Aridity-driven decoupling of δ¹³C between pedogenic carbonate and soil organic matter

Pedogenic carbonate is an invaluable archive for reconstructing continental paleoclimate and paleoecology. The δ¹³C of pedogenic carbonate (δ¹³C_c) has been widely used to document the rise and expansion of C₄ plants over the Cenozoic. This application requires a fundamental presumption that in soil pores, soil-respired CO₂ dominates over atmospheric CO₂ during the formation of pedogenic carbonates. However, the decoupling between δ¹³C_c and δ¹³C of soil organic matter (δ¹³C_(SOM)) have been observed, particularly in arid regions, suggesting that this presumption is not always valid. To evaluate the influence of atmospheric CO₂ on soil δ¹³C_c, here we performed systematic δ¹³C analyses of paleosols across the Chinese Loess Plateau, with the sample ages spanning three intervals: the Holocene, the Late Pleistocene, and the mid-Pliocene warm period. Our paired δ¹³C_c and δ¹³C_(SOM) data reveal broadly divergent trending patterns. Using a two-component CO₂-mixing model, we show substantial incorporations of atmospheric CO₂ (up to 60%) into soil pore space during carbonate precipitation. This result readily explains the enrichment of δ¹³C_c and its divergence from δ¹³C_(SOM). As a consequence, δ¹³C of pedogenic carbonates formed under semiarid and/or arid conditions are largely driven by regional aridity through its control on soil CO₂ composition, and thus cannot be used to evaluate the relative abundance of C₃ versus C₄ plants. Nonetheless, these carbonates can be applied for atmospheric CO₂ reconstructions, even for periods with low CO₂ levels

Aridity-driven decoupling of δ¹³C between pedogenic carbonate and soil organic matter

Pedogenic carbonate is an invaluable archive for reconstructing continental paleoclimate and paleoecology. The δ¹³C of pedogenic carbonate (δ¹³C_c) has been widely used to document the rise and expansion of C₄ plants over the Cenozoic. This application requires a fundamental presumption that in soil pores, soil-respired CO₂ dominates over atmospheric CO₂ during the formation of pedogenic carbonates. However, the decoupling between δ¹³C_c and δ¹³C of soil organic matter (δ¹³C_(SOM)) have been observed, particularly in arid regions, suggesting that this presumption is not always valid. To evaluate the influence of atmospheric CO₂ on soil δ¹³C_c, here we performed systematic δ¹³C analyses of paleosols across the Chinese Loess Plateau, with the sample ages spanning three intervals: the Holocene, the Late Pleistocene, and the mid-Pliocene warm period. Our paired δ¹³C_c and δ¹³C_(SOM) data reveal broadly divergent trending patterns. Using a two-component CO₂-mixing model, we show substantial incorporations of atmospheric CO₂ (up to 60%) into soil pore space during carbonate precipitation. This result readily explains the enrichment of δ¹³C_c and its divergence from δ¹³C_(SOM). As a consequence, δ¹³C of pedogenic carbonates formed under semiarid and/or arid conditions are largely driven by regional aridity through its control on soil CO₂ composition, and thus cannot be used to evaluate the relative abundance of C₃ versus C₄ plants. Nonetheless, these carbonates can be applied for atmospheric CO₂ reconstructions, even for periods with low CO₂ levels

Low CO_2 levels of the entire Pleistocene epoch

Quantifying ancient atmospheric pCO_2 provides valuable insights into the interplay between greenhouse gases and global climate. Beyond the 800-ky history uncovered by ice cores, discrepancies in both the trend and magnitude of pCO_2 changes remain among different proxy-derived results. The traditional paleosol pCO_2 paleobarometer suffers from largely unconstrained soil-respired CO_2 concentration (S(z)). Using finely disseminated carbonates precipitated in paleosols from the Chinese Loess Plateau, here we identified that their S(z) can be quantitatively constrained by soil magnetic susceptibility. Based on this approach, we reconstructed pCO_2 during 2.6–0.9 Ma, which documents overall low pCO_2 levels (<300 ppm) comparable with ice core records, indicating that the Earth system has operated under late Pleistocene pCO_2 levels for an extended period. The pCO_2 levels do not show statistically significant differences across the mid-Pleistocene Transition (ca. 1.2–0.8 Ma), suggesting that CO_2 is probably not the driver of this important climate change event

Ultrasound cavitation induced nucleation in metal solidification: an analytical model and validation by real-time experiments

Microstructural refinement of metallic alloys via ultrasonic melt processing (USMP) is an environmentally friendly and promising method. However, so far there has been no report in open literature on how to predict the solidified microstructures and grain size based on the ultrasound processing parameters.In this paper, an analytical model is developed to calculate the cavitation enhanced undercooling and the USMP refined solidification microstructure and grain size for Al-Cu alloys. Ultrafast synchrotron X-ray imaging and tomography techniques were used to collect the real-time experimental data for validating the model and the calculated results. The comparison between modeling and experiments reveal that there exists an effective ultrasound input power intensity for maximizing the grain refinement effects for the Al-Cu alloys, which is in the range of 20-45 MW/m2. In addition, a monotonous increase in temperature during USMP has negative effect on producing new nuclei, deteriorating the benefit of microstructure refinement due to the application of ultrasound

Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation

Instruction tuning has emerged to enhance the capabilities of large language models (LLMs) to comprehend instructions and generate appropriate responses. Existing methods either manually annotate or employ LLM (e.g., GPT-series) to generate data for instruction tuning. However, they often overlook associating instructions with existing annotated datasets. In this paper, we propose Dynosaur, a dynamic growth paradigm for the automatic curation of instruction-tuning data. Based on the metadata of existing datasets, we use LLMs to automatically construct instruction-tuning data by identifying relevant data fields and generating appropriate instructions. By leveraging the existing annotated datasets, Dynosaur offers several advantages: 1) it reduces the API cost for generating instructions (e.g., it costs less than $12 USD by calling GPT-3.5-turbo for generating 800K instruction tuning samples; 2) it provides high-quality data for instruction tuning (e.g., it performs better than Alpaca and Flan on Super-NI and Longform with comparable data sizes); and 3) it supports the continuous improvement of models by generating instruction-tuning data when a new annotated dataset becomes available. We further investigate a continual learning scheme for learning with the ever-growing instruction-tuning dataset, and demonstrate that replaying tasks with diverse instruction embeddings not only helps mitigate forgetting issues but generalizes to unseen tasks better. Code and data are available at https://github.com/WadeYin9712/Dynosaur.Comment: EMNLP 2023. Code and data are available at https://github.com/WadeYin9712/Dynosau

Measuring sustainability:Development and application of the Inclusive Wealth Index in China

It is increasingly common to use the Inclusive Wealth Index (IWI) to evaluate national sustainability; however, IWI's highly aggregated components and limited regional cases restrict its further application in achieving the Sustainable Development Goals (SDGs). This study extends the traditional three-component IWI framework into six disaggregated components, namely male/female human capital, advanced/ordinary produced capital, and renewable/non-renewable natural capital. We apply the modified framework to China and evaluate the sustainability performance at the provincial level. The results show that China continues to develop with an annual IWI per capita increase rate of 2.3%. Gender inequality is found to hinder the growth of IWI, whereas advanced product features benefit the growth of IWI. The results also suggest significant heterogeneity in provincial IWI primarily due to differences in economic development stages, geographic locations, and uneven IWI growth. IWI growth is largely driven by wealth accumulation resulting from human capital and advanced produced capital. In contrast, insufficient IWI growth is caused by a substantial amount of ordinary produced capital or a continued decline in natural capital. The study provides a basis for tracking progress toward the SDGs and measuring the heterogeneity of regional socio-economic development in China

3D local atomic structure evolution in a solidifying Al-0.4Sc dilute alloy melt revealed in operando by synchrotron X-ray total scattering and modelling

Using synchrotron X-ray total scattering and empirical potential structure refinement modelling, we studied systematically in operando condition the disorder-to-order local atomic structure transition in a pure Al and a dilute Al-0.4Sc alloy melt in the temperature range from 690 °C to 657 °C. In the liquid state, icosahedral short-range ordered Sc-centred Al polyhedrons form and most of them with Al coordination number of 10–12. As the melt is cooled to the semisolid state, the most Sc-centred polyhedrons become more connected atom clusters via vertex, edge and face-sharing. These polyhedrons exhibit partially icosahedral and partially face-centred-cubic symmetry. The medium-range ordered Sc-centred clusters with face-sharing are proved to be the “precursors” of the L12 Al3Sc primary phases in the liquid-solid coexisting state

Low CO_2 levels of the entire Pleistocene epoch

Quantifying ancient atmospheric pCO_2 provides valuable insights into the interplay between greenhouse gases and global climate. Beyond the 800-ky history uncovered by ice cores, discrepancies in both the trend and magnitude of pCO_2 changes remain among different proxy-derived results. The traditional paleosol pCO_2 paleobarometer suffers from largely unconstrained soil-respired CO_2 concentration (S(z)). Using finely disseminated carbonates precipitated in paleosols from the Chinese Loess Plateau, here we identified that their S(z) can be quantitatively constrained by soil magnetic susceptibility. Based on this approach, we reconstructed pCO_2 during 2.6–0.9 Ma, which documents overall low pCO_2 levels (<300 ppm) comparable with ice core records, indicating that the Earth system has operated under late Pleistocene pCO_2 levels for an extended period. The pCO_2 levels do not show statistically significant differences across the mid-Pleistocene Transition (ca. 1.2–0.8 Ma), suggesting that CO_2 is probably not the driver of this important climate change event

The thermal SZ tomography

The thermal Sunyaev-Zel'dovich (tSZ) effect directly measures the thermal pressure of free electrons integrated along the line of sight and thus contains valuable information on the thermal history of the universe. However, the redshift information is entangled in the projection along the line of sight. This projection effect severely degrades the power of the tSZ effect to reconstruct the thermal history. We investigate the tSZ tomography technique to recover this otherwise lost redshift information by cross correlating the tSZ effect with galaxies of known redshifts, or alternatively with matter distribution reconstructed from weak lensing tomography. We investigate in detail the 3D distribution of the gas thermal pressure and its relation with the matter distribution, through our adiabatic hydrodynamic simulation and the one with additional gastrophysics including radiative cooling, star formation and supernova feedback. (1) We find a strong correlation between the gas pressure and matter distribution, with a typical cross correlation coefficient r ~ 0.7 at k . 3h/Mpc and z < 2. This tight correlation will enable robust cross correlation measurement between SZ surveys such as Planck, ACT and SPT and lensing surveys such as DES and LSST, at ~20-100{\sigma} level. (2) We propose a tomography technique to convert the measured cross correlation into the contribution from gas in each redshift bin to the tSZ power spectrum. Uncertainties in gastrophysics may affect the reconstruction at ~ 2% level, due to the ~ 1% impact of gastrophysics on r, found in our simulations. However, we find that the same gastrophysics affects the tSZ power spectrum at ~ 40% level, so it is robust to infer the gastrophysics from the reconstructed redshift resolved contribution.Comment: 10 pages, 7 figures, 2 appendices, accepted by Ap