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This paper aims to investigate the effects of the COVID-19 crisis on trade flows in Asia Pacific countries and explores the causality between COVID-19-related shocks and trade.

The authors used two novel techniques, namely, two-stage instrumental-variables (2SIV) approach and Juodis, Karavias and Sarafids (JKS) causality test, to examine trade dynamics in the Asia Pacific region during the pandemic.

Using the monthly trade data of 17 Asia Pacific countries between January 2020 and December 2021, the results were threefold. Firstly, the empirical analysis showed that during the COVID-19 crisis, the flow of exports tended to persist idiosyncratically in comparison to the flow of imports. In particular, a specific finding was that the persistence level in exports was about 20%–25% higher than that in imports. Secondly, the authors found that the past values of COVID-19 cases and COVID-19 deaths contain information that helps to predict exports/imports over and above the information contained in the past values of exports/imports alone. Finally, the study established that the government response and stringency indexes have a Granger-causal relationship with exports and imports.

For the foreseeable future, these findings have significant policy ramifications. Firstly, if a COVID-19 crisis-like situation emerges in the future, it will be critical for countries to maintain their competitiveness throughout the crisis, like the COVID-19 pandemic, while also rebuilding trade relationships wherever possible. Secondly, because information about government responses and measures can also be used to predict future trade flows, prudent management of government responses and stringent measures will be necessary in a crisis like COVID-19 to achieve the optimum level of exports and imports. At the same time, the trading partners should give up the idea of trade protection and focus on finding a way to balance the conflicting needs of imports and exports.

To the best of the authors’ knowledge, the authors, for the first time, used a 2SIV approach and JKS causality test to examine trade dynamics in the Asia Pacific region during the pandemic. In addition, the authors present the first comprehensive analysis of the evolving relationships between export and import flows and governmental policy responses under COVID-19. As a result, it contributes uniquely to both public and international economics.

India’s historical fiscal performance has featured elevated deficit levels. Driven by the imperative need for fiscal stimulus measures in response to the crisis, efforts toward fiscal consolidation from 2003 to 2008 were reversed in 2008–2009 due to the financial crisis. These stimulus actions are believed to have wielded a notable influence on inflation dynamics. Presumably, a high inflation rate hinders growth and inflicts severe welfare costs. Accordingly, the principal objective of this paper is to scrutinise the threshold effects of fiscal deficit on inflation within the context of the Indian economy.

We employed the Smooth Transition Autoregressive (STAR) Model, a robust tool for capturing non-linear relationships, to discern the specific threshold level of fiscal deficit. Our analysis encompasses annual data spanning from 1971 to 2020. Additionally, we have leveraged the Toda-Yamamoto causality test to establish the existence and direction of a causal connection between fiscal deficit and inflation in the Indian economy.

Our analysis pinpointed a critical threshold level of 3.40% for fiscal deficit, a value beyond which inflation dynamics in India undergo a marked transition, signifying the presence of significant non-linear effects. Moreover, the results derived from the Toda-Yamamoto causality test offer substantiating evidence of a causal relationship originating from the fiscal deficit and leading to inflation within the Indian economic framework.

The findings of our study carry significant implications, particularly for the formulation and execution of both fiscal and monetary policies. Understanding the threshold effects of fiscal deficit on inflation in India provides policymakers with valuable insights into achieving a harmonious balance between these two critical economic variables.

To the best of our knowledge, this study is the first of its kind to empirically investigate threshold effects of fiscal deficit on inflation in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model.

The principal aim of this study is to examine the relationship between financial development and income inequality in India using the financial Kuznets curve (FKC) hypothesis.

This study uses the autoregressive distributed lag (ARDL) model and the Toda–-Yamamoto causality test to investigate the long-run and short-run relationship and causality between financial development and income inequality. In addition, this study employs a principal component analysis (PCA) to construct a comprehensive financial development index.

The study found a long-run relationship between financial development and income inequality in India for the period under consideration. Trade is found to improve the income distribution, while inflation worsens income distribution. Moreover, the empirical results revealed a feedback causality between financial development and income inequality. The study results confirm an inverted U-shaped relationship between financial sector development indicators and income inequality, thus validating the FKC hypothesis for the Indian economy.

The study draws attention of the government and policymakers, urging them to focus on building a strong financial sector by improving its efficiency. This, in turn, will lead to enhanced financial stability and a reduction in income inequality. They should prioritise the development of high-quality and sustainable financial products and services to ensure the robust growth of the financial sector.

To the best of our knowledge, this study is the latest of its kind to empirically test the financial development on income inequality and the FKC hypothesis simultaneously for the Indian economy using financial proxy variables from financial institutions (FIs) and financial markets (FMs) for the measurement of financial depth.

Standard economic theory predicts that any increase in public spending is accompanied by a rise in inflation in an economy. This paper presents empirical proof that prices do not always rise with an increase in public expenditure but only up to a certain threshold level. The primary aim of this paper is to unearth the government size-inflation nexus in India for the period from 1971 to 2019.

The logistic STAR (smooth transition autoregression) model is employed to unravel the government size-inflation nexus for the Indian economy from a non-linear perspective.

The finding of our study confirm the non-linear relationship between the size of the government and inflation in India. The estimated threshold level for government size is precisely found to be 9.27%. The size of the government exerts a negative influence on inflation until it reaches the optimal or threshold level. Any further increase in the size of government beyond this threshold level would result in a rise in inflation.

The findings have implications for the conduct of fiscal policy. Policymakers can increase government spending in a regime of small government size without having any inflationary impacts by generating revenues from taxes and other sources instead of relying much on the central bank. In the regime of a large-sized government, adhering strictly to the discipline in the conduct of fiscal and monetary policies would help curb inflation and enhance growth synchronously, hence alleviating any loss of welfare.

To the best of the authors’ knowledge, this study is an attempt to revisit the government size-inflation nexus in India from a non-linear perspective using the Smooth Transition Autoregression (STAR) model for the first time.

This study aims to observe the coloring efficacy of coffee-based natural brown colorant for cotton dyeing under microwave (MW) treatment.

The colorant extracted in particular (neutral and acidic) media was stimulated by MW treatment up to 6 min. Dyeing variables were optimized and 2–10 g/100 mL of sustainable anchors (mordants) have been used to get colorfast shades.

It has been found that un-irradiated acidic extract (RE) containing 5% of table salt at 80 °C for 50 min has given high color yield onto MW-irradiated cotton fabric (RC = 2 min). The utilization of 2% of Fe, 10% of tannic acid and 10% of sodium potassium tartrate before bio-coloration, whereas 4% of Fe, 10% of tannic acid and 6% of sodium potassium tartrate after bio-coloration has given good color characteristics. In comparison the application of 6% of pomegranate and turmeric extracts before bio-coloration and 6% of pomegranate and 10% of turmeric extracts after bio-coloration have given good color characteristics. New bio-mordants can be added to get more new colorfast shades.

There is no research limitation for this work. New bio-mordants can be added to get more new colorfast shades.

This work has practical application for artisans, textile industry and handicrafts. It is concluded that colorant from coffee beans can be possible alternative of synthetic brown dyes and inclusion of MW rays for extraction and plant molecules as shade developers can make process more green.

Socially, it has good impact on eco-system and global community because the effluent load is not carcinogenic in nature.

The work is original and contains value-added product for textiles and other allied fields.

Agricultural waste and food sources are some of the pollutants of the environment. One of these wastes is the peel of fruits that cannot be consumed as food. In this regard, walnut husk (WH) and oleaster peel (PO) are known as two important sources of tannin and are bulky wastes. Because of the high percentage of tannin, these materials can be used as a natural source for the preparation of bio-mordant in the dyeing process.

In this study, Reseda and Madder were used as natural dyes in the presence of a mixture of two bio-mordants. WH and PO were selected as bio-mordant. All natural resources are extracted to obtain the juice. The phenolic percentage of tannin-containing extracts was evaluated and then it was used for wool yarns by premordanting method. The results of evaluating the fastness properties using the ISO method.

The most important achievement of this research is the use of agricultural waste in the dyeing process to reduce environmental pollution and create added value. All compounds rich in tannin have some phenolic components, therefore the amount of phenolic content of these extracts was evaluated. The effect of mixing the mordant on the color characteristics of the yarns was investigated and the results showed that changing the ratio of the combination of two mordant is effective on the K/S values. The results of evaluating the fastness properties using the ISO method showed that the washing, rubbing and light fastness in the presence of mordant is good, good and moderate, respectively.

In this paper, to the best of the authors’ knowledge, for the first time, the combination of two natural extracts obtained from agricultural waste has been used to create a new bio-mordant on fibers and improve stability.

The roles recommendation systems play in health care have become crucial in achieving effective care and in meeting the needs of modern care giving. As a result, efforts have been geared toward using recommendation systems in the management of chronic diseases. Effectiveness of these systems is determined by evaluation following implementation and before deployment, using certain metrics and criteria. The purpose of this study is to ascertain whether consideration of criteria during the design of a recommendation system can increase acceptance and usefulness of the recommendation system.

Using survey-style requirements gathering method, the specific health and technology needs of people living with chronic diseases were gathered. The result was analyzed using quantitative method. Sets of harmonized criteria and metrics were used along with requirements gathered from stakeholders to establish relationship among the criteria and the requirements. A matching matrix was used to isolate requirements for prioritization. These requirements were used in the design of a mobile app.

Matching criteria against requirements highlights three possible matches, namely, exact, inferential and zero matches. In any of these matches, no requirement was discarded. This allows priority features of the system to be isolated and accorded high priority during the design. This study highlights the possibility of increasing the acceptance rate and usefulness of a recommendation system by using metrics and criteria as a guide during the design process of recommendation systems in health care. This approach was applied in the design of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People. The result has shown that with this method, it is possible to increase acceptance rate, robustness and usefulness of the product.

Inability to know the evaluation criteria beforehand, inability to do functional analysis of requirements, lack of well-defined requirements and often poor cooperation from people living with chronic diseases during requirements gathering for fear of stigmatization, confidentiality and privacy breaches are possible limitations to this study.

The result has shown that with this method, it is possible to isolate more important features of the system and use them during the design process, thereby speeding up the design and increasing acceptance rate, robustness and usefulness of the system. It also helps to see in advance the likely features of the system that will enhance its usefulness and acceptance, thereby increasing the confidence of the developers in their ability to deliver a system that will meet users’ needs. As a result, developers know beforehand where to concentrate their efforts during system development to ascertain the possibility of increasing usefulness and acceptance rate of a recommendation system. In addition, it will also save time and cost.

This paper demonstrates originality by highlighting and testing the possibility of using evaluation criteria and metrics during the design of a recommender system with a view to increasing acceptance and enhancing usefulness. It also shows the possibility of using the metrics and criteria in system’s development process for an exercise other than evaluation.