Extraction Method Research Articles

Extraction methods comparison and optimization for isoorientin and isovitexin from Thai jasmine rice leaves

Extraction methods comparison and optimization for isoorientin and isovitexin from Thai jasmine rice leaves

Development of an Enhanced Method for Copper Extraction from Sulfuric Acid Solutions

Development of an Enhanced Method for Copper Extraction from Sulfuric Acid Solutions

Micro‐motion parameters extraction of rotating target based on analytical solution in vortex electromagnetic wave radar

AbstractThe linear Doppler effect and angular Doppler effect in vortex electromagnetic wave radar echoes can be used to extract comprehensive micro‐motion parameters. However, the analytical solution of micro‐motion parameters for rotating targets in vortex EM wave radar has not been obtained. To solve the above problems, the analytical solution of micro‐motion parameters is derived, and a micro‐motion parameter extraction method is proposed. Firstly, the shape and properties of the angular Doppler curve in various cases are discussed. Subsequently, the properties of three points on the angular Doppler curve are derived. The micro‐motion parameters are obtained based on the three points. The simulations demonstrate that the proposed method can greatly reduce the computational complexity and improve the accuracy of micro‐motion parameter extraction.

A 3D Vision-Based Weld Seam Extraction Method for Arbitrarily Placed Spatial Planar Weldments

A 3D Vision-Based Weld Seam Extraction Method for Arbitrarily Placed Spatial Planar Weldments

Rapid detection of Impatiens necrotic spot virus from thrips vectors using reverse transcription-recombinase polymerase amplification

The plant virus, Impatiens necrotic spot virus (INSV), is an economically important pathogen of vegetables, fruits, and ornamental crops. INSV is vectored by the western flower thrips, Frankliniella occidentalis, a small insect pest that is globally distributed. In recent years, INSV outbreaks have reached epidemic levels in the Salinas Valley of California—an agriculturally rich region where most of the lettuce (Lactuca sativa) is produced in the United States. Due to the obligate nature in which virus transmission occurs, new tools that could rapidly detect INSV from thrips vectors would enhance our ability to predict where virus outbreaks may occur. Here, we report on the development of a reverse transcription-recombinase polymerase amplification (RT-RPA) assay that can detect INSV from individual thrips. The assay uses crude extraction methods, is performed at a single temperature of 42 °C, can be completed in 25 min, and provides sensitivity levels that are comparable to other available detection methods. When the assay was used on field populations of thrips, INSV was successfully identified and quantified from individual larvae and adults. The work provides a new cost-effective surveillance tool that can rapidly detect INSV from its insect vector and from plants.

A line scanning monitoring method for conveyor belt deviation using point cloud

Abstract A precise conveyor belt deviation monitoring method using line array point cloud data is proposed and demonstrated, which can ensure the healthy running of the conveyor system. The point cloud data characterizing the surface of the conveyor belt is collected in a line scanning way. Then, using a unique soft extraction method that weighted fusing three key features (cross-sectional variation, belt’s horizontal width, and previous frame) to process this data, the edge information of the conveyor belt can be accurately and robustly identified in real-time. Furthermore, the point cloud processing mode enables a belt-segmented deviation analysis method based on a standard sequence query. This can accurately determine the offset value and deviation trend of the conveyor belt, thereby achieving early warning of deviation faults. Experimental results show that the belt edge identification precision can reach 0.3 mm, and an early warning can be provided at least 57 m before the occurrence of a belt deviation fault. This belt deviation monitoring method can be widely applied in various working environments, especially in harsh conditions like mines and ports. It also has potential applications in automated production lines within Industry 4.0.

Application of MALDI-TOF mass spectrometry for identification of Nocardia species

BackgroundNocardiosis, despite its rarity and underreporting, is significant due to its severe impact, characterized by high morbidity and mortality rates. The development of a precise, reliable, rapid, and straightforward technique for identifying the pathogenic agent in clinical specimens is crucial to reduce fatality rates and facilitate timely antimicrobial treatment. In this study, we aimed to identify Nocardia spp. in clinical isolates, using MALDI-TOF MS as the primary method, with molecular methods as the gold standard. Clinical Nocardia isolates were identified using 16S rRNA/hsp65/gyrB/secA1/rpoB gene sequencing. Identification performance of the Bruker MALDI Biotyper 3.1 (V09.0.0.0_8468) and MBT Compass 4.1 (V11.0.0.0_10833) for Nocardia identification was evaluated.ResultsSeventy-six Nocardia isolates were classified into 12 species through gene sequencing. The MALDI Biotyper 3.1 (V09.0.0.0_8468) achieved 100% genus-level accuracy and 84.2% species accuracy (64/76). The MBT Compass 4.1 with the BDAL Database (V11.0.0.0_10833) improved species identification to 98.7% (75/76). The updated database enhanced species level identification with scores > 1.7, increasing from 77.6% (59/76) to 94.7% (72/76), a significant improvement (P = 0.001). The new and simplified extraction increased the proportion of strains identified to the species level with scores > 1.7 from 62.0% (18/29) to 86.2% (25/29) (P = 0.016). An in-house library construction ensured accurate species identification for all isolates.ConclusionsThe Bruker mass spectrometer can accurately identify Nocardia species, albeit with some variations observed between different database versions. The MALDI Biotyper 3.1 (V09.0.0.0_8468) has limitations in identifying Nocardia brasiliensis, with some strains only identifiable to the genus level. MBT Compass 4.1 (V11.0.0.0_10833) effectively addresses this shortfall, improving species identification accuracy to 98.7%, and offering quick and reliable identification of Nocardia. Both database versions incorrectly identified the clinically less common Nocardia sputorum as Nocardia araoensis. For laboratories that have not upgraded their databases and are unable to achieve satisfactory identification results for Nocardia, employing the new and simplified extraction method can provide a degree of improvement in identification outcomes.

A Comparative Analysis of Flavonoid and Phenolic concentration from Diverse Varieties of Moringa oleifera Leaves Utilizing Methanol and Ethanol

Having its leaves abundant in nutrients such as vitamins and minerals, the moringa plant is highly regarded because of its nutritious and industrial usefulness. Despite its widespread utilisation, little is understood concerning the way various Moringa oleifera cultivars vary with regard to their phenolic and flavonoid concentration, particularly when extracting the compound utilising various solvents. To attempt to throw insight into the ways that various solvent types and environment variables affects the phytochemical compounds of Moringa oleifera leaves, this research investigation compared the efficacy of ethanol and methanol in removing phenolics as well as flavonoids from the leaves. The information gathered through this research could assist to identify the most appropriate methods for extraction that will maximize the medical and nutritional advantages associated with Moringa oleifera. New leaves of five different types of Moringa oleifera had been bought from the Winfred Thomas Agricultural Research Station in Alabama A&M University. Upon being pulverised and dried, the resulting leaves had been preserved at room temperature. The leaves were immersed in a mixture of 70% ethanol as the solvent and 80% methanol all through the extraction method. The extracted samples had been then stirred, filtered, and freeze-dried. Following that, High-performance liquid chromatography was the technique employed to know the overall concentration of phenolic and flavonoid compounds. Descriptive and statistical analysis were performed using box plots, scatter plots, bar plots, and t-tests to evaluate the extent or degree to which both solvents removed phenolic and flavonoid compounds and estimated the total quantity of phenolic and flavonoids in the different cultivars. The findings from the descriptive study revealed the Nigerian variety had an increased phenolic content when extracted using methanol—roughly 822.3 µg/ml—than when removed using ethanol (80.6 µg/ml). The Indian type, on the contrary, had phenolic concentrations of 814.3 µg/ml as compared with 647.3 µg/ml in ethanol, revealing an important distinction in preference for methanol. The Nigerian cultivar possessed an increased extraction effectiveness of 1253.12 µg/ml using ethanol as opposed to methanol (1083.52 µg/ml) for flavonoids. The t-test results proved that though the difference was not statistically significant (t(28) = 0.608, p = 0.382), the average phenolic content obtained with methanol (M = 798.60, SD = 23.567) was slightly more than that obtained via ethanol (M = 790.60, SD = 45.183). In a similar vein extraction with methanol showed a smaller average flavonoid concentration (M = 1068.40, SD = 128.641) compared to the extraction with ethanol (M = 1129.40, SD = 166.018); nonetheless, this difference was not statistically significant (t(28) = 1.125, p = 0.334). The scatter diagram revealed a significant linear connection with both phenolic and flavonoid content, having a significant positive correlation (Pearson correlation coefficient = 0.95). Although some modifications depending on the variety, the research reveals that methanol and ethanol serve as suitable solvents for phenolic and flavonoid compound extraction from Moringa oleifera leaves. The usefulness of these developments in enhancing methods of extraction in manufacturing industries needs to be explored deeper.

Bioavailability of Acemanan: An Active Compound Found in Aloe Gel

Acemannan is said to be the biologically active substance in aloe vera (Aloe barbadensis). Many producers of aloe products utilize inadequate production and extraction methods, resulting in aloe products that contain little or no acemannan. This article outlines a systematic procedure for extracting the bioactive polysaccharide compound from the aloe plant. This paper also provides a description of the physical distinctive features of acemannan. The study also emphasized the determination of physical properties, such as the pKa and Log P values, of acemannan. The physical characteristics were used to evaluate the bioavailability and hydrophilicity of this chemical. The primary approach used to acquire these physical characteristics involves the extraction of acemannan from aloe vera, the creation of phosphate buffer with varying pH levels, the separation of acemannan between chloroform and buffer using the shake flask technique, and the utilization of spectrophotometric analysis. Chloroform was used as a representation of the lipid membrane in the experiment, whereas phosphate buffer was utilized to symbolize the blood. A buffer solution was used to maintain a steady pH at a desired value. The acemannan compound had a pKa value of 4.82 at a pH of 3.45, indicating its acidity. Additionally, the Log P value (chloroform/buffer) was determined to be -3.282, indicating its hydrophobicity. Thus, it was deduced that acemannan exhibited hydrophilic properties throughout the gastrointestinal system.

Development and Evaluation of Oromucosal Spray Formulation Containing Plant-Derived Compounds for the Treatment of Infectious and Inflammatory Diseases of the Oral Cavity

According to data in the literature, natural products and essential oils are often used in dental practice. To develop a new oromucosal spray for the treatment of infectious and inflammatory diseases of the oral cavity, clove CO2 extract and essential oils of lavender and grapefruit were used as active pharmaceutical ingredients. Clove extract was obtained by the method of subcritical extraction from various raw materials, the choice of which was based on the yield of the CO2 extract and the study of its phytochemical and microbiological properties. Based on the results of microscopic and diffraction analyses, the rational time of ultrasonic exposure for the emulsion of active pharmaceutical ingredients was established. Mucoadhesive polymers were used as stabilizers of the two-phase system and prolongators. This article discusses the impact of the type and concentration of mucoadhesive polymers on the stability of the emulsion system; the viscous, textural, adhesive, and film characteristics of oromucosal spray; and the parameters determining sprayability.

EMFSA: Emoji-based multifeature fusion sentiment analysis

Short texts on social platforms often suffer from insufficient emotional semantic expressions, sparse features, and polysemy. To enhance the accuracy achieved by sentiment analysis for short texts, this paper proposes an emoji-based multifeature fusion sentiment analysis model (EMFSA). The model mines the sentiments of emojis, topics, and text features. Initially, a pretraining method for feature extraction is employed to enhance the semantic expressions of emotions in text by extracting contextual semantic information from emojis. Following this, a sentiment- and emoji-masked language model is designed to prioritize the masking of emojis and words with implicit sentiments, focusing on learning the emotional semantics contained in text. Additionally, we proposed a multifeature fusion method based on a cross-attention mechanism by determining the importance of each word in a text from a topic perspective. Next, this method is integrated with the original semantic information of emojis and the enhanced text features, attaining improved sentiment representation accuracy for short texts. Comparative experiments conducted with the state-of-the-art baseline methods on three public datasets demonstrate that the proposed model achieves accuracy improvements of 2.3%, 10.9%, and 2.7%, respectively, validating its effectiveness.

Evaluation of Exchangeable Potassium Concentration in Sri Lankan Rice Paddy Soils with ICP-MS Using CaCl2 Extraction

ABSTRACT With the advancement of analytical techniques, multi-element extraction and detection have been developed. Universal extractans like CaCl2 and detection technologies like inductively coupled plasma-mass spectrometry (ICP-MS) could facilitate simultaneous analysis of multiple-elements, and would be useful in commercial scale soil analytical laboratories. The type of extractant and detection method could influence the concentration of exchangeable potassium (ex-K) determined in different soils. This study evaluated the effectiveness of 0.01 M CaCl2 as a multi-element extractant (CC) and ICP-MS and flame photometry (FP) as detection technologies when determining ex-K in soils. The widely used protocol for Sri Lankan soils, i.e. 1 M ammonium acetate (AA) as an extractant and FP as detection method, was used as the control for comparison of results. Altogether, 1,250 soil samples representing rice-growing regions in Sri Lanka were used. Soils were grouped under 16 categories based on soil type. Ex-K varied widely (26 to 1376 mg kg−1 from AA-FP method). Ex-K determined using three methods were in the order of AA-FP>CC-FP >CC-ICP-MS. On average, the values obtained from CC-FP and CC-ICP-MS methods were 53% and 24%, respectively, of those from AA-FP. Soil type-dependent variation in the detection of K using three methods was evident. In the 16 soil categories, coefficient of determination (R2) ranged from 0.23 to 0.86 for AA-FP and CC-ICP-MS, and from 0.05 to 0.70 for AA-FP and CC-FP. As a result, soil ex-K determined using CC-FP and CC-ICP-MS methods cannot be related to the results generated through AA-FP method across different soil types.

TTPXHunter: Actionable Threat Intelligence Extraction as TTPs from Finished Cyber Threat Reports

Understanding the modus operandi of adversaries aids organizations to employ efficient defensive strategies and share intelligence in the community. This knowledge is often present in unstructured natural language text within threat analysis reports. A translation tool is needed to interpret the modus operandi explained in the sentences of the threat report and convert it into a structured format. This research introduces a methodology named TTPXHunter for automated extraction of threat intelligence in terms of Tactics, Techniques, and Procedures (TTPs) from finished cyber threat reports. It leverages cyber domain-specific state-of-the-art natural language model to augment sentences for minority class TTPs and refine pinpointing the TTPs in threat analysis reports significantly. We create two datasets: an augmented sentence-TTP dataset of \(39,296\) sentence samples and a \(149\) real-world cyber threat intelligence report-to-TTP dataset. Further, we evaluate TTPXHunter on the augmented sentence and report datasets. The TTPXHunter achieves the highest performance of \(92.42\%\) f1-score on the augmented dataset, and it also outperforms existing state-of-the-art TTP extraction method by achieving an f1-score of \(97.09\%\) when evaluated over the report dataset. TTPXHunter significantly improves cybersecurity threat intelligence by offering quick, actionable insights into attacker behaviors. This advancement automates threat intelligence analysis and provides a crucial tool for cybersecurity professionals to combat cyber threats.

Research on the vibration load spectrum extraction method for electric drive assembly

Abstract It is vital to precisely extract the actual vibration load spectrum of the electric drive assembly since it is a crucial piece of fundamental load data for vibration testing and vibration fatigue performance development. A simulation iteration-based vibration load spectrum extraction method for electric drive assemblies is proposed by actually measuring the six-component load spectrum. Establishing the whole vehicle system dynamics model with the electric drive assembly as the research object. Based on this, the vertical displacement and five-part force of the four-wheel centers serve as input signals, while the vertical force of the four-wheel centers serves as output signals. An iterative system was set up, and the frequency response function was obtained. The excitation signals of the simulated iterative system are obtained by the simulated iterative algorithm and verified, with all relative errors within 5.0%. The vibration load spectrum at the corresponding position of the electric drive assembly was extracted under the excitation signal. The results indicate that the simulation iteration-based method for extracting the vibration load spectrum of the electric drive assembly can accurately simulate the loads on the electric drive assembly during actual vehicle operation. This proves the effectiveness of the method for extracting the vibration load spectrum of the electric drive assembly.

Comparison of Different DNA Sampling and Extraction Protocols for Bacterial and Archaeal Populations Analysis in Water Buffalo

Methane (CH4) is a potent greenhouse gas, and ruminants are a significant source of agricultural emissions. It has been hypothesized that the host's genome controls rumen microbial communities, but robust results require numerous samples. The feasibility of a research project will depend on the ease and representativeness of the sampling method, as well as the cost-efficiency of large-scale sequencing. This study aimed to compare different protocols to investigate whether non-invasive samples could serve as a substitute for ruminal digesta. DNA recovery was tested in various matrices (whole rumen content, feces, and buccal swabs) from five cannulated buffalo cows. Three types of buccal swabs were tested, as well as feces in different forms (as-is, pelleted, or in a glycerol solution) and the rumen content. The study compared different protocols for DNA extraction, including WUR protocol, Maxwell®, and Quick Extract™, and two sampling times. Saliva was a challenging matrix to process, obtaining unsatisfactory DNA yield. Feces showed higher yields when pelleted but lower than rumen. The highest amount of DNA was obtained from whole rumen content using all three DNA extraction methods. Quick Extract was the easiest method to perform, while WUR resulted in the highest yield of DNA, swabs excluded. The Maxwell® method gave satisfactory results with all three matrices. However, further metagenomic analysis is required to verify if the species composition is comparable.

Remote Exercise Engagement Among Individuals With Cardiovascular Disease

Purpose: To systematically review the literature regarding barriers and facilitators to remote exercise among individuals with cardiovascular diseases (CVD). Review Methods: Six databases were searched (inception—December 2023). Studies including barriers and facilitators for remote exercise reported by individuals living with CVD were considered. Quality was rated using the Mixed Methods Assessment Tool (MMAT). Results were synthesized following a thematic analysis approach. Characteristics of interventions were reported using the Template for Intervention Description and Replication (TIDieR). Summary: From an initial pool of 8543 records, 18 studies met the inclusion criteria. Among these, 13 were qualitative studies, with individual interviews being the most frequent data extraction method. Nine studies received 5/5 MMAT scores (ie, high quality). Twelve studies reported remote exercise interventions, mostly delivered within cardiac rehabilitation, by physiotherapists, nurses, and dietitians, predominantly via telephone calls or videoconferences, with only one study incorporating text messages. Five key themes influencing remote exercise interventions were identified: technology (encompassing access and literacy, self-monitoring/motivation, and security concerns), individual health considerations (health/personal aspects and coronavirus disease-2019), social factors (support from health care team and family/social support), environment (facilities), and logistical factors (time and displacement). Several themes served as both facilitators and barriers. Key insights for remote exercise interventions included mobile accessibility, interactive chat sessions, minimal click interactions, short sessions, personalized feedback, and flexible timing. Results emphasize the importance of promoting social interaction and support between participants and health care teams to mitigate barriers and enhance facilitators in remote exercise interventions for individuals with CVD.

A photovoltaic cell defect detection model capable of topological knowledge extraction

As the global transition towards clean energy accelerates, the demand for the widespread adoption of solar energy continues to rise. However, traditional object detection models prove inadequate for handling photovoltaic cell electroluminescence (EL) images, which are characterized by high levels of noise. To address this challenge, we developed an advanced defect detection model specifically designed for photovoltaic cells, which integrates topological knowledge extraction. Our approach begins with the introduction of a multi-scale dynamic context-based feature extraction method, capable of generating static context by thoroughly capturing the local texture and structural information of multi-scale defects. This static context is then combined with dynamic context to produce fine-grained local features. Subsequently, we developed a centralized feature pyramid structure, enhanced by spatial semantics, which models the explicit visual center. This structure effectively elucidates the relationship between local and global features in defect images, thereby improving the representation of defect characteristics. Finally, we implemented a feature enhancement strategy grounded in spatial semantic knowledge extraction. This strategy uncovers potential correlations among defect targets by constructing a spatial semantic topology of features, mapping these features to a higher-order representation, and ultimately delivering precise defect detection results.

Pectin from Agro-waste to Utility Product

The study aims to discuss innovative extraction approaches as compared to available traditional methods to optimize the yield and quality of pectin by eco-friendly techniques and emphasizes purification and analytical techniques for quality toward sustainable development of pectinbased products. Pectin is a complex polysaccharide present in plants, forming a protective barrier and providing mechanical strength to the plant cell. Therefore pectin, a by-product of the food industry, can be an efficient waste valorization product for utilization in the food and pharmaceutical industry as a thickener, stabilizer, and gelling agent. Pectin complex chemistry provides a wide scope for modification of monomers that can alter the properties of pectin and thereby add to the varied applications of pectin enlisted in the review. The review synthesizes findings from meticulously conducted research investigations and authorized scholarly articles. Information retrieval used reputable academic search engines, including PubMed, Elsevier, and Bentham publications with keywords such as “pectin” “chemical modification of pectin”, “drug delivery”, “green methods” and “agro-industrial residues" for a comprehensive exploration. The comprehensive review delves into pectin chemistry and extraction methods, modification, and characterization techniques are discussed along with versatile applications in the food, pharmaceutical, and other industries. Pectin abundantly present in the outer coat or peels of fruits and vegetables has been the best example of a circular economy and has led to zero waste in agricultural industries. The review has elaborated modifications in pectin for its use as an excipient in the pharmaceutical industry, therapeutic use, targeted drug delivery, and food industries.

Unveiling the Microplastics: Sources, Distribution, Toxicological Impacts, Extraction Methods, Degradational Strategies, Paving the Path to a Sustainable Future

Unveiling the Microplastics: Sources, Distribution, Toxicological Impacts, Extraction Methods, Degradational Strategies, Paving the Path to a Sustainable Future

Arabic Clustering Through Advanced Stemming and WordNet-Based Extraction for Water Cycle Cluster

Natural language processing represents human language in computational technique, which is to achieve the extraction of important words. The verbs and nouns found in the Arabic language are significantly pertinent in the process of differentiating each class label available for the purpose of machine learning, specifically in 'Arabic Clustering'. This paper implemented the extraction of verbs and nouns sourced from the Qur'an and text clustering for further evaluation by using two datasets. The limitations of conventional clusters were identified, such as k-means clustering on the initial centroids. Therefore, the current work incorporated a novel clustering optimisation technique known as the water cycle algorithm; when combined with k-means, the algorithm would select the optimal initial centroids. Consequently, the experiments revealed the proposed extraction technique to outperform other extraction methods when using an actual Qur'an dataset.