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Entropy generation analysis of tangent hyperbolic fluid in quadratic Boussinesq approximation using spectral quasi-linearization method
In many industrial applications, heat transfer and tangent hyperbolic fluid flow processes have been garnering increasing attention, owing to their immense importance in technology, engineering, and science. These processes are relevant for polymer solutions, porous industrial materials, ceramic processing, oil recovery, and fluid beds. The present tangent hyperbolic fluid flow and heat transfer model accurately predicts the shear-thinning phenomenon and describes the blood flow characteristics. Therefore, the entropy production analysis of a non-Newtonian tangent hyperbolic material flow through a vertical microchannel with a quadratic density temperature fluctuation (quadratic/nonlinear Boussinesq approximation) is performed in the present study. The impacts of the hydrodynamic flow and Newtons thermal conditions on the flow, heat transfer, and entropy generation are analyzed. The governing nonlinear equations are solved with the spectral quasi-linearization method (SQLM). The obtained results are compared with those calculated with a finite element method and the bvp4c routine. In addition, the effects of key parameters on the velocity of the hyperbolic tangent material, the entropy generation, the temperature, and the Nusselt number are discussed. The entropy generation increases with the buoyancy force, the pressure gradient factor, the non-linear convection, and the Eckert number. The non-Newtonian fluid factor improves the magnitude of the velocity field. The power-law index of the hyperbolic fluid and the Weissenberg number are found to be favorable for increasing the temperature field. The buoyancy force caused by the nonlinear change in the fluid density versus temperature improves the thermal energy of the system. 2021, Shanghai University. -
Entropy generation and heat transport analysis of Casson fluid flow with viscous and Joule heating in an inclined porous microchannel
The combined effects of the magnetic field, suction/injection, and convective boundary condition on heat transfer and entropy generation in an electrically conducting Casson fluid flow through an inclined porous microchannel are scrutinized. The temperature-dependent heat source is also accounted. Numerical simulation for the modelled problem is presented via RungeKuttaFelhberg-based shooting technique. Special attention is given to analyze the impact of involved parameters on the profiles of velocity (u(?)), temperature (?(?)), entropy generation (Ns), and Bejan number (Be.) It is established that entropy generation rate decreases at the walls with an increase in Hartmann number (M), while it increases at the center region of the microchannel. IMechE 2019. -
Entropy generation and thermal analyses of a Cross fluid flow through an inclined microchannel with non-linear mixed convection
The temperature difference of the various applications such as microchannel heat exchangers, microelectronics, solar collectors, automotive systems, micro fuel cells, and microelectromechanical systems (MEMS) is relatively large. The buoyancy force (mixed convection) modeled by the conventional Boussinesq approximation is inadequate since the density of the operating fluids fluctuates non-linearly with the temperature difference. Therefore, the mixed non-linear convective transport of the flow of Cross fluid through three different geometric aspects (horizontal, vertical, and inclined) of the microchannel under the non-linear Boussinesq (NBA) approximation is investigated. Mechanisms of internal heat source, Rosseland radiative heat flux, and frictional heating are incorporated into the thermal analysis. The mathematical construction is proposed using the Cross fluid model for a steady-state, and subsequent non-linear differential equations are deciphered by the spectral quasi-linearization method (SQLM). Graphical sketches were constructed and displayed that explore the stimulus of various key parameters on Bejan number, velocity, temperature, and entropy generation. It is found that the Bejan number and entropy production improved due to the non-linear density temperature variation. The convective heating boundary conditions augment the entropy production. The pressure gradient accelerates the transport of fluid in a microchannel. Furthermore, among three different geometries, the velocity, entropy production, and temperature are the highest for the vertical microchannel. 2023 Wiley-VCH GmbH. -
Environment and Human Rights - Interrelatedness
Shodh Prerak, Vol. 2, Issue 3, pp 69-73, ISSN No. 2231-413X -
Environmental and Sustainable Development Policies to Address the Pollution Catastrophe in India
Although the environment, crops, water, air, food and fiber, control the weather, and supply oxygen, its air, water, and soil are polluted too. Humans have altered about 75% of the earth, reducing wildlife and nature's space and harming the environment. Industrialisation, urbanisation, population growth, and globalisation have affected people and the environment. This study aims to investigate the environmental and sustainable development-focussed policies to address the pollution catastrophe. The study is a content analysis of prominent online newspaper media reports from January 1, 2020, to November 30, 2022, on legal, environmental, and sustainable issues to reduce pollution and advocate an Indian environmental and sustainable development policy. Since pollution and environmental degradation pose significant threat to humanity, ecosystems, and sustainable living are at risk. Despite national and international legislative and regulatory actions, the environment remains a significant issue. An environmental strategy that encourages sustainable development for future generations is the need of the times. It was found that there were legal and environmental offenses, the management of unscientific treatment procedures, the lack of fundamental education about existing court orders, and fatality-induced health problems. Therefore, India needs an environmental and sustainable development policy to limit environmental concerns' fatality and protect the earth from pollution. 2024 - IOS Press. All rights reserved. -
Environmental cost of food wastage: Integrated response through a mix of environmental policy instruments
Food, when wasted, reaches landfills and emits greenhouse gases. The impact of greenhouse gases (GHGs), in turn, is felt by even those who do not waste food in the place. Externalities thus created are known to distort market efficiency and the most widely discussed externality is climate change. This study takes the case of United States of America (USA) to ascertain the GHGs resulting due to food wastage. The difference between cost per capita due to emissions from animal-based products and emissions from plant-based products comes out to be $122. In the year 1997 total GHG emission for the entire population of the USA due to food wastage was 401.98 billion kgCO2eq, costing the country 45.42 billion US dollars. Two decades later, in 2017, the food waste costs went up by 6 billion US dollars amounting to 51.14 billion US dollars and 452.64 billion kgCO2eq of GHG emissions The novelty of this research lies in highlighting the carbon footprints of food wastage in terms of GHG's and monetizing these emissions. The study proposes an integrated response through a mix of environmental policy instruments of economic incentives, command and control and moral suasion. 2023 ERP Environment and John Wiley & Sons Ltd. -
Environmental degradation in geopolitical risk and uncertainty contexts for India: A comparison of ecological footprint, CO2 emissions, and load capacity factor
This study assesses the role of geopolitical risk and uncertainty in the degradation of the environment by forming the functions for ecological footprint, CO2 emissions, and load capacity factor for the period 19902019 in India. Besides, the specified function endogenizes economic growth, renewable energy consumption, and natural resource rent as the additional covariates. The use of the autoregressive distributed lag model (ARDL) confirms the long-run relationship between study variables. Further, the dynamic simulations of the autoregressive distributed lag model (DYNARDL) outcomes show that geopolitical risk improves the quality of the environment by reducing the ecological footprint and CO2 emissions. However, it degrades the environment by reducing the load capacity factor. Furthermore, the uncertainty improves the environmental quality by reducing the CO2 emissions and ecological footprint, but the reduced load capacity factor due to uncertainty implies the degradation of environmental quality in India. Given these findings, the study proposes different environmental conservation policies. 2023 Elsevier Ltd -
ENVIRONMENTAL JURISPRUDENCE IN INDIA: A JOURNEY TOWARDS ATTAINING ECO-CENTRIC IDEALS
Environmental Law has had a long, arduous journey in India, but has been able to keep up with the many changes that have taken place, around the globe, and has helped shape India's environmental legal regime. By tracing the growth of environmental law, through different ages, and by highlighting some of those factors, which have contributed immensely to its growth, the idea is to identify certain false grounds and figure out ways to make environmental law more effective. By looking at it through a sociocultural lens, the aim is to examine as to whether culture, tradition and rituals can be imbibed into law or given a legal recognition, and thereby giving more power to law. The development of Earth Jurisprudence principles and the way in which it is sought to be imbibed in India and the challenges that it faces too are discussed. 2022 Universitat Rovira i Virgili. All right reserved. -
Environmental Management: Pragmatic Suitability of Low Cost Activated Carbon in Lead (II)Ion Removal by Continuous Mode of Adsorption
Heavy metals such as chromium, lead, and arsenic are usually present in trace amounts in natural waters but many of them are toxic even at very low concentrations. An increasing quantity of heavy metals in our resources is currently an area of greater concern, especially since a large number of industries are discharging their metal containing effluents into freshwater without any adequate treatment. Activated carbons show a significant ability in removing heavy metal ions from an aqueous solution by adsorption, which has been examined by many researchers. Activated carbon derived from Manilkarazapota tree-wood (MZTWAC), which was found to be a suitable adsorbent for the removal of lead ions through continuous adsorption mode, was examined in this paper. A breakthrough curve has been plotted to find the effect of initial concentration and adsorbent bed height in the adsorption of lead (II)ion through MZTWAC. The breakthrough time and the saturation time increased as the initial concentration increased from 40 mg.L-1 to 60 mg.L-1. The saturation time was in the incremental mode when the bed height was increased from 5 cm to 7 cm bed thickness for 40 mg.L-1 concentration. Adams-Boharts model perfectly fits with this fixed-bed column in the removal of lead(II) from an aqueous solution using MZTWAC. Activated carbon derived from MZTWAC is better suited for the purpose of detoxifying metal-contaminated wastewater. 2021 Technoscience Publications. All rights reserved. -
Environmental value development among preadolescents: a content analysis of reflective responses
Addressing the environmentally detrimental values prevalent in society in the context of rapid climate change is the need of the hour. Combining empathy with cognitive skills such as reflective thinking effectively creates new values among people. The present study attempts to reveal the pattern of environmental value development among 33 preadolescents by reflecting upon the empathy-generating story experiences and the related contents. The study is part of a more extensive quasi-experimental study, and it specifically performs a content analysis on the participants responses in their workbooks. Biospheric nature-related values are the most highly developed, and social justice is the least developed value, implying the need to focus more on the value of social justice. Stories are aids, and reflective thinking and empathetic elicitation are effective techniques for passing environmental values. Empathy generation instead of negative emotions from self-concern and emotion regulation through reflective thinking may be helpful to promote well-being in the context of climate change. Reflective thinking helps environmental value development by enhancing comprehension, emotion regulation, and self-awareness of values, implying a shift from telling the moral of a story to exploring the same through reflective thinking. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Environmentally conscious synthesis of novel pyrano[2,3-d]pyrimidines via ternary deep eutectic solvents
Pyrano[2,3-d]pyrimidine and its analogues have gained considerable courtesy because of their diverse biological functions and wide-ranging applications, from pharmaceutical agents to essential natural pigments. However, synthesising pyrano[2,3-d]pyrimidine with multiple reactants is challenging and requires advanced green chemistry solutions. This study investigates the generation of thirteen new pyrano[2,3-d]pyrimidine analogues through a single-step, open-flask, multicomponent reaction (MCR) strategy involving aldehydes, phenylhydrazine, ethyl acetoacetate, and barbituric acid via deep eutectic solvents (DES). These DESs serve as environmentally friendly alternatives to traditional solvents. A ternary deep eutectic solvent (TDES) was evaluated for its catalytic solvent activity among ten different formulations. TDES-7 (5 mL) demonstrated the best performance, achieving 95 % product formation within 30 min at room temperature. Its remarkable catalytic activity and ability to produce high yields across multiple reaction cycles make it a standout choice for this application. The collaboration between MCR and TDES underscores an important blend of two significant green aspects, demonstrating their potential to achieve a green and productive sustainable synthesis method with an noble E-factor of 0.1236. 2024 Elsevier B.V. -
Environmentally responsible behaviour among the teachers: role of gratitude and perceived social responsibility
Purpose: Based upon the broaden-and-build theory of positive emotions, this study aims to assess the role of perceived social responsibility (PSR) in mediating the relationship between gratitude and environmentally responsible behaviour (ERB) among teachers. Design/methodology/approach: Data were collected, following a correlational design, from a total of 292 school teachers in Kerala state, India. In total, 256 data were taken for final analysis. Out of the total participants, 63.3% were female and the remaining 36.7% were male. Confirmatory factor analysis was carried out to verify the factor structure and discriminant as well as convergent validity of the study variables. The relationship between gratitude and ERB with mediating role of PSR was tested. Findings: The mediation analysis output revealed that PSR fully mediates the effect of gratitude on ERB, and it is concluded from the findings of the study that ERB can be enhanced by humanizing the citizens to integrate social responsibility in their acts and promoting the significance of having positive emotions like gratitude to widen their thoughtaction repertoires. Research limitations/implications: In line with the broaden-and-build theory, a positive state of mental faculty can be a prime facilitator to increase concern for green environments as an outcome of an expanded thoughtaction repertoire. The findings imply the importance of inculcating enduring personal resources like the sense of gratefulness as it weighs the effect of producing altruistic acts like ERB along with many other benefits associated with having a positive emotion which is obviously considered to be a fair contribution to serve social resources in the community. Social implications: The study findings can be an inspiration for the formation of policies to encourage pro-environmental behaviour and to further expansion of policies like national education policy of India. As teachers being the facilitators of knowledge and wisdom, they are potential sources to inspire students to practice healthy behaviours, they can be better models by practicing ERB. Originality/value: The authors have verified the application of broaden-and-build theory of positive emotion in the context of ERB along with identifying its relationship with gratitude and PSR. 2023, Emerald Publishing Limited. -
Environmentally sustainable zinc oxide nanoparticles for improved hazardous textile dye removal from water bodies
A sustainable, affordable, and cost-effective method was developed to synthesize zinc oxide nanoparticles (SB-ZnO-NPs) using leaf extracts of Strobilanthes barbatus. The synthesized SB-ZnO-NPs displayed an absorbance maximum at 359 nm with a band gap of 3.24 eV. The average diameter of the SB-ZnO-NPs, as determined by FESEM analysis, was 84.23 nm. The particles had nearly spherical morphologies. By using FTIR analysis, it was established that functional groups played a part in the formation of SB-ZnO-NPs. Reactive Yellow 86 (RY-86) and Reactive Yellow 145 (RY-145) textile dyes were degraded by SB-ZnO-NPs under the impact of UV irradiation, and the degradation rates were 87.50 and 91.11%, respectively, in 320 min. When dye solutions treated with SB-ZnO-NPs were tested for phytotoxicity, the results showed a sharp decline in the effectiveness of the inhibition compared to dye effluents. The synthesised SB-ZnO-NPs can, therefore, be employed as a substitute potential catalyst for the breakdown of textile colours both before and after release into water bodies. 2023 The Author. -
Enzyme based bioelectrocatalysis over laccase immobilized poly-thiophene supported carbon fiber paper for the oxidation of D-ribofuranose to D-ribonolactone
A modified electrode based on laccase immobilized poly-thiophene-3-carboxylic acid supported on carbon fiber paper was developed for the electrocatalytic oxidation of D-ribofuranose to otherwise difficult-to-access D-ribonolactone, a precursor for C-nucleoside based drug like Remdesivir. The electrochemical oxidation of D-ribofuranose was achieved by the TEMPO-mediated electrochemical process. The experimental parameters were optimized and validated using Design of Experiment (DoE) statistical tool indicating the concentration of TEMPO and stirring as important parameters in bulk electrolysis. The mechanism for the electrochemical oxidation of D-ribofuronose followed single electron anodic oxidation of TEMPO mediated by laccase to the corresponding oxoammonium nitrosonium species which was vital for the mediated electrochemical oxidation. The mechanism for the electrochemical oxidation was established using cyclic voltammetry and computational studies. The plausible interactions of laccase enzyme with TEMPO mediator were studied using molecular docking experiments. This facile method was successfully applied for the oxidation of D-ribofuranose to D-ribonolactone. 2022 -
Enzyme based bioelectrocatalysis over laccase immobilized poly-thiophene supported carbon fiber paper for the oxidation of D-ribofuranose to D-ribonolactone /
Molecular Catalysis, Vol.524, ISSN No: 2468-8231.
A modified electrode based on laccase immobilized poly-thiophene-3-carboxylic acid supported on carbon fiber paper was developed for the electrocatalytic oxidation of D-ribofuranose to otherwise difficult-to-access D-ribonolactone, a precursor for C-nucleoside based drug like Remdesivir. The electrochemical oxidation of D-ribofuranose was achieved by the TEMPO-mediated electrochemical process. The experimental parameters were optimized and validated using Design of Experiment (DoE) statistical tool indicating the concentration of TEMPO and stirring as important parameters in bulk electrolysis. -
Enzyme immobilization on biomass-derived carbon materials as a sustainable approach towards environmental applications
Enzymes with their environment-friendly nature and versatility have become highly important green tools with a wide range of applications. Enzyme immobilization has further increased the utility and efficiency of these enzymes by improving their stability, reusability, and recyclability. Biomass-derived matrices when used for enzyme immobilization offer a sustainable solution to environmental pollution and fuel depletion at low costs. Biochar and other biomass-derived carbon materials obtained are suitable for the immobilization of enzymes through different immobilization strategies. Environmental pollution has become an utmost topic of research interest due to an ever-increasing trend being observed in anthropogenic activities. This has widely contributed to the release of various toxic effluents into the environment in their native or metabolized forms. Therefore, more focus is being directed toward the utilization of immobilized enzymes in the bioremediation of water and soil, biofuel production, and other environmental applications. In this review, up-to-date literature concerning the immobilization and potential uses of enzymes immobilized on biomass-derived carbon materials has been presented. 2022 Elsevier Ltd -
Enzyme immobilized conducting polymer-based biosensor for the electrochemical determination of the eco-toxic pollutant p-nonylphenol
The unbridled release of harmful endocrine disruptors (EDs) into the environment is deteriorating human and animal health. A facile and efficacious biosensor was developed by immobilizing laccase over electropolymerized poly anthranilic acid on a carbon fiber paper (CFP) electrode, Lac/PAA/CFP for the detection of p-nonylphenol (PNP). PNP is a persistent phenolic endocrine disruptor and a harmful eco-toxic pollutant. Physico-chemical and electrochemical characterization of the fabricated electrode was carried out to study the modification of the Lac/PAA/CFP electrode. Cyclic voltammetric studies divulged that the prepared sensor has catalytic activity approximately twice greater than that of the bare CFP electrode. The influence of pH and scan rate was scrutinized for the modified electrode. Under optimized conditions differential pulse voltammetric studies were used for the quantification and the results revealed that the biosensor has a low limit of detection (LOD) and limit of quantification (LOQ) of 1.74 nM and 5 Nm, respectively with a broad linear dynamic range of 5250 nM. In the presence of interferants, the developed biosensor exhibited good selectivity toward the electrochemical detection of PNP. Molecular docking studies carried out revealed the hydrogen bonding interaction of the Asn264 residue of laccase Trametes versicolor. Further, the fabricated biosensor was accessed for its practicality in real samples collected from tap water and lake water. 2023 Elsevier Ltd -
EPCAEnhanced Principal Component Analysis for Medical Data Dimensionality Reduction
Innovations in technology from thelast one decade have led to the generation of colossal amounts of medical data with comparably low cost. Medical data should be collected with utmost care. Sometimes, the data have high features but not all the features play an important role in drawing the relations to the mining task. For the training of machine learning algorithms, all the attributes in the data set are not relevant. Some of the characteristics may be negligible and some characteristics may not influence the outcome of the forecast. The pressure on machine learning algorithms can be minimized by ignoring or taking out the irrelevant attributes. Reducing the attributes must be done at the risk of information loss. In this research work, an Enhanced Principal Component Analysis (EPCA) is proposed, which reduces the dimensions of the medical dataset and takes paramount care of not losing important information, thereby achieving good and enhanced outcomes. The prominent dimensionality reduction techniques such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Partial Least Squares (PLS), Random Forest, Logistic Regression, Decision Tree and the proposed EPCA are investigated on the following Machine Learning (ML) algorithms: Support Vector Machine (SVM), Artificial Neural Networks (ANN), Nae Bayes (NB) and Ensemble ANN (EANN) using statistical metrics such as F1 score, precision, accuracy and recall. To optimize the distribution of the data in the low-dimensional representation, EPCA directly mapped the data to a space with fewer dimensions. This is a result of feature correlation, which made it easier to recognize patterns. Additionally, because the dataset under consideration was multicollinear, EPCA aided in speeding computation by lowering the data's dimensionality and therebyenhancedthe classification model's accuracy. Due to these reasons, the experimental results showed that the proposed EPCA dimensionality reduction technique performed better when compared with other models. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
Epidemic Prediction using Machine Learning and Deep Learning Models on COVID-19 Data
A catastrophic epidemic of Severe Acute Respiratory Syndrome-Coronavirus, commonly recognised as COVID-19, introduced a worldwide vulnerability to human community. All nations around the world are making enormous effort to tackle the outbreak towards this deadly virus through various aspects such as technology, economy, relevant data, protective gear, lives-risk medications and all other instruments. The artificial intelligence-based researchers apply knowledge, experience and skill set on national level data to create computational and statistical models for investigating such a pandemic condition. In order to make a contribution to this worldwide human community, this paper recommends using machine-learning and deep-learning models to understand its daily accelerating actions together with predicting the future reachability of COVID-19 across nations by using the real-time information from the Johns Hopkins dashboard. In this work, a novel Exponential Smoothing Long-Short-Term Memory Networks Model (ESLSTM) learning model is proposed to predict the virus spread in the near future. The results are evaluated using RMSE and R-Squared values. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Epileptic seizure detection using EEG signals and multilayer perceptron learning algorithm
Purpose: Epileptic is a neurological chronic disorder that causes unprovoked, recurrent seizure. A seizure is a sudden rush of electrical activity in the brain. The central nervous system characterized by the loss of consciousness and convulsions. Epileptic is caused by abnormal electrical discharge that lead to uncountable movements, loss of consciousness and convulsions. 50-80 million people in the world are affected by this disorder. Now a days children and adults are affected the most and it has been medically treated. Sometimes it may lead to death and serious injuries. In this technology world the computerized detection is an enhanced solution to protect epileptic patients from dangers at the time of this seizure. Method: Perceptron learning algorithm is a supervised learning of binary classifiers and also it is a simple prototype of a biological neuron in artificial neural network. EEG is extensively documented for the diagnosing and assessing brain activates and related disorders. In this paper EEG signals are taken as dataset for epilepsy detection. The data is been represented based on three domains namely frequency, time and time-frequency applied by the chebysev filter for processing the signals. Result: Help the patients from dangers at the time of the seizure. Conclusion: The neurological diseases can be divided into two loss of consciousness and convulsions. In this technology world the seizure can be detected by computerized way like EEG and so on. This paper proposes an epileptic seizure detection using EEG (Electroencephalogram) and perceptron learning algorithm. 2020, IJSTR.