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Correction for ‘Curvature-induced hydrophobicity at imogolite–water interfaces’ by Alejandro Fernandez-Martinez et al., Environ. Sci.: Nano, 2020, DOI: 10.1039/d0en00304b.
Correction for ‘Synthesis and characterisation of brannerite compositions (U 0.9 Ce 0.1 ) 1−x M x Ti 2 O 6 (M = Gd 3+ , Ca 2+ ) for the immobilisation of MOX residues’ by D. J. Bailey et al ., RSC Adv. , 2018, 8 , 2092–2099. DOI: 10.1039/C7RA11742F.
Correction for ‘Co-self-assembly of multiple DNA origami nanostructures in a single pot’ by Joshua A. Johnson et al. , Chem. Commun. , 2021, 57 , 4795–4798, DOI: 10.1039/D1CC00049G.
Correction for ‘Character angle effects on dissociated dislocation core energy in aluminum’ by X. W. Zhou et al. , Phys. Chem. Chem. Phys. , 2021, 23 , 3290–3299, DOI: https://doi.org/10.1039/D0CP05333C.
Correction for ‘High-efficiency, anode-free lithium–metal batteries with a close-packed homogeneous lithium morphology’ by Laisuo Su et al. , Energy Environ. Sci. , 2022, 15 , 843–854, DOI: 10.1039/D1EE03103A.
Correction for ‘Optimizing accuracy and efficacy in data-driven materials discovery for the solar production of hydrogen’ by Yihuang Xiong et al. , Energy Environ. Sci. , 2021, 14 , 2335–2348; DOI: 10.1039/D0EE02984J.
Correction for ‘Carbon dioxide and nitrogen reduction reactions using 2D transition metal dichalcogenide (TMDC) and carbide/nitride (MXene) catalysts’ by Zhaodong Li et al. , Energy Environ. Sci. , 2021, 14 , 6242–6286, DOI: 10.1039/D1EE03211A.
Correction for ‘Neptunium transition probabilities estimated through laser induced breakdown spectroscopy (LIBS) measurements’ by H. B. Andrews et al. , J. Anal. At. Spectrom. , 2022, DOI: 10.1039/d1ja00423a.
Correction for ‘The nanocaterpillar's random walk: diffusion with ligand–receptor contacts’ by Sophie Marbach et al. , Soft Matter , 2022, 18 , 3130–3146, DOI: https://doi.org/10.1039/D1SM01544C.
[This corrects the article DOI: 10.1039/D5DD00019J.].
We develop a framework for the formation of exotic muonic kaon atoms ($K\mu$) in semileptonic $D^{0}$ decays, using the effective weak Hamiltonian, a helicity-based treatment of the leptonic current, and a nonrelativistic bound-state projection. The resulting branching ratio, $\mathrm{BR}(D^{0}\!\to(K\mu )\nu_{\mu})=2.29\times10^{-10}$, is implemented in a ROOT-based code to estimate yields at RHIC, LHC, and STCF. We show quantitatively that $K\mu$ atoms—also produced through coalescence in the quark--gluon plasma (QGP)—provide a sensitive probe of low-momentum primordial muons and early-time electromagnetic radiation, offering complementary constraints in an otherwise unexplored phase space for thermal dilepton and photon emission. Newly estimated dissociation cross sections in detector material indicate that secondary‑vertex reconstruction should be experimentally feasible, allowing clean experimental identification of the atoms. Projected yields from QGP coalescence in LHC and RHIC heavy-ion collisions, and from $D^{0}$ decays in LHC high-luminosity $p+p$ collisions indicate that the first observation of $K\mu$ atoms is within reach. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Article funded by SCOAP3 and published under licence by Chinese Physical Society and the Institute of High Energy Physics of the Chinese Academy of Science and the Institute of Modern Physics of the Chinese Academy of Sciences and IOP Publishing Ltd.
Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.
Persistent differences in wealth and power among prehispanic Pueblo societies are visible from the late AD 800s through the late 1200s, after which large portions of the northern US Southwest were depopulated. In this paper we measure these differences in wealth using Gini coefficients based on house size, and show that high Ginis (large wealth differences) are positively related to persistence in settlements and inversely related to an annual measure of the size of the unoccupied dry-farming niche. We argue that wealth inequality in this record is due first to processes inherent in village life which have internally different distributions of the most productive maize fields, exacerbated by the dynamics of systems of balanced reciprocity; and second to decreasing ability to escape village life owing to shrinking availability of unoccupied places within the maize dry-farming niche as villages get enmeshed in regional systems of tribute or taxation. We embed this analytical reconstruction in the model of an ‘Abrupt imposition of Malthusian equilibrium in a natural-fertility, agrarian society’ proposed by Puleston et al. (Puleston C, Tuljapurkar S, Winterhalder B. 2014 PLoS ONE 9, e87541 (doi:10.1371/journal.pone.0087541)), but show that the transition to Malthusian dynamics in this area is not abrupt but extends over centuries. This article is part of the theme issue ‘Evolutionary ecology of inequality’.
Here, we have conducted a comprehensive investigation into the magnetic properties of the chiral multiferroic material CoTeMoO 6 . In contrast with the previous claim of canted antiferromagnetic order with ferromagnetic components [Y. Doi et al., J. Solid State Chem. 182, 3232 (2009)], our investigation reveals an antiferromagnetic ground state with compensated moments, providing an interesting platform for exploring exotic material properties. Through careful measurements of magnetization under a series of applied fields, we demonstrate that there exist two sequential field-induced magnetic transitions in CoTeMoO 6 , with one occurring at 𝐻 𝑐1 =460 Oe along the 𝑎 axis, and the other at 𝐻 𝑐2 =1.16 T with the field along the 𝑏 axis. The values of 𝐻 𝑐1 and 𝐻 𝑐2 exhibit strong angular dependence and diverge with different rates as the applied field is rotated 90 ° within the 𝑎𝑏 plane. This reflects the distinct nature of these transitions, which is further supported by the different critical behavior of 𝐻 𝑐1 and 𝐻 𝑐2 , characterized by the values of 𝛾, in the function of 𝐻 𝑐 =𝐻 0 (1−𝑇/𝑇 𝑐 ) 𝛾 . Furthermore, we have demonstrated that there exist structural and magnetic twin domains in CoTeMoO 6 that strongly affect the experimental measurement of their macroscopic properties. Intriguingly, these twin domains can be related to the orthorhombicity/chirality of the crystal structure with the space group 𝑃2 1 2 1 2. We further explored the magnetic and structural domains with uniaxial pressure and polarized light microscopy. Our results suggest that CoTeMoO 6 could be used as a unique platform for investigating the intriguing physics involving intertwined degrees of freedom. The tunability of the underlying domain distribution and its strong anisotropy could also be useful for developing functional devices and applications.
This corrects the article DOI: 10.1103/PhysRevLett.129.080401.
B. Gibbs, J. McAvoy, S. T. Nutakki and R. Seetharam, "Repurposing Offshore Oil and Gas Platforms to Support Wind Power Generation," 2025 IEEE International Communications Energy Conference (INTELEC), Houstin, TX, USA, 2025, pp. 215-221, doi: 10.1109/INTELEC63987.2025.11214768.
Abstract—Grid following inverter-based renewable generation has replaced conventional generation in recent years, resulting in lower system inertia. The frequency resilience in such a lower inertia system is critical for emergency mitigation. In this paper, we propose a resilience metric based on frequency recovery to quantitatively represent system resilience in terms of the rate of change of frequency. Application of grid-forming converters provides a means to improve system resilience by providing virtual inertia. An under-frequency load shedding strategy is applied to further support frequency recovery in cases with high penetration of grid-forming inverters. Case studies are designed and performed in a modified IEEE 9-bus test system using the PSCAD/EMTDC platform. Simulation results demonstrate the validity of the proposed resilience metric and the effectiveness of the strategy for reducing frequency excursion in inverter-based power systems. citation: J. Gui, H. Lei, T. R. McJunkin and B. K. Johnson, "Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters," 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2023, pp. 1-5, doi: 10.1109/ISGT51731.2023.10066357.
Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).