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Increasing coherent interrogation times is central to advancing the precision of optical clocks. Synchronous differential optical clock comparisons have now demonstrated atomic coherence times that far exceed the coherence time of the clock laser. While atom coherence times are then primarily limited by errors induced by lattice Raman scattering, excited clock state radiative decay, and broadening from two-body collisions, many of these errors take the atoms out of the clock transition subspace, and can therefore be converted into “erasure” errors if the appropriate readout scheme is employed. Here we experimentally demonstrate a hyperfine-resolved readout technique for ${}^{87}\mathrm{Sr}$optical lattice clocks that mitigates decoherence from Raman scattering induced by the lattice as well as radiative decay. By employing hyperfine-resolved readout in synchronous differential comparisons between ${}^{87}\mathrm{Sr}$ensembles with both Ramsey and spin-echo spectroscopy sequences, we achieve enhanced atomic coherence times exceeding 100 and 150 s, respectively, enabling longer coherent measurements without a reduction in performance. We anticipate that this hyperfine-resolved readout technique will benefit applications of state-of-the-art optical lattice clock comparisons in which the coherence times are constrained by Raman scattering or radiative decay. 

With four components – distributive, procedural, interpersonal, and informational – organizational fairness provides a framework for examining institutional processes, including those that relate to pay. 

Communication is essential to teamwork and requires attention to be successful. By incorporating approaches that meet the needs of your deaf and hard-of-hearing (DHH) colleagues, you can improve access to communication for all. 

This series of questions can prepare you to learn more about your institution’s compensation system and illuminate potential areas for improvement. 

Ground rules reflect what is important to team members about how they interact and can promote inclusion within the team 

Understand the collective mix of salary, other pay, benefits, and non-pay considerations for faculty in higher ed. 

Fairness traps represent opportunities to fortify fairness by identifying guiding principles, raising awareness about assumptions being made, and inserting fairness checks into the process. 

The recent SARS-CoV-2 (COVID-19) pandemic exemplifies how newly emerging and reemerging viruses can quickly overwhelm and cripple global infrastructures. Coupled with synergistic factors such as increasing population densities, the constant and massive mobility of people across geographical areas and substantial changes to ecosystems worldwide, these pathogens pose serious health concerns on a global scale. Vaccines form an indispensable defense, serving to control and mitigate the impact of devastating outbreaks and pandemics. Towards these efforts, we developed a tunable vaccine platform that can be engineered to simultaneously display multiple viral antigens. Here, we describe a second-generation version wherein chimeric proteins derived from SARS-CoV-2 and bacteriophage lambda are engineered and used to decorate phage-like particles with defined surface densities and retention of antigenicity. This streamlines the engineering of particle decoration, thus improving the overall manufacturing potential of the system. In a prime-boost regimen, mice immunized with particles containing as little as 42 copies of the chimeric protein on their surface develop potent neutralizing antibody responses, and immunization protects mice against virulent SARS-CoV-2 challenge. The platform is highly versatile, making it a promising strategy to rapidly develop vaccines against a potentially broad range of infectious diseases. 

Abstract. Water quality in lakes is an emergent property of complex biotic and abiotic processes that differ across spatial and temporal scales. Water quality is also a determinant of ecosystem services that lakes provide and is thus of great interest to ecologists. Machine learning and other computer science techniques are increasingly being used to predict water quality dynamics as well as to gain a greater understanding of water quality patterns and controls. To benefit the sciences of both ecology and computer science, we have created a benchmark dataset of lake water quality time series and vertical profiles. LakeBeD-US contains over 500 million unique observations of lake water quality collected by multiple long-term monitoring programs across 17 water quality variables from 21 lakes in the United States. There are two published versions of LakeBeD-US: the “Ecology Edition” published in the Environmental Data Initiative repository (https://doi.org/10.6073/pasta/c56a204a65483790f6277de4896d7140, McAfee et al., 2024) and the “Computer Science Edition” published in the Hugging Face repository (https://doi.org/10.57967/hf/3771, Pradhan et al., 2024). Each edition is formatted in a manner conducive to inquiries and analyses specific to each domain. For ecologists, LakeBeD-US: Ecology Edition provides an opportunity to study the spatial and temporal dynamics of several lakes with varying water quality, ecosystem, and landscape characteristics. For computer scientists, LakeBeD-US: Computer Science Edition acts as a benchmark dataset that enables the advancement of machine learning for water quality prediction. 

Abstract Urea is hypothesized to be an important source of nitrogen and chemical energy to microorganisms in the deep sea; however, direct evidence for urea use below the epipelagic ocean is lacking. Here, we explore urea utilization from 50 to 4000 meters depth in the northeastern Pacific Ocean using metagenomics, nitrification rates, and single-cell stable-isotope-uptake measurements with nanoscale secondary ion mass spectrometry. We find that on average 25% of deep-sea cells assimilated urea-derived N (60% of detectably active cells), and that cell-specific nitrogen-incorporation rates from urea were higher than that from ammonium. Both urea concentrations and assimilation rates relative to ammonium generally increased below the euphotic zone. We detected ammonia- and urea-based nitrification at all depths at one of two sites analyzed, demonstrating their potential to support chemoautotrophy in the mesopelagic and bathypelagic regions. Using newly generated metagenomes we find that the ureC gene, encoding the catalytic subunit of urease, is found within 39% of deep-sea cells in this region, including the Nitrososphaeria (syn., Thaumarchaeota; likely for nitrification) as well as members of thirteen other phyla such as Proteobacteria, Verrucomicrobia, Plantomycetota, Nitrospinota, and Chloroflexota (likely for assimilation). Analysis of public metagenomes estimated ureC within 10–46% of deep-sea cells around the world, with higher prevalence below the photic zone, suggesting urea is widely available to the deep-sea microbiome globally. Our results demonstrate that urea is a nitrogen source to abundant and diverse microorganisms in the dark ocean, as well as a significant contributor to deep-sea nitrification and therefore fuel for chemoautotrophy.