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Abstract On 12 January 2022, an iceberg collapsed at the edge of frozen Atka Bay, Antarctica. The event generated seismic, hydroacoustic, and atmospheric infrasound waves recorded by a local network comprising land‐ and iceshelf‐based seismometers, an underwater hydrophone, and an on‐ice infrasound array. Analysis of the seismic and hydroacoustic data shows that the collapse occurred in at least three stages separated by approximately 16.5 and 8 s. The first stage produced a seismic head wave, a P‐wave, and a Rayleigh wave, and clear hydroacoustic and infrasound arrivals. Later stages were dominated by hydroacoustic and seismic Rayleigh waves. Two localization techniques were benchmarked: azimuthal cross‐bearing and a Bayesian joint inversion based on time‐difference‐of‐arrival. Both approaches accurately located the iceberg within a few hundred meters of its geolocation. These unique observations highlight the value of continuous seismo‐acoustic monitoring for investigating local cryospheric dynamics. 

Abstract Enzymes are highly specific catalysts delivering improved drugs and greener industrial processes. Naturally occurring enzymes must typically be optimized which is often accomplished through directed evolution; however, this is still a labor‐ and capital‐intensive process, due in part to multiple molecular biology steps including DNA extraction, in vitro library generation, transformation, and limited screening throughput. We present an effective and broadly applicable continuous evolution platform that enables controlled exploration of fitness landscape to evolve enzymes at ultrahigh throughput based on direct measurement of enzymatic activity. This drop‐based microfluidics platform cycles cells between growth and mutagenesis followed by screening with minimal human intervention, relying on the nCas9 chimera with mutagenesis polymerase to produce in vivo gene diversification using sgRNAs tiled along the gene. We evolve alditol oxidase to change its substrate specificity towards glycerol, turning a waste product into a valuable feedstock. We identify a variant with a 10.5‐fold catalytic efficiency. 

Abstract Viable nature-based climate solutions (NbCS) are needed to achieve climate goals expressed in international agreements like the Paris Accord. Many NbCS pathways have strong scientific foundations and can deliver meaningful climate benefits but effective mitigation is undermined by pathways with less scientific certainty. Here we couple an extensive literature review with an expert elicitation on 43 pathways and find that at present the most used pathways, such as tropical forest conservation, have a solid scientific basis for mitigation. However, the experts suggested that some pathways, many with carbon credit eligibility and market activity, remain uncertain in terms of their climate mitigation efficacy. Sources of uncertainty include incomplete GHG measurement and accounting. We recommend focusing on resolving those uncertainties before broadly scaling implementation of those pathways in quantitative emission or sequestration mitigation plans. If appropriate, those pathways should be supported for their cobenefits, such as biodiversity and food security. 

This paper describes the ways in which an established K12 informal learning program, called Young Women in Computing (YWIC), utilizes culturally sustaining pedagogical practices to support learning, development, and leadership of youth outreach participants as well as undergraduate instructional staff. Authors emphasize the leadership roles undergraduates (here, authors 1-3) play in developing and implementing outreach designed and embodied at a Hispanic[1]Serving Institution. The three themes illustrated in this study include (1) opportunities for agency, or ownership, choice and autonomy for undergraduate leaders, (2) an emphasis on relationality, or developing personal relationships among undergraduate leaders and youth, and (3) the multiplicity of relevant knowledge and “ways of knowing” which contribute to viable pathways into computing. This paper argues the elevation of undergraduates better apprentices the next diverse educators and leaders in computing. 

We present an all-sky search for long-duration gravitational waves (GWs) from the first part of the LIGO-Virgo-KAGRA fourth observing run (O4), called O4a and comprising data taken between May 24, 2023, and January 16, 2024. The GW signals targeted by this search are the so-called “long-duration” ( $\gtrsim 1\mathrm{s}$) transients expected from a variety of astrophysical processes, including nonaxisymmetric deformations in magnetars or eccentric binary coalescences. We make minimal assumptions on the emitted GW waveforms in terms of morphologies and durations. Overall, our search targets signals with durations of $\sim 1–1000\mathrm{s}$and frequency content in the range 16–2048 Hz. In the absence of significant detections, we report the sensitivity limits of our search in terms of root-sum-square signal amplitude ( $h_{\mathrm{rss}}$) of reference waveforms. These limits improve upon the results from the third LIGO-Virgo-KAGRA observing run (O3) by about 30% on average. Moreover, this analysis demonstrates substantial progress in our ability to search for long-duration GW signals owing to enhancements in pipeline detection efficiencies. As detector sensitivities continue to advance and observational runs grow longer, unmodeled long-duration searches will increasingly be able to explore a range of compelling astrophysical scenarios involving neutron stars and black holes. 

Abstract Progress in gravitational-wave (GW) astronomy depends upon having sensitive detectors with good data quality. Since the end of the Laser Interferometer Gravitational-Wave Observatory-Virgo-KAGRA third Observing run in March 2020, detector-characterization efforts have lead to increased sensitivity of the detectors, swifter validation of GW candidates and improved tools used for data-quality products. In this article, we discuss these efforts in detail and their impact on our ability to detect and study GWs. These include the multiple instrumental investigations that led to reduction in transient noise, along with the work to improve software tools used to examine the detectors data-quality. We end with a brief discussion on the role and requirements of detector characterization as the sensitivity of our detectors further improves in the future Observing runs. 

The binary black hole signal GW250114, the loudest gravitational wave detected to date, offers a unique opportunity to test Einstein’s general relativity (GR) in the high-velocity, strong-gravity regime and probe whether the remnant conforms to the Kerr metric. Upon perturbation, black holes emit a spectrum of damped sinusoids with specific, complex frequencies. Our analysis of the postmerger signal shows that at least two quasinormal modes are required to explain the data, with the most damped remaining statistically significant for about one cycle. We probe the remnant’s Kerr nature by constraining the spectroscopic pattern of the dominant quadrupolar ( $\ell =m=2$) mode and its first overtone to match the Kerr prediction to tens of percent at multiple postpeak times. The measured mode amplitudes and phases agree with a numerical-relativity simulation having parameters close to GW250114. By fitting a parametrized waveform that incorporates the full inspiral-merger-ringdown sequence, we constrain the fundamental $(\ell =m=4)$mode to tens of percent and bound the quadrupolar frequency to within a few percent of the GR prediction. We perform a suite of tests—spanning inspiral, merger, and ringdown—finding constraints that are comparable to, and in some cases 2–3 times more stringent than those obtained by combining dozens of events in the fourth Gravitational-Wave Transient Catalog. These results constitute the most stringent single-event verification of GR and the Kerr nature of black holes to date, and outline the power of black-hole spectroscopy for future gravitational-wave observations.