Indian Rupees Research Articles

Detecting anomalies in currency market of BRICS countries: insights into emerging economies

PurposeThe primary motive of the research paper is to investigate the efficiency of currency market of emerging economies (BRICS countries), by analyzing the presence and consistency of calendar anomalies – specifically the day-of-the-week (DOW) effect, the January effect and the Turn-of-the-month (TOM) effect. Daily data of around 23 years and 4 months were examined for the purpose of study. Segmented data of 8-year intervals were also analyzed to observe the changes in the pattern over a period. The findings are intended to offer insights into market behaviors and potential trading strategies for astute traders.Design/methodology/approachThe study employed a quantitative research design utilizing ordinary least squares regression with dummy variables and Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) (1,1) model. To study the calendar anomalies, the daily closing price of five currency pairs has been taken from Bloomberg’s software. The Kruskal–Wallis test was conducted to validate and check the robustness of analysis.FindingsThere are mixed results regarding calendar anomalies in the BRICS currency markets. Analysis of aggregate data revealed that DOW effect is present in all the currencies except USDZAR, with Monday showing positive return. The segmented analysis showed the presence of DOW effect in USDCNY and USDINR, while other currencies lacked consistent patterns. The January effect was evident for Indian Rupees and Chinese Yuan but not for other currencies. TOM effect was present only in Chinese Yuan. Overall, the Indian Rupee and Chinese Yuan displayed inefficiencies, indicating potential for trading strategies, while other currencies appeared efficient and lacked consistent patterns.Originality/valueThe literature on currency pricing anomalies is sparse, particularly in the context of developing and underdeveloped economies. While some research exists on anomalies within the currencies of developed nations, there is a significant gap in studies focusing on emerging economies. This paper seeks to address this deficiency by investigating the presence of calendar anomalies in the currencies of BRICS countries, providing new insights into the behaviors of these emerging economies.

Impact of De-Dollarisation Move on Indian Rupee

Since the Russia-Ukraine war, it seems to be an era ofeconomic uncertainties and tense geopolitical relations. Could India reap some benefits arising out of these tense geopolitical scenario and uncertain geo-economic conditions? Post the invasion of Ukraine by Russia, Russia and China entered into a strategic relationship which provides a window for a more multialigned India. India could really reap the benefits of this strategic relationship of Russia and China if it can utilise this as an opportunity and puts more emphasis on its economic growth and market-oriented reforms. This could be possible if India strives for driving service based exports besides extending the manufacturing sector and gaining a pivotal role on the economic front through major chunk of global trade. India can utilise this strategic alliance of Russia and China as an opportunity especially by strengthening its economic power by focussing on service based exports besides expansionary move in the manufacturing sector. India could really gain out of these opportunities since lot many events are occurring globally which are really aiding India. Recent complex notifications as being given by the Ministry of Commerce and Industry, emphasised a few class of exporters and importers to execute trade transactions in the India Rupee. It is really a turning point amidst latest phenomenon of global trade promoting globalisation in almost every sphere of trade with a great hue and cry. These bilateral trade orders really made the citizens nostalgic about EXIM policy in the past before the globalisation move. But how this time these notifications deviate from the times when India used to have a closed economic system. At that time the dollar was king, imports were strictly regulated by tariffs, foreign exchange reserves were limited and above all these recent measures of foreign trade in India in Indian Rupee pose an important question whether this is a move towards de-dollarisation and if it provides a window for Indian Rupee to rise.

Enhancing yield and economic benefits through sustainable pest management in Okra cultivation.

Okra (Abelmoschus esculentus) is a prominent vegetable crop in Asia, confronting persistent threats from pests such as leafhoppers, whiteflies, and shoot and fruit borers. Conventional chemical control methods, despite their adverse ecological effects, remain the primary approach for pest management. Indiscriminate chemical use has led to reduced biodiversity among natural predators and the disruption of food webs in ecosystems. To address these challenges, this study assessed the efficacy of integrated (IM) and biointensive (BM) pest management modules in comparison to conventional chemical methods (CM) for mitigating insect damage to okra leaves and fruits, and subsequently, their impact on okra yield. Our result revealed that the BM exhibited the least effectiveness but outperformed untreated control plots significantly. In contrast, both IM and CM significantly reduced damage from sap-sucking insects and borer pests. Notably, plots treated with the chemical module found decreased populations of natural enemies. The IM demonstrated the lowest fruit infestation rate (5.06%), yielding the highest crop production (8.97 t ha-1), along with the maximum net return (Indian Rupees: 44,245) and incremental cost-benefit ratio (3.31). Thus, the study suggested that the implementation of integrated pest management practices can result in higher okra yields and greater economic benefits. These findings shed light on the potential of sustainable agricultural practices as a safer and more economically viable alternative to chemical-intensive pest control in okra cultivation.

Exploring the factors influencing the health-related quality of life in patients experiencing adverse drug reactions: a cross-sectional study

BackgroundThis study aimed to assess the factors influencing health-related quality of life (HRQoL) in patients experiencing adverse drug reactions (ADRs) at a tertiary care public sector hospital. A cross-sectional study was conducted over a period of 18 months, and included both male and female patients aged 18 years and above. Patients who visited the outpatient and inpatient departments with complaints associated with ADRs were included in this study. HRQoL data were collected using the EuroQol—5 Dimension—5 Level (EQ-5D-5L) questionnaire to assess five dimensions of health on a five-level scale. Descriptive statistics, t-tests, and analysis of variance were used to analyze the data. Multivariate regression analysis was performed to identify the potential determinants of HRQoL.ResultsA total of 316 patients were included in the study among these participants, of which 54% were female, and 65% were from rural areas. The majority (68%) of the patients had moderately severe ADRs, and 63% of the participants had an income < 2.5 lakh Indian rupees (3009 USD). The mean EQ-5D-5L and EuroQoL Visual Analog Scale (EQ VAS) scores of the study participants were 0.714 and 69.73, respectively. The variables ADR severity, income, and age showed a significant difference (p < 0.05) in HRQoL.ConclusionThis study provides insights into HRQoL among patients with ADRs and identifies the determinants of HRQoL. The findings of this study will contribute to improving patient-centered care and optimizing patient outcomes.

The Correlation Dynamics Between Sensex 30 Returns and INR/USD Exchange Rate Movements

The Sensex 30 is a benchmark index for India's largest companies, indicating the health of the stock market. Its movements are influenced by domestic economic conditions, corporate performance, and global trends. The INR/USD exchange rate, which represents the Indian rupee vs. the US dollar, is crucial for India's international trade and investment. A depreciating rupee benefits export-oriented companies but increases import costs, affecting market performance. Understanding this dynamic is essential for investors and policymakers. The fluctuating link between the INR/USD currency pair and SENSEX 30 stock index is examined in this study from 2014 to 2024, with an emphasis on how changes in the exchange rate affect stock market performance. As India continues to integrate into the global economy, the interaction between foreign investments and the Indian stock market has become increasingly relevant for understanding investor sentiment and economic stability. This study particularly examines how returns from the SENSEX 30, an index that monitors 30 of India's biggest and most traded firms, are impacted by changes in the INR/USD exchange rate. The research's main finding is that there is a strong positive correlation between the INR/USD exchange rate and the SENSEX 30 index, with a rise of 1 in the SENSEX 30 for every 0.90 increase in the exchange rate. This implies that the depreciation of the Indian currency (INR) in relation to the US Dollar (USD) may result in increased stock market returns, especially in industries that rely heavily on exports, as Indian goods become more competitive in international markets due to the weaker currency. On the other hand, persistent depreciation may also result in higher import prices and inflationary pressures, which might be detrimental to business profitability and the state of the economy as a whole. Given that currency changes may have an impact on their investment decisions, foreign institutional investors (FIIs) are essential to this dynamic.. Decreased international gains are eroded by a lower INR, which frequently leads to portfolio modifications and more market volatility. Exchange rate fluctuations and stock market performance are influenced by the participation of foreign institutional investors (FIIs) and the Reserve Bank of India's (RBI) monetary policy choices. For example, the RBI's changes to interest rates have an effect on investor mood and influence market movements. Global economic variables that affect the US stock market and exchange rate include geopolitical tensions, changes in the price of commodities, particularly oil, and US Federal Reserve policies. The study uses a variety of statistical techniques, including as trend analysis, a t-test, and correlation analysis, to assess the link between the performance of the SENSEX 30 and the INR/USD exchange rate during a ten-year period. The results of the t-test demonstrate that the difference between the mean values of the SENSEX 30 and the INR/USD exchange rate is statistically significant, with a t-statistic of 30.278 and very tiny p-values. The SENSEX 30 exhibits a significantly bigger variation than the INR/USD, suggesting that the stock market is more volatile than the currency rate. This result is in line with predictions because stock markets are often more erratic than exchange rates. As a result, the study emphasizes how much exchange rate fluctuations affect the Indian stock market. It is recommended that investors keep a careful eye on currency changes since they have the International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 08 Issue: 09 | Sept - 2024 SJIF Rating: 8.448 ISSN: 2582-3930 © 2024, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM37610 | Page 2 potential to impact business profitability and stock market performance, particularly in industries that depend on imports or exports. The results also emphasize how crucial it is to diversify portfolios and hedge against risk related to currencies in order to successfully manage the intricate relationships between monetary policy, market volatility, and global economic situations.

Literature Survey on Revolutionizing Fake Currency Detection: CNN-Based Approach for Indian Rupee Notes

The proliferation of counterfeit currency poses a significant challenge in various economies, including India. To address this issue, several studies have proposed innovative image processing and machine learning techniques for detecting counterfeit coins and banknotes. Leveraging digital image processing, these studies aim to enhance the security measures against counterfeit currency through accurate and efficient recognition systems. Techniques such as preprocessing, segmentation, feature extraction, and clustering are employed to identify fraudulent currency. The use of Support Vector Machines (SVM), k-means clustering, and Convolutional Neural Networks (CNN) facilitates the recognition and classification of genuine and counterfeit currency. Moreover, these studies explore the application of spatial coding, component-based recognition, and deep learning algorithms to improve the accuracy and robustness of counterfeit detection systems. By developing real-time recognition systems capable of identifying counterfeit currency, these research efforts contribute to combating financial fraud and safeguarding economic integrity.

CLASSIFICATION MODEL FOR INDIAN CURRENCY USING DEEP LEARNING

The field of deep learning has revolutionized computer vision and image recognition, enabling significant advancements in various domains. Image recognition, in particular, has become a prominent use case for deep learning, finding applications in diverse fields for tasks such as image filtering and categorization. One domain where image processing plays a crucial role is the banking sector, where it is used to classify and verify currency notes. In this project, our aim is to propose a machine learning model specifically designed for the classification of Indian currency notes and coins. The model will have the capability to accurately classify and identify the denomination value of paper notes as well as coins. This classification system can be instrumental in detecting fake and counterfeit currencies, providing a valuable tool for ensuring the integrity of financial transactions. Furthermore, the proposed model can be integrated into existing notes and coins counters, as well as vending machines, to automate the classification process and enhance efficiency. By leveraging machine learning techniques, this project aims to streamline currency recognition processes and provide a reliable solution for accurately identifying the denomination value of Indian currency, benefiting various industries and sectors that deal with cash transactions. Keywords—Deep Learning, Convolutional Neural Network, Image Classification, Feature Extraction, Currency Recognition, Data Augmentation

Assessing the societal value of health lost to alcohol use in India compared to excise taxes on alcohol sales.

We retrospectively studied the societal value of lost health due to alcohol use and compared it with excise taxes on alcohol sales for India in 2019. We estimated the overall alcohol-attributable disease burden using disability-adjusted life-years (DALY) for India and its 30 states for all causes with alcohol use as a risk factor from the GBD 2019 Study. The societal value of lost health was calculated using value of life-year (VLY) approach by multiplying region-specific factors from 'Global Health 2035', 2019-2020 GDP per capita and DALYs. We acquired the national and state-level (top 10 states) alcohol sales excise taxes from the Reserve Bank of India. Net losses were assessed by subtracting the revenue collected from excise taxes from VLY. All values are in Indian rupees (INR). The societal value of health lost due to alcohol use in India was 6.2 (95% uncertainty interval 4.8, 7.8) trillion INR in 2019. The absolute state-level values varied from 7.3 (4.7, 10.4) billion INR in Mizoram to 1.1 (0.8, 1.4) trillion INR in Maharashtra. The per capita values ranged from 950.2 (642.9, 1285.3) INR for Bihar to 61,332 (39,273.7, 87,288.5) INR for Mizoram. Nationally, excise tax collection from alcohol sales was 1.8 trillion INR depicting a net loss of 4.4 (3.1, 6.0) trillion. Maharashtra had the largest absolute and per capita net loss. These are novel estimates depicting the net losses due to alcohol use in India with direct policy implications to disincentivise sales and adequately raise taxes.

Evaluating the cost-effectiveness of Cy-Tb for LTBI in India: a comprehensive economic modelling analysis.

Latent tuberculosis infection (LTBI) remains a significant challenge, as there is no gold standard diagnostic test. Current methods used for identifying LTBI are the interferon-γ release assay (IGRA), which is based on a blood test, and the tuberculin skin test (TST), which has low sensitivity. Both these tests are inadequate, primarily because they have limitations with the low bacterial burden characteristic of LTBI. This highlights the need for the development and adoption of more specific and accurate diagnostic tests to effectively identify LTBI. Herein we estimate the cost-effectiveness of the Cy-Tb test as compared with the TST for LTBI diagnosis. An economic modelling study was conducted from a health system perspective using decision tree analysis, which is most widely used for cost-effectiveness analysis using transition probabilities. Our goal was to estimate the incremental cost and number of TB cases prevented from LTBI using the Cy-Tb diagnostic test along with TB preventive therapy (TPT). Secondary data such as demographic characteristics, treatment outcome, diagnostic test results and cost data for the TST and Cy-Tb tests were collected from the published literature. The incremental cost-effectiveness ratio was calculated for the Cy-Tb test as compared with the TST. The uncertainty in the model was evaluated using one-way sensitivity analysis and probability sensitivity analysis. The study findings indicate that for diagnosing an additional LTBI case with the Cy-Tb test and to prevent a TB case by providing TPT prophylaxis, an additional cost of 18658 Indian rupees (US${\$}$223.5) is required. The probabilistic sensitivity analysis indicated that using the Cy-Tb test for diagnosing LTBI was cost-effective as compared with TST testing. If the cost of the Cy-Tb test is reduced, it becomes a cost-saving strategy. The Cy-Tb test for diagnosing LTBI is cost-effective at the current price, and price negotiations could further change it into a cost-saving strategy. This finding emphasizes the need for healthcare providers and policymakers to consider implementing the Cy-Tb test to maximize economic benefits. Bulk procurements can also be considered to further reduce costs and increase savings.

Year around study of tubular solar still with green almondshells biowaste as energy storage material: energy, economic, and environmental analysis.

Solar-based desalination is one of the prominent contributors to overcoming the water scarcity problems in desert areas and a major alternative to fossil fuel-based desalination methods. The present study focuses on utilizing green almond shells (green almond shells) as energy storage materials in tubular solar still (TSS) to enhance water productivity, energy efficiency, and economic and environmental analyses. Further, this study discusses the yearly water output, annual energy efficiency, and economic and environmental analyses. Two different TSS were utilized which consists of conventional TSS (CTSS) without any storage materials and modified TSS with the inclusion of green almond shells (MTSS) in the climatic conditions of Chennai, India. The yearly distilled water output from the CTSS and MTSS was evaluated as 512 and 691.2kg/m2, respectively. The yearly distilled water output from the MTSS is 26% higher when compared to the CTSS. Furthermore, the maximum monthly energy efficiency of the CTSS and MTSS was 14.4 and 19.44%, respectively. The annual energy efficiency of the CTSS and MTSS is 12.6 and 17.02%, respectively. The economic analysis of the system is also carried out, and the findings show that better economic feasibility is achieved in MTSS considering the INR 5 (Indian Rupees) cost of water. The payback period for MTSS was 12months, while for CTSS it is calculated to be 20months. Furthermore, CO2 emission and mitigation have also been evaluated, and the results indicate that the utilization of porous material has increased the emission for MTSS, while CO2 mitigation has been significantly higher as compared to the CTSS system.

How far India has succeeded in harnessing its export potential in rice? Evidence Using Stochastic Frontier Gravity Model

This study employs the stochastic frontier gravity model (SFGM) to objectively assess the determinants of India’s rice exports from 2001 to 2019 across 22 major export destinations, highlighting untapped export potential and providing actionable policy recommendations for enhancing competitiveness in global rice markets. Results show that India's economic growth (GDP) and the GDP of importing nations positively impact rice exports. Conversely, geographical distances (representing transportation costs) and higher import tariffs act as deterrents. The devaluation of the Indian rupee positively influences export revenues. Common language benefits exports, while regional trade agreements show minimal impact. The study estimates significant untapped export potential between India and its partners, emphasizing the need for improved trade facilitation, logistics, and agreements. To maximize India's rice export potential, policymakers should prioritize quality compliance, streamline regulations, and invest in infrastructure and R&D for rice cultivars. Negotiating favorable trade agreements and implementing existing export policies like the New Agricultural Export Policy will aid market access and competitiveness.

The impact of business model innovation and knowledge management on firm performance: an emerging markets perspective

PurposeDespite the growing literature on business model innovation (BMI) and its implications for firm performance, the research on the antecedents of BMI is still at a budding stage. Therefore, the purpose of this paper is to bridge this gap by examining the causal relationships between knowledge management, BMI, competitive advantage, and firm performance.Design/methodology/approachA purposive sample of 300 micro, small, and medium enterprises was collected with more than 500 employees and total revenue between 50 and 500 million Indian Rupees, according to the Development Act, 2005. The collected data were analyzed using structural equation modeling through smart PLS 3.FindingsThe study’s findings show that knowledge management significantly influences BMI. This study also highlights the synergic impact of Knowledge management and BMI on firm performance. Furthermore, findings highlight the mediating role of competitive advantage in the relationship between knowledge management, BMI, and firm performance.Practical implicationsUnderstanding the impact of BMI and knowledge management is crucial for business owners, managers, and other stakeholders to plan for the continuous improvement of their businesses. Managers can secure a favorable position in the competitive market and improve organizational performance by paying attention to effectively managing their knowledge resources.Originality/valueThe study is one of the first few empirical efforts to investigate the causal relationships between knowledge management, BMI and firm performance. The study adds to the scant literature in this area by highlighting the mediating role of competitive advantage.

An Assessment of the Relative Position of Indian Rupee vis-a-vis Selected Asian Currencies

The article aimed to examine the relative position of Indian rupee vis-a-vis those of some otherselected Asian economies (viz., China, Pakistan, Nepal, Sri Lanka, Indonesia, Malaysia,Philippines, Myanmar, Japan and Singapore) throughout the period from January 2001 toMarch 2021. These currencies have been estimated using nineteen functional forms and theselection of best-fit functional form was based on minimum value of Akaike’s InformationCriterion (AIC). The coefficients have been derived on the basis of the selected functional formand subsequently relative growth rates have been calculated at different time intervals. Thestudy brings out that the currency of Singapore has been the most-stable one, followed by thatof Japan and then of China. On other extreme, currency of Myanmar has been the most-fragileone, followed by that of Pakistan and then of Sri Lanka. So far as India is concerned, positionof its currency has just been mid-way, with a pooled rank of 5 in the group of 11 currencieswhich indicates moderate position of Indian rupee among the currencies that are most fragileone and most stable one.

Estimation of potential social support requirement for tuberculosis patients in India.

Providing social support to tuberculosis (TB) patients is a recommended strategy as households having TB patients find themselves in a spiral of poverty because of high cost, huge income loss and several other economic consequences associated with TB treatment. However, there are few examples of social support globally. The Indian government introduced the 'Nikshay Poshan Yojana' scheme in 2018 to provide nutritional support for all registered TB patients. A financial incentive of 500 Indian Rupee (6 United States Dollars) per month was proposed to be transferred directly to the registered beneficiaries' validated bank accounts. We examined the reach, timing, amount of benefit receipt and the extent to which the benefit alleviated catastrophic costs (used as a proxy to measure the impact on permanent economic welfare as catastrophic cost is the level of cost that is likely to result in a permanent negative economic impact on households) by interviewing 1482 adult drug-susceptible TB patients from 16 districts of four states during 2019 to 2023, using the methods recommended by the World Health Organization for estimating household costs of TB nationally. We also estimated the potential amount of social support required to achieve a zero catastrophic cost target. At the end of treatment, 31-54% of study participants received the benefit. In all, 34-60% of TB patients experienced catastrophic costs using different estimation methods and the benefit helped 2% of study participants to remain below the catastrophic cost threshold. A uniform benefit amount of Indian Rupee 10 000 (127 United States Dollars) for 6 months of treatment could reduce the incidence of catastrophic costs by 43%. To improve the economic welfare of TB patients, levels of benefit need to be substantially increased, which will have considerable budgetary impact on the TB programme. Hence, a targeted rather than universal approach may be considered. To maximize impact, at least half of the revised amount should be given immediately after treatment registration.

The cost-effectiveness of reusable flexible ureteroscopes: An institutional audit.

A flexible ureteroscope (FU) is an important tool in the urologist's armamentarium. This study aims to check the durability and cost-effectiveness of conventional FU. The institution registry of damaged FU over the last 7 years was reviewed. A total of 17 flexible scopes were used. The data of 13 scopes (11 Storz fiberoptic and 2 Seesheen digital) are included in this study. A total of 1905 cases were performed. The cost of scope, duration of use, number of cases done by each scope, and nature of damage were evaluated. We compared the cost-effectiveness of conventional scopes with published costs on disposable scopes. The mean number of cases done by fiberoptic scope was 159 (range 25-334). The total cases done by 2 digital scopes were 135 and 25. The mean life of fiberoptic and digital scopes was 17 (range 4-31) and 8 months, respectively. The mean cost of fiberoptic scope was Indian Rupee (INR) 338,951 ($4082.7221) and INR 525,000 ($6323.7138) for digital scope. The cost per case for reusable scope is calculated by dividing the mean cost of FU by the mean number of cases done. The reprocessing cost of INR 527 was then added. Thus, the average cost per procedure for fiberoptic and digital FU was INR 2658.76 and INR 7089.50, respectively. We compared this cost with a projected cost of disposable FUbased on today's market data, which ranged from INR 60,000 to 107,427. The reusable scopes are durable, cost-effective, and an excellent option for high case-load institutions.

Cost-Utility Analysis of TNF-α Inhibitors, B Cell Inhibitors, and JAK Inhibitors Versus csDMARDs for Rheumatoid Arthritis Treatment.

Rheumatoid arthritis (RA) is a progressive and debilitating disease, causing persistent joint pain that limits daily activities requiring long-term treatment. Newer targeted therapies expand RA treatment options, but their high cost necessitates a focus on cost effectiveness. To address this, we aim to conduct a cost-utility analysis of these newer RA pharmacotherapies to support evidence-based policy decision-making. We analyzed the cost-utility of sequential treatment with TNF-α, B cell and JAK-inhibitors compared with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) for RA treatment in methotrexate (MTX) nonresponders. We used a Markov model with lifetime horizon and 6-month cycles from an Indian health system perspective. Costs (INR 2022) and quality-adjusted life years (QALYs) were used to determine the incremental cost-effectiveness ratios (ICERs) at a cost-effectiveness threshold of India's gross domestic product (GDP) per capita (2022). We assessed uncertainty using univariate, probabilistic sensitivity, and scenario analyses. Despite additional QALYs, TNF-α, B cell, and JAK inhibitors were not cost-effective for treating moderate-to-severe patients with RA unresponsive to csDMARDs (including MTX) in India, as increased costs outweighed their clinical benefits. ICERs ranged from 10,46,206 to 31,09,207Indian Rupees in the base case analysis, exceeding three times India's GDP per-capita [approximately USD $13,287 to $39,487 and GBP £10,776 to £32,025]. Sensitivity analyses confirmed the results' robustness. Scenario analysis suggested that a cost reduction of over 75% in drug prices could make most of the interventions cost effective compared with csDMARDs. TNF-α, B cell, and JAK-inhibitors are not cost-effective compared with csDMARDs for patients with RA who have not responded to MTX in India at the current prices. Cost-effectiveness estimates were highly influenced by drug pricing variations. Therefore, reducing the prices of these interventions could enhance affordability, potentially leading to their inclusion in publicly funded health programs.

Analysis of Indian Foreign Exchange Markets: A Multifractal Detrended Fluctuation Analysis (MFDFA) Approach

The objectives of this paper are to analyse the presence of multifractality in daily exchange rates of the US dollar (USD), British Pound (GBP), Euro (EUR), and Japanese Yen (JPY) relative to the Indian Rupee (INR) for a specific period (1999–2018) and to investigate the source of the observed multifractality in these exchange rates. The research examines the multifractal spectra of logarithmic returns (daily price changes) for the four currencies. To investigate the origins of this multifractality, we conduct two transformations on the return series: (a) random shuffling of the original time series of logarithmic returns which disrupts any long-range correlations within the data. And (b) application of phase randomisation on the unaltered series which aims to preserve frequency information while altering timing-related characteristics of the data. We then look at the impact of these transformations on the multifractality. Our findings indicate that all four exchange rates exhibit multifractal characteristics in their return series. The source of multifractality differs between currencies: The USD is primarily driven by the “fat tail” of the distribution (extreme fluctuations). For the GBP and EUR, a combination of long-range correlations and fat tails contributed to multifractality. The JPY is mainly influenced by the broad tail of the distribution (more frequent but smaller fluctuations). These results have implications for policymakers and market participants. Based on these findings, policymakers should consider the specific characteristics of each currency when designing risk management strategies or regulatory interventions.

Thermal performance of an economical air heater for space heating using composite energy storage materials

ABSTRACT Energy storage materials have the potential to improve the performance of thermal systems due to their excellent thermo-physical properties. Different energy storage materials have been tested for different thermal systems and found adequate to improve their thermal performance. Present work focuses, (i) on the development of two different composite energy storage materials (CESM) by mixing graphite black powder (obtained from lithium batteries cells) in paraffin wax and coconut oil, and (ii) testing of these materials for solar space heating inside the two similar air heating systems namely, Model-2 and Model-3. Air heating trials have been conducted on four different configurations by placing CESM-filled containers on the absorber of the tested heaters. Results of natural and forced convective operations have been compared with a similar conventional air heater (Model-1) and also to some other relevant works on air heating systems. Results revealed that Model-3 is the best model. For this system, improved heat transfer was observed at 356.20 W/m2.K, thermal efficiency was observed at about 78.8%, overall heat loss was computed at 5.91 W/m2.K and maximum exhaust air temperature was observed at about 322.05 K. The cost of Model-3 was about $51.14 (₹ 4110 in Indian currency). Model-3 can be easily developed and used for air heating and drying operations under mild cold climate conditions.

Water, sanitation, and hygiene (WASH) practices of mothers and the health status of under-five children: a study from Rural Nayagarh, Odisha

ABSTRACT The objective of this study was to assess water, sanitation, and hygiene (WASH) practices of mothers with under-five children in rural pockets of the Nayagarh district, Odisha and examine how those practices are associated with the health status of children. A cross-sectional household survey was carried out with 370 participants having under-five children in rural pockets of the Nayagarh district, Odisha. A multistage sampling strategy was adopted. Participants were interviewed using a pre-tested structured schedule. Household information was analysed using descriptive statistics; logistic regression models were used to determine the association between mothers’ handwashing practices and the health status of their under-five children. Nearly 74.9% of the households in the sample earned less than 40,000 Indian rupees ($481) annually. Nearly 73% of mothers threw the childrens' faecal waste into drains and open garbage. Diarrhoea was strongly associated with mothers who did not encourage their children to wash their hands (p = 0.007). The frequency of mothers' handwashing before feeding was associated with childrens' episodes of fever, common cold, and cough (p = 0.045). A set of targeted interventions, such as health education and socio-behavioural changes, is needed to address significant WASH factors associated with the health of under-five children in rural areas.

Counterfeit Currency Detection Using Machine Learning

Counterfeit currency detection is a critical aspect of maintaining financial integrity. This paper introduces an innovative methodology for identifying counterfeit Indian rupee notes. By employing advanced image processing techniques and Convolutional Neural Networks (CNNs), specifically ResNet architecture, the proposed system achieves impressive accuracy in distinguishing genuine from counterfeit banknotes. The dataset, meticulously compiled through a combination of web scraping and synthetic printing, ensures robust training and evaluation. Experimental findings underscore the efficacy of the ResNet-based approach, highlighting its superiority over traditional CNN models. This research contributes significantly to bolstering currency security and trust in financial transactions, offering practical insights for combating counterfeit currency challenges.