Fast Extraction Method Research Articles

An Improved LC-MS/MS Method for the Analysis of Thirteen Cytostatics on Workplace Surfaces.

Cytostatics are drugs used in cancer treatment, which pose serious risks to healthcare workers. Dermal absorption via surface contamination is the key exposure route; thus, rapid, reliable, and validated analytical methods for multicomponent detection are crucial to identify the exposure risk. A surface-wipe-sampling technique compatible with hospitals’ safety requirements (gauze, 1 mL isopropanol) and a fast and simple extraction method (1 mL acetonitrile, 20 min ultrasonic bath, evaporation, reconstitution in 200 µL acetonitrile), coupled with liquid chromatography–tandem mass spectrometry analysis, were developed. It allowed identification and quantification of 13 cytostatics on surfaces: cyclophosphamide, doxorubicin, etoposide, ifosfamide, paclitaxel, bicalutamide, capecitabine, cyproterone, flutamide, imatinib, megestrol, mycophenolate mofetil, prednisone. Good linearity, sensitivity, and precision were achieved (R2 > 0.997, IDLs < 4.0 pg/cm2, average CV 16%, respectively). Accuracy for four model surfaces (melamine-coated wood, phenolic compact, steel 304, steel 316) was acceptable (80 ± 12%), except for capecitabine and doxorubicin. Global uncertainty is below 35% for concentrations above 100 pg/cm2 (except for capecitabine and doxorubicin)—a guidance value for relevant contamination. Method application in a Portuguese university hospital (28 samples) identified the presence of seven cytostatics, at concentrations below 100 pg/cm2, except for three samples. The widespread presence of cyclophosphamide evinces the necessity to review implemented procedures.

Research on Intelligent Inspection Method of Transmission Channel Satellite Remote Sensing Environmental Changes

With the shortage of transmission channel resources and the increase of human activities, the inspection of transmission channel environment changes is of great significance to the protection of line breakage, the management of transmission channel resources and the detection of hidden dangers in advance. In order to explore a fast and intelligent extraction method of environmental change information in the transmission channel, this paper takes a transmission line section in Tongzhou District of Beijing as the experimental area, takes two high-resolution satellite images of Beijing No.2 as the data source, and conducts principal component analysis and vegetation index processing analysis on the two satellite image data. An intelligent patrol method for transmission channel environmental change based on multi-source feature multi-scale segmentation technology and object-oriented classification algorithm is proposed. The results show that the satellite remote sensing environmental change intelligent patrol method proposed in this paper is sensitive and effective to the human activity change patrol of the transmission channel, and can be extended to the large-scale and normal intelligent patrol operation of the transmission channel against external breach.

A rapid and reliable method for genetic sex identification in sea cucumber, Apostichopus japonicus

Identification of sex-specific markers has important implications for genetic breeding and sex control breeding in aquaculture. Sea cucumber (Apostichopus japonicus) is one of the most important mariculture species in China. Although a substantial difference in immunocompetence has been observed between male and female sea cucumbers, the sex-specific marker remains unclear. Moreover, there is no reliable method for genetic sex identification in sea cucumbers. In this study, we first applied a 2b-RAD-seq method and identified two male-specific 2b-RAD-tags. This includes a 313 bp male-specific fragment that was mapped to scaffold MRZV01000576.1 of the male genome of A. japonicus. Several genes associated with the centromere, such as tesin-a-like gene, centromere-associated gene, reverse transcriptase gene, were also annotated within this scaffold. By designing three different sex-specific primers, we characterized genetic sex of sea cucumbers in different culture populations and the wild population. Using a fast and low-cost alkaline lysis method for DNA extraction, a reliable PCR amplification-mediated genetic sex identification method was developed. Hence, the sex-specific markers provide a solid basis to reveal the sex determination mechanism and the origin of sex-determining regions in sea cucumber. Furthermore, this study will improve the efficiency of genetic and sex control breeding in sea cucumbers.

Robust and fast image processing method for feature extraction of jet engine modulation signals

Robust and fast image processing method for feature extraction of jet engine modulation signals

Kinetic studies of internal boiling extraction and other two extraction techniques for polysaccharides from Cortex periplocae

A method based on the boiling of immersion agent inside the material to improve polysaccharide extraction efficiency called internal boiling method (IBE), is reported herein. It was compared with hot water extraction (HWE) and ultrasonic-assisted extraction (UAE) using an extracted mathematical model. The mathematical model was based on Fick’s second law, and the employed variables were the temperature, ultrasonic power, and extraction time. The rate constant (κ), diffusion coefficient (Ds), relative raffinate ratio, and extraction t0.8 were analyzed. In the case of IBE, the extraction process reached its equilibrium concentration after approximately 20–30 min, thereby indicating a more rapid extraction compared with UAE (30–50 min) and HWE (120–180 min). In addition, the equilibrium concentration of IBE (0.484 mg/mL, 358.15 K) was significantly higher than those of the UAE (0.451 mg/mL, 300 W) and HWE (0.256 mg/mL, 358.15 K) processes. Furthermore, the ranges of κ and Ds were in the order of IBE > UAE > HWE at temperatures ≥348.15 K. These results indicated that IBE is a fast, efficient, and simple method for polysaccharide extraction.

A fast and efficient method for selective extraction of lithium from spent lithium iron phosphate battery

A new recovery method for fast and efficient selective leaching of lithium from lithium iron phosphate cathode powder is proposed. Lithium is expelled out of the Oliver crystal structure of lithium iron phosphate due to oxidation of Fe 2 + into Fe 3 + by ammonium persulfate. 99% of lithium is therefore leached at 40 °C with only 1.1 times the amount of ammonium persulfate without the help of acid treatment. The use of ammonium persulfate also avoids the necessity to remove other metal ions in the later purification process. Various characterization methods including SEM, XPS, XRD are used to explore the experimental leaching mechanism. Theoretical investigations are performed which reveals the E-pH diagram of Fe–P–Li–H 2 O thermodynamic equilibrium. It confirms the possibility and suggests appropriate pH range allowing direct conversion from lithium iron phosphate to iron phosphate with great energy saving and reduced use of acid and base. Based on the experimental and theoretical results, a green and efficient closed-loop recycling route for lithium iron phosphate is proposed. • A fast efficient leaching of LiFePO 4 is achieved via oxidation by (NH 4 ) 2 S 2 O 8 . • 99% of lithium is leached without acid due to oxidation of LiFePO 4 to FePO 4 . • Mechanism studies are conducted to establish principles for recycling LiFePO 4 .

Fast fabric phase sorptive extraction of selected β-blockers from human serum and urine followed by UHPLC-ESI-MS/MS analysis

A fast fabric phase sorptive extraction method is presented herein for the rapid isolation of selected beta-blocker drugs from human serum and urine. Among many high efficiency sol-gel sorbent coated FPSE membranes, sol-gel CW20 M coated FPSE membrane was identified as the best FPSE membrane for the target beta-blocker drugs possessing logP values ranging from 0.1 (highly polar) to 3.1 (moderately polar). Due to the engineered affinity towards the analytes via complementary intermolecular interactions and high mass transfer rate of the analytes from the bulk sample solution to the FPSE membrane, the extraction is accomplished in relatively short time (15 min) while its high permeability permits the direct extraction of biological samples without any other pretreatment. The advantages of the fabricated extraction membrane were exploited for the determination of six beta-blockers (namely atenolol, nadolol, metoprolol, oxprenolol, labetalol and propranolol) in biological matrices in combination with UHPLC-ESI-MS/MS. Important parameters including extraction time, sample volume, sorbent size, elution solvent, etc. affecting the performance of the extraction were systematically investigated. The linearity of the method was evaluated in the range of 50–5000 ng mL−1 by constructing weighted (1/X) matrix-matched calibration curves. The intra-day and inter-day trueness were ranged between – 17.2 to 13.3% and – 10.8 to 12.6%, respectively. The intra-day and inter-day precision were less than 11.5 and 14.5 %, respectively. The proposed analytical scheme was successfully applied to the determination of the target drugs in human serum and urine.

Identification for adulteration of beef with chicken based on single primer-triggered isothermal amplification

Abstract Adulteration of beef with cheap chicken has become a growing problem worldwide. In this study, a quick, single primer-triggered isothermal amplification (SAMP) combined with a fast nucleic acid extraction method was employed to detect the chicken meat in adulterated beef. Chicken from adulterated beef was identified using the chicken species-specific primer designed according to the Gallus gallus mitochondrial conserved sequences. Our SAMP method displayed good specificity and sensitivity in detecting chicken and beef meat DNA–the limit of detection (LOD) of SAMP is 0.33 pg/μL of chicken and beef total DNA and 2% w/w chicken meat in beef. The whole work flow from DNA extraction to signal detection can be finished within 1 h, fulfilling the requirement of on-site meat species identification.

Nano-Interstice Driven Powerless Blood Plasma Extraction in a Membrane Filter Integrated Microfluidic Device.

Blood plasma is a source of biomarkers in blood and a simple, fast, and easy extraction method is highly required for point-of-care testing (POCT) applications. This paper proposes a membrane filter integrated microfluidic device to extract blood plasma from whole blood, without any external instrumentation. A commercially available membrane filter was integrated with a newly designed dual-cover microfluidic device to avoid leakage of the extracted plasma and remaining blood cells. Nano-interstices installed on both sides of the microfluidic channels actively draw the extracted plasma from the membrane. The developed device successfully supplied 20 μL of extracted plasma with a high extraction yield (~45%) in 16 min.

Fast Color Straight Line Pattern Recognition in an Object Using High Speed Self Learning Devices

Most of the man-made objects are having some straight lines with colors. A very high-speed object recognition method using color straight line patterns is carried out using a novel self-learning device (RKD - Rasiq Krishnakumar Device). Instead of that Artificial Neural Networks (ANN), RKD based networks are used for different steps in this pattern classification. The color and straight-line features are extracted by using high-speed color segmentation and fast efficient straight-line segment extraction methods using the RKD based systems. The training and the testing algorithms of the pattern classification are using RKD-based processing. The fast color features extraction method uses an array of RKD-based devices and the fast efficient straight-line segment extraction method employs an array of processing elements and a main control unit. Some fusion devices are used for a straight line with colors features. The area of interest and the area of line segments of a particular object are other features for improving the accuracy of object classification.

In situ adsorbent formation based dispersive micro-solid phase extraction using a deep eutectic solvent as an elution solvent for the extraction of some pesticides from honey samples prior to GC-MS analysis

In this work, a simple, inexpensive, green, and fast dispersive micro-solid phase extraction method has been developed for the extraction of several pesticides from honey samples. In this approach, a solution of curcumin was prepared in ethanol and it was dispersed into a sample solution with the aid of a syringe. Curcumin was precipitated in the sample solution as tiny particles and the analytes were adsorbed onto them. After centrifugation the adsorbed analytes were eluted with tetrabutylammonium chloride:dichloroacetic acid deep eutectic solvent. The dissolved analytes in the deep eutectic solvent were analyzed by gas chromatography-mass spectrometry. Parameters affecting the extraction efficiency of the method including sorbent amount, dispersive solvent type and volume, elution solvent type and volume, salting out effect, and sonication time were investigated. Extraction recovery of the method was obtained in the range of 70-83%. Also wide calibration ranges and low detection limits (0.22-0.81 ng g-1) were obtained. Relative standard deviation values for intra- and inter-day precisions were ≤10.2% for all analytes at a concentration of 5 ng g-1 of each (n = 6). Finally, ten honey samples were analyzed and data showed that all of the studied samples were free of the analytes.

A new framework for contour tracing using Euclidean distance mapping

In this paper, a new fast, efficient and accurate contour extraction method, using eight sequential Euclidean distance map and connectivity criteria based on maximal disk, is proposed. The connecti...

Development of a High Quality, Rapid, Efficient and Economical DNA Extraction Protocol from Climate Resilient Pearl Millet Crop Without Liquid Nitrogen

Extraction of good quality genomic deoxyribonucleic acid (DNA) from plants is a major prerequisite for molecular biology experiments. An efficient genomic DNA protocol must be simple, fast and cost effective with high yield and purity. Presence of polyphenols, polysaccharides and secondary metabolites in some plants hamper with DNA extraction making it a very laborious, difficult and time consuming procedure. Here, we portrayed a modified protocol based on the cetyl trimethyl ammonium bromide (CTAB) method to isolate DNA from climate resilient pearl millet leaf tissues having higher amount of polysaccharides. It also excludes the use of expensive chemicals and equipments like proteinase K, liquid nitrogen and tissue lyser. This method includes extraction of DNA using a buffer (pH 8.0) containing 200 mM Tris-HCl, 20 mM ethylenediamine tetracetic acid (EDTA),1.4 M NaCl, 2% CTAB, 2% sodium dodecyl sulphate (SDS) and 1.0 % β-mercaptoethanol followed by purification of DNA with phenol, chloroform, isoamyl alcohol and finally precipitation of DNA by sodium acetate and isopropanol. Good quality genomic DNA with sharp and clear bands was obtained from 48 pearl millet genotypes using this protocol. The yield of DNA varied from 105.2 to 328.3 ng/μl. The purity of DNA sample ranged from 1.74 to 1.95 based on the absorbance at A260/A280 ratio indicating that it’s free from ribonucleic acid (RNA) and protein contamination. PCR analysis using simple sequence repeat (SSR) primers exhibited consistent and reliable amplification products ranging from 150 to 650 bp.This study reveals a fast, simple, efficient, specific, reproducible, reliable and cost effective method for extraction of DNA from small to large number of plant samples amenable to PCR amplification and could be stored for longer duration.

Integrating saliency with fuzzy thresholding for brain tumor extraction in MR images

The automatic detection and extraction of tumor area in Magnetic Resonance Imaging (MRI) is an important and challenging task. This paper presents a fully automatic and unsupervised method for fast and accurate extraction of brain tumor area from MR images. The proposed method named as Saliency Based Segmentation (SBS) is based on visual saliency. The saliency model detects the pathologically important area and then fuzzy thresholding is used for extraction of the detected region. The performance of SBS is compared with Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering, Mean Shift and Fuzzy C-Means clustering with Level Set Method. The experimental evaluation validated on BRATS database using Jaccard index (0.84 ± 0.04), Dice Index (0.91 ± 0.02), Execution time (2.99 ± 0.29), Precision (0.82 ± 0.16), Recall (0.97 ± 0.03) and F-measure (0.88 ± 0.10) demonstrates that SBS achieves better segmentation results even in the presence of noise and uneven illumination in images.

Attention-based learning of self-media data for marketing intention detection

In the context of natural language processing, accuracy of intention detection is the basis for subsequent research on human-machine speech interaction. However, the problem of ambiguity in word vectors reduces the accuracy of intent detection. Meantime, there is a disconnection between local features and global features as well, resulting in text feature extraction that cannot fully reflect semantic information. These issues are all barriers of intention detection. Therefore, this paper proposes an attention-based convolutional neural network for self-media data learning (called A-CNN) for marketing intention. We cascade the traditional CNN with the self-attention model in the Attention networks to form a new network structure called A-CNN, and put forward a fast feature extraction method based on skip-gram-based learning called FSLText, to represent the high-dimension word vectors in the A-CNN. On the premise of maintaining the advantages of the CNN, A-CNN can not only solve the problem of local and global features disconnection caused by the CNN pooling layer, but also avoid the increase of algorithm complexity. The Self-Attention mechanism in the Attention model can effectively optimize the weight of local features of the information in global features, and retain local features that are more useful for intention detection. A fast feature extraction method which is based on Skip-gram can retain the semantic and word order information of the text. The method is beneficial to the marketing intention detection. According to the experiment, our A-CNN, compared with traditional machine learning methods, can improve 12.32% accuracy. Contrast to the dual-channel CNN, the accuracy rate is improved by 9.68%, and compared with the ATT-CNN, it is improved by 9.97%. On the F1 score, the A-CNN can improve the F1 score by about 9.37% in comparison with the traditional machine learning methods, the accuracy rate is increased by 9.68% compared with the dual-channel CNN, and 9.68% in contrast with ATT-CNN. It illustrates that our A-CNN can effectively address semantic and feature selection for marketing intention detection.

Visual-Inertial Odometry of Smartphone under Manhattan World

Based on the hypothesis of the Manhattan world, we propose a tightly-coupled monocular visual-inertial odometry (VIO) system that combines structural features with point features and can run on a mobile phone in real-time. The back-end optimization is based on the sliding window method to improve computing efficiency. As the Manhattan world is abundant in the man-made environment, this regular world can use structural features to encode the orthogonality and parallelism concealed in the building to eliminate the accumulated rotation error. We define a structural feature as an orthogonal basis composed of three orthogonal vanishing points in the Manhattan world. Meanwhile, to extract structural features in real-time on the mobile phone, we propose a fast structural feature extraction method based on the known vertical dominant direction. Our experiments on the public datasets and self-collected dataset show that our system is superior to most existing open-source systems, especially in the situations where the images are texture-less, dark, and blurry.

Fast and robust key frame extraction method for gesture video based on high-level feature representation

In gesture video, the inner-frame difference is too subtle to be projected via low-level features, and the gesture frames, expressing semantic information, are distributed only among the tiny part of the whole video frame. This paper introduces a fast and robust key frame extraction method for gesture video, founded upon high-level feature representation to extract the gesture key frame precisely without affecting the semantic information. Firstly, a gesture video segmentation model is designed by employing SSD, which classify gesture video into the semantic scene and the static scene. And then, the 2D-DWT-based perceptual hash algorithm is studied to extract candidate static key frames. Afterward, the multi-channel gradient magnitude frequency histogram (HGMF-MC) based on improved VGG16 is developed as a new image descriptor. Finally, a key frame extraction mechanism based on HGMF-MC is proposed to generate gesture video summary of two scenes, respectively. Experiments consistently show the superiority of the proposed method on Chinese sign language, Cambridge, ChaLearn and CVRR-Hands gesture datasets. The results demonstrate that the method proposed is effective, which improves the video compression ratio and outperforms the state-of-the-art methods.

A fast automatic extraction method for rock mass discontinuity orientation using fast k-means++ and fast silhouette based on 3D point cloud

In this paper, a fast automatic extraction method for rock discontinuity orientation using fast k-means++ and fast silhouette based on three-dimensional (3D) point cloud is proposed. The main contributions of the proposed method include: (1) a concept of base vector is proposed, (2) a fast k-means++ algorithm and a fast clustering validity index of silhouette are proposed and combined to automatically achieve a fast optimal grouping of discontinuities, and (3) the generation and optimization of independent discontinuity based on a double-clustering algorithm. The proposed method consists of three steps : (1) point cloud preprocessing, (2) optimal grouping of discontinuities, and (3) discontinuity generation and optimization. Several cases, including two polyhedral models under laboratory conditions and two rock slope models, are adopted to verify the accuracy and efficiency of the proposed method. A sensitivity analysis is performed to determine the optimal parameters. The results show that the proposed method can automatically achieve a fast and effective extraction of discontinuity orientations compared with the classical method, Slob (2010), Riquelme et al. (2014) and Li et al. (2016), and the efficiency is significantly improved compared with Rousseeuw (1987), Arthur and vassilvitskii (2007) and Li et al. (2016).

Development of Fast Sampling and High Recovery Extraction Method for Stable Isotope Measurement of Gaseous Mercury

A method involving fast large-volume sampling and bag extraction of total gaseous mercury (TGM) using a 5 mL acid solution was developed for stable mercury isotope ratio measurements. A big gold-coated sand trap (BAuT)—a 45 (i.d.) × 300 mm (length) quartz tube with 131 times more trapping material than a conventional gold trap—was used for the collection of a large amount of TGM. The collected TGM was extracted using 5 mL inversed aqua regia in a 2 L Tedlar bag followed by isotope measurements using a cold vapor generator coupled with a multicollector inductively coupled plasma mass spectrometer. Sampling tests demonstrated that the collection efficiency of the BAuT was 99.9% or higher during the 1–24 h sampling period under the flow rate of 20–100 L min−1. Recovery tests of 24 h bag extraction using 100 ng NIST SRM 8610 exhibited nearly 100% recovery yields. The five measured stable mercury isotope ratios agreed with reference values within 2σ intervals. The overall methodology tested during the pilot field and laboratory studies demonstrated its successful application in analysis, promising highly precise stable mercury isotopic data with a time resolution of less than 24 h.

Coupling of ion pair ultrasound assisted-cloud point extraction to microvolume UV-Vis spectrophotometry for speciation analysis of ionic NO2-,NO3- and total NO2-/NO3- without and with reduction in the selected beverage and food matrices

ABSTRACT This study proposes a simple, low-cost, easy to use, fast, accurate and reliable ultrasound assisted-cloud point extraction (UA-CPE) method for the enrichment and speciation analysis of low levels of ionic NO2 −, NO3 − and total NO2 −/NO3 − without and with reduction by micro-volume UV-vis spectrophotometry. The method relies on the reaction of NO2 − with excess iodide at pH 5.5 to form triiodide, and then the extraction of the oxidation product formed by charge transfer into micellar phase of Triton X-114 using cationic redox-sensitive phenazine dye, neutral red (NRH+) as ion-pairing in absence and presence of 1.5 mL of 1.0 × 10−3 mol L−1 Br− ions. The main variables affecting extraction efficiency were studied and optimised in detail. Under the optimal conditions, the calibration curves in solvent were linear over the ranges of 5–100 and 100–1280 µg L−1 with a detection limit of 1.32 µg L−1 while the matrix-matched calibration curves prepared from sample extracts were linear over the ranges of 5–125 and 125–1350 µg L−1 with a detection limit ranging from 1.15 to 1.50 µg L−1 for sample matrices. From pre-concentration of 25-mL sample, pre-concentration and sensitivity enhancement folds of 62.5 and 76.5 were obtained. The accuracy/precision studies after spiking were performed, and observed to be in range of 96.5–99.6% and 1.9–5.7% (15, 75 and 250 µg L−1, n: 5). The speciation analysis of ionic NO2 −, NO3 − and total NO2 −/NO3 − was performed from artificially prepared binary mixtures after reduction with a mixture of Zn and NaCl in acidic media. The free NO3 − contents of samples were calculated from difference between free NO2 − and total NO2 −/NO3 − contents. After validation by analysis of a certified sample, the method was successfully applied to the speciation analysis of the beverage, cured meat, vegetable and milk samples. After pre-treatment with two sample preparation steps, it was observed that the results obtained were also compatible with each other, statistically validating the method.