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  • Bentham Science Publishers Ltd.  (9)
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  • Bentham Science Publishers Ltd.  (9)
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  • 1
    Online Resource
    Online Resource
    Recent Patents on Concrete Pavers of Coalmines
    Bentham Science Publishers Ltd. ; 2022
    In:  Recent Patents on Engineering Vol. 16, No. 4 ( 2022-07)
    Details
    In: Recent Patents on Engineering, Bentham Science Publishers Ltd., Vol. 16, No. 4 ( 2022-07)
    Abstract: Concrete pavers are self-propelled units used in concrete pavement construction that have of paving, vibrating, and leveling functions. The existing concrete pavers have a large size, making it difficult for them to enter underground roadways, and it is difficult to adjust the paving equipment in real time when the width of the underground roadway is deformed. Objective: To realize intelligent concrete paving in coal mine roadways, based on the analysis of recent concrete paver patents, this paper proposes an intelligent virtual paving system based on 3D infrared scanning imaging. Method: The intelligent virtual paving system, which uses multiple groups of 3D infrared scanners and signal processing systems, can collect and analyze 3D images in the roadway and perform virtual paving in the computer. This system can obtain the required parameters of roadway paving, such as the feeding amount, driving speed, limiter height, and width of the synovium, as well as give the initial paving parameters. Results: In the actual paving process, through virtual paving parameters, the feeding amount and accelerator can be regulated in real time, and the difference between the actual paving and virtual paving can be judged to change the paving width in real time. Conclusion: Intelligent virtual paver systems have a guiding significance for the improvement of existing paver systems.
    Type of Medium: Online Resource
    ISSN: 1872-2121
    URL: Article
    DOI: 10.2174/1872214812666211015121227
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2022
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  • 2
    Online Resource
    Online Resource
    The Accomplices of NF-κB Lead to Radioresistance
    Bentham Science Publishers Ltd. ; 2015
    In:  Current Protein & Peptide Science Vol. 16, No. 4 ( 2015-04-29), p. 279-294
    Details
    In: Current Protein & Peptide Science, Bentham Science Publishers Ltd., Vol. 16, No. 4 ( 2015-04-29), p. 279-294
    Type of Medium: Online Resource
    ISSN: 1389-2037
    URL: Article
    DOI: 10.2174/138920371604150429152328
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2015
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    A Network Pharmacology Approach to Explore the Underlying Mechanism of Tufuling Qiwei Tangsan in Treating Psoriasis
    Bentham Science Publishers Ltd. ; 2021
    In:  Current Bioinformatics Vol. 16, No. 6 ( 2021-09-14), p. 829-845
    Details
    In: Current Bioinformatics, Bentham Science Publishers Ltd., Vol. 16, No. 6 ( 2021-09-14), p. 829-845
    Abstract: Tufuling Qiwei Tangsan (TQTS) is a commonly used Mongolian medicine preparation against psoriasis in China. However, its mechanism of action and molecular targets for the treatment of psoriasis is still unclear. Network pharmacology can reveal the synergistic mechanism of drugs at the molecular, target, and pathway levels and is suitable for the complex study of traditional Chinese medicine formulations. However, it is rarely involved in the application of Mongolian medicine with the same holistic concept of traditional Chinese medicine. Method: In this paper, the active compounds of TQTS were collected, and their targets were identified. Psoriasis-related targets were obtained by analyzing the differential expressed genes between psoriasis patients and healthy individuals. Then, the network concerning the interactions of potential targets of TQTS with well-known psoriasis-related targets was built. The core targets were selected according to topological parameters. And the enrichment analysis was carried out to explore the mechanism of action of TQTS. Moreover, molecular docking was performed to study the interaction between the selected ligands and receptors related to psoriasis. Result and Conclusion: Eighty-five active compounds of TQTS were screened, with corresponding 270 targets, and 313 differentially expressed genes were identified. Additionally, enrichment analysis showed that the targets of TQTS for treating psoriasis were mainly involved in multiple biological processes, including apoptosis, growth factor response, etc., and related pathways including PI3K-Akt and MAPK signaling pathway, and so on. Genes such as NFKB1, TP53, and MAPK1 are the key genes in the gene pathway network of TQTS against psoriasis. The 4 main active components of TQTS have certain binding activity with 13 potential targets, and the stability of their interaction with AKT1 is found to be the most efficient, which indicates the potential mechanism of TQTS on psoriasis.
    Type of Medium: Online Resource
    ISSN: 1574-8936
    URL: Article
    DOI: 10.2174/1574893616666210315093639
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2021
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    SIMEON: Prediction of Chemical-protein Interaction via Stacked Bi-GRU-normalization Network and External Biomedical Knowledge
    Bentham Science Publishers Ltd. ; 2022
    In:  Current Bioinformatics Vol. 17, No. 9 ( 2022-11), p. 848-859
    Details
    In: Current Bioinformatics, Bentham Science Publishers Ltd., Vol. 17, No. 9 ( 2022-11), p. 848-859
    Abstract: Chemical compounds and proteins/genes are an important class of entities in biomedical research, and their interactions play a key role in precision medicine, drug discovery, basic clinical research, and building knowledge bases. Many computational methods have been proposed to identify chemical–protein interactions. However, the majority of these proposed models cannot model long-distance dependencies between chemical and protein, and the neural networks used to suffer from gradient descent, with little taking into account the characteristics of the chemical structure characteristics of the compound. Methods: To address the above limitations, we propose a novel model, SIMEON, to identify chemical– protein interactions. First, an input sequence is represented with pre-trained language model and an attention mechanism is used to uncover contribution degree of different words to entity relations and potential semantic information. Secondly, key features are extracted by a multi-layer stacked Bidirectional Gated Recurrent Units (Bi-GRU)-normalization residual network module to resolve higherorder dependencies while overcoming network degradation. Finally, the representation is introduced to be enhanced by external knowledge regarding the chemical structure characteristics of the compound external knowledge Results: Excellent experimental results show that our stacked integration model combines the advantages of Bi-GRU, normalization methods, and external knowledge to improve the performance of the model by complementing each other Conclusion: Our proposed model shows good performance in chemical-protein interaction extraction, and it can be used as a useful complement to biological experiments to identify chemical-protein interactions.
    Type of Medium: Online Resource
    ISSN: 1574-8936
    URL: Article
    DOI: 10.2174/1574893617666220718104518
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2022
    SSG: 12
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    Online Resource
  • 5
    Online Resource
    Online Resource
    Recent Patents on Long Distance Pneumatic Conveying Technology
    Bentham Science Publishers Ltd. ; 2023
    In:  Recent Patents on Engineering Vol. 18 ( 2023-09-14)
    Details
    In: Recent Patents on Engineering, Bentham Science Publishers Ltd., Vol. 18 ( 2023-09-14)
    Abstract: Pneumatic conveying is the use of air flow energy to transport granular materials in the direction of airflow in a closed pipeline, which involves the disadvantages of low conveying efficiency and easy deposition of particles. Objective: It is necessary to develop pneumatic conveying devices to reduce particle deposition, promote particles to enter the flow field again to accelerate, and achieve the effect of extending the pneumatic conveying distance. Method: The anti-settling device re-accelerates the particles so that the particles return to the flow field, which effectively reduces the probability of settlement blockage of material particles during transportation. The pneumatic conveying pressurized separator uses a pot-shaped housing to generate an internal rotating flow field to screen particles, and the light dust adheres to the filter, reducing the possibility of pipeline dust explosion. Results: The anti-settling device can quickly replace the anti-settlement block according to the parameters of the conveying pipeline, which can effectively reduce the probability of settlement blockage of material particles during transportation. The pressurized separator can use the air compressor to cooperate with the return air pipe to effectively remove the dust in the pneumatic conveying pipe and carry out secondary pressurized transportation of the materials in the pneumatic conveying pipe, which improves the safety of pneumatic conveying. Conclusion: The above technology improves the efficiency of pneumatic conveying and gas utilization, enhances the speed of particle conveying, reduces particle settlement and collision, extends the distance of pneumatic conveying, and ensures the safety of pneumatic conveying and the feasibility of industrial applications.
    Type of Medium: Online Resource
    ISSN: 1872-2121
    URL: Article
    DOI: 10.2174/1872212118666230914095120
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2023
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  • 6
    Online Resource
    Online Resource
    Biomolecular-Level Event Detection: A New Representation of Generating Short Sentence and Sample Selection Strategy
    Bentham Science Publishers Ltd. ; 2019
    In:  Current Bioinformatics Vol. 14, No. 4 ( 2019-04-10), p. 359-370
    Details
    In: Current Bioinformatics, Bentham Science Publishers Ltd., Vol. 14, No. 4 ( 2019-04-10), p. 359-370
    Abstract: Biomolecular-level event extraction is one of the most important branches of information extraction. With the rapid growth of biomedical literature, it is difficult for researchers to manually obtain information of interest, e.g. unknown information of threatening human disease or some biological processes. Therefore, researchers are interested in automatically acquiring information of biomolecular-level events. However, the annotated biomolecular-level event corpus is limited and highly imbalanced, which affects the performance of the classification algorithms and can even lead to over-fitting. associations while known disease-lncRNA associations are required only. Method: In this paper, a new approach using the Pairwise model and convolutional neural network for biomolecular-level event extraction is introduced. The method can identify more accurate positive instances from unlabeled data to enlarge the labeled data. First, unlabeled samples are categorized using the Pairwise model. Then, the shortest dependency path with additional information is generated. Furthermore, two input forms with a new representation of the convolutional neural network model, which are dependency word sequence and dependency relation sequence are presented. Finally, with the sample selection strategy, the expanded labeled samples from unlabeled domain corpus incrementally enlarge the training data to improve the performance of the classifier. 〈 /P 〉 〈 P 〉 Result & Conclusion: Our proposed method achieved better performance than other excellent systems. This is due to our new representation of generated short sentence and proposed sample selection strategy, which greatly improved the accuracy of classification. The extensive experimental results indicate that the new method can effectively inculcate unlabeled data to improve the performance of classifier for biomolecular-level events extraction. 〈 /P 〉
    Type of Medium: Online Resource
    ISSN: 1574-8936
    URL: Article
    DOI: 10.2174/1574893614666190204153531
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2019
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    Diagnosability of Alternating Group Graphs with Missing Edges
    Bentham Science Publishers Ltd. ; 2018
    In:  Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) Vol. 11, No. 1 ( 2018-01-23)
    Details
    In: Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering), Bentham Science Publishers Ltd., Vol. 11, No. 1 ( 2018-01-23)
    Type of Medium: Online Resource
    ISSN: 2352-0965
    URL: Article
    DOI: 10.2174/2352096510666171107155511
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2018
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  • 8
    Online Resource
    Online Resource
    Water Boundary Line Detection for Unmanned Surface Vehicles
    Bentham Science Publishers Ltd. ; 2020
    In:  Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) Vol. 13, No. 8 ( 2020-12-03), p. 1145-1152
    Details
    In: Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering), Bentham Science Publishers Ltd., Vol. 13, No. 8 ( 2020-12-03), p. 1145-1152
    Abstract: Unmanned Surface Vehicles (USV) can undertake risks or special tasks in marine independently and will be widely used in the future. In the autonomous navigation of USV equipped with vision camera, the water boundary line needs to be detected in real time and it is one of these key intelligent environment perception methods for USV. Methods: An efficient water boundary line detection method based on Gray Level Co-occurrence Matrix (GLCM) texture entropy is proposed. In image preprocessing, the high-brightness areas are eliminated to avoid the effects of water boundary line detection. Results: GLCM entropy is employed to segment water, land and air for water line regression. The proposed method is efficient for the images with high-brightness areas. Conclusion: The experimental results demonstrate that the proposed method is not only more accurate than the existing water boundary line detection method, but also has good real-time performance and is suitable for the application in USV.
    Type of Medium: Online Resource
    ISSN: 2352-0965
    URL: Article
    DOI: 10.2174/2352096513999200519075215
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2020
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  • 9
    Online Resource
    Online Resource
    PARP1: A Promising Target for the Development of PARP1-based Candidates for Anticancer Intervention
    Bentham Science Publishers Ltd. ; 2016
    In:  Current Medicinal Chemistry Vol. 23, No. 17 ( 2016-06-03), p. 1756-1774
    Details
    In: Current Medicinal Chemistry, Bentham Science Publishers Ltd., Vol. 23, No. 17 ( 2016-06-03), p. 1756-1774
    Type of Medium: Online Resource
    ISSN: 0929-8673
    URL: Article
    DOI: 10.2174/0929867321666140915143516
    Language: English
    Publisher: Bentham Science Publishers Ltd.
    Publication Date: 2016
    SSG: 15,3
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