Search Results (99)

To investigate the impact of sand-laden flow on energy loss in Francis turbines, this study integrates entropy generation theory with numerical simulations conducted using ANSYS CFX. The mixture multiphase flow model and the SST k-ω turbulence model are employed to simulate the solid–liquid two-phase flow throughout the entire flow passage of the turbine at the Gengda Hydropower Station (Minjiang River Basin section, 103°17′ E and 31°06′ N). The energy loss characteristics under different off-design conditions are analyzed on the basis of the average sediment concentration during the flood season (2.9 kg/m³) and a median particle diameter of 0.058 mm. The results indicate that indirect entropy generation and wall entropy generation are the primary contributors to total energy loss, while direct entropy generation accounts for less than 1%. As the guide vane opening increases, the proportion of wall entropy generation initially rises and then decreases, while the total indirect entropy generation exhibits a non-monotonic trend dominated by the flow pattern in the draft tube. Entropy generation on the runner walls increases steadily with larger openings, whereas entropy generation on the draft tube walls first decreases and then increases. The variation in entropy generation on the guide vanes remains relatively small. These findings provide technical support for the optimal design and operation of turbines in sediment-rich rivers. Full article

Some knowledge bases (KBs) extracted from Wikipedia articles can achieve very high average precision values (over 95% in DBpedia). However, subtle mistakes including inconsistencies, outliers, and erroneous relations are usually ignored in the construction of KBs by extraction rules. Automatic detection and correction of these subtle errors is important for improving the quality of KBs. In this paper, an inductive logic programming with exceptional information (EILP) is proposed to automatically detect errors in large knowledge bases (KBs). EILP leverages the exceptional information problems that are ignored in conventional rule-learning algorithms such as inductive logic programming (ILP). Furthermore, an inductive logical correction method with exceptional features (EILC) is proposed to automatically correct these mistakes by learning a set of correction rules with exceptional features, in which respective metrics are provided to validate the revised triples. The experimental results demonstrate the effectiveness of EILP and EILC in detecting and repairing large knowledge bases, respectively. Full article

The Dujiangyan–Siguniangshan mountain rack railway project is China’s first mountain rail transit. Most of its lines are located in mountainous areas and close to natural ecological protection areas, which have strict restrictions on the vibration and noise of train operation. At the same time, the vibration of mountain rack railway trains is also an important factor affecting the safety and riding comfort of trains. However, due to the multi-source vibration of gear teeth, wheels, rails, and suspensions, it is difficult to clearly define the vibration characteristics and vibration transmission path of the train, which has a serious impact on its vibration noise suppression and optimization. To this end, this study proposed a set of evaluation methods for the vibration characteristics and transfer paths of mountain rack trains based on a combination of dynamics and operational transfer path analysis (OTPA). Considering the interaction between the dynamic behaviors of the primary and secondary suspensions, the gear tooth contact behavior, the wheel–rail contact behavior and the dynamic behaviors of the track system, a dynamic model of a mountain rack train based on the finite element method was established, and the effectiveness of the model was verified through field experiments. On this basis, the OTPA method was used to establish a vibration transfer path model between the secondary suspension and the center of mass of the car body, and it was used to analyze the vibration mechanism and transfer path of the train body at the rated speed (20 km/h) and the limited speed (30 km/h). This study is of great significance for suppressing the vibration noise of mountain rack trains, reducing the impact on the ecological environment and improving ride comfort. Full article

A megaproject is a complex technological-social-natural system, and its “double-edged sword” effect raises significant attention in research on system sustainability. However, prior studies often overlook the long-term characteristics of megaprojects, while paradox provides an effective lens for explaining their long-term evolution. Guided by a “context-cognition-action” analytical frame, this study employs an inductive and longitudinal case study approach to investigate the value creation process of a typical megaproject, focusing on paradoxical cognition, adaptive strategies, and core drivers of system sustainability. The findings reveal that “macro demand-tension cognition-adaptive governance” is an efficient pathway for value creation under dynamic contexts. Importantly, paradoxical cognition uncovers multi-level tensions (macro, meso, micro) in value creation, with a complex shift from a single layer to a nested structure as macro demands intensify. Correspondingly, adaptive strategies exhibit distinct logic: from reactive strategies to proactive strategies. This shift drives the evolution from the “Project–City–Environment” composite system to the “Project–City–Environment–Region” complex giant system. Furthermore, the evolution of responsibility is the core driver of system sustainability, characterized by a transition from intragenerational equity to intergenerational obligations driven by technological advancements. This study advances theoretical understanding of value creation and provides practical insights into the sustainable development of future megaprojects. Full article

Emerging radar sensing technology is revolutionizing cardiovascular monitoring by eliminating direct skin contact. This approach captures vital signs through electromagnetic wave reflections, enabling contactless blood pressure (BP) tracking while maintaining user comfort and privacy. We present a hierarchical neural framework that synergizes spatial and temporal feature learning for radar-driven, contactless BP monitoring. By employing advanced preprocessing techniques, the system captures subtle chest wall vibrations and their second-order derivatives, feeding dual-channel inputs into a hierarchical neural network. Specifically, Stage 1 deploys convolutional depth-adjustable lightweight residual blocks to extract spatial features from micro-motion characteristics, while Stage 2 employs a transformer architecture to establish correlations between these spatial features and BP periodic dynamic variations. Drawing on the intrinsic link between systolic (SBP) and diastolic (DBP) blood pressures, early estimates from Stage 2 are used to expand the feature set for the second-stage network, boosting its predictive power. Validation achieved clinically acceptable errors (SBP: −1.09 ± 5.15 mmHg, DBP: −0.26 ± 4.35 mmHg). Notably, this high degree of accuracy, combined with the ability to estimate BP at 2 s intervals, closely approximates real-time, beat-to-beat monitoring, representing a pivotal breakthrough in non-contact BP monitoring. Full article

Background/Objectives: Blood is an essential component of the immune system. As post-transcriptional regulators, miRNAs, abundant in blood, are necessary aspects in blood’s immune and physiological functions. However, there is limited knowledge about the expression and function of miRNAs in the blood of giant pandas. Methods: We comparatively analyzed miRNA expression profiles in the blood of giant pandas of different ages using small-RNA sequencing technology. Results: We identified 393 known miRNAs, 219 conserved miRNAs, and 71 novel miRNAs in the blood of giant pandas, and functional enrichment analysis showed that the genes regulated by DE (differentially expressed) miRNAs were mainly enriched in the regulation of enzyme-linked receptor protein signaling pathways and the signaling pathways of MAPK, Hippo, and FoXO. Conclusions: Our study clarified giant pandas’ blood miRNA expression profiles at different developmental stages, which will help elucidate the blood immunity and regulation of blood cell physiological functions in giant pandas. Full article

Against the backdrop of rapid urbanization, associated environmental problems, including low resource consumption, severe pollution emissions, and low environmental awareness, have become salient. The key to achieving sustainable development in Ya’an lies in accelerating the development of new urbanization while ensuring the preservation of existing ecological advantages. Firstly, this study constructs evaluation index systems for new urbanization and the ecological environment using the Population–Economic–Spatial–Social (PESS) and Pressure–State–Response (PSR) models, respectively. Then, the entropy weight model is used to calculate weights for each secondary indicator of the new urbanization and ecological environment systems. The coupling coordination degree (CCD) and relative development degree (RDD) models are applied to analyze spatial and temporal changes in new urbanization and the ecological environment in Ya’an from 2011 to 2021. Finally, spatial autocorrelation and geographically weighted regression (GWR) models are combined to analyze the factors influencing coupling coordination degree differences among Ya’an’s districts and counties. The results indicate the following: (1) From 2011 to 2021, the CCD of Ya’an shifted from basically balanced to highly balanced, and RDD shifted from new urbanization lag to systematic balanced. (2) The CCD of Ya’an varies significantly among regions, and the spatial differentiation of the effects of different factors has different characteristics. Full article

With the growth of the global population and the acceleration of industrialization, the problem of water pollution has become increasingly serious, posing a major threat to the ecosystem and human health. Traditional water treatment technologies make it difficult to cope with complex pollution, so the scientific community is actively exploring new and efficient treatment methods. Biochar (BC), as a low-cost, green carbon-based material, exhibits good adsorption and catalytic properties in water treatment due to its porous structure and abundant active functional groups. However, BC’s pure adsorption or catalytic capacity is limited, and researchers have dramatically enhanced its performance through modification means, such as loading metals or heteroatoms. In this paper, we systematically review the recent applications of BC and its modified materials for water treatment in adsorption, Fenton-like, electrocatalytic, photocatalytic, and sonocatalytic systems, and discuss their adsorption/catalytic mechanisms. However, most of the research in this field is at the laboratory simulation stage and still needs much improvement before it can be applied in large-scale wastewater treatment. This review improves the understanding of the pollutant adsorption/catalytic properties and mechanisms of BC-based materials, analyzes the limitations of the current studies, and investigates future directions. Full article

Climate and land-use change are key factors of vegetation dynamics, and impacts arising from both of them need to be further studied. This study simulated the fraction of vegetation coverage in 2050 through coupling the Patch-Generating Land Use Simulation (PLUS) model and the Dimidiate Pixel model and explored the effects of climate and land-use change on fraction vegetation coverage in the Chengdu-Chongqing Economic Circle region. The findings indicated that: (1) fraction vegetation coverage was mainly restored over the 2000–2020 period, accounting for 59.38% of the investigation area. Under the SSP245 and SSP585 scenarios, fraction vegetation coverage increased by 40.57% and 46.38%, respectively. (2) under the SSP245 and SSP585 scenarios, the superposition effect of climate and land use change on fraction vegetation coverage significantly outweighed the compensation effect. Specifically, the superposition effect of climate and land use change on fraction vegetation cover accounted for 90.69% and 90.57% of the total area, respectively. Conversely, the compensation effect constituted a relatively minor proportion, representing 9.31% and 9.43% of the total area, respectively. (3) the positive superposition effect of climate changes and land use on fraction vegetation coverage was 35.47% and 40.90%, respectively, while the negative superposition effect was 55.22% and 49.67%, respectively. These findings aimed to offer guidance for the execution of vegetation restoration initiatives in the upstream region. Full article

Xishu Gardens embodies the essence of traditional Chinese landscape design, boasting unique cultural heritage and local charm. However, research on it is often limited to the aesthetic aspects of gardens, lacking the scientific analysis of garden spaces. This paper explores Xishu Gardens through the lens of space syntax, a method commonly used for analyzing architectural features. The focus is Qingxi Garden, located within the Dujiangyan Scenic Area. It is one of the representative gardens of Xishu Gardens. Based on field investigation and spatial mapping, Qingxi Garden was digitally reconstructed for the first time followed by a detailed analysis in open-source software DepthmapX 0.8.0. This analysis involved a meticulous examination of the garden’s pathways and spatial elements, integrating on-site measurements and survey data to ensure precision. By conducting a quantitative analysis of the spatial structure of Qingxi Garden, the results indicate that areas with low visible depth, as well as high road connectivity and integration, are more accessible to visitors. This accessibility serves as the central spatial node within Qingxi Garden, where a collection of bonsai is prominently exhibited. The interplay between spatial features in the landscape and architectural spaces can significantly influence tourist activities. The landscape architecture of the garden features the distinctive ventilated lattice design characteristic of West Shu gardens, providing visitors with a comfortable spatial experience. The design of Qingxi Garden not only inherits the natural design principles of West Shu gardens but also scientifically integrates the spatial layout of bonsai exhibitions. The design of Qingxi Garden draws upon the traditional garden-making techniques of the Xishu region while also respecting the natural topography of the site. It incorporates local cultural elements, such as bonsai, into its framework. The arrangement of the bonsai exhibition is executed in a scientific and rational manner. Qingxi Garden aims to achieve a harmonious integration of natural beauty and cultural aesthetics in its design, resulting in a garden landscape that is both visually appealing and rich in cultural significance. The design principles and methodologies employed offer a novel perspective for contemporary garden design. Full article

To explore the mechanical properties and fracture modes of basalt fiber-reinforced concrete, single-doped and hybrid-doped basalt fiber-reinforced concrete was prepared, and uniaxial failure tests under different basalt fiber-reinforced concrete contents were carried out. At the same time, the smooth kernel function in the traditional SPH method was improved, and the basalt fiber random generation algorithm was embedded in the SPH program to realize the simulation of the progressive failure of basalt fiber-reinforced concrete. The results show that under the circumstance with no basalt fiber, the specimen final failure mode is damage on the upper and lower surface, as well as the side edge, while the interior of the specimen center is basically intact, indicating that there is an obvious stress concentration phenomenon on the upper and lower surface when the specimen is compressed. Under the circumstance with basalt fiber, longitudinal cracks begin to appear inside the specimen. With the increase in the content, the crack location gradually develops from the edge to the middle, and the crack number gradually increases. This indicates that appropriately increasing the fiber content in concrete may improve the stress state of concrete, change the eccentric compression to axial compression, and indirectly increase the compressive strength of concrete. The numerical simulation results are consistent with the test results, verifying the rationality of the numerical simulation algorithm. For the concrete model without the basalt fiber, shear cracks are generated around the model. For the concrete model with basalt fiber, in addition to shear cracks, the tensile cracks generated at the basalt fiber inside the model eventually lead to the splitting failure of the model. The strength of concrete samples with basalt content of 0.1%, 0.2%, and 0.3% is increased by 1.69%, 5.10%, and 4.31%, respectively, compared to the concrete sample without basalt fiber. It can be seen that with the increase in the content of single-doped basalt fiber, the concrete strength is improved to a certain extent, but the improvement degree is not high; For hybrid-doped basalt fiber-reinforced concrete, the strength of concrete samples with basalt content of 0.1%, 0.2%, and 0.3% is increased by 14.51%, 15.02%, and 30.31%, respectively, compared to the concrete sample without basalt fiber. Therefore, compared with the single-doped basalt fiber process, hybrid doping is easier to improve the strength of concrete. Full article

Non-grain-producing cultivated land (NGPCL) greatly affects sustainable agricultural development and food security, and its consolidation is important. With the Dujiangyan irrigation district as an example, an empirical study of NGPCL consolidation zoning was performed following the idea of “connotation definition and classification—potential identification—consolidation zoning”. On the basis of expert evaluation, NGPCL was classified into three levels according to the degree of damage to cultivated land by crop type. NGPCL was common in the study area, accounting for 53.8% of the total area. The spatial pattern of NGPCL was characterized as “continuous in the south and scattered in the north”. The assessment of theoretical and realistic NGPCL consolidation potentials suggested that areas with medium consolidation potential exhibited a contiguous distribution in the southern part of the study area, whereas it was dispersed in other regions. The proportion of area suitable for consolidation exceeded 40%. Finally, through a multiobjective optimization algorithm, a potential zoning scheme for NGPCL consolidation was constructed. The final experimental results revealed that the areas with medium or high consolidation potential accounted for 97.54% of the total area. This study is useful for supporting the governance of NGPCL. Full article

Hyperparameter tuning is crucial in the development of machine learning models. This study introduces the nonlinear shrinking factor and the Cauchy mutation mechanism to improve the Dujiangyan Irrigation System Optimization (DISO), proposing the improved Dujiangyan Irrigation System Optimization algorithm (IDISO) for hyperparameter tuning in machine learning. The optimization capabilities and convergence performance of IDISO were validated on 87 CEC2017 benchmark functions of varying dimensions and nine real-world engineering problems, demonstrating that it significantly outperforms DISO in terms of convergence speed and accuracy, and ranks first in overall performance among the seventeen advanced metaheuristic algorithms being compared. To construct a robust and generalizable prediction model for hydrochar element characteristics, this study utilized IDISO and DISO algorithms to fine-tune the parameters of the XGBoost model. The experimental results show that the IDISO-XGBoost model achieved an average prediction performance of 0.95, which represents a 4% improvement over the DISO-XGBoost model. These results indicate that the IDISO algorithm has significant potential and value in practical applications. Full article

After a landslide, swift and precise identification of the affected area is paramount for facilitating urgent rescue operations and damage assessments. This is particularly vital for land use planners and policymakers, enabling them to efficiently address hazard mitigation, the resettlement of those affected by the hazards, and to strategize land planning in the impacted regions. Despite the importance, conventional methods of monitoring landslides often fall short due to their restricted scope and the challenges associated with data acquisition. This study proposes a landslide detection method based on unsupervised multisource and target domain adaptive image segmentation (LUDAS) that is capable of achieving robust and generalized landslide mapping across multiple sources and target domains. Specifically, LUDAS consists of two phases. In the first phase, we introduce an unsupervised interdomain translation network to align the styles of multiple source domains to multiple target domains, generating pseudotarget domain data. Our interdomain translation network is capable of style transfer between any two domains. Through careful design of the network structure and loss functions, we ensure effective style transfer while preserving the content structure of the source domain images. In the second phase, the landslide segmentation model is trained in a supervised manner using annotated data from multiple source domains and multiple pseudotarget domains, resulting in a model with strong generalization capabilities that can adapt to multiple source and target domains. Finally, through extensive qualitative and quantitative analysis experiments, our study confirms that the proposed domain-adaptive segmentation model not only achieves exceptional landslide segmentation performance across multiple target domains but also, due to its good generalizability and transferability, has great potential for application in the emergency response to landslide. This capability can provide strong support for post-disaster emergency rescue, disaster assessment, and land planning in areas with scarce data. Full article

Red pandas evolved from carnivores to herbivores and are unique within Carnivora. Red pandas and carnivorous mammals consume milk during the suckling period, while they consume bamboo and meat during the adult period, respectively. Red pandas and carnivorous mammal ferrets have a close phylogenetic relationship. To further investigate the molecular mechanisms of dietary changes and nutrient utilization in red pandas from suckling to adult, comparative analysis of the whole transcriptome was performed on stomach tissues from red pandas and ferrets during the suckling and adult periods. The main results are as follows: (1) we identified ncRNAs for the first time in stomach tissues of both species, and found significant expression changes of 109 lncRNAs and 106 miRNAs in red pandas and 756 lncRNAs and 109 miRNAs in ferrets between the two periods; (2) up-regulated genes related to amino acid transport regulated by lncRNA-miRNA-mRNA networks may efficiently utilize limited bamboo amino acids in adult red pandas, while up-regulated genes related to amino acid degradation regulated by lncRNAs may maintain the balance of amino acid metabolism due to larger daily intakes in adult ferrets; and (3) some up-regulated genes related to lipid digestion may contribute to the utilization of rich nutrients in milk for the rapid growth and development of suckling red pandas, while up-regulated genes associated with linoleic acid metabolism regulated by lncRNA-miRNA-mRNA networks may promote cholesterol decomposition to reduce health risks for carnivorous adult ferrets. Collectively, our study offers evidence of gene expression adaptation and ncRNA regulation in response to specific dietary changes and nutrient utilization in red pandas during suckling and adult periods. Full article