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This paper seeks to examine the relationship between competitivenessand environment-friendly behaviour of producers under an economic liberalisation regime. For that purpose, it employs a probit model and estimates the influence of the prime movers of industrial growth suchas technical change and economies of scale on environmental degradation. The empirical results of the study of pulp and paper industry, identified as one of the most polluting industries in India, indicate that these variables, as the key players of competitiveness improvement, have positive influence on environment-friendly behaviour. Such findings, therefore, fail to provide support to a view that articulates ruthless exploitation of the environment under economic liberalisation programme. [ABSTRACT FROM AUTHOR]

In this paper, we address the effects of two fiscal policy delays on the dynamical analysis of macroeconomics. First, a time gap between the accrual of taxes and their payment is considered. Second, the time spent between the purchasing decisions and the actual expenditure is also taken into consideration. Since both these delays are significant in controlling macroeconomic conditions, this paper incorporates aforementioned delays into the IS–LM model. At first, a mathematical model is developed using delayed differential equations. Then a unique steady state solution is obtained. Around the equilibrium point, linear stability analysis is done. Also, the occurance of Hopf bifurcation is observed when delay crosses a critical point and switches in stability are also detected. Properties of Hopf bifurcation using center manifold theorem are discussed. Lastly, numerical simulations are run to verify our analysis. In this work, we considered a case study to perform simulation wherein GDP of India for last ten years is recorded for estimating some parameters. In different investment scenarios, numerical simulations corroborate the analytical findings of the model. Furthermore, rigorous analysis shows that adding the right mix of delays can help in maintaining/ regaining the stability after periods of instability, or even gaining stability in the long run. [ABSTRACT FROM AUTHOR]

In this paper, the performance of a PVT (photovoltaic thermal) air collector with V-groove absorber in the air channel is theoretically and experimentally examined under different climate conditions of Ghaziabad city, India, in summer, June 2019. A low power brushless DC fan is fixed at the input of the air-channel to ensure the circulation of air through the V-groove. The energy balance equation is developed with the matrix-inversion method to estimate the PV (photovoltaic) cell and air output temperatures. The theoretical results obtained using mathematical modeling has been compared with that of the real-time experimental results. The electrical, thermal, and overall efficiencies for the theoretical and experimental studies are found in the range of 10.39–10.26%, 41.78–41.57%, and 52.17–51.81%, respectively. It has been observed that the theoretical results are coherent with experimental results for the proposed model achieving an accuracy of 98.98%, 99.43%, and 99.31% for electrical, thermal, and overall efficiencies, respectively. [ABSTRACT FROM AUTHOR]

This paper focuses on irrigation schemes under rotational water supply in arid and semiarid regions. It presents a methodology for developing plans for optimum allocation of land area and water, considering performance measures such as productivity, equity and adequacy. These irrigation schemes are characterized by limited water supply and heterogeneity in soils, crops, climate and water distribution network, etc. The methodology proposed in this paper, therefore, uses a previously developed simulation–optimization model (Area and Water Allocation Model, AWAM) that considers the heterogeneity of the irrigation scheme in the allocation process, and modifies this to take account of equity and adequacy of supply to irrigated areas. The AWAM model has four phases to be executed separately for each set of irrigation interval over the irrigation season: 1. generation of irrigation strategies for each crop–soil–region combination (CSR unit), 2. preparation of irrigation programmes for each irrigation strategy, 3. selection of specified number of irrigation programmes for each CSR unit and 4. optimum allocation of land area and water to different parts of the irrigation scheme (allocation units) for maximizing productivity. In the modified AWAM model, the adequacy is included at Phase-2 (by including only the irrigation programmes for full irrigation of each CSR unit) and equity is included at Phase-4 (by including the constraints for equity). The paper briefly discusses the applicability of the modified AWAM model for a case study of Nazare medium irrigation scheme in Southern India. The results of the case study indicated that the performance measures of productivity, equity and adequacy conflict with each other. [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]

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]

Using the notion of co-integration theory and a vector error correction modelling approach, this paper examines in retrospect the long-run relationship between the exchange rate of silver-based currencies and the intrinsic value of silver in India and Iran in a bivariate model. The results based on unit root and co-integration tests indicate a reliable long-run relationship between the price of silver and the exchange rate of silver-based currencies. Our findings also suggest a bi-directional relationship between the price of silver and exchange rate of pound per rupee in the case of India and a feedback relationship between the intrinsic value of qiran and the exchange rate of pound per qiran in the case of Iran. [ABSTRACT FROM AUTHOR]

The climate change induced by global warming has raised concerns over safety of coastal and offshore infrastructure. At several places in the world therefore studies are being made to know the effect of such change on design and operational ocean parameters. This paper is oriented in this direction and its aim is to specify future changes in the design significant wave height (Hs) over a series of locations along the Indian coastline. Thirty-nine sites were selected along the 7000-km-long Indian coast and design Hs with a return period of 100 years were calculated on the basis of past as well as future wave data of duration 27 years each. The simulation of waves was done by running a numerical wave model forced by wind derived from a modeling experiment called CORDEX. Fitting of data to Generalized Pareto Distribution gave the 100-year Hs at all 39 locations. The results indicate that the design Hs calculated on the basis of projected data was much higher than the one based on historical data. Such increase was as small as 5 % and as high as 58 % as per the location. The west coast sites showed a higher rise in the Hs value than the east ones. [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]

Pillar design is of paramount importance to any underground mine design. Oversized pillars may lead to loss of coal while undersized pillars may lead to instability. While underground pillars are mostly square and rectangular, highwall mining pillars are long and narrow, as they are formed after driving parallel entries in the seam from the highwall. These pillars are termed as web pillars. The overall stability of highwall depends upon these pillars as no other supports are provided in the entries. Web pillar differs from usual coal pillars in respect of w/h ratio being <3.0, with an exceptionally longer length compared to its width, to the tune of 50-500 m. Several empirical coal pillar strength equations developed for rectangular pillars are still being used with some modifications to adapt to web pillars. Review and analysis of these empirical approaches for determining web pillar strength along with a numerical approach for web pillar design are discussed in this paper. Their application to some Indian case studies is also discussed. [ABSTRACT FROM AUTHOR]

Monsoon depressions, that form during the Indian summer monsoon season (June to September) are known to be baroclinic disturbances (horizontal scale 2,000-3,000 km) and are driven by deep convection that carries a very large vertical slope towards cold air aloft in the upper troposphere. Deep convection is nearly always organized around the scale of these depressions. In the maintenance of the monsoon depression the generation of eddy kinetic energy on the scale of the monsoon depression is largely governed by the 'in scale' covariance of heating and temperature and of vertical velocity and temperature over the region of the monsoon depression. There are normally about 6-8 monsoon depressions during a summer monsoon season. Recent years 2009, 2010 and 2011 saw very few (around 1, 0 and 1 per season respectively). The best numerical models such as those from ECMWF and US (GFS) carried many false alarms in their 3-5 day forecasts, more like 6-8 disturbances. Even in recent years with fewer observed monsoon depressions a much larger number of depressions is noted in ECMWF forecasts. These are fairly comprehensive models that carry vast data sets (surface and satellite based), detailed data assimilation, and are run at very high resolutions. The monsoon depression is well resolved by these respective horizontal resolutions in these models (at 15 and 35 km). These models carry complete and detailed physical parameterizations. The false alarms in their forecasts leads us to suggest that some additional important ingredient may be missing in these current best state of the art models. This paper addresses the effects of pollution for the enhancement of cloud condensation nuclei and the resulting disruption of the organization of convection in monsoon depressions. Our specific studies make use of a high resolution mesoscale model (WRF/CHEM) to explore the impacts of the first and second aerosol indirect effects proposed by Twomey and Albrecht. We have conducted preliminary studies including examination of the evolution of radar reflectivity (computed inversely from the model hydrometeors) for normal and enhanced CCN effects (arising from enhanced monsoon pollution). The time lapse histories show a major disruption in the organization of convection of the monsoon depressions on the time scale of a week to 10 days in these enhanced CCN scenarios. [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 theory and practice of sustainability involves the understanding and management of the coupled relationship between the environment and humans. This relationship is very evident in respect to mining where the impacts of operations, both positive and negative, are environmental and socioeconomic in nature. In recent years, evaluating the sustainability of a mining operation has grown within the literature due to the impacts that mining has upon a local community. However, the literature has been often characterised by a variety of case study-specific approaches to define and evaluate the sustainability of mining operations. This is due to the fundamental problem of defining what is sustainability. The paper applies, based on our previous research, a mathematical model of sustainability to the environmental impact assessment (EIA) of a proposed bauxite mining project in the Andhra Pradesh province, India. The model's application to the impact assessment, which used the rapid impact assessment matrix, was undertaken for the purpose of determining the level and nature of sustainability (if appropriate) of the proposed project. The results indicated that the project was considered as unsustainable in its current form, based on an obtained E value of 0.249 and an H value of 0.500. The results suggested that the project would greatly benefit from an environmental management plan in order to mitigate the extensive negative environmental and social impacts of the project. The results also indicated the potential of the model in assisting in the resolution of questions of the sustainability of local projects, which are assessed through quantitative-based EIA. [ABSTRACT FROM AUTHOR]

Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere. A common feature of the weather during the pre-monsoon season over the Indo-Gangetic Plain and northeast India is the outburst of severe local convective storms, commonly known as 'Nor'westers'(as they move from northwest to southeast). The severe thunderstorms associated with thunder, squall lines, lightning and hail cause extensive losses in agricultural, damage to structure and also loss of life. In this paper, sensitivity experiments have been conducted with the Non-hydrostatic Mesoscale Model (NMM) to test the impact of three microphysical schemes in capturing the severe thunderstorm event occurred over Kolkata on 15 May 2009. The results show that the WRF-NMM model with Ferrier microphysical scheme appears to reproduce the cloud and precipitation processes more realistically than other schemes. Also, we have made an attempt to diagnose four severe thunderstorms that occurred during pre-monsoon seasons of 2006, 2007 and 2008 through the simulated radar reflectivity fields from NMM model with Ferrier microphysics scheme and validated the model results with Kolkata Doppler Weather Radar (DWR) observations. Composite radar reflectivity simulated by WRF-NMM model clearly shows the severe thunderstorm movement as observed by DWR imageries, but failed to capture the intensity as in observations. The results of these analyses demonstrated the capability of high resolution WRF-NMM model in the simulation of severe thunderstorm events and determined that the 3 km model improve upon current abilities when it comes to simulating severe thunderstorms over east Indian region. [ABSTRACT FROM AUTHOR]

India Meteorological Department has implemented district level medium range rainfall forecast system applying multimodel ensemble technique, making use of model outputs of state-of-the-art global models from the five leading global NWP centres. The pre-assigned grid point weights on the basis of anomaly correlation coefficients (CC) between the observed values and forecast values are determined for each constituent model at the resolution of 0.25° ×0.25° utilizing two season datasets (1 June-30 September, 2007 and 2008) and the multimodel ensemble forecasts (day-1 to day-5 forecasts) are generated at the same resolution on a real-time basis. The ensemble forecast fields are then used to prepare forecasts for each district, taking the average value of all grid points falling in a particular district. In this paper, we describe the development strategy of the technique and performance skill of the system during summer monsoon 2009. The study demonstrates the potential of the system for improving rainfall forecasts at five days time scale over Indian region. Districtwise performance of the ensemble rainfall forecast reveals that the technique, in general, is capable of providing reasonably good forecast skill over most states of the country, particularly over the states where the monsoon systems are more dominant. [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 emphasizes on mathematical and field work approach to diagnosing the environmental pollution for Indore, India. These applications are based on the time-series statistics and for three semi-industrial as well as residential areas. The generalized additive models finds as a best fit-model in terms of autocorrelation and reduction of over-dispersion. The interdisciplinary study works on the principal of pollutant source, meteorological parameters, pollutant types, emission rates and various chemical processes. Several chemical or industrial processes like iron and steel production, combustion of fossil fuels, biomass burning, thermal power plants are major polluter in most of the mega cities. [ABSTRACT FROM AUTHOR]

Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. [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]

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]

A mathematical model based on the three-dimensional (3-D) boundary element method (BEM), including porous and non-porous breakwaters, is developed to determine the wave trapping characteristics of porous breakwater over the partially reflecting walls with variable bathymetry. In this formulation, a special form of Green's function is utilized to solve the Laplace equation in the 3-D domain to enhance the numerical accuracy. The order of convergence of the present numerical scheme shows a better convergence rate than simple Green's function. The numerical scheme with and without the porous breakwater is compared with the analytical studies of Yu et al. (1994) and Lee (1969), respectively. In addition, the numerical simulation for sloping bathymetry is conducted and compared with the analytical results of Wang et al. (2011). The numerical validation exhibits good agreement with and without porous breakwaters. Based on validation, the current numerical scheme is implemented on the realistic Visakhapatnam Port, Andhra Pradesh, India, at four different synthetic key locations S1 to S4 to analyze the hydrodynamic performance of porous and non-porous breakwaters. Wave amplification is determined for different porosity parameters, including variable linear resistance and inertial coefficient, and different reflecting coefficients of the port wall. Moreover, the wave amplitude within the Visakhapatnam Port is also estimated through a contour plot with and without porous breakwaters to identify the safe location for the moored ship. Overall, the porosity of the breakwaters and partial reflection coefficient on the port wall plays a significant role in inducing or reducing the resonance inside the port. [ABSTRACT FROM AUTHOR]

Modelling in ecology and evolution, especially in India, is often done by researchers trained in physics or engineering without much experience of studying living systems. This is partly driven by a fallacious conviction that modelling is largely about mathematical skills and that, consequently, modellers can equally effectively apply their skills to problems in fields as diverse as physics/engineering and ecology/evolution. I discuss why this fallacy arises, and the many ways in which modelling in ecology or evolution is actually a very different endeavour from that in much of physics, even though the form of the equations deployed across disciplines is typically quite similar. Since modelling is not primarily about the mathematics but about the system being studied, I believe that a reasonable degree of comfort with models and modelling is important for those researchers in ecology and evolution who primarily undertake empirical studies, whether in the laboratory or the field. Equally, I suggest that researchers doing modelling in ecology and evolution, who were trained in the mathematical or physical sciences, need to understand the systems they attempt to model and also appreciate how modelling ecological and evolutionary processes differs from much of the modelling done in classical physics and allied fields. I also discuss what models are, whether modelling is subjective or objective, and what modelling entails if it is to meaningfully add to scientific understanding. This article is aimed primarily at young researchers interested in ecological and evolutionary questions, whether coming from a background in the biological or physical/mathematical sciences. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 continues to spread across the world. During this COVID-19 pandemic, several variants of the SARS-CoV-2 have been found. Some of these new variants like the VOC-202012/01 of lineage B.1.1.7 or the most recently B.1.617 emerging in India have a higher infectiousness than those previously prevalent. We propose a mathematical model based on ordinary differential equations to investigate potential consequences of the appearance of a new more transmissible SARS-CoV-2 strain in a given region. The proposed mathematical model incorporates the presymptomatic and asymptomatic subpopulations in addition to the more usual susceptible, exposed, infected, and recovered subpopulations. This is important from a realistic point of view since it has been found recently that presymptomatic and asymptomatic individuals are relevant spreaders of the SARS-CoV-2. Using the next-generation matrix method, we find the basic reproduction number, R 0 , an important threshold parameter that provides insight regarding the evolution and outcome of a certain instance of the COVID-19 pandemic. The local and global stability of system equilibria are also presented. In particular, for the global stability we construct a Lyapunov functional and use the LaSalle invariant principle to prove that if the basic reproduction ratio is less than unity, the infection-free equilibrium is globally asymptotically stable. On the other hand, if R 0 > 1 the endemic equilibrium is globally asymptotically stable. Finally, we present numerical simulations to numerically support the analytic results and to show the impact of the introduction of a new more contagious SARS-CoV-2 variant in a population. [ABSTRACT FROM AUTHOR]

In present communication, a solar dryer having semi-transparent photovoltaic thermal (SPVT) roof has been used to dry bitter gourd. Experimentation has been done and results were validated with linear regression method through mathematical modelling as well as for non-linear Artificial Neural Network (ANN) modelling has been used. The experimental data namely, ambient air temperature, moisture evaporated, bitter gourd surface temperatures, solar intensity on different surfaces of dryer, room temperature and relative humidity have been recorded for the climatic condition of Varanasi, UP, India. The numerical value of convective heat transfer coefficients for bitter gourd found to be between 0.69–14.45 W/m2 K. The results for mass transfer (moisture evaporated) during drying of bitter gourd from theoretical model (linear regression method and ANN) and experiments showed good agreement. Further, net electrical energy, thermal energy and overall thermal energy were found to be 0.62, 3.77 and 5.41 kWh/m2/day respectively. The payback period at 10% interest rate and 4% inflation rate with ₹ 50 ($0.77) and ₹ 100 ($1.54) saving rate per kg were found to be 1.47 and 0.72 years respectively. [ABSTRACT FROM AUTHOR]

Since the first case of 2019 novel coronavirus disease (COVID-19) detected on 30 January, 2020, in India, the number of cases rapidly increased to 3819 cases including 106 deaths as of 5 April, 2020. Taking this into account, in the present work, we have analysed a Bats–Hosts–Reservoir–People transmission fractional-order COVID-19 model for simulating the potential transmission with the thought of individual response and control measures by the government. The real data available about number of infected cases from 14 March, 2000 to 26 March, 2020 is analysed and, accordingly, various parameters of the model are estimated or fitted. The Picard successive approximation technique and Banach's fixed point theory have been used for verification of the existence and stability criteria of the model. Further, we conduct stability analysis for both disease-free and endemic equilibrium states. On the basis of sensitivity analysis and dynamics of the threshold parameter, we estimate the effectiveness of preventive measures, predicting future outbreaks and potential control strategies of the disease using the proposed model. Numerical computations are carried out utilising the iterative Laplace transform method and comparative study of different fractional differential operators is done. The impacts of various biological parameters on transmission dynamics of COVID-19 is investigated. Finally, we illustrate the obtained results graphically. [ABSTRACT FROM AUTHOR]

Hereditary xerocytosis (HX), also known as dehydrated stomatocytosis (DHSt) is a dominantly inherited genetic disorder exhibiting red cell membrane dehydration caused by the loss of the monovalent cation K+ and water. Variants in mechanosensitive Piezo ionic channels of the PIEZO1 gene are the primary cause of HX. We have utilized high throughput and highly precise next-generation sequencing (NGS) to make a diagnosis and examine the genotype-phenotype relationship in inflexible HX cases. Seven unrelated patients with unexplained hemolytic anemia were scrutinized with a panel probing 8000 genes related to congenital anemia. Targeted next-generation sequencing identified 8 missense variants in the PIEZO1 gene in 7 unrelated Indian patients. Three of the 8 variants are novel (c.1795G > C, c.2915G > A, c.7372 T > C) and the remaining five (c.4082A > G, c.6829C > A, c.7374C > G, c.7381G > A, c.7483_7488dup) are previously reported. The variants have been validated by Sanger sequencing. One patient with autosomal dominant mutation (c.7372 T > C) is associated with iron refractory iron deficiency anemia. Of the 7 patients, one has HX in combination with a novel homozygous variant (c.994G > A) in the PKLR gene causing PK deficiency resulting in severe clinical manifestations with phenotypic variability. In silico prediction using bioinformatics tools were used to study the possible damaging effects of the novel variants. Structural-functional analysis of the novel variants was investigated by molecular modeling software (PyMOL and Swiss PDB). These results encompass the heterogeneous behavior of mechano-sensitive Piezo1 protein observed in HX patients in India. Moreover, NGS imparted a subtle, economical, and quick tool for understanding the genetic cause of undiagnosed cases of congenital hemolytic anemia. NGS grants a potential technology integrating clinical history together with molecular report profiting in such patients and their families. [ABSTRACT FROM AUTHOR]

The present work assesses the performance of 11 regional climate simulations in representing the precipitation patterns of summer monsoon over India for the period 1970-2005. These simulations have been carried out under Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project. The regional climate models (RCMs) have been inter-compared as well as evaluated against the observation to identify the common weaknesses and differences between them. For this, a number of statistical analysis has been carried out to compare the model precipitation field with the corresponding observation. Model uncertainty has been also evaluated through bias studies and analysis of the spread in the ensemble mean (hereafter, ensemble). The models which perform better than the rest are identified and studied to look for any improvement in the ensemble performance. These better performing experiments (best RCM experiments) are further assessed over the monsoon core region (MCR) of India. This has been done to understand how well the models perform in a spatially homogeneous zone of precipitation which is considered to be a representative region of Indian summer monsoon characteristics. Finally, an additional analysis has been done to quantify the skill of models based on two different metrics—performance and convergence including a combination of the two. The experiment with regional model RegCM4 forced with the global model GFDL-ESM2M shows the highest combined mean skill in capturing the seasonal mean precipitation. In general, a significant dry bias is found over a larger part of India in all the experiments which seems most pronounced over the central Indian region. Ensemble on an average tends to outperform many of the individual experiments with bias of smaller magnitude and an improved spatial correlation compared with the observation. Experiments which perform better over India improve the results but only slightly in terms of agreement among experiments and bias. [ABSTRACT FROM AUTHOR]

The Extended Range Forecasts System (ERFS) has been generating monthly and seasonal forecasts on real-time basis throughout the year over India since 2009. India is one of the major rice producer and consumer in South Asia; more than 50% of the Indian population depends on rice as staple food. Rice is mainly grown in kharif season, which contributed 84% of the total annual rice production of the country. Rice cultivation in India is rainfed, which depends largely on rains, so reliability of the rainfall forecast plays a crucial role for planning the kharif rice crop. In the present study, an attempt has been made to test the reliability of seasonal and sub-seasonal ERFS summer monsoon rainfall forecasts for kharif rice yield predictions at Kharagpur, West Bengal by using CERES-Rice (DSSATv4.5) model. These ERFS forecasts are produced as monthly and seasonal mean values and are converted into daily sequences with stochastic weather generators for use with crop growth models. The daily sequences are generated from ERFS seasonal (June-September) and sub-seasonal (July-September, August-September, and September) summer monsoon (June to September) rainfall forecasts which are considered as input in CERES-rice crop simulation model for the crop yield prediction for hindcast (1985-2008) and real-time mode (2009-2015). The yield simulated using India Meteorological Department (IMD) observed daily rainfall data is considered as baseline yield for evaluating the performance of predicted yields using the ERFS forecasts. The findings revealed that the stochastic disaggregation can be used to disaggregate the monthly/seasonal ERFS forecasts into daily sequences. The year to year variability in rice yield at Kharagpur is efficiently predicted by using the ERFS forecast products in hindcast as well as real time, and significant enhancement in the prediction skill is noticed with advancement in the season due to incorporation of observed weather data which reduces uncertainty of yield prediction. The findings also recommend that the normal and above normal yields are predicted well in advance using the ERFS forecasts. The outcomes of this study are useful to farmers for taking appropriate decisions well in advance for climate risk management in rice production during different stages of the crop growing season at Kharagpur. [ABSTRACT FROM AUTHOR]

The present study explores the properties of precipitating shallow echoes (PSEs) over the tropical areas (30°S-30°N) during Indian summer monsoon season using attenuated corrected radar reflectivity factor (Ze) measured by the Tropical Rainfall Measuring Mission satellite. Radar echoes observed in study are less than the freezing height, so they belong to warm precipitation. Radar echoes with at least 0.75 km wide are considered for finding the shallow echoes climatology. Western Ghats and adjoining ocean (Arabian sea) have the highest PSEs followed by Myanmar and Burma coast, whereas the overall west coast of Latin America consists of the lowest PSEs. Tropical oceanic areas contain fewer PSEs compared to coastal areas. Average vertical profiles show nearly similar Ze characteristics which peaks between 1.5 and 2 km altitude with model value 32-34 dBZ. Slope of Ze is higher for intense PSEs as radar reflectivity decreases more rapidly in intense PSEs. [ABSTRACT FROM AUTHOR]

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system. [ABSTRACT FROM AUTHOR]

Remote sensing (RS) and Geographic Information Systems (GIS) techniques have become very important these days as they aid planners and decision makers to make effective and correct decisions and designs. Principal Component Analysis (PCA) involves a mathematical procedure that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. It reduces the dimensionality of the data set and identifies a new meaningful underlying variable. Morphometric analysis and prioritization of the sub-watersheds of Shakkar River Catchment, Narsinghpur district in Madhya Pradesh State, India, is carried out using RS and GIS techniques as discussed in Gajbhiye et al. (Appl Water Sci 4(1):51-61, 2013b). In this study we apply PCA technique in Shakkar River Catchment for redundancy of morphometric parameters and find the more effective parameters for prioritization of the watershed and discuss the comparison between Gajbhiye et al. (Appl Water Sci 4(1):51-61, 2013b) and the present prioritization scheme. [ABSTRACT FROM AUTHOR]

A detailed regional drought study is carried out in the southern peninsula of India to characterize the spatio-temporal nature of droughts and to predict the drought magnitudes for various probabilities in the homogeneous drought regions. The method of several random initializations of the cluster centres of the K-means algorithm is suggested for the identification of the initial regions in the context of drought regionalization, which is shown to perform better than the initialization from the Ward's algorithm and the Ward's algorithm itself. The peninsula is classified into seven spatially well-separated homogeneous drought regions. The robust L-moment framework is used for the regional frequency analysis of drought magnitudes computed using the standardized precipitation index. The Pearson type III is found to be appropriate for regional drought frequency analysis in six of the regions, while the robust Wakeby distribution is suggested for one region. Low magnitude droughts are frequent and dominant in the northern part of west coast, the north-eastern coast and its adjoining inland region, while high magnitude droughts are less in number and are experienced in semi-arid central part, southern part of western coast, south-eastern part and north-western inland region. The spatial maps of drought magnitudes indicate that at higher return periods (100 and 200 years) the south-eastern part of the peninsula is likely to encounter high magnitude droughts, while the central region is likely to experience the same at lower return periods (10 and 50 years). Hence these regions need to be given special importance in the drought mitigation planning activities. [ABSTRACT FROM AUTHOR]

Surface level soil moisture from two gridded datasets over India are evaluated in this study. The first one is the UK Met Office (UKMO) soil moisture analysis produced by a land data assimilation system based on Extended Kalman Filter method (EKF), which make use of satellite observation of Advanced Scatterometer (ASCAT) soil wetness index as well as the screen level meteorological observations. Second dataset is a satellite soil moisture product, produced by National Remote Sensing Centre (NRSC) using passive microwave Advanced Microwave Scanning Radiometer 2 measurements. In-situ observations of soil moisture from India Meteorological Department (IMD) are used for the validation of the gridded soil moisture products. The difference between these datasets over India is minimum in the non-monsoon months and over agricultural regions. It is seen that the NRSC data is slightly drier (0.05%) and UKMO soil moisture analysis is relatively wet during southwest monsoon season. Standard AMSR-2 satellite soil moisture product is used to compare the NRSC and UKMO products. The standard AMSR-2 and UKMO values are closer in monsoon season and AMSR-2 soil moisture is higher than UKMO in all seasons. NRSC and AMSR-2 showed a correlation of 0.83 (significant at 0.01 level). The probability distribution of IMD soil moisture observation peaks at 0.25 m/m, NRSC at 0.15 m/m, AMSR-2 at 0.25 m/m and UKMO at 0.35 m/m during June-September period. Validation results show UKMO analysis has better correlation with in-situ observations compared to the NRSC and AMSR-2 datasets. The seasonal variation in soil moisture is better represented in UKMO analysis. Underestimation of soil moisture during monsoon season over India in NRSC data suggests the necessity of incorporating the actual vegetation for a better soil moisture retrieval using passive microwave sensors. Both products have good agreement over bare soil, shrubs and grassland compared to needle leaf tree, broad leaf tree and urban land cover types. [ABSTRACT FROM AUTHOR]

As an important constituent of hydrological cycle, estimation of Reference Evapotranspiration (ET) is essential for planning of projects related to water resources. This article compares the results obtained from the available pan evaporation based equations to estimate ET from pan evaporation (E) and proposes a new simplified methodology for estimation of ET, which needs only the data of relative humidity (H). The resulting model is based upon the collected meteorological data of a selected study area i.e. Nagpur District in Maharashtra State, which lies in western plateau and hills region of India. In the proposed methodology, E rates are adjusted to the values expected for 50 % relative humidity. Then, the relationship between ET and the adjusted E is established. The validation of the proposed new model has been carried out by comparing its results with the results obtained by the pan evaporation method, for the study area as well as for the data set of another area. This new model is found to be reasonably accurate for estimation of reference evapotranspiration for the study area and as such, is expected to be applicable to the river basins located in the regions having climatic conditions similar to that of the study area. Although, if the conditions are different then another site specific model can be developed by adopting the methodology proposed in this article. [ABSTRACT FROM AUTHOR]

The hydrology of high altitude glacierized basin in Himalaya is complex to understand due to high variability in climate and lack of hydro-meteorological data. In this study, analysis of hydrological, glacier ablation and meteorological records have been made for Dunagiri Glacier (~4,200 m) during the melt season (July - September), for the years 1985 and 1987-1989. In the daily cycle of mean diurnal discharge in summer months during 1985-1989, maximum discharge occurred at midnight, and minimum discharge occurred in the morning. Mean daytime and nighttime discharge volume was contributing approximately equal amounts. Such type of analysis will be the basis for designing/developing Run-off-the river type hydroelectric power projects which are heavily dependent on snow and glacier melt in Himalaya. Time series analysis of available hydro-meteorological records have been used to understand governing hydrological processes within the basin and to develop regression model for future development in runoff forecasting using climate data. [ABSTRACT FROM AUTHOR]

Flood inundation modelling in developing countries is severely limited by the lack of high resolution terrain data and suitable imagery to map flood extents. This study assessed the predictive uncertainty of modelled flood extents generated from TELEMAC2D model using low-cost, sparse input data commonly available in developing countries. We studied a river reach characterised by anabranching channels and river islands in eastern India. In this complex fluvial setting, we analysed computational uncertainty as a function of error in both satellite-derived flood-extent maps using a Generalised Likelihood Uncertainty Estimation (GLUE)-based approach. The model performance was quite sensitive to the uncertainty in the inflow hydrograph, particularly close to the flood peak. Evaluation of the flood inundation probability map, conditioned upon deterministic and probabilistic observed flood extents, reveals that the effect of using probabilistic observed data is only evident for portions of the model domain where the model output is free from consistent bias (over or under prediction) likely created by the imperfect terrain data. [ABSTRACT FROM AUTHOR]

Tropical cyclone is one of the most devastating weather phenomena all over the world. The Environmental Modeling Center (EMC) of the National Center for Environmental Prediction (NCEP) has developed a sophisticated mesoscale model known as Hurricane Weather Research and Forecasting (HWRF) system for tropical cyclone studies. The state-of-the-art HWRF model (atmospheric component) has been used in simulating most of the features our present study of a very severe tropical cyclone 'Mala', which developed on April 26 over the Bay of Bengal and crossed the Arakan coast of Myanmar on April 29, 2006. The initial and lateral boundary conditions are obtained from Global Forecast System (GFS) analysis and forecast fields of the NCEP, respectively. The performance of the model is evaluated with simulation of cyclone Mala with six different initial conditions at an interval of 12 h each from 00 UTC 25 April 2006 to 12 UTC 27 April 2006. The best result in terms of track and intensity forecast as obtained from different initial conditions is further investigated for large-scale fields and structure of the cyclone. For this purpose, a number of important predicted fields' viz. central pressure/pressure drop, winds, precipitation, etc. are verified against observations/verification analysis. Also, some of the simulated diagnostic fields such as relative vorticity, pressure vertical velocity, heat fluxes, precipitation rate, and moisture convergences are investigated for understanding of the characteristics of the cyclone in more detail. The vector displacement errors in track forecasts are calculated with the estimated best track provided by the India Meteorological Department (IMD). The results indicate that the model is able to capture most of the features of cyclone Mala with reasonable accuracy. [ABSTRACT FROM AUTHOR]

Release of long-lived radioactivity to the aquatic bodies from various nuclear fuel cycle related operations is of great environmental concern in view of their possible migration into biosphere. This migration is significantly influenced by various factors such as pH, complexing ions present in aquatic environment and sorption of species involving radionuclides on the sediments around the water bodies. Am are two major radionuclides which can contribute a great deal to radioactivity for several thousand years. In the present study, Am sorption on natural sediment collected from site near a nuclear installation in India, has been investigated under the varying conditions of pH (3-10) and ionic strength [ I = 0.01-1 M (NaClO)]. The sorption of Am increased with pH of the aqueous medium [10% (pH 2) to ~100% (pH 10)], which was explained in terms of the increased negative surface charge on the sediment particles. There was marginal variation in Am(III) sorption with increased ionic strength (within error limits) of the aqueous medium suggesting inner-sphere complexation/sorption process. Sediment was characterized for its elemental composition and structural phases using Energy Dispersive X-Ray (SEM-EDX) and X-Ray Diffraction (XRD) techniques. Zeta-potential measurement at I = 0.1 M (NaClO) suggested that Point of Zero Charge (pH) was ~2, indicating the presence of silica as major component in the sediment. Kurabtov plot using sorption data as a function of pH at fixed I = 0.1 M (NaClO) indicated the presence of multiple Am(III) species present on the surface. Potentiometric titration of the suspension indicated the presence of mineral oxide like behavior and assuming a generic nature (≡XOH) for all types of surface sites, protonation-deprotonation constants and total number of sites have been obtained. The sorption data has been modeled using 2-pK Diffuse Double Layer Surface Complexation Model (DDL-SCM). ≡XOAm has been identified as the main species responsible for the sorption profile. [ABSTRACT FROM AUTHOR]

high-resolution mesoscale numerical model (MM5) has been used to study the coastal atmospheric circulation of the central west coast of India, and Goa in particular. The model is employed with three nested domains. The innermost domain of 3 km mesh covers Goa and the surrounding region. Simulations have been carried out for three different seasons-northeast (NE) monsoon, transition period and southwest (SW) monsoon with appropriate physics options to understand the coastal wind system. The simulated wind speed and direction match well with the observations. The model winds show the presence of a sea breeze during the NE monsoon season and transition period, and its absence during the SW monsoon season. In the winter period, the synoptic flow is northeasterly (offshore) and it weakens the sea breeze (onshore flow) resulting in less diurnal variation, while during the transition period, the synoptic flow is onshore and it intensifies the sea breeze. During the northeast monsoon at an altitude of above 750 m, the wind direction reverses, and this is the upper return current, indicating the vertical extent of the sea breeze. A well-developed land sea breeze circulation occurs during the transition period, with vertical extension of 300 and 1,100 m, respectively. [ABSTRACT FROM AUTHOR]

The multiple objectives and interests of various stack holders' in reservoir operation bring forward many solutions to the problem. Possibly due to this complexity, in practice, the operating rules to be derived not only from heuristic approaches such as rules of thumb, rule curve, operator experience and engineering judgments but also through well defined mathematical models. An attempt is made to study the possibility of changing the crop (paddy crop instead of groundnut) and crop starting period for Sathanur irrigation system, India. This system is considered as one of the water-deficit irrigation system where the water is collected in the reservoir during north-east monsoon (Oct-Dec) and crops are cultivated after the rainfall season. Even though the first priority is to supply drinking water to Tiruvanamalai town and nearby villages, the quantity required for drinking water is very meagre when compared to irrigation demands. Genetic algorithm (GA) has been used to find the optimal crop-starting period that can give maximum performance and net benefit from the system. The results of the model study indicate that starting the cultivation of paddy crop between 1st and 10th of October every year provides maximum net benefit than starting the cultivation between 11th and 20th of December as practiced now. [ABSTRACT FROM AUTHOR]

Estimation of design rainfall intensity is crucial for design and planning of water resources engineering projects. The intent of the present study is to develop regional IDF curves for Tehri-Garhwal Himalayan region in India, wherein numbers of hydropower projects are in planning and execution stage. Self Recording Rain Gauge (SRRG) stations are generally not so frequent in the project locations. Under this situation, the engineers are forced to use regional intensity duration frequency (IDF) curves. Under this study, four stations viz. Tehri M.T.Lab, Mukhim, Pilkhi and Dhuttu were available with SRRG data. These data are used to develop the regional IDF curve for entire Tehri-Garwal region. After selection of the most intensive storms, return periods has been determined using regionalized L-moment method. After developing IDF curves for above four raingauge stations, Thiessen Ploygon method is applied to find out average IDF curve. To show the spatial variability, Isopluvial maps have been generated using ArcGIS and a relation equation has been developed. [ABSTRACT FROM AUTHOR]

A comparative study was performed to evaluate the performance of the UK Met Office’s Global Seasonal (GloSea) prediction General Circulation Model (GCM) for the forecast of maximum surface air temperature (Tmax) over the Indian region using the model generated hindcast of 15-members ensemble for 16 years (1987–2002). Each hindcast starts from 1st January and extends for a period of six months in each year. The model hindcast Tmax is compared with Tmax obtained from verification analysis during the hot weather season on monthly and seasonal scales from March to June. The monthly and seasonal model hindcast climatology of Tmax from 240 members during March to June and the corresponding observed climatology show highly significant (above 99.9% level) correlation coefficients (CC) although the hindcast Tmax is over-estimated (warm bias) over most parts of the Indian region. At the station level over New Delhi, although the forecast error (forecast-observed) at the monthly scale gradually increases from March to June, the forecast error at the seasonal scale during March to May (MAM) is found to be just 1.67 °C. The GloSea model also simulates well Tmax anomalies on monthly and seasonal scales during March to June with the lower Root Mean Square Error (RMSE) of bias corrected forecast (less than 1.2 °C), which is much less than the corresponding RMSE of climatology (reference) forecast. The anomaly CCs (ACCs) over the station in New Delhi are also highly significant (above 95% level) on monthly to seasonal time scales from March to June, except for April. The skill of the GloSea model for the seasonal forecast of Tmax as measured from the ACC map and the bias corrected RMSE map is reasonably good during MAM and April to June (AMJ) with higher ACC (significant at 95% level) and lower RMSE (less than 1.5 °C) found over many parts of the Indian regions. [ABSTRACT FROM AUTHOR]

In this article, linear programming and fuzzy optimization models are developed for planning and management of available land-water-crop system of Mahanadi-Kathajodi delta in eastern India. The models are used to optimize the economic return, production and labour utilization, and to search the related cropping patterns and intensities with specified land, water, fertilizer and labour availability, and water use pattern constraints. Due to extreme backwardness of the study area, it has been decided to keep all the three objectives of the linear programming models at the same priority level to obtain the compromised solution in a fuzzy environment that incorporates the imprecision in fuzzy goals and fuzzy constraints. These non-structural models facilitate the conjunctive use of available surface water and groundwater resources. A comparative evaluation along with the benefit-cost ratios of the existing and proposed farming systems is also presented. [ABSTRACT FROM AUTHOR]

To obtain optimal operating rules for storage reservoirs, large numbers of simulation and optimization models have been developed over the past several decades, which vary significantly in their mechanisms and applications. As every model has its own limitations, the selection of appropriate model for derivation of reservoir operating rule curves is difficult and most often there is a scope for further improvement as the model selection depends on data available. Hence, evaluation and modifications related to the reservoir operation remain classical. In the present study a Genetic Algorithm model has been developed and applied to Pechiparai reservoir in Tamil Nadu, India to derive the optimal operational strategies. The objective function is set to minimize the annual sum of squared deviation form desired irrigation release and desired storage volume. The decision variables are release for irrigation and other demands (industrial and municipal demands), from the reservoir. Since the rule curves are derived through random search it is found that the releases are same as that of demand requirements. Hence based on the present case study it is concluded that GA model could perform better if applied in real world operation of the reservoir. [ABSTRACT FROM AUTHOR]

Geophysical, geochemical, and hydrogeological parameters, for example longitudinal unit conductance (S), transverse unit resistance (T), total dissolved solids (TDS) and thickness of the weathered zone (Wz), have been compared for 25 sites of Navalgund taluk in Dharwar District of Karnataka State, India. Interrelation among these parameters has been analyzed quantitatively by the standard statistical technique leading to a suitable mathematical model. The contrasting geophysical, geochemical, and hydrogeological characteristics of the fresh water pockets in the regionally brackish aquifers are compared and illustrated. The study explains the significant bearing of these parameters on exploration, development, and exploitation of fresh groundwater sources in the areas affected by the occurrence of a brackish water aquifer. The importance of such a comparison in raising the confidence to identify a fresh groundwater aquifer in the brackish terrain by quantitative interpretation of resistivity data has been demonstrated. [ABSTRACT FROM AUTHOR]

This study examines empirical distributions of postpartum amenorrhea from three longitudinal studies of breastfeeding women conducted in Bangladesh, India, and Guatemala, both to provide information on the distribution of postpartum amenorrhea and to evaluate statistical models of postpartum amenorrhea. Observation of the empirical schedules indicates that the most common shape for a distribution of postpartum amenorrhea is bimodal. Amenorrhea is best represented by a curve that consists of two hills. Both an analytic model consisting of a mixed distribution and a logit model with a revised standard are suggested for use with data on postpartum amenorrhea. [ABSTRACT FROM AUTHOR]

TABRAP (TArget Birth Rate Acceptor Program) is a computer programmed model that provides a direct solution to the problem of determining the total annual numbers of contraceptive acceptors required to achieve a prescribed crude birth rate target path. Applied to an initial population for which age structure, the fertility schedule, and expected trends in life expectancy and age-specific proportions of females married are known, TABRAP incorporates the following factors: age at acceptance, with acceptors drawn from currently married nonusers; age-method-specific attrition rates of users; a potential fertility schedule of acceptors that allows for aging and sterility; and allowance both for postpartum anovulation and nine months for gestation to time properly the averted births. TABRAP generates annual data on acceptors, couple-years of use, births averted and age-specific fertility rates that meet the crude birth rate target. Resulting changes in population size, age structure and crude vital rates, also yielded, are invariant with respect to acceptor age and method mix. Assuming a target to reduce the crude birth rate from 45 to 30 in ten years, TABRAP is illustrated for seven mixes of acceptor age-method combinations applied to a population approximately that of Thailand, circa 1965. [ABSTRACT FROM AUTHOR]

This study is one of the few multivariate analyses of the relations of several demographic and socioeconomic variables to fertility and the use of contraception. For fertility, 56 of the 92 hypothesized paths are found to be significant at the .05 level or better. The five variables having a significant and direct effect on fertility, as shown by their path coefficients (p), are: duration of marriage (p = .721), spouse's cohort (p = -.093), spouse's age at marriage (p = .052), caste (p = -.071), and number of siblings of husband (p = .050). The use of contraception is affected by, in order of importance, the spouse's education (p = .267), the husband's education (p = .099), the husband's income (p = .089), and surplus children, i.e., number of living children exceeding ideal number of children (p = .059). Child mortality, which is linked to number of living children and thus indirectly to surplus children, is affected by, in order of importance, the number of children ever born (p = .723), the husband's education (p = -.166), the spouse's absence by death or separation (p = .084), and family structure (p = .035). The advantages and disadvantages of path analysis for this type of research are briefly mentioned. [ABSTRACT FROM AUTHOR]