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At least 163 records · Page 9

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Detection of Drizzle and Light Snowfall Over the Southern Ocean Using the GPM Combined Algorithm

Following the 2014 launch of the Global Precipitation Measurement Mission (GPM), an unprecedented combination of coincident active and passive microwave observations are available for state of the art precipitation retrieval. The GPM Combined Algorithm forms the backbone of this effort, optimizing geophysical variables for agreement with the multi-spectral information content. Combined retrievals are then utilized, along with a radiative transfer model, as a database applied for retrievals across a constellation of passive microwave radiometers of varying frequencies and viewing geometries. By keeping such retrievals related through the transfer standard of the combined algorithm, level 3 products such as the Integrated Multi-satellitE Retrievals for GPM (IMERG) are able to provide consistent global products for users at the higher temporal resolution required for hydrological applications on the global scale. In the current version of the combined product, precipitation retrievals are carried out only in the presence of a signal from the active radar. As a result, light precipitation and drizzle below the threshold of radar sensitivity are not included in any of the products down the chain from the constellation to IMERG. In this work, the effects of enhancing the retrievals with an optimal estimation-type (OE) water vapor and cloud retrieval using the passive observations are explored over the Southern Ocean on a regional scale. Non-convergence of the OE in areas with no detectable radar signal is used to identify areas with high probability of light precipitation and drizzle. Microphysical scale characterization of the light precipitation will be explored using information derived from the higher sensitivity CloudSat mission along with model information to identify and associate the related atmospheric state and dynamics. This is a physically-based approach requiring radiometric consistency with all available multi-spectral observations. Retrieved drizzle can then be included in the constellation databases continuing across all scales through to the level 3 products. The technique, successfully demonstrated for the Southern Ocean, can be easily adapted for light precipitation retrieval over other areas and surfaces leading to a global climatology of light precipitation.

Sarah Rinegerud↗

DOE OSTI2023

Spectral channel splicer for spectral beam combining laser system

A spectral beam combining system includes a spectral channel splicer comprising a plurality of reflectors and a spectral beam combiner comprising a diffraction optical element such as a diffraction grating. This spectral beam combining system may facilitate combining an increased number of spectral channels thereby producing higher optical power of the combining beam system.

Nguyen, Hoang T.↗

DOE OSTI2022

Machine Learning Pattern Recognition Algorithm With Applications to Coherent Laser Combination

Herein we analyze a new kind of machine learning algorithm designed to feedback stabilize coherently combined lasers. This algorithm learns differential, rather than absolute, values of action in phase space, in order to facilitate learning on initially unstable systems. Experiments have shown that this approach can control small-scale spatial beam combination with high stability. In this paper we analyze the algorithm's performance and limitations in depth, showing that it can continuously learn during operation in order to track changes. Using simulation, we extend the application to temporal combination, and show that it scales to more complex instances by combining 81 beams.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2006

An analysis of the phase dispersion in the symmetric beam combiner

An astronomical beam combiner combines the two beams of starlight to form white-light fringes. It is desirable that the dispersion of the beam combiner be minimized across the observation wavelength range. We present here an analysis of the phase dispersion from coatings for a symmetric beam combiner. The sensitivity of the dispersion to a slight mismatch in beamsplitter coatings is also studied.

coatings↗

DOE OSTI2020

Tumor Microenvironment Targeting Nano–Bio Emulsion for Synergistic Combinational X-Ray PDT with Oncolytic Bacteria Therapy

Various cancer therapies have been developed, but tumor recurrence with incomplete tumor killing and remaining tumor cells/tissues is frequent in monotherapies. Herein, a nano–bio therapeutic emulsion formulated with multifunctional nanoscintillators and anaerobic Clostridium novyi-NT spores for synergistic image-guided combinational cancer therapy is reported. MRI visible nanoscintillators (NSs) are synthesized with a NaGdF 4 :Tb,Ce@NaGdF 4 core/shell structure for an image-guided X-ray photodynamic therapy (PDT) of the normoxic peripheral tumor. An anaerobic oncolytic bacterium (C. novyi-NT) therapy is combined to treat the hypoxic central tumor tissues. Photosensitizer-coated NSs (PS-NSs) and C. novyi-NT spores are emulsified with clinically available ethiodized oil (Lipiodol) to be the nano–bio therapeutic emulsion and injected into the tumor with computed tomography image guidance. The distribution of nano–bio therapeutic emulsion, including PS-NSs and anaerobic C. novyi-NT spores in the tumor site, is confirmed by both X-ray and T1-weighted magnetic resonance imaging. Following the image-guided X-ray PDT and anaerobic C. novyi- NT combination treatment, apoptotic cell death in cancer tissues, including both peripheral and central tumor regions, is significantly higher than in the control groups. Finally, this combination therapy approach using a nano–bio therapeutic emulsion is expected to overcome the limitations of conventional cancer therapy, resulting in increased cancer-therapeutic efficacy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

A study of adhesive bonding in metal–metal, metal–CFRP, and CFRP–CFRP material combinations under shear deformation: Fracture morphologies and damage mechanisms

Safe design of adhesive joining in multi-materials in engineered structures requires the accumulation of numerous experimental data on the failure behavior of various adhesively-bonded material combinations under different loading conditions. The deep understanding of mechanical performance, fracturing morphologies, and main damage mechanisms is also quintessential for accelerating the development of proper physics-based and multi-scale models for assisting the design. Towards this goal, this work presents a comprehensive characterization of the failure behavior of adhesively-bonded metal–metal, metal–CFRP, and CFRP–CFRP material combinations under global shear deformation via single lap shear testing. Thanks to a synergistic combination of measurement methods by using Digital Imaging Correlation (DIC) and 3D optical profilometry, adhesive features on the adherend after failure were quantified and the main progressive damage mechanisms were identified. The characterization performed in this work provides quantitative data that contributes to a better understanding of shear failure in adhesive bonding across different bi-material combinations. Finally, the obtained results have practical implications, including the potential to enhance adhesive bonding design, identify failure causes in adhesive joints, and develop or validate computational models capable of capturing the observed behavior in various adhesively-bonded materials under global shear deformation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Prospective Clinical Investigation of the Efficacy of Combination Radiation Therapy With Immune Checkpoint Inhibition

Immune checkpoint inhibitors (ICIs) lead to durable responses in a subset of patients with cancer, but most patients do not respond to ICI, prompting interest in combining immunotherapy with other therapeutic regimens. Preclinical evidence supports the potential for therapeutic synergy between immunotherapy and radiation therapy through modulation of the tumor microenvironment and antitumor immune responses. Local therapy also has the potential to overcome localized sites of relative immune suppression and resistance. Prospective clinical trials have been initiated to test these hypotheses in the clinic as well as to investigate the toxicities and adverse events associated with combination immunotherapy and radiation therapy. In this review, we discuss the emerging results from prospective clinical trials of combination immunotherapy and radiation therapy, the safety and efficacy of their combination, concordance with preclinical and retrospective data, and some of the remaining open questions to be addressed by future clinical trials.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Moving Beyond the Standard of Care: Accelerate Testing of Radiation-Drug Combinations

Radiation therapy is a major treatment modality used in > 60% of cancer patients as definitive local treatment for inoperable locoregionally confined tumors and as palliative therapy. Although cytotoxic chemotherapy enhances the effectiveness of treatment, the benefit over radiation therapy alone is modest. There is a need to enhance the effectiveness of local tumor control over what sequentially or concurrently administered cytotoxic chemotherapy provides. Although many biological pathways are known to enhance the effectiveness of radiation therapy, there is currently a paucity of drugs approved for use in combination. Several clinical trials have tested the effectiveness of combining targeted agents or immunotherapies with radiation therapy, but the results of these trials have been negative, likely stemming from the relative lack of preclinical evidence using appropriate experimental standardization or model systems. Accelerating the identification of agents tested in an appropriate clinical context and experimental systems or models would greatly enhance the potential to bring forward early testing of drugs that would not only be safe but also more effective. This article provides an overview of the opportunities and challenges of developing therapeutics to combine with radiation therapy, and some guidance toward preclinical and early clinical testing to improve the chance that advanced phase testing of drug-radiation combinations would be successful in the long term.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

High-throughput screening of multifunctional nanocoatings based on combinations of polyphenols and catecholamines

Biomimetic surface coatings based on plant polyphenols and catecholamines have been used broadly in a variety of applications. However, the lack of a rational cost-effective platform for screening these coatings and their properties limits the true potential of these functional materials to be unleashed. Here, we investigated the oxidation behavior and coating formation ability of a library consisting of 45 phenolic compounds and catecholamines. UV–vis spectroscopy demonstrated significant acceleration of oxidation and polymerization under UV irradiation. We discovered that several binary mixtures resulted in non-additive behavior (synergistic or antagonistic effect) yielding much thicker or thinner coatings than individual compounds measured by ellipsometry. To investigate the properties of coatings derived from new combinations, we used a miniaturized high-throughput strategy to screen 2,532 spots coated with single, binary, and ternary combinations of coating precursors in one run. We evaluated the use of machine learning models to learn the relation between the chemical structure of the precursors and the thickness of the nanocoatings. Formation and stability of nanocoatings were investigated in a high-throughput manner via discontinuous dewetting. 30 stable combinations (hits) were used to tune the surface wettability and to form water droplet microarray and spot size gradients of water droplets on the coated surface. No toxicity was observed against eukaryotic HeLa cells and Pseudomonas aeruginosa (strain PA30) bacteria after 24 h incubation at 37 C. The strategy introduced here for high-throughput screening of nanocoatings derived from combinations of coating precursors enables the discovery of new functional materials for various applications in science and technology in a cost-effective miniaturized manner.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Deciphering the Mechanistic Role of Individual Oxide Phases and Their Combinations in Supported Mn–Na 2 WO 4 Catalysts for Oxidative Coupling of Methane

Oxidative coupling of methane (OCM) is an attractive direct route for upgrading methane to valuable chemicals. In this study, Temporal Analysis of Products (TAP) and steady state experiments are conducted to understand the role of individual oxide phases and their combinations in supported Mn-Na 2 WO 4 /SiO 2 catalysts for OCM. The results from TAP transient kinetic studies indicate that Mn plays an important role in promoting gas phase oxygen activation, while NaO x /SiO 2 and WO x /SiO 2 are relatively inert towards gas phase oxygen and methane activation. However, the supported catalyst combining Na and W in the form Na 2 WO 4 show enhanced gas phase oxygen activation exhibiting a much lower oxygen activation energy (148 kJ/mol) and enhanced activity toward methane activation as compared to the individual supported oxide catalysts. Addition of Mn to Na 2 WO 4 /SiO 2 further decreases the oxygen activation energy by 40 kJ/mol. Moreover, methane activation is also enhanced with CH 3 as the main intermediate but, with increasing Mn content, more CH 2 intermediates are observed. Different forms of oxygen (both dioxygen and atomic) are detected on the catalyst surface using isotopic pump/probe pulsing and their distribution is found to depend on the catalyst composition. An optimal Mn content in the Na 2 WO 4 /SiO 2 catalyst system is needed to enhance the amount of dioxide surface species (e.g., superoxide 16 O 2 - or peroxide 16 O 2 2- ) associated with the Na 2 WO 4 leading to high C 2 selectivity for OCM. When the Mn content is too high, the larger MnOx domains are shown to contribute to the formation of higher concertation of monoxide surface species that lead to nonselective OCM pathways. This insight from transient kinetic characterization using TAP combined with conventional steady state studies, provides a deeper understanding of the role of individual oxide phases and their combination on supported catalysts toward the formation of intermediate surface species and their impact on the OCM reaction mechanism. This knowledge is critical toward designing superior catalyst formulations for OCM.

10 SYNTHETIC FUELS↗

DOE OSTI2024

Development of a micro-combined heat and power powered by an opposed-piston engine in building applications

Residential homes and light commercial buildings usually require substantial heat and electricity simultaneously. A combined heat and power system enables more efficient and environmentally friendly energy usage than that achieved when heat and electricity are produced in separate processes. However, due to financial and space constraints, residential and light commercial buildings often limit the use of traditional large-scale industrial equipment. Here we develop a micro–combined heat and power system powered by an opposed-piston engine to simultaneously generate electricity and provide heat to residential homes or light commercial buildings. The developed prototype attains the maximum AC electrical efficiency of 35.2%. The electrical efficiency breaks the typical upper boundary of 30% for micro–combined heat and power systems using small internal combustion engines (i.e., <10 kW). Moreover, the developed prototype enables maximum combined electrical and thermal efficiencies greater than 93%. The prototype is optimally designed for natural gas but can also run renewable biogas and hydrogen, supporting the transition from current conventional fossil fuels to zero carbon emissions in the future. The analysis of the unit’s decarbonization and cost-saving potential indicate that, except for specific locations, the developed prototype might excel in achieving decarbonization and cost savings primarily in US northern and middle climate zones.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Safety and antiviral activity of triple combination broadly neutralizing monoclonal antibody therapy against HIV-1: a phase 1 clinical trial

HIV-1 therapy with single or dual broadly neutralizing antibodies (bNAbs) has shown viral escape, indicating that at least a triple bNAb therapy may be needed for robust suppression of viremia. We performed a two-part study consisting of a single-center, randomized, double-blind, dose-escalation, placebo-controlled first-in-human trial of the HIV-1 V2-glycan-specific antibody PGDM1400 alone or in combination with the V3-glycan-specific antibody PGT121 in 24 adults without HIV in part 1, as well as a multi-center, open-label trial of the combination of PGDM1400, PGT121 and the CD4-binding-site antibody VRC07-523LS in five viremic adults living with HIV not on antiretroviral therapy (ART) in part 2. The primary endpoints were safety, tolerability and pharmacokinetics for both parts and antiviral activity among viremic adults living with HIV and not on ART for part 2 of the study. The secondary endpoints were changes in CD4 + T cell counts and development of HIV-1 sequence variations associated with PGDM1400, PGT121 and VRC07-523LS resistance in part 2. Intravenously administered PGDM1400 was safe and well-tolerated at doses up to 30 mg kg -1 and when given in combination with PGT121 and VRC07-523LS. A single intravenous infusion of 20 mg kg -1 of each of the three antibodies reduced plasma HIV RNA levels in viremic individuals by a maximum mean of 2.04 log10 copies per ml; however, viral rebound occurred in all participants within a median of 20 days after nadir. Rebound viruses demonstrated partial to complete resistance to PGDM1400 and PGT121 in vitro, whereas susceptibility to VRC07-523LS was preserved. Viral rebound occurred despite mean VRC07-523LS serum concentrations of 93 µg ml -1 . The trial met the pre-specified endpoints. Our data suggest that future bNAb combinations likely need to achieve broad antiviral activity, while also maintaining high serum concentrations, to mediate viral control.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

KiDS-1000 cosmology: Combined second- and third-order shear statistics

Aims.In this work, we perform the first cosmological parameter analysis of the fourth release of Kilo Degree Survey (KiDS-1000) data with second- and third-order shear statistics. This paper builds on a series of studies aimed at describing the roadmap to third-order shear statistics. Methods.We derived and tested a combined model of the second-order shear statistic, namely, the COSEBIs and the third-order aperture mass statistics 〈ℳ ap 3 〉 in a tomographic set-up. We validated our pipeline withN-body mock simulations of the KiDS-1000 data release. To model the second- and third-order statistics, we used the latest version of HMCODE2020 for the power spectrum and BIHALOFITfor the bispectrum. Furthermore, we used an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering only equal smoothing radii for the 〈ℳ ap 3 〉 part of the data vector. This makes it possible to carry out a data analysis of the KiDS-1000 data release using a combined analysis of COSEBIs and third-order shear statistics. Results.We first validated the accuracy of our modelling by analysing a noise-free mock data vector, assuming the KiDS-1000 error budget, finding a shift in the maximum of the posterior distribution of the matter density parameter, ΔΩ m < 0.02 σ Ω m , and of the structure growth parameter, ΔS 8 < 0.05 σ S 8 . Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained Ω m = 0.248 −0.055 +0.062 andS 8 = σ 8 √(Ω m /0.3 )= 0.772 ± 0.022. The geometric average on the errors of Ω m andS 8 of the combined statistics decreases, compared to the second-order statistic, by a factor of 2.2.

Astronomy & Astrophysics↗

DOE OSTI2022

Closing the loop between microstructure and charge transport in conjugated polymers by combining microscopy and simulation

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.

42 ENGINEERING↗

DOE OSTI2022

The PDF4LHC21 combination of global PDF fits for the LHC Run III

A precise knowledge of the quark and gluon structure of the proton, encoded by the parton distribution functions (PDFs), is of paramount importance for the interpretation of high-energy processes at present and future lepton–hadron and hadron–hadron colliders. Motivated by recent progress in the PDF determinations carried out by the CT, MSHT, and NNPDF groups, we present an updated combination of global PDF fits: PDF4LHC21. It is based on the Monte Carlo combination of the CT18, MSHT20, and NNPDF3.1 sets followed by either its Hessian reduction or its replica compression. Extensive benchmark studies are carried out in order to disentangle the origin of the differences between the three global PDF sets. In particular, dedicated fits based on almost identical theory settings and input datasets are performed by the three groups, highlighting the role played by the respective fitting methodologies. We compare the new PDF4LHC21 combination with its predecessor, PDF4LHC15, demonstrating their good overall consistency and a modest reduction of PDF uncertainties for key LHC processes such as electroweak gauge boson production and Higgs boson production in gluon fusion. We study the phenomenological implications of PDF4LHC21 for a representative selection of inclusive, fiducial, and differential cross sections at the LHC. The PDF4LHC21 combination is made available via the LHAPDF library and provides a robust, user-friendly, and efficient method to estimate the PDF uncertainties associated to theoretical calculations for the upcoming Run III of the LHC and beyond.

quantum chromodynamics↗

DOE OSTI2026

Combined dark matter search towards dwarf spheroidal galaxies with Fermi -LAT, HAWC, H.E.S.S., MAGIC, and VERITAS

Dwarf spheroidal galaxies (dSphs) are excellent targets for indirect dark matter (DM) searches using gamma-ray telescopes because they are thought to have high DM content and a low astrophysical background. The sensitivity of these searches is improved by combining the observations of dSphs made by different gamma-ray telescopes. We present the results of a combined search by the most sensitive currently operating gamma-ray telescopes, namely: the satellite-borne Fermi -LAT telescope; the ground-based imaging atmospheric Cherenkov telescope arrays H.E.S.S., MAGIC, and VERITAS; and the HAWC water Cherenkov detector. Individual datasets were analyzed using a common statistical approach. Results were subsequently combined via a global joint likelihood analysis. We obtain constraints on the velocity-weighted cross section 〈σv〉 for DM self-annihilation as a function of the DM particle mass. This five-instrument combination allows the derivation of up to 2-3 times more constraining upper limits on 〈σv〉 than the individual results over a wide mass range spanning from 5 GeV to 100 TeV. Depending on the DM content modeling, the 95% confidence level observed limits reach 1.5×10 -24 cm 3 s -1 and 3.2×10 -25 cm 3 s -1 , respectively, in the τ + τ - annihilation channel for a DM mass of 2 TeV.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein–protein interaction network

Abstract Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover new synergistic drug combinations due to the combinatorial explosion. Deep learning technology holds immense promise for better prediction of in vitro synergistic drug combinations for certain cell lines. In methods applying such technology, omics data are widely adopted to construct cell line features. However, biological network data are rarely considered yet, which is worthy of in-depth study. In this study, we propose a novel deep learning method, termed PRODeepSyn, for predicting anticancer synergistic drug combinations. By leveraging the Graph Convolutional Network, PRODeepSyn integrates the protein–protein interaction (PPI) network with omics data to construct low-dimensional dense embeddings for cell lines. PRODeepSyn then builds a deep neural network with the Batch Normalization mechanism to predict synergy scores using the cell line embeddings and drug features. PRODeepSyn achieves the lowest root mean square error of 15.08 and the highest Pearson correlation coefficient of 0.75, outperforming two deep learning methods and four machine learning methods. On the classification task, PRODeepSyn achieves an area under the receiver operator characteristics curve of 0.90, an area under the precision–recall curve of 0.63 and a Cohen’s Kappa of 0.53. In the ablation study, we find that using the multi-omics data and the integrated PPI network’s information both can improve the prediction results. Additionally, the case study demonstrates the consistency between PRODeepSyn and previous studies.

Wang, Xiaowen↗

DOE OSTI2020

The cis-regulatory codes of response to combined heat and drought stress in Arabidopsis thaliana

Abstract Plants respond to their environment by dynamically modulating gene expression. A powerful approach for understanding how these responses are regulated is to integrate information about cis-regulatory elements (CREs) into models called cis-regulatory codes. Transcriptional response to combined stress is typically not the sum of the responses to the individual stresses. However, cis-regulatory codes underlying combined stress response have not been established. Here we modeled transcriptional response to single and combined heat and drought stress in Arabidopsis thaliana. We grouped genes by their pattern of response (independent, antagonistic and synergistic) and trained machine learning models to predict their response using putative CREs (pCREs) as features (median F-measure = 0.64). We then developed a deep learning approach to integrate additional omics information (sequence conservation, chromatin accessibility and histone modification) into our models, improving performance by 6.2%. While pCREs important for predicting independent and antagonistic responses tended to resemble binding motifs of transcription factors associated with heat and/or drought stress, important synergistic pCREs resembled binding motifs of transcription factors not known to be associated with stress. These findings demonstrate how in silico approaches can improve our understanding of the complex codes regulating response to combined stress and help us identify prime targets for future characterization.

Azodi, Christina B.↗