Single Extraction Research Articles

Recommendations for the integral diagnosis of chronic viral hepatitis in a single analytical extraction

Recommendations for the integral diagnosis of chronic viral hepatitis in a single analytical extraction

Effect of incubation time of three single extraction procedures on trace element extraction from sediment and soil.

The use of standard single-extraction procedures to evaluate the mobility and availability of trace elements is a common practice in most laboratories dealing with soil or sediment analysis. Most standard single-extraction procedures describe incubations last for 2h. However, these were tested and validated for soil analysis. Applying them for sediment analysis without further investigation might be misleading and should be reviewed with care. This paper investigates the effect of incubation time on the extraction efficiency of three standard single-extracting reagents (0.01M CaCl2, 1M NH4NO3, and 0.05M EDTA). Incubation experiments with sediment and soil samples lasting for 2h, 10h, and 10 d were performed. The results indicated that 2h appears sufficient to reach equilibrium using CaCl2 or NH4NO3 for soil analysis; but when analyzing sediments, incubation for 10 d resulted in higher concentrations. Incubation experiments with 0.05M EDTA showed that incubation for 2h was enough to extract Cd from the soil sample, Mn and to a lesser extent Cd from the sediment samples; while for the other elements, incubation for 10 d yielded higher concentrations for both sample types compared to that obtained after 2h and 10h separately. Relative to the pseudo-total metal contents, more than 55% of all studied elements were extracted by using 0.05M EDTA, indicating high bioavailable metal fraction.

Is L-PRF an effective hemostatic agent in single tooth extractions? A cohort study on VKA and DOAC patients

ObjectivesThe aim of this clinical observational study was to assess the efficacy of L-PRF as a hemostatic agent in patients under treatment with vitamin K antagonists (VKAs) or direct oral anticoagulants (DOACs).Materials and methodsPatients under oral anticoagulant therapy (VKA or DOACs) who needed a single simple tooth extraction were enrolled. L-PRF plug was positioned inside the alveolus and secured with non-absorbable sutures. Surgical time, pain-VAS, paracetamol intake, intra-operative, post-operative biological complications, and bleeding events have been registered.ResultsA total of 112 patients (59 patients for DOAC and 53 for VKA group) were enrolled. Post-operative bleeding was recorded in nine patients (17%) for VKA group and nine patients (15.3%) for DOACs group. None of the patients needed a medical support for managing of bleeding. Seven days after surgery, no cases of post-extractive complications occurred.ConclusionsThe use of L-PRF resulted in limited mild late post-operative bleedings without the need of medical intervention.Clinical relevanceThe use of L-PRF can be adopted for an uneventful post-operative curse in anticoagulated patients without chasing their therapy for single tooth extraction.

Trends in EEG signal feature extraction applications.

This paper will focus on electroencephalogram (EEG) signal analysis with an emphasis on common feature extraction techniques mentioned in the research literature, as well as a variety of applications that this can be applied to. In this review, we cover single and multi-dimensional EEG signal processing and feature extraction techniques in the time domain, frequency domain, decomposition domain, time-frequency domain, and spatial domain. We also provide pseudocode for the methods discussed so that they can be replicated by practitioners and researchers in their specific areas of biomedical work. Furthermore, we discuss artificial intelligence applications such as assistive technology, neurological disease classification, brain-computer interface systems, as well as their machine learning integration counterparts, to complete the overall pipeline design for EEG signal analysis. Finally, we discuss future work that can be innovated in the feature extraction domain for EEG signal analysis.

Design and Development of a Low-Cost UGV 3D Phenotyping Platform with Integrated LiDAR and Electric Slide Rail.

Unmanned ground vehicles (UGV) have attracted much attention in crop phenotype monitoring due to their lightweight and flexibility. This paper describes a new UGV equipped with an electric slide rail and point cloud high-throughput acquisition and phenotype extraction system. The designed UGV is equipped with an autopilot system, a small electric slide rail, and Light Detection and Ranging (LiDAR) to achieve high-throughput, high-precision automatic crop point cloud acquisition and map building. The phenotype analysis system realized single plant segmentation and pipeline extraction of plant height and maximum crown width of the crop point cloud using the Random sampling consistency (RANSAC), Euclidean clustering, and k-means clustering algorithm. This phenotyping system was used to collect point cloud data and extract plant height and maximum crown width for 54 greenhouse-potted lettuce plants. The results showed that the correlation coefficient (R2) between the collected data and manual measurements were 0.97996 and 0.90975, respectively, while the root mean square error (RMSE) was 1.51 cm and 4.99 cm, respectively. At less than a tenth of the cost of the PlantEye F500, UGV achieves phenotypic data acquisition with less error and detects morphological trait differences between lettuce types. Thus, it could be suitable for actual 3D phenotypic measurements of greenhouse crops.

Evaluating the repetitive mucus extraction effects on mucus biomarkers, mucous cells, and the skin-barrier status in a marine fish model

Among all the mucosal barriers, the skin and its surrounding mucus are possibly the main defensive tool against changes in the environment that can be harmful for fish. Due to the extraction of this mucus being less invasive, the study of its production and functions has attracted great interest in recent years. However, there are still many gaps concerning the sampling process as well as the possible alterations in skin integrity and mucus composition. In the current study, the effects of skin mucus extraction were determined by comparing the effects of a single extraction (single extraction group, SEG) with those of three successive extractions separated by 3 days (repetitive extractions group, REG). Intact skin histology without mucus extraction (ØEG) and both plasma and skin mucus biomarkers and antibacterial capacities were also assessed. Regarding the skin histology and skin barrier properties, both the SEG and REG did not show differences in the intact skin. Interestingly, repetitive mucus extractions seemed to activate skin mucus turnover, significantly increasing the number of small-sized mucous cells (cell area< 100 µm2) and reducing the number of large-sized mucous cells (cell area > 150 µm2). Repetitive extractions significantly decreased the amounts of soluble protein and increased cortisol secretion. These metabolites remained unaltered in the plasma, indicating different responses in the plasma and mucus. Despite changes in the mucus biomarkers, antibacterial capacity against pathogenic bacteria (Pseudomonas anguilliseptica and Vibrio anguillarum) was maintained in both the plasma and mucus irrespective of the number of mucus extractions. Overall, the mucus sampling protocol had little effect on skin integrity and mucus antibacterial properties, only modifying the amounts of soluble protein exuded and stimulating mucous cell replacement. This protocol is a feasible and minimally invasive way of studying and monitoring fish health and welfare and can be used as an alternative or a complement to plasma analysis. This methodology can be transferred to farm culture conditions and be very useful for studying threatened species in order to preserve fish welfare.

Role of herbal medicines in the treatment of infectious diseases.

Herbal medicines have helped to cure illness because the practice has continued for generations. Multiple alkaloids/compounds that occur naturally (as against single extracts) exhibit synergistic actions such as antiviral, antibacterial, anti-protozoal, and antioxidant. The cases related to viral, protozoal, and bacterial infections were selected. Patients with amoebiasis, E-coli, gastrointestinal infection, skin and urinary tract infections were treated using herbal drugs. Diagnoses were confirmed with investigations. Due to their cost effectiveness, these medicines are in great demand for primary health care with cultural acceptability and minimal side effects. The aim of the reported study is to show the actual use of Indian medicinal plants used for the treatment of various types of infectious diseases. Cases varying from COVID 19 to gastrointestinal infection, viral diseases, skin and wound infections are being treated effectively with herbal drugs.

Lightweight single pass numerical reading extraction for displays in the wild

Although considerable progress has been made in recognizing multi-character text from images, there are still cases where there is a lack of robust computationally-efficient methods that can execute on portable devices to read device displays in the wild. We specifically address the problem of parsing digits from 7 segment displays. Recognizing these displays is important for many tasks such as assisting users with tasks using augmented reality agents that need to verify actions or connecting legacy devices to the internet for process control using cheap cameras. Legacy techniques based on image processing operators and OCR are brittle whereas massive deep networks are too computationally expensive. We describe a computationally tractable VGG style backbone combined with a novel digit inference head that can be trained using a synthetic display generator with novel augmentations. We show the model trained on augmented synthetic data generalizes well to a corpus of real-world display images getting 97.8% single-frame accuracy and obtaining a throughput of 30 frames per second. We describe how the output can be further stabilized to improve accuracy through a kind of mode filtering.

One-step preparation of deep eutectic solvents/ reduced graphene oxide composite materials for the removal of dibenzothiophene in fuel oil

Deep eutectic solvents (DES)/reduced graphene oxide (rGO) composite materials can remove dibenzothiophene (DBT) from fuel oil by adsorption desulfurization. However, the whole synthesis process is complicated, and the DES/rGO is high-cost and not strong enough, which limits its application in industry. Therefore, a one-step method to produce DES/rGO composite materials is proposed. The performance of desulfurization was studied and the feasibility of industrial application was analyzed. First, the proposed method can improve the single extraction efficiency to 94.8% without a complicated process. Secondly, the DES/rGO can also be reused and recycled. Third, the proposed method overcomes the inconvenient storage and transportation of liquid DES. Finally, the proposed method could effectively reduce the cost of desulphurization in the industry.

Photovoltaic single diode model parameter extraction by dI/dV-assisted deterministic method

In this work, a state-of-the-art deterministic method is proposed for photovoltaic single diode model parameter extraction from experimental current–voltage (I-V) curves. This new method takes advantage of the numerical derivative (dI/dV) information, such that a high-quality solution can be obtained by linear least squares technique. The solution can be further improved through a two-step nonlinear optimization procedure using the trust-region-reflective or Levenberg-Marquardt algorithm. Compared with previous methods, the proposed method has achieved the best accuracy with the lowest computation cost up till now in the benchmark test of two commonly-used case studies. When comparing the computation costs of different works, it is pointed out for the first time that not only the number of iteration steps but also the single-step computation complexity should be taken into account if different deterministic optimization algorithms are implemented. Furthermore, the robustness of the proposed method is verified through a large-scale dataset containing more than one million I-V curves, showing that the method can be used for realtime monitoring of photovoltaic modules. Finally, a MATLAB app is developed and freely provided to the public.

Study on Gas Migration Mechanism and Multi-Borehole Spacing Optimization in Coal under Negative Pressure Extraction

In order to study the gas migration in gas-bearing coal, and reasonably arrange gas drainage boreholes to improve the efficiency of gas drainage, a gas-solid coupling model is established based on the pore-fracture dual medium porous model. The solid deformation of coal body, gas seepage and diffusion, and gas adsorption and desorption are considered in this model. The COMSOL software is used to simulate the gas change in the coal matrix and coal fracture under single borehole extraction. We analyze the effective extraction range and study the migration mechanism of gas between coal fracture and borehole, coal matrix and coal fracture, and coal matrix. The effective extraction area of multi-borehole negative pressure gas extraction varies with extraction time and borehole spacing. At 140 d, the effective extraction radius is r = 1.3 m, and the spacing of boreholes is 233 r=1.5 m, 2 r=2.6 m,4 m,5 m,and 6 m, respectively. The influence of the equilateral triangle shape of three boreholes on the gas extraction effect is studied. The simulation results show that when three boreholes are extracted for 140 days under different borehole spacing, different gas extraction effects will be affected by a superposition effect. Considering the change in gas pressure, the effect of gas extraction in the effective extraction area, and the safety and cost performance of gas extraction, it is concluded that the optimal hole spacing is 5 m around 140 d. This study aims to provide reference for underground gas drilling layout and reasonable hole spacing.

The role of microtubules in microalgae: promotion of lipid accumulation and extraction

BackgroundMicrotubules in cells are closely related to the growth and metabolism of microalgae. To date, the study of microalgal microtubules has mainly concentrated on revealing the relationship between microtubule depolymerization and synthesis of precursors for flagellar regeneration. While information on the link between microtubule depolymerization and biosynthesis of precursors for complex organic matter (such as lipid, carbohydrate and protein), is still lacking, a better understanding of this could help to achieve a breakthrough in lipid regulation. With the aim of testing the assumption that microtubule disruption could regulate carbon precursors and redirect carbon flow to promote lipid accumulation, Chlorella sorokiniana SDEC-18 was pretreated with different concentrations of oryzalin.ResultsStrikingly, microalgae that were pretreated with 1.5 mM oryzalin accumulated lipid contents of 41.06%, which was attributed to carbon redistribution induced by microtubule destruction. To promote the growth of microalgae, two-stage cultivation involving microtubule destruction was employed, which resulted in the lipid productivity being 1.44 times higher than that for microalgae with routine single-stage cultivation, as well as yielding a desirable biodiesel quality following from increases in monounsaturated fatty acid (MUFA) content. Furthermore, full extraction of lipid was achieved after only a single extraction step, because microtubule destruction caused removal of cellulose synthase and thereby blocked cellulose biosynthesis.ConclusionsThis study provides an important advance towards observation of microtubules in microalgae through immunocolloidal gold techniques combined with TEM. Moreover, the observation of efficient lipid accumulation and increased cell fragility engendered by microtubule destruction has expanded our knowledge of metabolic regulation by microtubules. Finally, two-stage cultivation involving microtubule destruction has established ideal growth, coupling enhanced lipid accumulation and efficient oil extraction; thus gaining advances in both applied and fundamental research in algal biodiesel production.

Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System.

The game of Jenga is a benchmark used for developing innovative manipulation solutions for complex tasks. Indeed, it encourages the study of novel robotics methods to successfully extract blocks from a tower. A Jenga game involves many traits of complex industrial and surgical manipulation tasks, requiring a multi-step strategy, the combination of visual and tactile data, and the highly precise motion of a robotic arm to perform a single block extraction. In this work, we propose a novel, cost-effective architecture for playing Jenga with e.Do, a 6DOF anthropomorphic manipulator manufactured by Comau, a standard depth camera, and an inexpensive monodirectional force sensor. Our solution focuses on a visual-based control strategy to accurately align the end-effector with the desired block, enabling block extraction by pushing. To this aim, we trained an instance segmentation deep learning model on a synthetic custom dataset to segment each piece of the Jenga tower, allowing for visual tracking of the desired block's pose during the motion of the manipulator. We integrated the visual-based strategy with a 1D force sensor to detect whether the block could be safely removed by identifying a force threshold value. Our experimentation shows that our low-cost solution allows e.DO to precisely reach removable blocks and perform up to 14 consecutive extractions in a row.

STUDY OF REACTION OF NICKEL (II) WITH 2.4-TYAZOLIDINDYON COMPLEX AND ITS DERIVATIVES

Spectrophotometric methods are used to study the reaction of the nickel complex with 2.4- tyazolidindico (L) and its derivatives {5- (gasilysiliden) -2,4-tyazolidindio (L1), 5- (2-chlorbenzyliden) -2,4- tyazolidindion (L2), 5-(2-hydroxybenzylide) -2,4-tiazoleader (L3), 5- (4-hydroxybenzylide)-2,4- tyazolidindion(L4),5-(2-Brom-5-methoxybenzyiliden)-2,4-tiazolyidinedion (L5). With a single extraction, the chloroform is extracted by 97.8-98.4 % of the nickel. The study of the dependence of complexation on pH showed that the optimal range of acidity, at which the optical density is maximum and constant, is at pH 2.3- 8.0. The optimal condition for the formation and extraction of the nickel complex of these compounds is (2.0- 2.5) × 10-4 M concentration L. Nickel complexes with L are stable in water and organic solvents and do not decompose for three days, and after extraction for more than a month. The maximum optical density is achieved within 5 minutes. The maximum analytical signal during the complex of nickel L is observed at 470-482 nm/ molar absorption coefficients (1.37-1.61)×104 . The comprehensive form of nickel is Ni2+while the number of protons supplanted by it from one molecule L turned out to be equal to 1. Nickel and its complexes in the organic phase are not polymerized and are in a monomeric form (γ = 1.01-1.07). The proposed method under already established optimal conditions is used to determine Ni (II) in wastewater, bottom deposits, as well as in oil and oil products.

Super-resolution reconstruction of binocular image based on multi-level fusion attention network

Super-resolution reconstruction of binocular image based on multi-level fusion attention network

Adaptive single tree extraction method based on fusion of airborne lidar and vegetation index

Adaptive single tree extraction method based on fusion of airborne lidar and vegetation index

Frequency and etiological denominators of alveolar osteitis at Northern Province of Kingdom of Saudi Arabia-An observational study.

Alveolar osteitis is a painful complication that often arises after tooth extraction, presenting a significant clinical challenge. It is imperative to gain a comprehensive understanding of both its occurrence and the contributing factors to enhance the quality of dental care. The aim of this study was to assess the frequency and prevalence of alveolar osteitis among patients and compare these variables based on demographic characteristics (age and sex), the number of teeth extractions, operator experience, health status, and smoking habits in the target population. This cross-sectional observational study was conducted from May 2019 to April 2020. It included all patients above 16 years of age, of both genders, who underwent permanent tooth extraction for various reasons. Patient demographics, smoking habits, health status, operating dental surgeon's clinical experience, extraction technique, and the number of teeth extracted were recorded. Statistical analysis was performed using SPSS version 25. Chi-square test and regression analysis were used to assess differences between age, sex, smoking habit, dentist category, and the number of teeth extractions in relation to alveolar osteitis. A total of 679 permanent tooth extractions were performed in 438 patients. Alveolar osteitis was observed in 107 cases (15.7%) following tooth extractions. Among these, 36 cases (33.6%) occurred in single tooth extraction cases, while 71 cases (66.4%) were present in patients with multiple extractions. Moreover, 67 cases (62.6%) of alveolar osteitis were found in cigarette smokers. In addition, 61 cases (57%) of dry sockets were reported after tooth extractions performed by dental interns, while 46 cases (43.0%) were noted in extractions performed by experienced dental surgeons and specialists. The study found a 15.7% incidence of alveolar osteitis in tooth extraction patients in the Al-Jouf region. Alveolar osteitis was more prevalent in males and the age group of 56-77 years. Multiple tooth extractions were associated with higher alveolar osteitis incidence, while operator inexperience increased post-extraction complication risks. In addition, a promising novel protocol and risk assessment scoring system have been devised which require further validation and future research.

Endmember Bundle Extraction Based on Improved Multiobjective Particle Swarm Optimization

Endmember extraction (EE) is a key task for hyperspectral image unmixing. The majority of EE algorithms extract only one pure spectrum for each class of material, which may lead to a large unmixing error in cases of spectral variability. Endmember bundle extraction (EBE), which identifies a set of endmembers representing the spectral variability within each class, has been developed to solve the spectral variability problem. To date, only a small number of EBE methods have been developed; moreover, these approaches mainly employ traditional convex-geometry-based EE methods to extract endmember bundles from subset data, which may result in the loss of some endmembers and an incomplete endmember bundle set. This paper proposes an improved multi-objective particle swarm optimization method for the identification of multiple endmember bundles, named IMPSO-EBE. The proposed approach follows the framework of the spatial-spectral EBE (SSEBE) method, which extracts endmember candidates first and then applies post-processing to remove redundant endmembers. However, unlike the SSEBE method, which uses the traditional pixel purity index (PPI) method to obtain candidate endmembers from single feature space, IMPSO-EBE proposes to cooperate across multiple dataspaces to obtain candidate endmembers based on multi-objective particle swarm optimization, making it able to extract candidate endmembers that cannot be identified in single feature space. We compare the performance of the proposed method with that of the single dataspace-based endmember bundle extraction methods using two real hyperspectral datasets. Results show that the endmember bundles identified by the proposed method are more complete than those of the comparison method.

Phytochemical Analyses, Glucose Stimulatory Effects and Cytotoxicity of Cassia abbreviata and Helinus integrifolius Leaf Extracts in in vitro Cell Cultures

Numerous phytochemical constituents are found in plants and have been used either as single entities or extracts to treat various ailments. This study investigated the extracts of Cassia abbreviata and Helinus integrifolius in vitro for phytochemicals and its effect on glucose utilization of C2C12 muscle and H-4-II-E liver cells and for cytotoxicity against raw 264.7 cells using the real-time xCelligence system method. The ethyl acetate and acetone extracts of phenolic rich C. abbreviata stimulated greater C2C12 muscle cells glucose utilization at concentrations of 0.065 mg/mL and 0.125 mg/mL and acetone extract of C. abbreviata enhanced a concentration dependent H-4-II-E cells glucose utilization. For cytotoxicity, all extracts in concentration dependent manner decreased the viability of the raw 264.7 cells in real time assay with concentrations of 0.05 mg/mL the least cytotoxic. The extracts of C. abbreviata in in vitro assay demonstrated glucose stimulatory potential but further investigation of the cytotoxicity is required.

Efficient separation of aristolochic acid I from Caulis aristolochiae manshuriensis (Guan-mu-tong) with copper mediated magnetic molecularly imprinted polymer.

Screening bioactive compounds from natural products is one of the most effective ways for new drug research and development. However, obtaining a single extract component on a large scale and with high purity from a complex matrix is still an arduous and challenging task. Herein, one metal mediated magnetic molecularly imprinted polymer (mMIP) was rationally designed and prepared for specifically capturing Aristolochic acid I (AAI). The preparation was done with copper(II) as binding pivot, (3-aminopropyl) triethoxysilane as functional monomer, and Fe3O4 as core, by a one-step sol-gel method. Under the optimized conditions, the apparent maximum binding amount of copper mediated mMIP (Cu-mMIP) reaches as high as 349.72 mg g-1, the highest among the reported AAI-MIPs. Moreover, the nanoparticles exhibit excellent specificity and selectivity, good reproducibility and stability, high superparamagnetism (60.32 emu g-1), and high imprinting efficiency (an imprinting factor of 7). By simulating an industrial-scale separation, 16.56 mg AAI (purity of 95.11%) is obtained after six cycles with 100 mg nanoparticles from 20 g Caulis aristolochiae manshuriensis (Guan-mu-tong). Notably, this takes only 3 hours and consumes 50 mL of methanol. The study provides a potent tool for the green, fast, and specific extraction of high-purity ingredients from natural plants in the manufacturing industry and conventional analysis in the lab.