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Amongst efforts to realize computer science (CS) for all, recent critiques of racially biased technologies have emerged (e.g., facial recognition software), revealing a need to critically examine the interaction between computing solutions and societal factors. Yet within efforts to introduce K-12 students to such topics, studies examining teachers' learning of critical computing are rare. To understand how teachers learn to integrate societal issues within computing education, we analyzed video of a teacher professional development (PD) session with experienced computing teachers. Highlighting three particular episodes of conversation during PD, our analysis revealed how personal and classroom experiences—from making a sensor-based project to drawing on family and teaching experiences—tethered teachers’ weaving of societal and technical aspects of CS and enabled reflections on their learning and pedagogy. We discuss the need for future PD efforts to build on teachers’ experiences, draw in diverse teacher voices, and develop politicized trust among teachers. 

The motility mechanisms of microorganisms are critical virulence factors, enabling their spread and survival during infection. Motility is frequently characterized by qualitative analysis of macroscopic colonies, yet the standard quantification method has mainly been limited to manual measurement. Recent studies have applied deep learning for classification and segmentation of specific microbial species in microscopic images, but less work has focused on macroscopic colony analysis. Here, we advance computational tools for analyzing colonies of Proteus mirabilis, a bacterium that produces a macroscopic bullseye-like pattern via periodic swarming, a process implicated in its virulence. We present a dual-task pipeline for segmenting (1) the macroscopic colony including faint outer swarm rings, and (2) internal ring boundaries, unique features of oscillatory swarming. Our convolutional neural network for patch-based colony segmentation and U-Net with a VGG-11 encoder for ring boundary segmentation achieved test Dice scores of 93.28% and 83.24%, respectively. The predicted masks at times improved on the ground truths from our automated annotation algorithms. We demonstrate how application of our pipeline to a typical swarming assay enables ease of colony analysis and precise measurements of more complex pattern features than those which have been historically quantified. An implementation of our work can be found on https://github.com/daninolab/proteus-mirabilis. 

Abstract Sustaining the organisms, ecosystems and processes that underpin human wellbeing is necessary to achieve sustainable development. Here we define critical natural assets as the natural and semi-natural ecosystems that provide 90% of the total current magnitude of 14 types of nature’s contributions to people (NCP), and we map the global locations of these critical natural assets at 2 km resolution. Critical natural assets for maintaining local-scale NCP (12 of the 14 NCP) account for 30% of total global land area and 24% of national territorial waters, while 44% of land area is required to also maintain two global-scale NCP (carbon storage and moisture recycling). These areas overlap substantially with cultural diversity (areas containing 96% of global languages) and biodiversity (covering area requirements for 73% of birds and 66% of mammals). At least 87% of the world’s population live in the areas benefitting from critical natural assets for local-scale NCP, while only 16% live on the lands containing these assets. Many of the NCP mapped here are left out of international agreements focused on conserving species or mitigating climate change, yet this analysis shows that explicitly prioritizing critical natural assets and the NCP they provide could simultaneously advance development, climate and conservation goals. 

Archaeological and paleoecological evidence shows that by 10,000 BCE, all human societies employed varying degrees of ecologically transformative land use practices, including burning, hunting, species propagation, domestication, cultivation, and others that have left long-term legacies across the terrestrial biosphere. Yet, a lingering paradigm among natural scientists, conservationists, and policymakers is that human transformation of terrestrial nature is mostly recent and inherently destructive. Here, we use the most up-to-date, spatially explicit global reconstruction of historical human populations and land use to show that this paradigm is likely wrong. Even 12,000 y ago, nearly three quarters of Earth’s land was inhabited and therefore shaped by human societies, including more than 95% of temperate and 90% of tropical woodlands. Lands now characterized as “natural,” “intact,” and “wild” generally exhibit long histories of use, as do protected areas and Indigenous lands, and current global patterns of vertebrate species richness and key biodiversity areas are more strongly associated with past patterns of land use than with present ones in regional landscapes now characterized as natural. The current biodiversity crisis can seldom be explained by the loss of uninhabited wildlands, resulting instead from the appropriation, colonization, and intensifying use of the biodiverse cultural landscapes long shaped and sustained by prior societies. Recognizing this deep cultural connection with biodiversity will therefore be essential to resolve the crisis. 

Abstract We detail the population properties of binary neutron star, neutron star–black hole binary, and binary black hole mergers using 158 events from the cumulative Gravitational-Wave Transient Catalog 4.0. The black hole primary mass distribution consists of a power-law-like continuum that steepens above 35M_⊙with overdensities at 10M_⊙and 35M_⊙. Binary black holes with primary masses near 10M_⊙are more likely to have less massive secondaries, with a mass ratio distribution peaking at $q=0.71_{-0.11}^{+0.12}$ , potentially a signature of stable mass transfer during binary evolution. Black hole spins are inferred to be nonextremal, with 90% of black holes havingχ < 0.6, and preferentially aligned with binary orbits, implying many merging binaries form in isolation. However, we find that a significant fraction, 0.23–0.41, of binaries have negative effective inspiral spins, suggesting many could be formed dynamically in gas-free environments. We find evidence for correlation between effective inspiral spin and mass ratio, driven either by variation in the mode of the distribution or the width. The binary black hole merger rate increases with redshift, consistent with the cosmic star formation density. While there is no evidence of the mass spectrum evolving with redshift, the distribution of effective inspiral spin is found to broaden as redshift increases out toz ≈ 1. We infer the local merger rates (atz= 0) to be 8.8–250 Gpc⁻³yr⁻¹for binary neutron stars, 9.3–86 Gpc⁻³yr⁻¹for neutron star–black hole binaries, and 13–26 Gpc⁻³yr⁻¹for binary black holes; all values reflect central 90% credible intervals. 

Abstract The Gravitational-Wave Transient Catalog (GWTC) is a collection of candidate gravitational-wave transient signals identified and characterized by the LIGO–Virgo–KAGRA Collaboration. Producing the contents of the GWTC from detector data requires complex analysis methods. These comprise techniques to model the signal; identify the transients in the data; evaluate the quality of the data and mitigate possible instrumental issues; infer the parameters of each transient; compare the data with the waveform models for compact binary coalescences; and handle the large amount of results associated with all of these different analyses. In this paper, we describe the methods employed to produce the catalog’s fourth release, GWTC-4.0, focusing on the analysis of the first part of the fourth observing run of Advanced LIGO, Advanced Virgo and KAGRA. 

Abstract The discovery of joint sources of high-energy neutrinos and gravitational waves has been a primary target for the LIGO, Virgo, KAGRA, and IceCube observatories. The joint detection of high-energy neutrinos and gravitational waves would provide insight into cosmic processes, from the dynamics of compact object mergers and stellar collapses to the mechanisms driving relativistic outflows. The joint detection of multiple cosmic messengers can also elevate the significance of the common observation even when some or all of the constituent messengers are subthreshold, i.e., not significant enough to declare their detection individually. Using data from the LIGO, Virgo, and IceCube observatories, including subthreshold events, we searched for common sources of gravitational waves and high-energy neutrinos during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Our search did not identify significant joint sources. We derive constraints on the rate densities of joint sources. Our results constrain the isotropic neutrino emission from gravitational-wave sources for very high values of the total energy emitted in neutrinos (>10⁵²–10⁵⁴ erg). 

Abstract The Gravitational-Wave Transient Catalog (GWTC) is a collection of short-duration (transient) gravitational-wave signals identified by the LIGO–Virgo–KAGRA Collaboration in gravitational-wave data produced by the eponymous detectors. The catalog provides information about the identified candidates, such as the arrival time and amplitude of the signal and properties of the signal’s source as inferred from the observational data. GWTC is the data release of this dataset, and version 4.0 extends the catalog to include observations made during the first part of the fourth LIGO–Virgo–KAGRA observing run up until 2024 January 31. This Letter marks an introduction to a collection of articles related to this version of the catalog, GWTC-4.0. The collection of articles accompanying the catalog provides documentation of the methods used to analyze the data, summaries of the catalog of events, observational measurements drawn from the population, and detailed discussions of selected candidates.