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  • MDPI AG  (124)
  • 1
    Online Resource
    Online Resource
    Heat Transfer Model of Natural Gas Pipeline Based on Data Feature Extraction and First Principle Models
    MDPI AG ; 2023
    In:  Energies Vol. 16, No. 3 ( 2023-01-19), p. 1096-
    Details
    In: Energies, MDPI AG, Vol. 16, No. 3 ( 2023-01-19), p. 1096-
    Abstract: The rapid development of natural gas pipelines has highlighted the need to utilize SCADA (supervisory control and data acquisition) system data. In this paper, a heat transfer model of a natural gas pipeline based on data feature extraction and first principle models, which makes full use of the measured temperatures at each end of the pipeline, is proposed. Three methods, the NARX neural network (nonlinear autoregressive neural network with exogenous inputs), time series decomposition, and system identification, were used to model the changes of gas temperatures of the pipeline. The NARX neural network method uses a cyclic neural network to directly model the relationship of temperature between the start and the end of the pipeline. The measured temperature series at the pipeline inlet and outlet were decomposed into trend items, fluctuation items, and noise items based on the time series decomposition method. Then the three items were fitted separately and combined to form a new temperature prediction series. The system identification method constructed the first-order and second-order transfer function to model the temperature. The simulation of the three data-driven models was compared with those of the physics-based simulation models. The results showed that the data-driven model has great advantages over the physics-based simulation models in both accuracy and efficiency. The proposed models are more suitable for applications such as online simulation and state observation of long-distance natural gas pipelines.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en16031096
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2437446-5
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  • 2
    Online Resource
    Online Resource
    Environmental Risk Assessment of Metals in the Volcanic Soil of Changbai Mountain
    MDPI AG ; 2019
    In:  International Journal of Environmental Research and Public Health Vol. 16, No. 11 ( 2019-06-10), p. 2047-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 16, No. 11 ( 2019-06-10), p. 2047-
    Abstract: Tianchi volcano is a dormant active volcano with a risk of re-eruption. Volcanic soil and volcanic ash samples were collected around the volcano and the concentrations of 21 metals (major and trace elements) were determined. The spatial distribution of the metals was obtained by inverse distance weight (IDW) interpolation. The metals’ sources were identified and their pollution levels were assessed to determine their potential ecological and human health risks. The metal concentrations were higher around Tianchi and at the north to the west of the study area. According to the geo-accumulation index (Igeo), enrichment factor (EF) and contamination factor (CF) calculations, Zn pollution was high in the study area. Pearson’s correlation analysis and principal component analysis showed that with the exception of Fe, Mn and As, the metals that were investigated (Al, K, Ca, Na, Mg, Ti, Cu, Pb, Zn, Cr, Ni, Ba, Ga, Li, Co, Cd, Sn, Sr) were mostly naturally derived. A small proportion of Li, Pb and Zn may have come from vehicle traffic. There is no potential ecological risk and non-carcinogenic risk because of the low concentrations of the metals; however, it is necessary to pay attention to the carcinogenic risk of Cr and As in children.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph16112047
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2175195-X
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  • 3
    Online Resource
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    Cytotoxicity of Biodegradable Zinc and Its Alloys: A Systematic Review
    MDPI AG ; 2023
    In:  Journal of Functional Biomaterials Vol. 14, No. 4 ( 2023-04-07), p. 206-
    Details
    In: Journal of Functional Biomaterials, MDPI AG, Vol. 14, No. 4 ( 2023-04-07), p. 206-
    Abstract: Zinc-based biodegradable metals (BMs) have been developed for biomedical implant materials. However, the cytotoxicity of Zn and its alloys has caused controversy. This work aims to investigate whether Zn and its alloys possess cytotoxic effects and the corresponding influence factors. According to the guidelines of the PRISMA statement, an electronic combined hand search was conducted to retrieve articles published in PubMed, Web of Science, and Scopus (2013.1–2023.2) following the PICOS strategy. Eighty-six eligible articles were included. The quality of the included toxicity studies was assessed utilizing the ToxRTool. Among the included articles, extract tests were performed in 83 studies, and direct contact tests were conducted in 18 studies. According to the results of this review, the cytotoxicity of Zn-based BMs is mainly determined by three factors, namely, Zn-based materials, tested cells, and test system. Notably, Zn and its alloys did not exhibit cytotoxic effects under certain test conditions, but significant heterogeneity existed in the implementation of the cytotoxicity evaluation. Furthermore, there is currently a relatively lower quality of current cytotoxicity evaluation in Zn-based BMs owing to the adoption of nonuniform standards. Establishing a standardized in vitro toxicity assessment system for Zn-based BMs is required for future investigations.
    Type of Medium: Online Resource
    ISSN: 2079-4983
    URL: Article
    DOI: 10.3390/jfb14040206
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2648525-4
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  • 4
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    Time-Series Neural Network: A High-Accuracy Time-Series Forecasting Method Based on Kernel Filter and Time Attention
    MDPI AG ; 2023
    In:  Information Vol. 14, No. 9 ( 2023-09-13), p. 500-
    Details
    In: Information, MDPI AG, Vol. 14, No. 9 ( 2023-09-13), p. 500-
    Abstract: This research introduces a novel high-accuracy time-series forecasting method, namely the Time Neural Network (TNN), which is based on a kernel filter and time attention mechanism. Taking into account the complex characteristics of time-series data, such as non-linearity, high dimensionality, and long-term dependence, the TNN model is designed and implemented. The key innovations of the TNN model lie in the incorporation of the time attention mechanism and kernel filter, allowing the model to allocate different weights to features at each time point, and extract high-level features from the time-series data, thereby improving the model’s predictive accuracy. Additionally, an adaptive weight generator is integrated into the model, enabling the model to automatically adjust weights based on input features. Mainstream time-series forecasting models such as Recurrent Neural Networks (RNNs) and Long Short-Term Memory Networks (LSTM) are employed as baseline models and comprehensive comparative experiments are conducted. The results indicate that the TNN model significantly outperforms the baseline models in both long-term and short-term prediction tasks. Specifically, the RMSE, MAE, and R2 reach 0.05, 0.23, and 0.95, respectively. Remarkably, even for complex time-series data that contain a large amount of noise, the TNN model still maintains a high prediction accuracy.
    Type of Medium: Online Resource
    ISSN: 2078-2489
    URL: Article
    DOI: 10.3390/info14090500
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2599790-7
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  • 5
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    Online Resource
    Typhoon Resistance Analysis of Offshore Wind Turbines: A Review
    MDPI AG ; 2022
    In:  Atmosphere Vol. 13, No. 3 ( 2022-03-10), p. 451-
    Details
    In: Atmosphere, MDPI AG, Vol. 13, No. 3 ( 2022-03-10), p. 451-
    Abstract: A typhoon is a tropical cyclone in the western Pacific Ocean and the China seas. Typhoons are some of the most destructive natural disasters on Earth. In China, typhoons have had major impacts on the stability and structural integrity of offshore wind turbines in the complex and harsh marine environment. In this research, first, the main causes of wind turbine damage were analyzed based on the characteristics of a typhoon and a wind turbine structure for typical typhoon-induced accidents. Second, the research progress of the anti-typhoon design of offshore wind turbines and the anti-typhoon strategy of wind farms operation and maintenance was summarized. Finally, the problems to be further solved in these research fields were presented to provide references for the development of offshore wind turbines, in particular, floating wind turbines in typhoon-prone areas.
    Type of Medium: Online Resource
    ISSN: 2073-4433
    URL: Article
    DOI: 10.3390/atmos13030451
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2605928-9
    SSG: 23
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  • 6
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    Rainfall Induced Landslide Susceptibility Mapping Based on Bayesian Optimized Random Forest and Gradient Boosting Decision Tree Models—A Case Study of Shuicheng County, China
    MDPI AG ; 2020
    In:  Water Vol. 12, No. 11 ( 2020-11-02), p. 3066-
    Details
    In: Water, MDPI AG, Vol. 12, No. 11 ( 2020-11-02), p. 3066-
    Abstract: Among the most frequent and dangerous natural hazards, landslides often result in huge casualties and economic losses. Landslide susceptibility mapping (LSM) is an excellent approach for protecting and reducing the risks by landslides. This study aims to explore the performance of Bayesian optimization (BO) in the random forest (RF) and gradient boosting decision tree (GBDT) model for LSM and applied in Shuicheng County, China. Multiple data sources are used to obtain 17 conditioning factors of landslides, Borderline-SMOTE and Randomundersample methods are combined to solve the imbalanced sample problem. RF and GBDT models before and after BO are adopted to calculate the susceptibility value of landslides and produce LSMs and these models were compared and evaluated using multiple validation approach. The results demonstrated that the models we proposed all have high enough model accuracy to be applied to produce LSM, the performance of the RF is better than the GBDT model without BO, while after adopting the Bayesian optimized hyperparameters, the prediction accuracy of the RF and GBDT models is improved by 1% and 7%, respectively and the Bayesian optimized GBDT model is the best for LSM in this four models. In summary, the Bayesian optimized RF and GBDT models, especially the GBDT model we proposed for landslide susceptibility assessment and LSM construction has a very good application performance and development prospects.
    Type of Medium: Online Resource
    ISSN: 2073-4441
    URL: Article
    DOI: 10.3390/w12113066
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2521238-2
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  • 7
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    Comparison of Soluble Dietary Fibers Extracted from Ten Traditional Legumes: Physicochemical Properties and Biological Functions
    MDPI AG ; 2023
    In:  Foods Vol. 12, No. 12 ( 2023-06-12), p. 2352-
    Details
    In: Foods, MDPI AG, Vol. 12, No. 12 ( 2023-06-12), p. 2352-
    Abstract: Soluble dietary fibers (SDFs) exist as the major bioactive components in legumes, which exhibit various biological functions. To improve the potential applications of legume SDFs as healthy value-added products in the functional food industry, the physicochemical properties and biological functions of SDFs from ten selected traditional legumes, including mung bean, adzuki bean, red bean, red sword bean, black bean, red kidney bean, speckled kidney bean, common bean, white hyacinth bean, and pea, were studied and compared. Results showed that the physicochemical properties of SDFs varied in different species of legumes. All legume SDFs almost consisted of complex polysaccharides, which were rich in pectic-polysaccharides, e.g., homogalacturonan (HG) and rhamnogalacturonan I (RG I) domains. In addition, hemicelluloses, such as arabinoxylan, xyloglucan, and galactomannan, existed in almost all legume SDFs, and a large number of galactomannans existed in SDFs from black beans. Furthermore, all legume SDFs exhibited potential antioxidant, antiglycation, immunostimulatory, and prebiotic effects, and their biological functions differed relative to their chemical structures. The findings can help reveal the physicochemical and biological properties of different legume SDFs, which can also provide some insights into the further development of legume SDFs as functional food ingredients.
    Type of Medium: Online Resource
    ISSN: 2304-8158
    URL: Article
    DOI: 10.3390/foods12122352
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704223-6
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  • 8
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    Discrete Element Simulation of the Macro-Meso Mechanical Behaviors of Gas-Hydrate-Bearing Sediments under Dynamic Loading
    MDPI AG ; 2022
    In:  Journal of Marine Science and Engineering Vol. 10, No. 8 ( 2022-07-29), p. 1042-
    Details
    In: Journal of Marine Science and Engineering, MDPI AG, Vol. 10, No. 8 ( 2022-07-29), p. 1042-
    Abstract: Under the action of dynamic loadings such as earthquakes and volcanic activities, the mechanical properties of gas-hydrate-bearing sediments will deteriorate, leading to a decrease in the stability of hydrate reservoirs and even inducing geological disasters such as submarine landslides. In order to study the effect of dynamic loading on the mechanical properties of hydrate sediments, triaxial compression tests of numerical specimens were carried out by using particle flow code (PFC2D), and the macro-meso mechanical behaviors of specimens were investigated. The results show that the loading frequency has a small effect on the stiffness of the hydrate sediment, while it has a large effect on the peak strength. The peak strength increases and then decreases with the increase in loading frequency. Under the same loading frequency, the peak strength of the hydrate sediment increases with the increase in loading amplitude, and the stiffness of the specimen decreases with the increase in loading amplitude. The maximum shear expansion of the specimen changes with the movement of the phase change point and the rearrangement of the particles. The maximum shear expansion of the specimen changes with the movement of the phase change point and the change of the bearing capacity of the particles after the rearrangement, and the more forward the phase change point is, the stronger the bearing capacity of the specimen in the plastic stage. The shear dilatancy angle and the shear dilatancy amount both increase linearly with the increase in loading amplitude. The influence of loading frequency and amplitude on the contact force chain, displacement, crack expansion, and the number of cementation damage inside the sediment is mainly related to the average axial stress to which the specimen is subjected, and the number of cracks and cementation damage of the sediment specimen increases with the increase in the average axial stress to which the sediment specimen is subjected. As the rate of cementation damage increases, the distribution of shear zones becomes more obvious.
    Type of Medium: Online Resource
    ISSN: 2077-1312
    URL: Article
    DOI: 10.3390/jmse10081042
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2738390-8
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  • 9
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    Polarization Attack on Continuous-Variable Quantum Key Distribution with a Local Local Oscillator
    MDPI AG ; 2022
    In:  Entropy Vol. 24, No. 7 ( 2022-07-18), p. 992-
    Details
    In: Entropy, MDPI AG, Vol. 24, No. 7 ( 2022-07-18), p. 992-
    Abstract: The estimation of phase noise of continuous-variable quantum key distribution protocol with a local local oscillator (LLO CVQKD), as a major process in quantifying the secret key rate, is closely relevant to the intensity of the phase reference. However, the transmission of the phase reference through the insecure quantum channel is prone to be exploited by the eavesdropper (Eve) to mount attacks. Here, we introduce a polarization attack scheme against the phase reference. Presently, in a practical LLO CVQKD system, only part of the phase reference pulses are measured to compensate for the polarization drift of the quantum signal pulses in a compensation cycle due to the limited polarization measurement rate, while the other part of the phase reference pulses are not measured. We show that Eve can control the phase noise by manipulating the polarization direction of the unmeasured phase reference to hide her attack on the quantum signal. Simulations show that Eve can obtain partial or total key rates information shared between Alice and Bob as the transmission distance increases. Improving the polarization measurement rate to 100% or monitoring the phase reference intensity in real-time is of great importance to protect the LLO CVQKD from polarization attack.
    Type of Medium: Online Resource
    ISSN: 1099-4300
    URL: Article
    DOI: 10.3390/e24070992
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2014734-X
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  • 10
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    Trade-Offs Analysis of Ecosystem Services for the Grain for Green Program: Informing Reforestation Decisions in a Mountainous Headwater Region, Northeast China
    MDPI AG ; 2020
    In:  Sustainability Vol. 12, No. 11 ( 2020-06-11), p. 4762-
    Details
    In: Sustainability, MDPI AG, Vol. 12, No. 11 ( 2020-06-11), p. 4762-
    Abstract: The effects of forest restoration on ecosystem services and their trade-offs are increasingly discussed by environmental managers and ecologists, but few demonstrations have analyzed ecosystem service trade-offs with a view to informing afforestation choices. Here, we examined how the Grain for Green Program (GGP), an ambitious reforestation program in China, affected ecosystem services. We quantified regulating services and provisioning service in the potential scenarios, which were developed to improve ecosystem services better. The results indicated the GGP drove 14.5% of land-use/land-cover from 2000 to 2015, and all the regulating services increased. Prioritizing reforestations in steep-sloped and riparian farmlands can promote flood mitigation, water purification, and soil retention services by 62.7%, 25.5%, and 216.1% as compared with 2015 levels, respectively, suggesting that the improvements strongly depend on afforestation locations. Driven by the new GGP policy, a high proportion of economic forest increased provisioning service (272.2%), but at the expense of decreases in soil retention (−25.1%), flood mitigation (−11.4%), water purification (−36.6%), and carbon storage (−48.5%). We identified a suitable scenario that would reduce the trade-offs, which associated with afforestation types and their spatial allocation. Identifying priority areas of afforestation types can inform the GGP policy to assure sustainable and broader benefits.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su12114762
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2518383-7
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