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At least 1,369 records · Page 76

Transforming layered 2D mats into multiphasic 3D nanofiber scaffolds with tailored gradient features for tissue regeneration

Abstract Multiphasic scaffolds with tailored gradient features hold significant promise for tissue regeneration applications. Herein, this work reports the transformation of two‐dimensional (2D) layered fiber mats into three‐dimensional (3D) multiphasic scaffolds using a ‘solids‐of‐revolution’ inspired gas‐foaming expansion technology. These scaffolds feature precise control over fiber alignment, pore size, and regional structure. Manipulating nanofiber mat layers and Pluronic F127 concentrations allows further customization of pore size and fiber alignment within different scaffold regions. The cellular response to multiphasic scaffolds demonstrates that the number of cells migrated and proliferated onto the scaffolds is mainly dependent on the pore size rather than fiber alignment. In vivo subcutaneous implantation of multiphasic scaffolds to rats reveals substantial cell infiltration, neo tissue formation, collagen deposition, and new vessel formation within scaffolds, greatly surpassing the capabilities of traditional nanofiber mats. Histological examination indicates the importance of optimizing pore size and fiber alignment for the promotion of cell infiltration and tissue regeneration. Overall, these scaffolds have potential applications in tissue modeling, studying tissue‐tissue interactions, interface tissue engineering, and high‐throughput screening for optimized tissue regeneration.

Shahriar, S. M. Shatil↗

Development and evaluation of an agar capture system (ACS) for high-throughput screening of insoluble particulate substrates with bacterial growth and enzyme activity assays

In this work, we describe a method for containing insoluble particulates for use as substrates in either bacterial growth or enzyme assays. This method was designed for high-throughput screening of environmental or engineered bacteria. Benchmarking this method with several model bacteria uncovered phenotypes not observable with the particulate substrates alone.

59 BASIC BIOLOGICAL SCIENCES↗

Simulation of natural circulation cartridge loop experiments and application to molten salt reactors

This work uses the TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics (TH) code to model natural circulation cartridge loop experiments previously conducted at Oak Ridge National Laboratory (ORNL) using water and compares the simulated and experimental results. TRACE is also used to characterize natural circulation in the cartridge loop vehicle using FLiNaK as the working fluid. The experimental vehicle is a buoyancy-aided, annular cartridge loop, referred to as a thermosyphon, and is designed to aid in qualifying liquid–fueled and/or liquid–cooled irradiation experiments for the Versatile Test Reactor (VTR), which is currently being designed in the United States. Out-of-pile water experiments have been conducted using the cartridge and the Thermosyphon Test Loop facility at ORNL, and future experiments are anticipated that would use other molten salt surrogates as the working fluid, followed by eventual insertion of a similar cartridge into VTR. Additionally, this work aims to determine how well TRACE can replicate the natural convection conditions that were observed experimentally; this serves as an initial step for validating the modeling tool for design and safety calculations to support future irradiation experiments in VTR. Initial predictions of potential experiments were made using FLiNaK as the natural circulation fluid to demonstrate the relevance of the cartridge design to molten salt reactors (MSRs). Results from this study indicate that TRACE can accurately capture natural convection phenomena in the thermosyphon and that several design changes to the current cartridge vehicle are necessary to achieve hydraulic conditions similar to those expected in MSRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Discovery, characterization, and application of chromosomal integration sites in the hyperthermophilic archaeon Sulfolobus islandicus

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, in this work, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗

A Guanidine-Degrading Enzyme Controls Genomic Stability of Ethylene-Producing Cyanobacteria

Recent studies have revealed the prevalence and biological significance of guanidine metabolism in nature. However, the metabolic pathways used by microbes to degrade guanidine or mitigate its toxicity have not been widely studied. Here, via comparative proteomics and subsequent experimental validation, we demonstrate that Sll1077, previously annotated as an agmatinase enzyme in the model cyanobacterium Synechocystis sp. PCC 6803, is more likely a guanidinase as it can break down guanidine rather than agmatine into urea and ammonium. The model cyanobacterium Synechococcus elongatus PCC 7942 strain engineered to express the bacterial ethylene-forming enzyme (EFE) exhibits unstable ethylene production due to toxicity and genomic instability induced by accumulation of the EFE-byproduct guanidine. Co-expression of EFE and Sll1077 significantly enhances genomic stability and enables the resulting strain to achieve sustained high-level ethylene production. These findings expand our knowledge of natural guanidine degradation pathways and demonstrate their biotechnological application to support ethylene bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗

A tidal disruption event coincident with a high-energy neutrino

Cosmic neutrinos provide a unique window into the otherwise hidden mechanism of particle acceleration in astrophysical objects. The IceCube Collaboration recently reported the likely association of one high-energy neutrino with a flare from the relativistic jet of an active galaxy pointed towards the Earth. However a combined analysis of many similar active galaxies revealed no excess from the broader population, leaving the vast majority of the cosmic neutrino flux unexplained. Here we present the likely association of a radio-emitting tidal disruption event, AT2019dsg, with a second high-energy neutrino. AT2019dsg was identified as part of our systematic search for optical counterparts to high-energy neutrinos with the Zwicky Transient Facility. The probability of finding any coincident radio-emitting tidal disruption event by chance is 0.5%, while the probability of finding one as bright in bolometric energy flux as AT2019dsg is 0.2%. Our electromagnetic observations can be explained through a multizone model, with radio analysis revealing a central engine, embedded in a UV photosphere, that powers an extended synchrotron-emitting outflow. This provides an ideal site for petaelectronvolt neutrino production. Assuming that the association is genuine, our observations suggest that tidal disruption events with mildly relativistic outflows contribute to the cosmic neutrino flux.

79 ASTRONOMY AND ASTROPHYSICS↗

Patch selection by bumble bees navigating discontinuous landscapes

Pollen and nectar resources are unevenly distributed over space and bees must make routing decisions when navigating patchy resources. Determining the patch selection process used by bees is crucial to understanding bee foraging over discontinuous landscapes. To elucidate this process, we developed four distinct probability models of bee movement where the size and the distance to the patch determined the attractiveness of a patch. A field experiment with a center patch and four peripheral patches of two distinct sizes and distances from the center was set up in two configurations. Empirical transition probabilities from the center to each peripheral patch were obtained at two sites and two years. The best model was identified by comparing observed and predicted transition probabilities, where predicted values were obtained by incorporating the spatial dimensions of the field experiment into each model’s mathematical expression. Bumble bees used both patch size and isolation distance when selecting a patch and could assess the total amount of resources available in a patch. Bumble bees prefer large, nearby patches. This information will facilitate the development of a predictive framework to the study of bee movement and of models that predict the movement of genetically engineered pollen in bee-pollinated crops.

54 ENVIRONMENTAL SCIENCES↗

The effect of triangularity on predicted pedestals for the CFETR

In this work, the dominant unstable magnetohydrodynamic mode and its stable region in the pedestal of the China Fusion Engineering Test Reactor are studied by numerical modeling with the peeling-ballooning theory over a wide range of triangularities (δ) and collisionalities (υ*). A new accessible stable region is found at δ<−0.1 for large βN,ped and υ*. This new stable region expands toward lower βN,ped and υ* with decreasing δ and is totally covered by the peeling unstable region with δ=−0.5 because of the increasing trapped particle fraction (ft,eff). The sensitivity of this new stable region to the kinetic ballooning mode constraint and elongation is studied. For negative and low δ<0.1, the boundary of the first stable region is determined from the ballooning mode. For δ>0.1, the peeling mode becomes dominant as the boundary approaches low s with low υ*, while the ballooning mode is still dominant at the boundary with high υ*. When δ increases beyond 0.46, the first stable region is expanded, and access to the second stable region of the ballooning mode opens up. The entire newly connected region of the first and second stable regions keeps expanding with further increases in δ until δ=0.6. Beyond this value, the ballooning mode becomes more unstable with increasing δ, while the peeling mode is approximately unchanged with increasing δ in this range. The change in the dominant mode and the stable region with increasing δ can be explained by the trade-off between the stabilization effect from the deeper poloidal magnetic well and destabilization due to the enlarged drive term.

Physics↗

Multi-fidelity parametric sensitivity estimation for large eddy simulation with the Spalart–Allmaras model

A computationally affordable approach to estimate parametric sensitivities of engineering relevant quantities of interest for a large eddy simulation (LES) is explored. The method is based on defining a Reynolds-averaged Navier–Stokes (RANS) problem that is constrained to reproduce the LES mean flow field. Here, the proposed method is described and assessed for a shock/boundary layer interaction problem, where the shock angle and wall temperature are considered variable or uncertain. In the current work, we show that the proposed method offers improved sensitivity predictions for certain flow features as compared to standalone RANS simulations, while using a fraction of the LES cost.

42 ENGINEERING↗

Cost Drivers for a Tokamak-Based Compact Pilot Plant

A comprehensive systems code that includes a range of physics and engineering considerations along with a simplified costing model has been utilized to evaluate the primary cost drivers for a compact tokamak pilot plant. The systems code has been benchmarked against several tokamak reactor designs and is utilized with sophisticated optimization algorithms to develop optimal solutions for a set of user-specified assumptions and design constraints. Here, in contrast to previous models that have focused on the cost of electricity as the key cost metric, this study uses the estimated capital cost of the facility. The analysis suggests that a pilot plant with the following features may offer potential for a cost-attractive pilot plant: A ~ 3, H 98y2 > 1.5, P net = 200 MW, 𝜏 𝑝⁢𝑢⁢𝑙⁢𝑠⁢𝑒 ~ 1 to 2 h utilizing rare-earth barium copper oxide (REBCO) magnet technology and a plug-bucked central solenoid/toroidal field (CS/TF) magnet support structure. While REBCO magnets offer some advantages relative to Nb 3 Sn magnets in all cases, the most gain is obtained when combined with the plug-bucked CS/TF bucking solution. Pulsed operation reduces capital cost requirements relative to steady-state operation, especially at low confinement. Cost sensitivity studies indicate that there are significant cost uncertainties associated with the achievable confinement quality, tritium breeding capability, attainable thermal efficiency, and achievable neutron wall loading, suggesting that these areas are the most critical areas in reducing the cost risk for a compact tokamak pilot plant. Further cost sensitivity studies indicate that the estimated cost is most sensitive to the underlying cost of the magnetic coils, providing further impetus to better establish cost-effective means for producing fusion magnets.

Compact pilot plant↗

Individualized empirical baselines for evaluating the energy performance of existing buildings

The evaluation of building energy performance requires a baseline for comparison. Common empirical baselines are usually used for existing buildings since they are fast and convenient. However, the same type of building at the same location will receive the same baseline despite their difference in usage. Individualized baselines by creating building energy models are possible solutions, but it is labor intensive and time-consuming. To fill the gap, this study is to develop individualized empirical baselines for existing buildings in a fast way. First, common empirical baselines are created based on survey data. Then, to get training samples, building energy models for large-scale existing buildings are created and simulated. So finally, based on simulation results, mathematical models to get individualized empirical baselines in a fast way are created. U.S. medium office buildings were used as an example to demonstrate the method. We developed 30 mathematical models for medium office buildings in two vintages (constructed before 1980 and after 1980) and 15 climate zones. The mean absolute percentage errors (MAPE) between the individualized empirical baselines and the modeled baselines for those 30 mathematical models are all lower than 5.5%. An engineer can obtain the individualized empirical baseline for an existing building in a few seconds by using the open-source tool we developed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fast switching magnet for heavy ion beam separation

This paper presents the design for a switching magnet capable of deflecting 6.5 MeV/u heavy-ion beams with mass-to-charge ratio of 7 by 10 degrees. This magnet can produce variable flat-top pulses from 1 to 30 ms with rise and fall times of less than 0.5 ms at a variable duty cycle of 3–91% into a heavily inductive load. The magnet has a laminated, iron dominated, H-shaped core. Directly-cooled copper pancake coils energize the magnet. We present the magnet design considerations, including the results of extensive computer modeling. Finally, we also present the conceptual engineering design and the studies of magnet yoke fabrication.

47 OTHER INSTRUMENTATION↗

Verification, Validation, and Uncertainty Quantification in Thermal Hydraulics, Freeman Scholar Lecture (2019)

Engineering problems are generally solved by analytical models or computer codes. These models, in addition to conservation equations, also include many empirical relationships and approximate numerical methods. Each of these components contributes to the uncertainty in the prediction. A systematic approach to judge the applicability of the code to the intended application is needed. It starts from verification of implementation of formulation in the code, identification of important phenomena, finding relevant tests with quantified uncertainty for these phenomena, and validation of the code by comparing predictions with the relevant test data. The relevant tests must address phenomena as expected in the intended application. In case of small size or limited condition tests, the scaling analyses are needed to assess the relevancy of the tests. Finally, a statement of uncertainty in the prediction is needed. Systematic approaches are described to aggregate uncertainties from different components of the code for intended application. Here, verification, validation, and uncertainty quantifications (VVUQs) are briefly described.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A High-efficacy CRISPRi System for Gene Function Discovery in Zymomonas mobilis

Zymomonas mobilis is a promising biofuel producer due to its high alcohol tolerance and streamlined metabolism that efficiently converts sugar to ethanol. Z. mobilis genes are poorly characterized relative to those of model bacteria, hampering our ability to rationally engineer the genome with pathways capable of converting sugars from plant hydrolysates into valuable biofuels and bioproducts. Many of the unique properties that make Z. mobilis an attractive biofuel producer are controlled by essential genes; however, these genes cannot be manipulated using traditional genetic approaches (e.g., deletion or transposon insertion) because they are required for viability. CRISPR interference (CRISPRi) is a programmable gene knockdown system that can precisely control the timing and extent of gene repression, thus enabling targeting of essential genes. Here, we establish a stable, high-efficacy CRISPRi system in Z. mobilis that is capable of perturbing all genes—including essential genes. We show that Z. mobilis CRISPRi causes either strong knockdowns (>100-fold) using single guide RNA (sgRNA) spacers that perfectly match target genes or partial knockdowns using spacers with mismatches. We demonstrate the efficacy of Z. mobilis CRISPRi by targeting essential genes that are universally conserved in bacteria, are key to the efficient metabolism of Z. mobilis, or underlie alcohol tolerance. Our Z. mobilis CRISPRi system will enable comprehensive gene function discovery, opening a path to rational design of biofuel production strains with improved yields.

lignocellulosic hydrolysate↗

Multilevel Monte Carlo Estimators For Derivative-Free Optimization Under Uncertainty

Optimization is a key tool for scientific and engineering applications; however, in the presence of models affected by uncertainty, the optimization formulation needs to be extended to consider statistics of the quantity of interest. Optimization under uncertainty (OUU) deals with this endeavor and requires uncertainty quantification analyses at several design locations; i.e., its overall computational cost is proportional to the cost of performing a forward uncertainty analysis at each design location. An OUU workflow has two main components: an inner loop strategy for the computation of statistics of the quantity of interest, and an outer loop optimization strategy tasked with finding the optimal design, given a merit function based on the inner loop statistics. Here, in this work, we propose to alleviate the cost of the inner loop uncertainty analysis by leveraging the so-called multilevel Monte Carlo (MLMC) method, which is able to allocate resources over multiple models with varying accuracy and cost. The resource allocation problem in MLMC is formulated by minimizing the computational cost given a target variance for the estimator. We consider MLMC estimators for statistics usually employed in OUU workflows and solve the corresponding allocation problem. For the outer loop, we consider a derivative-free optimization strategy implemented in the SNOWPAC library; our novel strategy is implemented and released in the Dakota software toolkit. We discuss several numerical test cases to showcase the features and performance of our approach with respect to its Monte Carlo single fidelity counterpart.

97 MATHEMATICS AND COMPUTING↗

WATTS: Workflow and template toolkit for simulation

Modeling and simulation in many science and engineering domains often involves the execution and/or iteration of a sequence of applications, with data transfer between applications typically required. These applications often do not have a formal application programming interface (API). Instead, executing an application requires first writing a text-based input file, the format of which is typically defined in a user’s manual. While text-based input files are suitable for simple one-off calculations, they can become cumbersome if a user wants to execute the applications multiple times and systematically vary input parameters, especially when a complex workflow is involved. In this case, they must resort to either manually making changes in the input file or developing their own script that modifies the input file and executes the application. Depending on the format of the input file, writing such a script can be a non-trivial and error-prone task.

97 MATHEMATICS AND COMPUTING↗

Concurrency Supply Chain Optimization (Final Report)

Brunswick is experiencing unprecedented volume for engines and fully produced boats. Supply Chain (parts) has difficulty accurately forecasting demand needs which presents problems in the manufacturing process. Streamline ordering process enabling the Brunswick Boat Group (BBG) to more efficiently forecast part demand for the Mercury Engine Group by setting up an AI/ML model. Initial focus will be 15 SKUs with inaccurate demand forecasting based on current manual processes.

97 MATHEMATICS AND COMPUTING↗

Predictive Capability Maturity Model Demonstration for Cylindrical Cavity Coupling Using Gemma in the Next Generation Workflow

The predictive capability maturity model (PCMM) uses the expert elicitation process to generate credibility evidence for a particular analysis. To ensure Gemma has the capability to efficiently produce this credibility evidence, next generation workflows (NGW) are created for the solution verification, calibration/validation, and input uncertainty quantification portions of the PCMM assessment. These workflows are then used on the Higgins cylinder problem, which is representative of applications involving external-to-internal electromagnetic field coupling through a slot. The uncertainties calculated using these workflows are then used to calculate the validation comparison error and the validation uncertainty for the model following the American Society of Mechanical Engineers (ASME) verification and validation (V&V) 20 standard. These workflows will enable analysts to iterate each element of PCMM more efficiently than if completed without using a NGW workflow. An example of this iterative process is shown in Section 7.2.

42 ENGINEERING↗