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  • Hindawi Limited  (12)
  • 1
    Online Resource
    Online Resource
    A Multistep Extending Truncation Method towards Model Construction of Infinite-State Markov Chains
    Hindawi Limited ; 2014
    In:  Mathematical Problems in Engineering Vol. 2014 ( 2014), p. 1-6
    Details
    In: Mathematical Problems in Engineering, Hindawi Limited, Vol. 2014 ( 2014), p. 1-6
    Abstract: The model checking of Infinite-State Continuous Time Markov Chains will inevitably encounter the state explosion problem when constructing the CTMCs model; our method is to get a truncated model of the infinite one; to get a sufficient truncated model to meet the model checking of Continuous Stochastic Logic based system properties, we propose a multistep extending advanced truncation method towards model construction of CTMCs and implement it in the INFAMY model checker; the experiment results show that our method is effective.
    Type of Medium: Online Resource
    ISSN: 1024-123X , 1563-5147
    URL: Article
    DOI: 10.1155/2014/764819
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2014
    detail.hit.zdb_id: 2014442-8
    SSG: 11
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  • 2
    Online Resource
    Online Resource
    Research on Electric Vehicle Charging Scheduling Strategy Based on the Multiobjective Algorithm
    Hindawi Limited ; 2022
    In:  Mathematical Problems in Engineering Vol. 2022 ( 2022-8-5), p. 1-6
    Details
    In: Mathematical Problems in Engineering, Hindawi Limited, Vol. 2022 ( 2022-8-5), p. 1-6
    Abstract: Under the influence of the low-carbon economy, the electric vehicles have been vigorously promoted. As the main place for charging, charging stations are classified as unstable loads in the power grid because of the large fluctuation of electricity demand. If a large number of charging stations in the system are not regulated and dispatched, the stability of the system will be greatly affected, so it is vital to further study the scheduling strategy of the cars. In this paper, a scheduling model based on the multiobjective algorithm is established, in which the PSO algorithm is used in the model. And the experimental analysis shows that the model can reduce the average charging time and improve the utilization rate of charging piles.
    Type of Medium: Online Resource
    ISSN: 1563-5147 , 1024-123X
    URL: Article
    DOI: 10.1155/2022/1959511
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2014442-8
    SSG: 11
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  • 3
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    Jieduan-Niwan Formula Reduces Liver Apoptosis in a Rat Model of Acute-on-Chronic Liver Failure by Regulating the E2F1-Mediated Intrinsic Apoptosis Pathway
    Hindawi Limited ; 2019
    In:  Evidence-Based Complementary and Alternative Medicine Vol. 2019 ( 2019-11-11), p. 1-11
    Details
    In: Evidence-Based Complementary and Alternative Medicine, Hindawi Limited, Vol. 2019 ( 2019-11-11), p. 1-11
    Abstract: Acute-on-chronic liver failure (ACLF) is a serious and complicated disease that threatens human health because its pathogenesis is unclear, and the outcome of the current therapies has been less than satisfactory. A national famous doctor of traditional Chinese medicine, Qian Ying, created the Jieduan-Niwan Formula (JDNW), based on his long-term clinical experience. However, despite the good clinical outcome, the biological mechanism by which it works is unknown. In the current study, we established an ACLF rat model by administering human serum albumin (HSA) combined with D-galactosamine (D-GalN) and lipopolysaccharide (LPS) to explore the potential mechanism of JDNW in treating ACLF. The rats were treated with JDNW by administration of the model substances and sacrificed after 4, 8, and 12 h. Then we divided the rats into normal group, model at 4 h, model at 8 h, model at 12 h, JDNW at 4 h, JDNW at 8 h, and JDNW at 12 h. Biochemical and histopathological examinations were performed to compare the rats in different groups. Compared with the ACLF model group, expression levels of alanine transaminase, aspartate aminotransferase, total bilirubin, and TNF- α and IL-6 proteins were reduced in the JDNW group at the corresponding time points, the survival rates of rats were increased, and the pathological condition of the liver was improved. In addition, JDNW treatment improved the ultrastructure of hepatocytes and mitochondria and decreased the hepatocyte apoptosis index. E2F1, P53, P73, Apaf-1, p14ARF, caspase-3, caspase-6, and caspase-7 levels in the JDNW group were distinctly lower than those in the untreated rats. Moreover, Bcl-2 and Mcl-1 levels increased. Thus, JDNW decreases ACLF-induced mortality in rats by modulating the E2F1-mediated intrinsic apoptotic pathway.
    Type of Medium: Online Resource
    ISSN: 1741-427X , 1741-4288
    URL: Article
    DOI: 10.1155/2019/8108503
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2019
    detail.hit.zdb_id: 2148302-4
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  • 4
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    Review on Selection and Experiment Method of Commonly Studied Simulated Radionuclides in Researches of Nuclear Waste Solidification
    Hindawi Limited ; 2020
    In:  Science and Technology of Nuclear Installations Vol. 2020 ( 2020-08-28), p. 1-13
    Details
    In: Science and Technology of Nuclear Installations, Hindawi Limited, Vol. 2020 ( 2020-08-28), p. 1-13
    Abstract: Although many types of simulated radionuclides have been widely used as a substitute for actual nuclear waste in the studies of nuclear waste solidification, the understanding of the applicability and validity of simulated radionuclides is still insufficient. In particular, the selection and use of simulated radionuclides, which can play a decisive role in the accuracy of the experimental results, still lack unified or integrated references. This paper provides a critical review on the selection, experimental methods, and applicability of the most commonly studied simulated radionuclides, followed by a careful discussion and recommendation of simulated radionuclides suitable for different solidified bodies. The main factors (e.g., temperature, pH, and atmosphere) affecting the choice of simulated radionuclides were analyzed in detail. This work helps to integrate the selection and use of simulated radionuclides, and it will be beneficial for improving the effectiveness of nuclide solidification research.
    Type of Medium: Online Resource
    ISSN: 1687-6075 , 1687-6083
    URL: Article
    DOI: 10.1155/2020/3287320
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2397941-0
    SSG: 3,6
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  • 5
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    Analysis and Research Based on the Crowdsourcing Corpus System in Guangdong-Hong Kong-Macao Greater Bay Area (GBA)
    Hindawi Limited ; 2022
    In:  Mathematical Problems in Engineering Vol. 2022 ( 2022-9-30), p. 1-14
    Details
    In: Mathematical Problems in Engineering, Hindawi Limited, Vol. 2022 ( 2022-9-30), p. 1-14
    Abstract: Objective. To sort out the application and status quo of some domestic crowdsourcing models, explore the factors affecting multilingual manual annotation through experiments and offer suggestions. Methodology. Crawling the government news texts in Mandarin, Cantonese, English, and Portuguese in Guangdong, Hong Kong, and Macao, and enter them into the database. Combine it with corpus tagging uses the established web platform to practice crowdsourcing and collect a large number of annotation results and behavior data. Results. Made assumptions about factors that may affect the quality of manual annotation, used SPSS and other data analysis software to evaluate the degree of interpretation of the assumptions, provided a regression formula for calculating the accuracy, and provided constructive suggestions for the corpus annotation quality assurance projects. Limitations. More corpus information in more languages and more professional annotators are needed. Conclusions. The study found that the accuracy of annotation is strongly related to the attributes of the corpus itself, such as the total number of vocabularies, the number of rare words, the complexity of parts of speech, etc., and the condition of languages are different from each other.
    Type of Medium: Online Resource
    ISSN: 1563-5147 , 1024-123X
    URL: Article
    DOI: 10.1155/2022/4815254
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2014442-8
    SSG: 11
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  • 6
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    Mechanism of Rock Burst Revealed by Numerical Simulation and Energy Calculation
    Hindawi Limited ; 2020
    In:  Shock and Vibration Vol. 2020 ( 2020-11-2), p. 1-15
    Details
    In: Shock and Vibration, Hindawi Limited, Vol. 2020 ( 2020-11-2), p. 1-15
    Abstract: We propose a new computational method to calculate the storage elastic energy value of surrounding rocks based on numerical simulation and theoretical calculation. By calculating the difference value in energy under different force states and comparing them with the energy level when rock burst occurs, we get the mechanism of rock burst: when roadway and surrounding rocks are in the condition of large ratio bias force field, certain triggering stress causes mass release of the elastic energy of surrounding rocks around the roadway, and when the energy reaches a certain level, rock burst will occur. We also put forward the specific force field conditions and triggering stress values of rock burst, which is of great guiding significance for the mechanism disclosure, monitoring, and control of rock burst.
    Type of Medium: Online Resource
    ISSN: 1875-9203 , 1070-9622
    URL: Article
    DOI: 10.1155/2020/8862849
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2070162-7
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  • 7
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    Machine Learning for Estimating Leaf Dust Retention Based on Hyperspectral Measurements
    Hindawi Limited ; 2018
    In:  Journal of Sensors Vol. 2018 ( 2018-09-06), p. 1-12
    Details
    In: Journal of Sensors, Hindawi Limited, Vol. 2018 ( 2018-09-06), p. 1-12
    Abstract: Hyperspectral sensors provide detailed information for dust retention content (DRC) estimation. However, rich hyperspectral data are not fully utilized by traditional image analysis techniques. We integrated several recently developed machine learning algorithms to estimate DRC on plant leaves using the spectra measured by the ASD FieldSpec 3. The experiments were carried out on three common green plants of southern China. The important hyperspectral variables were first identified by applying the random forest (RF) algorithm. Three estimation models were then developed using the support vector machine (SVM), classification and regression tree (CART), and RF algorithms. The results showed that the increase in dust retention contents on plant leaves enhanced their reflectance in the visible wavelength but weakened their reflectance in the infrared wavelength. Wavelengths in the ranges of 450–500 nm, 550–600 nm, 750–1000 nm, and 1100–1300 nm were identified as important variables using the RF algorithm and were used to estimate the DRC. The comparison of the three machine learning techniques for DRC estimation confirmed that the SVM and RF models performed well because their estimations were similar to the measured DRC. Specifically, the average R 2 for SVM and RF model are 0.85 and 0.88. The technical approach of this study proved to be a successful illustration of using hyperspectral measurements to estimate the DRC on plant leaves. The findings of this study can be applied to monitor the DRC on leaves of other plants and can also be integrated with other types of spectral data to measure the DRC at a regional scale.
    Type of Medium: Online Resource
    ISSN: 1687-725X , 1687-7268
    URL: Article
    DOI: 10.1155/2018/6026259
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2018
    detail.hit.zdb_id: 2397931-8
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  • 8
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    Artificial Intelligence Meets Whole Slide Images: Deep Learning Model Shapes an Immune-Hot Tumor and Guides Precision Therapy in Bladder Cancer
    Hindawi Limited ; 2022
    In:  Journal of Oncology Vol. 2022 ( 2022-9-19), p. 1-27
    Details
    In: Journal of Oncology, Hindawi Limited, Vol. 2022 ( 2022-9-19), p. 1-27
    Abstract: Background. To construct and validate a deep learning cluster from whole slide images (WSI) for depicting the immunophenotypes and functional heterogeneity of the tumor microenvironment (TME) in patients with bladder cancer (BLCA) and to explore an artificial intelligence (AI) score to explore the underlying biological pathways in the developed WSI cluster. Methods. In this study, the WSI cluster was constructed based on a deep learning procedure. Further rerecognition of TME features in pathological images was applied based on a neural network. Then, we integrated the TCGA cohort and several external testing cohorts to explore and validate this novel WSI cluster and a corresponding quantitative indicator, the AI score. Finally, correlations between the AI cluster (AI score) and classical BLCA molecular subtypes, immunophenotypes, functional heterogeneity, and potential therapeutic method in BLCA were assessed. Results. The WSI cluster was identified associated with clinical survival ( P 〈 0.001 ) and was proved as an independent predictor ( P = 0.031 ), which could also predict the immunology and the clinical significance of BLCA. Rerecognition of pathological images established a robust 3-year survival prediction model (with an average classification accuracy of 86%, AUC of 0.95) for BLCA patients combining TME features and clinical features. In addition, an AI score was constructed to quantify the underlying logic of the WSI cluster ( AUC = 0.838 ). Finally, we hypothesized that high AI score shapes an immune-hot TME in BLCA. Thus, treatment options including immune checkpoint blockade (ICB), chemotherapy, and ERBB therapy can be used for the treatment of BLCA patients in WSI cluster1 (high AI score subtype). Conclusions. In general, we showed that deep learning can predict prognosis and may aid in the precision medicine for BLCA directly from H & E histology, which is more economical and efficient.
    Type of Medium: Online Resource
    ISSN: 1687-8469 , 1687-8450
    URL: Article
    DOI: 10.1155/2022/8213321
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2461349-6
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  • 9
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    Exosomes as Nanocarriers for Theragnostic miRNA Markers in Nonsmall Cell Lung Cancer Therapy
    Hindawi Limited ; 2022
    In:  Journal of Nanomaterials Vol. 2022 ( 2022-3-22), p. 1-13
    Details
    In: Journal of Nanomaterials, Hindawi Limited, Vol. 2022 ( 2022-3-22), p. 1-13
    Abstract: Nonsmall cell lung carcinoma (NSCLC) is the leading cause of deaths related to carcinomas of lung by the involvement of several risk factors. Tumor cells, in general, exude larger quantities of biological macromolecules in comparison to their noncancerous opposites. Vesicular bodies or cavities created by the folding back of endosome membranes mingle with the plasma membrane and result in the release of exosomes into the extracellular space after which they enter proximal or distant cells of target. Exosomes are nanovesicles that can carry microRNAs (miRNAs) and other such macromolecules as cargos into the tumor environment by means of cell-to-cell communication. These materials transported by exosomes can act as indicators for oncogenesis and metastasis and result in resistance among therapy-sensitive cancer cells. The cargos inside the vesicles loaded with miRNAs vary according to their particular state and therefore can act as potential prognostic or diagnostic markers for a variety of diseases including lung cancer, especially NSCLC. Although the roles of exosomal miRNAs are unclear or contradictory, the possibility of using exosomes as efficient nanovesicles for the treatment of NSCLC using biological molecules such as miRNA remains critical. Hence, this review focuses on the roles of exosomal and cell-free miRNA in NSCLC therapy at preclinical and clinical levels.
    Type of Medium: Online Resource
    ISSN: 1687-4129 , 1687-4110
    URL: Article
    DOI: 10.1155/2022/8402500
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2229480-6
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  • 10
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    Hadoop-Based Medical Image Storage and Access Method for Examination Series
    Hindawi Limited ; 2021
    In:  Mathematical Problems in Engineering Vol. 2021 ( 2021-3-24), p. 1-10
    Details
    In: Mathematical Problems in Engineering, Hindawi Limited, Vol. 2021 ( 2021-3-24), p. 1-10
    Abstract: Under the background of electronic medical data, doctors use electronic images to replace the traditional film for diagnosis, and patients can view examination images at any time through various electronic means. The storage and frequent reading of massive data bring new challenges. Given the characteristics of the size and quantity of image files generated by different examination types, different merging strategies are proposed to improve the storage performance of the files; according to the characteristics of medical data with examination as the basic unit, a two-level model combined with medical imaging information is proposed. The indexing mechanism solves the problem that SEQ files cannot be read randomly without an index; given the time characteristics of data access, an improved 2Q algorithm is proposed to cache the prefetched files and the read files in different cache queues, which improves the efficiency of file reading. In the experimental comparison, the proposed algorithm surpasses the baseline method in storage and access performance.
    Type of Medium: Online Resource
    ISSN: 1563-5147 , 1024-123X
    URL: Article
    DOI: 10.1155/2021/5525009
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2014442-8
    SSG: 11
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