Scalable Spray-On Fabrication Approach for Voltage-Tunable Thermal Emissivity Surfaces
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Seeds of Col-0 wild type, sig6 T-DNA mutants (CS877785, ABRC), PRL-1-OE, and sig6 T-DNA mutants transfected with PRL-1 (sig6::PRL-1) were planted in 1/2 MS media. Seedlings growth including chlorophyll development defects were investigated across the genotypes. Four-days-old-post-light exposure seedlings were harvested and performed RNAseq analysis with four biological replicates.
Abstract Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration ( ET ) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM‐modeled fluxes, we employed an isotope‐enabled mass balance framework to simulate ET isotope values ( δET ) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulating δET values consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling‐Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest ( x ‐intercept of the multi‐site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land‐surface hydrologic processes.
The U.S. Department of Energy established the Alternative Fuel Transportation Program (Program) and associated regulatory requirements pursuant to the Energy Policy Act of 1992. The Program, otherwise known as the State and Alternative Fuel Provider Fleet Program, requires covered state government and alternative fuel provider fleets operating under Standard Compliance to acquire alternative fuel vehicles (AFVs) as a specific percentage of their annual non-excluded light-duty vehicle acquisitions. The opportunity for covered fleets operating under Standard Compliance to request exemptions from their AFV-acquisition requirements serves as administrative relief in the unlikely event a fleet is unable to satisfy its requirements through the normally available compliance alternatives. These alternatives include the acquisition of light-duty AFVs, the acquisition of other, creditable vehicles (e.g., gasoline-fueled hybrid electric vehicles), making certain investments, the purchase of biodiesel for use in medium- or heavy-duty vehicles to the maximum extent allowed, and purchasing or trading for banked AFV credits. This document addresses requests for exemptions from the AFV-acquisition requirements to help covered fleets better understand: How to file a request for an exemption, information and documentation DOE needs to process an exemption request, and important policies relevant for filing exemption requests.
Flash droughts are defined by the rapid onset and intensification of drought conditions - a feature common across various proposed indicators. However, the absence of a standardized definition and detection method makes them particularly difficult to anticipate and manage. This dataset includes flash drought classifications based on six different methods across 222 catchments (4-digit Hydrologic Units, HUC4) in the Contiguous United States (CONUS) from 1983 to 2023. It also includes the pairwise agreement between indicators and the event-level multi-indicator agreement. For a detailed description of each file, refer to README_MSDlive.pdf
Abstract Polyurethane foams (PUFs) represent a significant segment of the polyurethane (PU) and cellular plastics industries, owing to their versatile applications and desirable properties. However, the production of PUFs heavily relies on petroleum‐derived chemicals, including polyols and isocyanates, raising critical environmental concerns. Lignin, an abundant aromatic macromolecule, offers a promising alternative for replacing petroleum‐based polyols because of its intrinsic hydroxyl groups. While efforts have been made to produce and apply various lignin‐based polyurethane foams (LPUFs), their commercialization remains limited by challenges such as low product consistency, poor technical performances, and high production costs. This study critically evaluates recent advances in the development of LPUFs, including innovative synthesis methods, functional applications, and emerging research trends. Moreover, potential strategies are discussed, such as lignin fractionation, modification, and co‐solvent assistance, for addressing the challenges. By resolving them, LPUFs could play a pivotal role in transitioning the PU industry to help achieve a circular bioeconomy.
CRISPR/Cas9 based genome editing has advanced our understanding of a myriad of important biological phenomena. Important challenges to multiplex genome editing in maize include assembly of large complex DNA constructs, few genotypes with efficient transformation systems, and costly/labor-intensive genotyping methods. Here we present an approach for multiplex CRISPR/Cas9 genome editing system that delivers a single compact DNA construct via biolistics to Type I embryogenic calli, followed by a novel efficient genotyping assay to identify desirable editing outcomes. We first demonstrate the creation of heritable mutations at multiple target sites within the same gene. Next, we successfully created individual and stacked mutations for multiple members of a gene family. Genome sequencing found off-target mutations are rare. Multiplex genome editing was achieved for both the highly transformable inbred line H99 and Illinois Low Protein1 (ILP1), a genotype where transformation has not previously been reported. In addition to screening transformation events for deletion alleles by PCR, we also designed PCR assays that selectively amplify deletion or insertion of a single nucleotide, the most common outcome from DNA repair of CRISPR/Cas9 breaks by non-homologous end-joining. The Indel-Selective PCR (IS-PCR) method enabled rapid tracking of multiple edited alleles in progeny populations. The ‘end to end’ pipeline presented here for multiplexed CRISPR/Cas9 mutagenesis can be applied to accelerate maize functional genomics in a broader diversity of genetic backgrounds.
Herein is an one-pot mechanosynthesis of naloxone covalently linked poly(lactic acid) and nanoparticles (∼600 nm) with a drug loading (∼8.3% w/w).
Datasheets relating to the article "Brachypodium SPEECHLESS2 promoter drives expression of a synthetic EPF to reduce stomatal density in sugarcane without pleiotropic effects" published in Plant Biotechnology Journal.
Society faces increasingly severe flood hazards, intensifying demand for flood early warning systems (FEWS) that deliver accurate and actionable information. However, most existing FEWS remain prediction‐centric, treating decision‐making as a downstream consumer of hazard forecasts while offering limited support for uncertainty interpretation, risk communication, and real‐world response. This Perspective presents a vision and blueprint for a novel inland FEWS‐decision‐making (FEWS‐DM) framework that repositions decision‐making as an equal partner in the forecasting process—not a passive recipient of its outputs. The framework is built on three tightly coupled, co‐evolving thrusts: Physical Science (T1), which advances flood prediction with quantified uncertainty informed by decision relevance; Human Science (T2), which incorporates psychology, behavior, and cultural and institutional context; and Decision Science (T3), which unifies physical predictions and human factors through principled, utility‐based decision support with end‐to‐end uncertainty management. Rather than treating T1 as a solved problem, FEWS‐DM recognizes that forecast development itself must be shaped by decision needs through continuous bidirectional feedback. We identify key scientific, behavioral, and operational challenges limiting such integration and discuss the enabling role of AI, while emphasizing human‐centered design and community feedback as essential for building trust and improving flood risk management.
Shigellosis is a gastrointestinal infection caused by species of Shigella . A large outbreak of Shigella flexneri serotype 2a occurred in Albuquerque, New Mexico between May 2021 and November 2023 that involved humans and non-human primates (NHP) from a local zoo. We analyzed the genomes of 202 New Mexican isolates as well as 15 closely related isolates from other states, and four from NHP. The outbreak was initially detected within men who have sex with men but then predominantly affected people experiencing homelessness. Nearly 70% of cases were hospitalized and there was one human death. The outbreak extended into Albuquerque’s BioPark Zoo, causing high morbidity and six deaths in NHPs. All isolates were multidrug-resistant, including towards fluoroquinolones, a first line treatment option which led to treatment failures in human and NHP populations. We show the circulation of the same S. flexneri strain in humans and NHPs, causing fatalities in both populations. This study demonstrates the threat of antimicrobial resistant organisms to vulnerable human and NHP populations and emphasizes the value of genomic surveillance within a One Health framework.
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This is the final technical report for DOE Award DE-SC0005132 entitled “Discovery of Dielectric Response and Forces in Sub-Nanoscale Objects.” This award originated on August 15, 2010 with Principle Investigator Prof. Phil Batson of Rutgers, The State University of New Jersey. Prof. Batson transitioned to Professor Emeritus status on January 31, 2023. At that time PI status was transferred to Prof. Robert Bartynski of the Department of Physics and Astronomy at Rutgers, The State University of New Jersey, and Director of the Rutgers Laboratory for Surface Modification. The central theme of the research performed under this award is develop and refine a NION aberration-corrected Scanning Transmission Electron Microscope to attain atomic spatial resolution and sub 10meV energy resolution in electron energy loss spectroscopy (EELS) performed on the transmitted electron beam. These capabilities allow examination of the excitation properties (primarily plasmonic and vibrational [ie., phonons] of nanoscale objects when excited with a highly-localized (~ Angstrom-scale) high energy (~ 60 keV) electron beam. Direct excitations (i.e., the response to electrons impinging directly on the sample) as well as excitations in response to the dynamic electric (and magnetic!) fields of an aloof electron beam (i.e., a beam that is close to but displaced from the target) have been studied. Our experimental work has benefited greatly from close collaborations with theoretical colleagues, but at Rutgers and from around the world, providing a much more complete understanding of the observed phenomena and suggesting avenues for further study and practical applications. This report summarizes the technical and scientific achievements accomplished during the entire award period. More extensive details are available in the Progress Reports that have already been filed with the Department of Energy. The report is divided into six sections. The first four sections focus on exploring, developing and understanding several unique capabilities and phenomena discovered and accessible owing to the high spatial- and energy-resolution we have been able to achieve. The latter two sections focus on applications of the STEM’s novel capabilities to study atomic- and nanometer-scale properties of solids, as well as broader applications to advanced and bio-materials.
We present results from ATTO-Campina, a new permanent observational site in central Amazon, about 4 km from the ATTO towers. Operational since 2020, ATTO-Campina characterizes atmospheric, cloud and rainfall properties through remote sensing. The goal is to provide continuous, complementary measurements to the ATTO towers, addressing the rainforest’s complex gas-aerosol-cloud-precipitation dynamics. Using a 3.5-year dataset, we classified convective clouds into three types: shallow cumulus (ShCu), congestus (Con) or (Deep) clouds. The shallow-to-deep transition takes about three hours, starting with ShCu formation at 11:00 local time. The accumulated rainfall peak follows at about 16:00. Only weak downdrafts are present in the upper troposphere where previous studies indicate new particle formation (NPF) occurrence. Strong downdrafts are mostly limited to heights below 5 km. Con and Deep convective days have higher concentrations of ultrafine aerosol and lower concentrations of accumulation-mode particles compared to ShCu. Convective clouds also significantly modify gas mixing ratios. Deep convective clouds are associated with high near-surface O3, consistent with downward transport from the midtroposphere. Our results showcase the added detail achieved by integrating data from the ATTO towers and ATTO-Campina sites. Together, these sites support better understanding of interconnected gas-aerosol-cloud-precipitation processes in the Amazon and their evolution under climate change.
Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.
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Magnesium chloride (MgCl 2 )-based molten salt phase change materials (PCMs) are promising candidates for thermal energy storage (TES) owing to their advantageous thermophysical properties, however, their high corrosivity in the molten state limits material compatibility. In this study, the corrosion behavior of 304?L stainless steel (SS304L) exposed to MgCl2 PCM was investigated as a function of thermal cycling (up to 9000 cycles) relevant to PCM-based TES systems. Microstructural changes and elemental redistribution at the alloy-salt interface under thermal cycling conditions were characterized using synchrotron-based X-ray fluorescence (XRF) and scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDS). Results show that corrosion is governed by selective Cr-dissolution and elemental diffusion near the interface and grain boundaries. A clear transition in the dominant corrosion mechanism is observed with increasing thermal cycles. Surface corrosion is the dominant mechanism up to 1000 cycles, whereas intergranular corrosion becomes the primary degradation mode beyond 2000 cycles. These mechanistic changes are interpreted in terms of evolving interfacial chemistry, microstructure and the diffusion-driven redistribution of alloying elements.
Hyperon recoil polarization measurements for the exclusive electroproduction of 𝐾 + Λ and 𝐾 + Σ 0 final states from an unpolarized proton target have been carried out using the CLAS12 spectrometer at Jefferson Laboratory. The measurements at beam energies of 6.535 and 7.546 GeV span the range of four-momentum transfer 𝑄 2 from 0.3 to 4.5GeV 2 and invariant mass 𝑊 from 1.6 to 2.4 GeV, while covering the full center-of-mass angular range of the 𝐾 + . These new Λ polarization observables extend the existing data in a similar kinematic range but from a significantly larger dataset. However, they represent the first electroproduction measurements of this observable for the Σ 0 . These data will allow for better exploration of the reaction mechanism in strangeness production, for further understanding of the spectrum and structure of excited nucleon states that couple to 𝐾𝑌, and for improved insight into the strong interaction in the nonperturbative domain.