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  • MDPI AG  (114)
  • 2020-2024  (114)
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  • MDPI AG  (114)
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  • 2020-2024  (114)
Year
  • 1
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  International Journal of Molecular Sciences Vol. 22, No. 19 ( 2021-09-23), p. 10233-
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 22, No. 19 ( 2021-09-23), p. 10233-
    Abstract: Bone defects cause significant socio-economic costs worldwide, while the clinical “gold standard” of bone repair, the autologous bone graft, has limitations including limited graft supply, secondary injury, chronic pain and infection. Therefore, to reduce surgical complexity and speed up bone healing, innovative therapies are needed. Bone tissue engineering (BTE), a new cross-disciplinary science arisen in the 21st century, creates artificial environments specially constructed to facilitate bone regeneration and growth. By combining stem cells, scaffolds and growth factors, BTE fabricates biological substitutes to restore the functions of injured bone. Although BTE has made many valuable achievements, there remain some unsolved challenges. In this review, the latest research and application of stem cells, scaffolds, and growth factors in BTE are summarized with the aim of providing references for the clinical application of BTE.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  ISPRS International Journal of Geo-Information Vol. 10, No. 8 ( 2021-07-30), p. 515-
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 10, No. 8 ( 2021-07-30), p. 515-
    Abstract: Global climate change and human activities have resulted in immense changes in the Earth’s ecosystem, and the interaction between the land surface and the atmosphere is one of the most important processes. Wind is a reference for studying atmospheric dynamics and climate change, analyzing the wind speed change characteristics in historical periods, and studying the influence of wind on the Earth-atmosphere interaction; additionally, studying the wind, contributes to analyzing and alleviating a series of problems, such as the energy crisis, environmental pollution, and ecological deterioration facing human beings. In this study, data from 697 meteorological stations in China from 2000 to 2019 were used to study the distribution and trend of wind speed over the past two decades. The relationships between wind speed and climate factors were explored using statistical methods; furthermore, combined with terrain, climate change, and human activities, we quantified the contribution of environmental factors to wind speed. The results show that a downward trend was recorded before 2011, but overall, there was an increasing trend that was not significant; moreover, the wind speed changes showed obvious seasonality and were more complicated on the monthly scale. The wind speed trend mainly increased in the western region, decreased in the eastern region, was higher in the northeastern, northwestern, and coastal areas, and was lower in the central area. Temperature, bright sunshine duration, evaporation, and precipitation had a strong influence, in which wind speed showed a significant negative correlation with temperature and precipitation and vice versa for sunshine and evapotranspiration. The influence of environmental factors is diverse, and these results could help to develop environmental management strategies across ecologically fragile areas and improve the design of wind power plants to make better use of wind energy.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2655790-3
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  • 3
    In: Remote Sensing, MDPI AG, Vol. 12, No. 23 ( 2020-11-25), p. 3860-
    Abstract: Accurate precipitation data at high spatiotemporal resolution are critical for land and water management at the basin scale. We proposed a downscaling framework for Tropical Rainfall Measuring Mission (TRMM) precipitation products through integrating Google Earth Engine (GEE) and Google Colaboratory (Colab). Three machine learning methods, including Gradient Boosting Regressor (GBR), Support Vector Regressor (SVR), and Artificial Neural Network (ANN) were compared in the framework. Three vegetation indices (Normalized Difference Vegetation Index, NDVI; Enhanced Vegetation Index, EVI; Leaf Area Index, LAI), topography, and geolocation are selected as geospatial predictors to perform the downscaling. This framework can automatically optimize the models’ parameters, estimate features’ importance, and downscale the TRMM product to 1 km. The spatial downscaling of TRMM from 25 km to 1 km was achieved by using the relationships between annual precipitations and annually-averaged vegetation index. The monthly precipitation maps derived from the annual downscaled precipitation by disaggregation. According to validation in the Great Mekong upstream region, the ANN yielded the best performance when simulating the annual TRMM precipitation. The most sensitive vegetation index for downscaling TRMM was LAI, followed by EVI. Compared with existing downscaling methods, the proposed framework for downscaling TRMM can be performed online for any given region using a wide range of machine learning tools and environmental variables to generate a precipitation product with high spatiotemporal resolution.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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  • 4
    In: Materials, MDPI AG, Vol. 14, No. 22 ( 2021-11-20), p. 7042-
    Abstract: Engineered cementitious composites (ECC) used as runway pavement material may suffer different strain rate loads such as aircraft taxiing, earthquakes, crash impacts, or blasts. In this paper, the dynamic tensile behaviors of the steel grid-polyvinyl alcohol (PVA) fiber and KEVLAR fiber-reinforced ECC were investigated by dynamic tensile tests at medium strain rates. The mixture was designed with different volume fractions of fibers and layer numbers of steel grids to explore the reinforcement effectiveness on the dynamic performance of the ECC. The volume fractions of these two types of fibers were 0%, 0.5%, 1%, 1.5%, and 2% of the ECC matrix, respectively. The layer numbers of the steel grid were 0, 1, and 2. The dynamic tensile behaviors of the PVA fiber and the KEVLAR fiber-reinforced ECC were also compared. The experimental results indicate that under dynamic tensile loads, the PVA-ECC reveals a ductile and multi-cracking failure behavior, and the KEVLAR-ECC displays a brittle failure behavior. The addition of the PVA fiber and the KEVLAR fiber can improve the tensile peak stress of the ECC matrix. For the specimens A0.5, A1, A1.5, and A2.0, the peak stress increases by 84.3%, 149.4%, 209.6%, and 237.3%, respectively, compared to the matrix specimen. For the specimens K0.5, K1, K1.5, and K2, the peak stress increases by about 72.3%, 147.0%, 195.2%, and 263.9%, respectively, compared to the matrix specimen. The optimum fiber volume content is 1.5% for the PVA-ECC and the KEVLAR-ECC. The KEVLAR-ECC can supply a higher tensile strength than the PVA-ECC, but the PVA-ECC reveals more prominent deformation capacity and energy dissipation performance than the KEVLAR-ECC. Embedding steel grid can improve the tensile peak stress and the energy dissipation of the ECC matrix. For the strain rate of 10−3 s−1, the peak stress of the A0.5S1 and A0.5S2 specimens increases by about 49.1% and 105.7% compared to the A0.5 specimen, and the peak stress of the K0.5S1 and K0.5S2 specimens increases by about 61.5% and 95.8%, respectively, compared to the K0.5 specimen.
    Type of Medium: Online Resource
    ISSN: 1996-1944
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2487261-1
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  • 5
    In: Journal of Clinical Medicine, MDPI AG, Vol. 12, No. 2 ( 2023-01-12), p. 631-
    Abstract: Drug-related problems (DRPs) are common among surgical patients, especially older patients with polypharmacy and underlying diseases. DRPs can potentially lead to morbidity, mortality, and increased treatment costs. The enhanced recovery after surgery (ERAS) system has shown great advantages in managing surgical patients. Medication therapy management for surgical patients (established as “surgical pharmacy” by Guangdong Province Pharmaceutical Association (GDPA)) is an important part of the ERAS system. Improper medication therapy management can lead to serious consequences and even death. In order to reduce DRPs further, and promote the rapid recovery of surgical patients, the need for pharmacists in the ERAS program is even more pressing. However, the medication therapy management services of surgical pharmacy and how surgical pharmacists should participate in ERAS programs are still unclear worldwide. Therefore, this article reviews the main perioperative medical management strategies and precautions from several aspects, including antimicrobial agents, antithrombotic agents, pain medication, nutritional therapy, blood glucose monitoring, blood pressure treatment, fluid management, treatment of nausea and vomiting, and management of postoperative delirium. Additionally, the way surgical pharmacists participate in perioperative medication management, and the relevant medication pathways are explored for optimizing medication therapy management services within the ERAS programs. This study will greatly assist surgical pharmacists’ work, contributing to surgeons accepting that pharmacists have an important role in the multidisciplinary team, benefitting medical workers in treating, counseling, and advocating for their patients, and further improving the effectiveness, safety and economy of medication therapy for patients and promoting patient recovery.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662592-1
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  • 6
    In: Energies, MDPI AG, Vol. 13, No. 20 ( 2020-10-12), p. 5288-
    Abstract: During water and polymer flooding for enhanced oil recovery, pore structures may vary because of the fluid–rock interactions, which can lead to variations in petrophysical properties and affect oil field production. To investigate the effects of fluid flooding on pore structures, six samples were subjected to brine water, dual-system, and alkaline–surfactant–polymer (ASP) polymer displacement experiments. Before and after experiments, samples were scanned by X-ray CT. Thin sections, X-ray diffraction, and high pressure mercury injection tests were also carried out to characterize mineralogy and fractal dimension of pore systems before experiments. Experiment results show that water flooding with low injection pore volume ratio (IPVR) can improve reservoir quality since total porosity and connected porosity of samples rise after the flooding and the proportion of large pores also increases and heterogeneity of pore structure decreases. However, water flooding with high IPVR has reverse effects on pore structures. Polymer flooding reduces the total porosity, connected porosity, the percentage of small pores and enhances the heterogeneity of pore structures. It can be found that pore structures will change in fluid flooding and appropriate water injection can improve reservoir quality while excessive water injection may destroy the reservoir. Meanwhile, injected polymer may block throats and destroy reservoirs. The experimental results can be used as the basis for oil field development.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2437446-5
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  • 7
    Online Resource
    Online Resource
    MDPI AG ; 2023
    In:  International Journal of Molecular Sciences Vol. 24, No. 8 ( 2023-04-12), p. 7111-
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 8 ( 2023-04-12), p. 7111-
    Abstract: Understanding the vibrational information encoded within the terahertz (THz) spectrum of biomolecules is critical for guiding the exploration of its functional responses to specific THz radiation wavelengths. This study investigated several important phospholipid components of biological membranes—distearoyl phosphatidylethanolamine (DSPE), dipalmitoyl phosphatidylcholine (DPPC), sphingosine phosphorylcholine (SPH), and lecithin bilayer—using THz time-domain spectroscopy. We observed similar spectral patterns for DPPC, SPH, and the lecithin bilayer, all of which contain the choline group as the hydrophilic head. Notably, the spectrum of DSPE, which has an ethanolamine head group, was different. Interestingly, density functional theory calculations confirmed that the absorption peak common to DSPE and DPPC at approximately 3.0 THz originated from a collective vibration of their similar hydrophobic tails. Accordingly, the cell membrane fluidity of RAW264.7 macrophages with irradiation at 3.1 THz was significantly enhanced, leading to improved phagocytosis. Our results highlight the importance of the spectral characteristics of the phospholipid bilayers when studying their functional responses in the THz band and suggest that irradiation at 3.1 THz is a potential non-invasive strategy to increase the fluidity of phospholipid bilayers for biomedical applications such as immune activation or drug administration.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 8
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 10 ( 2023-05-16), p. 8858-
    Abstract: The present study presents the tertiary assembly of a POM, peptide, and biogenic amine, which is a concept to construct new hybrid bio-inorganic materials for antibacterial applications and will help to promote the development of antivirus agents in the future. To achieve this, a Eu-containing polyoxometalate (EuW10) was first co-assembled with a biogenic amine of spermine (Spm), which improved both the luminescence and antibacterial effect of EuW10. Further introduction of a basic peptide from HPV E6, GL-22, induced more extensive enhancements, both of them being attributed to the cooperation and synergistic effects between the constituents, particularly the adaptive responses of assembly to the bacterial microenvironment (BME). Further intrinsic mechanism investigations revealed in detail that the encapsulation of EuW10 in Spm and further GL-22 enhanced the uptake abilities of EuW10 in bacteria, which further improved the ROS generation in BME via the abundant H2O2 involved there and significantly promoted the antibacterial effects.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 9
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  Sensors Vol. 21, No. 17 ( 2021-08-28), p. 5802-
    In: Sensors, MDPI AG, Vol. 21, No. 17 ( 2021-08-28), p. 5802-
    Abstract: Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability assessment and index sensitivity. Aiming at the problem of overfitting and parameter optimization in neural network learning, the paper proposes an improved machine learning algorithm—the Ensemble Learning Based on Policy Optimization Neural Networks (ELPONN) with the policy optimization and ensemble learning. This algorithm presents an optimized neural network learning algorithm through different strategies evolution, and builds an ensemble learning model of multi-intelligent algorithms to assess the capability and analyze the sensitivity of the indexes. Through the assessment of capabilities, the algorithm effectively avoids parameter optimization from entering the minimum point in performance to improve the accuracy of equipment capability assessment, which is significantly better than previous neural network assessment methods. The experimental results show that the mean relative error is 4.10%, which is better than BP, GABP, and early stopping. The ELPONN algorithm has better accuracy and stability performance, and meets the requirements of capability assessment.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2052857-7
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  • 10
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  Sensors Vol. 21, No. 4 ( 2021-02-07), p. 1165-
    In: Sensors, MDPI AG, Vol. 21, No. 4 ( 2021-02-07), p. 1165-
    Abstract: In situ ground truth data are an important requirement for producing accurate cropland type map, and this is precisely what is lacking at vast scales. Although volunteered geographic information (VGI) has been proven as a possible solution for in situ data acquisition, processing and extracting valuable information from millions of pictures remains challenging. This paper targets the detection of specific crop types from crowdsourced road view photos. A first large, public, multiclass road view crop photo dataset named iCrop was established for the development of crop type detection with deep learning. Five state-of-the-art deep convolutional neural networks including InceptionV4, DenseNet121, ResNet50, MobileNetV2, and ShuffleNetV2 were employed to compare the baseline performance. ResNet50 outperformed the others according to the overall accuracy (87.9%), and ShuffleNetV2 outperformed the others according to the efficiency (13 FPS). The decision fusion schemes major voting was used to further improve crop identification accuracy. The results clearly demonstrate the superior accuracy of the proposed decision fusion over the other non-fusion-based methods in crop type detection of imbalanced road view photos dataset. The voting method achieved higher mean accuracy (90.6–91.1%) and can be leveraged to classify crop type in crowdsourced road view photos.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2052857-7
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