Strategy research has long linked sustained competitive advantage to barriers to imitation. We highlight network effects as an alternative mechanism and adopt a geotemporal perspective to theorize how firms sustain advantage as it unfolds over time in international markets. Our study examines this question through the performance persistence of social platforms, focusing on how institutional and demand-side conditions shape the sustainability of platforms’ competitive advantages. We propose that intellectual property rights protection may restrict the degree of freedom in information dissemination, dampening the role of network effects in sustaining superior performance, whilst demand heterogeneity may enhance the value of sizable network membership for information consumption. Evidence from a cross-country dataset of platforms supports these predictions. These findings enrich our understanding of how geographic variations shape the endurance of a platform’s competitive advantage over time, offering implications for both global strategy and platform governance.

Accurate identification of potentially toxic element (PTE) sources is crucial for effective risk mitigation; however, the complex solubility of trace elements hinders such identification. Here, levels of PTEs in the dust of 105 leaf samples from 21 sites in urban Guiyang (China) were measured and positive matrix factorization was applied to help identify PTE sources. These results were validated through correlating PTE concentrations with the land-use areas surrounding the sample sites. Ni and As in the leaf dust were linked to the cleanest conditions, followed by Cr. Conversely, Zn, Cu, Cd and Pb were associated with higher pollution levels. Three primary sources of PTEs were identified, with traffic-agriculture emissions being the largest contributor at 40.42%. Natural sources followed closely at 39.41%, while industrial processes accounted for the remaining 20.17%. High-pollution areas were clustered around traffic hubs, where frequent vehicle idling and acceleration increased emissions. As traffic emission was a major source of atmospheric pollution, targeted flow optimization is needed to reduce risks of human exposure.

To determine values for the digestible indispensable amino acid score (DIAAS), it is recommended that ileal amino acid (AA) digestibility values obtained in growing pigs are used to characterise protein quality in different foods. Therefore, an experiment was conducted to determine the standardised ileal digestibility (SID) of AA in eight energy ingredients (barley, sorghum, wheat, brown rice, rice bran, wheat bran, cassava, paddy rice) fed to pigs, where SID values in pigs can be used to calculate approximate DIAAS values in humans. Among the data obtained for all energy ingredients, Significant variations (P < 0.01) in CP and AA composition were observed. Rice bran and wheat bran had the highest CP (16.43% and 18.16%, respectively) and DIAAS scores of 81–88 for adult, qualifying as “good” protein sources (> 75). Cassava, with the lowest CP (2.74%), was limited by sulfur amino acid (SAA) (54). Lysine (Lys) was the first-limiting AA in barley (74), sorghum (51), and wheat (49), with SID values lowest in wheat (71.04%). Brown rice and paddy rice showed higher SIDLys (87.51% and 78.13%, respectively). These findings highlight the potential of bran-based ingredients and Lys fortification to improve protein quality in grain-dependent diets, providing the scientific basis to combat protein malnutrition.

This study examines how top managers engage in sensemaking to navigate dynamic and complex industrial policy environments and respond strategically. Based on a longitudinal narrative case study of a privately owned firm in China, we explore how managers interpret evolving policy signals and drive corporate strategic change. We extend sensemaking theory by incorporating an institutional logics perspective to investigate how top managers draw on multiple logics to make sense of policy shifts and craft organizational responses. The study develops a holistic process model that links industrial policy, sensemaking, and strategic change, highlighting the embedded agency of top managers in responding to evolving and diverse institutional pressures. By unpacking the temporal dynamics of sensemaking, we identify how the temporality of sensemaking contributes to heterogeneity in corporate strategic behavior. This research advances understanding of sensemaking as a key process linking shifting policies with firm strategic actions and contributes to the literature on sensemaking, institutional logics, and strategic change.

How does the receipt of public assistance and social insurance relate to charitable giving and volunteering? Using data from the 2017 wave of Panel Study of Income Dynamics in the US, we employ a series of multilevel logistic regressions and tobit models to answer the research question. Results show that the receipt of public assistance and social insurance is not significantly related to volunteering. The receipt of social insurance is also not significantly associated with charitable giving, but the receipt of public assistance has a small, negative relationship with the recipients’ charitable giving. Moreover, how public assistance associates with charitable giving and volunteering varies with different public assistance programs, whereas the relationship between social insurance and charitable giving and volunteering remains insignificant when different social insurance programs are analyzed.

Public policy can directly or indirectly affect private philanthropy. Although previous studies have investigated the role of tax incentives and government grants to nonprofits, scholars do not pay much attention to how public welfare receipt affects philanthropic behavior. This study fills the gap by examining the impact of public assistance use on individual charitable giving using data from the USA and China. We employ propensity score matching to reduce the issue of selection bias and adopt logistic regression and the Tobit model to answer our research question. Our analysis demonstrates the different impacts of public assistance use on charitable giving in the two countries. In the USA, public assistance income is negatively associated with secular giving, and prior public assistance use is negatively related to religious and total giving. However, in China, there is no statistically significant relationship between public assistance use and charitable giving.

Ionic surfactants are commonly employed to modify the rheological properties of fluids, particularly in terms of surface viscoelasticity. Concurrently, external electric fields can significantly impact the dynamics of liquid threads. A key question is how ionic surfactants affect the dynamic behaviour of threads in the presence of an electric field? To investigate this, a one-dimensional model of a liquid thread coated with surfactants within a radial electric field is established, employing the long-wave approximation. We systematically investigate the effects of dimensionless parameters associated with the surfactants, including surfactant concentration, dilatational Boussinesq number ${\textit{Bo}}_{\kappa \infty }$ and shear Boussinesq number ${\textit{Bo}}_{\mu \infty }$. The results indicate that increasing the surfactant concentration and the two Boussinesq numbers reduces both the maximum growth rate and the dominant wavenumber. In addition, both the electric field and surfactants mitigate the breakup of the liquid thread and the formation of satellite droplets. At low applied electric potentials, the surface viscosity induced by surfactants predominantly governs this suppression. Surface viscosity suppresses the formation of satellite droplets by maintaining the neck point at the centre of the liquid thread within a single disturbance wavelength. When the applied potential is high, the electric stress has two main effects: the external electric field exerts a normal pressure on the liquid thread surface, suppressing satellite droplet formation, while the internal electric field inhibits liquid drainage. Surface viscosity further stabilizes the system by suppressing flow dynamics during this process.

Previous studies revealed structural differences in cerebellar regions between monolinguals and bilinguals. However, the effect of bilingual experiences on cerebellar functional neuroplasticity remains unclear. Using resting-state functional magnetic resonance imaging (fMRI) data, we compared cerebellar functional connectivity (FC) between monolinguals and bilinguals, and then examined how age of second language acquisition (AoA-L2), immersion of L2 (Immersion-L2), proficiency level of L2 (PL-L2) and usage of L2 (Usage-L2) influence cerebellar FC in bilinguals. We found monolinguals exhibited increased FC between lobules VI, VIIIa and superior temporal gyrus. Increased AoA-L2 was related to decreased cerebello-cortical FC involving lobules VI, CrusI and precentral gyrus. Increased Immersion-L2 was associated with decreased cerebello-orbitofrontal FC. Higher PL-L2 corresponded to stronger cerebellar FC with posterior cingulate gyrus. Bilinguals who used L2 more frequently at home exhibited decreased cerebellar FC, while increased social Usage-L2 was associated with increased FC. These findings highlight bilingualism’s impact on cerebellar functional neuroplasticity, shaped by different bilingual experiences.

This study reports potassium (K) isotope compositions of diamondiferous kimberlites. Altered kimberlite samples exhibit δ41K values ranging from −1.293 ± 0.052 (2SD) to −0.114 ± 0.029 ‰, showing covariations with chemical indicators of alteration. This is consistent with the geochemical dynamics of K isotopes in hydrothermal fluid-related processes. In contrast, pristine kimberlite samples display restricted K isotope compositions, with δ41K values between −0.494 ± 0.057 and −0.270 ± 0.048 ‰. Notably, the δ41K values of these pristine kimberlite samples correlate well with K2O and Rb contents, suggesting that approximately ∼0.2 ‰ of K isotope fractionation is induced by phlogopite crystallization, as indicated by quantitative modelling. The estimated δ41K values of −0.458 ‰ for the primary kimberlite melt and of −0.414 ‰ for the kimberlite source imply a potential link to the bulk silicate Earth. These new measurements, along with literature data from various rocks, indicate that the K isotope composition in the deep mantle (>150 km) is more homogenous than in shallow regions, likely reflecting the efficiency of convection flow and K behaviour during subduction. In addition, the K isotope data reveal temporal variations in mantle-derived magmas from the Palaeozoic to the Cenozoic, highlighting the geological history and lithospheric destruction of the North China Craton. This study underscores the significance of K isotopes in enhancing our understanding of mantle dynamics, crustal recycling and the geochemical evolution of the Earth’s interior.

In the realm of data-to-text generation tasks, the use of large language models (LLMs) has become common practice, yielding fluent and coherent outputs. Existing literature highlights that the quality of in-context examples significantly influences the empirical performance of these models, making the efficient selection of high-quality examples crucial. We hypothesize that the quality of these examples is primarily determined by two properties: their similarity to the input data and their diversity from one another. Based on this insight, we introduce a novel approach, Double Clustering-based In-Context Example Selection, specifically designed for data-to-text generation tasks. Our method involves two distinct clustering stages. The first stage aims to maximize the similarity between the in-context examples and the input data. The second stage ensures diversity among the selected in-context examples. Additionally, we have developed a batched generation method to enhance the token usage efficiency of LLMs. Experimental results demonstrate that, compared to traditional methods of selecting in-context learning samples, our approach significantly improves both time efficiency and token utilization while maintaining accuracy.