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Abstract Coral reefs are essential for the foundation of marine ecosystems. However, ocean acidification (OA), driven by rising atmospheric carbon dioxide (CO₂) threatens coral growth and biological homeostasis. This study examines two Hawaiian coral species—Montipora capitataandPocillopora acutato elevated pCO₂simulating OA. Utilizing pH and O₂microsensors under controlled light and dark conditions, this work characterized interspecific concentration boundary layer (CBL) traits and quantified material fluxes under ambient and elevated pCO₂. The results of this study revealed that under increased pCO₂,P. acutashowed a significant reduction in dark proton efflux, followed by an increase in light O₂flux, suggesting reduced calcification and enhanced photosynthesis. In contrast,M. capitatadid not show any robust evidence of changes in either flux parameters under similar increased pCO₂conditions. Statistical analyses using linear models revealed several significant interactions among species, treatment, and light conditions, identifying physical, chemical, and biological drivers of species responses to increased pCO₂. This study also presents several conceptual models that correlate the CBL dynamics measured here with calcification and metabolic processes, thereby justifying our findings. We indicate that elevated pCO₂exacerbates microchemical gradients in the CBL and may threaten calcification in vulnerable species such asP. acuta, while highlighting the resistance ofM. capitata. Therefore, this study advances our understanding of how interspecific microenvironmental processes could influence coral responses to changing ocean chemistry. 

Abstract Kelp forests form some of the most productive areas on earth and are proposed to sequester carbon in the ocean, largely in the form of released dissolved organic carbon (DOC). Here we investigate the role of environmental, seasonal and age-related physiological gradients on the partitioning of net primary production (NPP) into DOC by the canopy forming giant kelp (Macrocystis pyrifera). Rates of DOC production were strongly influenced by an age-related decline in physiological condition (i.e. senescence). During the mature stage of giant kelp development, DOC production was a small and constant fraction of NPP regardless of tissue nitrogen content or light intensity. When giant kelp entered its senescent phase, DOC production increased substantially and was uncoupled from NPP and light intensity. Compositional analysis of giant kelp-derived DOC showed that elevated DOC production during senescence was due to the solubilization of biomass carbon, rather than by direct exudation. We coupled our incubation and physiological experiments to a novel satellite-derived 20-year time series of giant kelp canopy biomass and physiology. Annual DOC production by giant kelp varied due to differences in standing biomass between years, but on average, 74% of the annual DOC production by giant kelp was due to senescence. This study suggests DOC may be a more important fate of macroalgal NPP than previously recognized. 

Abstract In Sub-Saharan Africa (SSA), over 75% of households lack on-premises water access, requiring residents to spend time walking to collect water from outside their homes – a time burden that falls disproportionately on women and girls. Climate change is predicted to alter precipitation and temperature patterns in SSA, which could impact household water access. Here, we use spatial first differences to assess the causal effects of weather on water fetching walk time using household survey data (n = 979,759 observations from 31 countries) merged with geo- and temporally-linked precipitation and temperature data over time periods ranging from 7 to 365 days. We find increases in precipitation reduce water fetching times; a 1 cm increase in weekly rainfall over the past year decreases walking time by 3.5 min. Higher temperatures increase walk times, with a 1°C increase in temperature over the past year increasing walking time by 0.76 min. Rural household water fetching times are more impacted by recent weather compared to urban households; however, electricity access in rural communities mitigates the effect. Our findings suggest that future climate change will increase the water fetching burden in SSA, but that co-provision of electricity and water infrastructure may be able to alleviate this burden. 

Understanding information flow in the brain can be facilitated by arranging neurons in the fly connectome to form a maximally “feedforward” structure. This task is naturally formulated as the Minimum Feedback Arc Set (MFAS)—a well-known NP-hard problem, especially for large-scale graphs. To address this, we propose the Rocket-Crane algorithm, an efficient two-phase method for solving MFAS. In the first phase, we develop a continuous-space optimization method that rapidly generates excellent solutions. In the second phase, we refine these solutions through advanced exploration techniques that integrate randomized and heuristic strategies to effectively escape local minima. Extensive experiments demonstrate that Rocket-Crane outperforms state-of-the-art methods in terms of solution quality, scalability, and computational efficiency. On the primary benchmark—the fly connectom—our method achieved a feedforward arc set with a total forward weight of 35,459,266 (about 85$$\%$$ $\%$), the highest among all competing methods. The algorithm is open-source and available on GitHub. 

In the 1980s, high-performance computing (HPC) became another tool for research in the open (non-defense) science and engineering research communities. However, HPC came with a high price tag; the first Cray-2 machines, released in 1985, cost between $12 million and $17 million, according to the Computer History Museum, and were largely available only at government research labs or through national supercomputing centers. In the 1990s, with demand for HPC increasing due to vast datasets, more complex modeling, and the growing computational needs of scientific applications, researchers began experimenting with building HPC machines from clusters of servers running the Linux operating system. By the late 1990s, two approaches to Linux-based parallel computing had emerged: the personal computer cluster methodology that became known as Beowulf and the Roadrunner architecture aimed at a more cost-effective supercomputer. While Beowulf attracted attention because of its low cost and thereby greater accessibility, Roadrunner took a different approach. While still affordable compared to vector processors and other commercially available supercomputers, Roadrunner integrated its commodity components with specialized networking technology. Furthermore, these systems initially served different purposes. While Beowulf focused on providing affordable parallel workstations for individual researchers at NASA, Roadrunner set out to provide a multiuser system that could compete with the commercial supercomputers that dominated the market at the time. This paper analyzes the technical decisions, performance implications, and long-term influence of both approaches. Through this analysis, we can start to judge the impact of both Roadrunner and Beowulf on the development of Linux-based supercomputers. 

The Safe System Approach (SSA) aims to eliminate fatal and serious injury roadway crashes through a holistic view of the road system, moving away from traditional safety analysis based exclusively on historical crash data. One reason for this is the classification of crashes into broad categories (e.g., head-on, sideswipe), which does not capture crash progression or contributing factors. In this context, this paper applies crash sequence analysis to historical crash data and uses the findings to proactively identify safety issues in similar contexts, in alignment with the SSA framework. The method uses sequence-of-events information from crash data to generate clusters of crashes with similar underlying characteristics. Data from fatal and serious injury crashes from urban intersections in the state of Ohio between 2018 and 2022 were used in the analysis. The results show 12 clusters with unique characteristics that consider the sequence of events of each crash. Although derived from crash data, the clusters offer an in-depth understanding of the factors associated with each one and help identify cluster-specific countermeasures related to various SSA elements. State and local jurisdictions can use the presented methodology in transportation safety programs, by focusing on the clusters that represent local challenges or on countermeasures related to the issues of multiple clusters. Finally, the method can also be associated with site-specific analysis, providing a comprehensive toolkit for practitioners. 

Endotracheal intubation is a critical medical procedure for protecting a patient’s airway. Current intubation technology requires extensive anatomical knowledge, training, technical skill, and a clear view of the glottic opening. However, all of these may be limited during emergency care for trauma and cardiac arrest outside the hospital, where first-pass failure is nearly 35%. To address this challenge, we designed a soft robotic device to autonomously guide a breathing tube into the trachea with the goal of allowing rapid, repeatable, and safe intubation without the need for extensive training, skill, anatomical knowledge, or a glottic view. During initial device testing with highly trained users in a mannequin and a cadaver, we found a 100% success rate and an average intubation duration of under 8 s. We then conducted a preliminary study comparing the device with video laryngoscopy, in which prehospital medical providers with 5 min of device training intubated cadavers. When using the device, users achieved an 87% first-pass success rate and a 96% overall success rate, requiring an average of 1.1 attempts and 21 s for successful intubation, significantly (P = 0.008) faster than with video laryngoscopy. When using video laryngoscopy, the users achieved a 63% first-pass success rate and a 92% overall success rate, requiring an average of 1.6 attempts and 44 s for successful intubation. This preliminary study offers directions for future clinical studies, the next step in testing a device that could address the critical needs of emergency airway management and help democratize intubation.