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  • MDPI AG  (25)
  • 1
    Online Resource
    Online Resource
    The Prediction Method on the Early Failure of Hydropower Units Based on Gaussian Process Regression Driven by Monitoring Data
    MDPI AG ; 2020
    In:  Applied Sciences Vol. 11, No. 1 ( 2020-12-25), p. 153-
    Details
    In: Applied Sciences, MDPI AG, Vol. 11, No. 1 ( 2020-12-25), p. 153-
    Abstract: The hydropower units have a complex structure, complicated and changing working conditions, complexity and a diversity of faults. Effectively evaluating the healthy operation status and accurately predicting the failure for the hydropower units using the real-time monitoring data is still a difficult problem. To this end, this paper proposes a prediction method for the early failure of hydropower units based on Gaussian process regression (GPR). Firstly, by studying the correlation between different monitoring data, nine state parameters closely related to the operation of hydropower units are mined from the massive data. Secondly, a health evaluation model is established based on GPR using the historical multi-dimensional monitoring information and fault-free monitoring data at the initial stage of unit operation. Finally, a condition monitoring directive based on the Mahalanobis distance (MD) is designed. The effectiveness of the proposed method is verified by several typical examples of monitoring data of a hydropower station in Guangxi, China. The results show that, in three cases, the abnormal conditions of the unit are found 2 days, 4 days and 43 days earlier than those of regular maintenances respectively. Therefore, the method can effectively track the change process of the operation state of hydropower units, and detect the abnormal operation state of hydropower units in advance.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app11010153
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2704225-X
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  • 2
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    Online Resource
    A Novel Family of Winged-Helix Single-Stranded DNA-Binding Proteins from Archaea
    MDPI AG ; 2022
    In:  International Journal of Molecular Sciences Vol. 23, No. 7 ( 2022-03-22), p. 3455-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 7 ( 2022-03-22), p. 3455-
    Abstract: The winged helix superfamily comprises a large number of structurally related nucleic acid-binding proteins. While these proteins are often shown to bind dsDNA, few are known to bind ssDNA. Here, we report the identification and characterization of Sul7s, a novel winged-helix single-stranded DNA binding protein family highly conserved in Sulfolobaceae. Sul7s from Sulfolobus islandicus binds ssDNA with an affinity approximately 15-fold higher than that for dsDNA in vitro. It prefers binding oligo(dT)30 over oligo(dC)30 or a dG-rich 30-nt oligonucleotide, and barely binds oligo(dA)30. Further, binding by Sul7s inhibits DNA strand annealing, but shows little effect on the melting temperature of DNA duplexes. The solution structure of Sul7s determined by NMR shows a winged helix-turn-helix fold, consisting of three α-helices, three β-strands, and two short wings. It interacts with ssDNA via a large positively charged binding surface, presumably resulting in ssDNA deformation. Our results shed significant light on not only non-OB fold single-stranded DNA binding proteins in Archaea, but also the divergence of the winged-helix proteins in both function and structure during evolution.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms23073455
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 3
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    Online Resource
    Assessment of Long-Term Watershed Management on Reservoir Phosphorus Concentrations and Export Fluxes
    MDPI AG ; 2018
    In:  International Journal of Environmental Research and Public Health Vol. 15, No. 10 ( 2018-10-02), p. 2169-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 15, No. 10 ( 2018-10-02), p. 2169-
    Abstract: Source water nutrient management to prevent eutrophication requires critical strategies to reduce watershed phosphorus (P) loadings. Shanxi Drinking-Water Source Area (SDWSA) in eastern China experienced severe water quality deterioration before 2010, but showed considerable improvement following application of several watershed management actions to reduce P. This paper assessed the changes in total phosphorus (TP) concentrations and fluxes at the SDWSA outlet relative to watershed anthropogenic P sources during 2005–2016. Overall anthropogenic P inputs decreased by 21.5% over the study period. Domestic sewage, livestock, and fertilizer accounted for (mean ± SD) 18.4 ± 0.6%, 30.1 ± 1.9%, and 51.5 ± 1.5% of total anthropogenic P inputs during 2005–2010, compared to 24.3 ± 2.7%, 8.8 ± 10.7%, and 66.9 ± 8.0% for the 2011–2016 period, respectively. Annual average TP concentrations in SDWSA decreased from 0.041 ± 0.019 mg/L in 2009 to 0.025 ± 0.013 mg/L in 2016, a total decrease of 38.2%. Annual P flux exported from SDWSA decreased from 0.46 ± 0.04 kg P/(ha·a) in 2010 to 0.25 ± 0.02 kg P/(ha·a) in 2016, a decrease of 44.9%. The success in reducing TP concentrations was mainly due to the development of domestic sewage/refuse collection/treatment and improved livestock management. These P management practices have prevented harmful algal blooms, providing for safe drinking water.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph15102169
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2175195-X
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  • 4
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    An Extended Watershed-Based AHP Model for Flood Hazard Estimation: Constraining Runoff Converging Indicators via MFD-Derived Sub-Watershed by Maximum Zonal Statistical Method
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 10 ( 2022-05-20), p. 2465-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 10 ( 2022-05-20), p. 2465-
    Abstract: Floods threaten the sustainable development of areas with a high probability of hazard. A typical analytic hierarchy process (pixel-based AHP) based flood hazard estimation method may ignore the similar threat caused by neighborhood cells at the sub-watershed scale. This study proposed an extended watershed-based Zonal Statistical AHP for flood hazard estimation: Constraining converging related indicators by the sub-watersheds (WZSAHP-RC) model to improve this gap. Before calculating the flood hazard index, the proposed model uses the sub-watershed derived by the multiple flow direction method as a based unit to calculate the maximum zonal statistical value of runoff converging indicators. Moreover, taking the Chaohu basin of Anhui in China as the case study, the validation flooding ground-truthing was constructed from GF-3, and Landsat OLI images of the flood event from 20 July to 24 July 2020, which is the biggest flood recorded by the Zhongmiao station, which recorded a new water level, 0.82 m higher than the historical record. Compared with the validation, the results indicated the proposed method could improve the correct ratio by 38% (from 22% to 60%) and the fit ratio by 17% (from 18% to 35%) when considering the predicted flood hazard levels of “High” and “Very High” as flooded areas. Moreover, the flood hazard map derived by WZSAHP-RC demonstrated greater consistency in the flooded districts filtered by Baidu News than the pixel-based AHP. It revealed that considering two- or even multi-dimensional homogeneity may help to improve the accuracy of flood hazard maps on a catchment scale.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14102465
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
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  • 5
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    Emerging Issues in Mapping Urban Impervious Surfaces Using High-Resolution Remote Sensing Images
    MDPI AG ; 2023
    In:  Remote Sensing Vol. 15, No. 10 ( 2023-05-14), p. 2562-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 10 ( 2023-05-14), p. 2562-
    Abstract: Urban impervious surface (UIS) is a key parameter in climate change, environmental change, and sustainability. UIS extraction has been evolving rapidly in the past decades. However, high-resolution impervious surface mapping is a long-term need. There is an urgent requirement for impervious surface mapping from high-resolution remote sensing imagery. In this paper, we compare current extraction methods in terms of extraction units and extraction models and summarize their strengths and limitations. We discuss the challenges in impervious surface estimation from high spatial resolution remote sensing imagery in terms of selection of spatial resolution, spectral band, and extraction method. The uncertainties caused by clouds and snow, shadows, and vegetation occlusion are also analyzed. Automated sample labeling and remote sensing domain knowledge are the main directions in impervious surface extraction using deep learning methods. We should also focus on using continuous time series of high-resolution imagery and multi-source satellite imagery for dynamic monitoring of impervious surfaces.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15102562
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
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  • 6
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    The Influence of Magnetic Field on Fatigue and Mechanical Properties of a 35CrMo Steel
    MDPI AG ; 2021
    In:  Metals Vol. 11, No. 4 ( 2021-03-26), p. 542-
    Details
    In: Metals, MDPI AG, Vol. 11, No. 4 ( 2021-03-26), p. 542-
    Abstract: The influence of a magnetic field of 1.2–1.3 T on the variation of the fatigue behaviors and the mechanical properties of a 35CrMo steel after fatigue tests are investigated in this paper, in order to provide a basic guidance on the application in the similar environment of electrical machinery or vehicles. The microstructures of samples tested with and without magnetic fields are observed and analyzed by XRD, SEM, and TEM techniques. The fatigue life cycles are slightly increased by about 10–15% under magnetic field of 1.2–1.3 T according to the experimental results. A small increment of yield strength under fatigue life cycles of 10,000, 50,000, and 100,000 times is caused by the magnetic field, although the enhancement is only of 5–8 MPa. The dislocation density of the specimen is increased and the uniformity of dislocations is improved by magnetic fields applied during fatigue tests under the same load and cycles. The formation of micro-defects or micro-cracks will be postponed by the improvement in homogeneity of the material, leading to the increase of mechanical properties. The strengthening mechanisms such as deformation hardening and dislocation hardening effects are enhanced by the dislocation entangled structures and the higher density caused by magnetic field.
    Type of Medium: Online Resource
    ISSN: 2075-4701
    URL: Article
    DOI: 10.3390/met11040542
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2662252-X
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  • 7
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    Mapping Impervious Surface Areas Using Time-Series Nighttime Light and MODIS Imagery
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 10 ( 2021-05-13), p. 1900-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 10 ( 2021-05-13), p. 1900-
    Abstract: Mapping impervious surface area (ISA) dynamics at the regional and global scales is an important task that supports the management of the urban environment and urban ecological systems. In this study, we aimed to develop a new method for ISA percentage (ISA%) mapping using Nighttime Light (NTL) and MODIS products. The proposed method consists of three major steps. First, we calculated the Enhanced Vegetation Index (EVI)-adjusted NTL index (EANTLI) and performed intra-annual and inter-annual corrections on the DMSP-OLS data. Second, based on the geographically weighted regression (GWR) model, we built a consistent NTL product from 2000 to 2019 by performing an intercalibration between DMSP-OLS and VIIRS images. Third, we adopted a GA-BP neural network model to monitor ISA% dynamics using NTL imagery, MODIS imagery, and population data. Taking the Guangdong–Hong Kong–Macao Greater Bay as the study area, our results indicate that the ISA% in our study area increased from 7.97% in 2000 to 17.11% in 2019, with a mean absolute error (MAE) of 0.0647, root mean square error (RMSE) of 0.1003, Pearson’s coefficient of 0.9613, and R2 (R-squared) of 0.9239. Specifically, these results demonstrate the effectiveness of the proposed method in mapping ISA and investigating ISA dynamics using temporal features extracted from consistent NTL and MODIS products. The proposed method is feasible when generating ISA% at a large scale at high frequency, given the ease of implementation and the availability of input data sources.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13101900
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 8
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    Meta-FSEO: A Meta-Learning Fast Adaptation with Self-Supervised Embedding Optimization for Few-Shot Remote Sensing Scene Classification
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 14 ( 2021-07-14), p. 2776-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 14 ( 2021-07-14), p. 2776-
    Abstract: The performance of deep learning is heavily influenced by the size of the learning samples, whose labeling process is time consuming and laborious. Deep learning algorithms typically assume that the training and prediction data are independent and uniformly distributed, which is rarely the case given the attributes and properties of different data sources. In remote sensing images, representations of urban land surfaces can vary across regions and by season, demanding rapid generalization of these surfaces in remote sensing data. In this study, we propose Meta-FSEO, a novel model for improving the performance of few-shot remote sensing scene classification in varying urban scenes. The proposed Meta-FSEO model deploys self-supervised embedding optimization for adaptive generalization in new tasks such as classifying features in new urban regions that have never been encountered during the training phase, thus balancing the requirements for feature classification tasks between multiple images collected at different times and places. We also created a loss function by weighting the contrast losses and cross-entropy losses. The proposed Meta-FSEO demonstrates a great generalization capability in remote sensing scene classification among different cities. In a five-way one-shot classification experiment with the Sentinel-1/2 Multi-Spectral (SEN12MS) dataset, the accuracy reached 63.08%. In a five-way five-shot experiment on the same dataset, the accuracy reached 74.29%. These results indicated that the proposed Meta-FSEO model outperformed both the transfer learning-based algorithm and two popular meta-learning-based methods, i.e., MAML and Meta-SGD.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13142776
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 9
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    Effects of Cyclic Wetting-Drying Conditions on Elastic Modulus and Compressive Strength of Sandstone and Mudstone
    MDPI AG ; 2018
    In:  Processes Vol. 6, No. 12 ( 2018-11-22), p. 234-
    Details
    In: Processes, MDPI AG, Vol. 6, No. 12 ( 2018-11-22), p. 234-
    Abstract: The influence of water on the mechanical properties of rock is vital for determining the rock stability when subjected to changes of water conditions. In this paper, a series of uniaxial compression tests were conducted to investigate effects of cyclic wetting and drying on the mechanical properties of sandstone and mudstone collected from Chongqing city, China. The results showed that both elastic modulus and uniaxial compressive strength of sandstone and mudstone were reduced by wetting and drying cycles, and that the degradation rate of the two mechanic parameters of mudstone was always larger than sandstone. The parameters, including water adsorption, degradation degree of elastic modulus, degradation degree of uniaxial compressive strength, increase with the increase of the wetting-drying cycles (N). The relationship between these three parameters and the value of N + 1 could be well fitted by logarithmic curves. The average degradation degree was also used to describe the degradation of per time wetting-drying cycles. It is found that the average degradation degree of elastic modulus and uniaxial compressive strength decrease with the increase of wetting-drying cycles. Moreover, the relationships between the mechanical properties and the porosity are presented, which can be fitted by linear curves. In the cyclic wetting-drying process, the elastic modulus and the uniaxial compressive strength decreased with the porosity increasing, and the degradation rates of sandstone mechanic parameters were higher than those of mudstone.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    URL: Article
    DOI: 10.3390/pr6120234
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2720994-5
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  • 10
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    Interaction of the Escherichia coli HU Protein with Various Topological Forms of DNA
    MDPI AG ; 2021
    In:  Biomolecules Vol. 11, No. 11 ( 2021-11-19), p. 1724-
    Details
    In: Biomolecules, MDPI AG, Vol. 11, No. 11 ( 2021-11-19), p. 1724-
    Abstract: E. coli histone-like protein HU has been shown to interact with different topological forms of DNA. Using radiolabeled HU, we examine the effects of DNA supercoiling on HU–DNA interactions. We show that HU binds preferentially to negatively supercoiled DNA and that the affinity of HU for DNA increases with increases in the negative superhelical density of DNA. Binding of HU to DNA is most sensitively influenced by DNA supercoiling within a narrow but physiologically relevant range of superhelicity (σ = −0.06–0). Under stoichiometric binding conditions, the affinity of HU for negatively supercoiled DNA (σ = −0.06) is more than 10 times higher than that for relaxed DNA at physiologically relevant HU/DNA mass ratios (e.g., 1:10). This binding preference, however, becomes negligible at HU/DNA mass ratios higher than 1:2. At saturation, HU binds both negatively supercoiled and relaxed DNA with similar stoichiometries, i.e., 5–6 base pairs per HU dimer. In our chemical crosslinking studies, we demonstrate that HU molecules bound to negatively supercoiled DNA are more readily crosslinked than those bound to linear DNA. At in vivo HU/DNA ratios, HU appears to exist predominantly in a tetrameric form on negatively supercoiled DNA and in a dimeric form on linear DNA. Using a DNA ligase-mediated nick closure assay, we show that approximately 20 HU dimers are required to constrain one negative supercoil on relaxed DNA. Although fewer HU dimers may be needed to constrain one negative supercoil on negatively supercoiled DNA, our results and estimates of the cellular level of HU argue against a major role for HU in constraining supercoils in vivo. We discuss our data within the context of the dynamic distribution of the HU protein in cells, where temporal and local changes of DNA supercoiling are known to take place.
    Type of Medium: Online Resource
    ISSN: 2218-273X
    URL: Article
    DOI: 10.3390/biom11111724
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2701262-1
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