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Compacted cement stabilized gravel pile can effectively control secondary disasters of subgrade, while the bearing mechanism of semi-rigid pile composite foundation is not clear. The load–settlement ( Q – S ) curves, pile mechanical features and pile–soil stress characteristics of the composite foundation were analyzed by field tests and numerical simulation. Moreover, the characteristic value and calculating equation of the bearing capacity were discussed. Results show that the axial force of the group pile in composite foundation increases first and then decreases with the depth, the negative friction resistance is in the upper part, the neutral point is located at one-fifth of the length below the top. The lateral friction of the lower part of the pile plays a role before the upper lateral friction, and more than 90% of the pile load is supported by lateral friction. The curve of pile–soil stress ratio is hump-shaped, the stress ratio of pile to adjacent pile center soil is 6.08–6.65, and the stress ratio of pile to diagonal pile center soil is 7.5–9.45. Q – S curve of the single pile is characterized as a sharp decline, the characteristic value of the bearing capacity can be obtained by the equation of rigid pile, and the reduction coefficient of the pile strength is 0.25. Q – S curve of the composite foundation performs a slow downward tendency, the characteristic value of the bearing capacity can be obtained by the equation of compacted cement–soil piles, it is suggested that the correction coefficient of the vertical compressive bearing capacity is 1.0, and the bearing capacity correction coefficient of soil between piles is 1.05–1.15.

Tissue engineering approaches seem to be an attractive therapy for tendon rupture. Novel injectable porous gelatin microcryogels (GMs) can promote cell attachment and proliferation, thus facilitating the repair potential for target tissue regeneration. The research objectives of this study were to assess the efficacy of tissue-like microunits constructed by multiple GMs laden with adipose-derived mesenchymal stem cells (ASCs) in accelerated tendon regeneration in a rat model. Through a series of experiments, such as isolation and identification of ASCs, scanning electron microscopy, mercury intrusion porosimetry (MIP), laser scanning confocal microscopy and the CCK-8 test, the biocompatibility of GMs was evaluated. In an in vivo study, 64 rat right transected Achilles tendons were randomly divided into four groups: the ASCs+GMs group (microunits aggregated by multiple ASC-laden GMs injected into the gap), the ASCs group ( injected into the gap), the GMs group (GMs injected into the gap) and the blank defect group (non-treated). At 2 and 4 weeks postoperatively, the healing tissue was harvested to evaluate the gross observation and scoring, biomechanical testing, histological staining and quantitative scoring. Gait analysis was performed over time. The 64 rats were randomly assigned into 4 groups: (1) micro-unit group (ASCs+GMs) containing ASC (10 )-loaded 120 GMs in 60 μL DMEM; (2) cell control group (ASCs) containing 10 ASCs in 60 μL DMEM; (3) GM control group (GMs) containing 120 blank GMs in 60 μL DMEM; (4) blank defect group (Defect) containing 60 μL DMEM, which were injected into the defect sites. All animals were sacrificed at 2 and 4 weeks postsurgery (Table 1). In an in vitro study, GMs (from 126 μm to 348 μm) showed good porosities and a three-dimensional void structure with a good interpore connectivity of the micropores and exhibited excellent biocompatibility with ASCs. As the culture time elapsed, the extracellular matrix (ECM) secreted by ASCs encased the GMs, bound multiple microspheres together, and then formed active tendon tissue-engineering microunits. In animal experiments, the ASCs+GMs group and the ASCs group showed stimulatory effects on Achilles tendon healing. Moreover, the ASCs+GMs group was the best at improving the macroscopic appearance, histological morphology, Achilles functional index (AFI), and biomechanical properties of repair tissue without causing adverse immune reactions. Porous GMs were conducive to promoting cell proliferation and facilitating ECM secretion. The ASCs-GMs matrices showed an obvious therapeutic efficiency for Achilles tendon rupture in rats.

Recent evidence shows that carbon emissions in China are likely to peak ahead of 2030. However, the social and economic impacts of such an early carbon peak have rarely been assessed. Here we focus on the economic costs and health benefits of different carbon mitigation pathways, considering both possible socio-economic futures and varying ambitions of climate policies. We find that an early peak before 2030 in line with the 1.5 °C target could avoid ~118,000 and ~614,000 PM 2.5 attributable deaths under the Shared Socioeconomic Pathway 1, in 2030 and 2050, respectively. Under the 2 °C target, carbon mitigation costs could be more than offset by health co-benefits in 2050, bringing a net benefit of $393–$3,017 billion (in 2017 USD value). This study not only provides insight into potential health benefits of an early peak in China, but also suggests that similar benefits may result from more ambitious climate targets in other countries. Understanding benefits of carbon mitigation is an important impetus for governments to adopt more ambitious climate targets. Here, the authors show positive air quality and health co-benefits are possible if China’s CO 2 emissions peak before 2030.

Numerous global-scale land-cover datasets have greatly contributed to the study of global environmental change and the sustainable management of natural resources. However, land-cover datasets inevitably experience information loss because of the nature of the uncertainty in the interpretation of remote-sensing images. Therefore, analyzing the spatial consistency of multi-source land-cover datasets on the global scale is important to maintain the consistency of time and consider the effects of land-cover changes on spatial consistency. In this study, we assess the spatial consistency of five land-cover datasets, namely, GLC2000, CCI LC, MCD12, GLOBCOVER and GLCNMO, at the global and continental scales through climate and elevation partitions. The influencing factors of surface conditions and data producers on the spatial inconsistency are discussed. The results show that the global overall consistency of the five datasets ranges from 49.2% to 67.63%. The spatial consistency of Europe is high, and the multi-year value is 66.57%. In addition, the overall consistency in the EF climatic zone is very high, around 95%. The surface conditions and data producers affect the spatial consistency of land-cover datasets to different degrees. CCI LC and GLCNMO (2013) have the highest overall consistencies on the global scale, reaching 67.63%. Generally, the consistency of these five global land-cover datasets is relatively low, increasing the difficulty of satisfying the needs of high-precision land-surface-process simulations.

Recent studies show that international trade affects global distributions of air pollution and public health. Domestic interprovincial trade has similar effects within countries, but has not been comprehensively investigated previously. Here we link four models to evaluate the effects of both international exports and interprovincial trade on PM 2.5 pollution and public health across China. We show that 50–60% of China’s air pollutant emissions in 2007 were associated with goods and services consumed outside of the provinces where they were produced. Of an estimated 1.10 million premature deaths caused by PM 2.5 pollution throughout China, nearly 19% (208,500 deaths) are attributable to international exports. In contrast, interprovincial trade leads to improved air quality in developed coastal provinces with a net effect of 78,500 avoided deaths nationwide. However, both international export and interprovincial trade exacerbate the health burdens of air pollution in China’s less developed interior provinces. Our results reveal trade to be a critical but largely overlooked consideration in effective regional air quality planning for China. International and domestic interprovincial trade of China are entangled, but their health impacts have been treated separately in earlier studies. Here Wang. quantify the complex impacts of trade on public health across China within an integrative framework.

The COVID-19 pandemic continues to pose substantial challenges to achieving the Sustainable Development Goals (SDGs). Exploring systematic SDG strategies is urgently needed to aid recovery from the pandemic and reinvigorate global SDG actions. Based on available data and comprehensive analysis of the literature, this paper highlights ongoing challenges facing the SDGs, identifies the effects of COVID-19 on SDG progress, and proposes a systematic framework for promoting the achievement of SDGs in the post-pandemic era. Progress towards attaining the SDGs was already lagging behind even before the onset of the COVID-19 pandemic. Inequitable distribution of food–energy–water resources and environmental crises clearly threaten SDG implementation. Evidently, there are gaps between the vision for SDG realization and actual capacity that constrain national efforts. The turbulent geopolitical environment, spatial inequities, and trade-offs limit the effectiveness of SDG implementation. The global public health crisis and socio-economic downturn under COVID-19 have further impeded progress toward attaining the SDGs. Not only has the pandemic delayed SDG advancement in general, but it has also amplified spatial imbalances in achieving progress, undermined connectivity, and accentuated anti-globalization sentiment under lockdowns and geopolitical conflicts. Nevertheless, positive developments in technology and improvement in environmental conditions have also occurred. In reflecting on the overall situation globally, it is recommended that post-pandemic SDG actions adopt a “Classification–Coordination–Collaboration” framework. Classification facilitates both identification of the current development status and the urgency of SDG achievement aligned with national conditions. Coordination promotes domestic/international and inter-departmental synergy for short-term recovery as well as long-term development. Cooperation is key to strengthening economic exchanges, promoting technological innovation, and building a global culture of sustainable development that is essential if the endeavor of achieving the SDGs is to be successful. Systematic actions are urgently needed to get the SDG process back on track.

The streamflow of major global rivers changes under the influences of climate change and human activities and varies greatly in different regions. The Yellow River has undergone a dramatic shift during the last six decades. Its streamflow gradually dwindled away and even dried-up severely in the late 20th century, but in recent years it has recovered and remains stable. Comprehensive understanding of the river streamflow change and its driving forces promotes effective water resource management within this complex human-natural system. Here, we develop a runoff identity attribution approach to analyze 61 years of streamflow observations from the Yellow River. We find that between the 1950s and the 1980s, human water consumption contributed more than 90% to streamflow reduction, but from the 1970s onwards, land cover change became the major factor to decrease streamflow. Since 2000, government management schemes have prevented streamflow from declining further and guarantee its stability. Based on the analysis framework we propose, persistent droughts, which are related to abrupt streamflow abatement, may be the most uncontrollable factor in the future. A more resilient management system should be therefore built to grapple with the expected increased frequency of such extreme climate events in the future.

ContextConstructing a sustainable landscape pattern from the perspective of landscape sustainability is scientifically built on the clarification of the formation mechanisms of landscape services and their relationships. However, the trade-offs and synergies of landscape services have regional heterogeneity, and their influencing factors are largely unknown in polar ecosystem. The Qinghai–Tibet Plateau is a unique but fragile ecosystem, and its landscape services are vital components to the sustainability in this specific polar region.ObjectivesThis study sought to understand the landscape service relationships, their dynamics and influencing factors, and achieve a sustainable landscape management in the Qinghai–Tibet Plateau.MethodsIn this work, we evaluated the spatiotemporal distribution and relationships of multiple landscape services including soil retention (SR), water yield (WY), habitat quality (HQ), crop supply (CS) and livestock supply (LS). We further identified temperature, elevation, population size, land use and land cover (LULC) as influencing factors on landscape services relationships within specific landscape gradients.ResultsOur results show that: (1) SR, WY and HQ decreased significantly from the southeast to the northwest. (2) Regulating services-supporting services are mainly identified as synergies, and CS–HQ and CS–LS are manifested as trade-offs. (3) Geophysical factors (temperature, altitude) have impact on the distribution of CS and the trade-off and synergistic dynamics of WY–HQ, increased population size enhances CS–HQ trade-offs, while between supporting and regulating services show trade-offs in high-coverage grassland and unused land.ConclusionsThe quantitative assessment of landscape services and relationships provides the basis for sustainable landscape management in the context of national policies and climate change.

The performance of a hemispherical resonant gyroscope (HRG) is directly affected by the sphericity error of the thin-walled spherical shell of the hemispherical shell resonator (HSR). In the production process of the HSRs, high-speed, high-accuracy, and high-robustness requirements are necessary for evaluating sphericity errors. We designed a sphericity error evaluation method based on the minimum zone criterion with an adaptive number of subpopulations. The method utilizes the global optimal solution and the subpopulations’ optimal solution to guide the search, initializes the subpopulations through clustering, and dynamically eliminates inferior subpopulations. Simulation experiments demonstrate that the algorithm exhibits excellent evaluation accuracy when processing simulation datasets with different sphericity errors, radii, and numbers of sampling points. The uncertainty of the results reached the order of 10−9 mm. When processing up to 6000 simulation datasets, the algorithm’s solution deviation from the ideal sphericity error remained around −3 × 10−9 mm. And the sphericity error evaluation was completed within 1 s on average. Additionally, comparison experiments further confirmed the evaluation accuracy of the algorithm. In the HSR sample measurement experiments, our algorithm improved the sphericity error assessment accuracy of the HSR’s inner and outer contour sampling datasets by 17% and 4%, compared with the results given by the coordinate measuring machine. The experiment results demonstrated that the algorithm meets the requirements of sphericity error assessment in the manufacturing process of the HSRs and has the potential to be widely used in the future.