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  • MDPI AG  (51)
  • 1
    Online Resource
    Online Resource
    Ethyl Methyl Sulfonate-Induced Mutagenesis and Its Effects on Peanut Agronomic, Yield and Quality Traits
    MDPI AG ; 2020
    In:  Agronomy Vol. 10, No. 5 ( 2020-05-05), p. 655-
    Details
    In: Agronomy, MDPI AG, Vol. 10, No. 5 ( 2020-05-05), p. 655-
    Abstract: Peanut is an important oilseed and food crop worldwide; however, the development of new cultivars is limited by its remarkably low genetic variability. Therefore, in order to enhance peanut genetic variability, here, we treated two widely cultivated peanut genotypes, Huayu 22 and Yueyou 45, with different concentrations of the mutagen ethyl methyl sulfonate (EMS) for different durations. Based on median lethal dose (LD50) value, optimal EMS treatment concentrations for each duration were identified for each genotype. Mutants induced by EMS differed in various phenotypic traits, including plant height, number of branches, leaf characteristics, and yield and quality in plants of the M2 generation. Moreover, we identified potentially useful mutants associated with dwarfism, leaf color and shape, high oil and/or protein content, seed size and testa color, among individuals of the M2 generation. Mutations were stably inherited in M3-generation individuals. In addition to their contribution to the study and elucidation of the mechanisms underlying the regulation of the expression of some important agronomic traits, the mutants obtained in this study provide valuable germplasm resources for use in peanut improvement programs.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy10050655
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2607043-1
    SSG: 23
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  • 2
    Online Resource
    Online Resource
    A Monocular Vision Obstacle Avoidance Method Applied to Indoor Tracking Robot
    MDPI AG ; 2021
    In:  Drones Vol. 5, No. 4 ( 2021-09-26), p. 105-
    Details
    In: Drones, MDPI AG, Vol. 5, No. 4 ( 2021-09-26), p. 105-
    Abstract: The overall safety of a building can be effectively evaluated through regular inspection of the indoor walls by unmanned ground vehicles (UGVs). However, when the UGV performs line patrol inspections according to the specified path, it is easy to be affected by obstacles. This paper presents an obstacle avoidance strategy for unmanned ground vehicles in indoor environments. The proposed method is based on monocular vision. Through the obtained environmental information in front of the unmanned vehicle, the obstacle orientation is determined, and the moving direction and speed of the mobile robot are determined based on the neural network output and confidence. This paper also innovatively adopts the method of collecting indoor environment images based on camera array and realizes the automatic classification of data sets by arranging cameras with different directions and focal lengths. In the training of a transfer neural network, aiming at the problem that it is difficult to set the learning rate factor of the new layer, the improved bat algorithm is used to find the optimal learning rate factor on a small sample data set. The simulation results show that the accuracy can reach 94.84%. Single-frame evaluation and continuous obstacle avoidance evaluation are used to verify the effectiveness of the obstacle avoidance algorithm. The experimental results show that an unmanned wheeled robot with a bionic transfer-convolution neural network as the control command output can realize autonomous obstacle avoidance in complex indoor scenes.
    Type of Medium: Online Resource
    ISSN: 2504-446X
    URL: Article
    DOI: 10.3390/drones5040105
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2934569-8
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  • 3
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    Bumpless Transfer of Uncertain Switched System and Its Application to Turbofan Engines
    MDPI AG ; 2021
    In:  Energies Vol. 14, No. 16 ( 2021-08-23), p. 5204-
    Details
    In: Energies, MDPI AG, Vol. 14, No. 16 ( 2021-08-23), p. 5204-
    Abstract: Nonlinear control problems in turbofan engines are challenging. No single nonlinear controller can achieve desired control effects in a full flight envelope, but in the case of multiple controllers, there exist problems in the bumpless transfer between different controllers. To this end, this paper presents a bumpless transfer mechanism for an uncertain switched system based on integral sliding mode control (ISMC), and the mechanism can be used for the speed control of turbofan engines. The uncertain switched system is used to describe the turbofan engine dynamics. Then, the ISMC controller is derived for subsystems of the uncertain switched system. A resetting scheme is introduced for the ISMC controller to ensure the continuity of control inputs during the controller transition, as well as the bumpless transfer. In view of the transient behavior caused by controller switching, the global stability of the switched system is analyzed using the multiple Lyapunov function approach and average dwell time condition. Simulation results validate that the designed resetting scheme can ensure the continuity of control input signals and avoid the instability caused by high-frequency controller switching, and increase the control effectiveness of the proposed ISMC method within the full flight envelope.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en14165204
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2437446-5
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  • 4
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    Online Resource
    Osteocytic Pericellular Matrix (PCM): Accelerated Degradation under In Vivo Loading and Unloading Conditions Using a Novel Imaging Approach
    MDPI AG ; 2021
    In:  Genes Vol. 13, No. 1 ( 2021-12-28), p. 72-
    Details
    In: Genes, MDPI AG, Vol. 13, No. 1 ( 2021-12-28), p. 72-
    Abstract: The proteoglycan-containing pericellular matrix (PCM) controls both the biophysical and biochemical microenvironment of osteocytes, which are the most abundant cells embedded and dispersed in bones. As a molecular sieve, osteocytic PCMs not only regulate mass transport to and from osteocytes but also act as sensors of external mechanical environments. The turnover of osteocytic PCM remains largely unknown due to technical challenges. Here, we report a novel imaging technique based on metabolic labeling and “click-chemistry,” which labels de novo PCM as “halos” surrounding osteocytes in vitro and in vivo. We then tested the method and showed different labeling patterns in young vs. old bones. Further “pulse-chase” experiments revealed dramatic difference in the “half-life” of PCM of cultured osteocytes (~70 h) and that of osteocytes in vivo (~75 d). When mice were subjected to either 3-week hindlimb unloading or 7-week tibial loading (5.1 N, 4 Hz, 3 d/week), PCM half-life was shortened (~20 d) and degradation accelerated. Matrix metallopeptidase MMP-14 was elevated in mechanically loaded osteocytes, which may contribute to PCM degradation. This study provides a detailed procedure that enables semi-quantitative study of the osteocytic PCM remodeling in vivo and in vitro.
    Type of Medium: Online Resource
    ISSN: 2073-4425
    URL: Article
    DOI: 10.3390/genes13010072
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2527218-4
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  • 5
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    Phase-Separated Subcellular Compartmentation and Related Human Diseases
    MDPI AG ; 2022
    In:  International Journal of Molecular Sciences Vol. 23, No. 10 ( 2022-05-14), p. 5491-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 10 ( 2022-05-14), p. 5491-
    Abstract: In live cells, proteins and nucleic acids can associate together through multivalent interactions, and form relatively isolated phases that undertake designated biological functions and activities. In the past decade, liquid–liquid phase separation (LLPS) has gradually been recognized as a general mechanism for the intracellular organization of biomolecules. LLPS regulates the assembly and composition of dozens of membraneless organelles and condensates in cells. Due to the altered physiological conditions or genetic mutations, phase-separated condensates may undergo aberrant formation, maturation or gelation that contributes to the onset and progression of various diseases, including neurodegenerative disorders and cancers. In this review, we summarize the properties of different membraneless organelles and condensates, and discuss multiple phase separation-regulated biological processes. Based on the dysregulation and mutations of several key regulatory proteins and signaling pathways, we also exemplify how aberrantly regulated LLPS may contribute to human diseases.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms23105491
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 6
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    A Multi-Cavity Iterative Modeling Method for the Exhaust Systems of Altitude Ground Test Facilities
    MDPI AG ; 2022
    In:  Symmetry Vol. 14, No. 7 ( 2022-07-07), p. 1399-
    Details
    In: Symmetry, MDPI AG, Vol. 14, No. 7 ( 2022-07-07), p. 1399-
    Abstract: To solve the modeling problem of altitude ground test facility (AGTF) exhaust systems, which is caused by nonlinearity along the gas path and the difficulty of ejection factor calculation, a multi-cavity iterative modeling method is presented. The components of exhaust systems, such as the exhaust diffuser and cooler, are built with a series of volumes. It overcomes the disadvantage that traditional lumped-parameter models have, whereby they cannot calculate the dynamic parameters along the gas path. The exhaust system model is built with an iterative method based on multi-cavity components, and simulations are carried out under experimental conditions. The simulation results show that the maximum error of pressure is 2 kPa in the steady state and less than 6 kPa in the transient process compared with experimental data. Closed-loop simulations are also carried out to further verify the accuracy and effectiveness of the multi-cavity iterative exhaust system modeling method.
    Type of Medium: Online Resource
    ISSN: 2073-8994
    URL: Article
    DOI: 10.3390/sym14071399
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518382-5
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  • 7
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    Shear Behavior and Asperity Damage of 3D Rough Joints under CNS Boundary Conditions Based on CZM Simulation
    MDPI AG ; 2023
    In:  Sustainability Vol. 15, No. 6 ( 2023-03-13), p. 5064-
    Details
    In: Sustainability, MDPI AG, Vol. 15, No. 6 ( 2023-03-13), p. 5064-
    Abstract: Although boundary conditions can significantly impact the shear behaviors and asperity damage evolution of jointed rocks, numerical studies on the damage of 3D rough rock joints under the constant normal stiffness (CNS) boundary condition have rarely been reported. In this work, the three-dimensional model of the irregular joint surface is established by using point cloud reconstruction technology. Based on the cohesive zone model (CZM), we simulate the shear behavior of three-dimensional rough rock joints under the CNS boundary condition, which is realized by using embedded spring elements implemented with a Python subroutine. We conducted laboratory direct shear tests under CNS boundary conditions. The agreement with the laboratory experimental results verifies the fidelity of the numerical method. Our results show that boundary conditions can significantly affect the shear behavior of rock joints, especially in the post-peak stage. Under the same initial normal stress, the peak shear stress and the number of microcracks in the asperities increase significantly with the increase of normal stiffness. The proportion of shear cracks positively correlates with the normal stiffness, indicating that the normal stiffness affects the joint failure mode. The damaged area and the volume of asperities increase with the increase of normal stiffness. Moreover, the distribution of shear-induced asperity loss becomes more nonuniform, and the loss of joint roughness increases rapidly and nonlinearly.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su15065064
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2518383-7
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  • 8
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    Liquid Water Transport Characteristics and Droplet Dynamics of Proton Exchange Membrane Fuel Cells with 3D Wave Channel
    MDPI AG ; 2023
    In:  Energies Vol. 16, No. 16 ( 2023-08-09), p. 5892-
    Details
    In: Energies, MDPI AG, Vol. 16, No. 16 ( 2023-08-09), p. 5892-
    Abstract: Water management is a crucial aspect in the efficient functioning of proton exchange membrane fuel cells (PEMFCs). The presence of a two-phase flow, consisting of water and reactive gas, in the channel of the PEMFC is of utmost importance for effective water management. This study focuses on investigating the removal of liquid water in 3D wave channels and 2D straight channels using the volume of fluid method. The study analyzes the dynamic behavior of droplets emerging from the gas diffusion layer (GDL) into the channel under the influence of gas flow. The study also explores the effects of droplet growth, deformation, detachment, force, and pore size on critical water behavior and water content in the channel. The results indicate that the 3D wave channel is more effective in removing liquid water compared to the 2D straight channel. It is observed that increasing the velocity facilitates the discharge of liquid water. However, excessively high velocities lead to parasitic power losses. Furthermore, while larger pore sizes in the GDL are not advantageous for PEMFC performance, a moderate increase in pore size aids in the discharge of liquid water. The knowledge gained through this study deepens the understanding of droplet dynamics in PEMFC gas channels and assists in optimizing the design and operational conditions of these channels.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en16165892
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2437446-5
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  • 9
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    Recent Progress on the Key Materials and Components for Proton Exchange Membrane Fuel Cells in Vehicle Applications
    MDPI AG ; 2016
    In:  Energies Vol. 9, No. 8 ( 2016-07-29), p. 603-
    Details
    In: Energies, MDPI AG, Vol. 9, No. 8 ( 2016-07-29), p. 603-
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en9080603
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2437446-5
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  • 10
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    Research on Key Technology of Ship Re-Identification Based on the USV-UAV Collaboration
    MDPI AG ; 2023
    In:  Drones Vol. 7, No. 9 ( 2023-09-20), p. 590-
    Details
    In: Drones, MDPI AG, Vol. 7, No. 9 ( 2023-09-20), p. 590-
    Abstract: Distinguishing ship identities is critical in ensuring the safety and supervision of the marine agriculture and transportation industry. In this paper, we present a comprehensive investigation and validation of the progression of ship re-identification technology within a cooperative framework predominantly governed by UAVs. Our research revolves around the creation of a ship ReID dataset, the creation of a ship ReID dataset, the development of a feature extraction network, ranking optimization, and the establishment of a ship identity re-identification system built upon the collaboration of unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs). We introduce a ship ReID dataset named VesselID-700, comprising 56,069 images covering seven classes of typical ships. We also simulated the multi-angle acquisition state of UAVs to categorize the ship orientations within this dataset. To address the challenge of distinguishing between ships with small inter-class differences and large intra-class variations, we propose a fine-grained feature extraction network called FGFN. FGFN enhances the ResNet architecture with a self-attentive mechanism and generalized mean pooling. We also introduce a multi-task loss function that combines classification and triplet loss, incorporating hard sample mining. Ablation experiments on the VesselID-700 dataset demonstrate that the FGFN network achieves outstanding performance, with a Rank-1 accuracy of 89.78% and mAP of 65.72% at a state-of-the-art level. Generalization experiments on pedestrian and vehicle ReID datasets reveal that FGFN excels in recognizing other rigid body targets and diverse viewpoints. Furthermore, to further enhance the advantages of UAV-USV synergy in ship ReID performance, we propose a ranking optimization method based on the homologous fusion of multi-angle UAVs and heterologous fusion of USV-UAV collaborative architecture. This optimization leads to a significant 3% improvement in Rank-1 performance, accompanied by a 73% reduction in retrieval time cost.
    Type of Medium: Online Resource
    ISSN: 2504-446X
    URL: Article
    DOI: 10.3390/drones7090590
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2934569-8
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