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Results for “shifting functional data”

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At least 595 records · Page 33

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Structural analysis of a new carotenoid-binding protein: the C-terminal domain homolog of the OCP

Abstract The Orange Carotenoid Protein (OCP) is a water-soluble protein that governs photoprotection in many cyanobacteria. The 35 kDa OCP is structurally and functionally modular, consisting of an N-terminal effector domain (NTD) and a C-terminal regulatory domain (CTD); a carotenoid spans the two domains. The CTD is a member of the ubiquitous Nuclear Transport Factor-2 (NTF2) superfamily (pfam02136). With the increasing availability of cyanobacterial genomes, bioinformatic analysis has revealed the existence of a new family of proteins, homologs to the CTD, the C-terminal domain-like carotenoid proteins (CCPs). Here we purify holo-CCP2 directly from cyanobacteria and establish that it natively binds canthaxanthin (CAN). We use small-angle X-ray scattering (SAXS) to characterize the structure of this carotenoprotein in two distinct oligomeric states. A single carotenoid molecule spans the two CCPs in the dimer. Our analysis with X-ray footprinting-mass spectrometry (XFMS) identifies critical residues for carotenoid binding that likely contribute to the extreme red shift (ca. 80 nm) of the absorption maximum of the carotenoid bound by the CCP2 dimer and a further 10 nm shift in the tetramer form. These data provide the first structural description of carotenoid binding by a protein consisting of only an NTF2 domain.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression. Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to previous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding. Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1996

Identification of the cAMP response element that controls transcriptional activation of the insulin-like growth factor-I gene by prostaglandin E2 in osteoblasts

Insulin-like growth factor-I (IGF-I), a multifunctional growth factor, plays a key role in skeletal growth and can enhance bone cell replication and differentiation. We previously showed that prostaglandin E2 (PGE2) and other agents that increase cAMP activated IGF-I gene transcription in primary rat osteoblast cultures through promoter 1 (P1), the major IGF-I promoter, and found that transcriptional induction was mediated by protein kinase A. We now have identified a short segment of P1 that is essential for full hormonal regulation and have characterized inducible DNA-protein interactions involving this site. Transient transfections of IGF-I P1 reporter genes into primary rat osteoblasts showed that the 328-base pair untranslated region of exon 1 was required for a full 5.3-fold response to PGE2; mutation in a previously footprinted site, HS3D (base pairs +193 to +215), reduced induction by 65%. PGE2 stimulated nuclear protein binding to HS3D. Binding, as determined by gel mobility shift assay, was not seen in nuclear extracts from untreated osteoblast cultures, was detected within 2 h of PGE2 treatment, and was maximal by 4 h. This DNA-protein interaction was not observed in cytoplasmic extracts from PGE2-treated cultures, indicating nuclear localization of the protein kinase A-activated factor(s). Activation of this factor was not blocked by cycloheximide (Chx), and Chx did not impair stimulation of IGF-I gene expression by PGE2. In contrast, binding to a consensus cAMP response element (CRE; 5'-TGACGTCA-3') from the rat somatostatin gene was not modulated by PGE2 or Chx. Competition gel mobility shift analysis using mutated DNA probes identified 5'-CGCAATCG-3' as the minimal sequence needed for inducible binding. All modified IGF-I P1 promoterreporter genes with mutations within this CRE sequence also showed a diminished functional response to PGE2. These results identify the CRE within the 5'-untranslated region of IGF-I exon 1 that is required for hormonal activation of IGF-I gene transcription by cAMP in osteoblasts.

NASA Discipline Musculoskeletal↗

NASA NTRS2005

Cosmic Infrared Background and Early Galaxy Evolution

The cosmic infrared background (CIB) reflects the sum total of galactic luminosities integrated over the entire age of the universe. From its measurement the red-shifted starlight and dust-absorbed and re-radiated starlight of the CIB can be used to determine (or constrain) the rates of star formation and metal production as a function of time and deduce information about objects at epochs currently inaccessible to telescopic studies. This review discusses the state of current CIB measurements and the (mostly space-based) instruments with which these measurements have been made, the obstacles (the various foreground emissions) and the physics behind the CIB and its structure. Theoretical discussion of the CIB levels can now be normalized to the standard cosmological model narrowing down theoretical uncertainties. We review the information behind and theoretical modeling of both the mean (isotropic) levels of the CIB and their fluctuations. The CIB is divided into three broad bands: near-IR (NIR), mid-IR (MIR) and far-IR (FIR). For each of the bands we review the main contributors to the CIB flux and the epochs at which the bulk of the flux originates. We also discuss the data on the various quantities relevant for correct interpretation of the CIB levels: the star-formation history, the present-day luminosity function measurements, resolving the various galaxy contributors to the CIB, etc. The integrated light of all galaxies in the deepest NIR galaxy counts to date fails to match the observed mean level of the CIB, probably indicating a significant high-redshift contribution to the CIB. Additionally, Population III stars should have left a strong and measurable signature via their contribution to the CIB anisotropies for a wide range of their formation scenarios, and measuring the excess CIB anisotropies coming from high z would provide direct information on the epoch of the first stars.

Kashlinsky, Alexander↗

DOE OSTI2025

Finch: Toxicity Dose Response Curve Prediction of Chemical Compounds and Mixtures

A paradigm shift in chemical risk assessment is emphasizing mixture testing over single compound analysis, eliminating animal testing, and adopting advanced modeling approaches to understand mixture activity profiles. However, existing computational models largely focus on single chemicals, with few effective solutions for modeling complex mixtures that account for synergistic or antagonistic effects and multiple Modes of Action (MoA). Conventional methods like concentration addition (CA) and independent action (IA) are insufficient for this task as they are designed for simplistic interactions and struggle to account for the dynamic and multifaceted nature of chemical mixtures, such as overlapping MoA and non-linear interactions. Finch offers a novel approach utilizing deep learning (DL) embeddings and multi-task quantitative structure-activity relationship (QSAR) models to improve chemical exposure prediction. By leveraging molecular descriptors, physiochemical properties, and large language model (LLM) embeddings from SMILES inputs, Finch preserves critical information in a latent space thereby enhancing predictive accuracy. The multi-task learning aspect of Finch is highly advantageous, as it simultaneously optimizes multiple loss functions, leveraging all available data across tasks to develop generalized representations that effectively capture complex ingredient interactions within mixtures.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2013

North American Tropical Cyclone Landfall and SST: A Statistical Model Study

A statistical-stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones (TCs) is used to examine the relationship between climate and landfall rates along the North American Atlantic and Gulf Coasts. The model draws on archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and one of two different measures of sea surface temperature (SST): 1) SST averaged over the NA subtropics and the hurricane season and 2) this SST relative to the seasonal global subtropical mean SST (termed relSST). Here, the authors focus on SST by holding ENSO to a neutral state. Jackknife uncertainty tests are employed to test the significance of SST and relSST landfall relationships. There are more TC and major hurricane landfalls overall in warm years than cold, using either SST or relSST, primarily due to a basinwide increase in the number of storms. The signal along the coast, however, is complex. Some regions have large and significant sensitivity (e.g., an approximate doubling of annual major hurricane landfall probability on Texas from -2 to +2 standard deviations in relSST), while other regions have no significant sensitivity (e.g., the U.S. mid-Atlantic and Northeast coasts). This geographic structure is due to both shifts in the regions of primary TC genesis and shifts in TC propagation.

El Nino↗

DOE OSTI2024

Identification and characterization of a skin microbiome on Caenorhabditis elegans suggests environmental microbes confer cuticle protection

ABSTRACT In the wild, C. elegans are emersed in environments teeming with a veritable menagerie of microorganisms. The C. elegans cuticular surface serves as a barrier and first point of contact with their microbial environments. In this study, we identify microbes from C. elegans natural habitats that associate with its cuticle, constituting a simple “skin microbiome.” We rear our animals on a modified CeMbio, mCeMbio, a consortium of ecologically relevant microbes. We first combine standard microbiological methods with an adapted micro skin-swabbing tool to describe the skin-resident bacteria on the C. elegans surface. Furthermore, we conduct 16S rRNA gene sequencing studies to identify relative shifts in the proportion of mCeMbio bacteria upon surface-sterilization, implying distinct skin- and gut-microbiomes. We find that some strains of bacteria, including Enterobacter sp. JUb101 , are primarily found on the nematode skin, while others like Stenotrophomonas indicatrix JUb19 and Ochrobactrum vermis MYb71 are predominantly found in the animal’s gut. Finally, we show that this skin microbiome promotes host cuticle integrity in harsh environments. Together, we identify a skin microbiome for the well-studied nematode model and propose its value in conferring host fitness advantages in naturalized contexts. IMPORTANCE The genetic model organism C. elegans has recently emerged as a tool for understanding host–microbiome interactions. Nearly all of these studies either focus on pathogenic or gut-resident microbes. Little is known about the existence of native, nonpathogenic skin microbes or their function. We demonstrate that members of a modified C. elegans model microbiome, mCeMbio, can adhere to the animal's cuticle and confer protection from noxious environments. We combine a novel micro-swab tool, the first 16S microbial sequencing data from relatively unperturbed C. elegans , and physiological assays to demonstrate microbially mediated protection of the skin. This work serves as a foundation to explore wild C. elegans skin microbiomes and use C. elegans as a model for skin research.

16S RNA↗

NASA NTRSDate not supplied

Tracking Metabolic Changes in Microbial Culture using Redox Measurements

During long-term space missions, microbial cultures accumulate the effects of low-dose radiation, microgravity, and other factors; altered growth and metabolic activity may occur before viability effects. This could affect functionality of bioreactors or other bio-enabled mission systems, as well as shed light on human health. Spaceflight microbiology studies beyond the low Earth orbit exposure afforded by the ISS have been limited. Nanosatellites offer an increasingly popular alternative for deep space missions. However, the communications delay requires biofluidic automation of a pre-defined experimental protocol, and the lack of sample return (reliance on sensors in flight) can significantly limit feasible investigations. Previous biological CubeSats (PharmaSat, O/OREOS, EcAMSat) have used alamarBlue, an off-the-shelf formulation of the redox indicator dye resazurin, to track metabolic activity, as will BioSentinel, the upcoming interplanetary microbiology experiment. A series of ground experiments (see abstracts by Liddell, Santa Maria, and A. Kim) were conducted using a microbial culture system outfitted with an electrochemical sensor array (electrical conductivity, pH, oxidation-reduction potential, and dissolved oxygen) with alamarBlue and the same strain of Saccharomyces cerevisiae as BioSentinel. By improving mapping of measured changes in alamarBlue kinetics to physicochemical changes, and ultimately to biological alterations such as shifted metabolic pathways, this work supplements data analyses from past missions and planning for future missions using alamarBlue to characterize space radiation effects. Initial results indicate that alamarBlue acts like a redox buffer; its presence significantly changes redox kinetics in otherwise identical cultures. The initial color change (blue resazurin reduced to red/pink resorufin) appears as a redox plateau. A second plateau, likely corresponding to the second color transition (resorufin to the colorless hydroresorufin), occurs at a lower redox value. The relationship to carbon source exhaustion, dissolved oxygen depletion, cell death, and measured redox potential is complex and still under study.

Tracking↗

NASA NTRSDate not supplied

The Effect of Trailing Edge Grid Resolution in Large-Eddy Simulations

Ceramic Matrix Composite (CMC) with environmental barrier coating can tolerate significantly higher temperatures compared with the conventional metal alloy blades and thus can help achieve higher thermal efficiency in gas turbine engines. Due to the complex fabrication process of CMC blades, larger blade trailing edge thicknesses and larger leading-edge radii of curvature are expected. These features significantly alter aerodynamic performance especially near the trailing edge and thus the loss profile. In previous studies, the authors used the large eddy simulation (LES) as well as the Reynolds Averaged Navier-Stokes (RANS) coupled with an intermittency function-based transition model to simulate an aerodynamics performance of three different CMC blades and compared the predictions against the data acquired at NASA Glenn Transonic Turbine Blade Cascade Rig. Although we were able to successfully predict different characteristics of aerodynamic performance among three different blades (e.g., pressure loading and integrated losses), LES consistently predicted a small recirculation bubble at the end of the suction side. This was not inconsistent with the physics of the flow, but the pressure loading, locally, near the trailing edge, and as a result, the measured wake profiles did not match the experimental data. To delve further into these issues, a new LES grid with a much finer mesh near the trailing edge was generated where the spanwise extent of the grid was increased by 50%. An LES simulation for the CMC blade with the largest trailing edge thicknesses at the high-freestream turbulence (Tu=13%) condition showed that using such a mesh is necessary for LES to accurately capture the transition phenomena on the suction side. The resulting total pressure coefficient profile and the shift of the wake profile were greatly improved.

CMC↗

NASA NTRSDate not supplied

The Effect of Trailing Edge Grid Resolution in Large-Eddy Simulations

LES↗

DOE OSTI2026

Complex and Unusual Excited-State Relaxation Dynamics of 9,9′-Bifluorenylidene Revealed by Comprehensive Time-Resolved Spectroscopy and MRSF-TDDFT Calculations

Design of novel photochemical molecular motors often requires molecular building blocks that exhibit rather unusual photoactivity, for which conventional analyses of spectroscopic data can lead to conflicting interpretations. We here systematically investigated the excited-state relaxation dynamics of one such molecule, 9,9′-bifluorenylidene (BF), through comprehensive and complementary integration of ultrafast transient absorption (TA) and femtosecond stimulated Raman (FSRS) spectroscopies and first-principles mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT). TA and FSRS identified two sequentially formed transients following photoexcitation. The decay kinetics of the two intermediates differ in response to excitation wavelengths and the viscosity/polarity of solvents. MRSF-TDDFT calculations reveal a direct, barrierless internal-conversion pathway from the bright Franck−Condon state to a dark S1 minimum, where the excited-state population is transiently trapped, accounting for the first transient species observed in spectroscopic experiments. Further tracking down along the PES with MRSF-TDDFT mapped out two nonradiative relaxation pathways via conical intersections that connect the dark S 1 state to three configurations in the ground-state manifolds, within which a ring structure with a C8−C8′ bond and the vibrationally excited ground-state BF were identified from spectroscopic and kinetic data. The complexity of relaxation kinetics was attributed to the flexible torsional and twisting motions about the C9−C9′ bridge bond enabled by the diradical character of the S 1 state. These findings clarify unusual photoactive relaxation dynamics stemming from a novel correlation between structural flexibility and shifting electronic characteristics, and they demonstrate the importance of integrating spectroscopic and advanced electronic structure calculation studies for judicious clarification of complex, competing relaxation pathways of excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Biasing from galaxy trough and peak profiles with the DES Y3 redMaGiC galaxies and the weak lensing mass map

We measure the correspondence between the distribution of galaxies and matter around troughs and peaks in the projected galaxy density, by comparing redMaGiC galaxies (0.15 < z < 0.65) to weak lensing mass maps from the Dark Energy Survey (DES) Y3 data release. We obtain stacked profiles, as a function of angle θ, of the galaxy density contrast δ g and the weak lensing convergence κ, in the vicinity of these identified troughs and peaks, referred to as ‘void’ and ‘cluster’ superstructures. The ratio of the profiles depend mildly on θ, indicating good consistency between the profile shapes. We model the amplitude of this ratio using a function $F(\boldsymbol{\eta }, \theta )$ that depends on cosmological parameters $\boldsymbol{\eta }$, scaled by the galaxy bias. We construct templates of $F(\boldsymbol{\eta }, \theta )$ using a suite of N-body (‘Gower Street’) simulations forward-modelled with DES Y3-like noise and systematics. We discuss and quantify the caveats of using a linear bias model to create galaxy maps from the simulation dark matter shells. We measure the galaxy bias in three lens tomographic bins (near to far): $2.32^{+0.86}_{-0.27}, 2.18^{+0.86}_{-0.23}, 1.86^{+0.82}_{-0.23}$ for voids, and $2.46^{+0.73}_{-0.27}, 3.55^{+0.96}_{-0.55}, 4.27^{+0.36}_{-1.14}$ for clusters, assuming the best-fit Planck cosmology. Similar values with ∼0.1σ shifts are obtained assuming the mean DES Y3 cosmology. The biases from troughs and peaks are broadly consistent, although a larger bias is derived for peaks, which is also larger than those measured from the DES Y3 3 × 2-point analysis. This method shows an interesting avenue for measuring field-level bias that can be applied to future lensing surveys.

cosmology: observations↗

DOE OSTI2020

Nonlocal correlations in iron pnictides and chalcogenides

Deviations of low-energy electronic structurse of iron-based superconductors from density-functional-theory predictions have been parametrized in terms of band- and orbital-dependent mass renormalizations and energy shifts. The former have typically been described in terms of a local self-energy within the framework of dynamical mean field theory, while the latter appears to require nonlocal effects due to interband scattering. By calculating the renormalized band structure in both random phase approximation (RPA) and the two-particle self-consistent approximation (TPSC), we show that correlations in pnictide systems like LaFeAsO and LiFeAs can be described rather well by a nonlocal self-energy. In particular, Fermi pocket shrinkage as seen in experiments occurs due to repulsive interband finite-energy scattering. For the canonical iron chalcogenide system FeSe in its bulk tetragonal phase, the situation is, however, more complex since even including momentum-dependent band renormalizations cannot explain experimental findings. We propose that the nearest-neighbor Coulomb interaction may play an important role in band-structure renormalization in FeSe. Finally, we further compare our evaluations of nonlocal quasiparticle scattering lifetime within RPA and TPSC with experimental data for LiFeAs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1994

Orientation of human optokinetic nystagmus to gravity: a model-based approach

Optokinetic nystagmus (OKN) was induced by having subjects watch a moving display in a binocular, head-fixed apparatus. The display was composed of 3.3 degrees stripes moving at 35 degrees/s for 45 s. It subtended 88 degrees horizontally by 72 degrees vertically of the central visual field and could be oriented to rotate about axes that were upright or tilted 45 degrees or 90 degrees. The head was held upright or was tilted 45 degrees left or right on the body during stimulation. Head-horizontal (yaw axis) and head-vertical (pitch axis) components of OKN were recorded with electro-oculography (EOG). Slow phase velocity vectors were determined and compared with the axis of stimulation and the spatial vertical (gravity axis). With the head upright, the axis of eye rotation during yaw axis OKN was coincident with the stimulus axis and the spatial vertical. With the head tilted, a significant vertical component of eye velocity appeared during yaw axis stimulation. As a result the axis of eye rotation shifted from the stimulus axis toward the spatial vertical. Vertical components developed within 1-2 s of stimulus onset and persisted until the end of stimulation. In the six subjects there was a mean shift of the axis of eye rotation during yaw axis stimulation of approximately 18 degrees with the head tilted 45 degrees on the body. Oblique optokinetic stimulation with the head upright was associated with a mean shift of the axis of eye rotation toward the spatial vertical of 9.2 degrees. When the head was tilted and the same oblique stimulation was given, the axis of eye rotation rotated to the other side of the spatial vertical by 5.4 degrees. This counterrotation of the axis of eye rotation is similar to the "Muller (E) effect," in which the perception of the upright is counterrotated to the opposite side of the spatial vertical when subjects are tilted in darkness. The data were simulated by a model of OKN with a "direct" and "indirect" pathway. It was assumed that the direct visual pathway is oriented in a body, not a spatial frame of reference. Despite the short optokinetic after-nystagmus time constants, strong horizontal to vertical cross-coupling could be produced if the horizontal and vertical time constants were in proper ratio and there were no suppression of nystagmus in directions orthogonal to the stimulus direction. The model demonstrates that the spatial orientation of OKN can be achieved by restructuring the system matrix of velocity storage. We conclude that an important function of velocity storage is to orient slow-phase velocity toward the spatial vertical during movement in a terrestrial environment.

Non-NASA Center↗

DOE OSTI2020

A ``Tail" of Two Cities: Fatality-based Modeling of COVID-19 Evolution in New York City and Cook County, IL

I describe $SIR$ modeling of the COVID-19 pandemic in two U.S. urban environments, New York City (NYC) and Cook County, IL, from onset through the month of June, 2020. Since testing was not widespread early in the pandemic in the U.S., I do not use data on confirmed cases and rely solely on public fatality data to estimate model parameters. Fits to the first 20 days of data determine a degenerate combination of the basic reproduction number, $R_0$, and the mean time to removal from the infectious population, $\gamma^{-1}$, with $\gamma (R_0-1) = 0.25 (0.21)$ inverse days for NYC (Cook County). Equivalently, the initial doubling time was $t_d = 2.8 (3.4)$ days for NYC (Cook). The early fatality data suggest that both locations had infections in early February. I model the mitigation measures implemented in mid-March in both locations (distancing, quarantine, isolation, etc) via a time-dependent reproduction number $R_t$ that declines monotonically from $R_0$ to a sma ller asymptotic value, with a parameterized functional form. The timing (mid-March) and duration (several days) of the transitions in $R_t$ appear well determined by the data. However, the fatality data determine only a degenerate combination of the parameters $R_0$, the percentage reduction in social contact due to mitigation measures, $X$, and the infection fatality rate (IFR), $f$. With flat priors, based on simulations the NYC model parameters have 95.45\% credible intervals of $R_0 = 3.0-5.4$, $X= 80-99.9\%$ and $f=2-6\%$, with $5-13\%$ of the population asymptotically infected. A strong external prior indicating a lower value of $f$ or of $\gamma^{-1}$ would imply lower values of $R_0$ and $X$ and higher percentage infection of the population. For Cook County, the evolution was qualitatively different: after mitigation measures were implemented, the daily fatality counts reached a plateau for about a month before tailing off. This is consistent with an $SIR$ model that exhibits ``critical slowing-down", in which $R_t$ plateaus ! at a value just above unity. For Cook County, the 95.45\% credible intervals for the model parameters are much broader and shifted downward, $R_0=1.4-4.7$, $X=26-54\%$, and $f=0.1-0.6\%$ with $15-88\%$ of the population asymptotically infected. Despite the apparently lower efficacy of its social contact reduction measures, Cook County has had significantly fewer fatalities per population than NYC, $D_\infty/N=100$ vs. 270 per 100,000. In the model, this is attributed to the lower inferred IFR for Cook; an external prior pointing to similar values of the IFR for the two locations would instead chalk up the difference in $D/N$ to differences in the relative growth rate of the disease. I derive a model-dependent threshold, $X^{crit}_e$, for `safe' re-opening, that is, for easing of contact reduction that would not trigger a second wave; for NYC, the models predict that increasing social contact by more than 20\% from post-mitigation levels will lead to renewed spread, while for Cook County the threshold value is very uncertain, given the parameter degeneracies. The timing of 2nd-wave growth will depend on the amplitude of contact increase relative to $X^{crit}_e$ and on the asymptotic growth rate, and the impact in terms of fatalities will depend on the parameter $f$.

Frieman, Joshua↗

DOE OSTI2024

Foundations for the Future Power System: Inverter-Based Resource Interconnection Standards

As power systems evolve to become reliant on solar, wind, batteries, and other inverter-based resources (IBRs), it is essential that those resources meet certain minimum performance and capability criteria designed to ensure the power system operates stably and reliably. Because those criteria, as enshrined in interconnection standards, take years to develop and are very long lived, they need to account for not only the present state of the power system but also its expected future state over the lifetime of the power plants to which they will apply. In addition, they need to be specific enough to ensure reliability without over specifying and, thereby, impeding innovation. Because power systems are shifting rapidly from a state where IBRs make up a small to medium portion of generation to one where the generation will, at times, come predominantly from IBRs, interconnection standards are especially challenging to develop today. Good interconnection standards can make the power system more reliable and less costly to operate, whereas poorly designed standards can lead to major problems, like the famous German 50.2-Hz problem, which introduced a risk of losing many gigawatts of solar on a frequency excursion and resulted in many IBRs being retrofitted at great cost to mitigate a major system reliability risk. Readying the power system by specifying forward-looking technical minimum functional capabilities for IBRs can be an effective approach to avoid future retrofits.

data models↗

DOE OSTI2023

Open Building Operating System: An Open-Source Grid Responsive Control Platform for Buildings

Grid-interactive efficient buildings (GEBs) with flexible loads are a promising method to decarbonize buildings, shift loads during peak hours, and lower energy use and electricity costs. Despite the promising benefits of GEBs, automation systems that manage flexible loads in response to energy prices or other grid signals are still uncommon in small and medium commercial buildings. Recent literature demonstrates such control solutions, but they often rely on custom integrations lacking the tools and drivers needed for scalability. To address these gaps, our team has created a fully open-source software stack capable of integrating heterogeneous flexible building loads and implementing integrated portable control applications called the Open Building Operating System (OpenBOS). The software can be deployed over existing control architecture with a small capital cost. OpenBOS leverages semantic models, which have been the subject of recent investigations to facilitate application portability. The use of semantic data reduces the labor and expense required to deploy and update smart control applications, increasing scalability. In this paper, the semantic modeling schema "Brick" was used, but the proposed approach can also be applied to ASHRAE standard 223P, when released. This paper describes the methodology and software components of OpenBOS and demonstrates its functionality with a rule-based demand flexibility control application configured using a semantic model. This application was tested at a real building in NY that uses a dual-fuel heating system made up of five ductless heat pump mini-splits and a central furnace serving a single zone. The demonstration reduced electricity costs at the site by 27%, demand during a shed event by 49%, and furnace usage by 35%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Effect of Sample Mass, Confinement, and Preheating Time on the Thermal Response of LLM‐105: Experiments and Kinetic Analysis

Various small-scale experiments were performed to provide data for developing a model to predict the thermal response of LLM-105 over a wide range of conditions. The thermal decomposition of LLM-105 was studied as a function of sample mass, confinement of volatile products, and preheating time in both isothermal and ramped heating experiments. The thermal decomposition of LLM-105 is a two-step process, as shown by the two exothermic peaks in the heat flow profiles, which were fitted to two nth-order autocatalytic reaction models with a similar activation energy of ∼289 kJ/mol. The magnitude and shape of these peaks varied with sample mass and confinement. Increasing sample mass enhanced the second exotherm with respect to the first one, while increasing the level of confinement promoted a transition from a sublimation-dominated regime towards thermal decomposition. The effect of LLM-105 particle size on the rate of weight loss was evident for open-pan experiments, where bigger particles sublimed at lower temperatures than smaller particles. Thermal response and solid residue composition of LLM-105 samples were analyzed following preheating for different durations. Longer preheating times caused a shift of the second exotherm to lower temperatures and a decrease in the reaction enthalpy, confirming that LLM-105 decay is a consecutive reaction mechanism, probably autocatalytic. In conclusion, the kinetic model derived from ramped experiments was validated against the measured LLM-105 fraction remaining and the enthalpy remaining of the solid residue as a function of preheating times and showed good agreement.

Chemistry - Chemical explosives↗