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Here, stencil codes are compute-intensive algorithms, in which data points arranged in a large grid are being recomputed repeatedly from the values of data points in a predefined neighborhood. This fixed neighborhood pattern is called a stencil. Stencils codes see wide-spread use in computing the discrete solutions of partial differential equations and systems composed of such equations.
Summary Scientific datasets are growing rapidly and becoming critical to next‐generation scientific discoveries. The validity of scientific results relies on the quality of data used and data are often subject to change, for example, due to observation additions, quality assessments, or processing software updates. The effects of data change are not well understood and difficult to predict. Datasets are often repeatedly updated and recomputing derived data products quickly becomes time consuming and resource intensive and may in some cases not even be necessary, thus delaying scientific advance. Despite its importance, there is a lack of systematic approaches for best comparing data versions to quantify the changes, and ad‐hoc or manual processes are commonly used. In this article, we propose a novel hierarchical approach for analyzing data changes, including real‐time (online) and offline analyses. We employ a variety of fast‐to‐compute numerical analyses, graphical data change representations, and more resource‐intensive recomputations of a subset of the data product. We illustrate the application of our approach using three scientific diverse use cases, namely, satellite, cosmological, and x‐ray data. The results show that a variety of data change metrics should be employed to enable a comprehensive representation and qualitative evaluation of data changes.
Summary Many practical algorithms for numerical rank computations implement an iterative procedure that involves repeated multiplications of a vector, or a collection of vectors, with both a sparse matrix and its transpose. Unfortunately, the realization of these sparse products on current high performance libraries often deliver much lower arithmetic throughput when the matrix involved in the product is transposed. In this work, we propose a hybrid sparse matrix layout, named CSRC, that combines the flexibility of some well‐known sparse formats to offer a number of appealing properties: (1) CSRC can be obtained at low cost from the popular CSR (compressed sparse row) format; (2) CSRC has similar storage requirements as CSR; and especially, (3) the implementation of the sparse product kernels delivers high performance for both the direct product and its transposed variant on modern graphics accelerators thanks to a significant reduction of atomic operations compared to a conventional implementation based on CSR. This solution thus renders considerably higher performance when integrated into an iterative algorithm for the truncated singular value decomposition (SVD), such as the randomized SVD or, as demonstrated in the experimental results, the block Golub–Kahan–Lanczos algorithm.
Sorghum leaf blight and northern corn leaf blight, both caused by Exserohilum turcicum {(Pass.) K. J. Leonard and Suggs [syn. Setosphaeria turcica (Luttr.) K. J. Leonard and Suggs.]}, are major diseases of sorghum [Sorghum bicolor (L.) Moench] and maize (Zea mays L.), respectively. Examining the genetic architecture of resistance in sorghum will lead to a better understanding of the relationship between resistance in sorghum and maize, which can ultimately enhance management options in both crops. In 2018 and 2019, we evaluated two sorghum recombinant inbred line (RIL) populations for resistance to E. turcicum. The BTx623 × IS3620C and BTx623 × SC155 populations consisted of 235 and 81 RILs, respectively. Resistance in both populations was moderately to highly heritable. We identified a total of six quantitative trait loci (QTL) across the two populations. Three QTL with small- to moderate-effect sizes were identified in the BTx623 × IS3620C population. Three QTL, including a large-effect QTL on chromosome three that explained 24% of the variation, were identified in the BTx623 × SC155 population. We compared the identified QTL with the position of northern corn leaf blight candidate genes and found eight candidate resistance gene orthologs that colocalize with the sorghum leaf blight QTL. There were also several nucleotide-binding leucine-rich repeat encoding genes within the candidate intervals. Understanding host resistance in multiple species furthers our understanding of the Exserohilum turcicum patho-system.
AbstractThe collision‐activated fragmentation pathways and reaction mechanisms of 34 deprotonated model compounds representative of lignin degradation products were explored experimentally and computationally. The compounds were evaporated and ionized by using negative‐ion mode electrospray ionization doped with NaOH to produce abundant deprotonated molecules. The ions were isolated and subjected to collision‐activated dissociation (CAD). Their fragment ions were then isolated and also subjected to CAD. This was repeated until no further fragmentation was observed (up to MS6). This approach enabled the identification of characteristic reaction pathways and delineation of reasonable fragmentation mechanisms for deprotonated molecules containing various functional groups. The varying fragmentation patterns observed for different types of compounds allow for the identification of the functionalities in these compounds. This information was utilized to identify the presence of specific functionalities and their combinations in molecules in an organosolv lignin sample.
Abstract Microorganisms regulate the decomposition of soil organic matter and the flow of plant‐available nutrients. In a temperate pine forest in North Carolina, USA , where nitrogen (N) had been experimentally added for eight years, we combined DNA ‐based measures of fungal and bacterial biomass and composition with measures of seven extracellular enzymes (ecoenzymes). These measures were then correlated with soil chemistry. Our goals were to evaluate the relative sensitivity and repeatability of multiple structural and functional measures of community organization to long‐term N deposition. Measurements were conducted at three litter/soil depths, corresponding to the litter, Oa, and mineral A horizons (max depth 10 cm) with ten spatial replicates per experimental plot. Soil chemistry differed significantly with soil depth and N amendment. Total biomass (soil DNA ), as well as fungal and bacterial biomass (measured by qPCR ), was greatest in the litter horizon and declined significantly with depth. Ecoenzyme activity patterns also changed with soil depth, transitioning from high levels of C, N, and P metabolizing activities in the litter horizon to increased oxidative activities at the lower depth. Under N amendment, soil pH decreased and nitrate concentrations increased in all three soil horizons. Correspondingly, the estimated microbial C use efficiency decreased in N‐amended soils at all depths, despite differences in microbial biomass, community composition, and soil chemistry. Overall, bacterial composition was most responsive to nitrogen amendment, but the taxonomic context of the response varied with soil horizons in conjunction with shifts in soil chemistry and enzyme activities. While a single measure that would incorporate all of the C, N, and P metabolizing activities did not emerge, many measures correlated with each other, and/or with depth and/or N amendment.
Abstract Anodic stripping voltammetry (ASV) has been widely used for the detection of several heavy metal ions in neutral and acidic solution, in many cases employing electrodes and/or solutions incorporating Bi. In this work we demonstrate that Bi(OH) 4 − ion concentration can be measured in highly alkaline 8.5 M KOH solution using ASV. The addition of Pb in similar concentrations to the Bi(OH) 4 − being measured is shown to improve both the sensitivity and precision of the method. When the Pb additive is employed, a formal limit of detection of 8.5 ppb is achieved, compared to 17.3 ppb when the Pb additive is not used. Due to the use of Bi additives in alkaline battery chemistries, it follows that separators which limit Bi(OH) 4 − diffusion into the bulk electrolyte and away from the electrodes are of interest. For this purpose, we utilize ASV to determine Bi(OH) 4 − diffusion rates through Celgard 3501, cellophane 350P00, and Nafion 211. Bi(OH) 4 − crossover rates, as determined by ASV, are shown to be repeatable and consistent with expectations from the known separator structure.
Chemical looping combustion is a promising technology for the capture of CO 2 involving reduction and oxidation of materials known as oxygen carriers. One particular carrier is hematite as it is readily available and relatively inexpensive as well as being non-toxic. The objective of this paper is to present a new particle model and reaction kinetics that can be applied to Barracuda® simulations of the fuel reactor. This was done since Barracuda does not allow for the JMA (nucleation and growth) type kinetics that were developed from analytical study the results from TGA and fixed bed experiments. This paper summarizes the analytical analysis of the fixed bed reduction experiments conducted in a cycling fixed bed reactor and subsequently modeled with Barracuda® CFD software to develop the new model. The experiments were conducted using nominally 1000 g of hematite material. The cyclic processing began with the reduction step then proceeded to the oxidation step repeating this analysis for several cycles (5 to 10). The effects of fuel partial pressure (8.4, 7.2 and 5 mole %) on the conversion were investigated. The JMA analysis assumed the reactions to occur in the shell surrounding the particle grains with diffusion of oxygen to the grain surface from the core. In contrast, working with the particle kinetics allowed in Barracuda®, the reactions occur with different hematite species (surface and core) homogeneously mixed. Therefore it is necessary to develop a new particle model with the rates being related to the amount of reactant (surface or core) in the particle. This paper presents the development of such a particle model and compares the results with experimental results.
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Abstract One Generation IV nuclear reactor, which uses a fluoride salt as a coolant, graphite reflector blocks as a moderator, and circulating buoyant TRISO pebbles as fuel is at an advanced stage of development. To characterize the seismic behavior of components of this reactor, validate numerical models for analysis, and develop recommendations for design, a set of earthquake‐simulator experiments on a scaled model of the reactor vessel and its internals was executed on a six‐degree‐of‐freedom earthquake simulator. The model was seismically isolated at its base using two types of spherical sliding bearings. The scaled model involved representations of the prototype reactor vessel, core barrel, reflector blocks, coolant, and spherical fuel pebbles. The material and geometric properties of different test components were selected based on a dynamic similitude scaling analysis and an approximate length scale of 0.4. Four sets of three‐component earthquake motions were used as inputs for testing. Instrumentation on the test specimen recorded the dynamic responses of the outer vessel, core barrel, and reflector‐block assembly, the hydrodynamic responses (sloshing and hydrodynamic pressure) of the liquid coolant, pebble consolidation under earthquake shaking, and the behavior of the isolation systems. This paper describes the design of the experiments and presents key results from the tests. The dynamic responses of the outer vessel, core barrel, and the reflector blocks revealed that the components responded as a unit for the intense shaking used in the experiments. The sloshing response of the fluid in a thin annulus near the perimeter of the vessel was heavily damped. The change in the packing fraction of the pebble bed under repeated, intense 3D earthquake shaking was less than 3%. Seismically isolating the vessel substantially reduced demands on its internal components.
Abstract Quantifying geomorphic conditions that impact riverine ecosystems is critical in river management due to degraded riverine habitat, changing flow and thermal conditions, and increasing anthropogenic pressure. Geomorphic complexity at different scales directly impacts habitat heterogeneity and affects aquatic biodiversity resilience. Here we showed that the combination of continuous spatial survey at high resolution, topobathymetric light detection and ranging (LiDAR), and continuous wavelet analysis can help identify and characterize that complexity. We used a continuous wavelet analysis on 1‐m resolution topobathymetry in three rivers in the Salmon River Basin, Idaho (USA), to identify different scales of topographic variability and the potential effects of this variability on salmonid redd site selection. On each river, wavelet scales characterized the topographic variability by portraying repeating patterns in the longitudinal profile. We found three major representative spatial wavelet scales of topographic variability in each river: a small wavelet scale associated with local morphology such as pools and riffles, a mid‐wavelet scale that identified larger channel unit features, and a large wavelet scale related to valley‐scale controls. The small wavelet scale was used to identify pools and riffles along the entire lengths of each river as well as areas with differing riffle‐pool development. Areas along the rivers with high local topographic variability (high wavelet power) at all wavelet scales contained the largest features (i.e., deepest or longest pools) in the systems. By comparing the wavelet power for each wavelet scale to Chinook salmon redd locations, we found that higher small‐scale wavelet power, which is related to pool‐riffle topography, is important for redd site selection. The continuous wavelet methodology objectively identified scales of topographic variability present in these rivers, performed efficient channel‐unit identification, and provided geomorphic assessment without laborious field surveys.
Downhole monitoring plays a crucial part in a geological carbon dioxide (CO 2 ) sequestration project, especially in providing early warnings of failure. However, most downhole monitoring technologies are often low in spatial resolution and time-consuming, or expensive and have system longevity issues. To address this issue, a robust and cost-effective distributed coaxial cable Fabry-Perot interferometer-based temperature sensor is proposed for real-time downhole monitoring. The coaxial cable sensor (CCS) was made in house and tested using a high pressure high temperature (HPHT) testing apparatus to study the sensor accuracy, sensitivity, stability, and crosstalk effect in simulated downhole conditions. The laboratory test results indicate that the sensor can work under simulated downhole conditions of pressures up to 1000 psia and temperatures up to 110°C. At 1 ATM, the sensor has an accuracy of about 1%. At 1000 psia, the hysteresis phenomenon is observed, but it is reduced and tends to stabilize after repeated heating and cooling treatments. The pressure crosstalk effect was observed on the flexible cable sensor and minimized on the rigid cable sensor. The temperature and pressure range of the distributed CCS allows long-term in situ monitoring for a well depth up to 2500 feet, which would prove of great value in detecting temperature change associated with wellbore leakage that may lead to groundwater contamination.
Glaciers of the McMurdo dry valleys (MDVs) Antarctica are the main source of streamflow in this polar desert. Because summer air temperatures hover near 0°C small changes in the energy balance strongly affect meltwater generation. In this work, we demonstrate that increased surface roughness, which alters the turbulent transfer of energy between the ice surface and atmosphere, yields a detectable increase in meltwater runoff. At low elevations on the glaciers, basin-like topography became significantly rougher over 13 years between repeat lidar surveys, yielding greater melt. In contrast, the smoother ice at higher elevation exhibited no detectable change in roughness. We pose a conceptual model of the cycle of glacier surface change as a result of climate forcing whereby glacier surfaces transition from being dominated by sublimation to becoming increasingly melt-dominated, which is reversible under prolonged cool periods. This research advances our understanding of warm season effects on polar glaciers.
Post traumatic osteoarthritis (PTOA) is a form of secondary osteoarthritis (OA) that develops in ~50% of cases of severe articular joint injuries and leads to chronic and progressive degradation of articular cartilage and other joint tissues. PTOA progression can be exacerbated by repeated injury and systemic inflammation. Few studies have examined approaches for blunting or slowing down PTOA progression with emphasis on systemic inflammation; most arthritis studies focused on the immune system have been in the context of rheumatoid arthritis. To examine how the gut microbiome affects systemic inflammation during PTOA development, we used a chronic antibiotic treatment regimen starting at weaning for 6 weeks before anterior cruciate ligament (ACL) rupture in STR/ort mice combined with lipopolysaccharide (LPS)-induced systemic inflammation. STR/ort mice develop spontaneous OA as well as a more severe PTOA phenotype than C57Bl/6J mice. By 6 weeks post injury, histological examination showed a more robust cartilage staining in the antibiotic-treated (AB) STR/ort mice than in the untreated STR/ort controls. Furthermore, we also examined the effects of AB treatment on systemic inflammation and found that the effects of LPS administration before injury are also blunted by AB treatment in STR/ort mice. The AB- or AB+LPS-treated STR/ort injured joints more closely resembled the C57Bl/6J VEH OA phenotypes than the vehicle- or LPS-treated STR/ort, suggesting that antibiotic treatment has the potential to slow disease progression and should be further explored therapeutically as prophylactic post injury.
Abstract The objective of this study is to demonstrate that melittin, a well‐studied antimicrobial peptide (AMP), can be solubilized in an active form in bicontinuous microemulsions (BMEs) that employ biocompatible oils. The systems investigated consisted of Winsor‐III and ‐IV BME phases composed of Water/Aerosol‐OT (AOT)/Polysorbate 85/isopropyl myristate and a Winsor‐IV BME employing Polysorbate 80 and limonene. We found that melittin resided in an α‐helix‐rich configuration and was in an apolar environment for the AOT/Polysorbate 85 Winsor‐III system, suggesting that melittin interacted with the surfactant monolayer and was in an active conformation. An apolar environment was also detected for melittin in the two Winsor‐IV systems, but to a lesser extent than the Winsor‐III system. Small‐angle X‐ray scattering analysis indicated that melittin at a concentration of 1.0 g/L aq in the aqueous subphase of the Winsor‐IV systems led to the greatest impact on the BME structure (e.g., decrease of quasi‐periodic repeat distance and correlation length and induction of interfacial fluidity). The antimicrobial activity of the Polysorbate 80 Winsor‐IV system was evaluated against several bacteria prominent in chronic wounds and surgical site infections (SSIs). Melittin‐free BMEs inhibited the growth of all tested bacteria due to its oil, limonene, while the inclusion of 1.0 g/L aq of melittin in the BMEs enhanced the activity against several bacteria. A further increase of melittin concentration in the BMEs had no further enhancement. These results demonstrate the potential utility of BMEs as a delivery platform for AMPs and other hydrophilic and lipophilic drugs to inhibit antibiotic‐resistant microorganisms in chronic wounds and SSIs.
Abstract Photocuring and vat photopolymerization (VP) additive manufacturing (AM) is reported for two families of fully amorphous poly(dimethyl siloxane) (PDMS) terpolymers containing either diphenylsiloxy (DiPhS) or diethylsiloxy (DiEtS) repeating units. A thiol‐functionalized PDMS crosslinker enables rapid crosslinking in air using efficient thiol–ene addition. Differential scanning calorimetry and dynamic mechanical analysis (DMA) confirm the absence of crystallinity for the DiPhS‐containing systems, while DMA shows a rubbery plateau extending to greater than 200 °C for the DiEtS‐containing system. VP‐AM of both photopolymer systems afford well‐defined 3D geometries, including high aspect ratio structures, which demonstrate feasibility of these photopolymers for the 3D printing of unique geometric objects that require elastomeric performance to temperatures as low as −120 °C.
Collagen-mimetic peptides (CMPs) are engineered molecules designed to replicate the triple-helical structure of natural collagen. A repeating x–y-Gly sequence is the defining motif of CMPs and is critical to their triple-helical structure and stability. Substitutions to the residues occupying the x and y positions present a means to modulate the CMP structure and properties. Peptoid residues—N-substituted glycine derivatives—present an attractive potential substitution due to their thermal stability, proteolytic resistance, biocompatibility, and diverse palette of non-natural side chains, but also tend to introduce a high degree of backbone flexibility that can diminish the stability of the triple helix. In this work, we report a computational active learning cycle comprising molecular dynamics simulation, Gaussian process regression, and Bayesian optimization to computationally identify a number of promising peptoid substitutions predicted to stabilize the desired quaternary structure through side chain interactions and produce stable peptoid-based collagen-like triple helices. To experimentally test the computational predictions, a top candidate identified by the screen was synthesized and imaged using scanning electron microscopy to resolve fibril-like bundles consistent with collagen-like triple helices. This work predicts a number of CMP peptoid substitutions capable of forming stable triple-helical structures, presents a generalizable design strategy for engineering desired peptoid structures, and opens new avenues for the design of peptoid-based biomimetic materials.