Immunoassays are currently not available in commercial kits for the quantification of valproic acid, vigabatrin, pregabalin, and gabapentin, which also cannot suffer the limitations of interferences ...of substances with similar structures. Chromatography is a good alternative to immunoassay. In this study, a simple and robust non‐derivatization gas chromatography‐mass spectrometry method for simultaneous determination of the above four drugs in human plasma was developed and validated for therapeutic drug monitoring purposes. This method employed benzoic acid as the internal standard with hydrochloric acid for plasma acidification and ACN for precipitate protein. The supernatant was directly injected into gas chromatography‐mass spectrometry for analysis. Good linearity was obtained with linear correlation coefficients of the four analytes of 0.9988–0.9996. Extraction recoveries of valproic acid, vigabatrin, pregabalin, and gabapentin were respectively in the ranges of 91.3%–94.5%, 90.0%–90.9%, 90.0%–92.1%, and 88.0%–92.2% with the relative standard deviation values less than 12.6%. Intra‐ and inter‐batch precision and accuracy, and stability assays were all acceptable. Taken together, the novel method developed in this study provided easy plasma pretreatment, good extraction yield, and high chromatographic resolution, which has been successfully validated through the quantification of valproic acid in the plasma of 46 patients with epilepsy.
Synthetic aperture radar (SAR) ship detection is an important part of marine monitoring. With the development in computer vision, deep learning has been used for ship detection in SAR images such as ...the faster region-based convolutional neural network (R-CNN), single-shot multibox detector, and densely connected network. In SAR ship detection field, deep learning has much better detection performance than traditional methods on nearshore areas. This is because traditional methods need sea-land segmentation before detection, and inaccurate sea-land mask decreases its detection performance. Though current deep learning SAR ship detection methods still have many false detections in land areas, and some ships are missed in sea areas. In this letter, a new network architecture based on the faster R-CNN is proposed to further improve the detection performance by using squeeze and excitation mechanism. In order to improve performance, first, the feature maps are extracted and concatenated to obtain multiscale feature maps with ImageNet pretrained VGG network. After region of interest pooling, an encoding scale vector which has values between 0 and 1 is generated from subfeature maps. The scale vector is ranked, and only top <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula> values will be preserved. Other values will be set to 0. Then, the subfeature maps are recalibrated by this scale vector. The redundant subfeature maps will be suppressed by this operation, and the detection performance of detector can be improved. The experimental results based on Sentinel-1 images show that the detection performance of the proposed method achieves 0.836 which is 9.7% better than the state-of-the-art method when using F1 as matric and executes 14% faster.
Synthetic aperture radar (SAR) ship detection has been playing an increasingly essential role in marine monitoring in recent years. The lack of detailed information about ships in wide swath SAR ...imagery poses difficulty for traditional methods in exploring effective features for ship discrimination. Being capable of feature representation, deep neural networks have achieved dramatic progress in object detection recently. However, most of them suffer from the missing detection of small-sized targets, which means that few of them are able to be employed directly in SAR ship detection tasks. This paper discloses an elaborately designed deep hierarchical network, namely a contextual region-based convolutional neural network with multilayer fusion, for SAR ship detection, which is composed of a region proposal network (RPN) with high network resolution and an object detection network with contextual features. Instead of using low-resolution feature maps from a single layer for proposal generation in a RPN, the proposed method employs an intermediate layer combined with a downscaled shallow layer and an up-sampled deep layer to produce region proposals. In the object detection network, the region proposals are projected onto multiple layers with region of interest (ROI) pooling to extract the corresponding ROI features and contextual features around the ROI. After normalization and rescaling, they are subsequently concatenated into an integrated feature vector for final outputs. The proposed framework fuses the deep semantic and shallow high-resolution features, improving the detection performance for small-sized ships. The additional contextual features provide complementary information for classification and help to rule out false alarms. Experiments based on the Sentinel-1 dataset, which contains twenty-seven SAR images with 7986 labeled ships, verify that the proposed method achieves an excellent performance in SAR ship detection.
Over 17 and 160 types of chemical modifications have been identified in DNA and RNA, respectively. The interest in understanding the various biological functions of DNA and RNA modifications has lead ...to the cutting-edged fields of epigenomics and epitranscriptomics. Developing chemical and biological tools to detect specific modifications in the genome or transcriptome has greatly facilitated their study. Here, we review the recent technological advances in this rapidly evolving field. We focus on high-throughput detection methods and biological findings for these modifications, and discuss questions to be addressed as well. We also summarize third-generation sequencing methods, which enable long-read and single-molecule sequencing of DNA and RNA modification.
Coordinated aggregation of a large population of thermostatically controlled loads (TCLs) presents a great potential to provide various ancillary services to the grid. One of the key challenges of ...integrating TCLs into system-level operation and control is developing a simple and portable model to accurately capture their aggregate flexibility. In this paper, we propose a geometric approach to model the aggregate flexibility of TCLs. We show that the set of admissible power profiles of an individual TCL is a polytope, and their aggregate flexibility is the Minkowski sum of the individual polytopes. In order to represent their aggregate flexibility in an intuitive way and achieve a tractable approximation, we develop optimization-based algorithms to approximate the polytopes by the homothets of a given convex set. As a special application, this set is chosen as a virtual battery model, and the corresponding optimal approximations are solved efficiently by equivalent linear programming problems. Numerical results show that our algorithms yield significant improvement in characterizing the aggregate flexibility over existing modeling methods. We also conduct case studies to demonstrate the efficacy of our approaches by coordinating TCLs to track a frequency regulation signal from the Pennsylvania-New Jersey-Maryland Interconnection.
A dual-template magnetic molecularly imprinted polymer (Dt-MMIP) with a specific recognition capability for carbamazepine (CBZ) and lamotrigine (LTG) was synthesized using methacrylic acid as a ...functional monomer, and ethylene glycol dimethylmethacrylate as a cross-linking agent. A magnetic non-molecularly imprinted polymer without templates (MNIP) was also prepared using the same procedure. The prepared polymers were characterized using scanning electron microscopy, Fourier-transform infrared spectroscopy and adsorption experiments. Results indicated that both Dt-MMIPs and MNIPs were microspherical nanoparticles, and the surface of the Dt-MMIP was rougher than that of the MNIP. In addition, the prepared Dt-MMIPs possessed a higher adsorption capacity and better selectivity for CBZ and LTG than the MNIPs. The maximum static adsorption capacities of Dt-MMIP for CBZ and LTG were 249.5 and 647.9 μg g
−1
, respectively, whereas those of MNIP were 75.8 and 379.8 μg g
−1
, respectively. The obtained Dt-MMIPs were applied as a magnetic solid-phase extraction sorbent for the rapid and selective extraction of CBZ and LTG in rat serum samples, and determination was performed by high-performance liquid chromatography with UV detection (HPLC-UV). The developed method of dispersive SPE based on Dt-MMIPs coupled to HPLC-UV has good rapidity and selectivity, and application prospects in serum.
A dual-template magnetic molecularly imprinted polymer (Dt-MMIP) with a specific recognition capability for carbamazepine and lamotrigine was synthesized using methacrylic acid as a functional monomer, and ethylene glycol dimethylmethacrylate as a cross-linking agent.
Abstract
This study proposes a new model in explicit form to predict the diameter of the jet grouting column of three popular jet grouting systems (i.e., single, double, and triple). The proposed ...model can quantify the uncertainty associated with the prediction. Bayesian model selection was used to determine the optimal models and, the bootstrap sampling method was adopted to avoid bias in the collected database. The predictions agree well with the measured data, and the 95% credible intervals can cover almost all the measured data on the testing dataset, which indicates the robustness of the proposed model. A simple formula combined with a table was established to facilitate the engineers in applying the proposed model. The results reveal that soil type has a significant impact on diameter prediction. Uncertainty quantification can reveal possible fluctuations in column diameter and is vital to get a cost‐efficient design.
In plants, macroautophagy/autophagy has mainly been associated with stress-related processes but how it impacts normal physiological and developmental processes remains largely unexplored. Pollen ...germination is the critical first step toward fertilization in flowering plants. It is metabolically demanding and relies on high levels of cytoplasmic reorganization activities to support a dramatic morphological transformation that underlies the development of a pollen tube as the conduit to deliver sperm for fertilization. The role of autophagy in this process remains unclear. Here we provide evidence that pollen germination is accompanied by elevated autophagic activity and successful pollen tube emergence depends on autophagy-mediated cytoplasmic deletion. Genetic and cytological experiments demonstrate that inhibition of autophagy prevents pollen germination while induces the persistence of a layer of undegraded cytoplasm at the germination aperture. Together, these results unveil a novel compartmentalized autophagy. Furthermore, high-throughput comparative lipidomic analyses show that suppressed autophagy-induced inhibition of pollen germination is accompanied by altered profiles of stored and signaling lipids. Proteomic analyses reveal that autophagy likely exert its role in pollen germination via downstream mitochondria-related pathways. These findings reveal a critical role for autophagy in initiating pollen germination and provide evidences for compartmental cytoplasmic deletion being crucial for male fertility.
Abbreviations: 3-MA: 3-methyladenine; ATG: autophagy-related gene; Cer: ceramide; CL: cardiolipin; Con A: concanamycin A; DAG: diradylglycerol; GO: gene ontology; HAG: hour after germination; LC-MS: liquid chromatography-mass spectrometry; MAG: min after germination; MDC: monodansylcadaverine; PE: phosphatidylethanolamine; PI: phosphatidylinositol; PLD: phospholipase D; PtdIns3K: phosphatidylinositol 3-kinase; RT-qPCR: quantitative real-time reverse transcription PCR; TAG: triradylglycerol; TEM: transmission electron microscopy; TMT: tandem mass tagging.
•Coriandrum sativum L. is widely used as a condiment and in folk medicine.•There are six categories of main active constituents in coriander.•The yields and compositions of coriander extracts vary ...depending on many factors.•Coriander essential oil and other extracts have different degrees of bioactivities.•Coriander and its extracts are safe for medical and edible use.
Coriandrum sativum L. is well known around the world because of its food and medicine uses. The main bioactive constituents in C. sativum are essential oil, fatty acids, tocol, sterol and carotenoids, their yields and chemical compositions being influenced by genotype, variety, planting season, ecotype, planting condition, growth stage, plant part, harvesting time, extracting process and other factors. Coriander and its different extracts possess varying degrees of antioxidative and antimicrobial activities on account of different active constituents. The general usages, chemical compositions and bioactivities of coriander are summarized in this review, along with safety considerations.
The deep convolutional neural network (CNN) has been widely used for target classification, because it can learn highly useful representations from data. However, it is difficult to apply a CNN for ...synthetic aperture radar (SAR) target classification directly, for it often requires a large volume of labeled training data, which is impractical for SAR applications. The highway network is a newly proposed architecture based on CNN that can be trained with smaller data sets. This letter proposes a novel architecture called the convolutional highway unit to train deeper networks with limited SAR data. The unit architecture is formed by modified convolutional highway layers, a maxpool layer, and a dropout layer. Then, the networks can be flexibly formed by stacking the unit architecture to extract deep feature representations for classification. Experimental results on the moving and stationary target acquisition and recognition data set indicate that the branched ensemble model based on the unit architecture can achieve 99% classification accuracy with all training data. When the training data are reduced to 30%, the classification accuracy of the ensemble model can still reach 94.97%.