Instruction Cache Optimizations in Embedded Real-Time Systems

Ph.DDOCTOR OF PHILOSOPH

Analysis on spatial heterogeneity of ecological restoration demand in resource-based cities: taking Jiawang District of Xuzhou city as an example

After a long period of coal resource exploitation in resource-based cities, the imbalance and disharmony between resource development and ecological protection in coal mining areas are prominent. In the context of ecological civilization construction, clarifying the spatial heterogeneity of ecological restoration needs and reasonably arranging the priority of ecological restoration work will become the basic work for efficient and coordinated ecological protection and restoration, which will help to plan as a whole, coordinate and orderly promote the high-quality sustainable development of resource-based cities. From the comprehensive perspective of the coordinated development of ecosystem and human well-being, Jiawang District, Xuzhou City, was selected as an example, and the historical remote sensing images, historical mine information and social and economic statistics in 2000, 2010 and 2019 were taken as the data sources. The equivalent assignment method was used to calculate the regional ecosystem service value and make coefficient correction. The landscape ecological risk assessment system was constructed by integrating the topographic location index, mining area disturbance index and landscape vulnerability index. The spatial and temporal patterns of ecosystem service value and ecological risk index in the study area were analyzed, and the sharpe ratio was introduced to further explore the spatial heterogeneity of ecological restoration needs. The results showed that: ① From 2000 to 2019, the total value of ecosystem services in Jiawang district increased first and then decreased, and the value of ecological risk index decreased first and then increased. The growth rate was relatively flat, showing a small range; the spatial distribution of ecological service value and ecological risk level shows a trend of overall connectivity, with local circles moving outward. Urbanization and coal mining subsidence land management are the main factors influencing the spatial pattern differentiation. ② At the quantitative level, the ecosystem service value per unit area and the ecological risk index have strong negative grade correlations, but there is no obvious functional relationship; At the spatial level, the overall Moran’s I index of unit ecosystem service value and ecological risk index in Jiawang District from 2000 to 2019 were negative, showing negative spatial correlation. Ecological risks and ecosystem services have obvious dislocation characteristics. ③ The heterogeneity index R of ecological restoration demand in Jiawang district presents a gradient spatial change trend to a certain extent, and the overall ecological restoration demand tends to decrease, but the R index is still too high or too low in some regions; with the increase of degree of deviation, the range of high value areas for ecological restoration needs gradually narrowed and transformed to low value areas, and the areas requiring key ecological construction tend to be more centralized. The research conclusion can provide reference for the decision-making arrangement of systematic and integrated ecological restoration of resource exhausted cities

New Heuristics for Over-Constrained Flight to Gate Assignments

We consider the over-constrained Airport Gate Assignment Problem where the number of flights exceed the number of gates available, and where the objectives are to minimize the number of ungated flights and the total walking distances. The problem is formulated as a binary quadratic programming problem. We design a greedy algorithm and use a Tabu Search meta-heuristic to solve the problem. The greedy algorithm minimizes ungated flights while we devise a new neighbourhood search technique, the Interval Exchange Move, which allows us flexibility in seeking good solutions, especially when flight schedules are dense in time. Experiments conducted give good results

Spatial–Temporal Multivariate Correlation Analysis of Ecosystem Services and Ecological Risk in Areas of Overlapped Cropland and Coal Resources in the Eastern Plains, China

The overlapped areas of cropland and coal resources play a fundamental role in promoting economic and social progress. However, intensive mining operations in high water-level areas have brought significant spatial–temporal heterogeneity and ecological problems. From the dual dimensions of the ecosystem service value (ESV) and ecological risk (ER), it is of great significance to explore the influence characteristics of underground mining on the landscape, such as above-ground cultivated land, which is valuable to achieving regional governance and coordinated development. In this study, taking Peixian as the research area, a multiple-dimensional correlation framework was constructed based on the revised ESV and ER, integrating the grey relational degree, spatial–temporal heterogeneity, disequilibrium, and inconsistency index to explore the ESV and ER assessment and correlation characteristics from 2010 to 2020. The results show that (1) the ESV showed a high agglomerated distribution pattern in the east, with a net decrease of 13.61%. (2) The ER decreased by 78.18 and was concentrated in the western and southern regions, with overall contiguous and local agglomeration characteristics. This indicates that the ecological security of the region has improved. (3) The comprehensive grey correlation between the cultural service value and the ecological risk index was the highest. Furthermore, the spatial–temporal heterogeneity of the ESV and ER weakened, and the disequilibrium rose and then fell, indicating that the ecosystem gradually tended to be stable. The study is crucial for overlapped cropland and coal resource areas to maintain stability and sustainable development. The multivariate correlation framework provides practical value for ecosystem management and risk control

Microbial Community Structure and Predictive Functional Analysis in Reclaimed Soil with Different Vegetation Types: The Example of the Xiaoyi Mine Waste Dump in Shanxi

We explored the characteristics of soil bacterial communities and their ecological functions under different types of vegetation reclamation in open-pit mines on the Loess Plateau, which is the guiding significance for the selection of vegetation and the improvement of restoration effect in mining areas. The research object was to reclaim the soil of the aluminum mine waste dump in Xiaoyi County, Shanxi. The soil characteristics were measured under different types of vegetation reclamation. The soil bacterial community under different vegetation reclamation was measured using the 16S rRNA gene high-throughput sequencing technology. The ecological function was predicted using the PICRUSt method. The correlation between soil physical and chemical properties and bacterial community structure and function was analyzed. From the results, (1) the bacterial compositions of the reclaimed soil samples were 33 phyla, 90 classes, 121 orders, 207 families, 298 genera, and 140 species. The abundance and diversity of the soil microbial community showed the rule of yellow rose > lespedeza and sweet wormwood herb > alfalfa. (2) Proteobacteria were the dominant bacteria in alfalfa and sweet wormwood herb samples, accounting for 36.09–43.36%. Proteobacteria and actinobacteria were the dominant bacteria in the yellow rose and lespedeza samples accounted for 53.34–53.39%. α-Proteobacteria, actinobacteria, and β-proteobacteria were the dominant bacteria of the four vegetation types. The relative abundance of the α-proteobacteria and β-proteobacteria was positively correlated with soil organic carbon (SOC) and negatively correlated with soil total kalium (TK). Actinobacteria were positively correlated with available kalium (AK) and negatively correlated with SOC and total nitrogen (TN). (3) There was no difference in the primary functions of the soil bacterial community after the reclamation of different plants, and the main functions were metabolism, genetic information processing, and environmental information processing, with the function abundance accounting for 81.52%. (4) The abundance of functional genes in the metabolism of other amino acids, folding, sorting, and degradation and glycan biosynthesis and metabolism were relatively rich in the rhizosphere soil of yellow rose. The abundance of functional genes in signal molecules and interaction, transport, and catabolism in the rhizosphere soil of lespedeza was the highest. The abundance of functional genes in carbohydrate metabolism, translation, and energy metabolism in the rhizosphere soil of alfalfa was the highest. Therefore, there were significant differences in the structure and function of rhizosphere soil microbial communities among yellow rose, lespedeza, sweet wormwood herb, and alfalfa, and they were also affected by the soil properties. Hence, we concluded that the differences and diversity of soil microbial structure and function can help select plants for the sustainable development of soil remediation in mining areas

Impacts of Ground Fissures on Soil Properties in an Underground Mining Area on the Loess Plateau, China

Mining-induced ground fissures are the main type of geological disasters found on the Loess Plateau, China, and cause great impacts on the soil properties around ground fissures. However, little research has been conducted on the quantitative relationship between ground fissures and changes in soil properties. To address this, 40 ground fissures in the Yungang mining area, Datong City, Shanxi Province, China, were investigated, and changes in soil properties (soil organic matter, soil moisture, field capacity, bulk density, soil porosity, and grain compositions) were revealed by the difference in soil properties between the edge and contrast points around ground fissures. Redundancy analyses were used to illustrate the relationships between the value (Si_DV) and percentage (Si_DP) of the difference in soil properties between the edge and contrast points, as well as the ground fissures. The characteristics of ground fissures that had a significant correlation according to Pearson correlation analysis with Si_DP were selected and analyzed via multivariate linear fitting model, random forest model, and Back Propagation (BP) neural network model, respectively. Results show that soil organic matter, soil moisture content, bulk density, field capacity, and the content of clay at the edge points were significantly less than those at the contrast points; conversely, soil porosity at the edge points was significantly greater. The average percentage of the difference between the edge points and contrast points of ground fissures in these six properties was 15.27%, while soil moisture content showed the greatest change (20.65%). The Si_DP was significantly correlated with the width, slope, and vegetation coverage of ground fissures; however, the vegetation coverage was the determining factor. BP neural network model had the greatest performance in revealing the relationships between ground fissures and changes in soil properties. The model for soil organic matter had the highest accuracy (R2 = 0.89), and all others were above 0.5. This research provides insights into the quantitative relationship between ground fissures and their impacts on soil physical properties, which can be used in conjunction with remote sensing images to rapidly assess soil erosion risks caused by mining on a large scale, given that soil physical properties are closely related to topsoil stability

Comparison of Soil Bacterial Communities under Canopies of <i>Pinus tabulaeformis</i> and <i>Populus euramericana</i> in a Reclaimed Waste Dump

To compare the effects of different remediation tree species on soil bacterial communities and provide a theoretical basis for the selection of ecosystem function promotion strategies after vegetation restoration, the characteristic changes in soil bacterial communities after Pinus tabulaeformis and Populus euramericana reclamation were explored using high-throughput sequencing and molecular ecological network methods. The results showed that: (1) With the increase in reclamation years, the reclaimed soil properties were close to the control group, and the soil properties of Pinus tabulaeformis were closer to the control group than those of P. euramericana. (2) The dominant bacteria under the canopies of P. tabulaeformis and P. euramericana was the same. Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Gemmatimonadetes, Planctomycetes, Bacteroidetes, and Cyanobacteria were the dominant bacteria in the restored soil, accounting for more than 95% of the total abundance. The average values of the Shannon diversity index, Simpson diversity index, Chao 1 richness estimator, and abundance-based coverage estimator of the bacterial community in the P. euramericana reclaimed soil were higher than those in the P. tabulaeformis reclaimed soil. The influence of reclamation years on the bacterial community of samples is greater than that of species types. (3) The results of ecological network construction showed that the total number of nodes, total number of connections, and average connectivity of the soil bacterial network under P. euramericana reclamation were greater than those under P. tabulaeformis reclamation. The bacterial molecular ecological network under P. euramericana was more abundant. (4) Among the dominant bacteria, the relative abundance of Actinobacteria was negatively correlated with soil pH, soil total nitrogen content, and the activities of urease, invertase, and alkaline phosphatase, while the relative abundance of Proteobacteria and Bacteroidetes was positively correlated with these environmental factors. The relationship between the soil bacterial community of P. tabulaeformis and P. euramericana and the environmental factors is not completely the same, and even the interaction between some environmental factors and bacteria is opposite

Detecting long-term effects of mining-induced ground deformation on plant succession in semi-arid areas using a cellular automata model

Mining-induced ground deformation affects various plant communities in different ways. However, little is known about the effects of ground deformation on plant succession; no known quantitative approach currently exists to detecting the long-term effects. To address this issue, a plant community succession model based on cellular automata was developed. Plant succession over 30 years within a subsidence area in the Yungang mining area in China was simulated and compared under mining and non-mining scenarios, including under two sets of initial conditions (vegetated and bare). The normalized mean square error was applied to test the accuracy of the plant community succession model and to reveal the effects of ground deformation at the patch scale, which was 0.06–0.59 for simulated and observed plant patterns. Landscape indicators including contagion, patch cohesion, interspersion and juxtaposition, Shannon’s diversity, Shannon’s evenness, and aggregation indices were calculated and compared to reveal the effects of mine subsidence at the landscape scale. The results showed that the interspersion and juxtaposition, Shannon’s diversity, Shannon’s evenness, and aggregation indices were significantly influenced by ground deformation (P < 0.05) under vegetated conditions, indicating that ground deformation resulted in a loose, isolated, and mixed pattern of vegetation. In terms of the shrub and tree communities, the normalized mean square errors fluctuated at a high level under bare conditions, especially at the patch scale of 10 × 10 m, where it remained at greater than 0.5. Overall, mining-induced ground deformation had long-term effects on plant succession by limiting tree communities and promoting shrub communities, as well as by leading to a heterogenous vegetation pattern. Ground deformation altered the topography of the previously mined area, influencing hydrological processes such as rainfall, infiltration, and evaporation, which were closely related to plant succession. Although these long-term effects were not directly a result of ground deformation, changes in the topography of a subsidence area would interfere with the spontaneous succession of plant communities. Therefore, the long-term effects of mining-induced ground deformation should be considered during the ecological restoration of a mining area, which can promote the application of nature-based solutions and the natural regeneration of plant communities

Targeting the Influences of Under-Lake Coal Mining Based on the Value of Wetland Ecosystem Services: What and How?

Under the growing restrictions of the Chinese eco-environmental policies, the impact of under-lake coal mining on wetlands is receiving increasing attention from both coal mining enterprises and local governments. This paper focuses on the impact of under-lake coal mining on the Nansi Lake wetland from 1991 to 2021. Field measurements, resident surveys, and remote sensing inversion were comprehensively employed to quantitatively assess the impact. The calculation of the assessment indicators refers to the elastic coefficient, the information for which comes from four major categories of ecosystem service values (ESVs) and eight sub-ESVs. According to the results of the remote sensing interpretation and inversion, by 2021 the range had enlarged by 32.3 km2, and the water depth had increased by 1.9 m in the mining-disturbed area relative to 1991. The ESV fluctuations in the Nansi Lake wetland also exhibited a generally increasing trend over time. Our results show that the under-lake mining disturbs the ESVs, but the disturbance is not sufficient to result in significant consequences. Based on the data analysis, we suggest several well-directed, appropriate restoration strategies to achieve the desired objectives and target the response of the ESV changes. Such measures will help to relieve some of the anxiety and concern about the wetland changes caused by the under-lake mining