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  • Open Access

    REVIEW

    Development of PROTACS degrading KRAS and SOS1

    GERHARD HAMILTON*, MARIE-THERESE EGGERSTORFER, SANDRA STICKLER

    Oncology Research, Vol.32, No.8, pp. 1257-1264, 2024, DOI:10.32604/or.2024.051653 - 17 July 2024

    Abstract The Kirsten rat sarcoma virus—son of sevenless 1 (KRAS-SOS1) axis drives tumor growth preferentially in pancreatic, colon, and lung cancer. Now, KRAS G12C mutated tumors can be successfully treated with inhibitors that covalently block the cysteine of the switch II binding pocket of KRAS. However, the range of other KRAS mutations is not amenable to treatment and the G12C-directed agents Sotorasib and Adragrasib show a response rate of only approximately 40%, lasting for a mean period of 8 months. One approach to increase the efficacy of inhibitors is their inclusion into proteolysis-targeting chimeras (PROTACs), which… More > Graphic Abstract

    Development of PROTACS degrading KRAS and SOS1

  • Open Access

    ARTICLE

    Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

    Zhuoqun Xia1, Hangyu Hu1, Wenjing Li2,3, Qisheng Jiang1, Lan Pu1, Yicong Shu1, Arun Kumar Sangaiah4,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 409-430, 2024, DOI:10.32604/cmes.2024.030052 - 16 April 2024

    Abstract Early screening of diabetes retinopathy (DR) plays an important role in preventing irreversible blindness. Existing research has failed to fully explore effective DR lesion information in fundus maps. Besides, traditional attention schemes have not considered the impact of lesion type differences on grading, resulting in unreasonable extraction of important lesion features. Therefore, this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator (MPAG) and a lesion localization module (LLM). Firstly, MPAG is used to predict patches of different sizes and generate a weighted attention map based on the prediction score and… More >

  • Open Access

    ARTICLE

    Combined Optimal Dispatch of Thermal Power Generators and Energy Storage Considering Thermal Power Deep Peak Clipping and Wind Energy Emission Grading Punishment

    Junhui Li1, Xuanzhong Luo1,2, Changxing Ge3, Cuiping Li1,*, Changrong Wang4

    Energy Engineering, Vol.121, No.4, pp. 869-893, 2024, DOI:10.32604/ee.2024.029722 - 26 March 2024

    Abstract Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing, which affects the stabilization of the PS (power system). This paper suggests integrated optimal dispatching of thermal power generators and BESS (battery energy storage system) taking wind energy emission grading punishment and deep peak clipping into consideration. Firstly, in order to minimize wind abandonment, a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced, and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.… More > Graphic Abstract

    Combined Optimal Dispatch of Thermal Power Generators and Energy Storage Considering Thermal Power Deep Peak Clipping and Wind Energy Emission Grading Punishment

  • Open Access

    ARTICLE

    Acidic Magnetic Biocarbon-Enabled Upgrading of Biomass-Based Hexanedione into Pyrroles

    Zhimei Li1, Kuan Tian2, Keping Wang2, Zhengyi Li2, Haoli Qin1,*, Hu Li2,*

    Journal of Renewable Materials, Vol.11, No.11, pp. 3847-3865, 2023, DOI:10.32604/jrm.2023.030122 - 31 October 2023

    Abstract Sustainable acquisition of bioactive compounds from biomass-based platform molecules is a green alternative for existing CO2-emitting fossil-fuel technologies. Herein, a core–shell magnetic biocarbon catalyst functionalized with sulfonic acid (Fe3O4@SiO2@chitosan-SO3H, MBC-SO3H) was prepared to be efficient for the synthesis of various N-substituted pyrroles (up to 99% yield) from bio-based hexanedione and amines under mild conditions. The abundance of Brønsted acid sites in the MBC-SO3H ensured smooth condensation of 2,5-hexanedione with a variety of amines to produce N-substituted pyrroles. The reaction was illustrated to follow the conventional PallKnorr coupling pathway, which includes three cascade reaction steps: amination, loop closure… More > Graphic Abstract

    Acidic Magnetic Biocarbon-Enabled Upgrading of Biomass-Based Hexanedione into Pyrroles

  • Open Access

    ARTICLE

    Optimization of DC Resistance Divider Up to 1200 kV Using Thermal and Electric Field Analysis

    Dengyun Li, Baiwen Du, Kai Zhu, Jicheng Yu*, Siyuan Liang, Changxi Yue

    Energy Engineering, Vol.120, No.11, pp. 2611-2628, 2023, DOI:10.32604/ee.2023.028282 - 31 October 2023

    Abstract Self-heating and electric field distribution are the primary factors affecting the accuracy of the Ultra High Voltage Direct Current (UHVDC) resistive divider. Reducing the internal temperature rise of the voltage divider caused by self-heating, reducing the maximum electric field strength of the voltage divider, and uniform electric field distribution can effectively improve the UHVDC resistive divider’s accuracy. In this paper, thermal analysis and electric field distribution optimization design of 1200 kV UHVDC resistive divider are carried out: (1) Using the proposed iterative algorithm, the heat dissipation and temperature distribution of the high voltage DC resistive… More >

  • Open Access

    ARTICLE

    An Automatic Classification Grading of Spinach Seedlings Water Stress Based on N-MobileNetXt

    Yanlei Xu, Xue Cong, Yuting Zhai, Zhiyuan Gao, Helong Yu*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3019-3037, 2023, DOI:10.32604/iasc.2023.040330 - 11 September 2023

    Abstract To solve inefficient water stress classification of spinach seedlings under complex background, this study proposed an automatic classification method for the water stress level of spinach seedlings based on the N-MobileNetXt (NCAM+MobileNetXt) network. Firstly, this study reconstructed the Sandglass Block to effectively increase the model accuracy; secondly, this study introduced the group convolution module and a two-dimensional adaptive average pool, which can significantly compress the model parameters and enhance the model robustness separately; finally, this study innovatively proposed the Normalization-based Channel Attention Module (NCAM) to enhance the image features obviously. The experimental results showed that More >

  • Open Access

    ARTICLE

    PLDMLT: Multi-Task Learning of Diabetic Retinopathy Using the Pixel-Level Labeled Fundus Images

    Hengyang Liu, Chuncheng Huang*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1745-1761, 2023, DOI:10.32604/cmc.2023.040710 - 30 August 2023

    Abstract In the field of medical images, pixel-level labels are time-consuming and expensive to acquire, while image-level labels are relatively easier to obtain. Therefore, it makes sense to learn more information (knowledge) from a small number of hard-to-get pixel-level annotated images to apply to different tasks to maximize their usefulness and save time and training costs. In this paper, using Pixel-Level Labeled Images for Multi-Task Learning (PLDMLT), we focus on grading the severity of fundus images for Diabetic Retinopathy (DR). This is because, for the segmentation task, there is a finely labeled mask, while the severity… More >

  • Open Access

    ARTICLE

    Leveraging Retinal Fundus Images with Deep Learning for Diabetic Retinopathy Grading and Classification

    Mohammad Yamin1,*, Sarah Basahel1, Saleh Bajaba2, Mona Abusurrah3, E. Laxmi Lydia4

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1901-1916, 2023, DOI:10.32604/csse.2023.036455 - 09 February 2023

    Abstract Recently, there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy (DR). DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged people in the developed world. Initial detection of DR becomes necessary for decreasing the disease severity by making use of retinal fundus images. This article introduces a Deep Learning Enabled Large Scale Healthcare Decision Making for Diabetic Retinopathy (DLLSHDM-DR) on Retinal Fundus Images. The proposed DLLSHDM-DR technique intends to assist physicians with the DR decision-making method. In the DLLSHDM-DR… More >

  • Open Access

    ARTICLE

    LuNet-LightGBM: An Effective Hybrid Approach for Lesion Segmentation and DR Grading

    Sesikala Bapatla1, J. Harikiran2,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 597-617, 2023, DOI:10.32604/csse.2023.034998 - 20 January 2023

    Abstract Diabetes problems can lead to an eye disease called Diabetic Retinopathy (DR), which permanently damages the blood vessels in the retina. If not treated early, DR becomes a significant reason for blindness. To identify the DR and determine the stages, medical tests are very labor-intensive, expensive, and time-consuming. To address the issue, a hybrid deep and machine learning technique-based autonomous diagnostic system is provided in this paper. Our proposal is based on lesion segmentation of the fundus images based on the LuNet network. Then a Refined Attention Pyramid Network (RAPNet) is used for extracting global… More >

  • Open Access

    ARTICLE

    An Auto-Grading Oriented Approach for Off-Line Handwritten Organic Cyclic Compound Structure Formulas Recognition

    Ting Zhang, Yifei Wang, Xinxin Jin, Zhiwen Gu, Xiaoliang Zhang, Bin He*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2267-2285, 2023, DOI:10.32604/cmes.2023.023229 - 23 November 2022

    Abstract Auto-grading, as an instruction tool, could reduce teachers’ workload, provide students with instant feedback and support highly personalized learning. Therefore, this topic attracts considerable attentions from researchers recently. To realize the automatic grading of handwritten chemistry assignments, the problem of chemical notations recognition should be solved first. The recent handwritten chemical notations recognition solutions belonging to the end-to-end trainable category suffered from the problem of lacking the accurate alignment information between the input and output. They serve the aim of reading notations into electrical devices to better prepare relevant e-documents instead of auto-grading handwritten assignments.… More >

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