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Nickel–iron slag, a byproduct of industrial processes in China with an annual production exceeding 400,000 tons, is considered an industrial waste material. This study focuses on the rational utilization of nickel–iron slag by investigating its mechanical properties and road performance as a roadbed fill material. Initially, a detailed analysis of the grading curve of pure nickel–iron slag was conducted, leading to the proposal of various modification schemes for nickel–iron slag. Subsequently, static triaxial tests were performed on nickel–iron slag-clay mixtures to explore the impact of different factors on the stress–strain curve of nickel–iron slag-modified soil. Utilizing these discoveries, a formula for the molar Coulomb shear strength of nickel–iron slag-modified soil was derived. In addition, a numerical simulation study of a nickel–iron slag-reinforced embankment was conducted, integrating field tests. This aimed to investigate the variations in the compression layer sedimentation-thickness ratio and settlement factor of nickel–iron slag-modified soil reinforced embankment under different filling heights and slope rates. The results informed the development of a prediction model for the settlement ratio of nickel–iron slag-modified soil-reinforced embankment. Key findings indicate that pure nickel–iron slag exhibits poorly graded gravel sand characteristics, and optimal gradation is achieved when clay doping ranges from 30% to 40%. As the clay content increases, the stress–strain curve of nickel–iron slag-clay transitions from strain-hardening to strain-softening. Furthermore, the stress–strain curve of nickel–iron slag-cement-clay exhibits strain-softening, and the shear strength fitting formula demonstrates high computational accuracy with a small error range. Numerical simulations reveal that the sink-thickness ratio and settlement factor are minimally affected by the slope rate. The sink-thickness ratio increases with the elevation of filling height, while the settlement factor fluctuates within a small range. The proposed sink-thickness ratio prediction model exhibits high accuracy and strong generalization capabilities. This comprehensive study provides valuable insights into the efficient utilization of nickel–iron slag in construction and road engineering. • Nickel–iron slag, a major industrial waste in China, can be efficiently repurposed for roadbed fill material. • Optimal gradation is achieved with 30%–40% clay doping, impacting the stress–strain curve of nickel–iron slag. • Study unveils formula for molar Coulomb strength of nickel–iron slag. • Numerical simulations reveal minimal impact of slope rate on sink-thickness ratio in reinforced embankments. • Accurate prediction model for settlement in nickel–iron slag-modified soil. [ABSTRACT FROM AUTHOR]

A new grey incidence model, called the grey dynamic trend incidence model GDTIM(t) , is designed to broaden the scope of this type of model. In particular, a degree of the grey trend incidence, an array and a matrix of the grey dynamic trend incidence are obtained from two data sets which include both time series and panel data, by using the GDTIM(t) model. The new model includes two parts. One component is a judgment factor which is used to determine whether the trend of two sequences is the same or different. The other part is a measurement factor for calculating the absolute degree of grey trend incidence. Then, the properties of the model GDTIM(t) are discussed. Two extended models based on GDTIM(t) , which are utilized for application to panel data, are established. One is for calculating the connection between indicators, and the other one is for different objects. The new model is used to dynamically analyze factors connected to smog weather in south Jiangsu province. [ABSTRACT FROM AUTHOR]

Dissolved black carbon (DBC), the water-soluble component of black carbon, which is formed by incomplete combustion of fossil fuels or biochar, takes up about 10% of dissolved organic matter (DOM) in river water. However, the distribution of DBC in water environment especially in source water is not clear and as an important component of DOM, whether DBC can produce disinfection byproducts (DBPs) like other DOM during disinfection remains unknown. In this study, the DBC concentrations in seventeen source water samples from East China were measured. The concentrations of DBC in the source water samples ranged from 60 to 270 μg/L, which were positively correlated with UV 254 absorbance and chemical oxygen demand. The levels of DBC in wet season were higher than that in dry season. The average concentrations of DBC in different types of source water samples followed the order of reservoir > canal > lake > river. DBC could only be removed by 20% during the simulated coagulation, and further generate different categories of DBPs during chlorination, among which the concentrations of haloacetic acids (HAA) were the highest. The results indicated that DBC widely distributes in source water and is an important precursor of HAAs and THMs during chlorination. [Display omitted] ● DBC derived from biochar was used for the QA/QC of benzene polycarboxylic acid method. ● DBC was widely spread in source water and significantly correlated with UV 254. ● DBC could generate higher concentration of DBPs than SRNOM during chlorination. [ABSTRACT FROM AUTHOR]

Abstract: Groundwater contamination risk assessment is an effective tool for groundwater management. Most existing risk assessment methods only consider the basic contamination process based upon evaluations of hazards and aquifer vulnerability. In view of groundwater exploitation potentiality, including the value of contamination-threatened groundwater could provide relatively objective and targeted results to aid in decision making. This study describes a groundwater contamination risk assessment method that integrates hazards, intrinsic vulnerability and groundwater value. The hazard harmfulness was evaluated by quantifying contaminant properties and infiltrating contaminant load, the intrinsic aquifer vulnerability was evaluated using a modified DRASTIC model and the groundwater value was evaluated based on groundwater quality and aquifer storage. Two groundwater contamination risk maps were produced by combining the above factors: a basic risk map and a value-weighted risk map. The basic risk map was produced by overlaying the hazard map and the intrinsic vulnerability map. The value-weighted risk map was produced by overlaying the basic risk map and the groundwater value map. Relevant validation was completed by contaminant distributions and site investigation. Using Beijing Plain, China, as an example, thematic maps of the three factors and the two risks were generated. The thematic maps suggested that landfills, gas stations and oil depots, and industrial areas were the most harmful potential contamination sources. The western and northern parts of the plain were the most vulnerable areas and had the highest groundwater value. Additionally, both the basic and value-weighted risk classes in the western and northern parts of the plain were the highest, indicating that these regions should deserve the priority of concern. Thematic maps should be updated regularly because of the dynamic characteristics of hazards. Subjectivity and validation means in assessing the vulnerability result were also discussed. In addition, GIS technology was essential in completing the assessment work. [Copyright &y& Elsevier]

Abstract: Futures trading is the core of futures business, and it is considered as one of the typical complex systems. To investigate the complexity of futures trading, we employ the analytical method of complex networks. First, we use real trading records from the Shanghai Futures Exchange to construct futures trading networks, in which nodes are trading participants, and two nodes have a common edge if the two corresponding investors appear simultaneously in at least one trading record as a purchaser and a seller, respectively. Then, we conduct a comprehensive statistical analysis on the constructed futures trading networks. Empirical results show that the futures trading networks exhibit features such as scale-free behavior with interesting odd–even-degree divergence in low-degree regions, small-world effect, hierarchical organization, power-law betweenness distribution, disassortative mixing, and shrinkage of both the average path length and the diameter as network size increases. To the best of our knowledge, this is the first work that uses real data to study futures trading networks, and we argue that the research results can shed light on the nature of real futures business. [ABSTRACT FROM AUTHOR]

• Four lithofacies with different diagenetic alteration characteristics are identified. • Compaction is the most significant reason for the decrease in primary porosity.Compaction is the most significant reason for the decrease in primary porosity. • Carbonate cement is concentrated near the top and base of Lithofacies i and ii. • The presence of two types of illite causes a reduction in reservoir quality. • Five diagenetic patterns are identified to affect reservoir qualities. The Ordos Basin is rich in tight oil resources, and the Upper Triassic Yanchang Formation tight oil reservoir is one of the most important exploration targets. In the study area, the Chang 6 3 tight sandstone reservoir exhibits lacustrine deep-water lobe-shaped delta deposits with low porosity, low permeability and a complex diagenetic alteration history. The reservoir quality is extremely heterogeneous because of the heterogeneity of the depositional lithofacies and diagenetic alterations. This research integrates multiple techniques to investigate the depositional lithofacies, the characteristics and distributions of various diagenetic alterations, and their controls on reservoir quality. Four lithofacies are identified, and the various lithofacies have different diagenetic characteristics and diverse reservoir qualities. The Chang 6 3 tight sandstone reservoir has experienced significant diagenetic alteration. Mechanical compaction and authigenic illite are the most important causes of the decrease in reservoir quality. Carbonate cementation preferentially occurs in sandstones of lithofacies "i" and "ii" near the mudstone-sandstone contact surfaces. Sandstones within 1 m of adjacent mudstone-sandstone contact surfaces are usually tightly cemented by carbonate cement. Illite can be divided into two types according to its morphology. Both types of illite lead to a decrease in reservoir quality. Ultimately, by combining the relationship between depositional facies and lithofacies with the distribution of different diagenetic processes, five evolutionary patterns are identified for reservoir quality in the lacustrine deep-water lobe-shaped delta deposits can be summarized by ratings of best, moderate, relatively poor, poor and worst. [ABSTRACT FROM AUTHOR]

Global warming, mainly caused by rising carbon dioxide (CO 2) emissions in the atmosphere, has led to severe effects worldwide. Hence, reducing carbon emissions has become an urgent need to mitigate the adverse effects. To do so, accurately forecasting CO 2 emissions is crucial for policymakers in formulating climate and energy policies. Existing CO 2 emission forecast models rely on various longitudinal economy, energy or environment data collected at the same periods, e.g., yearly, as indicators. However, these data usually come from diverse sources with different sampling frequencies, e.g., monthly vs. daily. Therefore, in this paper, we introduce for the first time a Mixed-frequency data Sampling Grey system Model (MSGM) that can exploit the potential information in high-frequency sampling (HF) data of economic and social indicators to effectively forecast annual CO 2 emissions. In MSGM, (1) we directly model low-frequency CO 2 emissions and HF economic-energy influence indicators without undertaking same-frequency conversion, thereby avoiding potential information loss and enhancing prediction accuracy; (2) we introduce polynomial weight functions to address the frequency mismatch, and its parameters are obtained through search optimization algorithms; (3) unlike existing grey system models, the whitening equation of MSGM adopts a reduced-order form to address the exponential explosion issue caused by HF data accumulation; (4) the time and cumulative terms are also introduced separately to explore the effects of temporal development and historical data on future CO 2 emissions. Extensive Monte-Carlo simulations show that MSGM exhibits high accuracy on both training and testing datasets and outperforms many other state-of-the-art rival techniques like MIDAS, AR-MIDAS, AMTGM, MLRM, BPNN, SVR, ARIMA and TVGBM. We further demonstrate the potential of MSGM to forecast China's CO 2 emissions under three distinct scenarios. Out-of-sample forecasting results indicate that only under a tight-contraction scenario does the growth rate of CO 2 emissions decrease. To the best of our knowledge, the MSGM is the first technique that can exploit different frequency data to effectively forecast CO 2 emissions. [Display omitted] • A novel grey system forecast model based on mixed-sampling frequency is proposed. • Introducing more higher frequency data from economic and social indicators. • Selecting popular local search algorithms to find optimal unstructured parameters. • The CO 2 emission forecast for 2022–2026 is carried out under three distinct scenarios. [ABSTRACT FROM AUTHOR]

Tight oil is a significant component of unconventional oil and gas resources. The pore structures of tight oil reservoirs determine the seepage law, which is a significant factor in evaluating reservoir quality. However, because of the strong heterogeneity of the pore structure in tight oil reservoirs, it is difficult to characterize the pore structure by conventional methods. Therefore, on the basis of conventional reservoirs research methods, combined with high-pressure mercury intrusion (HPMI) and constant-pressure mercury intrusion (CPMI), the pore-throat size distribution of tight sandstone reservoirs and its control on reservoir physical properties were studied. The main pore types in the study area were residual intergranular pores, secondary intragranular pores, intercrystalline micropores and microfractures, and throat types were sheet-like and tube throats. The pore-throat size distribution characterized by HPMI ranges from 0.0025 to 2.79 μm, and pore-throats larger than 10 μm occurred less frequently. The pore size distribution characterized by CPMI was between 90 and 350 μm, and the peak value distribution of the pore radius of the different samples was relatively concentrated, while the throat size distribution was between 0.12 and 6 μm, indicating that the throat radius of the different samples showed a strong heterogeneity, which also led to a strong heterogeneity of pore-throat radius ratio. Although HPMI and CPMI had their own limitations in characterizing the pore-throat size distribution, their combination could effectively characterize the whole pore-throat size distribution of tight reservoirs, which ranged from 0.0025 to 350 μm. The permeability of the tight sandstone reservoirs is primarily determined by the relatively wider pore-throats with small proportions, and the permeability decreased as the proportion of narrower pore-throats increased. The nanoscale pore throats (radius < 0.1 μm) were widely developed in the tight reservoirs, which had little influence on permeability, but these pore throats could be used as oil and gas storage spaces and played an important role in improving reservoir porosity. • The pore-throat size scales spanned from nanometer to several hundred microns. • The combination of HPMI and CPMI could effectively characterize the whole-distribution characteristics of the pore-throat size. • The porosity was not only controlled by the wider pore throats, but the nanoscale pore throats (radius < 0.1 μm) also contributed, while the permeability was controlled by relatively wider pore throats with a small proportion. [ABSTRACT FROM AUTHOR]

The degradation of organic matter in soils plays an important role in the carbon cycle. Lignin is the main source of soil organics and it can be used to trace the source, distribution and turnover of organic matter. In this study the distribution and degradation of lignin were investigated to identify the source and degradation of soil organic matter during the succession of China's Zoige Plateau. Lignin monomers were determined by gas chromatography-mass spectrometry with alkaline CuO oxidation and the soils' δ13C and δ15N contents were interpreted to explore the turnover rate of lignin and organic matter. The main source of organics was identified as C3 non-woody angiosperm tissues. Lignin in the topsoil (0–30 cm) was derived from litter and roots, and it then migrated vertically to the deep soil (30–80 cm). Correlations of δ13C/δ15N with the soil's elemental composition showed that the organics degraded more quickly in meadow soil than in bog soil. The soil communities in the meadow and bog soils were generally similar, but there were certain differences in the dominant microbial phyla at different depths. The meadow soil's effectiveness as a carbon sink was gradually weakened, while that of the bog soil strengthened with depth. These results provide a scientific basis for accurately assessing the carbon sink capacity of the soils in Zoige Plateau. [Display omitted] • Two representative soils in the bog degeneration in Zoige Plateau were selected. • SOM turnover was identified by lignin biomarkers and δ13C & δ15N abundances. • Correlations of SOC, C/N & isotopes showed SOM degraded more slowly in bog soil. • Environmental factors and microbes jointly affected SOM turnover in meadow soil. • Effective carbon sink between two typical soils were opposite with soil depth. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we investigated the killer cell immunoglobulin-like receptor (KIR) genes and HLA-C1/C2 dimorphism in 819 healthy, unrelated individuals composed of two southern Chinese Han populations (Hunan Han and Guangdong Han) and two northern Chinese populations (Inner Mongolia Han and Inner Mongolia Mongol), using polymerase chain reaction-sequence-specific priming (PCR-SSP) method. Fifty-one Chinese families were used to determine KIR haplotypic configuration. Our data showed that KIR2DL4, KIR3DL2, KIR3DL3, and KIR3DP1 genes were present in all of the 819 individuals. However, KIR2DL4 and KIR3DP1 genes were not detected in two members of a northern Chinese family. None of the KIR genes showed significant difference between the four populations. Thirty-five different KIR gene profiles were identified, one of which has not been previously reported in the Allele Frequencies KIR database. Eleven distinct KIR haplotypic configurations were determined through family analysis. Individuals with KIR2DLl and KIR2DL3 genes but lacking KIR2DSl and KIR2DS2 genes, coupled with HLA-C1 (Asn80) homozygosity, predominated in each population. At least one known inhibitory KIR–HLA pair was detected in each individual. The findings shown here are valuable for future studies of the potential role of KIR genes as well as KIR–HLA interaction in disease susceptibility in related ethnic groups. [Copyright &y& Elsevier]

Exposure to air pollutants has become a major global health threat and is a dominant contributor to increasing respiratory mortality. Accurate projections of respiratory mortality are crucial to mitigating the adverse influences of air pollution on public health and guiding long-term policy implementation. However, the forecasting models' accuracy is difficult to guarantee because seasonal factors perturb the raw series of air pollutants and respiratory mortality. This paper proposes an enhanced seasonal and self-adaptive multivariate grey convolution model to solve this dilemma. The innovations of the proposed model reside in the following areas: firstly, a seasonal operator vector of multidimensional data is initially built to digitize the seasonality of air pollutants and related mortality. Secondly, a multivariate grey convolution model with an adaptive time-lag cumulative optimization item is put forward. The weight coefficients of each driving variable at different periods are intended to adapt dynamically. Thirdly, the self-adaptive time-delay coefficient is determined by the Particle Swarm Algorithm, enhancing the accuracy of predictions. Theoretically, the generalizability and adaptability of the newly presented model are well-validated. Moreover, its practical applicability and higher forecasting performance are further verified in estimating the respiratory mortality attributable to the comprehensive effects of air pollutants in China. [ABSTRACT FROM AUTHOR]

In tight shales, occurrence characteristics limit oil migration and recovery. This paper proposes an innovative approach based on experimental and theoretical models to investigate the oil occurrence mechanism in nanoporous shales. Thermogravimetry (TG) and nuclear magnetic resonance (NMR) tests were conducted to investigate the migrations and distributions of adsorbed, irreducible, and movable oils. Furthermore, the oil micro-occurrence characteristics within shales were quantitatively clarified using the theoretical equation for the adsorption ratio. Lacustrine shales with different lithofacies from Dongying Sag, Bohai Bay Basin, China, were evaluated as a case study. The results showed that adsorbed, irreducible, and movable oils occur in different pore sizes. The adsorbed oil is primarily saturated in micropores (<0.1 μm) and mesopores (0.1–1 μm) but hardly in macropores (>1 μm), characterized by an average density of around 1.4974 g/cm3 and a mean adsorption thickness of approximately 0.723 nm at a temperature of 60 °C. The irreducible oil predominantly occurs in mesopores, whereas the movable oil primarily exists in mesopores and macropores, and the weight ratio rapidly increases with increased pore size. Additionally, the NMR T 1 –T 2 patterns of the adsorbed, irreducible, and movable oils were reported, and these patterns can directly reveal the states of oil micro-occurrence in shale pore-fracture systems. This study gives substantial insights into the oil occurrence mechanisms in nanoporous shales. • An innovative method evaluating the micro-occurrence of shale oil was developed. • The mean density and adsorption thickness of adsorbed oil at 60 °C were disclosed. • The NMR T 1 – T 2 patterns of the adsorbed, irreducible, and movable oils were presented. [ABSTRACT FROM AUTHOR]

High N fertilizer inputs in subtropical vegetable systems under the warm and humid climatic conditions increase the risk of nitrous oxide (N 2 O) emissions. However, there is limited information available on integrated N management strategies to reduce N 2 O emissions from intensive open-field vegetable systems in subtropical region. Two plot-based field experiments were conducted in subtropical southwest China to examine the effects of different N management strategies on N 2 O emissions from a typical open-field pepper (Capsicum annuum L.) production system. Experiment 1 included five N rates (0, 175, 250, 325, and 400 kg ha−1) with conventional urea. Experiment 2 included a 0 N control and four N sources (conventional urea, organic fertilizer, nitrification inhibitor-based enhanced efficiency fertilizer ENTEC26, and controlled release urea) applied under an optimized N rate (250 kg N ha−1). The results of Experiment 1 showed that cumulative N 2 O emission and emission factor were 4.05 kg N ha−1 season−1 and 0.96%, respectively, under the conventional management (N400). N 2 O emissions increased exponentially with increasing N rates. Compared to the N400 treatment, application of conventional urea at the optimal rate (250 kg N ha−1) significantly reduced cumulative N 2 O emissions by 54% while maintaining similar pepper yield. The results from Experiment 2 indicated that the use of enhanced efficiency fertilizers at the optimal rate further reduced N 2 O emission by 30%− 50% compared to conventional urea, while increasing pepper yield by 6.7%− 9.0%. This resulted in a 36%− 53% reduction of yield-scaled N 2 O emission intensity. In particular, the use of nitrification inhibitor was 28% more effective than controlled release urea for N 2 O mitigation. These results suggest that the application of enhanced efficiency fertilizers at an optimum N rate could produce more vegetables while reducing N 2 O emission, thereby promoting sustainable vegetable production in the subtropic regions. [Display omitted] • Innovative N management strategy was proposed to produce more vegetables with lower N 2 O emission in the subtropics. • Optimizing rate and timing of conventional urea significantly decreased N 2 O emission by 54% compared to farmer's practice. • Enhanced-efficiency fertilizers further reduced N 2 O emission by 30%− 50% compared to conventional urea. • Nitrification inhibitor showed better performance than controlled release urea for N 2 O mitigation. [ABSTRACT FROM AUTHOR]

[Display omitted] • The growth of exotic mangrove was significantly faster than that of native species. • The morphological patterns can be used to indicate the hotspots of mangroves. • Sonneratia species was found in the forest gap and forest edge of native mangroves. • The spread of Sonneratia species is fast in bare tidal flat and tidal creek zones. • Invasive potentials of Sonneratia mangrove in Shenzhen Bay should not be ignored. Mangroves are essential forest communities in tropical and subtropical coastal zones, providing unique ecological functions and significant social and economic value. Accurate and efficient monitoring of mangroves is crucial for their protection and management. The impact of exotic species on native species is still debated, especially for mangroves, the spatiotemporal dynamics of introduced species and native mangrove species need to be closely monitored. This study aimed to investigate how exotic mangrove species affects the spatial dynamics of mangroves in Shenzhen Bay, China. Yearly Landsat images from 2000 to 2011 and Chinese high spatial resolution images during 2012–2022 were obtained and the pixel-based and multiscale object-based methods were used to obtain mangrove distribution. The results showed that: (1) Overall, mangroves in the study area increased from 281.51 ha to 526.43 ha from 2000 to 2022, with different spatiotemporal patterns in Shenzhen (+5.14%) and Hong Kong (+2.38%); (2) rapid spread of Sonneratia species was one of the main contributions to the growth of mangrove hotspots, and growth hotspots were mainly concentrated in the estuary delta; and (3) Sonneratia mangrove species was dominant in interspecific competition, not only invading the habitat of local mangroves, but also preventing the expansion of native mangrove growth. The results provide a reference for fine-scale and accurate mangrove mapping with high spatial and temporal resolutions, and highlight the need to pay more attentions to the spread and invasive potential of exotic mangrove species in the study area, as well as cooperation in adjacent reserves. [ABSTRACT FROM AUTHOR]

Effluents containing disinfection byproducts (DBPs) from wastewater treatment plants (WWTPs) may be discharged to the receiving water bodies or reused for irrigation, landscaping, and environmental supplies as well as a source to replenish groundwater. Thus the formation and risk of the DBPs in disinfected wastewater effluents should be concerned. In this study, the occurrence of 44 DBPs including 6 trihalomethanes (THMs), 9 haloaceticacids (HAAs), 2 haloketones (HKs), 9 halonitromethanes (HNMs), 9 haloacetonitriles (HANs) and 9 nitrosamines (NAs) was investigated in 12 chlorinated WWTP effluents from five cities of East China. The contribution of each class of DBPs to the total DBPs concentration and additive toxicity was calculated. The average concentrations of the 6 classes of DBPs were ranked as follows: HAAs (47.0 μg/L) > THMs (28.0 μg/L) > HANs (9.9 μg/L) > HNMs (2.9 μg/L) > HKs (0.79 μg/L) > NAs (0.69 μg/L). The significant positive correlations were observed between the formation of THMs and HAAs, THMs and HANs, as well as HAAs and HANs. The results showed that HAAs and THMs were the dominant DBPs on a mass concentration basis and accounted for 54% and 29%, respectively in the total measured DBPs, but they made a minor contribution to the calculated DBP-associated cytotoxicity. HANs and NAs dominated the DBP-associated cytotoxicity, accounting for 50% and 34% on an additive toxicity basis despite the minor contributions to the mass concentration with 10% and 1%, respectively. The risk quotients for three taxonomic groups (fish, daphnid, and green algae) were calculated to assess the ecological risk of DBPs, and the results demonstrated that both HAAs and HANs had high ecological risk for green algae in chlorinated wastewater effluents. Image 1 • Higher concentration and frequency of NDEA were detected than NDMA in WWTP effluents. • N-DBPs including HANs and NAs were the main contributors for the cytotoxicity. • HAAs and HANs had high ecological risks for green algae in chlorinated effluents. [ABSTRACT FROM AUTHOR]

Highlights • We propose a 2D-to-3D strategy for invasive plants mapping in mountain area, using UAV-derived 2D digital ortho map (DOM) and 3D mesh model. • The texture features overcome the shortcomings of RGB-only image, and helps to better distinguish invasive vegetation. • A 3D mesh model could better visualize the final results, and show the distribution of invasive plants in the mountains. Abstract Invasive plants constitute one of the major causes of biodiversity loss, and its monitoring plays an important role in the management of coastal ecological systems. This study aimed to apply high precision 3D mesh-model and digital orthophoto map (DOM) derived from unmanned aerial vehicle (UAV) multi view images to monitor the invasive plants over coastal mountain region in Shenzhen, China. To overcome the limitations of RGB images, the Gray-level Co-occurrence Matrix (GLCM) features of images were analyzed and combined with spectral features to obtain the 2-dimentional distribution of invasive plants first, using an object-based image analysis technique. A fine analysis was then introduced to obtain a more accurate 3-dimentional distribution of invasive plant by combining 2-dimentional distribution of invasive plant and 3D mesh model. the results have shown that: (1) Although the UAV RGB image has limited spectral information, the low-altitude makes the spatial resolution very high, which can effectively enhance the effectiveness of the texture in mapping invasive plants, and finally achieved an overall accuracy of 93.25%. (2) The use of 3D mesh model, on the one hand, could significantly alleviate the impact of undulatory terrain over mountain area and improve the classification result; on the other hand, it could better visualize the final results, helping us more intuitively understanding the distribution of invasive plants. This study demonstrated the great potential of UAV-derived 3D mesh model in accurate natural resource management over mountain areas. [ABSTRACT FROM AUTHOR]

The occurrence and mobility of oil obtained from shales are primarily controlled by the pore–fracture networks of the shales. To clarify the distributions and characteristics of the type, morphology, and size in lacustrine shale pores, shale samples obtained from the Shahejie Formation, Dongying Sag, Bohai Bay Basin in China were examined using argon ion milling and scanning electron microscopy. In this study, pores were mainly classified as interparticle pores, intraparticle pores, and fractures and further classified into 14 types, comprising intraparticle pores (7 types), interparticle pores (6 types), and fractures, based on the differences in their components. Interparticle pores have more complex morphologies than intraparticle pores and fractures. Complex shapes characterize the interparticle pores between quartz granules and at the edges of feldspar granules. Intraparticle pores mainly contribute to mesopores and then to macropores, while interparticle pores behave in the opposite manner. Micropores are primarily derived from the intraparticle pores present in clay aggregates and dissolution pores present in calcite or dolomite granules. However, macropores mainly come from the interparticle pores present within or at the edges of quartz granules; consequently, siliceous-rich shales may be the favorable shale oil reservoirs called interlayer shale oil. Moreover, organic-rich calcareous shales with numerous large dissolution pores can become optimal self-generation and self-storage shale oil reservoirs. This study gives insight into the evaluation of shale oil exploration and development in the Dongying Sag in the Bohai Bay Basin. • Fracture, 7 types of intra- and 6 types of interparticle pores were observed. • The morphology and size of each type of pore were well revealed. • Micropores mainly come from intraparticle pores in clay and carbonate minerals. • Macropores primarily come from interparticle pores associated with quartz granules. [ABSTRACT FROM AUTHOR]

• A novel nonlinear interactive grey model based on dynamic compensation is proposed. • The new method can be used to forecast nonlinear interactive coupled systems. • The WOA algorithm is utilized to determine the optimal nonlinear parameters. • Three different cases verify the feasibility and effectiveness of the novel model. • Empirical results demonstrate the novel model's excellent forecasting performance. Achieving the goals of emissions intensity reduction and energy structure transformation while ensuring stable economic development is essential for sustainable development in China. Establishing a concise and accurate model for predicting the 3E (economy-energy-environment) system is beneficial for decision-makers in developing optimal long-term energy and environmental planning. Although previous studies have concentrated on the interaction of variables in the 3E system, frameworks for prediction have thus far been limited. In this paper, we develop a novel nonlinear interactive grey multivariable model based on dynamic compensation, denoted as D C N I G M 1 , N , to perform the prediction of the 3E system. More specifically, the proposed model innovatively takes into account nonlinear driving effects to elucidate nonlinear interactive relationships between the system variables. A dynamic compensation mechanism is introduced into the systematic grey modeling for the first time to adapt to a dynamic system. In addition, the Whale Optimization Algorithm (WOA) is employed to determine the optimal nonlinear parameters to improve the forecast accuracy. To evaluate the performance of the D C N I G M 1 , N model in forecasting the 3E system, two existing grey forecasting models, three statistical approaches, and three machine learning models are selected as the benchmark models. Moreover, two more cases with different variables of the 3E system are applied to verify the feasibility and effectiveness of the proposed model. Experimental results indicate that the D C N I G M 1 , N model possesses the most excellent performance in all cases, showing the effectiveness and generalizability of the proposed method. The prediction from 2019 to 2020 shows that carbon emissions, total energy consumption, and gross domestic product will grow steadily. [ABSTRACT FROM AUTHOR]

This paper investigates the long-term performance of structural concretes in China southeast coastal area, the city of Shenzhen, exposed to atmosphere and chlorides. The structural concretes, incorporating large quantity of supplementary cementitious materials (SCM), were among the first massive application of such mixtures in construction in China. In both cases, in-field sampling and tests have been conducted during more than 20 years for the resistance of concretes to carbonation and chloride ingress respectively. The synthetic analysis of these results shows that (1) the concretes have substantial strength growth in atmospheric environment with exposure age, but the carbonation rate does not all obey the square root law of exposure time; (2) the protection of silane impregnation of high-performance concrete against chloride ingress maintains its hydrophobic effect after nearly 20 years; (3) Notable "skin" effect of surface concrete was observed for both atmospheric and marine exposures. [ABSTRACT FROM AUTHOR]

Wind and solar power have embraced a strong development in recent years due to the energy crisis in China. However, owing to their nature of fluctuation and intermittency, some power grid management problems can be caused. Therefore a novel hybrid wind-solar-compressed air energy storage (WS-CAES) system was proposed to solve the problems. The WS-CAES system can store unstable wind and solar power for a stable output of electric energy and hot water. Also, combined with organic Rankin cycle (ORC), the cascade utilization of energy with different qualities was achieved in the WS-CAES system. Aiming to obtain the optimum performance, the analysis of energy, exergy and parametric sensitivity were all conducted for this system. Furthermore, exergy destruction ratio of each component in the WS-CAES system was presented. The results show that the electric energy storage efficiency, round trip efficiency and exergy efficiency can reach 87.7%, 61.2% and 65.4%, respectively. Meanwhile, the parameters analysis demonstrates that the increase of ambient temperature has a negative effect on the system performance, while the increase of turbine inlet temperature has a positive effect. However, when the air turbine inlet pressure varies, there is a tradeoff between the system performance and the energy storage density. [ABSTRACT FROM AUTHOR]

In this study, an ecological vulnerability assessment indicator system was constructed using the “exposure–climate sensitivity–adaptive capacity” framework according to the theory of ecological vulnerability. An improved ecosystem service value calculation model was proposed based on empirical parameters. Using Yancheng Nature Reserve in China as an example, we employed remote sensing data to conduct an empirical analysis of the changes in the spatiotemporal pattern, ecological vulnerability, and ecosystem services of typical landscape types over the period from 1987 to 2013. The statistical results derived from landscape pattern indices (LPIs) showed that during the investigation period, three natural wetland landscape types (i.e., Spartina alterniflora , Suaeda glauca , and Phragmites australis ) showed gradually increased fragmentation in the study area. The ecological vulnerability scores of the major landscape types (in descending order) were P. australis (0.053), farmland (0.047), S. alterniflora (0.042), S. glauca (0.031), and bare mud flat (0.002). The results derived from the ecosystem service value fluctuation index ( ESVFI ) showed that from 1987 to 1997, the value of the ecosystem services provided by S. glauca and P. australis wetlands decreased, whereas that of S. alterniflora wetlands increased continuously. From 2002 to 2013, the value of the ecosystem services provided by all three types of natural wetland showed a downward trend. In conclusion, the combined effects of human and natural factors, including the expansion of farmland and the invasion of S. alterniflora , and changes in seawater erosion and deposition led to changes in the landscape patterns, ecological vulnerability, and ecosystem services of the Yancheng Nature Reserve during the investigation period. The results indicate that a “dual adaptive” management system based on natural succession and supplemented by appropriate manual intervention should be implemented, and the management efficiency and flexibility should be improved to meet the common needs of biodiversity conservation and economic development. [ABSTRACT FROM AUTHOR]

• Climate-sensitive nonlinear mixed-effects height-diameter model was developed for 14 tree species in mixed forests. • The inclusion of climate and species diversity improved the H-D model. • The impact of environmental gradients on tree height growth was simulated. • The sensitivity of multiple species in mixed forest to environmental gradient changes varies with species. Models based on height-diameter (H-D) are helpful for estimating forest biomass and carbon storage on a large scale. Climate change has an impact on allometric height-diameter growth. H-D models explaining climatic effects are still inadequate due to the complexity of mixed forests. This paper developed climate-sensitive mixed-effects models for 14 tree species based on 316 natural mixed forest plots in Northeastern China and compared the response of tree height growth to environmental gradients for multiple species. The results showed that the species heterogeneity leads to the differences in scaling exponents in varying degrees. The analysis revealed that incorporating mean annual temperature (MAT), mean annual precipitation (MAP), dominant tree height (HT), basal area of the larger trees (BAL), and Shannon diversity index significantly enhanced the predictive ability of the model. By exploring the tree height change patterns of each tree species under different gradients of environmental factors, we found that increases in temperature, precipitation, site quality, and competition intensity positively affected height growth in mixed forests. In contrast, increases in species diversity inhibited height growth. The degree to which environmental factors regulate the H-D allometric growth of trees in mixed forests is related to species specificity. This paper provides theoretical support for tree height estimates of major tree species in mixed forests under global climate change by introducing environmental factors to improve the H-D model of 14 tree species. [ABSTRACT FROM AUTHOR]

The importance for the accurate forecast of carbon emissions affected by many factors is gradually emerging. Carbon emissions usually lag behind the related factors, which cannot be dynamically reflected in the existing grey forecasting models. Therefore, investigating the dynamic lag relationships remains the key challenge to carbon emissions forecast. For this purpose, an enhanced dynamic time-delay discrete grey forecasting model, denoted as D T D G M (1 , N , τ) , is proposed to predict the systems having dynamic time-lag effects. More specifically, a time-lag driving term consisting of both the interval and intensity of the time lags is developed to reflect the lag process of different factors to carbon emissions. The impulse response analysis of the vector autoregressive (VAR) model is carried out for determining the dynamic lags between carbon emissions and the related factors. In addition, a linear correction term is designed in the proposed model to extend the grey forecasting theory. Extensive experimental results about carbon emissions prediction from 1995 to 2017 show that the D T D G M (1 , N , τ) model considering the delayed relationships can significantly improve the fitting and prediction performance of the model in comparison with the six benchmark models, including the three existing grey forecasting models, two machine learning models and one statistical prediction approach. • An enhanced dynamic time-delay discrete grey forecasting model is proposed. • The novel model reveals the lag relationships between variables and the factors. • The dynamic lag processes over time are depicted by the impulse response analysis. • The new method improves the applicability of the grey forecasting model. • Empirical results comprehensively verify the efficacy of the enhanced method. [ABSTRACT FROM AUTHOR]

Abstract: Background: Drug use and sex work have had facilitative roles in the transmission of HIV/AIDS in China. Stopping drug use among sex workers may help to control the growth of the HIV/AIDS epidemic among Chinese sex workers. Methods: From March 2006 to November 2009, female sex workers (FSW) in Kaiyuan City, Yunnan, China were recruited into an open cohort study. Participants were interviewed and tested for drug use and HIV/sexually transmitted infection (STI) prevalence. Follow-up surveys were conducted every six months. Multivariate Cox proportional hazards regression model with time dependent variables was used to measure the associations between independent variables and drug initiation. Results: During the course of the study, 66 (8.8%) FSWs initiated drug use yielding an overall incidence of 6.0 per 100 person years (PY) (95% confidence interval [CI], 4.67–7.58). In the multivariate Cox proportional hazards regression model, being HIV-positive and aware of positive serostatus (adjusted hazard ratio [AHR] 2.6, 95% CI 1.24–5.55), age at initiation of commercial sex work <20 years (AHR 1.8, 95% CI 1.12–3.01), and working in a high-risk establishment (AHR 1.9, 95% CI 1.14–3.04) were associated with illicit drug initiation. Conclusions: Being HIV-positive and aware of positive serostatus was the most salient predictor for the initiation of illicit drug use. Interventions offering sources of education, treatment, support, and counseling to HIV-positive FSWs need to be implemented in order to help promote self-efficacy and safe behaviors among this group of high-risk women. [Copyright &y& Elsevier]

• A variable trigeneration system based on liquid air energy storage is proposed. • Systematic thermo-economic analysis for different seasons and regions is made. • Better performance comes from higher ambient temperature and energy price. Liquid air energy storage is a promising long-time energy storage technology with the advantages of large capacity and no geographical restrictions. However, the cycle efficiency still has potential to improve and the operation modes need to be investigated. Thus a novel trigeneration system based on the liquid air energy storage is proposed. The system can store the off-peak electricity and supply the cooling, heating and power at the peak time. With different needs for the multiple energy, the optimal configuration of the trigeneration system for different seasons is studied, and the thermodynamics and economics are both analyzed. The results show that the round-trip efficiencies of the system in winter, the transition season and summer for Jinan City are 55.41%, 55.35% and 54.68%, respectively. The dynamic payback period and the levelized cost of energy for the trigeneration system are 5.46 years and 0.13 $/kWh, respectively. Furthermore, the thermo-economic analysis of five typical regions in China is carried out. Guangzhou City owns the best economic performance with the largest annual total profit of 709.81 k$ and the smallest dynamic payback period of 4.49 years. It can be concluded that the system has inspiring adaptability and feasibility under variable operation modes. [ABSTRACT FROM AUTHOR]

Most studies assessing brain–personality mechanisms have used Western personality questionnaires. However, Western personality questionnaires may not objectively reflect the personality characteristics of individuals in Eastern cultures such as China. Hence, we adopted the functional magnetic resonance imaging (fMRI) and the Chinese localized scale, FPPI, to explore the brain mechanisms differences of typical yin and typical yang personalities of individuals in China. 30 typical yin personality participants (TYI) and 34 typical yang personality participants (TYA) were enrolled according to the FPPI. The group differences of the functional brain networks among 90 specific brain regions were mapped using fMRI data and then analyzed by the conventional network metrics (CNM) and frequency subgraph mining (FSM). The CNM and FSM differences between two typical personality groups were traced to the frontal, temporal, and parietal cortices. The yin group, reflecting the rich emotions and feelings of individuals, showed higher betweenness centrality (BCi) and nodal efficiency (Ei) values in putamen and middle frontal gyrus. The yang group, reflecting active behaviors and tendency to adapting to the changing surroundings, showed higher BCi and Ei values in precuneus, posterior cingulate gyrus, and inferior parietal lobule, brain areas in the default mode network (DMN). These results supplied evidence for the neurobiological differences between typical yin and typical yang personality participants based on Chinese culture. These results also provide a new perspective to help researchers understand brain mechanism differences between yin and yang personality groups in the Chinese culture. [ABSTRACT FROM AUTHOR]