76 research outputs found
Thermodynamic Simulation of Carbonate Cements-Water-Carbon Dioxide Equilibrium in Sandstone for Prediction of Precipitation/Dissolution of Carbonate Cements
Carbonate cements, such as calcite, dolomite, ferrocalcite and ankerite, play important roles in the formation of pores in sandstones: precipitation of carbonate cements modifies pores and inhibits compaction, while dissolution creates secondary pores. This work proposed a precipitation-dissolution model for carbonate cements-CO2-H2O system by means of ion equilibrium concentration ([M2+], M = Ca, Mg, Fe or Mn) with different factors, such as temperature, depth, pH, [Formula: see text], variable rock composition and overpressure. Precipitation-dissolution reaction routes were also analyzed by minimization of the total Gibbs free energy (ΔG). Δ[M2+], the variation of [Ca2+], [Fe2+], [Mg2+] or [Mn2+] for every 100 m of burial depths, is used to predict precipitation or dissolution. The calculation results indicate that the increasing temperature results in decrease of equilibrium constant of reactions, while the increasing pressure results in a relatively smaller increase of equilibrium constant; As a result, with increasing burial depth, which brings about increase of both temperature and pressure, carbonate cements dissolve firstly and produces the maximal dissolved amounts, and then precipitation happens with further increasing depth; For example, calcite is dissolving from 0.0 km to 3.0 km with a maximal value of [Ca2+] at depth of 0.8 km, and then precipitates with depth deeper than 3.0 km. Meanwhile, with an increasing CO2 mole fraction in the gaseous phase from 0.1% to 10.0% in carbonate systems, the aqueous concentration of metal ions increases, e.g., dissolved amount of CaFe0.7Mg0.3(CO3)2 increases and reaches maximum of 1.78 mmol·L-1 and 8.26 mmol·L-1 at burial depth of 0.7 km with CO2 mole fraction of 0.1% and 10.0%, respectively. For the influence of overpressure in the calcite system, with overpressure ranging from 36 MPa to 83 MPa, pH reaches a minimum of 6.8 at overpressure of 51 MPa; meanwhile, Δ[Ca2+] increases slightly from -2.24 mmol·L-1 to -2.17 mmol·L-1 and remains negative, indicating it is also a precipitation process at burial depth of 3.9 km where overpressure generated. The method used in this study can be applied in assessing burial precipitation-dissolution processes and predicting possible pores in reservoirs with carbonate cement-water-carbon dioxide
Rice Soluble Starch Synthase I: Allelic Variation, Expression, Function, and Interaction With Waxy
Starch, which is composed of amylose and amylopectin, is the key determinant of rice quality. Amylose is regulated by the Waxy (Wx) gene, whereas amylopectin is coordinated by various enzymes including eight soluble starch synthases (SSSs), of which SSSI accounts for ∼70% of the total SSS activity in cereal endosperm. Although great progress has been made in understanding SSSI gene expression and function, allelic variation and its effects on gene expression, rice physicochemical properties and qualities, and interactions with the Wx gene remain unclear. Herein, SSSI nucleotide polymorphisms were analyzed in 165 rice varieties using five distinct molecular markers, three of which reside in an SSSI promoter and might account for a higher expression of the SSSIi allele in indica ssp. than of the SSSIj allele in japonica ssp. The results of SSSI promoter-Beta-Glucuronidase (β-GUS) analysis were consistent with the expression results. Moreover, analysis of near isogenic lines (NILs) in the Nipponbare (Nip) background showed that Nip (SSSIi) and Nip (SSSIj) differed in their thermal properties, gel consistency (GC), and granule crystal structure. Knockdown of SSSI expression using the SSSI-RNA interference (RNAi) construct in both japonica and indica backgrounds caused consistent changes in most tested physicochemical characteristics except GC. Moreover, taste value analysis (TVA) showed that introduction of the SSSI allele in indica or knockdown of SSSI expression in japonica cultivars significantly reduced the comprehensive taste value, which was consistent with the superior taste of japonica against indica. Furthermore, to test the potential interaction between SSSI and different Wx alleles, three NILs within the Wx locus were generated in the indica cv. Longtefu (LTF) background, which were designated as LTF (Wxa), LTF (Wxb), and LTF (wx). The SSSI-RNAi construct was also introduced into these three NILs, and physiochemical analysis confirmed that the knockdown of SSSI significantly increased the rice apparent amylose content (AAC) only in the Wxa and Wxb background and caused different changes in GC in the NILs. Therefore, the effect of SSSI variation on rice quality also depends on its crosstalk with other factors, especially the Wx gene. These findings provide fundamental knowledge for future breeding of rice with premium eating and cooking qualities
Extracting urban road area based on combination of trajectory continuity and image feature similarity
Urban road area detecting is the imperious demand in the area of management of city land use, transportation planning and so on. Trajectory extraction, remote sensing image classification and artificial collection are the traditional methods for road network detection with some limits on automation degree or extraction quality. This paper proposes a method for detecting road area in high-resolution remote sensing image based on trajectory continuity and image feature similarity, and this method utilizes the advantages of GNSS trajectory and remote sensing image. The proposed methods could be divided into three steps: firstly, using GNSS trajectory points to construct images of trajectory feature and selecting the high-confidence grids with high density value. Secondly, generating road objects based on trajectory continuity in average direction feature image. Thirdly, dividing high-resolution remote sensing image into several small areas by using road segments and extending road areas based on image feature similarity automatically to detect roads which not covered by trajectory. The experiment evidences that this method could detect road areas efficiency and accuracy in high-resolution remote sensing image and decreasing the bad effect on the different roads with different spectrums. Compared with the traditional remote sensing image classification methods, the proposed method has a higher precision and automatic degree
Experimental Study on Silt Soil Improved by Microbial Solidification with the Use of Lignin
At present, in the field of geotechnical engineering and agricultural production, with increasingly serious pollution an environmentally friendly and efficient means is urgently needed to improve the soil mass. This paper mainly studied the microbial induced calcium carbonate precipitation (MICP) technology and the combined effect of MICP technology and lignin on the improvement of silt in the Beijing area. Through unconfined compressive strength and dynamic triaxial test methods, samples improved by microorganisms were studied to obtain the optimal values of cement concentration and lignin under these two test schemes. The results show that after the incubation time of Sporosarcina pasteurii reached 24 h, the OD600 value was 1.7–2.0 and the activity value (U) was 930–1000 mM ms/min. In the unconfined static pressure strength test, after MICP treatment the optimal concentration of cementitious solution for constant temperature and humidity samples and constant-temperature immersion samples was 1.25 mol/L. The compressive strength of the constant temperature and humidity sample was 1.73 MPa, and the compressive strength of the constant-temperature immersion sample was 3.62 Mpa. At the concentration of 1.25 mol/L of cement solution, MICP technology combined with lignin could improve the constant temperature and humidity silt sample. The optimal addition ratio of lignin was 4%, and its compressive strength was 1.9 MPa. The optimal lignin addition ratio of the sample soaked at a constant temperature was 3%, and the compressive strength was 4.84 MPa. In the dynamic triaxial multi-stage cyclic load test, the optimal concentration of cementation solution for the constant temperature and humidity sample after MICP treatment was 1.0 mol/L, and the failure was mainly inclined cracks. However, in the condition of joint improvement of MICP and lignin, the sample mainly had a drum-shaped deformation, the optimal lignin addition ratio was 4%, and the maximum axial load that the sample could bear was 306.08 N. When the axial dynamic load reached 300 N, the strain accumulation of the 4% group was only 2.3 mm. In this paper, lignin, an ecofriendly material, was introduced on the basis of MICP technology. According to the failure shape and relevant results of the sample, the addition of lignin was beneficial for the improvement of the compressive strength of the sample
Water permeability prediction of sponge city pavement materials based on different machine learning algorithms
Permeable pavement material is one of the most important supporting materials in the construction of sponge city, and its water permeability is the most important performance index. The water permeability test of permeable pavement materials is a tedious and complicated experimental work. It is of great research significance to predict the water permeability of permeable pavement materials through structural parameters modeling. In this paper, the database is first established by experimental means, and then the prediction models of LASSO (Least absolute shrinkage and selection operator), SVR (Support vector regression) and GBR (Gradient Boosting Regression) machine learning algorithms are established. Through the four factors of particle size, particle size distribution, shape parameters and binder content predict the water permeability of sponge city pavement materials. The results show that different machine learning algorithms have different sensitivity to the distribution of data samples. The fitting effect of GBR model water permeability prediction is better than that of SVR and LASSO models. The test value-predicted value MSE is 0.0051 and R2 is 0.92, which can effectively predict the water permeability of sponge city pavement materials
Experimental Study on Silt Soil Improved by Microbial Solidification with the Use of Lignin
At present, in the field of geotechnical engineering and agricultural production, with increasingly serious pollution an environmentally friendly and efficient means is urgently needed to improve the soil mass. This paper mainly studied the microbial induced calcium carbonate precipitation (MICP) technology and the combined effect of MICP technology and lignin on the improvement of silt in the Beijing area. Through unconfined compressive strength and dynamic triaxial test methods, samples improved by microorganisms were studied to obtain the optimal values of cement concentration and lignin under these two test schemes. The results show that after the incubation time of Sporosarcina pasteurii reached 24 h, the OD600 value was 1.7–2.0 and the activity value (U) was 930–1000 mM ms/min. In the unconfined static pressure strength test, after MICP treatment the optimal concentration of cementitious solution for constant temperature and humidity samples and constant-temperature immersion samples was 1.25 mol/L. The compressive strength of the constant temperature and humidity sample was 1.73 MPa, and the compressive strength of the constant-temperature immersion sample was 3.62 Mpa. At the concentration of 1.25 mol/L of cement solution, MICP technology combined with lignin could improve the constant temperature and humidity silt sample. The optimal addition ratio of lignin was 4%, and its compressive strength was 1.9 MPa. The optimal lignin addition ratio of the sample soaked at a constant temperature was 3%, and the compressive strength was 4.84 MPa. In the dynamic triaxial multi-stage cyclic load test, the optimal concentration of cementation solution for the constant temperature and humidity sample after MICP treatment was 1.0 mol/L, and the failure was mainly inclined cracks. However, in the condition of joint improvement of MICP and lignin, the sample mainly had a drum-shaped deformation, the optimal lignin addition ratio was 4%, and the maximum axial load that the sample could bear was 306.08 N. When the axial dynamic load reached 300 N, the strain accumulation of the 4% group was only 2.3 mm. In this paper, lignin, an ecofriendly material, was introduced on the basis of MICP technology. According to the failure shape and relevant results of the sample, the addition of lignin was beneficial for the improvement of the compressive strength of the sample
Experimental Study on Different Improvement Schemes of EICP-Lignin Solidified Silt
In practical engineering applications, silt is prone to liquefaction and quicksand. This paper mainly studies the improvement effects of urease, lignin and their mixture on the strength and liquefaction resistance of silt. Based on the results and phenomena of an unconfined compressive strength and dynamic triaxial test, the improvement effects of the compressive strength, deformation resistance and liquefaction resistance of silt under different improvement schemes are analyzed, and the optimal values of the cement or lignin when enzyme-induced calcium carbonate precipitation (EICP) technology, lignin alone or EICP and lignin are obtained. The results show that the optimum concentration of the constant temperature and humidity sample (referred to as the constant humidity sample) and the constant temperature immersion sample (referred to as the soaking sample) of urease in the unconfined compressive strength test is 1.0 mol/L, and the compressive strength of the soaking sample is 4.9 MPa, which is 1.56 times that of the constant humidity sample; the optimum addition ratio of the lignin-improved constant humidity sample is 3%, and its compressive strength is 2.07 Mpa; the optimum addition ratio of the samples immersed at constant temperature is 4%, and the compressive strength is 3.05 MPa; when urease combines with lignin to improve silt, 4% is the best lignin addition ratio, the compressive strength of the constant humidity sample reaches 1.57 Mpa and the compressive strength of the soaking sample reaches 3.75 MPa; in the dynamic triaxial multi-stage cyclic load test, all samples were cured at constant humidity sample, and in the urease modified silt scheme, 1.0 mol/L was the optimal cement concentration; in the scheme of improving silt with lignin, 3% is the optimal addition ratio; when 1.25 mol/L cementation solution plus urease crude extract is combined with different ratios of lignin in the experimental scheme, 3% is the best lignin addition ratio
Two-Stage Tour Route Recommendation Approach by Integrating Crowd Dynamics Derived from Mobile Tracking Data
Tourism activities essentially represent the interaction between crowds and attractions. Thus, crowd dynamics are critical to the quality of the tourism experience in personalized tour recommendations. In order to generate dynamic, personalized tour routes, this paper develops a tourist trip design problem with crowd dynamics (TTDP-CD), which is quantified with the crowd dynamics indicators derived from mobile tracking data in terms of crowd flow, crowd interaction, and crowd structure. TTDP-CD attempts to minimize the perceived crowding and maximize the assessed value of destinations while minimizing the total distance and proposes a two-stage route strategy of “global optimization first, local update later” to deal with the sudden increase in crowding in realistic scenarios. An evolutionary algorithm is extended with container-index coding, mixed mutation operators, and a global archive to create a personalized day tour route at the urban scale. To corroborate the performance of this approach, a case study was carried out in Dalian, China. The results demonstrate that the suggested method outperforms previous approaches, such as NSGA-II, MOPSO, MOACO, and WSM, in terms of performance and solution quality and decreases real-time crowding by an average of 7%
Two-Stage Tour Route Recommendation Approach by Integrating Crowd Dynamics Derived from Mobile Tracking Data
Tourism activities essentially represent the interaction between crowds and attractions. Thus, crowd dynamics are critical to the quality of the tourism experience in personalized tour recommendations. In order to generate dynamic, personalized tour routes, this paper develops a tourist trip design problem with crowd dynamics (TTDP-CD), which is quantified with the crowd dynamics indicators derived from mobile tracking data in terms of crowd flow, crowd interaction, and crowd structure. TTDP-CD attempts to minimize the perceived crowding and maximize the assessed value of destinations while minimizing the total distance and proposes a two-stage route strategy of “global optimization first, local update later” to deal with the sudden increase in crowding in realistic scenarios. An evolutionary algorithm is extended with container-index coding, mixed mutation operators, and a global archive to create a personalized day tour route at the urban scale. To corroborate the performance of this approach, a case study was carried out in Dalian, China. The results demonstrate that the suggested method outperforms previous approaches, such as NSGA-II, MOPSO, MOACO, and WSM, in terms of performance and solution quality and decreases real-time crowding by an average of 7%
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