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Entry of children to primary schools in India marks a sudden shift in the pedagogical approach as play-based pedagogy gives way to formal instruction. This paper argues that children's play motives do not subside when they enter school, rather play takes a more mature form and represents a strong linkage between their thought and reality. The recently introduced National Education Policy 2020 in India mandates a large-scale achievement survey at the age of 8, the fear is that this will lead to formalisation and academisation of early schooling. The paper presents a case study of a school in rural India that follows a play-based pedagogy in the primary years. The study uses dialectical-interactive approach for data collection and analysis. The analysis shows that play creates a pedagogic opportunity for the teacher and children to engage with each other's motives thus creating a shared 'object of activity' that ensures children's motivated engagement in their learning. [ABSTRACT FROM AUTHOR]

The role of services globalization in inclusive growth is already getting attention in the literature. We add to this literature using India as a case study. India's state-level services value added and employment data studied in this paper reveal that globalization-induced opportunities are filtering down to the country's high per capita income states. More significantly, our empirical analysis, motivated by the New Economic Geography literature and the work of Davis and Weinstein (1996, 1999, 2003), suggests that these opportunities are also creating demand linkages throughout the country. Moreover, the wider network of sub-national demand linkages may be getting formed independently of historical income, skill or locational advantages, which has potentially generalizable implications for other services-globalization-led economies. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this study is to develop a methodology for sustainable drinking water management by assessing the existing state of the water supply system in the study area (Allahabad, India). An attempt is made to identify various problems and gaps in the existing system and evolve solutions for the present water supply problems in a GIS framework. Finally, the paper proposes a conceptual framework for sustainable drinking water management. Design/methodology/approach - The study was conducted in four stages. The first stage involved collection of data and background information through various primary and secondary sources including reports and publications of various organizations. This was followed by discussions with various officials of Uttar Pradesh (UP) Jal Nigam (Water Corporation), Jal Sansthan (Water Board), State Ground Water Board, Central Ground Water Board and Municipal Corporation of the city. The second stage involved field studies in a few zones of the city. The third stage involved data input and analysis on a GIS platform, and the fourth stage includes the development of a solution of the present problems and proposing a conceptual framework for ensuring sustainable drinking water management for Allahabad City. Findings - ArcInfo 9.1 has been used as a tool for storing all types of relevant data for analysis and decision making. The various thematic maps include water supply zone map, water deficit localities map, land use map, location of tubewells, overhead tanks, zonal pumping station, ward boundaries, population map, water demand and supply map. Research limitations/implications - Applicability of a partnership between the public and the private sector has to be checked for proper institutional analysis in Allahabad City. Originality/value - The paper assesses the problems in the existing water supply system in Allahabad and proposes to give a GIS-based solution strategy for its sustainability. The proposed GIS-based conceptual framework would improve the current practice of drinking water management and would reduce the present problem of water crisis. The findings of the study would be useful for cities with similar problems in underdeveloped and developing countries. [ABSTRACT FROM AUTHOR]

Health insurance has evolved as a most steady financial management instrument for Indian people who are interested and who are seeking for health care. India health insurance received a major boost after the outbreak of deadly COVID-19 pandemic. During the starting phase of the prevalent pandemic, there has been change in mindset and thought process of individual. The individual opinions saw major transformation about medical and health related issues. The public became more serious and started taking health seriously and individual opinion about medical and health insurance programs also saw major shift. Hence, this study makes an effort to find out the effect of Covid 19 on demand for health insurance policies in Mumbai region. It also tries to understand and to know the perceptions of individual towards buying health insurance policies. It can be concluded that Covid -19 had a positive impact on the buying behaviour of health insurance policy. [ABSTRACT FROM AUTHOR]

AimIn this paper, we assess the degree to which the observed consistency in maternal health-care utilization can be accounted for by social and economic demand determinants at individual and household level on the one hand and community access to health services in terms of health, road and education facilities on the other.Data and methodsData from the three rounds of national family health survey of India (NFHS-1, -2 and -3) conducted in 1992–93, 1998–99 and 2005–06 are used in this analysis. The results of the analysis are presented in two sections. First, statewise profiles of maternal health-care utilization from NFHS-1, -2 and -3 are presented to compare the trends. Second, the influence of demand and access factors estimated from multi-level logistic regression models are presented for selected states of India.ResultsResults reveal that inequalities in maternal health-care utilization by socio-economic status have narrowed because of the impact of complementing factors of greater community access, and social and economical advancement in the south Indian states, where overall maternal health-care coverage is at the top end of the scale. In contrast, in the demographically lagging northern states of India, which are at the bottom end of the health coverage scale, both access and socio-economic demand determinants indicate greater inequalities in maternal health-care utilization.ConclusionLack of access to health care, slow progress in socio-economic conditions and cultural constraints are major determinants of poor maternal health-care coverage among Indian states. [ABSTRACT FROM AUTHOR]

In this paper we derive long run structural relationships for all the three classes, viz. upper, second and ordinary second class, of non-suburban long distance passenger transport demand for Indian railways using annual time series data for 1970–1995. We employ some of the recent developments in multivariate dynamic econometric time series modeling including estimation of long-run structural cointegrating relationships, short-run dynamics and measurement of the effects of shocks and their persistence on evolution of the dynamic passenger transport demand system. The models are estimated using a cointegrating vector autoregressive (VAR) modeling framework, which allows for endogeneity of regressors. The demand systems are found to be stable for all the classes in the long run and they converge to equilibrium in a period of around 2–4 years after a typical system-wide shock. Any disequilibrium in the short-run is corrected in the long-run with adjustments in passenger transport demand and the price variable, i.e. real rate charged per passenger kilometer. Results show that travel demand in all classes would rise with income, although the rise is less than proportionate in the case of ordinary class. High price elasticity in long-run and short-run impulse responses indicate that passenger fare hike could lead to substantial decline in travel demand leading to decline in revenue earnings of the railways. [ABSTRACT FROM AUTHOR]

The nation deserves to learn what India's future energy demand will be in order to plan and implement an energy policy. This energy demand will have to be fulfilled by an adequate mix of existing energy sources, considering the constraints imposed by future economic and social changes in the direction of a more sustainable world. Forecasting energy demand, on the other hand, is a tricky task because it is influenced by numerous micro-variables. As a result, an macro model with only a few factors that may be predicted globally, rather than a detailed analysis for each of these variables, is required. In this work, a hybrid approach is proposed for identifying the optimal generation-based mix of electricity systems in India. This approach is developed by combing Recalling-Enhanced Recurrent Neural Network (RERNN) and Giza Pyramids Construction (GPC). RERNN possesses selective memory features whereas GPC is a meta-heuristic algorithm that deals with different sets of problems. The goal of this approach is to assess the present load requirements and production profile to understand the current requirement and its production methods. Data on regards to electricity load profile involving the generation of all power plants, capacity factors and transmission limits were gathered from different sources including the Indian National Load Dispatch Centre, Central Electricity Authority database, annual reports of India and regional load dispatching centers. The proposal has introduced the RERNN technique to analyze the optimal time series whereas the GPC technique is involved in the optimization of RERNN parameters. The present work is simulated in MATLAB and the performance assessed with different parameters. The present technique gives an effective results in terms of accuracy, computational efficiency and feasibility. [ABSTRACT FROM AUTHOR]

This work presents an economic analysis of a hybrid renewable energy source (HRES) integrated with an energy storage system (ESS) using batteries with a new proposed strategy. Here, the HRES system comprises wind turbines (WT) and a photovoltaic (PV) system. The hybrid WT, PV and energy storage system with battery offer several benefits, in particular, high wind generation utilization rate, and optimal generation for meeting supply-demand gaps. The real recorded data of various parameters of a 22 KV hybrid 'Regen' feeder of 110/22 KV Vagarai Substation of TANTRANSCO in Palani of Tamilnadu in India was gathered, studied for the entire year of 2018, and utilized in this paper. The proposed strategy is the hybridization of two algorithms called Radial Basis Function Neural Network (RBFNN) and Oppositional Elephant Herding Optimization (OEHO) named the RBFNOEHO technique. With the help of RBFNN, the continuous load demand required for the HRES and be tracked. OEHO is used to optimize a perfect combination of HRES with the predicted load demand. The aim of the proposed hybrid RBFNOEHO is to study the cost comparison of the HRES system with the existing conventional base method, energy storage method (ESS) with batteries and with HOMER. The proposed Hybrid RBFNOEHO technique is evaluated by comparing it with the other techniques; it is found that the proposed method yields a more optimal solution than the other techniques. [ABSTRACT FROM AUTHOR]

India's energy security is intricately linked to economic and population growth, accessibility, availability, affordability, and supply and demand. India's quest for energy security is going slow and after a late start. India embraced various domestic efforts and has drawn up supplier relationships around the globe in coal, oil, gas, nuclear, hydroelectric power, and renewable energy. It appears India is not likely to be fully independent of external sources of supply for its energy requirements in the short-term and medium-term. There is no major technological breakthrough in alternative energy to free the country from its energy predicament, thus, India needs to adopt multi-dimensional strategic energy security approaches. In the absence of major oil and gas reserves in Indian territory, the country may be forced down a perilous path that includes a massive increase in the use of coal, associated with environmental concerns, and increasing dependence on external sources. The key focus of the study is to examine the key concerns, trends, challenges, and various options available to India to face the challenges in energy security. [ABSTRACT FROM AUTHOR]

With the technical growth and the reduction of deployment cost for distributed energy resources (DERs), such as solar photovoltaic (PV), energy trading has been recently encouraged to energy consumers, which can sell energy from their own energy storage system (ESS). Meanwhile, due to the unprecedented rise of greenhouse gas (GHG) emissions, some countries (e.g., Republic of Korea and India) have mandated using a renewable energy certificate (REC) in energy trading markets. In this paper, we propose an energy broker model to boost energy trading between the existing power grid and energy consumers. In particular, to maximize the profits of energy consumers and the energy provider, the proposed energy broker is in charge of deciding the optimal demand and dynamic price of energy in an REC-based energy trading market. In this solution, the smart agents (e.g., IoT intelligent devices) of consumers exchange energy trading associated information, including the amount of energy generation, price and REC. For deciding the optimal demand and dynamic pricing, we formulate convex optimization problems using dual decomposition. Through a numerical simulation analysis, we compare the performance of the proposed dynamic pricing strategy with the conventional pricing strategies. Results show that the proposed dynamic pricing and demand control strategies can encourage energy trading by allowing RECs trading of the conventional power grid. [ABSTRACT FROM AUTHOR]

The changing scenario of consumption and production of pulses will have significant influence on the demand-supply prospects of pulses in India. The country as whole, production of redgram had increased marginally (0.45%) during 1980-2012(Overall study period), though there is positive and significant growth in production (2.86%) during 1980-90 (Period-I), mainly due to lower growth during 1991-2012(period-II). The significant growth in production (1.39%) and productivity (1.04%) of bengalgram in the entire period except area (0.35%) was observed. However, growth in greengram production (1.14%) and productivity (1.21%) was found almost similar. In case of blackgram, positive growth rate in area, productivity and production in both the periods have ultimately resulted higher growth rates in the overall period. The growth in total pulses production indicated that growth in area (-0.10%) was negative while it was positive both in production (1.49%) and productivity (1.59%) during period-I. Similar pattern of growth was observed during period-II and in the overall study period. The estimated demand for pulses were 183.62 lakh tonnes over supply of 148.66 lakh tonnes indicating deficit of 34.96 lakh tonnes during 2001-2011. Further, demand for pulses expected to reach 225.36 and 255.16 lakh tonnes in the year 2020 and 2030 respectively. Whereas, supply of pulses will reach 218.50 and 237.00 lakh tonnes in the same period indicating narrow gap between demand and supply in the future. [ABSTRACT FROM AUTHOR]

In response to the Deaton and Dreze (2009) explanation of a downward shift in the calorie Engel curve in terms of lower requirements due to health improvements and lower activity levels in India, we develop an alternative explanation embedded in a standard demand theory framework, with food prices and expenditure (as a proxy for income) cast in a pivotal role. We find robust food price and expenditure effects and shifting food price elasticities. There are shifts in demands due to factors other than lower requirements. So, while the Deaton and Dreze (2009) explanation is not rejected, it is arguable that it is complementary to the demand based explanations. [ABSTRACT FROM AUTHOR]

Most commonly used river water quality models for biochemical oxygen demand (BOD) and dissolved oxygen (DO) simulations are mainly based on advection, decay, settling, and loading functions. Using these concepts, refined river water quality models for BOD and DO simulations are developed in the present work considering a large number of physically based parameters and input variables. The refined models developed can be transformed to some of the commonly used river water quality models, if physically based parameters and input variables are omitted or removed. To test the applicability of the refined models developed and commonly used models, a total of 732 water quality and flow data sets are collected during March 1999–February 2000 from 22 sampling stations of the River Kali in India. River Kali is a highly polluted river in India and receives continuous inflow of untreated point source pollution from municipal and industrial wastes and nonpoint source pollution from agricultural areas. Newton–Raphson technique is used to optimize the model parameters during calibration and the performance of different models are evaluated using error estimation, viz. standard error and mean multiplicative error, and correlation statistics (r2). The results indicate that the BOD–DO models proposed by Camp in 1963 provide better results in comparison to other commonly used models. Moreover, the refined models developed for BOD and DO simulations minimize error estimates and improve correlation between observed and computed BOD and DO values of River Kali. [ABSTRACT FROM AUTHOR]