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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.

This paper aims to consider the potential implications of the layering of regulation in relation to hydraulic fracturing (fracking) at the borders between the nations of the UK.

This paper uses a qualitative research method grounded in particular in legal geography to examine the existing approaches to regulating hydraulic fracturing and identify the places and their features that are constructed as a result of their intersection at the borders of the nations comprising the UK.

The current regulatory framework concerning hydraulic fracturing risks restricts the places in which the practice can occur in such a manner as to potentially cause greater environmental harm should the process be used. The regulations governing the process are not aligned in relation to the surface and subsurface aspects of the process to enable their management, once operational, as a singularly constructed place of extraction. Strong regulation at the surface can have the effect of influencing placement of the site only in relation to the place at which the resource sought reaches the surface, whilst having little to no impact on the environmental harms, which will result at the subsurface or relative to other potential surface site positions, and potentially even increasing them.

This paper is limited by uncertainty as to the future use of hydraulic fracturing to extract oil and gas within the UK. The issues raised within it would also be applicable to other extractive industries where a surface site might be placed within a radius of the subsurface point of extraction, rather than having to be located at a fixed point relative to that in the subsurface. This paper therefore raises concerns that might be explored more generally in relation to the regulation of the place of resource extraction, particularly at legal borders between jurisdictions, and the impact of regulation, which does not account for the misalignment of regulation of spaces above and below the surface that form a single place at which extraction occurs.

This paper considers the potential impacts of misaligned positions held by nations in the UK in relation to environmentally harmful practices undertaken by extractive industries, which are highlighted by an analysis of the extant regulatory framework for hydraulic fracturing.

Whilst the potential for cross internal border extraction of gas within the UK via hydraulic fracturing and the regulatory consequences of this has been highlighted in academic literature, this paper examines the implications of regulation for the least environmentally harmful placement of the process.

In order to improve the computation efficiency of the four-point rainflow algorithm, a new fast four-point rainflow cycle counting algorithm (FFRA) using a novel loop iteration mode is proposed.

In this new algorithm, the loop iteration mode is simplified by reducing the number of iterations, tests and deletions. The high efficiency of the new algorithm makes it a preferable candidate in fatigue life online estimation of structural health monitoring systems.

The extensive simulation results show that the extracted cycles by the new FFRA are the same as those by the four-point rainflow cycle counting algorithm (FRA) and the three-point rainflow cycle counting algorithm (TRA). Especially, the simulation results indicate that the computation efficiency of the FFRA has improved an average of 12.4 times compared to the FRA and an average of 8.9 times compared to the TRA. Moreover, the equivalence of cycle extraction results between the FFRA and the FRA is proved mathematically by utilizing some fundamental properties of the rainflow algorithm. Theoretical proof of the efficiency improvement of the FFRA in comparison to the FRA is also given.

This merit makes the FFRA preferable in online monitoring systems of structures where fatigue life estimation needs to be accomplished online based on massive measured data. It is noticeable that the high efficiency of the FFRA attributed to the simple loop iteration, which provides beneficial guidance to improve the efficiency of existing algorithms.

This research paper takes a narrow approach to examining the apparent link between poverty and the resource extraction industries. However, it acknowledges that much more is to be explored about this relationship. Many complexities influence the occurrence and degree of poverty in a particular country, region, or community.

The literature review identified proposed and operational poverty reduction actions and processes categorized under the broad concept of community development projects. The surveyed cases describe how various corporate strategies, work processes, labor requirements and efficient management and governance solutions are purported to improve poverty-reduction efforts potentially.

No causal linkages between poverty and hypothetically valuable and successful community development projects were found. No poverty monitoring evaluations and learning data (MEL) for these projects were proposed and published in most of the literature. However, associations were observed between some business practices implemented in these resource extraction community development projects and observations of indicators of lower poverty levels.

The research improves our understanding of the requirements and opportunities for successful community development projects by highlighting processes, company strategy, human resource programs and enlightened governance that can contribute to reducing poverty.

The paper identifies the characteristics of community development projects that appear to span natural resource extraction industries and countries. Effective management strategies and representative and formally designated organisational governance boards are essential for these projects.

The objective of this study was to evaluate the technical-economic process efficiency of obtaining simultaneous lipo-soluble (LSF) and water-soluble (WSF) fractions from annatto seeds.

The batches of annatto seeds were submitted to the refrigerated solid-liquid extraction process in four stages: pre-extraction, aqueous extraction, separation by decantation and filtration. After that, LSF and WSF from annatto seeds were obtained. The process efficiency and the quality of LSF and WSF were analyzed in terms of average yield and bioactive compounds (bixin, norbixin, phenolics and flavonoids) and their antioxidant and antimicrobial activities. Furthermore, they were economically evaluated in terms of costs of manufacturing and profitability parameters.

The process was efficient in terms of overall average yield (LSF = 8.68% and WSF = 2.76%) (w/w) and in terms of quality, mainly with higher average yields of bixin (82.34% in LSF) and norbixin (29.59% in WSF) (w/w). The concentration of bioactive compounds in the fractions promoted an increase in inhibiting free radicals (DPPH* and ABTS*+) and in the ferric-reducing power (FRAP). LSF showed a minimum inhibitory concentration of 0.06 mg mL-1 for S. aureus and 0.13 mg mL-1 for S. Typhimurium and S. Enteritidis. The lowest manufacturing costs were obtained for the LSF due to its higher extraction yield compared to the WSF. Plants on an industrial scale of 100 and 1000 L were considered economically viable, with a return on investment of 5 and 2 years.

Thus, fractions (WSF and LSF) can be applied as natural additives, as sources of bioactive compounds for nutraceutical and/or pharmaceutical, and in the development of other innovative processes. These results have practical applicability for pharmaceutical and food industry.

1. Green processing of annatto seeds obtains fractions rich in antioxidant compounds.

2. Efficiently presents a high yield of bixin and other bioactive compounds.

3. Effective in concentrating compounds that inhibit microbial growth.

4. Fractions are more accessible sources of bioactive compounds for isolation.

5. Cost of manufacturing (COM) and profitability are studied.

Green processing of annatto seeds obtains fractions rich in antioxidant compounds.

Efficiently presents a high yield of bixin and other bioactive compounds.

Effective in concentrating compounds that inhibit microbial growth.

Fractions are more accessible sources of bioactive compounds for isolation.

Cost of manufacturing (COM) and profitability are studied.

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

The purpose of this study is to extract and characterize a novel natural dye from the leaves of Lannea coromandelica and the extraction with finding ways of dyeing cotton fabric using three mordants.

The colouring agents were extracted from the leaves of Lannea coromandelica using an aqueous extraction method. The extract was characterized using analysis methods of pH, gas chromatography-mass spectrometry (GC-MS), Fourier transform infrared (FTIR), ultraviolet-visible (UV-vis) and cyclic voltammetry measurement. The extract was applied to cotton fabric samples using a non-mordant and three mordants under the two mordanting methods. The dyeing performance of the extracted colouring agent was evaluated using colour fastness properties, colour strength (K/S) and colour space (CIE Lab).

The aqueous dye extract showed reddish-brown colour, and its pH was 5.94. The GC-MS analysis revealed that the dye extract from the leaves of Lannea coromandelica contained active chemical compounds. The UV-vis and FTIR analyses found that groups influenced the reddish-brown colour of the dye extraction. The cyclic voltammetry measurements discovered the electrochemical properties of the dye extraction. The mordanted fabric samples showed better colour fastness properties than the non-mordanted fabric sample. The K/S and CIE Lab results indicate that the cotton fabric samples dyed with mordants showed more significant dye affinities than non-mordanted fabric samples.

Researchers have never discovered that the Lannea coromandelica leaf extract is a natural dye for cotton fabric dyeing. The findings of this study showed that natural dyes extracted from Lannea coromandelica leaf could be an efficient colouring agent for use in cotton fabric.

The study examines the effect of natural resources (NRs) and the control of corruption, voice and accountability and regulatory quality on carbon emissions in Africa. Aside from their individual effects, the moderation effect of institutional quality is assessed.

Data from 32 African countries from 2002 to 2021 and the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) regression methods were used for the investigation.

In the long term, the NRs effect is sensitive to the estimation technique employed. However, quality regulatory framework, robust corruption control and voice and accountability abate any positive effect of NRs on carbon emissions. Institutional quality can be argued to moderate the CO2-emitting potentials of resource extraction in the selected African countries.

Enhancing regulation quality, enforcing corruption control and empowering citizens towards greater participation in governance and demanding accountability are essential catalyst to effectively mitigate CO2 emissions resulting from NRs.

The moderation effect of control of corruption, voice and accountability and regulatory quality on the NR–carbon emission nexus is examined.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. The authors used three feature extraction methods: handcrafted features, convolutional features and autoencoder features. Subsequently, these features were mapped to contact locations through a contact location regression network. Finally, the network performance was evaluated using spherical fittings of three different radii to further determine the optimal feature extraction method.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image.

This research indicates that data collected by probes can be used for contact localization. Introducing a batch normalization layer after the feature extraction stage significantly enhances the model’s generalization performance. Through qualitative and quantitative analyses, the authors conclude that convolutional methods can more accurately estimate contact locations.

The paper provides both qualitative and quantitative analyses of the performance of three contact localization methods across different datasets. To address the challenge of obtaining accurate contact locations in quantitative analysis, an indirect measurement metric is proposed.

This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component.

This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated.

Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target.

Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.