Internet-of-Things (IoT) devices. CPES security evaluation is challenging since the physical and cyber layers are often not considered holistically. Existing literature focuses on only optimizing the operation of either the physical or cyber layer while ignoring the interactions between them. This paper proposes a metric, the Cyber-Physical Energy System Quantitative Security Metric (CPES-QSM), that quantifies the interaction between the cyber and physical layers across three domains: electrical, cyber-risk, and network topology. A method for incorporating the proposed cyber-metric into operational decisions is also proposed by formulating a cyber-constrained AC optimal power flow (C-ACOPF) that considers the status of all the CPES layers. The C-ACOPF considers the vulnerabilities of physical and cyber networks by incorporating factors such as voltage stability, contingencies, graph-theory, and IoT cyber risks, while using a multi-criteria decision-making technique. We note that simulation studies are conducted using standard IEEE test systems to evaluate the effectiveness of the proposed metric and the C-ACOPF formulation.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Composition, Growth, Succession, and Function in the Cladophora Microbiome: Insights From Quantitative Stable Isotope Probing and NanoSIMS Imaging
The branching green macroalga Cladophora glomerata and its epiphytic microbiome dominate summer biomass in the Eel River, a Northern California river under Mediterranean (summer drought, winter rain) seasonality. Green Cladophora streamers proliferate in early summer, then change to yellow and then red-brown as epiphyte loads increase. Here, we characterised successional changes in epiphytic bacteria on Cladophora, examining both community composition and growth rates, using quantitative Stable Isotope Probing (qSIP) and 16S rRNA gene amplicon sequencing. The number of bacterial taxa increased with succession while growth rates peaked in the middle stage. NanoSIMS imaging confirmed high sulphur (S) concentrations in Cladophora cell walls relative to surrounding biomass, coinciding with a bloom of sulphur bacteria (bacteria that reduce or oxidise sulphur/sulphates). In general, relative abundances and growth rates were independent, indicating that either metric alone is insufficient for understanding how taxonomy and functional groups affect ecosystem processes. For instance, the relative abundance of nitrogen fixers peaked in the late summer when their relative growth rates were slowest. Such patterns may be driven by space competition limiting growth. Together, changes in abundance and relative growth rates suggest different limiting factors for different functional groups in the Cladophora microbiome at multiple successional stages.
Biological and medical sciences↗
Genome‐wide quantitative trait loci detection for biofuel traits in switchgrass ( Panicum virgatum L.)
Abstract Switchgrass ( Panicum virgatum L.) has been identified as a potential feedstock for cellulosic ethanol production in United States for its high biomass yield and adaptation to marginal lands. Composition of the cell wall plays an important role in bioethanol conversion. A total of 209 pseudo‐F 1 testcross progenies obtained from a biparental cross, AP13 × VS16, were grown at three locations from 2008 to 2011. Near‐infrared spectroscopy was used to estimate cell wall composition from biomass harvested at maturity. A linkage map of the pseudo‐F 1 testcross was constructed with 8,757 SNPs developed by genotyping‐by‐sequencing. Quantitative trait loci (QTL) analysis was performed on eight lignocellulosic traits, namely, klason lignin, sugar, glucose, xylose, hexose, ethanol, hexosoic ethanol, and cell wall ethanol conversion percentage. A total of 327 QTL were recorded for the eight lignocellulosic traits. We have identified 111 major regions in the switchgrass genome that underlie these lignocellulosic traits. Scanning of the genome sequence for genes flanking the QTL peaks, we identified 45 important genes that are involved in lignin biosynthesis, carbohydrate and sugar metabolism, and other biological and cellular functions. Identification of valuable genes associated with QTL along with pleotropic effects of the significant number of QTL suggests that simultaneous selection and genetic improvement of these traits are possible using marker‐assisted selection.
Ali, Shahjahan↗
Engineering quantitative stomatal trait variation and local adaptation potential by cis‐regulatory editing
Summary Cis‐regulatory element editing can generate quantitative trait variation that mitigates extreme phenotypes and harmful pleiotropy associated with coding sequence mutations. Here, we applied a multiplexed CRISPR/Cas9 approach, informed by bioinformatic datasets, to generate genotypic variation in the promoter ofOsSTOMAGEN, a positive regulator of rice stomatal density. Engineered genotypic variation corresponded to broad and continuous variation in stomatal density, ranging from 70% to 120% of wild‐type stomatal density. This panel of stomatal variants was leveraged in physiological assays to establish discrete relationships between stomatal morphological variation and stomatal conductance, carbon assimilation and intrinsic water use efficiency in steady‐state and fluctuating light conditions. Additionally, promoter alleles were subjected to vegetative drought regimes to assay the effects of the edited alleles on developmental response to drought. Notably, the capacity for drought‐responsive stomatal density reprogramming instomagenand two cis‐regulatory edited alleles was reduced. Collectively our data demonstrate that cis‐regulatory element editing can generate near‐isogenic trait variation that can be leveraged for establishing relationships between anatomy and physiology, providing a basis for optimizing traits across diverse environments.
Biotechnology & Applied Microbiology↗
Quantitative far-infrared band strengths of iodine monochloride (ICl), a molten salt off-gas product
The gaseous (by)products generated from molten salt reactors need to be monitored to prevent the release of potentially toxic gases to the environment. In particular, 129I has a long half-life and its toxicity and persistence in the environment make iodine and iodine-containing compounds (such as ICl from chloride containing molten salt systems) of great concern. Optical spectroscopy tools, including Raman and Fourier-transform infrared (FTIR) spectroscopies, are ideal for monitoring and quantifying such off-gas products. Iodine (I2) has a strong and distinct Raman signature and the change in signal with a change in concentration can be used for quantification of these byproducts. Iodine monochloride (ICl) has distinct signatures in both the Raman and the infrared, and its spectrum can also potentially be used for quantitative measurement of this species. In this paper we discuss our recent results on the quantification of iodine monochloride using infrared spectroscopy, in particular first reports of the absolute infrared band strength of ICl.
infrared (IR) spectroscopy, Molten Salt Reactors, ↗
Quantitative cross-species translators of cardiac myocyte electrophysiology: Model training, experimental validation, and applications
Animal experimentation is key in the evaluation of cardiac efficacy and safety of novel therapeutic compounds. However, interspecies differences in the mechanisms regulating excitation-contraction coupling can limit the translation of experimental findings from animal models to human physiology and undermine the assessment of drugs’ efficacy and safety. Here, we built a suite of translators for quantitatively mapping electrophysiological responses in ventricular myocytes across species. We trained these statistical operators using a broad dataset obtained by simulating populations of our biophysically detailed computational models of action potential and Ca 2+ transient in mouse, rabbit, and human. We then tested our translators against experimental data describing the response to stimuli, such as ion channel block, change in beating rate, and β-adrenergic challenge. We demonstrate that this approach is well suited to predicting the effects of perturbations across different species or experimental conditions and suggest its integration into mechanistic studies and drug development pipelines.
60 APPLIED LIFE SCIENCES↗
Quantitative Stable-Isotope Probing (qSIP) with Metagenomics Links Microbial Physiology and Activity to Soil Moisture in Mediterranean-Climate Grassland Ecosystems
The growth and physiology of soil microorganisms, which play vital roles in biogeochemical cycling, are shaped by both current and historical soil environmental conditions. Here, we developed and applied a genome-resolved metagenomic implementation of quantitative stable isotope probing (qSIP) with an H 2 18 O labeling experiment to identify actively growing soil microorganisms and their genomic capacities. qSIP enabled measurement of taxon-specific growth because isotopic incorporation into microbial DNA requires production of new genome copies. We studied three Mediterranean grassland soils across a rainfall gradient to evaluate the hypothesis that historic precipitation levels are an important factor controlling trait selection. We used qSIP-informed genome-resolved metagenomics to resolve the active subset of soil community members and identify their characteristic ecophysiological traits. Higher year-round precipitation levels correlated with higher activity and growth rates of flagellar motile microorganisms. In addition to heavily isotopically labeled bacteria, we identified abundant isotope-labeled phages, suggesting phage-induced cell lysis likely contributed to necromass production at all three sites. Further, there was a positive correlation between phage activity and the activity of putative phage hosts. Contrary to our expectations, the capacity to decompose the diverse complex carbohydrates common in soil organic matter or oxidize methanol and carbon monoxide were broadly distributed across active and inactive bacteria in all three soils, implying that these traits are not highly selected for by historical precipitation.
54 ENVIRONMENTAL SCIENCES↗
Quantitative Characterization of the Microstructure-Property Relationships in Ni and MIEC Nanocatalyst-Infiltrated Ni/YSZ Anodes
The performance of solid oxide fuel cell (SOFC) anodes can be improved by infiltration of nanoscale electrocatalysts, which increases triple phase boundary (TPB) density, but only when the added TPBs are active. Quantitative characterization of the microstructure of infiltrated nanocatalysts remains a critical challenge in understanding their role in improved performance. This paper explores the relationship between electrochemical performance and microstructure for Ni/YSZ anodes infiltrated with Ni, gadolinium-doped-ceria (GDC), and Ni/GDC nanocatalysts using a combination of electrochemical impedance spectroscopy (EIS), distribution of relaxation times (DRT) analysis, scanning electron microscopy (SEM) microstructural characterization, and three-dimensional (3-D) anode reconstruction. Estimated polarization resistance improvements as a result of nickel nanoparticle infiltration are discussed.
Rix, Jillian↗
A Quantitative Failure Analysis on Capacity Fade in Rechargeable Lithium Metal Cells
Rechargeable lithium battery (RLB) technology is transforming portable devices, vehicle electrification, and grid modernization. To make RLB durable, reliable and safe, conducting failure mode and effect analysis (FMEA) to identify failure mechanism under the operating conditions is very desirable. However, this ability is often overlooked or even lacking. The failure analysis (FA) is often conducted by laboratory testing and postmortem analysis, and the knowledge typically empirical. Here we present a quantitative approach for FMEA that can reveal how failure modes and effects reduce the capacity of a RLB. This approach is based on the state of the battery for FMEA, contrary to the conventional approach based on operating or testing conditions. The key aspect of this FMEA method is to convert the experimental results to a state-of-charge (SOC)-based analytic methodology. Such a conversion can separate the thermodynamic and kinetic attributes of capacity fade based on compositional correspondence in the electrode, so the loss and the decreased utilization of the active materials can be determined respectively.
25 ENERGY STORAGE↗
Quantitative Evaluation of Top Coal Caving Methods at the Working Face of Extra‐Thick Coal Seams Based on the Random Medium Theory
Adopting an effective top coal caving method is the key to enhancing coal recovery and reducing gangue content for the fully mechanized top coal caving working face with extra‐thick coal seams. In this study, the movement of coal particles generated during top coal caving is considered to follow a normal distribution. Then, the caving body and coal‐rock settlement along the working face during the caving process are studied based on both the random media theory and probability theory. Accordingly, the optimal caving interval and caving sequences are determined, and a novel interval symmetrical coal caving method is proposed. The proposed method is systematically verified with results from physical similarity tests, and different caving methods are assessed by field tests. The results show the following: (1) The coal‐rock settlement and the caving body demonstrate clear axial symmetrical features along the working face; the size of the caving body increases as the caving height grows and its shape turns progressively from semicircular to semielliptical with a lower foot of the coal‐rock settlement. (2) The caving interval is derived using the sum of the radii of the coal‐rock settlement curves formed by the two largest caving bodies. (3) The symmetrical caving approach provides a symmetrical space for the subsequent movement of the broken top coal, which enables a uniform development of the caving body. (4) Compared with the traditional sequential coal caving method with the same number of supports, the interval symmetrical caving method results in a 21.7% of coal production increase, 17% caving rate promotion, and a shortened caving time by 23.4%. (5) The interval symmetrical caving method is found to improve the controllability of the caving process at the fully mechanized top coal caving working face. In general, this work presents a theoretical approach to select the optimal caving methods for the fully mechanized caving working face in extra‐thick coal seams for an improved production efficiency of the work face. The results of this study can also provide theoretical significance and referencing value for quantitative analyses of the coal caving methods for work faces with similar geological conditions.
Jiulin, Shi (ORCID:0000000155819062)↗
Surface Quantitative Precipitation Estimates (SQUIRE) of Snow Water Equivalent from the Surface Atmospheric Integrated Field Laboratory
The upper Colorado River basin is the primary source of water for 40 million people. With declining snowpack in the basin, forecasting hydrological budgets in the Southwest United States is more important than ever. However, due in part, to a lack of reliable observations of precipitation in complex terrain, hydrological models struggle to assess and forecast snowpack snow water equivalent (SWE) in the upper Colorado River basin (UCRB). Therefore, the need for more reliable SWE forecasts in the UCRB motivated the U.S. Department of Energy Atmospheric Radiation Measurement Facility’s Surface Atmospheric Integrated Field Laboratory (SAIL) that occurred from June 2021 to June 2023. During SAIL, the X-band precipitation radar from Colorado State University conducted volume scans sampling the precipitation properties over the UCRB. The ARM facility developed a gridded Surface Quantitative Precipitation Estimates (SQUIRE) product from the radar observations. To do this, various daily SWE estimates from radar using the radar reflectivity factor Z e and specific differential phase K dp were compared against ground-based precipitation gauges. SWE in precipitation calculated from Wolfe and Snider’s S–Z e estimator was in best agreement with the rain gauges for the days when SWE < 12 mm. For days with SWE > 12 mm, the WSR-88D Intermountain West relationship had the best agreement with the precipitation gauges. Airborne snow depth observations show that SQUIRE captures regions of orographic enhancement in the mountains to the west and northwest of the SAIL study area, indicating that the scientific community should focus on understanding and ultimately simulating orographic atmospheric precipitation processes to improve UCRB snowpack SWE assessment and forecasting.
Hydrology↗
Quantitative stable isotope probing (qSIP) and cross-domain networks reveal bacterial-fungal interactions in the hyphosphere
Interactions between fungi and bacteria have the potential to substantially influence soil carbon dynamics in soil, but we have yet to fully identify these interactions and partners in their natural environment. In this study, we stacked two powerful methods, 13 C quantitative stable isotope probing (qSIP) and cross-domain co-occurrence network, to identify interacting fungi and bacteria in a California grassland soil. We used in-field whole plant 13 CO 2 labeling along with sand-filled ingrowth bags (that trap fungi and hyphae-associated bacteria) to amplify the signal of fungal-bacterial interactions, separate from the bulk soil background. We found a total of 54 bacterial ASVs and 9 fungal OTUs that were significantly 13 C-enriched. These were saprotrophic and biotrophic fungi, and motile, sometimes predatory bacteria. Among these, 70% of all 13 C-enriched bacteria identified were motile. Notably, we detected fungal-bacterial network links between a fungal OTU of the genus Alternaria and several bacterial ASVs of the genera Bacteriovorax, Mucilaginibacter, and Flavobacterium, providing empirical evidence of their direct interactions through C exchange. We observed a strong positive co-occurrence pattern between predatory bacteria of the phylum Bdellovibrionota and fungal OTUs, suggesting the transfer of C across the soil food web. To date, our ability to associate microbial co-occurrence network patterns with biological interactions is limited, but the incorporation of qSIP allowed us to more precisely detect interacting partners by narrowing in on the taxa that were actively incorporating plant-fixed, fungal-transported labeled substrates. Together, these approaches can help build a mechanistic understanding of the complex nature of fungal-bacterial interactions in soil.
59 BASIC BIOLOGICAL SCIENCES↗
Visualizing bleb mass dynamics in single cells using quantitative phase microscopy
Understanding biological responses to directed energy (DE) is critical to ensure the safety of personnel within the Department of Defense. At the Air Force Research Laboratory, we have developed or adapted advanced optical imaging systems that quantify biophysical responses to DE. One notable cellular response to DE exposure is the formation of blebs, or semi-spherical protrusions of the plasma membrane in living cells. In this work, we demonstrate the capacity of quantitative phase imaging (QPI) to both visualize and quantify the formation of membrane blebs following DE exposure. QPI is an interferometric imaging tool that uses optical path length as a label-free contrast mechanism and is sensitive to the non-aqueous mass density, or dry mass, of living cells. Blebs from both CHO-K1 and U937 cells were generated after exposure to a series of 600 ns, 21.2 kV/cm electric pulses. These blebs were visualized in real time, and their dry mass relative to the rest of the cell body was quantified as a function of time. It is our hope that this system will lead to an improved understanding of both DE-induced and apoptotic blebbing.
Steelman, Zachary A.↗
A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2
The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2–3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.
59 BASIC BIOLOGICAL SCIENCES↗
Quantitative comparison between sub-millisecond time resolution single-molecule FRET measurements and 10-second molecular simulations of a biosensor protein
Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BP SS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BP SS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BP SS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BP SS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R 0 ) and fluorophore orientation factor (κ 2 ) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET.
59 BASIC BIOLOGICAL SCIENCES↗