Search results

Wastewater treatment plants (WWTPs) have long-time environmental impacts. The purpose of this paper is to assess the environmental footprint of two advanced wastewater treatment (WWT) technologies in a life cycle and sustainability perspective and identify the improvement alternatives.

In this study life cycle-based environmental assessment of two advanced WWT technologies (moving bed biofilm reactor (MBBR) and sequencing batch reactor (SBR)) has been carried out to compare different technological options. Life cycle impacts were computed using GaBi software employing the CML 2 (2010) methodology. Primary data were collected and analysed through surveys and on-site visits to WWTPs. The present study attempts to achieve significantly transparent results using life cycle assessment (LCA) in limited availability of data.

The results of both direct measurements in the studied wastewater systems and the LCA support the fact that advanced treatment has the best environmental performance. The results show that the operation phase contributes to nearly 99 per cent for the impacts of the plant. The study identified emissions associated with electricity production required to operate the WWTPs, chemical usage, emissions to water from treated effluent and heavy metal emissions from waste sludge applied to land are the major contributors for overall environmental impacts. SBR is found to be the best option for WWT as compared to MBBR in the urban context. In order to improve the overall environmental performance, the wastewater recovery, that is, reusable water should be improved. Further, sludge utilisation for energy recovery should be considered. The results of the study show that the avoided impacts of energy recovery can be even greater than direct impacts of greenhouse gas emissions from the wastewater system. Therefore, measures which combine reusing wastewater with energy generation should be preferred. The study highlights the major shortcoming, i.e., the lack of national life cycle inventories and databases in India limiting the wide application of LCA in the context of environmental decision making.

The results of this study express only the environmental impacts of the operation phase of WWT system and sludge management options. Therefore, it is recommended that further LCAs studies should be carried out to investigate construction and demolition phase and also there is need to reconsider the toxicological- and pathogen-related impact categories. The results obtained through this type of LCA studies can be used in the decision-making framework for selection of appropriate WWT technology by considering LCA results as one of the attributes.

The results of LCA modelling show that though the environmental impacts associated with advanced technologies are high, these technologies produce the good reusable quality of effluent. In areas where water is scarce, governments should promote reusing wastewater by providing additional treatment under safe conditions as much as possible with advanced WWT. The LCA model for WWT and management planning can be used for the environmental assessment of WWT technologies.

The current work provides a site-specific data on sustainable WWT and management. The study contributes to the development of the regional reference input data for LCA (inventory development) in the domain of wastewater management.

The main aim of this paper is to examine the claim that economic value added (EVA) advocates its superiority over the traditional accounting-based financial performance measures, i.e. profit after tax (PAT), earnings per share (EPS), return on assets (ROA), return on equity (ROE) and return on investment (ROI) in the Indian manufacturing sector and at the same time, give empirical facts. It also tests and examines the information content of various performance measures and their relationship with stock returns.

The paper uses the sample of 534 Indian manufacturing companies from the Bombay Stock Exchange (BSE) during the period 2000–2018. Multiple regression models are applied to examine the information content of EVA and traditional performance measures in explaining shareholders’ returns.

Relative information content tests revealed that traditional accounting-based measures such as EPS, ROE and ROA performed better than EVA in explaining the returns of Indian manufacturing companies. Incremental information content of EVA adds little contribution to information content above traditional performance measures. The claim of superiority of EVA over accounting-based measures in association with shareholder returns is proved invalid in Indian manufacturing companies.

This study concludes that EVA has no superiority over traditional accounting-based financial performance measures in explaining stock returns of Indian manufacturing companies. To achieve heftiness in outcomes, panel data are tested by using Breusch–Pagan–Godfrey (BPG) test for heteroskedasticity, Hausman’s test for fixed and random effect, variance inflation factor (VIF) test for multicollinearity and Durbin–Watson test for autocorrelation.

Artificial intelligence (AI) has the potential to address significant challenges in education, innovate learning and teaching practices and achieve SDG 4. However, existing literature often overlooks the behavioural aspects of students regarding AI in education, focusing predominantly on technical and pedagogical dimensions. Hence, this study aims to explore the significant relationships among AI literacy, AI usage, learning outcomes and academic performance of generation Z students in the Indian educational context.

The study used structural equation modelling (SEM) on Gen Z students born in the years 1997–2012 as a sample population for the research in the north Indian states like Punjab, Haryana, Himachal and regions like Chandigarh and N.C.R. Delhi.

The results established significant positive relationships between AI literacy, AI usage, AI learning outcomes and academic performance. Specifically, higher levels of AI literacy were associated with increased engagement with AI technologies and tools for learning purposes, leading to better learning outcomes and academic performance. The findings demonstrated that AI literacy plays a crucial role in providing effective learning experiences and fostering skills such as problem-solving and critical thinking among Gen Z students.

The implications of the study include the significance of integrating AI education initiatives into curricula, prioritising professional development programmes for educators and making sure that every student has equitable access to AI technologies.

The study introduces a novel perspective by examining variables such as AI literacy, AI usage, AI learning outcomes and academic performance and developing a model that has not been previously studied. It provides a new discourse and proposes a framework uniquely combining AI-infused curriculum design, educator empowerment, robust assessment mechanisms and sustainable practices.

Soybean is potentially a rich source of protein and lipids along with isoflavone. However, the use of soybean is limited due to presence of anti-nutritional factors such as trypsin inhibitor, phytic acid, etc. The present study aimed at evaluation of Harit soya seeds of different treatments such as soaking, dehulling, germination, soaking+roasting and roasting in order to enhance its quality.

Harit soya seeds were utilized were soaked overnight and subjected for dehulling, germination for 3 days as well as roasting followed by drying to obtain fine powder for quality evaluation.

Dehulling and germination produce significant (p < 0.01) increase in protein, crude fiber, total chlorophyll, ascorbic acid, total phenolics, flavonoids and isoflavones while fat was decreased non-significantly. The highest value of 12.4 mg/100g, 5.3 mgGAE/g and 6.6 mg/g for ascorbic acid, total phenolics and isoflavones was found in germinated seeds. Also, the effect of soaking, roasting and their combination lead to significant decrease in the functional properties of the seeds. Anti-nutritional factors were significantly (p < 0.01) reduced in all forms of treated seeds while pepsin and trysin digestibility was enhanced during soaking, dehulling and germination with maximum value of 72.6 and 25.8%, respectively in germinated seeds.

Improvement in quality of evergreen variety of soybean using cost effective traditional methods

This study presents a systematic literature review on green banking (GB) and sustainability from 2012 to 2024, filtering 45 out of 561 research publications.

Using NVivo and Biblioshiny, the study employed a combination of bibliometric analysis and thematic analysis, representing a novel approach in this field.

The analysis of ‘term frequency' results has indicated that the term “green banking” has gained significant attention during the peak of the COVID-19 pandemic, followed by sustainability and green finance. This suggests that approximately 12.5% of the literature on GB has emerged shortly after the first wave of the COVID-19 crisis. Cluster analysis and network analysis has divided the GB articles into two major clusters and one minor cluster. Most studies cover titles such as “sustainable”, “sustainable development” and “sustainability.” However, there is a significant gap in research on the theme of GB. Aside from legitimacy and stakeholder theories, no clear theoretical frameworks have yet been published in the field of GB. Among all categories of publishers, Elsevier ranks highest for publishing journal articles on “green” topics. According to publication output by country, China leads with 17 publications, followed by Malaysia with 11, and both Australia and India with nine each.

The in-depth research on GB provides fresh insights for policymakers and academics regarding future research directions.

This study is likely the first to incorporate both bibliometric and thematic analysis to explore the growing phenomenon of GB. Furthermore, none of the existing banking literature explicitly addresses the relevant questions and themes that could benefit future researchers and policymakers.

Internal fluffy portion along with fibrous strands of ripe pumpkin is considered as waste in processing industries though it contains sufficient amount of ß-carotene pigment. The purpose of this paper is to use the leftover fluffy portion of ripe pumpkin (Cucurbita maxima) after the use of its flesh for the purpose of processing.

The data were analyzed statistically by following a complete randomized design (CRD). All analysis were performed using the software OPSTAT.

One hour pre-enzymatic treatment before solvent extraction showed significant improvement in extraction yield in comparison to the isolation of ß-carotene pigment through solvent only. Temperature time combination was optimized as 40°C for 2 h during solvent extraction to obtain maximum yield irrespective of the type of extraction method used.

Extracted carotene pigment can further be used as a natural food colorant in processed food products not only to enhance the color appeal but also it improves the nutritional value of the product as ß-carotene acts as a precursor of vitamin A.

Coloring agents of natural origin are becoming famous among society due to their health benefits. Consumers are becoming reluctant to use synthetic colors because of the undesirable allergic reactions caused by them, so carotene bio-pigment produced is a natural coloring compound with wide application in the food sector.

Even though few researchers have worked on the extraction of carotene pigment from pumpkin, but no researcher has reported the use of a waste fluffy portion of C. maxima for extraction of ß-carotene pigment.

This study aims to encapsulate the crude carotene pigment isolated from waste portion of Cucurbita maxima with the help of different encapsulating agents through lyophilization to transform crude pigment into stable form for further utilization.

This paper opted for encapsulation of extracted carotene pigment by lyophilization using various carrier materials such as maltodextrin 20 dextrose equivalent (DE), maltodextrin 10 DE and tapioca starch along with emulsifier polysorbate-80. After encapsulation of crude carotene pigment, prepared encapsulated powder was subjected to chemical analysis. The data was analysed statistically by a complete randomized design.

Maximum encapsulation efficiency, carotene content, antioxidant activity and water solubility index were achieved when 0.06% of crude carotene pigment was emulsified with same quantity of polysorbate-80, followed by encapsulation with 20% of maltodextrin 20 DE during lyophilization.

Even though few researchers have worked on the encapsulation of colour pigments, no researcher has reported encapsulation of carotene pigment extracted from waste of C. maxima.

The purpose of the study is to highlights the conceptual and scientific knowledge regarding bioavailability of food bioactive components which is essential for the thorough understanding of their role in disease prevention and factors that limit their absorption.

Nutrikinetics is an extended version of pharmacokinetics that is used for studying the bioavailability and bioaccessibility of components through different techniques such as metabolic profiling, multi-level data analysis and population-based modeling.

There are different phases of nutrikinetics study of the bioactive components. The initial stage of nutrikinetics is starting from simplest in-vitro assay which is applicable in the early stage of functional foods development. Thereafter, the next stage of nutrikinetics studies are related to human intervention studies as designed by European Food Safety Authority. The aim of such studies are to develop dose-exposure and exposure response study of a bioactive component.

This paper will enlighten the concept of nutrikinetics, its requirement and the future perspectives of nutrikinetics study including long-term efficacy studies and multi-compartmental analysis of the different bioactive components.

Although founders are often replaced with external CEOs prior to firms making IPOs, firms that do retain founder CEOs generally perform better at IPO. However, this relationship may be contingent upon context. This study aims to investigate how national context influences the relationship between a founder CEO and IPO long-run performance. The authors hypothesize that founder-CEOs will perform better in IPO firms in countries where managerial discretion, future orientation, and the level of conformity to professionalize management are high, and uncertainty avoidance is low.

Using insights from the upper echelon and institutional theory, the authors used hierarchical linear modeling to analyze over 1,000 firms across eight countries.

Founder CEOs perform best in IPO firms in a national context where managerial discretion is low, uncertainty avoidance is high and the level of conformity is high.

This study contributes to a growing area of cross-national IPO research in management by investigating the relationship between culture, management and IPO performance.