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Mathematics is not only a subject but it is also a language consisting of many different symbols and relations. Taught as a compulsory subject up the 10th class, students are then able to choose whether or not to study mathematics as a main subject. The present paper discusses mathematical modeling in mathematics education. The article provides models for high school, secondary, and higher mathematics education.

Background: The World Health Organization Astana Declaration of 2018 sees primary healthcare as key to universal health coverage and gives further support to the goal of building sustainable models of community palliative care. Yet evaluating the benefits of such models continues to pose methodological and conceptual challenges. Objective: To explore evaluation issues associated with a community-based palliative care approach in Kerala, India. Design: An illuminative case study using a rapid evaluation methodology. Methodology: Qualitative interviews, documentary analysis and observations of home care and community organising. Results: We appraise a community palliative care programme in Kerala, India, using three linked 'canvases' of enquiry: (1) 'complex' multi-factorial community-based interventions and implications for evaluation; (2) 'axiological' orientations that foreground values in any evaluation process and (3) the status of evaluative evidence in postcolonial contexts. Three values underpinning the care process were significant: heterogeneity, voice and decentralisation. We identify 'objects of interest' related to first-, second- and third-order outcomes: (1) individuals and organisations; (2) unintended targets outside the core domain and (3) indirect, distal effects within and outside the domain. Conclusion: We show how evaluation of palliative care in complex community circumstances can be successfully accomplished when attending to the significance of community care values. Plain language summary: Where are the values in evaluating palliative care? Learning from community-based palliative care provision The evaluation of any intervention or service will inevitably involve a series of decisions on what we measure, what criteria we use to judge whether the intervention has been successful (or not), what type of data we actually collect and what methods we use to do this. When evaluating a range of palliative care interventions, we suggest that these decisions have often been taken in a concealed way and tend to favour relatively narrow quantitative measures linked to end outcomes. Our paper reports on the evaluation of a community-based palliative care intervention on Kerala, India. In it, we suggest that such complex work requires a broader approach to evaluation that: makes the values being used to assess success explicit; draws on a range of data types; is interested in delivery processes; and places the voices of participants at the heart of the assessment. The paper concludes with some broader observations on how these principles might be applied more widely within palliative care. [ABSTRACT FROM AUTHOR]

Although it is well known that vaccines against many infectious diseases confer positive economic externalities via indirect protection, analysts have typically ignored possible herd protection effects in policy analyses of vaccination programs. Despite a growing literature on the economic theory of vaccine externalities and several innovative mathematical modeling approaches, there have been almost no empirical applications. The first objective of the paper is to develop a transparent, accessible economic framework for assessing the private and social economic benefits of vaccination. We also describe how stated preference studies (for example, contingent valuation and choice modeling) can be useful sources of economic data for this analytic framework. We demonstrate socially optimal policies using a graphical approach, starting with a standard textbook depiction of Pigouvian subsidies applied to herd protection from vaccination programs. We also describe nonstandard depictions that highlight some counterintuitive implications of herd protection that we feel are not commonly understood in the applied policy literature. We illustrate the approach using economic and epidemiological data from two neighborhoods in Kolkata, India. We use recently published epidemiological data on the indirect effects of cholera vaccination in Matlab, Bangladesh (Ali et al., 2005) for fitting a simple mathematical model of how protection changes with vaccine coverage. We use new data on costs and private demand for cholera vaccines in Kolkata, India, and approximate the optimal Pigouvian subsidy. We find that if the optimal subsidy is unknown, selling vaccines at full marginal cost may, under some circumstances, be a preferable second-best option to providing them for free. (Contains 14 footnotes, 2 tables, and 8 figures.)

Due to Covid Pandemic, all are heading towards digitization of the process of manual work being conducted in organization. In this paper the current working of the student grading system is reviewed. The mechanical way to device the results is monitored and efforts required are assessed. In rural India, still at many colleges, the student's academic performance is assessed and derived on the basis of preparing results manually by the teachers which require large amount of time. There are certain limitationsobserved with current system. A Mathematical model based Framework is proposed for analysis of academic performance of the student, class and institution. [ABSTRACT FROM AUTHOR]

More than supply the demand for health care usually determines the design of public health services. This is more so when technological developments, including that of information and communication technologies, pierce through the process of utilization of any service by the public. Although prior research papers have focused on the factors that impact on the adoption of information technology, there are limited empirical research works that simultaneously capture technology factors (TAM, TAM2) and end-user development specifc factors (perceived technology usage and intention to recommend) helping healthcare professionals to adopt Health Management Information System (HMIS) software in the healthcare environment. To fill this gap, the present paper used the Technology Acceptance Model (TAM), the extended TAM model (TAM2) and identified the important determinants of user acceptance perceived risk and trust. This is specifcally undertaken in order to describe ESIChealthcare professionals behavioral intention to adopt HMIS software services. The study was conducted in the Employees' State Insurance Corporation (ESIC) main hospital and dispensaries in the Tirunelveli sub-region. The required data were collected from 171 ESIC healthcare professionals in the Tirunelveli sub-region. A Structural Equation Model (SEM) approach was used. Convergence anddivergence with earlier findings were found, confrming that Perceived Usefulness (PU), Perceived Ease of Use (PEOU), social infuence, facilitating conditions and training hadsignificant infuence on the intention of healthcare professionals to adopt HMIS software. The study provideda basis for further refnement of technology adoption model. Improvingperceived usefulness factor (perceived long-term usefulness) may turn healthcare professionals towards adoption of HMIS. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a stochastic Knapsack Problem (KP) based mathematical model for small-scale vegetable sellers in India and solved it by an advanced Genetic Algorithm. The knapsack problem considered here is a bounded one, where vegetables are the objects. In this model, we have assumed that different available vegetables (objects) have different weights (that are available), purchase costs, and profits. The maximum weight of vegetables that can be transported by a seller is limited by the carrying capacity of the vegetable carrier and the business capital of the seller is also limited. The aim of the proposed mathematical model is to maximize the total profit of the loaded/traded items, with a set of predefined constraints on the part of the vegetable seller or retailer. This problem has been solved in a Type-2 fuzzy environment and the Critical Value (CV) reduction method is utilized to defuzzify the objective value. We have projected an improved genetic algorithm based approach, where we have incorporated two features, namely refinement and immigration. We have initially considered benchmark instances and subsequently some redefined cases for experimentation. Moreover, we have solved some randomly generated proposed KP instances in Type-2 fuzzy environment. [ABSTRACT FROM AUTHOR]

At this moment in time, an outbreak of COVID-19 is transmitting from human to human. Different parts have different quality of life (e.g., India compared to Russia), which implies the impact varies in each part of the world. Although clinical vaccines are available to cure, the question is how to minimize the spread without considering the vaccine. In this paper, via a mathematical model, the transmission dynamics of novel coronavirus with quarantine and isolation facilities have been proposed. The examination of the proposed model is set in motion with the boundedness and positivity of the solution, sole disease-free equilibrium, and local stability. Then, the condition for the existence of sole endemic equilibrium and its local stability has established. In addition, the global stability of the endemic equilibrium for a special case has been investigated. Further, it has shown that the system undergoes a transcritical bifurcation. A threshold analysis has also performed to examine the effect of quarantine on transmission dynamics. Lastly, numerical simulations are giving support to theoretical results. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore the nature of the association and the possible existence of a shortrun and long-run relationship between the stock-market indices of South Africa, India and the USA. The idea behind this combination is to know how the stock markets of these three prominent countries are related to each other. The study employs monthly data from the stock indices, namely JALSH (South Africa), NIFTY (India) and NASDAQ (USA) composite from April 2004 to March 2014. After testing for the normality of the data distribution and the stationarity of the time series data, this paper discovered a strong correlation between the stock market indices of South Africa, India and the USA. The correlation among the stock markets is high, particularly between South Africa and India. In addition, the paper attempts to discover the presence of any predictive ability among these markets by applying the Granger causality test. The result indicates that the NASDAQ index has no predictive ability as far as the JALSH and NIFTY indices are concerned. However, the JALSH index has a predictive ability on the NIFTY index. After testing the Granger cause relationship, the existence of a long-run and short-run relationship is tested. The long-run relationships among the stock market indices are analysed, following the Johansen and Juselius multivariate cointegration approach. The result suggests the absence of a long-run relationship among the three stock market indices. Short-run relationship is investigated with the Vector Autoregression (VAR) model, and the outcome obtained shows that both the USA and the South African stock markets are predicted only by their own past lags. However, the Indian stock market is seen to be a function of its own past lags and the past lags of the South African stock index. [ABSTRACT FROM AUTHOR]

The long-term evolution of multi agent multi criteria decision making (MCDM) and to obtain sustainable decision a novel methodology is proposed based on evolutionary game theory. In this paper multi agent MCDM is represented as an evolutionary game and the evolutionary strategies are defined as sustainable decisions. Here we consider the problem of decision making in Indian Tea Industry. The agents in this game are essentially Indian Tea Estate owner and Indian Tea board. The replicator dynamics of the evolutionary game are studied to obtain evolutionary strategies which could be defined as sustainable strategies. The multi agent MCDM in Indian Tea Industry is considered under different socio-political and Corporate Social Responsibility scenario and groups of Indian Tea Industry. Again, the impacts of imprecision and market volatility on the outcome of some strategies (decisions) are studied. In this paper the imprecision on the impact of the strategies are modelled as fuzzy numbers whereas the market volatility is taken into account as white noise. Hence the MCDM problem for Indian Tea Industry is modelled as a hybrid evolutionary game. The probabilities of strategies are obtained by solving hybrid evolutionary game and could be represented as a Dempster-Shafer belief structure. The simulation results facilitate the Decision Makers to choose the strategies (decisions) under different type of uncertainty. [ABSTRACT FROM AUTHOR]

The design and tuning of controllers for the industrial process is an art, which plays a vital role in many of the process control industries. The industries such as sugar, chemical, paper and other process control-based industries hold the nature of non-linearity due to their uneven distribution of load influence with disturbances. This paper highlights the study and investigation of different controlling parameters associated with the sugar industry which is located in the southern region of Tamil Nadu, India. After the analysis of various processes, the impact of controlling strategy needs to be implemented in an advanced way to minimize the resource utilization with high productivity. The behaviour of various process parameters, such as flow, temperature, level, pressure, is studied and one of these has been discussed in detail along with the controller design. The controller, such as proportional, integral, derivative, has been modified with advanced control phenomena and applied to process model with the presence of delay time provides the excellent tracking of operating point to bring the stability of a certain process in a tremendous manner. [ABSTRACT FROM AUTHOR]

Low-temperature drying (withering) is the first stage in black tea processing. Determination of appropriate end moisture content of green tea leaf as well as temperature and relative humidity (RH) maintained during withering eventually aid the final quality of the processed tea. Therefore, the tea leaf withering (partial drying) properties were evaluated in an environmental chamber using mathematical models. The temperatures and RH considered were 25, 30, 35 °C and 80, 85, 90%, respectively. A total of nine combinations of temperature and RH were considered by keeping one parameter constant. The conditions were taken adhering to that of the climatic conditions of Assam, India. The withering data from experiments were fitted into five drying models using the curve fitting method. The Page model gave better predictions with an R² value of 0.9989 at 30 °C temperature and 90% RH. The total phenolic and flavonoid contents of the tea leaf samples were evaluated. The best results were 50.60 ± 0.02 mg GAE·g-1 (GAE - gallic acid equivalent) and 22.47 ± 0.01 mg QCE·g-1 (QCE - quercetin equivalent) at 30 °C withering temperature. [ABSTRACT FROM AUTHOR]

Competition for the 2010 Daniel H. Wagner Prize for Excellence in Operations Research Practice provided the five finalist papers featured in this special issue of Interfaces. The prestigious Wagner Prize emphasizes quality and originality of mathematical models along with clarity of written and oral exposition. Authors from IBM's Watson Research Center won the competition with their innovative, diverse suite of models to improve critical choices for managing skilled personnel, choices so important in service industries; their models have been implemented in the IBM Integrated Technology Services business. A finalist team from Georgia Tech joined with the US Centers for Disease Control to solve a physician's often challenging problem of creating the best new schedule for a person who misses one or more previously scheduled vaccinations; the team's optimization approach is implemented in software now freely available to American physicians, and in software with Canadian rules soon to be available to Canadian physicians. A team from Kimberly-Clark Latin America and Penn State University developed optimization models to improve production and inventory control; after overcoming slow solution speeds with heuristics that furnish good solutions in minutes, the models have so far been implemented in Kimberly-Clark plants in five countries. A finalist team from the University of Texas at Dallas worked with Blockbuster, Inc. to improve efficiency and speed in Blockbuster's central system to fill orders from the company's numerous retail stores; implementation of the resulting optimization models led to reduced costs and more balanced workloads in the Blockbuster order-fulfillment center where different processing departments compete for shared resources. Finally, an India-based team from GE Global Research developed models to improve the selection of customers who receive special product offers from a GE commercial bank in Europe; the team's diverse models are now helping the GE bank to improve its customer responses. [ABSTRACT FROM AUTHOR]

Introduction: Although India has made significant progress in institutional delivery after the implementation of the National Rural Health Mission under which the Janani Suraksha Yojana (JSY) is a sub-programme which played a vital role in the increase of institutional delivery in public facilities. Therefore, this paper aims to provide an understanding of the JSY coverage at the district level in India. Further, it tries to carve out the factors responsible for the regional disparity of JSY coverage at district levels. Methods: The study used the National Family Health Survey data, which is a cross-sectional survey conducted in 2015–16, India. The sample size of this study was 148,145 women aged 15–49 years who gave last birth in the institution during 5 years preceding the survey. Bivariate and multivariate regression analysis was used to fulfill the study objectives. Additionally, Moran's I statistics and bivariate Local Indicator for Spatial Association (LISA) maps were used to understand spatial dependence and clustering of JSY coverage. Ordinary least square, spatial lag and spatial error models were used to examine the correlates of JSY utilization. Results: The value of spatial-autocorrelation for JSY was 0.71 which depicts the high dependence of the JSY coverage over districts of India. The overall coverage of JSY in India is 36.4% and it highly varied across different regions, districts, and even socioeconomic groups. The spatial error model depicts that if in a district the women with no schooling status increase by 10% then the benefits of JSY get increased by 2.3%. Similarly, if in a district the women from poor wealth quintile, it increases by 10% the benefits of JSY also increased by 4.6%. However, the coverage of JSY made greater imperative to understand it due to its clustering among districts of specific states only. Conclusion: It is well reflected in the EAGs states in terms of spatial-inequality in service coverage. There is a need to universalize the JSY programme at a very individual level. And, it is required to revisit the policy strategy and the implementation plans at regional or district levels. [ABSTRACT FROM AUTHOR]

The paper proposes a structured model for evaluating vendor selection using the analytical hierarchy process (AHP) and fuzzy AHP. The model is developed using evidence from an empirical study. The paper aims to demonstrate how the model can help in solving such decisions in practice. A usability evaluation of the AHP-based model with three vendors is discussed. It also examines the structure of the decision hierarchy, whether it can represent vendor selection decisions in reality and whether it covers all key factors affecting vendor selection choices. The effectiveness of the AHP model is illustrated using a company in the southern part of India and the results validated using fuzzy AHP. [ABSTRACT FROM AUTHOR]

Background: Equity and justice in healthcare payment form an integral part of health policy and planning. In the majority of low and middle-income countries (LMICs), healthcare inequalities are further aggravated by Out of Pocket Expenditure (OOPE). This paper examines the pattern of health equity and regional disparities in healthcare spending among Indian states by applying Andersen's behavioural model of healthcare utilization. Methods: The present study uses data from the 66th quinquennial round of Consumer Expenditure Survey, of the National Sample Survey Organization (NSSO), conducted in 2009-10 by Ministry of Statistics and Programme Implementation (MoSPI), Government of India (GoI). To measure equity and regional disparities in healthcare expenditure, states have been categorized under three heads on the basis of monthly OOPE i.e., Category A (OOPE > =INR 100); Category B (OOPE between INR 50 to 99) and Category C (OOPE < INR 50). Multiple Generalised Linear Regression Model (GLRM) has been employed to explore the effect of various socio-economic covariates on the level of OOPE. Results: The gap in the ratio of average healthcare spending between the poorest and richest households was maximum in Category A states Category B (richest/poorest = 14.60), followed by (richest/poorest 11.70) and Category C (richest/poorest 11.40). Results also indicate geographical concentration of lower level healthcare spending among Indian states (e.g., Odisha, Chhattisgarh and all the north-eastern states). Results from the multivariate analysis suggest that people residing in urban areas, having higher economic status, belonging to non-Muslim communities, non-Scheduled Tribes (STs), and non-poor households spend more on healthcare than their counterparts. Conclusions: In spite of various efforts by the government to reduce the burden of healthcare spending, widespread inequalities in healthcare expenditure are prevalent. Households with high healthcare needs (SCs/STs, and the poor) are in a more disadvantaged position in terms of spending on health care. It has also been observed that spending on healthcare was comparatively lower among backward or isolated states. No doubt, the overall social security measures should be enhanced, but at the same time, looking at the regional differences, more priority should be assigned to the disadvantaged states to reduce the burden of OOPE. It is proposed that there is need to increase government spending, especially for the disadvantaged states and population, to minimise the burden of OOPE. [ABSTRACT FROM AUTHOR]

Healthcare consumers may be behaving to some extent based on the nature of healthcare being a necessity or otherwise. The choice of either of public and private providers may depend upon factors like availability, accessibility, cost and quality. To some extent, this is revealed through their elasticities based on income, cost, quality and socio-economic factors. Objective of this paper is to explore the demand for healthcare services in India and estimate consumers' elasticities to these factors. Using logit results we find that an individual may choose his preference for private or public based on distance of facility from residence. It may also depend whether it is rural or urban area and whether the income levels of state are below or above all India average. Comparing our results for two all India surveys, it is observed that people's perception and thus preferences are mostly based on choices of nearby location, suitable timings, presence of medical personnel and less waiting time. The presence of insurance either by a national or state sponsored scheme seems to have changed the nature of healthcare demand in India from a stark necessity to a matter of better choice. [ABSTRACT FROM AUTHOR]

Common information model (CIM) in vogue represents transmission and distribution components, and market operations in the perspective of electrical system, as unified modeling language (UML) objects. UML is object centric. CIM can offer interoperability and facilitate model exchange for large systems and is being adopted by many utilities. However, dealing effectively with multiple business processes is the backbone of the restructured power systems. Since CIM lacks chronological process sense, this has to be superimposed on CIM models, which is not easy due to inherent limitations of UML. To overcome this, this paper proposes to utilize business process modeling notation (BPMN) standards as a kind of pre-processor. BPMN is used to represent process centric interoperability requirements as business objects. UML object representation in CIM model is derived subsequently from it. The proposal is illustrated with an application use case—deriving CIM model of day-ahead market (DAM) transaction of distribution company, from its business process representation. Semantic model of DAM transaction using CIM IEC 62325 (Markets) and extensions required are presented with a sample Indian system. DAM models in BPMN and CIM can be utilized to build an efficient software application. [ABSTRACT FROM PUBLISHER]

This paper is an attempt to study the negative impact of Psychological Contract Breach on Organisational Citizenship Behaviour in India and to explore the mediating effect of Psychological well-being of employees. It's classic argument between the social exchange theory and the self-determination theory. A regression analysis is used to study the variables. The results confirm that positive organisational behaviours suppress the influence of psychological contract breach. [ABSTRACT FROM AUTHOR]

In this paper, we have considered a mathematical model that deals with the effectiveness of the measures that may be helpful for reducing the spread of the COVID-19 virus in the society. Here we have illustrated the importance of lock down in controlling and maintaining the spread of the COVID-19 virus. The impact of the virus on the susceptible population has been considered in the model. Also, we have taken into account the susceptible population, which by taking preventive measures viz., by having strong immunity, maintaining social distancing, wearing PPE kits and masks etc., is able to reduce the possibility of getting infected from the virus. Local as well as global stability of the equilibrium points of the model have been studied using Lyapunov function and the geometrical approach techniques. Basic reproduction number has also been obtained by using the next generation matrix. To show the effectiveness of the model, different cases obtained by varying the parameters involved in the model have been considered. A comparison between the actual number of infected cases in India and that obtained by the proposed model, showing the effectiveness of the proposed model, has also been carried out. [ABSTRACT FROM AUTHOR]

Background: Equitable access to healthcare for rural, tribal, and underprivileged people has been an emerging area of interest for researchers, academicians, and policymakers worldwide. Improving equitable access to healthcare requires innovative interventions. This calls for clarifying which operational model of a service innovation needs to be strengthened to achieve transformative change and bring sustainability to public health interventions. The current study aimed to identify the components of an operational model of mobile medical units (MMUs) as an innovative intervention to provide equitable access to healthcare. Methods: The study empirically examined the impact of scalability, affordability, replicability (SAR), and immunization performance on the sustainability of MMUs to develop a framework for primary healthcare in the future. Data were collected via a survey answered by 207 healthcare professionals from six states in India. Partial least squares structural equation modeling (PLS-SEM) was conducted to empirically determine the interrelationships among various constructs. Results: The standardized path coefficients revealed that three factors (SAR) significantly influenced immunization performance as independent variables. Comparing the three hypothesized relationships demonstrates that replicability has the most substantial impact, followed by scalability and affordability. Immunization performance was found to have a significant direct effect on sustainability. For evaluating sustainability, MMUs constitute an essential component and an enabler of a sustainable healthcare system and universal health coverage. Conclusion: This study equips policymakers and public health professionals with the critical components of the MMU operational model leading toward sustainability. The research framework provides reliable grounds for examining the impact of scalability, affordability, and replicability on immunization coverage as the primary public healthcare outcome. [ABSTRACT FROM AUTHOR]

Construction process activities are very complex in nature and there have been attempts to simulate them via numerous methods. Manual work, which constitutes a large proportion of total construction in India and developing countries, requires emphasis. Field data-based mathematical simulations develop an empirical relation between inputs and outputs; once the model is developed and weaknesses have been identified, methods can be easily improved and optimised for output goals. This paper covers in detail the process of developing models for the rebar cutting subactivity of reinforced concrete construction in residential buildings. These models are evaluated using sensitivity analysis, optimisation techniques and reliability analysis and are validated using artificial neural networks. [ABSTRACT FROM AUTHOR]

Given limited resource availability in a developing nation like India, faced with high incidences of crime, it is important to optimize on the resources spent in combating crime by channelling them to proper direction. This requires an understanding of the actual and overall level of crime across India. Our paper provides a complete understanding of the various indicators of violent crime and the determinants of these crimes in India using district level data for three census years, namely, 1981, 1991 and 2001. We construct three alternative crime-burden indices. Including a variable like voter turnout in state election at the district level, we document significant impact of public awareness to reduce and combat crime. The constructed crime burden index shows that states located in northern parts of India have more incidences of crime compared to states in the south. We also find that our estimated crime-burden indices tend to report in general a higher level of crime-burden than the average based index. This suggests controlling for the factors beyond population while constructing the aggregate crime-burden index for any country is essential. Our work although is limited to the Indian data, we however, believe that this can be easily applied to various other countries. [ABSTRACT FROM AUTHOR]

This paper provides evidence on the patterns of multiproduct firm production in a large developing country, India, during a period that spans market reforms. In the cross-section, multiproduct firms in India look remarkably similar to their U.S. counterparts. The time-series patterns, however, exhibit important differences. In contrast to evidence from the United States, product churning, particularly product rationalization, is far less common in India. We find no link between product rationalization and output tariff declines following India's 1991 trade liberalization. The lack of "creative destruction" is consistent with the role of industrial regulation in preventing an efficient allocation of resources. [ABSTRACT FROM AUTHOR]

Background: This paper explores the heterogeneities in antenatal care (ANC) utilization in India's most populated state, Uttar Pradesh. Taking an intersectionality lens, multiple individual- and district-level factors are used to identify segments of any antenatal care usage in Uttar Pradesh Objective: This paper seeks to understand the multilevel contexts of ANC utilization. The planning and programming challenge is that such knowledge of contextual specificity is rarely known upfront at the initial stages of planning or implementing an intervention. Exploratory data analysis might be needed to identify such contextual specificity. Methods: Tree-structured regression methods are used to identify segments and interactions between factors. The results from the tree-structured regression were complemented with multilevel models that controlled for the clustering of individuals within districts. Results: Heterogeneities in utilization of any ANC were observed. The multiple segments of ANC utilization that were developed went from a low utilization of 23.7% for respondents who were not literate and did not have home ownership to a high of 82.4% for respondents who were literate and at the highest level of wealth. Key variables that helped define the segments of ANC utilization include: woman's literacy, ownership of home, wealth index, and district-level sex ratio. Based on the multilevel model of any ANC utilization, cross-level interactions also were obtained between sex ratio and ownership of home as well as between sex ratio and literacy. Increases in sex ratio increased the influence of ownership of home on any ANC, while increases in sex ratio reduced the impact of woman's literacy on receiving any ANC. Conclusion: We argue that a focus on heterogeneous segments of utilization can help build knowledge of the mechanisms that underlie inequities in maternal health utilization. Such knowledge of heterogeneity needs to be incorporated in contextualizing interventions to meet a variety of recipients' needs. [ABSTRACT FROM AUTHOR]

In this paper we develop and test a theory of childhood mortality after the first month of life. Parents are assumed to have well-defined family size and sex composition objectives and to face severe budget constraints. In this set of circumstances, it is understandable that they will make allocative decisions that will affect the survival probabilities of children. These decisions and the environmental influences on mortality are the basic forces which determine whether a child will survive through the post-neonatal period. The model is tested with survey data from rural Uttar Pradesh, India. The results are consistent with the hypothetical framework discussed above. The burden of this pattern of choice is felt particularly strongly by female births. [ABSTRACT FROM AUTHOR]

Abstract: The advances in robotics, in the last ten years, have enabled robot technology to solve many practical problems that humans encounter in day-to-day activities. But, even today manual scavenging of the sewage is practiced in urban areas of India, wherein man enter the manholes and clean the scales and clogs in the sewage pipelines manually with virtually no technical equipment. This practice might jeopardize the lives of humans; therefore, a sewage cleaning robot is essential to replace the human intervention. The conventional sewage cleaning robots available are not capable and effective in cleaning a variable diameter pipelines. In order to overcome this issue, an attempt has been is made to design and develop a reconfigurable type sewage cleaning mobile manipulator, which can efficiently clean the scales and clogs formed in the variable diameter sewage pipeline. A conceptual model of the manipulator has been created in solid model using solid works. It will give a clear understanding of the manipulator and its subsystem interactions. A prototype model of the manipulator has been developed based on the design concept and its working environment i. e, various goals that robot has to do after entering the sewage pipe and hence the functional requirements are finalized. It consists of various links and joints. The joints are drive through the various motors which are discussed in the paper. Preliminary investigations are carried out on the developed prototype model and some of the results are discussed in the paper. [Copyright &y& Elsevier]

This paper examines the impact of regulatory reform on productivity growth and its components for Indian banks from 1992 to 2009. We estimate parametric and nonparametric efficiency frontiers, followed by Divisia and Malmquist indexes of total factor productivity, respectively. To account for technology heterogeneity among ownership types, we use a metafrontier approach. Results are consistent across methodologies and show sustained productivity growth, driven mainly by technological progress. Furthermore, results indicate that different ownership types react differently to changes in the operating environment. The position of foreign banks becomes increasingly dominant, and their production technology becomes the best practice in the industry. [ABSTRACT FROM AUTHOR]

This paper uses the recent approach of multidimensional deprivation measures to provide a comprehensive and wide ranging assessment of changes to living standards in India during the period, 1992/93-2004/5. This covers the reforms and the immediate post reforms time periods. The study is the first to be based on the simultaneous use of two parallel data sets, namely the National Sample Survey (NSS) and National Family Health Survey (NFHS) data sets, covering proximate rounds and near identical time periods. The results allow a check of consistency on the picture of deprivation in India between these two data sets. The study is conducted both at regionally disaggregated levels and by socio economic groups. The deprivation dimensions range widely from the conventional expenditure dimensions to non-expenditure dimensions such as access to drinking water and clean fuel, to health dimensions such as child stunting and the mother's BMI. The use of decomposable deprivation measures allows the identification of regions, socio economic groups and deprivation dimensions that are contributing more than others to total deprivation. [ABSTRACT FROM AUTHOR]

The issue of ranking higher education institutions has drawn much attention as of late. Many ranking models are being introduced; however, only a few of them incorporate quality dimensions rather than just absolute number of published papers, awards gained, etc. As a possible remedy to the issue, we applied statistical I-distance method on a dataset presented by SCImago Institutions Rankings methodology. Results pointed out that quality indicators such as 'Excellence Rate' and 'Normalized Impact' are far more important than gross number of published papers. In addition, a comparison of scientific output between China and India is elaborated upon. [ABSTRACT FROM AUTHOR]

Link performance functions commonly used for traffic assignment are often based on Volume Delay Functions (VDF) developed for homogeneous traffic. However, VDFs relating stream speed to the volume of traffic based on homogeneous lane-based traffic are not adequate for traffic assignment in developing countries due to the heterogeneous nature of traffic that is characterized by a mix of a wide range of vehicle classes with significant differences in static and dynamic characteristics and an imperfect lane discipline. Unfortunately, the use of VDFs similar to those for homogeneous traffic flow situations imposes strong restrictions considering two respects: 1) travel times at path and link levels can be obtained for an aggregated stream but not for individual vehicle types; 2) the effect of varying composition and asymmetric interactions is captured only to a limited extent by converting all vehicles into equivalent Passenger Car Unit (PCU). Hence, this paper proposes the development of VDFs specific to different classes of heterogeneous traffic, as it is more realistic in traffic assignment than the use of the same VDF for all classes of vehicles in a link. This study is aimed at developing models to determine the speed of each vehicle class as a function of flow and composition for six lane roads with heterogeneous traffic based on data obtained from Chennai city, India. Heterogeneity in this study mainly refers to differences in vehicle types (two-wheeler, car, bus, etc.) participating in mixed traffic. To develop multiple user class VDFs, the speed and flow of each vehicle class for a wide range of traffic flow conditions need to be recorded. As this is not possible using field measurements, an established micro-simulation model (HETEROSIM) is used for determining speeds for each vehicle type by systematically varying the volume and composition levels over a range of values that represent relevant and practical traffic conditions observed in six lane divided roads in Chennai city. The proposed delay functions are different from standard single user class VDFs in three key respects: first, they enable more realistic behaviour by modelling differences in class wise speeds at a given volume and composition level; second, they allow for capturing asymmetric interactions of different vehicle types on an average speed of a given vehicle class. Finally, speed-flow relationships for each class are also allowed to vary across volume levels which enable the representation of differential interactions at different levels of congestion in mixed traffic. The need for homogenizing the volumes in terms of a single class is obviated. The models significantly outperformed single class VDFs in both calibration and validation datasets. Further, the proposed models are used for analyzing heterogeneous traffic characteristics. Empirical evidence of asymmetric interactions and the impact of composition on classwise performance are also found and quantified. Finally, two applications of the proposed models are demonstrated for the level of service analysis of different classes and impact analysis of excluding some classes. The proposed models may have applications such as determining class wise road user costs and performance measures (e.g. emissions) that depend on class-specific speeds. [ABSTRACT FROM AUTHOR]

Background: Sustainability is the holy grail of many development projects, yet there is limited evidence about strategies that effectively support transition of programs from donor funding to national governments. The first phase of Avahan, the India AIDS Initiative supported by the Bill and Melinda Gates Foundation (2003--2009), aimed to demonstrate an HIV/AIDS prevention program at scale, primarily targeted at high-risk groups. During the second phase (2009--2013), this large-scale program will be transitioned to its natural owners: the Government of India and local communities. This paper describes the evaluation design for the Avahan transition strategy. Methods/Design: A detailed logic model for the transition was developed. The Avahan transition strategy focuses on three activities: (1) enhancing capacities among communities, non-governmental organizations (NGOs), and government entities, in line with India's national AIDS control strategy; (2) aligning technical and managerial aspects of Avahan programs with government norms and standards; and (3) promoting and sustaining commitment to services for most-at-risk populations. It is anticipated that programs will then transfer smoothly to government and community ownership, become institutionalized within the government system, and support a sustained HIV/AIDS response. The research design evaluates the implementation and effectiveness of (1) activities undertaken by the program; (2) intermediate effects including the process of institutionalization and the extent to which key Avahan organizational procedures and behaviors are integrated into government systems; and (3) overarching effects namely the impact of the transition process on the sustained delivery of HIV/AIDS prevention services to high-risk groups. Both qualitative and quantitative research approaches are employed so that the evaluation will both assess outcomes and explain why they have occurred. Conclusions: It is unusual for donor-supported projects in low- and middle-income countries to carefully plan transition processes, and prospectively evaluate these. This evaluation is designed so as to both inform decision making throughout the transition process and answer larger questions about the transition and sustainability of donor programs. [ABSTRACT FROM AUTHOR]

This paper compares economic outcomes across areas in India that were under direct British colonial rule with areas that were under indirect colonial rule. Controlling for selective annexation using a specific policy rule, I find that areas that experienced direct rule have significantly lower levels of access to schools, health centers, and roads in the postcolonial period. I find evidence that the quality of governance in the colonial period has a significant and persistent effect on postcolonial outcomes. [ABSTRACT FROM AUTHOR]

Climate change associated with sea level rise (SLR) is one of the major environmental concerns of today. This paper presents an assessment of the impacts of sea level rise on the coastal zone of Kanyakumari District in Tamilnadu, India. Digital Elevation Model (DEM) combined with overlay techniques in GIS are used in determining the inundation zones along the coastal region. The analysis evaluated the impact on coastal fishing villages, landuse, tourist spots and sensitive areas under threat. The vulnerability of the coastal areas in Kanyakumari to inundation was quantified, based on the projected sea level rise scenarios of 0.5 and 1 m. Our findings reveal that approximately 13 km2 of the land area of Kanyakumari would be permanently inundated due to SLR. This would result in loss of land, alteration of the coastal zone and affects coastal ecosystem. From the study, the mitigation measures (engineering measures) and Coastal Zone Management practices that can be taken to protect human life and property from sea level rise are suggested. [ABSTRACT FROM AUTHOR]

This paper deals with the mathematical modeling of the second wave of COVID-19 and verifies the current Omicron variant pandemic data in India. We also we discussed such as uniformly bounded of the system, Equilibrium analysis and basic reproduction number R 0 . We calculated the analytic solutions by HPM (homotopy perturbation method) and used Mathematica 12 software for numerical analysis up to 8th order approximation. It checked the error values of the approximation while the system has residual error, absolute error and h curve initial derivation of square error at up to 8th order approximation. The basic reproduction number ranges between 0.8454 and 2.0317 to form numerical simulation, it helps to identify the whole system fluctuations. Finally, our proposed model validated (from real life data) the highly affected five states of COVID-19 and the Omicron variant. The algorithm guidelines are used for international arrivals, with Omicron variant cases updated by the Union Health Ministry in January 2022. Right now, the third wave is underway in India, and we conclude that it may peak by the end of May 2022. [ABSTRACT FROM AUTHOR]

In this study, we formulate an eight-compartment mathematical model with vaccination as one of the compartments to analyze the dynamics of COVID-19 transmission. We examine the model's qualitative properties, such as positivity and boundedness of solutions, and stability analysis of the illness-free equilibrium with respect to the basic reproduction number. We estimate ten significant parameters and also compute the magnitude of the basic reproduction number for India by fitting the proposed model to daily confirmed and cumulative confirmed COVID-19 cases in India. Sensitivity analysis with respect to basic reproduction number is conducted, and the main parameters that impact the widespread of disease are determined. We further extend this model to an optimal control problem by including four non-pharmaceutical and pharmaceutical intervention measures as control functions. Our numerical results show that the four control strategy has greater impact than the three control strategies, two control strategies, and single control strategies on reducing the dynamics of COVID-19 transmission. [ABSTRACT FROM AUTHOR]

In a series of research articles El-khorazaty, Horne and Suchindran have showed how one can derive for any given population indirectly various childbearing and Bongaart fertilityinhibiting indices using only given information on the ASFRs, and the mathematical and regression models suggested by them. Very recently Bongaart revised his old model and suggested a set of new revised formulae to estimate various fertility-inhibiting indices. Following El-Khorazaty and Horne it is aimed to show in the present paper how one can derive various Bongaart revised fertility-inhibiting indices from the given information on various childbearing indices which were further seen derived from the only given information on TFR and a set of regression models that were earlier suggested by the first author and it is shown that the present study succeed in giving meaningful estimates for India its States, UTs, and Districts. Various regression models referring to estimation of childbearing indices used in this study were developed earlier by Ponnapalli using the state level time series of ASFRs overtime of the SRS of India and Horne et al., mathematical model. The regression models used in indirect estimation of the fertility-inhibiting indices from the TFR and also from the childbearing indices were developed by Ponnapalli using the Bongart indices of the DHS surveys earlier given by Bongaart in his revised recent study. [ABSTRACT FROM AUTHOR]

This paper describes experience with application of operations research techniques in planning new roads and social service centers for the Dharampur area in India. The work involved designing a road network using a minimal spanning tree algorithm; selecting the number and location of the service centers to be constructed over a five year period using a set covering algorithm and developing a schedule for the construction of the service centers using dynamic programming. Substantial economic benefits resulted from using the mathematical models. The experience shows that operations research models can be useful in providing an objective rationale for administrative decisions, thus playing an important role in the resolution of political conflict. [ABSTRACT FROM AUTHOR]

This paper presents a reliable mathematical method to predict the energy generation from grid connected photovoltaic plant of different commercially used technologies in different zones of India. Global horizontal insolation (GHI) and daytime temperature are the two major parameters affecting the output of photovoltaic (PV) plant. Depending on those two major parameters, India is classified into 15 climatic zones. Typical Meteorological Year data were collected from National Renewable Energy Laboratory to classify India in different climatic zones. Energy generation of different commercially used PV technologies in different climatic zones of India is predicted using proposed mathematical method. These results show a decisive study to choose the best PV technology for different climatic zones of India. Results predict that in almost all climatic zones, amorphous silicon (a-Si) is the best suitable PV technology. In very low-temperature zones, irrespective of GHI, the second best suitable PV technology is mono and cadmium telluride (CdTe) as generation from these two technologies is same. Whereas in other climatic zones, after a-Si the best suitable is CdTe PV technology. Predicted energy generation is validated with the 1-year generation of 2014 from 15 working PV plants of different technologies. Predicted generation is in good co-relation with the actual real-time generation from the PV plants. [ABSTRACT FROM AUTHOR]

Background: Cancer remains an escalating and challenging public health issue. The management, especially palliative care (PC), is disintegrated and out of reach of in need patients. The overall aim of the project is to develop a feasible and scalable Comprehensive Coordinated Community based PC model for Cancer Patients (C3PaC); congruent with socio-cultural, context and unmet needs in north India. Methods: A mixed method approach will be used for three-phased pre- and post-intervention study in one of the districts of North India, having a high incidence of cancer. During phase I, validated tools will be used for quantitative assessment of palliative needs among cancer patients and their caregivers. Barriers and challenges for provision of palliative care will be explored using in-depth interviews and focus group discussions among participants and health care workers. The findings of phase I along with inputs from national experts and literature review will provide inputs for the development of the C3PAC model in phase II. During phase III C3PAC model will be deployed over a period of 12 months and its impact assessed. Categorical and continuous variables will be depicted as frequency (percentages) and mean ± SD/median (IQR) respectively. Chi-square test/Fischer test, independent samples Student t-tests and Mann–Whitney U tests will be used for categorical, normally and non-normally distributed continuous variables, respectively. Qualitative data will be analyzed using thematic analysis using Atlas.ti 8 software. Discussion: The proposed model is designed to address the unmet palliative care needs, to empower community-based healthcare providers in comprehensive home-based PC and to improve the quality of life of cancer patients and caregivers. This model will provide pragmatic scalable solutions in comparable health systems particularly in low- and lower-middle Income countries. Trial registration: The study has been registered with the Clinical Trial Registry-India (CTRI/2023/04/051357). [ABSTRACT FROM AUTHOR]

This work aims at providing a concise review of various agri-food models that employ fractional differential operators. In this context, various mathematical models based on fractional differential equations have been used to describe a wide range of problems in agri-food. As a result of this review, we found out that this new area of research is finding increased acceptance in recent years and that some reports have employed fractional operators successfully in order to model real-world data. Our results also show that the most commonly used differential operators in these problems are the Caputo, the Caputo–Fabrizio, the Atangana–Baleanu, and the Riemann–Liouville derivatives. Most of the authors in this field are predominantly from China and India. [ABSTRACT FROM AUTHOR]

In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people's increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios—in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program are successful measures in significantly controlling the size of infected population. We show that for a country like India, a reduction in contact rate by 50% compared to a reduction of 10% reduces death from 0.0268 to 0.0141% of population. Similarly, for a country like Italy we show that reducing contact rate by half can reduce a potential peak infection of 15% population to less than 1.5% of population, and potential deaths from 0.48 to 0.04%. With respect to vaccination, we show that even a 75% efficient vaccine administered to 50% population can reduce the peak number of infected population by nearly 50% in Italy. Similarly, for India, a 0.056% of population would die without vaccination, while 93.75% efficient vaccine given to 30% population would bring this down to 0.036% of population, and 93.75% efficient vaccine given to 70% population would bring this down to 0.034%. [ABSTRACT FROM AUTHOR]

Since 2015, the United Nations sustainable development goals (SDGs) agenda 2030 has been designed with 17 goals, 169 targets, and 232 unique indicators to help address environmental, development, and sustainability issues globally. India, like other developing nations, desired to achieve its vision 2030 targets. Several authors studied India's SDGs with different approaches. However, none of the studies explores the concept of neutrosophic programming (NP). It is against this drawback; this study presents an optimization model for India's socio-economic and environmental goals based on the NP concept. The NP model is capable of handling indeterminacy in optimization-related problems for which other techniques do not. The formulated models simultaneously optimized the gross domestic product (GDP) growth, electricity consumption, and greenhouse gas (GHG) emissions. The solutions revealed that the degree of satisfaction for the goals related to GDP, electricity consumption, and GHG emissions could be achieved partially. Also, it suggested the required optimal number of employment for each economic sector to achieve India's vision 2030. The SDGs model was further solved with the goal programming (GP) technique and compared with the NP results to validate the proposed concept. It has been found that the proposed model gives a better compromise solution than the GP model. The study can help and guide policymakers in working toward vision 2030 attaintment. Other interested researchers can use the concept in other countries to help decision-makers understand managerial policy implications. [ABSTRACT FROM AUTHOR]

There have been considerable losses in terms of human and economic resources due to the current coronavirus pandemic. This work, which contributes to the prevention and control of COVID-19, proposes a novel modified epidemiological model that predicts the epidemic's evolution over time in India. A mathematical model was proposed to analyze the spread of COVID-19 in India during the lockdowns implemented by the government of India during the first and second waves. What makes this study unique, however, is that it develops a conceptual model with time-dependent characteristics, which is peculiar to India's diverse and homogeneous societies. The results demonstrate that governmental control policies and suitable public perception of risk in terms of social distancing and public health safety measures are required to control the spread of COVID-19 in India. The results also show that India's two strict consecutive lockdowns (21 days and 19 days, respectively) successfully helped delay the spread of the disease, buying time to pump up healthcare capacities and management skills during the first wave of COVID-19 in India. In addition, the second wave's severe lockdown put a lot of pressure on the sustainability of many Indian cities. Therefore, the data show that timely implementation of government control laws combined with a high risk perception among the Indian population will help to ensure sustainability. The proposed model is an effective strategy for constructing healthy cities and sustainable societies in India, which will help prevent such a crisis in the future. [ABSTRACT FROM AUTHOR]

This paper explores the causes and consequences of regional taste differences. I introduce habit formation into a standard general equilibrium model. Household tastes evolve over time to favor foods consumed as a child. Thus, locally abundant foods are preferred in every region, as they were relatively inexpensive in prior generations. These patterns alter the correspondence between price changes and nutrition. For example, neglecting this relationship between tastes and agro-climatic endowments overstates the short-run nutritional gains from agricultural trade liberalization, since preferred foods rise in price in every region. I examine the model's predictions using household survey data from many regions of India. (JEL D12, I12, O12, O18, R23) [ABSTRACT FROM AUTHOR]

The amount of solar energy that reaches the earth in one hour is sufficient to supply the world's energy needs for one year. Harvesting this energy efficiently is a huge challenge. In most countries including India, the number of observing stations is inadequate. Therefore, it is essential that some reliable mathematical models be developed to estimate the solar radiation for places where measurements are not carried out and for places where measurement records are not available. In this paper, Angstrom-Prescott model parameters are estimated for seven different sites in India, and a correlation is developed for India, which is found to be a good fit. Also a correlation is developed for predicting the solar radiation using only sunshine hour data. [ABSTRACT FROM AUTHOR]

Thermal aspect of solar energy is widely used in the desalination plants. Experimental investigation and mathematical modeling of inverted V-type solar still integrated with drip system are presented in this paper. The experiment is performed in the Kerala climatic conditions (10.8439°N, 76.0328°E), March 2012 at M E S College of Engineering, Kuttippuram. A two segment still of 2 m² is constructed. Experimental investigations on productivity and internal heat transfer are analyzed. The results indicate that the mean standard deviations between theoretical and experimental values are less than 7% (temperature of rippled wick), 8% (temperature of glass in rippled system), 11% (temperature of flat wick), and 7% (temperature of glass in flat system), an average for the working hours of the day. [ABSTRACT FROM AUTHOR]

Abstract: Hooghly–Matla estuarine ecosystem is one of the largest estuarine ecosystems of the world. Sagar island is the largest delta in this estuarine complex. This island is criss-crossed by small and large creeks with mangrove vegetation and all are connected to the principal estuarine water. Decomposition of mangrove litter in soil is major source of inorganic nutrient to phytoplankton of the adjacent creeks. Deforestation of mangrove affects the primary production, which in turn reduces the availability of dissolved oxygen for the organisms residing in the estuary. Considering the importance of dissolved oxygen in various aspects of aquatic life, a dynamic model of dissolved oxygen at Sagar island of Hooghly–Matla estuarine complex with the help of single dimension differential equation is proposed in the present paper. Different physical, chemical and biological factors such as solar irradiance, temperature, salinity of water, particulate organic matter, re-aeration, wind velocity, phytoplankton and zooplankton, which control the fluctuation of dissolved oxygen, are included in the present model. Most of the parameter values are collected directly from the field surveys. The parameter values which are not able to collect from the field, obtained from literatures are calibrated. To make the model realistic it is properly validated with observed data and to know the statistical significance, chi square goodness fit test is performed. Field surveys are performed over two years. During calibration and validation, two sets of data (first year and second year data) are used. Chi-square values are 5.97 and 6.17 for first and second sets of data respectively (p <0.05). Sensitivity analysis reveals that optimal light intensity is the most sensitive parameter for dissolved oxygen dynamics. Results also show that wind velocity, solar irradiation, salinity of water and temperature are important factors for controlling the dynamics of dissolved oxygen. Macrophytes have very little contribution to oxygen production in the creeks of Sagar island. Model reveals that low dissolved oxygen in the creek water is one of the causes of decline in fish population of the estuary. [Copyright &y& Elsevier]

This paper applied the Malmquist productivity index in order to estimate total factor productivity growth and its components (efficiency change and technological progress) in Indian manufacturing during the pre- and post-reform periods. The results illustrate that the economic reforms have not exerted positive effects on productivity growth in Indian manufacturing. However, the impacts of economic reforms differ between sectors and between components of total factor productivity. First, after reform, the productivity of heavy industries increased, whereas the productivity of light industries decreased. Second, reform improves both the efficiency and the technological progress in the heavy industries, but failed to improve efficiency in light industries. The results of this study suggest that specific policies should be implemented in order to improve efficiency as well as technical progress, thus ultimately facilitating long-run productivity growth. [ABSTRACT FROM AUTHOR]