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Keywords = OSGP

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19 pages, 8892 KiB  
Article
The Predicted Functional Compartmentation of Rice Terpenoid Metabolism by Trans-Prenyltransferase Structural Analysis, Expression and Localization
by Min Kyoung You, Yeo Jin Lee, Ji Su Yu and Sun-Hwa Ha
Int. J. Mol. Sci. 2020, 21(23), 8927; https://doi.org/10.3390/ijms21238927 - 25 Nov 2020
Cited by 7 | Viewed by 3280
Abstract
Most terpenoids are derived from the basic terpene skeletons of geranyl pyrophosphate (GPP, C10), farnesyl-PP (FPP, C15) and geranylgeranyl-PP (GGPP, C20). The trans-prenyltransferases (PTs) mediate the sequential head-to-tail condensation of an isopentenyl-PP (C5) with [...] Read more.
Most terpenoids are derived from the basic terpene skeletons of geranyl pyrophosphate (GPP, C10), farnesyl-PP (FPP, C15) and geranylgeranyl-PP (GGPP, C20). The trans-prenyltransferases (PTs) mediate the sequential head-to-tail condensation of an isopentenyl-PP (C5) with allylic substrates. The in silico structural comparative analyses of rice trans-PTs with 136 plant trans-PT genes allowed twelve rice PTs to be identified as GGPS_LSU (OsGGPS1), homomeric G(G)PS (OsGPS) and GGPS_SSU-II (OsGRP) in Group I; two solanesyl-PP synthase (OsSPS2 and 3) and two polyprenyl-PP synthases (OsSPS1 and 4) in Group II; and five FPSs (OsFPS1, 2, 3, 4 and 5) in Group III. Additionally, several residues in “three floors” for the chain length and several essential domains for enzymatic activities specifically varied in rice, potentiating evolutionarily rice-specific biochemical functions of twelve trans-PTs. Moreover, expression profiling and localization patterns revealed their functional compartmentation in rice. Taken together, we propose the predicted topology-based working model of rice PTs with corresponding terpene metabolites: GPP/GGPPs mainly in plastoglobuli, SPPs in stroma, PPPs in cytosol, mitochondria and chloroplast and FPPs in cytosol. Our findings could be suitably applied to metabolic engineering for producing functional terpene metabolites in rice systems. Full article
(This article belongs to the Special Issue Biological Networks of Specialized Metabolites and Plants)
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18 pages, 645 KiB  
Article
An Efficient Interface for the Integration of IoT Devices with Smart Grids
by Felipe Viel, Luis Augusto Silva, Valderi Reis Quietinho Leithardt, Juan Francisco De Paz Santana, Raimundo Celeste Ghizoni Teive and Cesar Albenes Zeferino
Sensors 2020, 20(10), 2849; https://doi.org/10.3390/s20102849 - 17 May 2020
Cited by 21 | Viewed by 4633
Abstract
The evolution of computing devices and ubiquitous computing has led to the development of the Internet of Things (IoT). Smart Grids (SGs) stand out among the many applications of IoT and comprise several embedded intelligent technologies to improve the reliability and the safety [...] Read more.
The evolution of computing devices and ubiquitous computing has led to the development of the Internet of Things (IoT). Smart Grids (SGs) stand out among the many applications of IoT and comprise several embedded intelligent technologies to improve the reliability and the safety of power grids. SGs use communication protocols for information exchange, such as the Open Smart Grid Protocol (OSGP). However, OSGP does not support the integration with devices compliant with the Constrained Application Protocol (CoAP), a communication protocol used in conventional IoT systems. In this sense, this article presents an efficient software interface that provides integration between OSGP and CoAP. The results obtained demonstrate the effectiveness of the proposed solution, which presents low communication overhead and enables the integration between IoT and SG systems. Full article
(This article belongs to the Special Issue Sensors for Smart Grids)
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26 pages, 25284 KiB  
Article
Adaptive Window-Based Constrained Energy Minimization for Detection of Newly Grown Tree Leaves
by Shih-Yu Chen, Chinsu Lin, Chia-Hui Tai and Shang-Ju Chuang
Remote Sens. 2018, 10(1), 96; https://doi.org/10.3390/rs10010096 - 12 Jan 2018
Cited by 26 | Viewed by 5124
Abstract
Leaf maturation from initiation to senescence is a phenological event of plants that results from the influences of temperature and water availability on physiological activities during a life cycle. Detection of newly grown leaves (NGL) is therefore useful for the diagnosis of tree [...] Read more.
Leaf maturation from initiation to senescence is a phenological event of plants that results from the influences of temperature and water availability on physiological activities during a life cycle. Detection of newly grown leaves (NGL) is therefore useful for the diagnosis of tree growth, tree stress, and even climatic change. This paper applies Constrained Energy Minimization (CEM), which is a hyperspectral target detection technique to spot grown leaves in a UAV multispectral image. According to the proportion of NGL in different regions, this paper proposes three innovative CEM based detectors: Subset CEM, Sliding Window-based CEM (SW CEM), and Adaptive Sliding Window-based CEM (AWS CEM). AWS CEM can especially adjust the window size according to the proportion of NGL around the current pixel. The results show that AWS CEM improves the accuracy of NGL detection and also reduces the false alarm rate. In addition, the results of the supervised target detection depend on the appropriate signature. In this case, we propose the Optimal Signature Generation Process (OSGP) to extract the optimal signature. The experimental results illustrate that OSGP can effectively improve the stability and the detection rate. Full article
(This article belongs to the Special Issue Hyperspectral Imaging and Applications)
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