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  • MDPI AG  (18)
  • 1
    Online Resource
    Online Resource
    Prediction of Buckwheat Maturity in UAV-RGB Images Based on Recursive Feature Elimination Cross-Validation: A Case Study in Jinzhong, Northern China
    MDPI AG ; 2022
    In:  Plants Vol. 11, No. 23 ( 2022-11-27), p. 3257-
    Details
    In: Plants, MDPI AG, Vol. 11, No. 23 ( 2022-11-27), p. 3257-
    Abstract: Buckwheat is an important minor grain crop with medicinal and edible functions. The accurate judgment of buckwheat maturity is beneficial to reduce harvest losses and improve yield. With the rapid development of unmanned aerial vehicle (UAV) technology, it has been widely used to predict the maturity of agricultural products. This paper proposed a method using recursive feature elimination cross-validation (RFECV) combined with multiple regression models to predict the maturity of buckwheat in UAV-RGB images. The images were captured in the buckwheat experimental field of Shanxi Agricultural University in Jinzhong, Northern China, from September to October in 2021. The variety was sweet buckwheat of “Jinqiao No. 1”. In order to deeply mine the feature vectors that highly correlated with the prediction of buckwheat maturity, 22 dimensional features with 5 vegetation indexes, 9 color features, and 8 texture features of buckwheat were selected initially. The RFECV method was adopted to obtain the optimal feature vector dimensions and combinations with six regression models of decision tree regression, linear regression, random forest regression, AdaBoost regression, gradient lifting regression, and extreme random tree regression. The coefficient of determination (R2) and root mean square error (RMSE) were used to analyze the different combinations of the six regression models with different feature spaces. The experimental results show that the single vegetation index performed poorly in the prediction of buckwheat maturity; the prediction result of feature space “5” combined with the gradient lifting regression model performed the best; and the R2 and RMSE were 0.981 and 1.70 respectively. The research results can provide an important theoretical basis for the prediction of the regional maturity of crops.
    Type of Medium: Online Resource
    ISSN: 2223-7747
    URL: Article
    DOI: 10.3390/plants11233257
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704341-1
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  • 2
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    Polychlorinated Diphenyl Ethers in the Environment: A Review and Future Perspectives
    MDPI AG ; 2023
    In:  International Journal of Environmental Research and Public Health Vol. 20, No. 5 ( 2023-02-23), p. 3982-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 20, No. 5 ( 2023-02-23), p. 3982-
    Abstract: Polychlorinated diphenyl ethers (PCDEs) are a class of synthetic halogenated aromatic compounds, which have gradually attracted widespread attention due to potential environmental risks to humans and ecosystems. This paper presents a literature review of research on PCDEs using PubMed, Web of Science and Google Scholar as search engines/databases with no constraints on publishing year or number. A total of 98 publications on the sources, environmental levels, environmental behavior and fate, synthesis and analysis and toxicology of PCDEs were retrieved. Existing studies have shown that PCDEs widely exist in the environment with the ability of long-range transport, bioaccumulation and biomagnification, which are almost comparable to polychlorinated biphenyls. They can elicit adverse effects including hepatic oxidative stress, immunosuppression, endocrine disorders, growth retardation, malformations, reduced fertility and increased mortality in organisms, among which some seem to be related to the activation of the aryl hydrocarbon receptor. PCDEs can be metabolized into other organic pollutants, such as hydroxylated and methoxylated PCDEs and even polychlorinated dibenzo-p-dioxins and furans through biotransformation, photolysis and pyrolysis reactions in the environment. Compared with reviews on PCDEs published previously, some new information and findings are summarized in this review, such as new sources, current environmental exposure levels, main metabolism pathways in aquatic organisms, acute toxicity data for more species and relationships between structural parameters and toxicity and bioaccumulation potentials of PCDE congeners. Finally, current research deficiencies and future research perspectives are proposed to facilitate the assessment of health and ecological risks of PCDEs.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph20053982
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2175195-X
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  • 3
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    A Theoretical Study of the Interactions between Persistent Organic Pollutants and Graphene Oxide
    MDPI AG ; 2022
    In:  International Journal of Environmental Research and Public Health Vol. 19, No. 18 ( 2022-09-09), p. 11340-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 19, No. 18 ( 2022-09-09), p. 11340-
    Abstract: Persistent organic pollutants (POPs) have adverse effects on the human health and ecosystem functioning. Graphene oxide (GO) has been developed to remove trace levels of POPs from wastewater samples. However, many questions involved in these processes are still unresolved (e.g., the role of π–π interaction, the effect of GO on the degradation of POPs, and so on). Revealing the microscopic interactions between GO and POPs is of benefit to resolve these questions. In the present study, a quantum chemical calculation was used to calculate the molecular doping and adsorption energy between eight representative POPs and GO. The influences of GO on the thermodynamic parameters, such as the Gibbs free energy and the highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, were also reported. We found the molecular doping is dependent on the species of POPs. The adsorption energy of the majority of POPs on GO is between 7 and 8 kJ/mol. Consequently, the GO may make degradation of POPs in wastewater more productive and lead to a change of kinetics of the degradation of POPs.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph191811340
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2175195-X
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  • 4
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    The Role of Oxidative Stress in Skeletal Muscle Myogenesis and Muscle Disease
    MDPI AG ; 2022
    In:  Antioxidants Vol. 11, No. 4 ( 2022-04-11), p. 755-
    Details
    In: Antioxidants, MDPI AG, Vol. 11, No. 4 ( 2022-04-11), p. 755-
    Abstract: The contractile activity, high oxygen consumption and metabolic rate of skeletal muscle cause it to continuously produce moderate levels of oxidant species, such as reactive oxygen species (ROS) and reactive nitrogen species (RNS). Under normal physiological conditions, there is a dynamic balance between the production and elimination of ROS/RNS. However, when the oxidation products exceed the antioxidant defense capacity, the body enters a state of oxidative stress. Myogenesis is an important process to maintain muscle homeostasis and the physiological function of skeletal muscle. Accumulating evidence suggests that oxidative stress plays a key role in myogenesis and skeletal muscle physiology and pathology. In this review, we summarize the sources of reactive oxygen species in skeletal muscle and the causes of oxidative stress and analyze the key role of oxidative stress in myogenesis. Then, we discuss the relationship between oxidative stress and muscle homeostasis and physiopathology. This work systematically summarizes the role of oxidative stress in myogenesis and muscle diseases and provides targets for subsequent antioxidant therapy and repair of inflammatory damage in noninflammatory muscle diseases.
    Type of Medium: Online Resource
    ISSN: 2076-3921
    URL: Article
    DOI: 10.3390/antiox11040755
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704216-9
    SSG: 15,3
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  • 5
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    New Approaches for Robust and Efficient Detection of Persistent Scatterers in SAR Tomography
    MDPI AG ; 2019
    In:  Remote Sensing Vol. 11, No. 3 ( 2019-02-11), p. 356-
    Details
    In: Remote Sensing, MDPI AG, Vol. 11, No. 3 ( 2019-02-11), p. 356-
    Abstract: Persistent scatterer interferometry (PSI) has the ability to acquire submeter-scale digital elevation model (DEM) and millimeter-scale deformation. A limitation to the application of PSI is that only single persistent scatterers (SPSs) are detected, and pixels with multiple dominant scatterers from different sources are discarded in PSI processing. Synthetic aperture radar (SAR) tomography is a promising technique capable of resolving layovers. In this paper, new approaches based on a novel two-tier network aimed at robust and efficient detection of persistent scatterers (PSs) are presented. The calibration of atmospheric phase screen (APS) and the detection of PSs can be jointly implemented in the novel two-tier network. A residue-to-signal ratio (RSR) estimator is proposed to evaluate whether the APS is effectively calibrated and to select reliable PSs with accurate estimation. In the first-tier network, a Delaunay triangulation network is constructed for APS calibration and SPS detection. RSR thresholding is used to adjust the first-tier network by discarding arcs and SPS candidates (SPSCs) with inaccurate estimation, yielding more than one main network in the first-tier network. After network adjustment, we attempt to establish reliable SPS arcs to connect the main isolated networks, and the expanded largest connected network is then formed with more manual structure information subtracted. Furthermore, rather than the weighted least square (WLS) estimator, a network decomposition WLS (ND-WLS) estimator is proposed to accelerate the retrieval of absolute parameters from the expanded largest connected network, which is quite useful for large network inversion. In the second-tier network, the remaining SPSs and all the double PSs (DPSs) are detected and estimated with reference to the expanded largest connected network. Compared with traditional two-tier network-based methods, more PSs can be robustly and efficiently detected by the proposed new approaches. Experiments on interferometric high resolution TerraSAR-X SAR images are given to demonstrate the merits of the new approaches.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs11030356
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2513863-7
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  • 6
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    Sustainable Road Pothole Detection: A Crowdsourcing Based Multi-Sensors Fusion Approach
    MDPI AG ; 2023
    In:  Sustainability Vol. 15, No. 8 ( 2023-04-13), p. 6610-
    Details
    In: Sustainability, MDPI AG, Vol. 15, No. 8 ( 2023-04-13), p. 6610-
    Abstract: Real-time road quality monitoring, involves using technologies to collect data on the conditions of the road, including information on potholes, cracks, and other defects. This information can help to improve safety for drivers and reduce costs associated with road damage. Traditional methods are time-consuming and expensive, leading to limited spatial coverage and delayed responses to road conditions. With the widespread use of smartphones and ubiquitous computing technologies, data can be collected from built-in sensors of mobile phones and in-vehicle video, on a large scale. This has raised the question of how these data can be used for road pothole detection and has significant practical relevance. Current methods either use acceleration sequence classification techniques, or image recognition techniques based on deep learning. However, accelerometer-based detection has limited coverage and is sensitive to the driving speed, while image recognition-based detection is highly affected by ambient light. To address these issues, this study proposes a method that utilizes the fusion of accelerometer data and in-vehicle video data, which is uploaded by the participating users. The preprocessed accelerometer data and intercepted video frames, were then encoded into real-valued vectors, and projected into the public space. A deep learning-based training approach was used to learn from the public space and identify road anomalies. Spatial density-based clustering was implemented in a multi-vehicle scenario, to improve reliability and optimize detection results. The performance of the model is evaluated with confusion matrix-based classification metrics. Real-world vehicle experiments are carried out, and the results demonstrate that the proposed method can improve accuracy by 6% compared to the traditional method. Consequently, the proposed method provides a novel approach for large-scale pavement anomaly detection.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su15086610
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2518383-7
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  • 7
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    A Decentralized LQR Output Feedback Control for Aero-Engines
    MDPI AG ; 2023
    In:  Actuators Vol. 12, No. 4 ( 2023-04-06), p. 164-
    Details
    In: Actuators, MDPI AG, Vol. 12, No. 4 ( 2023-04-06), p. 164-
    Abstract: Aero-engine control systems generally adopt centralized or distributed control schemes, in which all or most of the tasks of the control system are mapped to a specific processor for processing. The performance and reliability of this processor have a significant impact on the control system. Based on the aero-engine distributed control system (DCS), we propose a decentralized controller scheme. The characteristic of this scheme is that a network composed of a group of nodes acts as the controller of the system, so that there is no core control processor in the system, and the computation is distributed throughout the entire network. An LQR output feedback control is constructed using system input and output, and the control tasks executed on each node in the decentralized controller are obtained. The constructed LQR output feedback is equivalent to the optimal LQR state feedback. The primal-dual principle is used to tune the parameters of each decentralized controller. The parameter tuning algorithm is simple to calculate, making it conducive for engineering applications. Finally, the proposed scheme was verified by simulation. The simulation results show that a high-precision feedback gain matrix can be obtained with a maximum of eight iterations. The parameter tuning algorithm proposed in this paper converges quickly during the calculation process, and the constructed output feedback scheme achieves equivalent performance to the state feedback scheme, demonstrating the effectiveness of the design scheme proposed in this paper.
    Type of Medium: Online Resource
    ISSN: 2076-0825
    URL: Article
    DOI: 10.3390/act12040164
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2682469-3
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  • 8
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    A Linear Iterative Controller for Software Defined Control Systems of Aero-Engines Based on LMI
    MDPI AG ; 2023
    In:  Actuators Vol. 12, No. 7 ( 2023-06-23), p. 259-
    Details
    In: Actuators, MDPI AG, Vol. 12, No. 7 ( 2023-06-23), p. 259-
    Abstract: Currently, most control systems of the aero-engines possess a central controller. The core tasks for the control system, such as control law calculations, are executed in this central controller, and its performance and reliability greatly impact the entire control system. This paper introduces a control system design named Software Defined Control Systems (SDCS), which features a controller-decentralized architecture. In SDCS, a network composed of a set of nodes serves as the controller, so there is no central controller in the system, and computations are distributed throughout the entire network. Since the controller is decentralized, there is a need for decentralized control tasks. To address this, this paper introduces a method for designing decentralized control tasks using periodic linear iteration. Each node in the network periodically broadcasts its own state and updates its next-step state as a weighted sum of its current state and the received current states of other nodes in the network. Each node in the network acts as a linear dynamic controller and maintains an internal state through information exchange with other nodes. We modeled the decentralized controller and obtained the model of the entire control system, and the workload of each obtained decentralized control task is balanced. Then, we obtained a parameter tuning method for each decentralized controller node based on Linear Matrix Inequalities (LMI) to stabilize the closed-loop system. Finally, the effectiveness of the proposed method was verified through digital simulation.
    Type of Medium: Online Resource
    ISSN: 2076-0825
    URL: Article
    DOI: 10.3390/act12070259
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2682469-3
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  • 9
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    Mechanically Enhanced Electrical Conductivity of Polydimethylsiloxane-Based Composites by a Hot Embossing Process
    MDPI AG ; 2019
    In:  Polymers Vol. 11, No. 1 ( 2019-01-02), p. 56-
    Details
    In: Polymers, MDPI AG, Vol. 11, No. 1 ( 2019-01-02), p. 56-
    Abstract: Electrically conductive polymer composites are in high demand for modern technologies, however, the intrinsic brittleness of conducting conjugated polymers and the moderate electrical conductivity of engineering polymer/carbon composites have highly constrained their applications. In this work, super high electrical conductive polymer composites were produced by a novel hot embossing design. The polydimethylsiloxane (PDMS) composites containing short carbon fiber (SCF) exhibited an electrical percolation threshold at 0.45 wt % and reached a saturated electrical conductivity of 49 S/m at 8 wt % of SCF. When reducing the sample thickness from 1.0 to 0.1 mm by the hot embossing process, a compression-induced percolation threshold occurred at 0.3 wt %, while the electrical conductivity was further enhanced to 378 S/m at 8 wt % SCF. Furthermore, the addition of a second nanofiller of 1 wt %, such as carbon nanotube or conducting carbon black, further increased the electrical conductivity of the PDMS/SCF (8 wt %) composites to 909 S/m and 657 S/m, respectively. The synergy of the densified conducting filler network by the mechanical compression and the hierarchical micro-/nano-scale filler approach has realized super high electrically conductive, yet mechanically flexible, polymer composites for modern flexible electronics applications.
    Type of Medium: Online Resource
    ISSN: 2073-4360
    URL: Article
    DOI: 10.3390/polym11010056
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2527146-5
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  • 10
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    Research on a Real-Time Driver Fatigue Detection Algorithm Based on Facial Video Sequences
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 4 ( 2022-02-21), p. 2224-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 4 ( 2022-02-21), p. 2224-
    Abstract: The research on driver fatigue detection is of great significance to improve driving safety. This paper proposes a real-time comprehensive driver fatigue detection algorithm based on facial landmarks to improve the detection accuracy, which detects the driver’s fatigue status by using facial video sequences without equipping their bodies with other intelligent devices. A tasks-constrained deep convolutional network is constructed to detect the face region based on 68 key points, which can solve the optimization problem caused by the different convergence speeds of each task. According to the real-time facial video images, the eye feature of the eye aspect ratio (EAR), mouth aspect ratio (MAR) and percentage of eye closure time (PERCLOS) are calculated based on facial landmarks. A comprehensive driver fatigue assessment model is established to assess the fatigue status of drivers through eye/mouth feature selection. After a series of comparative experiments, the results show that this proposed algorithm achieves good performance in both accuracy and speed for driver fatigue detection.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app12042224
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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