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Women climate scientists are connected, productive, and successful but have shorter careers
Scholars have long been concerned about gender representation in scientific research but there has been little work on gender differences in participation and performance in climate science, a field that engages with both male-majority disciplines (e.g., geosciences, engineering) and female-majority disciplines (e.g., life sciences, medical science). This has implications for both gender equity and viewpoint representation. Sampling over 400,000 publications and a similar number of authors, we examine gender differences in several scholarly outcomes including publication count, career survival, coauthor gender, journal status, and mean citation count. We find men and women are similarly productive, successful, and connected, though women have shorter research careers and thus fewer papers. We also find gender homophily effects in collaboration, but no evidence of gender bias in peer review.
Mapping global floods with 10 years of satellite radar data
Abstract Floods cause extensive global damage annually, making effective monitoring essential. While satellite observations have proven invaluable for flood detection and tracking, comprehensive global flood datasets spanning extended time periods remain scarce. In this study, we introduce a deep learning flood detection model that leverages the cloud-penetrating capabilities of Sentinel-1 Synthetic Aperture Radar (SAR) satellite imagery, enabling consistent flood extent mapping through cloud cover and in both day and night conditions. By applying this model to 10 years of SAR data, we create a unique, longitudinal global flood extent dataset with predictions unaffected by cloud coverage, offering comprehensive and consistent insights into historically flood-prone areas over the past decade. We use our model predictions to identify historically flood-prone areas in Ethiopia and demonstrate real-time disaster response capabilities during the May 2024 floods in Kenya. Additionally, our longitudinal analysis reveals potential increasing trends in global flood extent over time, although further validation is required to explore links to climate change. To maximize impact, we provide public access to both our model predictions and a code repository, empowering researchers and practitioners worldwide to advance flood monitoring and enhance disaster response strategies.
Industrializable interlayer with catalytic conversion of dead lithium for Ah–level Nickel–rich lithium metal batteries
Self-rectifying memristors with high rectification ratio for attack-resilient autonomous driving systems
Tailoring Zn‐ion Solvation Structures for Enhanced Durability and Efficiency in Zinc–Bromine Flow Batteries
Abstract Aqueous zinc‐bromine flow batteries (ZBFBs) are among the most appealing technologies for large‐scale stationary energy storage due to their scalability, cost‐effectiveness, safety and sustainability. However, their long‐term durability is challenged by issues like the hydrogen evolution reaction (HER) and dendritic zinc electroplating. Herein, we address these challenges by reshaping the Zn 2+ ion solvation structures in zinc bromide (ZnBr 2 ) aqueous electrolytes using a robust hydrogen bond acceptor as a cosolvent additive. Our findings highlight the critical role of interactions within the first and second Zn 2+ solvation shells in determining electrochemical performance. By selectively incorporating a low volume percentage of organic additive into the second coordination shell of Zn 2+ , we achieve effective proton capture, electrolyte pH stabilization during the Zn 0 electroplating, and mitigation of ion transport resistance. This approach prevents the formation of a passivation interphase layer on the electrode surface, which typically occurs with higher additive concentrations, leading to increased interphase resistance and cell polarization. This work opens a new avenue in modulating Zn 2+ reactivity and stability through precise solvation structure design, enabling efficient and reversible Zn 0/2+ plating/stripping in aqueous electrolytes with suppressed H 2 evolution. These findings pave the way for the development of commercially viable, high‐performance ZBFBs for energy storage applications.
Two-photon polymerization based 4D printing of poly(N-isopropylacrylamide) hydrogel microarchitectures for reversible shape morphing
Relumino mode may provide video terminal assistance for the amblyopic patients
Continuous beta-2 microglobulin–based clearance highlights superiority of high-Dose HDF over high-flux HD in predicting outcomes
Abstract Recent studies suggest that high-dose hemodiafiltration (HDF) may reduce mortality more effectively than high-flux hemodialysis (HD), though the mechanisms remain unclear. Traditional metrics such as Kt/V and convective volume do not fully capture overall dialysis efficiency. This study proposes a novel approach using circulating beta-2-microglobulin (ß2M) levels to estimate an equivalent Continuous Dialytic Clearance (eCDCß2M), reflecting an equivalent glomerular filtration rate. Using data from the FRENCHIE study, we calculated eCDCß2M and assessed its association with patient outcomes, including all-cause and cardiovascular mortality, in comparison with traditional dialysis dose metrics. Our analysis showed that HDF achieved higher treatment efficiency than high-flux HD, with a mean increase of + 1.5 ml/min in eCDCß2M. Moreover, eCDCß2M demonstrated superior predictive value for mortality risk compared to Kt/V. These findings support eCDCß2M as a meaningful and physiologically relevant measure of dialysis efficiency and adequacy. By better reflecting the continuous function of the native kidney, this approach may improve patient stratification and outcome prediction across all forms of kidney replacement treatment schedule. Further validation in independent patient cohorts is warranted.
Application of a novel metaheuristic algorithm inspired by Adam gradient descent in distributed permutation flow shop scheduling problem and continuous engineering problems
Impacts of dietary Saccharomyces cerevisiae fermentation derived postbiotic on growth performance and health status of Pacific white shrimp
Model for selective vehicle problem considering mixed fleet with capacitated electric vehicles
Investigating the performance of the fluorescent sensor g-C3N4/Fe/Cu in detecting the Tenofovir drug
Non-ergodic dissociative valence double ionization of SF6
Abstract The dissociative double ionization of sulphur hexafluoride, SF 6 , in the ionization energy range from threshold up to 48.4 eV has been examined in detail using a multiple coincidence electron-ion technique. The results are interpreted by comparison with molecular dynamics simulations, high level molecular structure calculations and with a statistical model of the ion breakdown. Comparison between the experimental breakdown pattern and the pattern derived on the basis of statistical theory indicates that the energy redistribution required for fully statistical behaviour is incomplete on the timescale of the dissociation reactions of $${\text{SF}}_6^{2 + }$$ , suggesting that the molecular size at which ergodic behaviour becomes dominant is larger for doubly and multiply charged ions than for neutral and singly ionized molecules.
Spatial metabolomics informs the use of clinical imaging for improved detection of cribriform prostate cancer
Cribriform prostate cancer (crPCa) is associated with poor clinical outcomes, yet its accurate detection remains challenging due to the poor sensitivity of standard-of-care diagnostic tools. Here, we use untargeted spatial metabolomics to identify fatty acid biosynthesis as a key metabolic pathway enriched in crPCa epithelium. We also show that imaging tumor lipid metabolism using [1- 11 C]acetate PET/CT and proton magnetic resonance spectroscopy differentiates cribriform from noncribriform intermediate-risk prostate cancers in two prospective patient cohorts. These findings support the feasibility of using clinical metabolic imaging techniques as adjunctive tools for improving crPCa detection in clinical practice, with prospective studies in larger cohorts warranted to obtain definitive results.
Microbial bioremediation of persistent organic pollutants in plant tissues provides crop growth promoting liquid fertilizer
Fluorine-induced gradient electric field in mesoporous covalent organic frameworks for efficient separation of polarized perfluorinated gases
Graphene-driven correlated electronic states in one dimensional defects within WS2
Abstract Tomonaga-Luttinger liquid (TLL) behavior in one-dimensional systems has been predicted and shown to occur at semiconductor-to-metal transitions within two-dimensional materials. Reports of one-dimensional defects hosting a Fermi liquid or a TLL have suggested a dependence on the underlying substrate, however, unveiling the physical details of electronic contributions from the substrate require cross-correlative investigation. Here, we study TLL formation within defectively engineered WS 2 atop graphene, where band structure and the atomic environment is visualized with nano angle-resolved photoelectron spectroscopy, scanning tunneling microscopy and spectroscopy, and non-contact atomic force microscopy. Correlations between the local density of states and electronic band dispersion elucidated the electron transfer from graphene into a TLL hosted by one-dimensional metal (1DM) defects. It appears that the vertical heterostructure with graphene and the induced charge transfer from graphene into the 1DM is critical for the formation of a TLL.