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  • MDPI AG  (7)
  • Li, Zihan  (7)
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  • MDPI AG  (7)
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  • 1
    Online Resource
    Online Resource
    Autoformer-Based Model for Predicting and Assessing Wheat Quality Changes of Pesticide Residues during Storage
    MDPI AG ; 2023
    In:  Foods Vol. 12, No. 9 ( 2023-04-28), p. 1833-
    Details
    In: Foods, MDPI AG, Vol. 12, No. 9 ( 2023-04-28), p. 1833-
    Abstract: Proper grain storage plays a critical role in maintaining food quality. Among a variety of grains, wheat has emerged as one of the most important grain reserves globally due to its short growing period, high yield, and storage resistance. To improve the quality assessment of wheat during storage, this study collected and analyzed monitoring data from more than 20 regions in China, including information on storage environmental parameters and changes in wheat pesticide residue concentrations. Based on these factors, an Autoformer-based model was developed to predict the changes in wheat pesticide residue concentrations during storage. A comprehensive wheat quality assessment index Q was set for the predicted and true values of pesticide residue concentrations, then combined with the K-means++ algorithm to assess the quality of wheat during storage. The results of the study demonstrate that the Autoformer model achieved the optimal prediction results and the smallest error values. The mean absolute error (MAE) and the other four error values are 0.11017, 0.01358, 0.04681, 0.11654, and 0.13005. The findings offer technical assistance and a scientific foundation for enhancing the quality of stored wheat.
    Type of Medium: Online Resource
    ISSN: 2304-8158
    URL: Article
    DOI: 10.3390/foods12091833
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704223-6
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  • 2
    Online Resource
    Online Resource
    Diet-Wide Association, Genetic Susceptibility and Colorectal Cancer Risk: A Prospective Cohort Study
    MDPI AG ; 2023
    In:  Nutrients Vol. 15, No. 22 ( 2023-11-16), p. 4801-
    Details
    In: Nutrients, MDPI AG, Vol. 15, No. 22 ( 2023-11-16), p. 4801-
    Abstract: Background: Both genetic and dietary factors play significant roles in the etiology of colorectal cancer (CRC). To evaluate the relationship between certain food exposures and the risk of CRC, we carried out a large-scale association analysis in the UK Biobank. Methods: The associations of 139 foods and nutrients’ intake with CRC risk were assessed among 118,210 participants. A polygenic risk score (PRS) of CRC was created to explore any interaction between dietary factors and genetic susceptibility in CRC risk. The hazard ratio (HR) and 95% confidence interval (CI) of CRC risk linked to dietary variables and PRS were estimated using Cox regression models. Multiple comparisons were corrected using the error discovery rate (FDR). Results: During a mean follow-up of 12.8 years, 1466 incidents of CRC were identified. In the UK Biobank, alcohol and white bread were associated with increased CRC risk, and their HRs were 1.08 (95% CI: 1.03–1.14; FDRP = 0.028) and 1.10 (95% CI: 1.05–1.16; FDRP = 0.003), whereas dietary fiber, calcium, magnesium, phosphorus, and manganese intakes were inversely associated. We found no evidence of any PRS–nutrient interaction relationship in relation to CRC risk. Conclusions: Our results show that higher intakes of alcohol and white bread are associated with increased CRC risk, whilst dietary fiber, calcium, magnesium, phosphorus, and manganese are inversely associated.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    URL: Article
    DOI: 10.3390/nu15224801
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2518386-2
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  • 3
    Online Resource
    Online Resource
    FEDformer-Based Paddy Quality Assessment Model Affected by Toxin Change in Different Storage Environments
    MDPI AG ; 2023
    In:  Foods Vol. 12, No. 8 ( 2023-04-18), p. 1681-
    Details
    In: Foods, MDPI AG, Vol. 12, No. 8 ( 2023-04-18), p. 1681-
    Abstract: The storage environment can significantly impact paddy quality, which is vital to human health. Changes in storage can cause growth of fungi that affects grain quality. This study analyzed grain storage monitoring data from over 20 regions and found that five factors are essential in predicting quality changes during storage. The study combined these factors with the FEDformer (Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting) model and k-medoids algorithm to construct a paddy quality change prediction model and a grading evaluation model, which showed the highest accuracy and lowest error in predicting quality changes during paddy storage. The results emphasize the need for monitoring and controlling the storage environment to preserve grain quality and ensure food safety.
    Type of Medium: Online Resource
    ISSN: 2304-8158
    URL: Article
    DOI: 10.3390/foods12081681
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704223-6
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  • 4
    Online Resource
    Online Resource
    A Model for Predicting and Grading the Quality of Grain Storage Processes Affected by Microorganisms under Different Environments
    MDPI AG ; 2023
    In:  International Journal of Environmental Research and Public Health Vol. 20, No. 5 ( 2023-02-25), p. 4120-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 20, No. 5 ( 2023-02-25), p. 4120-
    Abstract: Changes in storage environments have a significant impact on grain quality. Accurate prediction of any quality changes during grain storage in different environments is very important for human health. In this paper, we selected wheat and corn, which are among the three major staple grains, as the target grains whose storage monitoring data cover more than 20 regions, and constructed a grain storage process quality change prediction model, which includes a FEDformer-based grain storage process quality change prediction model and a K-means++-based grain storage process quality change grading evaluation model. We select six factors affecting grain quality as input to achieve effective prediction of grain quality. Then, evaluation indexes were defined in this study, and a grading evaluation model of grain storage process quality was constructed using clustering model with the index prediction results and current values. The experimental results showed that the grain storage process quality change prediction model had the highest prediction accuracy and the lowest prediction error compared with other models.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph20054120
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2175195-X
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  • 5
    Online Resource
    Online Resource
    Large-Scale Synthesis of Tunable Fluorescent Carbon Dots Powder for Light-Emitting Diodes and Fingerprint Identification
    MDPI AG ; 2023
    In:  Molecules Vol. 28, No. 15 ( 2023-08-07), p. 5917-
    Details
    In: Molecules, MDPI AG, Vol. 28, No. 15 ( 2023-08-07), p. 5917-
    Abstract: The emergence and fast development of carbon dots (CDs) provide an unprecedented opportunity for applications in the field of photoelectricity, but their practicability still suffers from complicated synthesis procedures and the substrate dependence of solid-state fluorescence. In this study, we design a unique microwave-assisted solid-phase synthesis route for preparing tunable fluorescent CD powders with yellow, orange, and red fluorescence (Y-CDs, O-CDs, R-CDs) by simply adjusting the mass ratio of reactants, a method which is suitable for the large-scale synthesis of CDs. The Y-/O-/R-CDs were systematically characterized using physics and spectroscopy techniques. Based on the perfect solid-state fluorescence performance of the proposed fluorescent CD powders, the Y-/O-/R-CDs were successfully applied for the construction of multi-color and white light-emitting diode devices at low cost. Furthermore, the Y-CDs displayed much higher yield and luminous efficiency than the O-CDs and R-CDs and were further used for fingerprint identification on the surfaces of glass sheets and tinfoil. In addition, the R-CD aqueous solution fluorescence is sensitive to pH, suggesting its use as a pH indicator for monitoring intracellular pH fluctuations. The proposed series of fluorescent powders composed of CDs may herald a new era in the application of optical components and criminal investigation fields.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules28155917
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2008644-1
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  • 6
    Online Resource
    Online Resource
    Detecting Moving Target on Ground Based on Its Shadow by Using VideoSAR
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 16 ( 2021-08-20), p. 3291-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 16 ( 2021-08-20), p. 3291-
    Abstract: Video synthetic aperture radar (VideoSAR) can detect and identify a moving target based on its shadow. A slowly moving target has a shadow with distinct features, but it cannot be detected by state-of-the-art difference-based algorithms because of minor variations between adjacent frames. Furthermore, the detection boxes generated by difference-based algorithms often contain such defects as misalignments and fracture. In light of these problems, this study proposed a robust moving target detection (MTD) algorithm for objects on the ground by fusing the background frame detection results and the difference between frames over multiple intervals. We also discuss defects that occur in conventional MTD algorithms. The difference in background frame was introduced to overcome the shortcomings of difference-based algorithms and acquire the shadow regions of objects. This was fused with the multi-interval frame difference to simultaneously extract the moving target at different velocities while identifying false alarms. The results of experiments on empirically acquired VideoSAR data verified the performance of the proposed algorithm in terms of detecting a moving target on the ground based on its shadow.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13163291
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2513863-7
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  • 7
    Online Resource
    Online Resource
    Suppressing False Alarm in VideoSAR viaGradient-Weighted Edge Information
    MDPI AG ; 2019
    In:  Remote Sensing Vol. 11, No. 22 ( 2019-11-15), p. 2677-
    Details
    In: Remote Sensing, MDPI AG, Vol. 11, No. 22 ( 2019-11-15), p. 2677-
    Abstract: VideoSAR (Video Synthetic Aperture Radar) technology provides an important mean for real-time and continuous earth observation, whereas the ever-changing scattering characteristics may destroy the accuracy of target motion perception and bring in massive false alarms subsequently. False alarms emerge easily in the edge region for its sharper variations of the scattering characteristics. Utilizing the gradient difference between the target shadow edge and other edge regions in the image, this letter proposes a VideoSAR false alarm reduction method based on gradient-weighted edge information. By considering the reasonable gradient and area of the overlapping edge region between changing region and background, this method could reduce the amount of false alarms ( P f a = 18 . 4 % ) and retain the correct shadow of moving target ( P d = 74 . 8 % ). Experiments on a real footage verify the excellent effect of the proposed method.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs11222677
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2513863-7
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