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This paper aims to critically review the isolation and chemistry of plant pigments.

A literature survey from 1974 to 2022 was carried out and studied thoroughly. The authors reviewed literature in various areas such as isolation methods and catalytic properties of pigments.

With vast growing research in the field of catalytic activities of various pigments like chlorophyll, anthocyanin and flavonoids, there is still scope for further research for the pigments such as Lycopene, carotenoids and xanthophyll as there has not been any significant work in this area.

Plant pigments may be used as an ecofriendly catalyst for chemical reactions.

One can get the direction of pigment research.

Plant pigments are natural and ecofriendly catalyst which can reduce the pollution.

This is an original work. This paper precisely depicts the advantages as well as disadvantages of the isolation techniques of pigments. This study also presents the chemistry of plant pigments.

The traditional vision system cannot automatically adjust the feature point extraction method according to the type of welding seam. In addition, the robot cannot self-correct the laying position error or machining error. To solve this problem, this paper aims to propose a hierarchical visual model to achieve automatic arc welding guidance.

The hierarchical visual model proposed in this paper is divided into two layers: welding seam classification layer and feature point extraction layer. In the welding seam classification layer, the SegNet network model is trained to identify the welding seam type, and the prediction mask is obtained to segment the corresponding point clouds. In the feature point extraction layer, the scanning path is determined by the point cloud obtained from the upper layer to correct laying position error. The feature points extraction method is automatically determined to correct machining error based on the type of welding seam. Furthermore, the corresponding specific method to extract the feature points for each type of welding seam is proposed. The proposed visual model is experimentally validated, and the feature points extraction results as well as seam tracking error are finally analyzed.

The experimental results show that the algorithm can well accomplish welding seam classification, feature points extraction and seam tracking with high precision. The prediction mask accuracy is above 90% for three types of welding seam. The proposed feature points extraction method for each type of welding seam can achieve sub-pixel feature extraction. For the three types of welding seam, the maximum seam tracking error is 0.33–0.41 mm, and the average seam tracking error is 0.11–0.22 mm.

The main innovation of this paper is that a hierarchical visual model for robotic arc welding is proposed, which is suitable for various types of welding seam. The proposed visual model well achieves welding seam classification, feature point extraction and error correction, which improves the automation level of robot welding.

Terminology is the set of technical words or expressions used in specific contexts, which denotes the core concept in a formal discipline and is usually applied in the fields of machine translation, information retrieval, information extraction and text categorization, etc. Bilingual terminology extraction plays an important role in the application of bilingual dictionary compilation, bilingual ontology construction, machine translation and cross‐language information retrieval etc. This paper aims to address the issues of monolingual terminology extraction and bilingual term alignment based on multi‐level termhood.

A method based on multi‐level termhood is proposed. The new method computes the termhood of the terminology candidate as well as the sentence that includes the terminology by the comparison of the corpus. Since terminologies and general words usually have different distribution in the corpus, termhood can also be used to constrain and enhance the performance of term alignment when aligning bilingual terms on the parallel corpus. In this paper, bilingual term alignment based on termhood constraints is presented.

Experimental results show multi‐level termhood can get better performance than the existing method for terminology extraction. If termhood is used as a constraining factor, the performance of bilingual term alignment can be improved.

The termhood of the candidate terminology and the sentence that includes the terminology is used for terminology extraction, which is called multi‐level termhood. Multi‐level termhood is computed by the comparison of the corpus. Bilingual term alignment method based on termhood constraint is put forward and termhood is used in the task of bilingual terminology extraction. Experimental results show that termhood constraints can improve the performance of terminology alignment to some extent.

Owing to the complex space environment and limited computing resources, traditional and deep learning-based methods cannot complete the task of satellite component contour extraction effectively. To this end, this paper aims to propose a high-quality real-time contour extraction method based on lightweight space mobile platforms.

A contour extraction method that combines two edge clues is proposed. First, Canny algorithm is improved to extract preliminary contours without inner edges from the depth images. Subsequently, a new type of edge pixel feature is designed based on surface normal. Finally, surface normal edges are extracted to supplement the integrity of the preliminary contours for contour extraction.

Extensive experiments show that this method can achieve a performance comparable to that of deep learning-based methods and can achieve a 36.5 FPS running rate on mobile processors. In addition, it exhibits better robustness under complex scenes.

The proposed method is expected to promote the deployment process of satellite component contour extraction tasks on lightweight space mobile platforms.

A pixel feature for edge detection is designed and combined with the improved Canny algorithm to achieve satellite component contour extraction. This study provides a new research idea for contour extraction and instance segmentation research.

The purpose of this study was to review the information on the scientific efforts and achievements in sustainable industrial textile applications of natural colourants. Then the paper suggests the ways of improving the industrial textile applications of plant-based colourants.

The literature on the chemistry, sources and extraction of plant-based natural colourants was reviewed. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested. Lastly, the current situation of industrial application of natural dyes in textiles is presented.

Despite the scientific achievement to overcome the challenges of natural colourants for textiles, the global industrial application of natural colourants is still low. Inadequate knowledge of the dyers results into poor performance of the natural dyed textile. The natural dyed textiles are expensive due to the scarcity of raw materials for manufacturing of natural colourants. The selection of suitable extraction, application methods and type of substrate should consider the chemistry of the particular colourant. The society should be educated about the benefits of natural dyed textiles. Cultivation of colourant-bearing plants should be promoted to meet the industrial material demand.

The paper provides a synthesized collection of information about the source, chemistry, extraction, textile application and challenges of plant-based natural colourants. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested.

This paper aims to perform an exhaustive revision of relevant and recent related studies, which reveals that both extraction methods are currently used to analyze credibility on Twitter. Thus, there is clear evidence of the need of having different options to extract different data for this purpose. Nevertheless, none of these studies perform a comparative evaluation of both extraction techniques. Moreover, the authors extend a previous comparison, which uses a recent developed framework that offers both alternates of data extraction and implements a previously proposed credibility model, by adding a qualitative evaluation and a Twitter-Application Programming Interface (API) performance analysis from different locations.

As one of the most popular social platforms, Twitter has been the focus of recent research aimed at analyzing the credibility of the shared information. To do so, several proposals use either Twitter API or Web scraping to extract the data to perform the analysis. Qualitative and quantitative evaluations are performed to discover the advantages and disadvantages of both extraction methods.

The study demonstrates the differences in terms of accuracy and efficiency of both extraction methods and gives relevance to much more problems related to this area to pursue true transparency and legitimacy of information on the Web.

Results report that some Twitter attributes cannot be retrieved by Web scraping. Both methods produce identical credibility values when a robust normalization process is applied to the text (i.e. tweet). Moreover, concerning the time performance, Web scraping is faster than Twitter API and it is more flexible in terms of obtaining data; however, Web scraping is very sensitive to website changes. Additionally, the response time of the Twitter API is proportional to the distance from the central server at San Francisco.

The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including materials science, as it is impossible to manually read and extract knowledge from millions of published literature. The purpose of this study is to address this challenge by exploring knowledge extraction in materials science, as applied to digital scholarship. An overriding goal is to help inform readers about the status knowledge extraction in materials science.

The authors conducted a two-part analysis, comparing knowledge extraction methods applied materials science scholarship, across a sample of 22 articles; followed by a comparison of HIVE-4-MAT, an ontology-based knowledge extraction and MatScholar, a named entity recognition (NER) application. This paper covers contextual background, and a review of three tiers of knowledge extraction (ontology-based, NER and relation extraction), followed by the research goals and approach.

The results indicate three key needs for researchers to consider for advancing knowledge extraction: the need for materials science focused corpora; the need for researchers to define the scope of the research being pursued, and the need to understand the tradeoffs among different knowledge extraction methods. This paper also points to future material science research potential with relation extraction and increased availability of ontologies.

To the best of the authors’ knowledge, there are very few studies examining knowledge extraction in materials science. This work makes an important contribution to this underexplored research area.

The purpose of this paper is to evaluate the antioxidant activity and toxicity of Clinacanthus nutans leaves from three conventional extraction methods, i.e. maceration, Soxhlet and magnetic stirring.

Total flavonoid content (TFC) and phenolic content (TPC) were determined using colorimetric method of aluminum chloride and Folin-Ciocalteu (FC) assay, respectively. Antioxidant property of C. nutans was evaluated using 2,2'-diphenyl-1-pierylhydrazyl (DPPH) free radical scavenging assay. Cytotoxic activity of C. nutans against brine shrimp was evaluated based on LC50 (lethality concentration) after 24 h exposure to the plant extract.

The highest TPC of C. nutans was observed with Soxhlet extraction method (98.87 ± 10.43 mg of gallic acid equivalents (GAE/g) followed by maceration (68.77 ± 2.45 mg of GAE/g) and magnetic stirring (46.75 ± 2.45 mg of GAE/g). Interestingly, remarkable highest TFC was observed with magnetic stirring (568.90 ± 4.85 mg of rutin equivalent (RE)/g) followed by maceration (249.60 ± 2.79 mg of RE/g) and Soxhlet (174.8 ± 1.74 mg of RE/g). On the other hands, the extract obtained using maceration method showed the highest antioxidant activity (IC50: 14.18 mg/mL compared to ascorbic acid 144.36 µg/mL). Cytotoxicity of C. nutans from all extraction methods showed similar LC50 values with maceration (3.81 mg/mL), Soxhlet (2.61 mg/mL) and magnetic stirring (4.56 mg/mL), respectively.

Both phenolic and flavonoids are responsible for the antioxidant activity, of C. nutans extracts. Based on Meyer's toxicity index, all extracts were nontoxic (LC50>1 mg/mL).

This paper aims to review the chemical composition and industrial benefits of oil extracted from dikanut kernels.

Several literatures on chemical composition of dikanut kernels, methods of oil extraction from dikanut kernels and chemical composition of oil extracted from dikanut kernels were critically reviewed.

The review showed that proximate composition of dikanut kernels ranged from 2.10 to 11.90 per cent, 7.70 to 9.24 per cent, 51.32 to 70.80 per cent, 0.86 to 10.23 per cent, 2.26 to 6.80 per cent and 10.72 to 26.02 per cent for moisture, crude protein, crude fat, crude fibre, ash and carbohydrate contents, respectively. The methods of oil extraction from dikanut kernels include soxhlet extraction method, novel extraction method, enzymatic extraction method and pressing method. The quality attributes of dikanut kernel oil ranged from 1.59 to 4.70 g/100g, 0.50 to 2.67 meq/Kg, 4.30 to 13.40 g/100g, 187.90 to 256.50 mg KOH/g and 3.18 to 12.94 mg KOH/g for free fatty acid, peroxide value, iodine value, saponification value and acid value, respectively. Also, the percentage compositions of oleic, myristic, stearic, linolenic, palmitic, lauric, saturated fatty acids, monosaturated fatty acids and polyunsaturated fatty acids ranging from 0.00 to 6.90, 20.50 to 61.68, 0.80 to 11.40, 0.27 to 6.40, 5.06 to 10.30, 27.63 to 40.70, 97.45 to 98.73, 1.82 to 2.12 and 0.27 to 0.49 respectively. The results showed that dikanut kernels has appreciable amount of protein, carbohydrate and high level of fat content while oil extracted from dikanut kernels have high saponification value, high myristic acid and high lauric acid.

There are scanty information/published works on industrial products made from oil extracted from dikanut kernels.

The review helps in identifying different methods of extraction of oil from dikanut kernels apart from popular soxhlet extraction method (uses of organic solvent). Also, it helps to identify the domestic and industrial benefits of oil extracted from dikanut kernels.

The review showed that oil extracted from dikanut kernels could be useful as food additive, flavour ingredient, coating fresh citrus fruits and in the manufacture of margarine, oil creams, cooking oil, defoaming agent, cosmetics and pharmaceutical products.

Everyone is extremely concerned about environmental protection and health safety due to the rise in living standards. Plant-derived natural dyes have garnered much industrial attention in food, pharmaceutical, textile, cosmetics, etc. owing to their health and environmental benefits. The present study aims to focus on the elimination of the use of synthetic dyes and provides brief information about natural dyes, their sources, extraction procedures with characterization and various advantages and disadvantages.

In producing natural colors, extraction and purification are essential steps. Various conventional methods used till date have a low yield, as these consume a lot of solvent volume, time, labor and energy or may destroy the coloring behavior of the actual molecules. The establishment of proper characterization and certification protocols for natural dyes would improve the yielding of natural dyes and benefit both producers and users.

However, scientists have found modern extraction methods to obtain maximum color yield. They are also modifying the fabric surface to appraise its uptake behavior of color. Various extraction techniques such as solvent, aqueous, enzymatic and fermentation and extraction with microwave or ultrasonic energy, supercritical fluid extraction and alkaline or acid extraction are currently available for these natural dyes and are summarized in the present review article.

If natural dye availability can be increased by the different extraction measures and the cost of purified dyes can be brought down with a proper certification mechanism, there is a wide scope for the adoption of these dyes by small-scale dyeing units.