Search for: All records

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. 

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. 

We develop a systematic framework for the spin adaptation of the cumulants of p-particle reduced density matrices (RDMs), with explicit constructions for p = 1 to 3. These spin-adapted cumulants enable rigorous treatment of both Ŝz and Ŝ2 symmetries in quantum systems, providing a foundation for spin-resolved electronic structure methods. We show that complete spin adaptation—referred to as completeS-representability—can be enforced by constraining the variances of Ŝz and Ŝ2, which require the 2-RDM and 4-RDM, respectively. Importantly, the cumulants of RDMs scale linearly with system size—size-extensive—making them a natural object for incorporating spin symmetries in scalable electronic structure theories. The developed formalism is applicable to density-based methods, one-particle RDM functional theories, and two-particle RDM methods. We further extend the approach to spin–orbit-coupled systems via total angular momentum adaptation. Beyond spin, the framework enables the adaptation of RDM theories to additional symmetries through the construction of suitable irreducible tensor operators. 

This research presents an enhanced Graph Attention Convolutional Neural Network (GAT) tailored for the analysis of open-source package vulnerability remediation. By meticulously examining control flow graphs and implementing node centrality metrics—specifically, degree, norm, and closeness centrality—our methodology identifies and evaluates changes resulting from vulnerability fixes in nodes, thereby predicting the ramifications of dependency upgrades on application workflows. Empirical testing on diverse datasets reveals that our model challenges established paradigms in software security, showcasing its efficacy in delivering comprehensive insights into code vulnerabilities and contributing to advancements in cybersecurity practices. This study delineates a strategic framework for the development of sustainable monitoring systems and the effective remediation of vulnerabilities in open-source software.