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At least 163 records · Page 9

Engineering activatable promoters for scalable and multi-input CRISPRa/i circuits

Dynamic, multi-input gene regulatory networks (GRNs) are ubiquitous in nature. Multilayer CRISPR-based genetic circuits hold great promise for building GRNs akin to those found in naturally occurring biological systems. We develop an approach for creating high-performing activatable promoters that can be assembled into deep, wide, and multi-input CRISPR-activation and -interference (CRISPRa/i) GRNs. By integrating sequence-based design and in vivo screening, we engineer activatable promoters that achieve up to 1,000-fold dynamic range in an Escherichia coli-based cell-free system. These components enable CRISPRa GRNs that are six layers deep and four branches wide. We show the generalizability of the promoter engineering workflow by improving the dynamic range of the light-dependent EL222 optogenetic system from 6-fold to 34-fold. Additionally, high dynamic range promoters enable CRISPRa systems mediated by small molecules and protein–protein interactions. We apply these tools to build input-responsive CRISPRa/i GRNs, including feedback loops, logic gates, multilayer cascades, and dynamic pulse modulators. Our work provides a generalizable approach for the design of high dynamic range activatable promoters and enables classes of gene regulatory functions in cell-free systems.

42 ENGINEERING↗

Effect of Soil Properties and Input Motion on Site Amplification Using Validated Nonlinear Soil Model

Here, three-dimensional (3-D) nonlinear site response analyses are conducted using finite element models of actual soil profiles from ten nuclear power plant (NPP) sites in the United States to investigate the effects of soil properties and input motions on site amplification. The modeling approach developed in this study combines several novel elements, such as 3-D analysis (including vertical motions), nonlinear inelastic behavior of soil (strain-dependent shear modulus reduction and hysteretic damping), formulation of nonreflecting boundary conditions at the base, and generation of realistic outcrop ground motions for specific sites. All these elements of the modeling approach are first validated using actual data from five earthquakes at three downhole array stations recorded in the Kiban-Kyoshin network (KiK-net), Japan. The same approach is then used to develop site models of ten NPP sites in the United States and corresponding ground motions that are spectrally matched to the site hazard spectra. Eight sets of three-component input motions are used in the study and are categorized on the basis of presence or absence of a near-field pulse in the seed ground motions used for spectral matching. It is found that all sites retain a definite site amplification function regardless of the input motion, provided that the seed motion is spectrally matched to the site hazard spectra. The magnitude of site amplification and frequencies at which they occur depend upon soil properties, particularly the shear wave velocity profile and the constitutive relationship (strain-dependent shear modulus reduction and hysteretic damping) of soil. Amplification of spectral acceleration in the vertical direction (up-down motion) is found to be just as much as, if not more than, the amplification in the horizontal direction. Peak shear strain is found to be about 20% larger for near-field motions compared to far-field motions whereas maximum horizontal site amplification for far-field motions is found to be consistently larger than that of near-field motions, even though the differences between the two remain within the scatter resulting from individual ground motions.

99 GENERAL AND MISCELLANEOUS↗

Microbiome processing of organic nitrogen input supports growth and cyanotoxin production of Microcystis aeruginosa cultures

Abstract Nutrient-induced blooms of the globally abundant freshwater toxic cyanobacterium Microcystis cause worldwide public and ecosystem health concerns. The response of Microcystis growth and toxin production to new and recycled nitrogen (N) inputs and the impact of heterotrophic bacteria in the Microcystis phycosphere on these processes are not well understood. Here, using microbiome transplant experiments, cyanotoxin analysis, and nanometer-scale stable isotope probing to measure N incorporation and exchange at single cell resolution, we monitored the growth, cyanotoxin production, and microbiome community structure of several Microcystis strains grown on amino acids or proteins as the sole N source. We demonstrate that the type of organic N available shaped the microbial community associated with Microcystis, and external organic N input led to decreased bacterial colonization of Microcystis colonies. Our data also suggest that certain Microcystis strains could directly uptake amino acids, but with lower rates than heterotrophic bacteria. Toxin analysis showed that biomass-specific microcystin production was not impacted by N source (i.e. nitrate, amino acids, or protein) but rather by total N availability. Single-cell isotope incorporation revealed that some bacterial communities competed with Microcystis for organic N, but other communities promoted increased N uptake by Microcystis, likely through ammonification or organic N modification. Our laboratory culture data suggest that organic N input could support Microcystis blooms and toxin production in nature, and Microcystis-associated microbial communities likely play critical roles in this process by influencing cyanobacterial succession through either decreasing (via competition) or increasing (via biotransformation) N availability, especially under inorganic N scarcity.

54 ENVIRONMENTAL SCIENCES↗

Data and scripts associated with “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” (v3)

This data package is associated with the publication “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” submitted to Journal of Advances in Modeling Earth Systems (Butler et al. 2025). This study developed the Sequential Precipitation Input Tagging (SPIT) framework to tag input precipitation and estimate water transit times and hydrologic tracers. SPIT tags all precipitation events at regular intervals over an extended period (monthly tags over seven years) in a hydrologic model from 2016-2022. SPIT is applied at six National Ecological Observatory Network (NEON) sites across the continental United States to calculate transit time distributions (TTD) and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations in stream water (δ18O) within a water-tagging enabled version of the Weather Research and Forecast (WT-WRF-Hydro) model with national water model (NWM) configurations. We go on to validate WT-WRF-Hydro estimates against Butler et al. (2023), who analyzed the same NEON sites using stable water isotope data to estimate water transit times. This new tracking method provides a detailed picture of water movement and helps improve predictions about water availability in the future. This data package was originally published in January 2025. It was updated May 2025 (v2; new and modified files) and October 2025 (v3; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. This data package contains the data and scripts used to develop the SPIT framework WT-WRF-Hydro (Water Tagging Weather Research and Forecasting Hydrologic) model and is associated with the following GitHub repository: https://github.com/zbutler33/SPIT-Framework. This data package contains five parent folders: (1) “Manipulated_outputs”, (2) “Metadata”, (3) “Observed”, (4) “Outputs”, and (5) “Scripts”. Each of these parent folders contains additional subfolders and files. Please see the FLMD (“v*_Butler_2024_WT_WRF_Hydro_flmd.csv”) for a list of all the files contained in this data package and descriptions for each. See the data dictionary (“v*_Butler_2024_WT_WRF_Hydro_dd.csv”) for definitions and units of all of the tabular (files ending in “.csv” and ".tsv") column headers.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux FLUXNET-1F US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3). This is the FLUXNET version of the carbon flux data for the site US-OPE Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) produced by applying the standard ONEFlux (1F) software. Site Description - The Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) site is located at the Beltsville Agricultural Research Center in Prince George's County, MD, and consists of a 22-ha production field, with an adjacent riparian wetland and first-order stream. Scientists from several U.S. Federal agencies, universities (foreign and domestic), and private industry have conducted multidisciplinary research at this location since 1998.

Alfieri, Joe [USDA-ARS Hydrology and Remote Sensin↗

Generating MCNP Input Files for Unstructured Mesh Geometries

Los Alamos National Laboratory's (LANL) Monte Carlo N-Particle (MCNP) transport code version 6 has the capability for tracking particles on unstructured mesh (UM) geometry models. The MCNP UM feature has been developed for performing calculations of complex geometry models. This capability tracks particles on hybrid geometries where finite element meshes are embedded into constructive solid geometry (CSG) cells. The MCNP UM feature was originally designed to read UM models created by Abaqus/CAE software suite. MCNP versions 6.2.0 and later can process UM models read from Abaqus input les or MCNPUM les converted from Abaqus input les. Sandia National Laboratory's Cubit Toolkit and other finite element analysis software packages may generate UM models and then convert these models into Abaqus input formats.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Community Solar Program Design Considerations & Modeling Inputs

Designing and modeling a community solar (CS) program is a complex process with numerous variable inputs that are interconnected. Modeling a CS program can be useful to inform the programs design itself while also providing stakeholders of all types with information. Accurate data inputs and assumptions are key to ensuring that a model is informative and as representative of real market conditions as possible. This report is an exploration of community solar program modeling considerations, especially as it relates to data inputs such as capital costs, administrative fees, and subscription size, using a CS program in North Carolina as a case study.

14 SOLAR ENERGY↗

Polaris-PARCS Sensitivity Study on LWR Fuel Cycles: Polaris Input Options

This study is the first of a multi-phase effort to assess the sensitivity of light-water reactor (LWR) core-level prediction biases to changes in lattice-level calculation parameters. Prediction bias is the measured-to-predicted difference in a core-level quantity of interest (QOI) which can be estimated by comparing the simulation results with the plant-measured data for key nuclear parameters. The LWR two-step neutronics codes employed herein are the SCALE–Polaris lattice physics code (v6.3.1) and the Purdue Advanced Reactor Core Simulator (PARCS) nodal diffusion simulator (v3.4.2), both funded and used for confirmatory analysis to support licensing by the US Nuclear Regulatory Commission (NRC). Polaris–PARCS is used to model Watts Bar Unit 1 cycles 1–3 and Peach Bottom Unit 2 cycles 1–3. This study focuses on the impact of changes to Polaris input options such as scattering treatment or quadrature settings and how these input options induce changes in core-level quantities of interest (QOIs)bias. The report documents multiple bias assessments for different modeling choices and compares the bias magnitude to the QOI measurement uncertainties. Future companion reports will investigate the sensitivity of core-level LWR prediction bias to Polaris input options and Polaris-computed QOIs such as few-group assembly-homogenized cross sections to gain an understanding of the key drivers of prediction bias at lattice and core levels for application of a two-step LWR neutronics procedure in a licensing scenario.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FY25 MOOSE Usability Improvements: 3D Meshing Capabilities, Initiation of Geometry Support for Monte Carlo Tools, and Enhancement of MOOSE/Workbench User Input Interactions

Usability improvements have been made to MOOSE and Workbench in FY25 to enhance usability and user workflows. Assorted enhancement have been made to MOOSE’s intrinsic meshing capabilities in order to enable more flexible and complex meshing of nuclear reactor systems, in particular for 3D applications. Mesh generators have been added to perform operations such as batch mesh generation, surface mesh generation, and creation of 3D transition layers. These mesh generation capabilities make it much easier to generate high quality non-extruded 3D meshes. Additionally, work to integrate Monte Carlo reactor physics simulations into MOOSE-based multi-physics workflows has reached another milestone with the implementation of the Constructive Solid Geometry (CSG) base framework. This framework lays the foundation for mesh generators to offer the user a generic CSG output option (as opposed to a finite element mesh). To support users, workshop on the MOOSE Reactor Module was delivered which featured hands-on examples using the NEAMS Workbench on INL’s High Performance Computing system. Recent updates to the NEAMS Workbench, WASP, and the MOOSE language server have introduced several improvements aimed at making MOOSE-based simulation setup and input management faster, more accurate, and easier to use. Key capabilities that have been added include multi-tab-stop autocompletion, visual input diagnostics, developer-directed data visualizations, upgraded ParaView integration, and Workspace-level file tracking. Together, these changes make it easier for users to build, validate, and manage complex MOOSE-based simulation models — especially those involving reusable components, included files, and datasets. The improvements are designed to save time, reduce input errors, and help users get to a successful simulation run faster, with more confidence in the results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[ 18 F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [ 18 F]Nifene, displaying similar pKa and binding affinity to nicotine. Time–activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

2-FA85380↗

Modeling Kilonova Light Curves: Dependence on Nuclear Inputs

The mergers of binary neutron stars, as well as black hole–neutron star systems, are expected to produce an electromagnetic counterpart that can be analyzed to infer the element synthesis that occurred in these events. We investigate one source of uncertainties pertinent to lanthanide-rich outflows: the nuclear inputs to rapid neutron capture nucleosynthesis calculations. We begin by examining 32 different combinations of nuclear inputs: eight mass models, two types of spontaneous fission rates, and two types of fission daughter product distributions. We find that such nuclear physics uncertainties typically generate at least one order of magnitude uncertainty in key quantities such as the nuclear heating (one and a half orders of magnitude at 1 day post-merger), the bolometric luminosity (one order of magnitude at 5 days post-merger), and the inferred mass of material from the bolometric luminosity (factor of 8 when considering the 8–10 day region). Since particular nuclear processes are critical for determining the electromagnetic signal, we provide tables of key nuclei undergoing β-decay, α-decay, and spontaneous fission important for heating at different times, identifying decays that are common among the many nuclear input combinations.

79 ASTRONOMY AND ASTROPHYSICS↗

Sensitivity Analysis of Numerical Modeling Input Parameters on Wind Turbine Loads in Deterministic Transient Load Cases

Aero-hydro-elastic-servo numerical models used to design and analyze wind turbines are based on thousands of variable input parameters that dictate the inflow, aerodynamic, structural, and control characteristics of the system as well as sea state, hydrodynamic, and mooring characteristics for fixed-bottom and floating offshore wind turbines. Each of these parameters has some level of uncertainty, which can significantly impact the predicted loads. Understanding the uncertainty in the inputs is critical to understanding the uncertainty in the outputs. This work demonstrates a screening technique to identify which parameters ultimate loads are most sensitive to so that more focus can be given to quantifying the possible range of those parameters. This technique has been demonstrated previously for different turbine and load case types and is extended here for a floating offshore wind turbine in design load cases with transient events both in the inflow and operations. Each load case features a deterministic gust, including variations in wind speed, direction, and shear. Load cases are considered with an operating turbine as well as with prescribed fault, startup, and shutdown procedures. The study found that key input parameters with a large impact on loads include the length of the gust, the magnitude of direction change and speed in the gust, the initial wind speed, and the shape of the gust profile.

17 WIND ENERGY↗

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads

Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.

17 WIND ENERGY↗

Input noise approximation in tracker modeling

The validity of approximating random Gaussian distributed inputs used in human response modeling by sums of discrete sine waves is studied. An ideal rectangular power density spectrum is simulated using both filtered Gaussian white noise and sums-of-discrete sine waves with three different input cutoff frequencies in the same compensatory tracking task. Resulting normalized tracking error and quality operator observations are used to investigate apparent discrepancies in human operator characteristics. Results show that discrete and continuous input tracking data compare favorable when the power in the crossover region is taken into account.

Torrey, P. F.↗

NASTRAN postprocessor program for transient response to input accelerations

The description of a transient analysis program for computing structural responses to input base accelerations is presented. A hybrid modal formulation is used and a procedure is demonstrated for generating and writing all modal input data on user tapes via NASTRAN. Use of several new Level 15 modules is illustrated along with a problem associated with reading the postprocessor program input from a user tape. An example application of the program is presented for the analysis of a spacecraft subjected to accelerations initiated by thrust transients. Experience with the program has indicated it to be very efficient and economical because of its simplicity and small central memory storage requirements.

Wingate, R. T.↗

A Theoretical Investigation of the Input Characteristics of a Rectangular Cavity-Backed Slot Antenna

Equations which represent the magnetic and electric stored energies are derived for an infinite section of rectangular waveguide and a rectangular cavity. These representations which are referred to as being physically observable are obtained by considering the difference in the volume integrals appearing in the complex Poynting theorem. It is shown that the physically observable stored energies are determined by the field components that vanish in a reference plane outside the aperture. These physically observable representations are used to compute the input admittance of a rectangular cavity-backed slot antenna in which a single propagating wave is assumed to exist in the cavity. The slot is excited by a voltage source connected across its center; a sinusoidal distribution is assumed in the slot. Input-admittance calculations are compared with measured data. In addition, input-admittance curves as a function of electrical slot length are presented for several size cavities. For the rectangular cavity backed slot antenna, the quality factor and relative bandwidth were computed independently by using these energy relationships. It is shown that the asymptotic relationship which is usually assumed to exist between the quality bandwidth and the reciprocal of relative bandwidth is equally valid for the rectangular cavity backed slot antenna.

Cockrell, C. R.↗

On the design of optimal input signals in system identification

The problem of designing optimal inputs in the identification of multi-input multi-output linear systems with unknown time-varying parameters is considered using a Bayesian approach. A sensitivity index gives a measure of performance for the closed-loop system inputs. The computation of the optimal closed-loop mappings is shown to be a nontrivial exercise in stochastic control with no analytic solution, but optimal open-loop and affine laws yield much more tractable problems. For time-invariant systems, the sensitivity index considered is shown to be equivalent to the trace of the (strictly positive definite) information matrix associated with the system. Numerical examples are given. A Kalman filter is used to estimate the parameters. A necessary condition for the Kalman filter not to diverge when applying linear feedback is also given.

Lopez-Toledo, A. A.↗