Search Results (2,526)

Near-surface air temperature (Tair) is critical for addressing urban challenges in China, particularly in the context of rapid urbanization and climate change. While many studies estimate Tair at a national scale, they typically provide only daily data (e.g., maximum and minimum Tair), with few focusing on sub-daily urban Tair at high spatial resolution. In this study, we integrated MODIS-based land surface temperature (LST) data with 18 auxiliary data from 2013 to 2023 to develop a Tair estimation model for major Chinese cities, using random forest algorithms across four diurnal and seasonal conditions: warm daytime, warm nighttime, cold daytime, and cold nighttime. Four model schemes were constructed and compared by combining different auxiliary data (time-related and space-related) with LST. Cross-validation results were found to show that space-related and time-related variables significantly affected the model performance. When all auxiliary data were used, the model performed best, with an average RMSE of 1.6 °C (R² = 0.96). The best performance was observed on warm nights with an RMSE of 1.47 °C (R² = 0.97). The importance assessment indicated that LST was the most important variable across all conditions, followed by specific humidity, and convective available potential energy. Space-related variables were more important under cold conditions (or nighttime) compared with warm conditions (or daytime), while time-related variables exhibited the opposite trend and were key to improving model accuracy in summer. Finally, two samples of Tair patterns in Beijing and the Pearl River Delta region were effectively estimated. Our study offered a novel method for estimating sub-daily Tair patterns using open-source data and revealed the impacts of predictive variables on Tair estimation, which has important implications for urban thermal environment research. Full article

The Paleogene Enping Formation in the Huizhou Sag, Pearl River Mouth Basin, has been identified as a key target for deep oil and gas exploration. However, research on the diagenesis of these deep reservoirs still remains limited. This study evaluated the role played by diagenetic processes on the reservoir quality of the Paleogene Enping Formation in the Huizhou Sag, Pearl River Mouth Basin, from braided river deltas to meandering river deltas. A core observation, thin section examination, cathode luminescence analysis, scanning electron microscopy, mercury penetration, porosity–permeability test, and other analytical methods were performed to analyze the diagenesis and its impact on the physical properties of the deep, low-permeability sandstone reservoirs in the Enping Formation within the study area. It was shown that the reservoir composition maturity of the Paleogene Enping Formation in Huizhou Sag is relatively high, and the reservoir space is dominated by dissolved pores, accounting for more than 48.2%. The deep and ultra-deep clastic reservoirs are typically characterized by “low porosity, low permeability, and strong heterogeneity”. In particular, the reservoir space of the deep, low-permeability reservoir of the Enping Formation is significantly affected by diagenesis in which mechanical compaction notably altered the porosity of the Enping Formation reservoir, with a reduction in pore volume ranging from 12.5 to 27.2% (average 18.9%); cementation usually enhances pore reduction by between 2.1 and 28.7% (average 11.7%), while dissolution has resulted in an increase in pore volume ranging from 1.4 to 25.6% (average 10.1%). A further analysis revealed that the deep reservoir type in this region is characterized by “densification”, as evidenced by the correlation between reservoir porosity–permeability evolution and hydrocarbon accumulation. Full article

Slow-moving landslides are often precursors of catastrophic failure, posing a major threat to human life and property safety. Interferometric synthetic aperture radar (InSAR) has become a crucial tool for investigating slow-moving landslides hazard because of its high-precision detection capability for slow surface deformation. However, landslides usually occur in alpine canyon areas and vegetation coverage areas where InSAR measurements are still limited by temporal and spatial decorrelation and atmospheric influences. In addition, there are several difficulties in monitoring the multiscale characterization of landslides from the InSAR results. To address this issue, this paper proposes a novel method for slow-moving landslide hazard assessment in low-coherence regions. A window-based atmosphere correction method is designed to highlight the surface deformation signals of InSAR results in low-coherence regions and reduce false alarms in landslide hazard assessment. Then, the deformation annual velocity rate map, coherence map and DEM are used to construct the InSAR sample set. A landslide hazard assessment model named Landslide-SE-Unilab is subsequently proposed. The global–local relationship aggregation structure is designed to capture the spatial relationship between local pixel-level deformation features and global landslides, which can reduce the number of missed assessments and false assessments of small-scale landslides. Additionally, a squeeze-and-excitation network is embedded to adjust the weight relationship between the features of each channel in order to enhance the performance of network evaluation. The method was evaluated in Kangding city and the Jinsha River Valley in the Hengduan Mountains, where a total of 778 potential landslides with slow deformation were identified. The effectiveness and accuracy of this approach for low-coherence landslide hazard assessment are demonstrated through comparisons with optical images and previous research findings, as well as evaluations via time-series deformation results. Full article

This study explores the “gap reduction effect” of new infrastructure on regional economic disparities, investigating both its impact and underlying mechanisms in narrowing these gaps. Focusing on 41 prefecture-level cities within the Yangtze River Delta, this paper constructs an evaluation index system for new infrastructure and quantitatively measures its development. The results reveal that while the overall level of new infrastructure in the region is relatively advanced, there are notable disparities between cities. The benchmark analysis demonstrates a significant positive relationship between the development of new infrastructure and the promotion of coordinated regional economic growth. New infrastructure fosters industrial and spatial integration through three primary pathways: enhancing the efficiency of the resource allocation within regions, driving industrial upgrades, and facilitating the diffusion of technological innovations. These factors collectively contribute to the balanced and coordinated development of regional economies. Further investigation uncovers a threshold effect, suggesting that the level of digitalization plays a crucial role in facilitating the regional economic integration catalyzed by new infrastructure. Full article

Seabed liquefaction induced by wave loading poses considerable risks to marine structures and requires careful consideration in marine engineering design and construction. Traditional methods relying on statistical wave parameters for analyzing random waves often underestimate the potential for seabed liquefaction. To address this underestimation, the present study employs field observations and numerical simulations to examine wave characteristics and liquefaction distribution across various wave return periods in the Chengdao Sea area of the Yellow River subaqueous delta. The research results indicated that the wave decay phase exhibited a higher liquefaction potential than the growth phase, primarily because of the prevalence of low-frequency swell waves. The China Hydrological Code Spectrum (CHC Spectrum) effectively captured the wave characteristics in the study area, with parameterization grounded in measured data. The poro-elastic wave–sediment interaction model further elucidated the liquefaction distribution under extreme wave conditions, revealing a maximum liquefaction depth exceeding 3 m and prominent liquefaction zones at water depths of 5–15 m. Notably, seabed properties emerged as a critical factor for liquefaction and overshadowed water depth, with non-liquefaction zones occurring at water depths of less than 15 m at high clay content, highlighting the general liquefaction risk of silty seabed. This study enhances understanding of the seabed liquefaction process and offers valuable insights into engineering safety. Full article

This study assessed heavy metal contamination in industrial solid waste (S1, S2, S3, and S4) from the Yangtze River Delta region, employing nine risk assessment methods including total content indices (e.g., Igeo, CF) and speciation indices (e.g., ICF, GCF). Four types of industrial solid waste not classified as hazardous but containing heavy metals were analyzed. Key findings revealed significant variability in risk assessments based on chemical speciation versus total content. For example, while S1, S3, and S4 exceeded background levels, S4 showed higher mobility of Pb, Cr (VI), Cu, Ni, and As despite lower overall content. Elements like Cd and Cr (VI) exhibited discrepancies between total content and speciation-based assessments due to low background values and high toxicity. Multi-element indices (DC, RI) indicated higher pollution degrees compared to speciation indices (GCF, GRI). These results underscore the need for integrating multiple assessment methods to accurately evaluate environmental risks in judicial practices. Full article

Coastal saline cropland ecosystems are becoming increasingly vital for food security in China, driven by the decline in arable land and the growing demand for resource-intensive diets. Although developing and utilizing saline land can boost productivity, it also impacts greenhouse gas (GHG) emissions. This study uses the Yellow River Delta as a case study to analyze the spatial-temporal patterns of carbon footprints in saline croplands from 2001 to 2020 and their correlations with climate factors, cropland management scale, and agricultural mechanization. The results reveal that agricultural production in this region is characterized by high inputs, emissions, and outputs, with carbon emission efficiency improving significantly due to a reduction in net carbon emissions. Major sources of carbon emissions include electricity, chemical nitrogen fertilizers, nitrogen input, and straw return, which together account for 65.06% of total emissions. Based on these findings, three key principles have been proposed for policy recommendations to enhance carbon emission efficiency. First, adopt tailored strategies for regions with different salinization levels. Second, strengthen cropland drainage infrastructure to mitigate the adverse effects of heavy rainfall. Third, expand the scale of cropland management through land transfers and promote agricultural mechanization. These insights offer valuable guidance for mitigating GHG emissions in coastal saline cropland ecosystems. Full article

Carbon fiber reinforced epoxy resin composites (CFRP) demonstrate superior wear resistance and fatigue durability, which are anticipated to markedly enhance the service life of structures under complex conditions. In the present paper, the friction behaviors and wear mechanisms of CFRP under different applied loads, sliding speeds, service temperatures, and water lubrication were studied and analyzed in detail. The results indicated that the tribological properties of CFRP were predominantly influenced by the applied loads, as the tangential displacement generated significant shear stress at the interface of the friction pair. Serviced temperature was the next most impactful factor, while the influence of water lubrication remained minimal. Moreover, when subjected to a load of 2000 g, the wear rate and scratch width of the samples exhibited increases of 158% and 113%, respectively, compared to those loaded with 500 g. This observed escalation in wear characteristics can be attributed to irreversible debonding damage at the fiber/resin interface, leading to severe delamination wear. At elevated temperatures of 100 °C and 120 °C, the wear rate of CFRP increased by 75% and 112% compared to that at room temperature. This augmentation in wear was attributed to the transition of the epoxy resin from a glassy to an elastic state, which facilitated enhanced fatigue wear. Furthermore, both sliding speed and water lubrication displayed a negligible influence on the friction coefficient of CFRP, particularly under water lubrication conditions at 60 °C, where the friction coefficient was only 15%. This was because the lubricant properties and thermal management provided by the water molecules, which mitigated the frictional interactions, led to only minor abrasive wear. In contrast, the wear rate of CFRP at a sliding speed of 120 mm/s was found to be 74% greater than that observed at 60 mm/s. This significant increase can be attributed to the disparity in sliding rates, which induced uncoordinated deformation in the surface and subsurface of the CFRP, resulting in adhesive wear. Full article

The efficiency of scientific and technological innovation in universities is strongly influenced by both institutional structures and policies. However, existing research predominantly emphasizes the role of internal factors—such as resource allocation, management efficiency, personnel systems within universities, and education-sector policies—on innovation efficiency. This focus often overlooks the significant impact of regional factors on innovation outcomes. This study compares and analyzes the scientific and technological innovation efficiency of universities, growth rates, sources of inefficiency, inter-regional disparities, and intra-regional differences between universities in three strategically important regions in China, namely the Yangtze River Delta, the Pearl River Delta, and the Beijing–Tianjin–Hebei region, based on their respective regional planning from 2007 to 2017. Additionally, it employs the Tobit model to explore the pathways to improve the scientific and technological innovation efficiency of universities within these three major strategic regions. This study finds that the implementation of targeted regional policies significantly enhances the efficiency of scientific and technological innovation in Chinese universities. Furthermore, it reveals that this positive impact also exhibits differences between universities and regions. The promotion effect of targeted regional policies on the efficiency of scientific and technological innovation in universities shows a high degree of similarity. In more developed cities, however, the scientific and technological innovation efficiency of universities tends to be lower. Both the Yangtze River Delta and the Pearl River Delta regions within the three major strategic areas are significantly affected by the negative impact of financial assets, while the Beijing–Tianjin–Hebei region, although affected negatively, is not significant. Moreover, this study uncovers that population density and fixed assets also serve as factors that can enhance the scientific and technological innovation efficiency of universities. Full article

In the expanding landscape of biomedical literature, numerous latent associations outlined in scholarly papers await discovery and integration into biomedical databases. Biomedical Natural Language Processing (NLP) research focuses on automating knowledge extraction and mining from this literature, particularly emphasizing the essential task of Relation Extraction (RE). However, existing models have limitations, mainly in their applicability to partial datasets for RE tasks. Moreover, conventional models often treat RE as a binary classification challenge, which proves suboptimal given the diverse relationships, including intricate ones like similarity and hierarchy, present in the RE dataset. These limitations are exacerbated by the models’ inability to capture word-level positional nuances and sentence-level language features. In response to these challenges, we present a novel RE model called BicapBert. This model integrates neural networks and capsule networks, enhancing them with hybrid knowledge graph embeddings to extract relevant features. BicapBert utilizes PubMedBERT and capsule networks to extract word-level positional and sentence-level language features. It further captures knowledge features from a biomedical knowledge graph, integrating them with the aforementioned linguistic features. The amalgamated information is then input into a multi-layer perceptron, culminating in results derived through a softmax classifier. Experimental evaluations on three extensive RE task datasets showcase the state-of-the-art performance of our proposed model. Additionally, we validate the model’s efficacy on three randomly selected biomedical datasets for various tasks, further affirming its superiority. Full article

Ice jamming is the primary mechanism that can generate overland flooding and recharge the isolated basins of the Peace–Athabasca Delta (PAD), a valuable ecosystem of international importance and the ancient homeland of the Indigenous Peoples of the region. Focusing on the regulated Peace River and the Peace Sector of the delta, which has been experiencing a drying trend in between rare ice-jam floods over the last ~50 years, this study describes recent notable breakup events, associated observational data, and numerical applications to determine river discharge during the breakup events. Synthesis and interpretation of this material provide a new physical understanding that can inform the ongoing development of a protocol for strategic flow releases toward enhancing basin recharge in years when major ice jams are likely to form near the PAD. Additionally, several recommendations are made for future monitoring activities and improvements in proposed antecedent criteria for early identification of “promising” breakup events. Full article

The human gastrointestinal microbiota plays a vital role in maintaining host health and preventing diseases, prompting the creation of simulators to replicate this intricate system. The Simulator of the Human Intestinal Microbial Ecosystem (SHIME^®), a multicompartment dynamic simulator, has emerged as a pivotal in vitro model for studying the interactions and interferences within the human gut microbiota. The continuous and real-time monitoring hallmarks, along with the programmatically flexible setup, bestow SHIME^® with the ability to mimic the entire human intestinal ecosystem with high dynamics and stability, allowing the evaluation of various treatments on the bowel microbiota in a controlled environment. This review outlines recent developments in SHIME^® systems, including the M-SHIME^®, Twin-SHIME^®, Triple-SHIME^®, and Toddle SHIME^® models, highlighting their applications in the fields of food and nutritional science, drug development, gut health research, and traditional Chinese medicine. Additionally, the prospect of SHIME^® integrating with other advanced technologies is also discussed. The findings underscore the versatility of SHIME^® technology, demonstrating its significant contributions to current gut ecosystem research and its potential for future innovation in microbiome-related fields. Full article

Eliminating poverty, reducing inequality, and achieving balanced development are one of the United Nations Sustainable Development Goals. Objectively and accurately measuring regional economic vitality and development equilibrium is a pressing scientific issue that needs to be addressed in order to achieve common prosperity. Nighttime light (NTL) remote sensing data have been proven to be a good proxy variable for socio-economic development, and are widely used due to their advantages of convenient access and wide spatial coverage. Based on multi-source data, this study constructs an Economic Development Index (EDI) that comprehensively reflects regional economic vitality from two aspects, economic quality and development potential, combines the Nighttime Light Development Index (NLDI) as the evaluation indicators to measure the economic vitality and development equilibrium, analyzes the economic vitality and development equilibrium of 300 district and county units in China’s three major urban agglomerations from 2000 to 2020 and their temporal and spatial variation characteristics, and discusses the connotation of EDI and its availability. The results show the following: (1) From 2000 to 2020, the average growth rate of EDI in China’s three major urban agglomerations reached 36.32%, while the average decrease rate of NLDI reached 38.75%; both economic vitality and the development equilibrium have been continuously enhanced. Among them, the Yangtze River Delta (YRD) urban agglomeration experienced the fastest economic growth, while the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) exhibited the strongest economic strength. (2) Both economic vitality and the development equilibrium in these three urban agglomerations exhibited distinct spatial agglomeration characteristics, namely center-surrounding distribution, coastal–inland distribution, and radial belt–pole distribution, respectively. (3) Over the past two decades, the economic development of these three urban agglomerations has progressed towards the pattern of regional coordinated development, pole-driven development and urban–rural integrated development. The research results can provide new research perspectives and scientific support for promoting regional balanced development, achieving sustainable development goals, and reducing inequality. Full article

Estuaries and deltas hold significant socioeconomic importance and immense ecological value due to their dynamic geomorphic processes and unique geographical advantages. However, in recent decades, delta recession and the instability of river regimes have become global challenges, driven by intensive human interventions in upstream river basins and local regions. This study examines the South Branch of the Changjiang Estuary as a typical case to investigate its morphological evolution over the past decades and project future trends, offering suitable solutions to enhance the river regime stability. Analysis of bathymetric data reveals substantial channel–shoal adjustments in the South Branch from 1958 to 2016, characterized by significant erosion and deposition on a decadal scale. After 1997, reduced fluvial sediment supply has led to widespread erosion in the South Branch. Further disturbances at the Baimao Shoal and Biandan Shoal have exacerbated the instability of the river regime. Numerical predictions indicate continued erosion in the South Branch over the next 20 years, accompanied by further channel–shoal pattern adjustments. Hydrodynamic modeling of proposed measures demonstrates an improved flow ratio for the North Baimao Shoal Channel, contributing to enhanced channel–shoal system stability. These integrated governance measures have been incorporated into the latest renovation plan for the Changjiang Estuary. The findings provide valuable scientific guidance for the comprehensive management of the Changjiang Estuary and offer insights applicable to other large estuaries facing similar challenges. Full article

Soil erosion is one of the causes of ecosystem fragility in the Yellow River Delta. Plant roots can improve soil shear strength and effectively prevent soil erosion. However, there are no studies on soil shear strength in the Yellow River Delta. In this study, Phragmites australis (PA) root–soil composites with different root area ratios (RARs) (RARs = 0%, 0.06%, 0.14%, 0.17%, 0.19%, 0.24%, 0.36%) were prototypically sampled from the Yellow River Delta. Direct shear tests of root–soil composites were performed by a ZJ-type (three-speed) strain-controlled direct shear apparatus. The normal stresses were 25, 50, 100, and 200 kPa, and the shear rate was 1.2 mm/min. The results showed that PA roots significantly increased soil shear strength and cohesion with maximum growth rates of 219.0% and 440.1%, respectively. An optimal RAR of 0.14% in the range of 0~0.36% maximized the shear strength and cohesion of the root–soil composites. The internal friction angles of root–soil composites with different RARs did not differ significantly from those of the rootless soil. This indicates that the increase in shear strength was mainly due to an increase in cohesion. In addition, overall shear failure was the primary failure mode of rootless soil, with the roots pulled out of the soil in the root–soil composite failure mode. It is important to note that the root is deflected during shear in the direction opposite to the direction of the shear stress. These findings deepen our understanding of the effect of vegetation roots on soil shear characteristics and provide a scientific basis for the protection of bank slopes, soil and water conservation, and vegetation restoration in the Yellow River Delta. Full article