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At least 55 records · Page 3

Opacity probability distribution functions for electronic systems of CN and C2 molecules including their stellar isotopic forms.

The basis and techniques are presented for generating opacity probability distribution functions for the CN molecule (red and violet systems) and the C2 molecule (Swan, Phillips, Ballik-Ramsay systems), two of the more important diatomic molecules in the spectra of carbon stars, with a view to including these distribution functions in equilibrium model atmosphere calculations. Comparisons to the CO molecule are also shown. T he computation of the monochromatic absorption coefficient uses the most recent molecular data with revision of the oscillator strengths for some of the band systems. The total molecular stellar mass absorption coefficient is established through fifteen equations of molecular dissociation equilibrium to relate the distribution functions to each other on a per gram of stellar material basis.

Querci, F.↗

Outer midplane neutral density measurements and H-mode fueling studies in NSTX-U

Neutral density profiles are measured on the outboard midplane of the National Spherical Torus Experiment Upgrade (NSTX-U) using a two dimensional camera (ENDD, edge neutral density diagnostic) filtered for deuterium Balmer α (D α ) emission interpreted via simulations using the Monte Carlo neutral transport code DEGAS 2. Deuterium atomic densities n D are calculated by inverting the line-integrated D α brightness and using local measurements of electron density ne and temperature T e to determine atomic rate coefficients. The assumptions used in the derivation of n D from D α emissivity are validated using DEGAS 2 to estimate contributions to emissivity due to electron impact excitation and molecular processes. In this work, experimental measurements and DEGAS 2 simulations are compared over a database of L- and H-mode discharges, showing good agreement in D α emissivity profiles. Residual disagreement between experiment and simulations is suggestive of the possible role of intermittent transport and uncertainties in the molecular data. DEGAS 2 simulations are further used to complement the ENDD diagnostic, extracting neutral (atomic and molecular) densities at locations where the ENDD measurement are not made or where the assumptions used in the ENDD analysis are not valid. Deuterium atomic densities and ionization profiles on the outer midplane are compared for L-mode and H-mode discharges in NSTX-U. One-way coupling of DEGAS 2 to UEDGE multi-fluid simulations constrained by experimental data is used to study edge fueling and neutral penetration in NSTX-U discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Laboratory Astrophysics: Enabling Scientific Discovery and Understanding

NASA's Science Strategic Roadmap for Universe Exploration lays out a series of science objectives on a grand scale and discusses the various missions, over a wide range of wavelengths, which will enable discovery. Astronomical spectroscopy is arguably the most powerful tool we have for exploring the Universe. Experimental and theoretical studies in Laboratory Astrophysics convert "hard-won data into scientific understanding". However, the development of instruments with increasingly high spectroscopic resolution demands atomic and molecular data of unprecedented accuracy and completeness. How to meet these needs, in a time of severe budgetary constraints, poses a significant challenge both to NASA, the astronomical observers and model-builders, and the laboratory astrophysics community. I will discuss these issues, together with some recent examples of productive astronomy/lab astro collaborations.

Kirby, K.↗

Unified epigenomic, transcriptomic, proteomic, and metabolomic taxonomy of Alzheimer’s disease progression and heterogeneity

Alzheimer’s disease (AD) is a heterogeneous disorder with abnormalities in multiple biological domains. In an advanced machine learning analysis of postmortem brain and in vivo blood multi-omics molecular data ( N = 1863), we integrated epigenomic, transcriptomic, proteomic, and metabolomic profiles into a multilevel biological AD taxonomy. We obtained a personalized multilevel molecular index of AD dementia progression that predicts severity of neuropathologies, and identified three robust molecular-based subtypes that explain much of the pathologic and clinical heterogeneity of AD. These subtypes present distinct patterns of alteration in DNA methylation, RNA, proteins, and metabolites, identifiable in the brain and subsequently in blood. In addition, the genetic variations that predispose to the various AD subtypes in brain predict distinct spatial patterns of alteration in cell types, suggesting a unique influence of each putative AD variant on neuropathological mechanisms. These observations support that an individually tailored multi-omics molecular taxonomy of AD may represent distinct targets for preventive or treatment interventions.

60 APPLIED LIFE SCIENCES↗

The P( 4 S) + NH( 3 Σ – ) and N( 4 S) + PH( 3 Σ – )reactions as sources of interstellar phosphorus nitride

Phosphorus nitride (PN) is believed to be one of the major reservoirs of phosphorus in the interstellar medium (ISM). For this reason, understanding which reactions produce PN in space and predicting their rate coefficients is important for modelling the relative abundances of P-bearing species and clarifying the role of phosphorus in astrochemistry. Here, in this work, we explore the potential energy surfaces of the $\textrm{P}(^4\textrm{S}) + \textrm{NH}(^3\Sigma^-)$ and $\textrm{N}(^4\textrm{S}) + \textrm{PH}(^3\Sigma^-)$ reactions and the formation of $\textrm{H}(^2\textrm{S}) + \textrm{PN}(^1\Sigma^+)$ through high accuracy ab initio calculations and the variable reaction coordinate transition state theory (VRC-TST). We found that both reactions proceed without an activation barrier and with similar rate coefficients that can be described by a modified Arrhenius equation ( $k(T)=\alpha\!\left( T/300 \right)^{\beta} \exp\!{(\!-\!\gamma/T)})$ with $\alpha=0.93\times 10^{-10}\rm cm^3\,s^{-1}$ , $\beta=-0.18$ and $\gamma=0.24\, \rm K$ for the $\textrm{P} + \textrm{NH} \longrightarrow \textrm{H} + \textrm{PN}$ reaction and $\alpha=0.88\times 10^{-10}\rm cm^3\,s^{-1}$ , $\beta=-0.18$ and $\gamma=1.01\, \rm K$ for the $\textrm{N} + \textrm{PH} \longrightarrow \textrm{H} + \textrm{PN}$ one. Both reactions are expected to be relevant for modelling PN abundances even in the cold environments of the ISM. Given the abundance of hydrogen in space, we have also predicted rate coefficients for the destruction of PN via H + PN collisions.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data

In vivo assessments of influenza A virus (IAV) pathogenicity and transmissibility in ferrets represent a crucial component of many pandemic risk assessment rubrics, but few systematic efforts to identify which data from in vivo experimentation are most useful for predicting pathogenesis and transmission outcomes have been conducted. To this aim, we aggregated viral and molecular data from 125 contemporary IAV (H1, H2, H3, H5, H7, and H9 subtypes) evaluated in ferrets under a consistent protocol. Three overarching predictive classification outcomes (lethality, morbidity, transmissibility) were constructed using machine learning (ML) techniques, employing datasets emphasizing virological and clinical parameters from inoculated ferrets, limited to viral sequence-based information, or combining both data types. Among 11 different ML algorithms tested and assessed, gradient boosting machines and random forest algorithms yielded the highest performance, with models for lethality and transmission consistently better performing than models predicting morbidity. Comparisons of feature selection among models was performed, and highest performing models were validated with results from external risk assessment studies. Our findings show that ML algorithms can be used to summarize complex in vivo experimental work into succinct summaries that inform and enhance risk assessment criteria for pandemic preparedness that take in vivo data into account.

59 BASIC BIOLOGICAL SCIENCES↗

A comparison of probabilistic generative frameworks for molecular simulations

Generative artificial intelligence is now a widely used tool in molecular science. Despite the popularity of probabilistic generative models, numerical experiments benchmarking their performance on molecular data are lacking. Here, in this work, we introduce and explain several classes of generative models, broadly sorted into two categories: flow-based models and diffusion models. We select three representative models: neural spline flows, conditional flow matching, and denoising diffusion probabilistic models, and examine their accuracy, computational cost, and generation speed across datasets with tunable dimensionality, complexity, and modal asymmetry. Our findings are varied, with no one framework being the best for all purposes. In a nutshell, (i) neural spline flows do best at capturing mode asymmetry present in low-dimensional data, (ii) conditional flow matching outperforms other models for high-dimensional data with low complexity, and (iii) denoising diffusion probabilistic models appear the best for low-dimensional data with high complexity. Our datasets include a Gaussian mixture model and the dihedral torsion angle distribution of the Aib9 peptide, generated via a molecular dynamics simulation. We hope our taxonomy of probabilistic generative frameworks and numerical results may guide model selection for a wide range of molecular tasks.

Artificial intelligence↗

Signatures of transposon-mediated genome inflation, host specialization, and photoentrainment in Entomophthora muscae and allied entomophthoralean fungi

Despite over a century of observations, the obligate insect parasites within the order Entomophthorales remain poorly characterized at the genetic level. In this manuscript, we present a genome for a laboratory-tractable Entomophthora muscae isolate that infects fruit flies. Our E. muscae assembly is 1.03 Gb, consists of 7810 contigs and contains 81.3% complete fungal BUSCOs. Using a comparative approach with recent datasets from entomophthoralean fungi, we show that giant genomes are the norm within Entomophthoraceae owing to extensive, but not recent, Ty3 retrotransposon activity. In addition, we find that E. muscae and its closest allies possess genes that are likely homologs to the blue-light sensor white-collar 1, a Neurospora crassa gene that has a well-established role in maintaining circadian rhythms. We uncover evidence that E. muscae diverged from other entomophthoralean fungi by expansion of existing families, rather than loss of particular domains, and possesses a potentially unique suite of secreted catabolic enzymes, consistent with E. muscae’s species-specific, biotrophic lifestyle. Finally, we offer a head-to-head comparison of morphological and molecular data for species within the E. muscae species complex that support the need for taxonomic revision within this group. Altogether, we provide a genetic and molecular foundation that we hope will provide a platform for the continued study of the unique biology of entomophthoralean fungi.

59 BASIC BIOLOGICAL SCIENCES↗

Monoceros R2 - Far-infrared observations of a very young cluster

The young infrared cluster in Mon R2 has been observed at wavelengths from 30 microns to 1 mm and at angular resolutions from 16 arcsec to 1 arcmin. The brightest sources - RS 1 and IRS 3 - have luminosities equivalent to those of early B-type stars. It is not possible to estimate reliably the evolutionary stage of IRS 3, but IRS 1 appears to be powered by a star close to B0 V. The star probably dominates the energetics of the cluster. The gas density estimated from the infrared and radio molecular data is much larger than that of the associated, extended H II region. This appears consistent with the idea that the ionized zone is expanding out from the back of the molecular cloud.

Thornson, H. A., Jr.↗

Artificial intelligence “sees” split electrons

Chemical bonds between atoms are stabilized by the exchange-correlation (xc) energy, a quantum-mechanical effect in which “social distancing” by electrons lowers their electrostatic repulsion energy. Kohn-Sham density functional theory (DFT) states that the electron density determines this xc energy, but the density functional must be approximated. Furthermore, this is usually done by satisfying exact constraints of the exact functional (making the approximation predictive), by fitting to data (making it interpolative), or both. Two exact constraints—the ensemble-based piecewise linear variation of the total energy with respect to fractional electron number and fractional electron z-component of spin —require hard-to-control nonlocality. On page 1385 of this issue, Kirkpatrick et al. have taken a big step toward more accurate predictions for chemistry through the machine learning of molecular data plus the fractional charge and spin constraints, expressed as data that a machine can learn.

74 ATOMIC AND MOLECULAR PHYSICS↗

Research on Spectroscopy, Opacity, and Atmospheres

To make my calculations more readily accessible I have set up a web site cfaku5.harvard.edu that can also be accessed by FTP. it has 5 9GB disks that hold all of my atomic and diatomic molecular data, my tables of distribution function opacities, my grids of model atmospheres, colors, fluxes, etc, my program that are ready for distribution, most of my recent papers. Atlases and computed spectra will be added as they are completed. New atomic and molecular calculations will be added as they are completed. I got my atomic programs that had been running on a Cray at the San Diego Supercomputer Center to run on my Vaxes and Alpha. I started with Ni and Co because there were new laboratory analyses that included isotopic and hyperfine splitting. Those calculations are described in the appended abstract for the 6th Atomic Spectroscopy and oscillator Strengths meeting in Victoria last summer. A surprising finding is that quadrupole transitions have been grossly in error because mixing with higher levels has not been included. I now have enough memory in my Alpha to treat 3000 x 3000 matrices. I now include all levels up through n=9 for Fe I and 11, the spectra for which the most information is available. I am finishing those calculations right now. After Fe I and Fe 11, all other spectra are "easy", and I will be in mass production. ATL;LS12, my opacity sampling program for computing models with arbitrary abundances, has been put on the web server. I wrote a new distribution function opacity program for workstations that replaces the one I used on the Cray at the San Diego Supercomputer Center. Each set of abundances would take 100 Cray hours costing $100,000. 1 ran 25 cases. Each of my opacity CDs contains three abundances. I have a new program -iinning on the Alpha that takes about a week. I am going to have to get a faster processor or I will have to dedicate a whole workstation just to opacities.

Kurucz, Robert L.↗

Research on Spectroscopy, Opacity, and Atmospheres

With this funding I produced a web site kurucz.harvard.edu that can also be accessed by FTP. it has a 73GB disk that holds all of my atomic and diatomic molecular data, my tables of distribution function opacities, my grids of model atmospheres, colors, fluxes, etc., my programs that are ready for distribution, and most of my recent papers. Atlases and computed spectra will be added as they are completed. New atomic and molecular calculations will be added as they are completed.

Kurucz, Robert L.↗

Atomic and molecular supernovae

Atomic and molecular physics of supernovae is discussed with an emphasis on the importance of detailed treatments of the critical atomic and molecular processes with the best available atomic and molecular data. The observations of molecules in SN 1987A are interpreted through a combination of spectral and chemical modelings, leading to strong constraints on the mixing and nucleosynthesis of the supernova. The non-equilibrium chemistry is used to argue that carbon dust can form in the oxygen-rich clumps where the efficient molecular cooling makes the nucleation of dust grains possible. For Type Ia supernovae, the analyses of their nebular spectra lead to strong constraints on the supernova explosion models.

Liu, Weihong↗

Laboratory Astrophysics Under the Ultraviolet, Visible, and Gravitational Astrophysics Research Program

Space-borne facilities, such as the Hubble Space Telescope, the recent ORFEUS-SPAS II Shuttle mission, and the soon-to-be launched Far Ultraviolet Spectroscopic Explorer, are providing data at ultraviolet wavelengths of unprecedented quality for spectroscopic studies of many astronomical environments. The first step in the analysis of these data involves the derivation of abundances. Obtaining accurate abundances is possible only when the correspondence between line strength and abundance is well known. The conversion of line strength to abundance relies on knowledge of transition probabilities and oscillator strengths, often obtained from mean lives branching fractions. For many ultraviolet transitions, the necessary atomic and molecular data are either relatively imprecise or not available. Our program addresses this need for accurate oscillator strengths; our focus is on transitions that probe the nature and composition of the interstellar medium.

Federman, Steven R.↗

Laboratory studies in ultraviolet solar physics

The research activity comprised the measurement of basic atomic processes and parameters which relate directly to the interpretation of solar ultraviolet observations and to the development of comprehensive models of the component structures of the solar atmosphere. The research was specifically directed towards providing the relevant atomic data needed to perform and to improve solar diagnostic techniques which probe active and quiet portions of the solar chromosphere, the transition zone, the inner corona, and the solar wind acceleration regions of the extended corona. The accuracy with which the physical conditions in these structures can be determined depends directly on the accuracy and completeness of the atomic and molecular data. These laboratory data are used to support the analysis programs of past and current solar observations (e.g., the Orbiting solar Observatories, the Solar Maximum Mission, the Skylab Apollo Telescope Mount, and the Naval Research Laboratory's rocket-borne High Resolution Telescope and Spectrograph). In addition, we attempted to anticipate the needs of future space-borne solar studies such as from the joint ESA/NASA Solar and Heliospheric Observatory (SOHO) spacecraft. Our laboratory activities stressed two categories of study: (1) the measurement of absolute rate coefficients for dielectronic recombination and electron impact excitation; and (2) the measurement of atomic transition probabilities for solar density diagnostics. A brief summary of the research activity is provided.

Parkinson, W. H.↗

Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l

Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations.

59 BASIC BIOLOGICAL SCIENCES↗

Particle excitation, airglow and H2 vibrational disequilibrium in the atmosphere of Jupiter

The extreme ultraviolet EUV emission produced by particle excitation of the hydrogen atmospheres of Jupiter and Saturn is examined using model calculations to determine the nature of the energy deposition process and the effect of such processes on atmospheric structure. Tasks ranging from examination of phenomenologically related processes on Saturn and Titan to analysis of experimental laboratory data required to allow accurate modeling of emissions from hydrogenic atmospheres are investigated. An explanation of the hydrogen H Ly(alpha) bulge in Jupiter's emission from the equatorial region is presented. It is proposed that Saturn, rather then Titan is the major source of the extended hydrogen cloud. The atomic hydrogen detected at the rings of Saturn may originate predominantly from the same source. A cross calibration is obtained between the Pioneer 10 EUV photometer and the Voyager EUV spectrometers, thus providing a direct measure of the temporal morphology of Jupiter between a minimum and a maximum in solar activity. Atomic and molecular data required for the research program are analyzed. An extrapolation of conditions in the upper atmospheres of Jupiter and Saturn produces a predicted condition at Uranus in terms of excitation and hydrogen escape rates that may be observed at Voyager-Uranus encounter.

Shemansky, D. E.↗