Beryllium isotopes (stable 9Be and cosmogenic meteoric 10Be) enter the oceans through distinct pathways – i.e., from the continents and the atmosphere respectively – and display non-conservative behaviour in seawater. This isotope system has served as a powerful tool for quantifying a variety of processes, including geomagnetism, sedimentation, continental input, and ocean circulation. However, processes at land–ocean boundaries and within the ocean interior may either amplify or buffer the seawater isotope response to environmental changes. In the last decade, substantial effort has been invested in understanding external sources and internal cycling of Be isotopes, offering an excellent opportunity to revisit their modern oceanic cycle. Here, we investigate the controls on the modern oceanic cycling of Be isotopes using a three-dimensional ocean model, constrained by observational data on input fluxes and water-column distributions of 9Be and 10Be. In addition to modelling the previously known controls, we highlight the key role of marine benthic fluxes and scavenging onto particulate organic matter and opal in determining the mass balance and spatial distribution of Be isotopes. Inter-basin Be transport by the circulation is less important than external inputs at continent/atmosphere–ocean boundaries, except in the South Pacific. Therefore, the distribution of seawater 10Be/9Be ratios largely reflects that of the external inputs in most basins in the modern ocean. Finally, we apply our data-constrained mechanistic model to test the sensitivity of basin-wide 10Be/9Be ratios to changes of external sources and internal cycling. This analysis shows that seawater 10Be/9Be ratios are to some extent buffered against changes in continental denudation. For example, a 50 % decrease in denudation rates results in a 13–48 % increase in ocean-wide 10Be/9Be ratios. Moreover, the interplay between particle scavenging and ocean circulation can cause divergent responses in 10Be/9Be ratios in different basins. Weaker scavenging (e.g., 50 % decrease in intensity) would increase the homogenising effect of ocean circulation, making North Atlantic and North Pacific 10Be/9Be ratios converge (∼20 % change in isotope ratios). The mechanistic understanding developed from this Be cycling model provides important insights into the various applications of marine Be isotopes, and offers additional tools to assess the causes of spatio-temporal Be isotope variations. We also identify the key oceanic processes that require further constraints to achieve a complete understanding of Be cycling in the modern ocean and back through time.
Using the census data from 2000-2015 and a pseudo-event study design, we estimate the motherhood penalty in China and explore its association with declining fertility. We find that one-third of working women leave their jobs in the year when they give birth, and the penalty persists for over eight years. The motherhood penalty increases significantly across almost all provinces during this period, and provinces with larger increases in the penalty experience greater declines in fertility rates. Using a mover-based design, we find that the rising motherhood penalty has caused a significant decline in the total fertility rate.
Multi-focus image fusion (MFIF) is a critical technique for enhancing depth of field in photography, producing an all-in-focus image from multiple images captured at different focal lengths. While deep learning has shown promise in MFIF, most existing methods ignore the physical model of defocus blurring in their neural architecture design, limiting their interoperability and generalization. This paper presents a novel framework that integrates explicit defocus blur modeling into the MFIF process, leading to enhanced interpretability and performance. Leveraging an atom-based spatially-varying parameterized defocus blurring model, our approach first calculates pixel-wise defocus descriptors and initial focused images from multi-focus source images through a scale-recurrent fashion, based on which soft decision maps are estimated. Afterward, image fusion is performed using masks constructed from the decision maps, with a separate treatment on pixels that are probably defocused in all source images or near boundaries of defocused/focused regions. Model training is done with a fusion loss and a cross-scale defocus estimation loss. Extensive experiments on benchmark datasets have demonstrated the effectiveness of our approach.
WeproposeanODEapproachtosolvingmultiplechoicepolynomialprogram- ming (MCPP) after assuming that the optimum point can be approximated by the ex- pected value of so-called thermal equilibrium as usually did in simulated annealing. The explicit form of the feasible region and the affine property of the objective function are both fully exploited in transforming an MCPP problem into an ODE system. We also show theoretically that a local optimum of the former can be obtained from an equilib- rium point of the latter. Numerical experiments on two typical combinatorial problems, MAX-k-CUT and the calculation of star discrepancy, demonstrate the validity of the ODE approach, and the resulting approximate solutions are of comparable quality to those obtained by the state-of-the-art heuristic algorithms but with much less cost. When compared with the numerical results obtained by using Gurobi to solve MCPP directly, our ODE approach is able to produce approximate solutions of better quality in most instances. This paper also serves as the first attempt to use a continuous algorithm for approximating the star discrepancy.
Recent advances on time series forecasting mainly focus on improving the forecasting models themselves. However, when the time series data suffer from potential structural breaks or concept drifts, the forecasting performance might be significantly reduced. In this paper, we introduce a novel approach called Optimal Starting Point Time Series Forecast (OSP-TSP) for optimal forecasting, which can be combined with existing time series forecasting models. By adjusting the sequence length via leveraging the XGBoost and LightGBM models, the proposed approach can determine the optimal starting point (OSP) of the time series and then enhance the prediction performances of the base forecasting models. To illustrate the effectiveness of the proposed approach, comprehensive empirical analysis have been conducted on the M4 dataset and other real world datasets. Empirical results indicate that predictions based on the OSP-TSP approach consistently outperform those using the complete time series dataset. Moreover, comparison results reveals that combining our approach with existing forecasting models can achieve better prediction accuracy, which also reflect the advantages of the proposed approach.
This study examines how overconfidence shapes individuals' preference for redistribution. We contend that overconfidence inflates individuals' income expectations, which reduces the perceived benefits of redistribution for these individuals and thereby weakens their preference for such policies. Using data from the 2014 China Family Panel Studies, we find that overconfident individuals are more confident in their future life and exhibit less concerns for economic inequality, healthcare, and social security issues—key proxies for preference for redistribution. These results are more pronounced among less wealthy individuals. In addition, our results remain unchanged after controlling for individuals' trust in government and risk preference. These findings highlight the role of biased belief in shaping individuals’ attitude toward redistribution, offering new insights for discussions on redistributive policies.
Mineral crystallization is central to myriad natural processes from the formation of snowflakes to stalagmites, but the molecularscale mechanisms are often far more complex than models reflect. Feedbacks between the hydro-, bio-, and geo-spheres drive complex crystallization processes that challenge our ability to observe and quantify them, motivating an expansion of crystallization theories. In this article, we discuss how the driving forces and timescales of nucleation are influenced by factors ranging from simple geometric confinement to distinct interfacial solution structures involving solvent organization, electrical double layers, and surface charging effects. Taken together, these ubiquitous natural phenomena can preserve metastable intermediates, drive precipitation of undersaturated phases, and modulate crystallization in time and space.
Language and language education are central to studies of Chinese diasporic culture. However, existing scholarship has overwhelmingly focused on how overseas Chinese populations navigate language politics in their host societies. This research adopts a different perspective by examining the crucial roles overseas Chinese played in establishing Indonesian language programs in mainland China between the mid-1940s and mid-1960s. Specifically, overseas Chinese “returnees” were indispensable in founding the National College of Oriental Studies during World War II and launching several Indonesian language programs in the early years of the People’s Republic of China. While these programs served vastly different political purposes over time, they also reveal critical yet often overlooked aspects of—and surprising continuities in—China-Indonesia cultural exchange amid decolonization, domestic conflicts, and the Cold War. Although the primary aim of these programs was to fulfill the operational needs of state agencies and government-affiliated organizations, returnee networks played essential roles in promoting Indonesian culture in China. They actively participated in circulatory cultural diplomacy between the two countries, contributing significantly to China’s long-term knowledge production on Indonesia.
Nickel (Ni) is a biologically active metal whose reactivity and isotope fractionation in the marine realm are strongly influenced by biological and redox-related processes, giving the stable isotope system potential for studying past ocean environments. Reducing, organic-rich, sediments constitute an important sink of Ni from the modern ocean. Importantly, at open ocean upwelling margins, these kinds of sediment record the isotope composition of the modern deep ocean. Thus, records of their Ni isotope composition in the past have the potential to record the past deep ocean isotope composition and the oceanic isotope mass balance. However, the detailed processes controlling the upwelling sink are not fully understood. Here, we address this issue through data for sediments, porewaters and the water column of Kiel Bight in the Western Baltic Sea. This setting preserves sediments that have similar characteristics to those of open ocean upwelling margins, allowing us to study specific controlling processes in a well constrained setting. In common with sediments from open-ocean upwelling settings, Ni is well-correlated with carbon in solid sediment, suggesting delivery of Ni via rain of organic carbon from the water column. Overall, porewaters at all sites studied show increasing Ni concentrations from around 10 nM near the sediment–water interface to as high as 50 nM at 25 cm depth. This increase is correlated with increases in ammonia concentrations, suggesting release of Ni from anaerobic respiration of organic matter. However, porewater Ni/NH4 ratios are always lower than Ni:N of water column suspended particulate matter, suggesting an additional process that removes Ni from the porewater. Porewater sulphide also increases with depth, from as low as zero at the sediment–water interface to levels as high as 3 mM at 25 cm. Overall, porewater Ni isotopes become heavier with depth, from bottom water δ60Ni around +0.5 to +1‰, to values as high as +2.3‰ at depth. All these observations strongly suggest that Ni is removed from porewater into a solid sulphide. Mass balance indicates that over 90% of the Ni delivered in organic material to the sediment–water interface is transferred from organic matter into solid sulphide. Upward diffusive fluxes lead to the loss of a small amount back to the water column via a benthic flux. Given the large proportion of Ni retained within the sediment, the loss of such Ni does not strongly impact the isotope composition of the buried pool. These data are crucial in clarifying the processes controlling the size and isotope composition of organic-rich sediments on upwelling margins.
