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Open AccessArticle
PulseNetOne: Fast Unsupervised Pruning of Convolutional Neural Networks for Remote Sensing
Remote Sens. 2020, 12(7), 1092; https://doi.org/10.3390/rs12071092 (registering DOI) - 29 Mar 2020
Abstract
Scene classification is an important aspect of image/video understanding and segmentation. However, remote-sensing scene classification is a challenging image recognition task, partly due to the limited training data, which causes deep-learning Convolutional Neural Networks (CNNs) to overfit. Another difficulty is that images often [...] Read more.
Scene classification is an important aspect of image/video understanding and segmentation. However, remote-sensing scene classification is a challenging image recognition task, partly due to the limited training data, which causes deep-learning Convolutional Neural Networks (CNNs) to overfit. Another difficulty is that images often have very different scales and orientation (viewing angle). Yet another is that the resulting networks may be very large, again making them prone to overfitting and unsuitable for deployment on memory- and energy-limited devices. We propose an efficient deep-learning approach to tackle these problems. We use transfer learning to compensate for the lack of data, and data augmentation to tackle varying scale and orientation. To reduce network size, we use a novel unsupervised learning approach based on k-means clustering, applied to all parts of the network: most network reduction methods use computationally expensive supervised learning methods, and apply only to the convolutional or fully connected layers, but not both. In experiments, we set new standards in classification accuracy on four remote-sensing and two scene-recognition image datasets. Full article
Open AccessAbstract
Super-Sweet Purple Sweetcorn: Breaking the Genetic Link
Proceedings 2019, 36(1), 6134; https://doi.org/10.3390/proceedings2019036134 (registering DOI) - 29 Mar 2020
Abstract
Purple-pericarp supersweet sweetcorn currently does not exist as a horticultural product. Purple pericarp comprises the outer layers of the kernel, with the purple pigment being produced by anthocyanin. Unlike the aleurone layer which can also be pigmented, the pericarp is maternal tissue. Although [...] Read more.
Purple-pericarp supersweet sweetcorn currently does not exist as a horticultural product. Purple pericarp comprises the outer layers of the kernel, with the purple pigment being produced by anthocyanin. Unlike the aleurone layer which can also be pigmented, the pericarp is maternal tissue. Although standard purple sweetcorn based on mutations such as sugary1 (su1) and sugary enhancer (se1) are in existence, the development of purple supersweet sweetcorn based on the widely used shrunken2 (sh2) gene mutation is much more challenging. This is because there is an extremely close genetic linkage between the supersweet shrunken-2 mutation and the anthocyanin biosynthesis gene, anthocyaninless-1 (a1). As distance between these two genes is only 0.1 cM, the development of purple supersweet sweetcorn depends on breaking this close genetic link, which occurs at a very low frequency of 1 in 1000 meiotic crossovers. To make this possible, we crossed a white supersweet variety (a1a1sh2sh2) with a purple-pericarp Peruvian maize (A1A1Sh2Sh2) to obtain an initial heterozygous hybrid (A1a1Sh2sh2). The hybrid seed was sown and subsequently self-pollinated to produce seed segregating for the double recessive homozygote, sh2sh2 (1 in 4). These kernels present a visually distinctive phenotype, characterised by the seed’s shrunken appearance. Approximately 2760 sh2sh2 seeds were separated and resown. Due to the low frequency of linkage breakage, the majority of these plants (~99.9%) produced supersweet white cobs (a1a1sh2sh2). Three plants (0.1%) however, produced supersweet purple cobs (A1a1sh2sh2), due to a single low-frequency linkage break. These cobs will form the basis for a purple-pericarp supersweet sweetcorn breeding program. Full article
Open AccessArticle
Improving VerticalWind Speed Extrapolation Using Short-Term Lidar Measurements
Remote Sens. 2020, 12(7), 1091; https://doi.org/10.3390/rs12071091 (registering DOI) - 29 Mar 2020
Abstract
This study investigates how short-term lidar measurements can be used in combination
with a mast measurement to improve vertical extrapolation of wind speed. Several methods are
developed and analyzed for their performance in estimating the mean wind speed, the wind
speed distribution, and [...] Read more.
This study investigates how short-term lidar measurements can be used in combination
with a mast measurement to improve vertical extrapolation of wind speed. Several methods are
developed and analyzed for their performance in estimating the mean wind speed, the wind
speed distribution, and the energy yield of an idealized wind turbine at the target height of
the extrapolation. These methods range from directly using the wind shear of the short-term
measurement to a classification approach based on commonly available environmental parameters
using linear regression. The extrapolation strategies are assessed using data of ten wind profiles up
to 200 m measured at different sites in Germany. Different mast heights and extrapolation distances
are investigated. The results show that, using an appropriate extrapolation strategy, even a very
short-term lidar measurement can significantly reduce the uncertainty in the vertical extrapolation of
wind speed. This observation was made for short as well as for very large extrapolation distances.
Among the investigated methods, the linear regression approach yielded better results than the other
methods. Integrating environmental variables into the extrapolation procedure further increased the
performance of the linear regression approach. Overall, the extrapolation error in (theoretical) energy
yield was decreased by around 50% to 70% on average for a lidar measurement of approximately one
to two months depending on the extrapolation height and distance. The analysis of seasonal patterns
revealed that appropriate extrapolation strategies can also significantly reduce the seasonal bias that
is connected to the season during which the short-term measurement is performed. Full article
(This article belongs to the Special Issue Remote Sensing of Energy Meteorology)
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Open AccessAbstract
Northern Beef Industry Emerging Market, Supply Chain Gap Analysis & Sector Capacity Baseline Study
Proceedings 2019, 36(1), 133; https://doi.org/10.3390/proceedings2019036133 (registering DOI) - 29 Mar 2020
Abstract
With an ongoing interest in developing northern Australia, we undertook a beef situation analysis to assist the Cooperative Research Centre for Developing Northern Australian in tailoring their investment decisions. The northern beef industry is dominated by rangeland enterprises that include family farms, indigenous [...] Read more.
With an ongoing interest in developing northern Australia, we undertook a beef situation analysis to assist the Cooperative Research Centre for Developing Northern Australian in tailoring their investment decisions. The northern beef industry is dominated by rangeland enterprises that include family farms, indigenous pastoral enterprises and large corporate interests. The analysis was a whole of supply chain examination of current practices, strategies and plans. It included consultation with producers, industry groups, research organisations and government departments. The competitive advantages of the northern beef industry are its adapted production systems, low cost base and geographic positioning that allows it to take advantage of south-east Asian markets. However, the inherent low productivity, high capital costs and over reliance on a small number of markets make it vulnerable to market shocks. We found that the industry faces challenges in maintaining profitability and the ability to translate research to practice to enhance productivity its social license to operate. The review makes recommendation under four themes: There is an ongoing need for research and develop for profitability and productivity gains for the top businesses; There is a need to improve the translation of proven R and D to farm practice for the majority of the northern Australian beef industry; There is a need to support and develop business cases for economic enabling infrastructure to allow the northern Australian beef industry to remain competitive and intensify production, and; There remains some regulatory reform and derisking required to support investment in the industry and allow diversification. Full article
Open AccessReview
Histone Deacetylation Inhibitors as Modulators of Regulatory T Cells
Int. J. Mol. Sci. 2020, 21(7), 2356; https://doi.org/10.3390/ijms21072356 (registering DOI) - 29 Mar 2020
Abstract
Regulatory T cells (Tregs) are important mediators of immunological self-tolerance and homeostasis. Being cluster of differentiation 4+Forkhead box protein3+ (CD4+FOXP3+), these cells are a subset of CD4+ T lymphocytes and can originate from [...] Read more.
Regulatory T cells (Tregs) are important mediators of immunological self-tolerance and homeostasis. Being cluster of differentiation 4+Forkhead box protein3+ (CD4+FOXP3+), these cells are a subset of CD4+ T lymphocytes and can originate from the thymus (tTregs) or from the periphery (pTregs). The malfunction of CD4+ Tregs is associated with autoimmune responses such as rheumatoid arthritis (RA), multiple sclerosis (MS), type 1 diabetes (T1D), inflammatory bowel diseases (IBD), psoriasis, systemic lupus erythematosus (SLE), and transplant rejection. Recent evidence supports an opposed role in sepsis. Therefore, maintaining functional Tregs is considered as a therapy regimen to prevent autoimmunity and allograft rejection, whereas blocking Treg differentiation might be favorable in sepsis patients. It has been shown that Tregs can be generated from conventional naïve T cells, called iTregs, due to their induced differentiation. Moreover, Tregs can be effectively expanded in vitro based on blood-derived tTregs. Taking into consideration that the suppressive role of Tregs has been mainly attributed to the expression and function of the transcription factor Foxp3, modulating its expression and binding to the promoter regions of target genes by altering the chromatin histone acetylation state may turn out beneficial. Hence, we discuss the role of histone deacetylation inhibitors as epigenetic modulators of Tregs in this review in detail. Full article
(This article belongs to the Special Issue Histone Deacetylase Inhibitors in Health and Disease II)
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Open AccessFeature PaperArticle
Design of a Cyberattack Resilient 77 GHz Automotive Radar Sensor
Electronics 2020, 9(4), 573; https://doi.org/10.3390/electronics9040573 (registering DOI) - 28 Mar 2020
Abstract
In this paper, we propose a novel 77 GHz automotive radar sensor, and demonstrate its cyberattack resilience using real measurements. The proposed system is built upon a standard Frequency Modulated Continuous Wave (FMCW) radar RF-front end, and the novelty is in the DSP [...] Read more.
In this paper, we propose a novel 77 GHz automotive radar sensor, and demonstrate its cyberattack resilience using real measurements. The proposed system is built upon a standard Frequency Modulated Continuous Wave (FMCW) radar RF-front end, and the novelty is in the DSP algorithm used at the firmware level. All attack scenarios are based on real radar signals generated by Texas Instruments AWR series 77 GHz radars, and all measurements are done using the same radar family. For sensor networks, including interconnected autonomous vehicles sharing radar measurements, cyberattacks at the network/communication layer is a known critical problem, and has been addressed by several different researchers. What is addressed in this paper is cyberattacks at the physical layer, that is, adversarial agents generating 77 GHz electromagnetic waves which may cause a false target detection, false distance/velocity estimation, or not detecting an existing target. The main algorithm proposed in this paper is not a predictive filtering based cyberattack detection scheme where an “unusual” difference between measured and predicted values triggers an alarm. The core idea is based on a kind of physical challenge-response authentication, and its integration into the radar DSP firmware. Full article
(This article belongs to the Section Microwave and Wireless Communications)
Open AccessArticle
Learning Effective Skeletal Representations on RGB Video for Fine-Grained Human Action Quality Assessment
Electronics 2020, 9(4), 568; https://doi.org/10.3390/electronics9040568 (registering DOI) - 28 Mar 2020
Abstract
In this paper, we propose an integrated action classification and regression learning framework for the fine-grained human action quality assessment of RGB videos. On the basis of 2D skeleton data obtained per frame of RGB video sequences, we present an effective representation of [...] Read more.
In this paper, we propose an integrated action classification and regression learning framework for the fine-grained human action quality assessment of RGB videos. On the basis of 2D skeleton data obtained per frame of RGB video sequences, we present an effective representation of joint trajectories to train action classifiers and a class-specific regression model for a fine-grained assessment of the quality of human actions. To manage the challenge of view changes due to camera motion, we develop a self-similarity feature descriptor extracted from joint trajectories and a joint displacement sequence to represent dynamic patterns of the movement and posture of the human body. To weigh the impact of joints for different action categories, a class-specific regression model is developed to obtain effective fine-grained assessment functions. In the testing stage, with the supervision of the action classifier’s output, the regression model of a specific action category is selected to assess the quality of skeleton motion extracted from the action video. We take advantage of the discrimination of the action classifier and the viewpoint invariance of the self-similarity feature to boost the performance of the learning-based quality assessment method in a realistic scene. We evaluate our proposed method using diving and figure skating videos of the publicly available MIT Olympic Scoring dataset, and gymnastic vaulting videos of the recent benchmark University of Nevada Las Vegas (UNLV) Olympic Scoring dataset. The experimental results show that the proposed method achieved an improved performance, which is measured by the mean rank correlation coefficient between the predicted regression scores and the ground truths. Full article
(This article belongs to the Special Issue Intelligent Electronic Devices)
Open AccessFeature PaperArticle
Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations
Electronics 2020, 9(4), 570; https://doi.org/10.3390/electronics9040570 (registering DOI) - 28 Mar 2020
Abstract
Peak-time rebates offer an opportunity to introduce demand response in electricity markets. To implement peak-time rebates, utilities must accurately determine the consumption level if the program were not in effect. Reliable calculations of customer baseline load elude utilities and independent system operators, due [...] Read more.
Peak-time rebates offer an opportunity to introduce demand response in electricity markets. To implement peak-time rebates, utilities must accurately determine the consumption level if the program were not in effect. Reliable calculations of customer baseline load elude utilities and independent system operators, due to factors that include heterogeneous demands and random variations. Prevailing research is limited for residential markets, which are growing rapidly with the presence of load aggregators and the availability of smart grid systems. Our research pioneers a novel method that clusters customers according to the size and predictability of their demands, substantially improving existing customer baseline calculations and other clustering methods. Full article
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Open AccessArticle
Iron Loss Minimization Strategy for Predictive Torque Control of Induction Motor
Electronics 2020, 9(4), 566; https://doi.org/10.3390/electronics9040566 (registering DOI) - 28 Mar 2020
Abstract
Today’s modern control strategies of an induction motor (IM) drive require a power source with an adjustable output voltage frequency and amplitude. The most commonly used converter topology is a two-level voltage-source inverter (VSI). However, the utilization of a VSI introduces additional voltage [...] Read more.
Today’s modern control strategies of an induction motor (IM) drive require a power source with an adjustable output voltage frequency and amplitude. The most commonly used converter topology is a two-level voltage-source inverter (VSI). However, the utilization of a VSI introduces additional voltage and current distortion, which leads to additional power losses in the machine’s magnetic circuit. Both the transistor switching frequency and the type of the inverter control determine the total harmonic distortion (THD) of the motor’s phase currents. In this paper, the influence of the inverter DC-link voltage on the iron losses of an IM controlled by a predictive torque control (PTC) is presented. It is shown that if the IM drive operates below the rated speed, it is possible to modify the PTC algorithm to reduce the additional iron losses caused by the non-harmonic inverter output voltage. The control of the DC-link voltage is achieved by using a silicon-controlled rectifier. Experiments were conducted on a 5.5 kW IM controlled by PTC, and the results are compared against a sinusoidal voltage supply created by a synchronous generator. Full article
(This article belongs to the Section Power Electronics)
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Open AccessFeature PaperArticle
10-GHz Fully Differential Sallen–Key Lowpass Biquad Filters in 55nm SiGe BiCMOS Technology
Electronics 2020, 9(4), 563; https://doi.org/10.3390/electronics9040563 (registering DOI) - 28 Mar 2020
Abstract
Multi-GHz lowpass filters are key components for many RF applications and are required for the implementation of integrated high-speed analog-to-digital and digital-to-analog converters and optical communication systems. In the last two decades, integrated filters in the Multi-GHz range have been implemented using III-V [...] Read more.
Multi-GHz lowpass filters are key components for many RF applications and are required for the implementation of integrated high-speed analog-to-digital and digital-to-analog converters and optical communication systems. In the last two decades, integrated filters in the Multi-GHz range have been implemented using III-V or SiGe technologies. In all cases in which the size of passive components is a concern, inductorless designs are preferred. Furthermore, due to the recent development of high-speed and high-resolution data converters, highly linear multi-GHz filters are required more and more. Classical open loop topologies are not able to achieve high linearity, and closed loop filters are preferred in all applications where linearity is a key requirement. In this work, we present a fully differential BiCMOS implementation of the classical Sallen Key filter, which is able to operate up to about 10 GHz by exploiting both the bipolar and MOS transistors of a commercial 55-nm BiCMOS technology. The layout of the biquad filter has been implemented, and the results of post-layout simulations are reported. The biquad stage exhibits excellent SFDR (64 dB) and dynamic range (about 50 dB) due to the closed loop operation, and good power efficiency (0.94 pW/Hz/pole) with respect to comparable active inductorless lowpass filters reported in the literature. Moreover, unlike other filters, it exploits the different active devices offered by commercial SiGe BiCMOS technologies. Parametric and Monte Carlo simulations are also included to assess the robustness of the proposed biquad filter against PVT and mismatch variations. Full article
(This article belongs to the Special Issue Filter Design Solutions for RF systems)
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Open AccessArticle
Sustainable IoT Sensing Applications Development through GraphQL-Based Abstraction Layer
Electronics 2020, 9(4), 564; https://doi.org/10.3390/electronics9040564 (registering DOI) - 28 Mar 2020
Abstract
Internet of Things (IoT) networks are mostly comprised of power-constrained devices, therefore the most important consideration in designing IoT applications, based on sensor networks is energy efficiency. Minor improvement in energy conservation methods can lead to a significant increase in the lifetime of [...] Read more.
Internet of Things (IoT) networks are mostly comprised of power-constrained devices, therefore the most important consideration in designing IoT applications, based on sensor networks is energy efficiency. Minor improvement in energy conservation methods can lead to a significant increase in the lifetime of IoT devices and overall network. To achieve efficient utilisation of energy, different solutions are proposed such as duty cycling optimization, design changes at the MAC layer, etc. In this paper, we propose a new approach to overcome this challenge in cloud-based IoT sensing applications, based on integration of an abstraction layer with constrained application mechanism. To achieve energy conservation and efficient data management in IoT sensing applications, we incorporate modules of efficient web framework with cloud services, in order to minimize the number of round trips for data delivery and graph-based data representation. Our study is the first attempt in the literature, to the best of our knowledge, which introduces the potential of this integration for achieving the aforementioned objectives in the target applications. We implemented the proposed interfacing of abstraction layer in constrained applications, to develop a testbed using Z1 IoT motes, Contiki OS and GraphQL web framework with Google cloud services. Experimental comparisons against baseline REST architecture approach show that our proposed approach achieved significant reductions in data delivery delay and energy consumption (minimum 51.53% and 52.88%, respectively) in IoT applications involving sensor network. Full article
(This article belongs to the Section Computer Science & Engineering)
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Open AccessArticle
Accurate Closed-Form Solution for Moving Underwater Vehicle Localization Using Two-Way Travel Time
Electronics 2020, 9(4), 565; https://doi.org/10.3390/electronics9040565 (registering DOI) - 28 Mar 2020
Abstract
Position information is essential for an underwater vehicle that can affect the performance of many other applications. Vehicle motion during the two-way travel time (TWTT) using an acoustic positioning system can affect the localization accuracy of the estimators based on the traditional static [...] Read more.
Position information is essential for an underwater vehicle that can affect the performance of many other applications. Vehicle motion during the two-way travel time (TWTT) using an acoustic positioning system can affect the localization accuracy of the estimators based on the traditional static model. A new time measurement model for moving vehicle localization is presented, which compensates for the vehicle motion. The Cramér–Rao lower bounds (CRLBs) of the proposed model are derived for two different cases, where the depth of the underwater vehicle is unknown or known. Then, closed-form solutions for the two cases using the proposed model are derived and the solutions are shown analytically to reach the CRLBs. Simulations collaborate the theoretical performance of the proposed estimators and the moving model significantly improves the localization accuracy in comparison with the static model. Full article
(This article belongs to the Section Electrical and Autonomous Vehicles)
Open AccessArticle
Phylogenetic Analyses of Sites in Different Protein Structural Environments Result in Distinct Placements of the Metazoan Root
Biology 2020, 9(4), 64; https://doi.org/10.3390/biology9040064 (registering DOI) - 28 Mar 2020
Abstract
Phylogenomics, the use of large datasets to examine phylogeny, has revolutionized the study of evolutionary relationships. However, genome-scale data have not been able to resolve all relationships in the tree of life; this could reflect, at least in part, the poor-fit of the [...] Read more.
Phylogenomics, the use of large datasets to examine phylogeny, has revolutionized the study of evolutionary relationships. However, genome-scale data have not been able to resolve all relationships in the tree of life; this could reflect, at least in part, the poor-fit of the models used to analyze heterogeneous datasets. Some of the heterogeneity may reflect the different patterns of selection on proteins based on their structures. To test that hypothesis, we developed a pipeline to divide phylogenomic protein datasets into subsets based on secondary structure and relative solvent accessibility. We then tested whether amino acids in different structural environments had distinct signals for the topology of the deepest branches in the metazoan tree. We focused on a dataset that appeared to have a mixture of signals and we found that the most striking difference in phylogenetic signal reflected relative solvent accessibility. Analyses of exposed sites (residues located on the surface of proteins) yielded a tree that placed ctenophores sister to all other animals whereas sites buried inside proteins yielded a tree with a sponge+ctenophore clade. These differences in phylogenetic signal were not ameliorated when we conducted analyses using a set of maximum-likelihood profile mixture models. These models are very similar to the Bayesian CAT model, which has been used in many analyses of deep metazoan phylogeny. In contrast, analyses conducted after recoding amino acids to limit the impact of deviations from compositional stationarity increased the congruence in the estimates of phylogeny for exposed and buried sites; after recoding amino acid trees estimated using the exposed and buried site both supported placement of ctenophores sister to all other animals. Although the central conclusion of our analyses is that sites in different structural environments yield distinct trees when analyzed using models of protein evolution, our amino acid recoding analyses also have implications for metazoan evolution. Specifically, our results add to the evidence that ctenophores are the sister group of all other animals and they further suggest that the placozoa+cnidaria clade found in some other studies deserves more attention. Taken as a whole, these results provide striking evidence that it is necessary to achieve a better understanding of the constraints due to protein structure to improve phylogenetic estimation. Full article
(This article belongs to the Special Issue Feature Papers 2019)
Open AccessArticle
Glycofullerenes Inhibit Particulate Matter Induced Inflammation and Loss of Barrier Proteins in HaCaT Human Keratinocytes
Biomolecules 2020, 10(4), 514; https://doi.org/10.3390/biom10040514 (registering DOI) - 28 Mar 2020
Abstract
Exposure to particulate matter (PM) has been linked to pulmonary and cardiovascular dysfunctions, as well as skin diseases, etc. PM impairs the skin barrier functions and is also involved in the initiation or exacerbation of skin inflammation, which is linked to the activation [...] Read more.
Exposure to particulate matter (PM) has been linked to pulmonary and cardiovascular dysfunctions, as well as skin diseases, etc. PM impairs the skin barrier functions and is also involved in the initiation or exacerbation of skin inflammation, which is linked to the activation of reactive oxygen species (ROS) pathways. Fullerene is a single C60 molecule which has been reported to act as a good radical scavenger. However, its poor water solubility limits its biological applications. The glyco-modification of fullerenes increases their water solubility and anti-bacterial and anti-virus functions. However, it is still unclear whether it affects their anti-inflammatory function against PM-induced skin diseases. Hence, glycofullerenes were synthesized to investigate their effects on PM-exposed HaCaT human keratinocytes. Our results showed that glycofullerenes could reduce the rate of PM-induced apoptosis and ROS production, as well as decrease the expression of downstream mitogen-activated protein kinase and Akt pathways. Moreover, PM-induced increases in inflammatory-related signals, such as cyclooxygenase-2, heme oxygenase-1, and prostaglandin E2, were also suppressed by glycofullerenes. Notably, our results suggested that PM-induced impairment of skin barrier proteins, such as filaggrin, involucrin, repetin, and loricrin, could be reduced by pre-treatment with glycofullerenes. The results of this study indicate that glycofullerenes could be potential candidates for treatments against PM-induced skin diseases and that they exert their protective effects via ROS scavenging, anti-inflammation, and maintenance of the expression of barrier proteins. Full article
Open AccessArticle
A Novel NAD-RNA Decapping Pathway Discovered by Synthetic Light-Up NAD-RNAs
Biomolecules 2020, 10(4), 513; https://doi.org/10.3390/biom10040513 (registering DOI) - 28 Mar 2020
Abstract
The complexity of the transcriptome is governed by the intricate interplay of transcription, RNA processing, translocation, and decay. In eukaryotes, the removal of the 5’-RNA cap is essential for the initiation of RNA degradation. In addition to the canonical 5’-N7-methyl guanosine cap in [...] Read more.
The complexity of the transcriptome is governed by the intricate interplay of transcription, RNA processing, translocation, and decay. In eukaryotes, the removal of the 5’-RNA cap is essential for the initiation of RNA degradation. In addition to the canonical 5’-N7-methyl guanosine cap in eukaryotes, the ubiquitous redox cofactor nicotinamide adenine dinucleotide (NAD) was identified as a new 5’-RNA cap structure in prokaryotic and eukaryotic organisms. So far, two classes of NAD-RNA decapping enzymes have been identified, namely Nudix enzymes that liberate nicotinamide mononucleotide (NMN) and DXO-enzymes that remove the entire NAD cap. Herein, we introduce 8-(furan-2-yl)-substituted NAD-capped-RNA (FurNAD-RNA) as a new research tool for the identification and characterization of novel NAD-RNA decapping enzymes. These compounds are found to be suitable for various enzymatic reactions that result in the release of a fluorescence quencher, either nicotinamide (NAM) or nicotinamide mononucleotide (NMN), from the RNA which causes a fluorescence turn-on. FurNAD-RNAs allow for real-time quantification of decapping activity, parallelization, high-throughput screening and identification of novel decapping enzymes in vitro. Using FurNAD-RNAs, we discovered that the eukaryotic glycohydrolase CD38 processes NAD-capped RNA in vitro into ADP-ribose-modified-RNA and nicotinamide and therefore might act as a decapping enzyme in vivo. The existence of multiple pathways suggests that the decapping of NAD-RNA is an important and regulated process in eukaryotes. Full article
(This article belongs to the Special Issue Nicotinamide in Health and Diseases)
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Open AccessFeature PaperArticle
Electrical and Photovoltaic Properties of Layered Composite Films of Covalently Bonded Graphene and Single-Walled Carbon Nanotubes
Coatings 2020, 10(4), 324; https://doi.org/10.3390/coatings10040324 (registering DOI) - 28 Mar 2020
Abstract
In this paper, we present the results of a computational study of the electrical and photovoltaic properties of a perspective composite material; that is, layered composite films of covalently bonded graphene and single-walled carbon nanotubes (SWCNTs). The purpose of the study is to [...] Read more.
In this paper, we present the results of a computational study of the electrical and photovoltaic properties of a perspective composite material; that is, layered composite films of covalently bonded graphene and single-walled carbon nanotubes (SWCNTs). The purpose of the study is to identify the topological patterns in controlling the electrical and photovoltaic properties of mono- and bilayer graphene/CNT composite films with a covalent bonding of a nanotube and graphene sheet, using in silico methods. This in silico study was carried out for the super-cells of mono- and bilayer graphene/CNT composite films with the CNTs (10,0) and (12,0) at distances between the nanotubes of 10 and 12 hexagons. This found that the type of conductivity of the nanotubes does not fundamentally affect the patterns of current flow in the graphene/CNT composite films. This control of the diameter of the nanotubes and the distance between them allows us to control the profile of the absorption spectrum of the electromagnetic waves in the range of 20–2000 nm. The control of the distance between the SWCNTs allows one to control the absorption intensity without a significant peak shift. This revealed that there is no obvious dependence of the integrated photocurrent on the distance between the nanotubes, and the photocurrent varies between 3%–4%. Full article
(This article belongs to the Special Issue Photocatalytic Surfaces for Environmental Applications)
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