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  • MDPI AG  (146)
  • Wang, Haiyan  (146)
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  • MDPI AG  (146)
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  • 1
    Online-Ressource
    Online-Ressource
    A New Evaluation Method of Shale Oil Sweet Spots in Chinese Lacustrine Basin and Its Application
    MDPI AG ; 2021
    In:  Energies Vol. 14, No. 17 ( 2021-09-03), p. 5519-
    Details
    In: Energies, MDPI AG, Vol. 14, No. 17 ( 2021-09-03), p. 5519-
    Kurzfassung: Compared with the marine shale from North America, Chinese lacustrine basins have more complex geological and reservoir conditions, which makes the selection of sweet spot intervals in the shale oil reservoir particularly difficult. It is thus crucial to accurately predict the shale oil sweet spots for effective exploration and development of shale oil in a lacustrine basin. In this paper, we propose an innovative evaluation method of shale oil sweet spots, which considers five primary parameters (i.e., total oil content, movable oil ratio, reservoir pressure coefficient, permeability, and rock brittleness index) to construct a comprehensive weighting factor, which is used to quantitatively identify a favorable shale oil reservoir. This method firstly constructs an evaluation function for each of the parameters, and then calculates a comprehensive weighting factor to determine the shale oil sweet spot. Statistical results show that the oil production of formation testing intervals have a good positive correlation with the average value of the comprehensive weighting factor of the intervals, which verifies the feasibility of the method. Based on this method, one of the key exploratory wells, Qiang21 in the Raoyang Sag of Bohai Bay basin, was selected as a case study and was determined to be a sweet spot interval of the shale oil reservoir in the upper third member of the Shahejie Formation. This study provides a new way to obtain a favorable exploration interval of shale oil reservoirs and serves shale oil development.
    Materialart: Online-Ressource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en14175519
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2021
    ZDB Id: 2437446-5
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 2
    Online-Ressource
    Online-Ressource
    Annual Direct Cost and Cost-Drivers of Systemic Lupus Erythematosus: A Multi-Center Cross-Sectional Study from CSTAR Registry
    MDPI AG ; 2023
    In:  International Journal of Environmental Research and Public Health Vol. 20, No. 4 ( 2023-02-16), p. 3522-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 20, No. 4 ( 2023-02-16), p. 3522-
    Kurzfassung: Background: To estimate the annual direct costs and cost-drivers associated with systemic lupus erythematosus (SLE) patients in China. Methods: A multi-center, cross-sectional study was conducted based on the CSTAR registry. The information on demography and expenditures for outpatient and inpatient visits due to SLE were collected using online questionnaires. These patients’ medical records were from the database of the Chinese Rheumatology Information System (CRIS). The average direct costs and 95% confidence interval were estimated using the bootstrap method with 1000 bootstrap samples by resampling with replacement. The cost-drivers were identified using multivariate regression models. Results: A total of 1778 SLE patients from 101 hospitals participated in our study, with 92.58% as females, a mean age of 33.8 years old, a median duration of SLE of 4.9 years, 63.8% in an active disease state, 77.3% with two organs or more damaged, and 8.3% using biologics as treatment. The average annual direct cost per patient was estimated at CNY 29,727, which approximates to 86% for direct medical costs. For moderate to severe disease activities, the use of biologics, hospitalization, treatment of moderate or high dose glucocorticoids, and peripheral vascular, cardiovascular, and/or renal system involvements were found to substantially increase the direct costs, while health insurance slightly decreased the direct costs of SLE. Conclusions: This study provided reliable insight into financial pressures on individual SLE patients in China. The efforts focusing on preventing flare occurrences and limiting disease progression were recommended to further reduce the direct cost of SLE.
    Materialart: Online-Ressource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph20043522
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2175195-X
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 3
    Online-Ressource
    Online-Ressource
    Pleiotropic Effect of the compactum Gene and Its Combined Effects with Other Loci for Spike and Grain-Related Traits in Wheat
    MDPI AG ; 2022
    In:  Plants Vol. 11, No. 14 ( 2022-07-13), p. 1837-
    Details
    In: Plants, MDPI AG, Vol. 11, No. 14 ( 2022-07-13), p. 1837-
    Kurzfassung: Club wheat (Triticum aestivum ssp. compactum) with a distinctly compact spike morphology was conditioned by the dominant compactum (C) locus on chromosome 2D and resulted in a redistribution of spike yield components. The disclosure of the genetic basis of club wheat was a prerequisite for the development of widely adapted, agronomically competitive club wheat cultivars. In this study, we used a recombinant inbred line population derived from a cross between club wheat Hiller and modern cultivar Yangmai 158 to construct a genetic linkage map and identify quantitative trait loci associated with 15 morphological traits. The club allele acted in a semi-dominant manner and the C gene was mapped to 370.12–406.29 Mb physical region on the long arm of 2D. Apart from compact spikes, C exhibited a pleiotropic effect on ten other agronomic traits, including plant height, three spike-related traits and six grain-related traits. The compact spike phenotype was correlated with decreased grain size and weight, but with an increase in floret fertility and grain number. These pleiotropic effects make club wheat have compatible spike weight with a normal spike from common wheat. The genetic effects of various gene combinations of C with four yield-related genes, including Ppd-D1, Vrn-D3, Rht-B1b and Rht8, were evaluated. C had no epistatic interaction with any of these genes, indicating that their combinations would have an additive effect on other agronomically important traits. Our research provided a theoretical foundation for the potentially effective deployment of C gene into modern breeding varieties in combination with other favorable alleles.
    Materialart: Online-Ressource
    ISSN: 2223-7747
    URL: Article
    DOI: 10.3390/plants11141837
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2704341-1
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 4
    Online-Ressource
    Online-Ressource
    Network Pharmacology to Unveil the Biological Basis of Health-Strengthening Herbal Medicine in Cancer Treatment
    MDPI AG ; 2018
    In:  Cancers Vol. 10, No. 11 ( 2018-11-21), p. 461-
    Details
    In: Cancers, MDPI AG, Vol. 10, No. 11 ( 2018-11-21), p. 461-
    Kurzfassung: Health-strengthening (Fu-Zheng) herbs is a representative type of traditional Chinese medicine (TCM) widely used for cancer treatment in China, which is in contrast to pathogen eliminating (Qu-Xie) herbs. However, the commonness in the biological basis of health-strengthening herbs remains to be holistically elucidated. In this study, an innovative high-throughput research strategy integrating computational and experimental methods of network pharmacology was proposed, and 22 health-strengthening herbs were selected for the investigation. Additionally, 25 pathogen-eliminating herbs were included for comparison. First, based on network-based, large-scale target prediction, we analyzed the target profiles of 1446 TCM compounds. Next, the actions of 166 compounds on 420 antitumor or immune-related genes were measured using a unique high-throughput screening strategy by high-throughput sequencing, referred to as HTS2. Furthermore, the structural information and the antitumor activity of the compounds in health-strengthening and pathogen-eliminating herbs were compared. Using network pharmacology analysis, we discovered that: (1) Functionally, the predicted targets of compounds from health strengthening herbs were enriched in both immune-related and antitumor pathways, similar to those of pathogen eliminating herbs. As a case study, galloylpaeoniflorin, a compound in a health strengthening herb Radix Paeoniae Alba (Bai Shao), was found to exert antitumor effects both in vivo and in vitro. Yet the inhibitory effects of the compounds from pathogen eliminating herbs on tumor cells proliferation as a whole were significantly stronger than those in health-strengthening herbs (p 〈 0.001). Moreover, the percentage of assay compounds in health-strengthening herbs with the predicted targets enriched in the immune-related pathways (e.g., natural killer cell mediated cytotoxicity and antigen processing and presentation) were significantly higher than that in pathogen-eliminating herbs (p 〈 0.05). This finding was supported by the immune-enhancing effects of a group of compounds from health-strengthening herbs indicated by differentially expressed genes in the HTS2 results. (2) Compounds in the same herb may exhibit the same or distinguished mechanisms in cancer treatment, which was demonstrated as the compounds influence pathway gene expressions in the same or opposite directions. For example, acetyl ursolic acid and specnuezhenide in a health-strengthening herb Fructus Ligustri lucidi (Nv Zhen Zi) both upregulated gene expressions in T cell receptor signaling pathway. Together, this study suggested greater potentials in tumor immune microenvironment regulation and tumor prevention than in direct killing tumor cells of health-strengthening herbs generally, and provided a systematic strategy for unveiling the commonness in the biological basis of health-strengthening herbs in cancer treatment.
    Materialart: Online-Ressource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers10110461
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2018
    ZDB Id: 2527080-1
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 5
    Online-Ressource
    Online-Ressource
    The Regulatory Network of CMPG1-V in Wheat–Blumeria graminis f. sp. tritici Interaction Revealed by Temporal Profiling Using RNA-Seq
    MDPI AG ; 2020
    In:  International Journal of Molecular Sciences Vol. 21, No. 17 ( 2020-08-19), p. 5967-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 21, No. 17 ( 2020-08-19), p. 5967-
    Kurzfassung: Wheat powdery mildew (Pm), caused by Blumeria graminis f. sp. tritici (Bgt), is a prevalent fungal disease. The diploid wheat relative Haynaldia villosa (H. villosa) showed broad-spectrum resistance (BSR) to Pm. A previous study reported an E3 ligase gene, CMPG1-V from H. villosa, showing BSR to Pm. To elucidate the regulatory network mediated by CMPG1-V, in this study, gene expression profiling of CMPG1-V transgenic plant (CMPG1-VOE) and its receptor Yangmai 158 was analyzed and compared after Bgt inoculation at four infection stages. GO and KEGG analysis revealed obvious reprogramming of SA and ABA signaling, starch/sucrose metabolism, and photosynthesis in CMPG1-VOE, compared with those in Yangmai 158. Transcripts of SA synthesis genes SARD1 and UGT, signaling factors TGA and PRs, and SnRKs in ABA signaling were specifically upregulated in CMPG1-VOE rather than Yangmai 158. Transcripts of LHCII in photosynthesis, GLUC and TPP in starch/sucrose metabolism were also induced distinctly in CMPG1-VOE. WGCNA analysis showed crucial regulatory candidates of CMPG1-V, involving serine/threonine-protein kinase in phosphorylation, glucosyltransferase in flavonoid biosynthesis, defense factor WRKYs, and peroxidase in oxidative stress. Our results facilitate the deciphering of the resistant regulatory network of CMPG1-V and the identification of key candidates which might be employed in breeding programs.
    Materialart: Online-Ressource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms21175967
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2020
    ZDB Id: 2019364-6
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 6
    Online-Ressource
    Online-Ressource
    Effect of Different Culture Conditions on Anthocyanins and Related Genes in Red Pear Callus
    MDPI AG ; 2023
    In:  Agronomy Vol. 13, No. 8 ( 2023-07-31), p. 2032-
    Details
    In: Agronomy, MDPI AG, Vol. 13, No. 8 ( 2023-07-31), p. 2032-
    Kurzfassung: Red pears are appreciated for their abundant nutritional benefits and visually striking red hue, rendering them a favored option among consumers and stimulating substantial market demand. The present study employs the flesh of a red pear as the explant, subjecting the flesh callus to varying sugar sources, MS concentrations, light qualities, and temperatures to investigate the alterations in secondary metabolites, including anthocyanins, within the callus. It was found that sucrose can induce more anthocyanins, and its related metabolites and genes also increase as the sucrose and MS concentrations increase. Under the conditions of red-blue light and a temperature of 15 °C, it can further induce the production of more anthocyanins and secondary metabolites and can also upregulate the synthesis of anthocyanin-related genes. As such, this investigation serves to elucidate the factors that contribute to anthocyanin accumulation in red pears, thereby providing a theoretical foundation for understanding the mechanisms underlying color change.
    Materialart: Online-Ressource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy13082032
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2607043-1
    SSG: 23
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 7
    Online-Ressource
    Online-Ressource
    HRST: An Improved HRNet for Detecting Joint Points of Pigs
    MDPI AG ; 2022
    In:  Sensors Vol. 22, No. 19 ( 2022-09-23), p. 7215-
    Details
    In: Sensors, MDPI AG, Vol. 22, No. 19 ( 2022-09-23), p. 7215-
    Kurzfassung: The body size of pigs is a vital evaluation indicator for growth monitoring and selective breeding. The detection of joint points is critical for accurately estimating pig body size. However, most joint point detection methods focus on improving detection accuracy while neglecting detection speed and model parameters. In this study, we propose an HRNet with Swin Transformer block (HRST) based on HRNet for detecting the joint points of pigs. It can improve model accuracy while significantly reducing model parameters by replacing the fourth stage of parameter redundancy in HRNet with a Swin Transformer block. Moreover, we implemented joint point detection for multiple pigs following two steps: first, CenterNet was used to detect pig posture (lying or standing); then, HRST was used for joint point detection for standing pigs. The results indicated that CenterNet achieved an average precision (AP) of 86.5%, and HRST achieved an AP of 77.4% and a real-time detection speed of 40 images per second. Compared with HRNet, the AP of HRST improved by 6.8%, while the number of model parameters and the calculated amount reduced by 72.8% and 41.7%, respectively. The study provides technical support for the accurate and rapid detection of pig joint points, which can be used for contact-free body size estimation of pigs.
    Materialart: Online-Ressource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s22197215
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2022
    ZDB Id: 2052857-7
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 8
    Online-Ressource
    Online-Ressource
    Analysis of the Current Status and Hot Technologies of Coal Spontaneous Combustion Warning
    MDPI AG ; 2023
    In:  Processes Vol. 11, No. 8 ( 2023-08-18), p. 2480-
    Details
    In: Processes, MDPI AG, Vol. 11, No. 8 ( 2023-08-18), p. 2480-
    Kurzfassung: Coal spontaneous combustion disasters are one of the most serious types of mine disasters in China at present, posing a huge threat to underground personal safety and coal production operations. In order to prevent and control coal spontaneous combustion hazards and construct an efficient early warning system, this paper presents a review of coal spontaneous combustion early warning based on the Web of Science database search of 583 papers related to coal spontaneous combustion early warning collected from 2002 to 2021, using VOSviewer visualization software. The number of publications and partnerships at the author, institution and country levels are obtained, and the research hotspots in the field of coal spontaneous combustion warning are obtained based on keyword co-occurrence and clustering. The results show that the research results of scholars with a high publication volume have significant influence in the field of coal spontaneous combustion warning and prevention and control, and a more mature camp has been formed among the research authors; a more stable core group of institutions has been formed in the field of coal spontaneous combustion warning; most of the national publications are concentrated in mineral resource-mining countries; the analysis of hot keywords shows that “sign gas warning” and “warning models and technologies” are the key contents of this field. The analysis of hot keywords shows that “sign gas early warning” and “early warning model and technology” are the key contents of this field. The research content of this paper is helpful for researchers to find the latest information on the current research and trends in the field of spontaneous combustion prevention and coal seam monitoring.
    Materialart: Online-Ressource
    ISSN: 2227-9717
    URL: Article
    DOI: 10.3390/pr11082480
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2720994-5
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 9
    Online-Ressource
    Online-Ressource
    Regional Influenza Prediction with Sampling Twitter Data and PDE Model
    MDPI AG ; 2020
    In:  International Journal of Environmental Research and Public Health Vol. 17, No. 3 ( 2020-01-21), p. 678-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 17, No. 3 ( 2020-01-21), p. 678-
    Kurzfassung: The large volume of geotagged Twitter streaming data on flu epidemics provides chances for researchers to explore, model, and predict the trends of flu cases in a timely manner. However, the explosive growth of data from social media makes data sampling a natural choice. In this paper, we develop a method for influenza prediction based on the real-time tweet data from social media, and this method ensures real-time prediction and is applicable to sampling data. Specifically, we first simulate the sampling process of flu tweets, and then develop a specific partial differential equation (PDE) model to characterize and predict the aggregated flu tweet volumes. Our PDE model incorporates the effects of flu spreading, flu recovery, and active human interventions for reducing flu. Our extensive simulation results show that this PDE model can almost eliminate the data reduction effects from the sampling process: It requires lesser historical data but achieves stronger prediction results with a relative accuracy of over 90% on the 1% sampling data. Even for the more aggressive data sampling ratios such as 0.1% and 0.01% sampling, our model is still able to achieve relative accuracies of 85% and 83%, respectively. These promising results highlight the ability of our mechanistic PDE model in predicting temporal–spatial patterns of flu trends even in the scenario of small sampling Twitter data.
    Materialart: Online-Ressource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph17030678
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2020
    ZDB Id: 2175195-X
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 10
    Online-Ressource
    Online-Ressource
    Research on Black Smoke Detection and Class Evaluation Method for Ships Based on YOLOv5s-CMBI Multi-Feature Fusion
    MDPI AG ; 2023
    In:  Journal of Marine Science and Engineering Vol. 11, No. 10 ( 2023-10-09), p. 1945-
    Details
    In: Journal of Marine Science and Engineering, MDPI AG, Vol. 11, No. 10 ( 2023-10-09), p. 1945-
    Kurzfassung: To enhance the real-time detection accuracy of ship exhaust plumes and further quantify the degree of darkness, this study proposes a multi-feature fusion approach that combines the YOLOv5s-CMBI algorithm for ship exhaust plume detection with the Ringerman Blackness-based grading method. Firstly, diverse datasets are integrated and a subset of the data is subjected to standard optical model aerosolization to form a dataset for ship exhaust plume detection. Subsequently, building upon the YOLOv5s architecture, the CBAM convolutional attention mechanism is incorporated to augment the network’s focus on ship exhaust plume regions while suppressing irrelevant information. Simultaneously, inspired by the BiFPN structure with weighted bidirectional feature pyramids, a lightweight network named Tiny-BiFPN is devised to enable multi-path feature fusion. The Adaptive Spatial Feature Fusion (ASFF) mechanism is introduced to counteract the impact of feature scale disparities. The EIoU_Loss is employed as the localization loss function to enhance both regression accuracy and convergence speed of the model. Lastly, leveraging the k-means clustering algorithm, color information is mined through histogram analysis to determine clustering centers. The Mahalanobis distance is used to compute sample similarity, and the Ringerman Blackness-based method is employed to categorize darkness levels. Ship exhaust plume grades are estimated by computing a weighted average grayscale ratio between the effective exhaust plume region and the background region. Experimental results reveal that the proposed algorithm achieves improvements of approximately 3.8% in detection accuracy, 5.7% in recall rate, and 4.6% in mean average precision (mAP0.5) compared to the original model. The accuracy of ship exhaust plume darkness grading attains 92.1%. The methodology presented in this study holds significant implications for the establishment and application of future ship exhaust plume monitoring mechanisms.
    Materialart: Online-Ressource
    ISSN: 2077-1312
    URL: Article
    DOI: 10.3390/jmse11101945
    Sprache: Englisch
    Verlag: MDPI AG
    Publikationsdatum: 2023
    ZDB Id: 2738390-8
    Standort Signatur Einschränkungen Verfügbarkeit
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