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In addition to agriculture, energy production, and industries, potable water plays a significant role in many fields, further increasing the demand for potable water. Purification and desalination play a major role in meeting the need for clean drinking water. Clean water is necessary in different areas, such as agriculture, industry, food industries, energy generation and in everyday chores.

The authors have used the different search engines like Google Scholar, Web of Science, Scopus and PubMed to find the relevant articles and prepared this mini review.

The various stages of water purification include coagulation and flocculation, coagulation, sedimentation and disinfection, which have been discussed in this mini review. Using nanotechnology in wastewater purification plants can minimize the cost of wastewater treatment plants by combining several conventional procedures into a single package.

In society, we need to avail clean water to meet our everyday, industrial and agricultural needs. Purification of grey water can meet the clean water scarcity and make the environment sustainable.

This mini review will encourage the researchers to find out ways in water remediation to meet the need of pure water in our planet and maintain sustainability.

Purpose – In this research, we have prepared activated carbon (AC) from the waste of banana peels (Musa acuminate L.) using potassium hydroxide (KOH) for carbon monoxide (CO) adsorption from motorcycle gas emission.

Design/Methodology/Approach – The activation was conducted using a chemical activator (KOH) at various concentrations of 1, 2, and 3 N for 1, 2, and 3 h, respectively. Characteristics of banana peels AC (BPAC) produced were analyzed using the Fourier-transform infra-red spectroscopy and scanning electron microscopy.

Findings – Results showed that KOH concentration and activation time strongly affected the CO adsorption and opening of the AC surface pore. There was an increase in the CO sorption when the KOH concentration was increased up to 3 N concentration. The highest CO adsorption from the emission occurred at 70.95% under KOH concentration of 3 N during the 3-h preparation.

Research Limitations/Implications – BPAC has been used as an adsorbent for only CO from motorcycle gas emission but not as an adsorbent for HC, NO, NO_x, or H₂S.

Practical Implications – BPAC can be used as the potential adsorbent for the removal of CO from motorcycle gas emission, and it is an environmental friendly, low cost, and easy to make adsorbent.

Originality/Value – In this study, the AC is made from biomass and is used in wastewater treatment, but limited studies are found on the removal of CO from motorcycle gas emission.

The volatility of bitcoin (BTC) and time horizon is the center point for investment decisions. However, attention is not often drawn to the relationship between BTC and equity indices. Thus, the purpose of this paper is to investigate the volatility and time frequency domain of BTC with stock markets.

The purpose of this paper is to focus on the removal of hexavalent chromium [Cr(VI)] from wastewater by using activated carbon-supported Fe catalysts derived from walnut shell prepared using a wetness impregnation process. The different conditions of preparation such as impregnation rate and calcination conditions (temperature and time) were optimized to determine their effects on the catalyst’s characteristics.

The catalyst samples were characterized using thermogravimetric analysis, scanning electron microscopy and Fourier transform infrared spectroscopy. The adsorption of Cr(VI) by using using activated carbon supported Fe catalysts derived from walnut shell as an adsorbent and catalyst was investigated under different adsorption conditions. The parameters studied were contact time, adsorbent dose, solution pH and initial concentrations.

Results showed that higher adsorption capacity and rapid kinetics were obtained when the activated walnut shell was impregnated with Fe at 5 per cent and calcined under N₂ flow at 400°C for 2 h. The adsorption isotherms data were analyzed with Langmuir and Freundlich models. The better fit is obtained with the Langmuir model with a maximum adsorption capacity of 29.67 mg/g for Cr(VI) on Fe5-AWS at pH 2.0.

A comparison of two kinetic models shows that the adsorption isotherms system is better described by the pseudo-first-order kinetic model.

The purpose of this paper is to investigate the direct and indirect links between environmental, social and governance (ESG) practices and financial performance using the mediate role of green innovation.

To test the current study hypotheses, the authors applied linear regressions with a panel data using the Thomson Reuters ASSET4 and Bloomberg database from a sample of 115 UK and 90 Germany companies selected from the ESG index over the period 2005–2019.

The results show that the strengths ESG increase the firm value and the weaknesses decrease it. In addition, the authors find that green innovation fully mediates the relationship between ESG practices and financial performance in UK and Germany.

The findings provide interesting implications to academics practitioners and regulators who are interested in discovering ESG score, financial performance and green innovation. The results also provide insights to regulators and the board of directors on future growth opportunities for the company and the country.

This study is unique in examining the mediation effect of green innovation on the relationship between ESG practices and financial performance.

This study reviews the extent of application of artificial intelligence (AI) tools in the construction industry.

A thorough literature review (based on 165 articles) was conducted using Elsevier's Scopus due to its simplicity and as it encapsulates an extensive variety of databases to identify the literature related to the scope of the present study.

The following items were extracted: type of AI tools used, the major purpose of application, the geographical location where the study was conducted and the distribution of studies in terms of the journals they are published by. Based on the review results, the disciplines the AI tools have been used for were classified into eight major areas, such as geotechnical engineering, project management, energy, hydrology, environment and transportation, while construction materials and structural engineering. ANN has been a widely used tool, while the researchers have also used other AI tools, which shows efforts of exploring other tools for better modelling abilities. There is also clear evidence of that studies are now growing from applying a single AI tool to applying hybrid ones to create a comparison and showcase which tool provides a better result in an apple-to-apple scenario.

The findings can be used, not only by the researchers interested in the application of AI tools in construction, but also by the industry practitioners, who are keen to further understand and explore the applications of AI tools in the field.

There are no studies to date which serves as the center point to learn about the different AI tools available and their level of application in different fields of AEC. The study sheds light on various studies, which have used AI in hybrid/evolutionary systems to develop effective and accurate predictive models, to offer researchers and model developers more tools to choose from.

Library intelligence institutions, which are a kind of traditional knowledge management organization, are at the frontline of the big data revolution, in which the use of unstructured data has become a modern knowledge management resource. The paper aims to discuss this issue.

This research combined theme logic structure (TLS), artificial neural network (ANN), and ensemble empirical mode decomposition (EEMD) to transform unstructured data into a signal-wave to examine the research characteristics.

Research characteristics have a vital effect on knowledge management activities and management behavior through concentration and relaxation, and ultimately form a quasi-periodic evolution. Knowledge management should actively control the evolution of the research characteristics because the natural development of six to nine years was found to be difficult to plot.

Periodic evaluation using TLS-ANN-EEMD gives insights into journal evolution and allows journal managers and contributors to follow the intrinsic mode functions and predict the journal research characteristics tendencies.