State University of New York at Oswego

The HITRAN database is a compilation of molecular spectroscopic parameters. It was established in the early 1970s and is used by various computer codes to predict and simulate the transmission and emission of light in gaseous media (with an emphasis on terrestrial and planetary atmospheres). The HITRAN compilation is composed of five major components: the line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, experimental infrared absorption cross-sections (for molecules where it is not yet feasible for representation in a line-by-line form), collision-induced absorption data, aerosol indices of refraction, and general tables (including partition sums) that apply globally to the data. This paper describes the contents of the 2020 quadrennial edition of HITRAN. The HITRAN2020 edition takes advantage of recent experimental and theoretical data that were meticulously validated, in particular, against laboratory and atmospheric spectra. The new edition replaces the previous HITRAN edition of 2016 (including its updates during the intervening years). All five components of HITRAN have undergone major updates. In particular, the extent of the updates in the HITRAN2020 edition range from updating a few lines of specific molecules to complete replacements of the lists, and also the introduction of additional isotopologues and new (to HITRAN) molecules: SO, CH3F, GeH4, CS2, CH3I and NF3. Many new vibrational bands were added, extending the spectral coverage and completeness of the line lists. Also, the accuracy of the parameters for major atmospheric absorbers has been increased substantially, often featuring sub-percent uncertainties. Broadening parameters associated with the ambient pressure of water vapor were introduced to HITRAN for the first time and are now available for several molecules. The HITRAN2020 edition continues to take advantage of the relational structure and efficient interface available at www.hitran.org and the HITRAN Application Programming Interface (HAPI). The functionality of both tools has been extended for the new edition.

Abstract We report multiple lines of evidence for a stochastic signal that is correlated among 67 pulsars from the 15 yr pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves. The correlations follow the Hellings–Downs pattern expected for a stochastic gravitational-wave background. The presence of such a gravitational-wave background with a power-law spectrum is favored over a model with only independent pulsar noises with a Bayes factor in excess of 10 14 , and this same model is favored over an uncorrelated common power-law spectrum model with Bayes factors of 200–1000, depending on spectral modeling choices. We have built a statistical background distribution for the latter Bayes factors using a method that removes interpulsar correlations from our data set, finding p = 10 −3 (≈3 σ ) for the observed Bayes factors in the null no-correlation scenario. A frequentist test statistic built directly as a weighted sum of interpulsar correlations yields p = 5 × 10 −5 to 1.9 × 10 −4 (≈3.5 σ –4 σ ). Assuming a fiducial f −2/3 characteristic strain spectrum, as appropriate for an ensemble of binary supermassive black hole inspirals, the strain amplitude is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msubsup> <mml:mrow> <mml:mn>2.4</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>0.6</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>0.7</mml:mn> </mml:mrow> </mml:msubsup> <mml:mo>×</mml:mo> <mml:msup> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>15</mml:mn> </mml:mrow> </mml:msup> </mml:math> (median + 90% credible interval) at a reference frequency of 1 yr −1 . The inferred gravitational-wave background amplitude and spectrum are consistent with astrophysical expectations for a signal from a population of supermassive black hole binaries, although more exotic cosmological and astrophysical sources cannot be excluded. The observation of Hellings–Downs correlations points to the gravitational-wave origin of this signal.

We are often told that data are the new oil. But unlike oil, data are not a substance found in nature. It must be appropriated. The capture and processing of social data unfolds through a process we call data relations, which ensures the “natural” conversion of daily life into a data stream. The result is nothing less than a new social order, based on continuous tracking, and offering unprecedented new opportunities for social discrimination and behavioral influence. We propose that this process is best understood through the history of colonialism. Thus, data relations enact a new form of data colonialism, normalizing the exploitation of human beings through data, just as historic colonialism appropriated territory and resources and ruled subjects for profit. Data colonialism paves the way for a new stage of capitalism whose outlines we only glimpse: the capitalization of life without limit.

The fields of theoretical and computational chemistry have come a long way since their inception in the mid-20th century. Fifty years ago, only rudimentary approximations for very simple molecules could be performed. Thanks in part to the ongoing development of very fast computers, and the efforts of theoretical chemists in developing fast and accurate quantum mechanical (QM) methods for calculating electronic energies of atoms and molecules, theoretical and computational chemistry can now give reliable geometries, energies, reactivities, and electronic properties for molecules. Such information has become indispensable in understanding and explaining experimental results that would be otherwise difficult to interpret.

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.

[1] The potentially significant role of the biogenic trace gas dimethylsulfide (DMS) in determining the Earth's radiation budget makes it necessary to accurately reproduce seawater DMS distribution and quantify its global flux across the sea/air interface. Following a threefold increase of data (from 15,000 to over 47,000) in the global surface ocean DMS database over the last decade, new global monthly climatologies of surface ocean DMS concentration and sea-to-air emission flux are presented as updates of those constructed 10 years ago. Interpolation/extrapolation techniques were applied to project the discrete concentration data onto a first guess field based on Longhurst's biogeographic provinces. Further objective analysis allowed us to obtain the final monthly maps. The new climatology projects DMS concentrations typically in the range of 1–7 nM, with higher levels occurring in the high latitudes, and with a general trend toward increasing concentration in summer. The increased size and distribution of the observations in the DMS database have produced in the new climatology substantially lower DMS concentrations in the polar latitudes and generally higher DMS concentrations in regions that were severely undersampled 10 years ago, such as the southern Indian Ocean. Using the new DMS concentration climatology in conjunction with state-of-the-art parameterizations for the sea/air gas transfer velocity and climatological wind fields, we estimate that 28.1 (17.6–34.4) Tg of sulfur are transferred from the oceans into the atmosphere annually in the form of DMS. This represents a global emission increase of 17% with respect to the equivalent calculation using the previous climatology. This new DMS climatology represents a valuable tool for atmospheric chemistry, climate, and Earth System models.

Structure determination of proteins and other macromolecules has historically required the growth of high-quality crystals sufficiently large to diffract x-rays efficiently while withstanding radiation damage. We applied serial femtosecond crystallography (SFX) using an x-ray free-electron laser (XFEL) to obtain high-resolution structural information from microcrystals (less than 1 micrometer by 1 micrometer by 3 micrometers) of the well-characterized model protein lysozyme. The agreement with synchrotron data demonstrates the immediate relevance of SFX for analyzing the structure of the large group of difficult-to-crystallize molecules.

Twenty-nine teams involving 61 analysts used the same data set to address the same research question: whether soccer referees are more likely to give red cards to dark-skin-toned players than to light-skin-toned players. Analytic approaches varied widely across the teams, and the estimated effect sizes ranged from 0.89 to 2.93 ( Mdn = 1.31) in odds-ratio units. Twenty teams (69%) found a statistically significant positive effect, and 9 teams (31%) did not observe a significant relationship. Overall, the 29 different analyses used 21 unique combinations of covariates. Neither analysts’ prior beliefs about the effect of interest nor their level of expertise readily explained the variation in the outcomes of the analyses. Peer ratings of the quality of the analyses also did not account for the variability. These findings suggest that significant variation in the results of analyses of complex data may be difficult to avoid, even by experts with honest intentions. Crowdsourcing data analysis, a strategy in which numerous research teams are recruited to simultaneously investigate the same research question, makes transparent how defensible, yet subjective, analytic choices influence research results.

Predation risk" and "fear" are concepts well established in animal behavior literature. We expand these concepts to develop the model of the "landscape of fear". The landscape of fear represents relative levels of predation risk as peaks and valleys that reflect the level of fear of predation a prey experiences in different parts of its area of use. We provide observations in support of this model regarding changes in predation risk with respect to habitat types, and terrain characteristics. We postulate that animals have the ability to learn and can respond to differing levels of predation risk. We propose that the landscape of fear can be quantified with the use of well documented existing methods such as givingup densities, vigilance observations, and foraging surveys of plants. We conclude that the landscape of fear is a useful visual model and has the potential to become a unifying ecological concept.

Abstract The 15 yr pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) shows positive evidence for the presence of a low-frequency gravitational-wave (GW) background. In this paper, we investigate potential cosmological interpretations of this signal, specifically cosmic inflation, scalar-induced GWs, first-order phase transitions, cosmic strings, and domain walls. We find that, with the exception of stable cosmic strings of field theory origin, all these models can reproduce the observed signal. When compared to the standard interpretation in terms of inspiraling supermassive black hole binaries (SMBHBs), many cosmological models seem to provide a better fit resulting in Bayes factors in the range from 10 to 100. However, these results strongly depend on modeling assumptions about the cosmic SMBHB population and, at this stage, should not be regarded as evidence for new physics. Furthermore, we identify excluded parameter regions where the predicted GW signal from cosmological sources significantly exceeds the NANOGrav signal. These parameter constraints are independent of the origin of the NANOGrav signal and illustrate how pulsar timing data provide a new way to constrain the parameter space of these models. Finally, we search for deterministic signals produced by models of ultralight dark matter (ULDM) and dark matter substructures in the Milky Way. We find no evidence for either of these signals and thus report updated constraints on these models. In the case of ULDM, these constraints outperform torsion balance and atomic clock constraints for ULDM coupled to electrons, muons, or gluons.

Researchers have used J. Bowlby's (1969/1982, 1973, 1980, 1988) attachment theory frequently as a basis for examining whether experiences in close personal relationships relate to the processing of social information across childhood, adolescence, and adulthood. We present an integrative life-span-encompassing theoretical model to explain the patterns of results that have emerged from these studies. The central proposition is that individuals who possess secure experience-based internal working models of attachment will process--in a relatively open manner--a broad range of positive and negative attachment-relevant social information. Moreover, secure individuals will draw on their positive attachment-related knowledge to process this information in a positively biased schematic way. In contrast, individuals who possess insecure internal working models of attachment will process attachment-relevant social information in one of two ways, depending on whether the information could cause the individual psychological pain. If processing the information is likely to lead to psychological pain, insecure individuals will defensively exclude this information from further processing. If, however, the information is unlikely to lead to psychological pain, then insecure individuals will process this information in a negatively biased schematic fashion that is congruent with their negative attachment-related experiences. In a comprehensive literature review, we describe studies that illustrate these patterns of attachment-related information processing from childhood to adulthood. This review focuses on studies that have examined specific components (e.g., attention and memory) and broader aspects (e.g., attributions) of social information processing. We also provide general conclusions and suggestions for future research.

We show that a firm's CSR policy is significantly influenced by the CSR policies of firms in the same three‐digit zip code, an effect possibly due to investor clienteles, local competition, and/or social interactions. We then exploit the variation in CSR across the zip codes to estimate the effect of CSR on credit ratings under the assumption that zip code assignments are exogenous. We find that more socially responsible firms enjoy more favorable credit ratings. In particular, an increase in CSR by one standard deviation improves the firm's credit rating by as much as 4.5%.

This paper describes the design, implementation, and performance of a Java framework for supporting a style of parallel programming in which problems are solved by (recursively) splitting them into subtasks that are solved in parallel, waiting for them to complete, and then composing results. The general design is a variant of the work-stealing framework devised for Cilk. The main implementation techniques surround efficient construction and management of tasks queues and worker threads. The measured performance shows good parallel speedups for most programs, but also suggests possible improvements. 1. INTRODUCTION Fork/Join parallelism is among the simplest and most effective design techniques for obtaining good parallel performance. Fork/join algorithms are parallel versions of familiar divideand -conquer algorithms, taking the typical form: Result solve(Problem problem) { if (problem is small) directly solve problem else { split problem into independent parts fork new subtas...

We have compiled a record of the geochronology of mantle plume activity between 3.8 and 1.6 Ga. Over this time period, the ages of komatiites, and those of global plumes, correlate strongly, at the 99% confidence level, with the ages of banded iron formations (BIFs). The ages of continental plumes correlate more weakly, at an overall 85% confidence level. Using the geochronological records of these events, we can define four periods characterized by mantle superplume activity. Three of these periods are also times of enhanced BIF deposition. The fourth mantle plume period may similarly be coeval with increased BIF accumulation, but the BIF chronostratigraphic resolution is not accurate enough to test this rigorously. Mantle superplume volcanism may promote BIF deposition by increasing the Fe flux to the global oceans through continental weathering and/or through submarine hydrothermal processes. It may also be enhanced by increasing the number of paleotectonic environments appropriate for BIF deposition (particularly plume‐induced ocean plateaus, seamounts, and intracratonic rifts) and by promoting global anoxic, Fe‐rich hydrothermal plumes in the shallow to intermediate marine water column.

Abstract The NANOGrav 15 yr data set shows evidence for the presence of a low-frequency gravitational-wave background (GWB). While many physical processes can source such low-frequency gravitational waves, here we analyze the signal as coming from a population of supermassive black hole (SMBH) binaries distributed throughout the Universe. We show that astrophysically motivated models of SMBH binary populations are able to reproduce both the amplitude and shape of the observed low-frequency gravitational-wave spectrum. While multiple model variations are able to reproduce the GWB spectrum at our current measurement precision, our results highlight the importance of accurately modeling binary evolution for producing realistic GWB spectra. Additionally, while reasonable parameters are able to reproduce the 15 yr observations, the implied GWB amplitude necessitates either a large number of parameters to be at the edges of expected values or a small number of parameters to be notably different from standard expectations. While we are not yet able to definitively establish the origin of the inferred GWB signal, the consistency of the signal with astrophysical expectations offers a tantalizing prospect for confirming that SMBH binaries are able to form, reach subparsec separations, and eventually coalesce. As the significance grows over time, higher-order features of the GWB spectrum will definitively determine the nature of the GWB and allow for novel constraints on SMBH populations.

Abstract We present observations and timing analyses of 68 millisecond pulsars (MSPs) comprising the 15 yr data set of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). NANOGrav is a pulsar timing array (PTA) experiment that is sensitive to low-frequency gravitational waves (GWs). This is NANOGrav’s fifth public data release, including both “narrowband” and “wideband” time-of-arrival (TOA) measurements and corresponding pulsar timing models. We have added 21 MSPs and extended our timing baselines by 3 yr, now spanning nearly 16 yr for some of our sources. The data were collected using the Arecibo Observatory, the Green Bank Telescope, and the Very Large Array between frequencies of 327 MHz and 3 GHz, with most sources observed approximately monthly. A number of notable methodological and procedural changes were made compared to our previous data sets. These improve the overall quality of the TOA data set and are part of the transition to new pulsar timing and PTA analysis software packages. For the first time, our data products are accompanied by a full suite of software to reproduce data reduction, analysis, and results. Our timing models include a variety of newly detected astrometric and binary pulsar parameters, including several significant improvements to pulsar mass constraints. We find that the time series of 23 pulsars contain detectable levels of red noise, 10 of which are new measurements. In this data set, we find evidence for a stochastic GW background.

Redshifts for a total sample of 238 galaxies to a limiting magnitude of 15.0 are used to study the three-dimensional distribution of galaxies in the region of the sky ranging from approximately 11.5 h to 13.3 h right ascension between declinations of about 19 and 32 deg, within which lie the two rich clusters Coma and A1367. The results obtained demonstrate that the two clusters are embedded in a common supercluster of very large extent. It is found that there are three observationally distinct populations of galaxies within this supercluster, including galaxies located in the two rich cluster cores, those located in intermediate- or low-mass clusters, and a nearly homogeneously distributed population of isolated galaxies; in addition, a population of foreground galaxies located in low-mass clusters rather than being distributed in a homogeneous 'field' is also identified. The redshift of formation for the foreground groups is estimated to be no more than about 9, and the morphology of the galaxies is examined. It is suggested that every nearby very rich cluster is located in a supercluster and that all clusters of richness class greater than or equal to 2 will eventually be found to lie in superclusters.

This study tested whether dispositional measures of optimism, pessimism, and anxiety affected ambulatory blood pressure (BP) and mood and whether any cardiovascular effects of dispositions were moderated by mood. Pessimistic and anxious adults had higher BP levels and felt more negative and less positive than did optimists or low anxious adults throughout the monitoring. The few times that optimists did feel negative were associated with levels of BP as high as those observed among pessimists or anxious individuals, regardless of their mood. To the extent that trait anxiety measures neuroticism, these findings suggest that neuroticism is directly related to health indicators rather than simply to illness behavior. Furthermore, the results suggest that pessimism has broad physiological and psychological consequences.

Abstract To understand the development of students’ higher-order thinking skills (HOTS) in the smart classroom environment, a structural equation modeling analysis was used to examine the relationships between key factors that influence students’ learning and their HOTS within a smart classroom environment. A sample of 217 first-year Chinese college students, who studied in a smart classroom environment for one semester, completed a survey that measures their smart classroom preferences, learning motivation, learning strategy, peer interaction, and HOTS. The results indicated that peer interaction and learning motivation had a direct impact on students’ HOTS. Furthermore, indirect effects were found between students’ learning strategy and HOTS through the mediator peer interaction, and between smart classroom preferences and HOTS through the following: learning motivation, the combination of learning strategy and peer interaction, and the combination of learning motivation, learning strategy and peer interaction. Based on these findings, this study recommends that instructors teaching in a smart learning environment should focus on improving peer interaction and learning motivation, as well as smart classroom preferences and learning strategy, to hone students’ HOTS.

Datafication is not just the making of information, which, in one sense, human beings have been doing since the creation of symbols and writing. Rather, datafication is a contemporary phenomenon which refers to the quantification of human life through digital information, very often for economic value. This process has major social consequences. Disciplines such as political economy, critical data studies, software studies, legal theory, and—more recently— decolonial theory, have considered different aspects of those consequences to be important. Fundamental to all such approaches is the analysis of the intersection of power and knowledge.