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  • 1
    Online Resource
    Online Resource
    High-Throughput Determination of Sodium Danshensu in Beagle Dogs by the LCMS/MS Method, Employing Liquid-Liquid Extraction Based on 96-Well Format Plates
    MDPI AG ; 2017
    In:  Molecules Vol. 22, No. 5 ( 2017-04-25), p. 667-
    Details
    In: Molecules, MDPI AG, Vol. 22, No. 5 ( 2017-04-25), p. 667-
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules22050667
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2008644-1
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  • 2
    Online Resource
    Online Resource
    Determination of Vancomycin in Human Serum by Cyclodextrin-Micellar Electrokinetic Capillary Chromatography (CD-MEKC) and Application for PDAP Patients
    MDPI AG ; 2017
    In:  Molecules Vol. 22, No. 4 ( 2017-03-28), p. 538-
    Details
    In: Molecules, MDPI AG, Vol. 22, No. 4 ( 2017-03-28), p. 538-
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules22040538
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2008644-1
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  • 3
    Online Resource
    Online Resource
    Mining Candidate Genes Related to Heavy Metals in Mature Melon (Cucumis melo L.) Peel and Pulp Using WGCNA
    MDPI AG ; 2022
    In:  Genes Vol. 13, No. 10 ( 2022-09-30), p. 1767-
    Details
    In: Genes, MDPI AG, Vol. 13, No. 10 ( 2022-09-30), p. 1767-
    Abstract: The content of metal ions in fruits is inseparable from plant intake of trace elements and health effects in the human body. To understand metal ion content in the fruit and pericarp of melon (Cucumis melo L.) and the candidate genes responsible for controlling this process, we analyzed the metal ion content in distinct parts of melon fruit and pericarp and performed RNA-seq. The results showed that the content of metal ions in melon fruit tissue was significantly higher than that in the pericarp. Based on transcriptome expression profiling, we found that the fruit and pericarp contained elevated levels of DEGs. GO functional annotations included cell surface receptor signaling, signal transduction, organic substance metabolism, carbohydrate derivative binding, and hormone-mediated signaling pathways. KEGG pathways included pectate lyase, pentose and glucuronate interconversions, H+-transporting ATPase, oxidative phosphorylation, plant hormone signal transduction, and MAPK signaling pathways. We also analyzed the expression patterns of genes and transcription factors involved in hormone biosynthesis and signal transduction. Using weighted gene co-expression network analysis (WGCNA), a co-expression network was constructed to identify a specific module that was significantly correlated with the content of metal ions in melon, after which the gene expression in the module was measured. Connectivity and qRT–PCR identified five candidate melon genes, LOC103501427, LOC103501539, LOC103503694, LOC103504124, and LOC107990281, associated with metal ion content. This study provides a theoretical basis for further understanding the molecular mechanism of heavy metal ion content in melon fruit and peel and provides new genetic resources for the study of heavy metal ion content in plant tissues.
    Type of Medium: Online Resource
    ISSN: 2073-4425
    URL: Article
    DOI: 10.3390/genes13101767
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527218-4
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  • 4
    Online Resource
    Online Resource
    Toward Collaborative Intelligence in IoV Systems: Recent Advances and Open Issues
    MDPI AG ; 2022
    In:  Sensors Vol. 22, No. 18 ( 2022-09-15), p. 6995-
    Details
    In: Sensors, MDPI AG, Vol. 22, No. 18 ( 2022-09-15), p. 6995-
    Abstract: Internet of Vehicles (IoV) technology has been attracting great interest from both academia and industry due to its huge potential impact on improving driving experiences and enabling better transportation systems. While a large number of interesting IoV applications are expected, it is more challenging to design an efficient IoV system compared with conventional Internet of Things (IoT) applications due to the mobility of vehicles and complex road conditions. We discuss existing studies about enabling collaborative intelligence in IoV systems by focusing on collaborative communications, collaborative computing, and collaborative machine learning approaches. Based on comparison and discussion about the advantages and disadvantages of recent studies, we point out open research issues and future research directions.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s22186995
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2052857-7
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  • 5
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    Online Resource
    Research on the Mesoscopic Characteristics of Kelvin–Helmholtz Instability in Polymer Fluids with Dissipative Particle Dynamics
    MDPI AG ; 2023
    In:  Processes Vol. 11, No. 6 ( 2023-06-08), p. 1755-
    Details
    In: Processes, MDPI AG, Vol. 11, No. 6 ( 2023-06-08), p. 1755-
    Abstract: In this paper, the two-dimensional Kelvin–Helmholtz (KH) instability occurring in the shear flow of polymer fluids is modeled by the dissipative particle dynamics (DPD) method at the coarse-grained molecular level. A revised FENE model is proposed to properly describe the polymer chains. In this revised model, the elastic repulsion and tension are both considered between the adjacent beads, the bond length of which is set as one segment’s equilibrium length. The entanglements between polymer chains are described with a bead repulsive potential. The characteristics of such a KH instability in polymer fluid shear flow can be successfully captured in the simulations by the use of the modified FENE model. The numerical results show that the waves and vortexes grow more slowly in the shear flow of the polymer fluids than in the Newtonian fluid case, these vortexes become flat, and the polymer impedes the mixing of fluids and inhibits the generation of turbulence. The effects of the polymer concentration, chain length, and extensibility are also investigated regarding the evolution of KH instability. It is shown that the mixing of two polymer fluids reduces, and the KH instability becomes more suppressed as the polymer concentration increases. The vortexes become much longer with the evolution of the elongated interface as the chain length turns longer. As the extensibility increases, the vortexes become more flattened. Moreover, the roll-up process is significantly suppressed if the polymer has sufficiently high extensibility. These observations show that the polymer and its properties significantly influence the formation and evolution of the coherent structures such as the waves and vortexes in the KH instability progress.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    URL: Article
    DOI: 10.3390/pr11061755
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2720994-5
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  • 6
    Online Resource
    Online Resource
    CFD-DEM Simulation of Fast Fluidization of Fine Particles in a Micro Riser
    MDPI AG ; 2023
    In:  Processes Vol. 11, No. 8 ( 2023-08-11), p. 2417-
    Details
    In: Processes, MDPI AG, Vol. 11, No. 8 ( 2023-08-11), p. 2417-
    Abstract: In recent years, the discrete element method (DEM) has gradually been applied to the traditional fluidization simulation of fine particles in a micro fluidized bed (MFB). The application of DEM in the simulating fast fluidization of fine particles in MFB has not yet received attention. This article presents a drag model that relies on the surrounding environment of particles, namely the particle circumstance-dependent drag model or PCDD model. Fast fluidization in an MFB of fine particles is simulated using DEM based on the PCDD model. Simulations indicate that the local structure in an MFB exhibits particle aggregation, which is a natural property of fast fluidization, forming a structure where a continuous dilute phase and dispersed concentrated phase coexist. There exists a strong effect of solid back-mixing in an MFB, leading to relatively low outlet solid flux. The gas back-mixing effect is, however, not so distinct. The axial porosity shows a monotonically increasing distribution with the bed height but does not strictly follow the single exponential distribution. The solid volume fraction at the bottom of the bed is significantly lower than the correlated value in CFB. The axial heterogeneous distribution of the cross-sectional average porosity in the lower half of the bed is also weakened. The radial porosity shows a higher distribution pattern in the central region and a lower one in the sidewall region.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    URL: Article
    DOI: 10.3390/pr11082417
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2720994-5
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  • 7
    Online Resource
    Online Resource
    Knowledge-Driven Network for Object Detection
    MDPI AG ; 2021
    In:  Algorithms Vol. 14, No. 7 ( 2021-06-28), p. 195-
    Details
    In: Algorithms, MDPI AG, Vol. 14, No. 7 ( 2021-06-28), p. 195-
    Abstract: Object detection is a challenging computer vision task with numerous real-world applications. In recent years, the concept of the object relationship model has become helpful for object detection and has been verified and realized in deep learning. Nonetheless, most approaches to modeling object relations are limited to using the anchor-based algorithms; they cannot be directly migrated to the anchor-free frameworks. The reason is that the anchor-free algorithms are used to eliminate the complex design of anchors and predict heatmaps to represent the locations of keypoints of different object categories, without considering the relationship between keypoints. Therefore, to better fuse the information between the heatmap channels, it is important to model the visual relationship between keypoints. In this paper, we present a knowledge-driven network (KDNet)—a new architecture that can aggregate and model keypoint relations to augment object features for detection. Specifically, it processes a set of keypoints simultaneously through interactions between their local and geometric features, thereby allowing the modeling of their relationship. Finally, the updated heatmaps were used to obtain the corners of the objects and determine their positions. The experimental results conducted on the RIDER dataset confirm the effectiveness of the proposed KDNet, which significantly outperformed other state-of-the-art object detection methods.
    Type of Medium: Online Resource
    ISSN: 1999-4893
    URL: Article
    DOI: 10.3390/a14070195
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2455149-1
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  • 8
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    Online Resource
    The Room Temperature Fracture Behaviors of GNPs/TA15 Composites by Pre-Sintering and Hot Extrusion
    MDPI AG ; 2022
    In:  Materials Vol. 16, No. 1 ( 2022-12-29), p. 318-
    Details
    In: Materials, MDPI AG, Vol. 16, No. 1 ( 2022-12-29), p. 318-
    Abstract: Graphene nanoplates (GNPs)/TA15 composites were fabricated by pre-sintering and hot extrusion. During a room temperature tensile test, the dislocation was generated in grains. With increasing strain, the dislocation piled up along the interface between GNPs and Ti matrix, leading to stress concentration and microcracks. Then, the microcracks extended to GNPs or along the interface. The GNPs cracked under the shear force and the GNPs pulled out along with the crack propagation along the interface. This work provides a new sight in the room temperature tensile fracture behaviors.
    Type of Medium: Online Resource
    ISSN: 1996-1944
    URL: Article
    DOI: 10.3390/ma16010318
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2487261-1
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  • 9
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    A Novel POSS-Based Copolymer Functionalized Graphene: An Effective Flame Retardant for Reducing the Flammability of Epoxy Resin
    MDPI AG ; 2019
    In:  Polymers Vol. 11, No. 2 ( 2019-02-01), p. 241-
    Details
    In: Polymers, MDPI AG, Vol. 11, No. 2 ( 2019-02-01), p. 241-
    Abstract: In this study, a novel copolymer, PbisDOPOMA-POSSMA-GMA (PDPG), containing methacryloisobutyl polyhedral oligomeric silsesquioxane (POSSMA), reactive glycidyl methacrylate (GMA), and bis-9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide methacrylate (bisDOPOMA) and derivative functionalized graphene oxide (GO) were synthesized by a one-step grafting reaction to create a hybrid flame retardant (GO-MD-MP). GO-MD-MP was characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), transmission electron microscopy (TEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA). Flame-retardant epoxy resin (EP) composites were prepared by adding various amounts of GO-MD-MP to the thermal-curing epoxy resin of diglycidyl ether of bisphenol A (DGEBA, trade name E-51). The thermal properties of the EP composites were remarkably enhanced by adding the GO-MD-MP, and the residue char of the epoxy resin also increased greatly. With the incorporation of 4 wt % GO-MD-MP, the limiting oxygen index (LOI) value was enhanced to 31.1% and the UL-94 V-0 rating was easily achieved. In addition, the mechanical strength of the epoxy resin was also improved.
    Type of Medium: Online Resource
    ISSN: 2073-4360
    URL: Article
    DOI: 10.3390/polym11020241
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2527146-5
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  • 10
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    Online Resource
    Asymmetric Effects of Daytime and Nighttime Warming on Boreal Forest Spring Phenology
    MDPI AG ; 2019
    In:  Remote Sensing Vol. 11, No. 14 ( 2019-07-11), p. 1651-
    Details
    In: Remote Sensing, MDPI AG, Vol. 11, No. 14 ( 2019-07-11), p. 1651-
    Abstract: Vegetation phenology is the most intuitive and sensitive biological indicator of environmental conditions, and the start of the season (SOS) can reflect the rapid response of terrestrial ecosystems to climate change. At present, the model based on mean temperature neglects the role of the daytime maximum temperature (TMAX) and the nighttime minimum temperature (TMIN) in providing temperature accumulation and cold conditions at leaf onset. This study analyzed the spatiotemporal variations of spring phenology for the boreal forest from 2001 to 2017 based on the moderate-resolution imaging spectro-radiometer (MODIS) enhanced vegetation index (EVI) data (MOD13A2) and investigated the asymmetric effects of daytime and nighttime warming on the boreal forest spring phenology during TMAX and TMIN preseason by partial correlation analysis. The results showed that the spring phenology was delayed with increasing latitude of the boreal forest. Approximately 91.37% of the region showed an advancing trend during the study period, with an average advancement rate of 3.38 ± 0.08 days/decade, and the change rates of different land cover types differed, especially in open shrubland. The length of the TMIN preseason was longer than that of the TMAX preseason and diurnal temperatures showed an asymmetrical increase during different preseasons. The daytime and nighttime warming effects on the boreal forest are asymmetrical. The TMAX has a greater impact on the vegetation spring phenology than TMIN as a whole and the effect also has seasonal differences; the TMAX mainly affects the SOS in spring, while TMIN has a greater impact in winter. The asymmetric effects of daytime and nighttime warming on the SOS in the boreal forest were highlighted in this study, and the results suggest that diurnal temperatures should be added to the forest terrestrial ecosystem model.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs11141651
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2513863-7
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