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In the context of increasing applications of various nanomaterials in construction, this work reviews the renewed knowledge of nanotechnology in cement-based materials, focusing on the relevant papers published over the last decade. The addition of nanomaterials in cement-based materials, associated with their dispersion in cement composites, is explored to evaluate their effects on the resistance of cement-based materials to physical deteriorations, chemical deteriorations, and rebar corrosion. This review also examines the proposed nanoscale modeling of interactions between admixed nanomaterials and cement hydration products. At last, the recent progress of advanced characterization that employs techniques to characterize the properties of cement-based materials at the nanoscale is summarized.

To determine the relationship between underground mining, groundwater storage change, and surface deformation, we first used two sets of ENVISAT data and one set of Sentinel-1A data to obtain surface deformation in eastern Xuzhou coalfield based on the temporarily coherent point interferometric synthetic aperture radar (TCPInSAR) technique. By comparison with underground mining activities, it indicated that the surface subsidence is mainly related to mine exploitation and residual subsidence in the goaf, while the surface uplift is mainly related to restoration of the groundwater level. The average groundwater storage change in the eastern Xuzhou coalfield from January 2005 to June 2017 was obtained through the Gravity Recovery and Climate Experiment (GRACE) data, and the results indicated that the groundwater storage changed nonlinearly with time. The reliability of the groundwater monitoring results was qualitatively validated by using measured well data from April 2009 to April 2010. Combining with time of mining and mine closing analysis, groundwater storage change within the research area had a strong correlation with drainage activity of underground mining. An analysis was finally conducted on the surface deformation and the groundwater storage change within the corresponding time. The results indicated that the groundwater storage variation in the research area has a great influence on the surface deformation after the mine closed.

The built environment is an important determinant of travel demand and mode choice. Studying the relationship between the built environment and transportation usage can support and assist traffic policy interventions. Previous studies often assumed that this relationship is linear; however, the impact of the built environment on non-motorized travel efficiency may be more complex than the typically modeled linear relationships. This paper focuses on the core area of Chengguan District in Lanzhou City, utilizing multi-source big data including POI, OpenStreetMap, street view images, and built environment data. Using ArcGIS spatial analysis tools combined with the Extreme Gradient Boosting (XGBoost) model, we analyze the non-linear influence mechanisms and threshold effects of the built environment on non-motorized travel efficiency and establish a ranking of the relative importance of all built environment factors. The results indicate that factors such as the branch road/street, land-use mix, land-use density, neighborhood entrance/exit density, bus station density, and dead-end-roads density are key influences on non-motorized travel efficiency. Additionally, based on the non-linear thresholds presented in the partial dependence plots for built environment factors, this paper proposes optimization strategies for small-scale road network patterns, mixed land use, and bus-friendly environments, providing effective threshold ranges and decision-making references for urban planning and traffic management.

BackgroundIdentifying past temporal trends in non-alcoholic steatohepatitis (NASH)-associated liver cancer (NALC) can increase public awareness of the disease and facilitate future policy development.MethodsAnnual deaths and age-standardized death rates (ASDR) for NALC from 1990 to 2019 were collected from the Global Burden of Disease (GBD) 2019 study. The long-term trend and the critical inflection of mortality of NALC were detected by Joinpoint analysis. Age–period–cohort analysis was employed to evaluate the effects of age, period, and cohort. Last, decomposition analysis was used to reveal the aging and population growth effects for NALC burden.ResultsBetween 1990 and 2019, the ASDR of NALC witnessed an overall declining trend on a global scale, with a decrease in females and a stable trend in males. However, the global ASDR demonstrated a significant upward trend from 2010 to 2019. Southern sub-Saharan Africa and Southeast Asia have the highest NALC burdens, while high socio-demographic index (SDI) region experienced the fastest escalation of NALC burdens over 30 years. The decomposition analysis revealed that population growth and aging were the primary catalysts behind the increase in global NALC deaths. Age–period–cohort analyses showed that NALC mortality declined the fastest among females aged 40–45 years in high SDI region, accompanied by a deteriorating period effect trend during the period of 2010–2019.ConclusionThe global absolute deaths and ASDR of NALC have witnessed a rise in the past decade, with populations exhibiting considerable disparities based on sex, age, and region. Population growth, aging, and metabolism-related factors were the main factors behind the increase in global NALC deaths.

As the Zhurong rover landed on the surface of Mars in 2021, it began a months-long collection of Mars data. Equipped with highly sensitive sensors, Zhurong is capable of being a meteorological station at the surface of Mars. The Mars Climate Station, one of the onboard sensors with high sensitivity, helps the Tianwen-1 lander to collect meteorological data at the Martian surface, via which the air temperature, atmospheric pressure, wind speed and direction are measured. In this paper, we present results of surface pressure, air temperature and wind data from the Mars Climate Station at Zhurong’s landing site. The data is collected in 176 solar days out of the entire rover’s mission time, 325 solar days. We use a trigonometric function to fit the relationship between the solar longitude (Ls) and the pressure, after which we compare the results with those of Viking I. Our analysis of the temperature shows that seasonal evolution is similar to the patterns concluded in previous Mars missions at different landing sites. We discover that wind speed appears the maximum in early summer near Zhurong’s landing site, and analyze the occurrence of dust storms by combining the data of wind and temperature. Our results provide some evidence of the seasonal changes in meteorological pattern at Tianwen-1’s landing site, south of Utopia Planitia. With the mission ongoing further, more results are expected in the future.

A large number of mines have been closed due to resource depletion, failure to meet safety production requirements, and other reasons. To effectively ensure the safety of the ecological environment above these closed mines along with the safety of engineering construction, it is necessary to monitor the secondary deformation of closed mines. Based on TerraSAR-X, Sentinel-1A data, and InSAR technology, this study obtained high-density secondary surface deformation data on the Jiahe Coal Mine and Pangzhuang Coal Mine in the western Xuzhou area. Combining mining geological data, we analyzed the spatiotemporal variation patterns and mechanisms of secondary deformation in multi-seam mining of closed mines. It was found that when mining multiple seams involves large interlayer spacing, the secondary deformation pattern shows a “W” shape. In this situation, the deformation can be divided into five stages: subsidence, uplift, re-subsidence, re-uplift, and relative stability. This study provides technical support for the evaluation and prevention of secondary deformation hazards in closed mines.

Safety concerns are progressively emerging regarding the adoption of Unmanned Aircraft Systems (UASs) in diverse civil applications, particularly within the booming air transportation system, such as in Advanced Air Mobility. The outcomes of risk assessment determine operation authorization and mitigation strategies. However, civil UAS operations bring novel safety issues distinct from traditional aviation, like ground impact risk, etc. Existing studies vary in their risk definitions, modelling mechanisms, and objectives. There remains an incomplete gap of challenges, opportunities, and future efforts needed to collaboratively address diverse safety risks. This paper undertakes a comprehensive review of the literature in the domain, providing a summative understanding of the risk assessment of civil UAS operations. Specifically, four basic modelling approaches utilized commonly are identified comprising the safety risk management process, causal model, collision risk model, and ground risk model. Then, this paper reviews the state of the art in each category and explores the practical applications they contribute to, the support offered to participants from multiple stakeholders, and the primary technical challenges encountered. Moreover, potential directions for future work are outlined based on the high-level common problems. We believe that this review from a holistic perspective contributes towards better implementation of risk assessment in civil UAS operations, thus facilitating safe integration into the airspace system.

In recent years, the prolonged exploitation of coal resources has led to the depletion of coal reserves in some mining areas, resulting in the closure of certain mines worldwide. After mine closures, the fractured rock masses in abandoned mine cavities undergo weathering and degradation due to factors such as stress and groundwater, leading to reduced strength. This change alters the stress distribution and load-bearing capacity of the fractured rock within the abandoned voids, resulting in secondary or multiple deformations on the surface, which pose significant potential threats to surface infrastructure and public safety. Research into the mechanisms, patterns, and predictive methods of secondary surface subsidence in closed mines is thus of great theoretical and practical significance. Based on a literature review and practical monitoring experience in closed mine sites, this study systematically examines and analyzes the current state of secondary surface subsidence monitoring methods, formation mechanisms, spatiotemporal distribution patterns, and prediction methods in closed mines, as well as existing challenges. Initially, we compare the advantages and limitations of conventional surface deformation monitoring techniques with remote sensing techniques, emphasizing the benefits and issues of using InSAR technology for monitoring surface subsidence in closed mines. Next, by reviewing extensive data, we analyze the formation mechanisms and spatiotemporal evolution of secondary surface subsidence in closed mines. Building on this analysis, we discuss numerical and analytical methods for predicting secondary surface subsidence mechanisms in closed mines, evaluating the strengths and weaknesses of each approach. Predictive models for surface subsidence and uplift phases in the longwall collapse method are presented based on the constitutive relationships of fractured rock masses. Finally, the study highlights that the mechanisms and patterns of surface subsidence in closed mines represent a highly complex physical–mechanical process involving geological mining environments, fractured rock structures, constitutive relations, deformation characteristics, hydro-mechanical interactions, and groundwater dynamics, underscoring the need for further in-depth research.

Mining goafs can cause many hazards, such as burst water, spontaneous combustion of coal seams, surface collapse, etc. In this paper, a feature-points-based method for the efficient location of mining goafs is proposed. Different interferometric synthetic aperture radar (DInSAR) is used to monitor the subsidence basin caused by mining. Using the principles of the probability integral method (PIM), the inflection points and the boundary points of the basin monitored by DInSAR are determined and used as feature points to locate the goaf. In this paper, the necessity of locating goafs and the traditional methods used for this task are discussed first. Then, the results of verifying the proposed method by both a simulation experiment and real data experiment are presented. Six RADARSAT-2 images from 13th October 2015 to 5th March 2016 were used to acquire the subsidence basin caused by the 15235 working faces of the Jiulong mining area. The average relative errors of the simulation experiment and real data experiment were about 6.43% and 12.59%, respectively. The average absolute errors of the simulation experiment and real data experiment were about 28 m and 38 m, respectively. In the final part of this paper, the error sources are discussed to illustrate the factors that can affect the location result.

What are the main findings? * A time-progressive framework based on panels with different cessation times reconstructs the full life-cycle evolution of surface deformation in old goafs. * A complete life-cycle evolution pattern of surface deformation in strip pillar mining old goafs is identified as “residual subsidence—stage-wise stabilization—secondary subsidence—deformation stabilization”, with a total duration of 18 years. A time-progressive framework based on panels with different cessation times reconstructs the full life-cycle evolution of surface deformation in old goafs. A complete life-cycle evolution pattern of surface deformation in strip pillar mining old goafs is identified as “residual subsidence—stage-wise stabilization—secondary subsidence—deformation stabilization”, with a total duration of 18 years. What are the implications of the main findings? * A time-progressive analysis framework based on panels with different cessation times provides a novel strategy to reconstruct long-term deformation processes without full historical observations. * The stacking ensemble model (SVR–Huber–LightGBM) enables accurate prediction of deformation trends, providing methodological support for long-term subsidence trend forecasting and risk management. A time-progressive analysis framework based on panels with different cessation times provides a novel strategy to reconstruct long-term deformation processes without full historical observations. The stacking ensemble model (SVR–Huber–LightGBM) enables accurate prediction of deformation trends, providing methodological support for long-term subsidence trend forecasting and risk management. Surface deformation induced by underground coal mining shows a clear time-lag effect, with persistent residual deformation in old goafs under strip pillar mining conditions, drawing significant research attention. This study focuses on the Gucheng mining area, where 210 Sentinel-1A SAR images (May 2017–January 2025) were processed using SBAS-InSAR to derive 7.5 years of time-series surface deformation. Based on these results, five strip pillar mining panels with different cessation times were selected. Through comparative analysis, a time-progressive sequence was constructed to identify post-mining residual deformation and stage-wise stabilization characteristics, and to reveal long-term deformation responses occurring years after cessation, thereby reconstructing the long-term evolution of surface deformation in old goafs. Furthermore, a stacking ensemble prediction model was developed to predict subsidence trends at representative feature points. The results indicate that subsidence mainly ranges from −20 to −10 mm/a, with a maximum of approximately −64 mm/a and cumulative subsidence of about −515 mm. Surface deformation follows a stage-wise evolution pattern of “residual subsidence—stage-wise stabilization—secondary subsidence—deformation stabilization”, with durations of approximately 2, 2, and 14 years, respectively, and overall stabilization occurring after approximately 18 years. The predicted results from the stacking model are highly consistent with the SBAS-InSAR monitoring data and can reliably describe the evolution trend of surface subsidence. The findings provide important evidence for understanding long-term surface deformation in old goafs of strip pillar mining areas.