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Nanoparticles have been considered in many fields such as medicine and industry due to their very small size and their special physicochemical properties. Biosynthesis of nanoparticles has advantages over other methods. This paper examines the bibliography of the relationship between nanotechnology and fungi from 1985 to 2021. Data were collected from three databases consisting of Web of Science, Scopus, and Dimensions. The number and type of documents were examined and then the analysis was continued using VOSviewer and Bibliometrix-package on the documents of the Scopus database. Analysis of 1203 documents from this database showed an upward trend in the publication in recent years. The term "Fungi" was also identified as the keyword index and India as the country with the most published documents. Future research is likely to be on using modern techniques in the study of nanoparticles as well as focusing on other genera of fungi. This paper explores the relationship between nanotechnology and fungi from 1985 to 2021. Biosynthesis offers advantages in creating nanoparticles, which are tiny particles with unique properties used in many fields. Data from three databases were analysed, indicating an increasing trend in publications in recent years. Future research is likely to focus on modern techniques to study nanoparticles and other types of fungi. [ABSTRACT FROM AUTHOR]

In this paper, an SIRS epidemic model using Grunwald–Letnikov fractional-order derivative is formulated with the help of a nonlinear system of fractional differential equations to analyze the effects of fear in the population during the outbreak of deadly infectious diseases. The criteria for the spread or extinction of the disease are derived and discussed on the basis of the basic reproduction number. The condition for the existence of Hopf bifurcation is discussed considering fractional order as a bifurcation parameter. Additionally, using the Grunwald–Letnikov approximation, the simulation is carried out to confirm the validity of analytic results graphically. Using the real data of COVID-19 in India recorded during the second wave from 15 May 2021 to 15 December 2021, we estimate the model parameters and find that the fractional-order model gives the closer forecast of the disease than the classical one. Both the analytical results and numerical simulations presented in this study suggest different policies for controlling or eradicating many infectious diseases. [ABSTRACT FROM AUTHOR]

The paper traces the origin of the Middle East conflict and discusses the gradual evolution of the Israel-Palestine conflict from a historical perspective. The paper discusses the peace negotiations undertaken for the region during different periods and the contribution of the international community in reaching a compromise formula. The paper discusses the emergence and the role of Hamas and how it gained political legitimacy. The paper concludes with the views of Israel and India perspective. [ABSTRACT FROM AUTHOR]

In the current era, entire global economies are transitioning to sustainable development because of global warming and climate change. Due to turbulence in environmental issues such as weather shocks, climate change and basic infrastructure and industrial planning, many countries are changing their approach and taking green steps. This paper assesses sustainable finance in India and the ways in which India can mitigate climate changing risk toward zero carbon policy and supporting SDGs 2030. It talks about the physical and transitional climate risks in India like surface temperature, heat wave concourse, etc., and provides a comprehensive analysis of how the corporate sector is imparting its role in sustainable nature through corporate social responsibility (CSR). India is an emerging economy where energy is an essential component. This study analyzes about supply of energy and how India is shifting from traditional energy sources to renewal energy sources. Thus, the objective of this study is to focus on the initiatives taken by the Indian government for sustainable finance through green bond policy at national and international platforms using the Panchamrit framework adopted by India thereby focusing on India's sustainable policy support for SDGs 2030. Also, this research proposes numerous recommendations for future sustainable finance research in the context to India, which includes developing and diffusing innovative sustainable financing instruments, magnifying, and managing the profitability and returns of sustainable financing, making sustainable finance more sustainable, and leveraging the power of new-age technologies for sustainable finance. [ABSTRACT FROM AUTHOR]

Text classification involves organizing textual information into predefined classes, a task which is particularly useful in domains like sentiment analysis, spam detection, and content labeling. In India, where a massive amount of information is generated daily through newspapers and social media, Hindi is one of the most widely used and spoken languages. However, there is limited research on Hindi text classification and, particularly, regarding Hindi news classification. This paper presents a research study to classify Hindi news articles published in Hindi-language newspapers in India by using and comparing various Machine Learning (ML) and Deep Learning (DL) algorithms. To prepare the textual news data for classification, pre-processing and feature engineering techniques, such as count vectorizer, Tf-Idf vectorizer and Doc2Vec, were used and applied to convert texts into vectors. This pre-processing step on the textual data was very challenging due to the presence of multimodal words, conjunctions, punctuation, and special characters in Hindi texts. The study considered Hindi news headlines from predetermined categories (Science, Sports, Entertainment and Business) and, among the different ML and DL models tested and evaluated, Linear Regression with Doc2Vec vectorizer and SGD classifier with Tf-Idf vectorizer produced best accuracies of 97.04% and 96.59%, respectively. The best performing DL model was found to be the Bi-LSTM with an accuracy of approximately 97% on the testing data. [ABSTRACT FROM AUTHOR]

Japan and India are the two oldest and largest democracies in Asia. Since the inception of their diplomatic relations in 1952, the two countries have maintained a cordial relationship. They remain aloof during the Cold War period due to their ideological differences. After that, India following the economic liberalization followed by the "Look East" policy in the post-Cold War period had a positive impact on bilateral relations. This took a sudden gap due to India's second Pokhran nuclear test in 1998 followed by Japanese economic sanctions. However, the relations normalized soon when Mori visited India along with other South Asian nations in 2000. The bilateral relations further improved when the two countries signed the "strategic orientation of Japan-India global partnership" during Koizumi's visit in 2005. Since then, the two countries have been engaging in different aspects of strategic partnership, and a peaceful and stable Indo-Pacific along with the "rule-based order" has always been their priority. Thus, different scholars and statesmen from both countries started the discussion on building a new architecture of 'rule-based order' in the Indo-Pacific. To that end, Japan and India have continuously engaged themselves in bilateral and multilateral dialogue such as G4, Shangri-La Dialogue and Quad. Thus, this paper will try to see how far the two countries can persuade the international community to push the concept of "rule-based order" in the Indo-Pacific. [ABSTRACT FROM AUTHOR]

The labor force participation rate of women in India has decreased despite economic growth, which has limited the advancement of their rights unlike in most other countries. This paper examines the determinants of labor force participation by gender in rural and urban areas using a probit model with data from the India Human Development Survey (IHDS) for 2011–2012 to analyze the factors that restrict workforce participation. The estimation results are presented below. First, the marital status of males, both rural and urban, has a significant impact on their participation in the workforce due to family support. In contrast, females face multiple restrictions based on marital, caste and religion, demonstrating that sociocultural factors have limited their participation regardless of regional factors. Second, in rural areas, the educational years of female workers negatively affect labor participation, but the constraints of marriage are weaker than in urban areas. Women in lower castes participate more in the rural labor force, which is interpreted as a result of their livelihood in the industrial structure consisting of agriculture. On the other hand, the caste system negatively affects female participation in urban areas. Finally, these results indicate that the low-labor participation of females is the result of a complicated process influenced by various factors, including regional effects and patriarchal cultural values in India. Therefore, it is necessary to provide employment opportunities and encourage economic incentives for more women to enter the labor market spontaneously, considering regional effects in policies, in order for women to emerge as one group of social leaders. [ABSTRACT FROM AUTHOR]

In recent times, the virtual power plant (VPP) is gaining more attention in power system engineering due to its tremendous potential in enhancing sustainable urbanism, in which, it supplies clean energy from distributed generators. Electricity is deemed a basic requirement for future automotive and ultra-modern technologies. The deficiency of traditional energy resources and their complex generation process make the production cost of electricity increase dramatically. Moreover, traditional power distribution systems are encountering issues in distributing electrical energy to fulfill customer demands. Therefore, this paper proposes a novel power management system named 'the hybrid genetic local binary knowledge (HGLBK) algorithm' to manage power distribution in the transmission lines and to optimize the total operation cost of the network. The hybrid optimization algorithm effectively controls the load by supplying the surplus power load to the adjacent feeders thereby optimally selecting and placing the distributed energy resource (DER). The proposed concept is implemented at Kayathar, Tamil Nadu in India, and their real-time data are utilized for modeling the VPP. The proposed VPP concept is implemented in the IEEE-9 bus system and the performance of VPP is simulated using the MATLAB software. The performance of the proposed HGLBK algorithm is assessed by comparing its effectiveness with the existing approaches. [ABSTRACT FROM AUTHOR]

Culinary globalization in Indian cities has resulted in new patterns of food consumption and production. Aside from the increasing presence of global franchises such as Costa Coffee, McDonald's and Kentucky Fried Chicken, local and foreign entrepreneurs have established restaurants that offer various national cuisines. In Delhi, for example, Japanese-themed restaurants cater to the city's growing appetite for new culinary experiences. So far our knowledge of culinary globalization in Indian cities has focused on consumption: How emerging gastronomic patterns relate to identity formations. The production of cuisines as part of the city's culinary globalization is rarely explored. In this paper, I focus on the role of Filipino 'sushi chefs' as cultural intermediaries who localize Japanese cuisine. This paper discusses their emergent practices of cultural mediation, namely adapting to local taste, peer mentoring and communicative labor. I argue that such practices of cultural mediation point to the social dynamics of cultural production. [ABSTRACT FROM AUTHOR]

Considering the prevailing situations, the mathematical modeling and dynamics of novel coronavirus (2019-nCoV) particularly in India are studied in this paper. The goal of this work is to create an effective SEIRS model to study about the epidemic. Four different SEIRS models are considered and solved in this paper using an efficient homotopy perturbation method. A clear picture of disease spreading can be obtained from the solutions derived using this method. We parametrized the model by considering the number of infection cases from 1 April 2020 to 30 June 2020. Finally, numerical analysis and graphical representations are provided to interpret the spread of virus. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) for early diagnosis of damage in structures has become vital in improving the structural integrity and safety of the structure and thereby providing a smooth operation for most of the important in-service civil structures such as buildings and bridges. SHM also contributes to the substantial reduction in the maintenance cost of the structure. During serious structural failures, SHM can safeguard human life through an early warning system. This paper presents an output-only model-free technique by extracting damage features from the energy profiles derived from measured time-history responses. The proposed algorithm is organized into two phases i.e. the learning phase and the monitoring phase. While the learning phase can optionally be executed offline, the monitoring phase can preferably be online. The damage feature is extracted by carrying out a fractal dimension analysis of the continuous waveform of energy associated with the jolt (i.e. rate of change of acceleration) evaluated from the acceleration responses of the structure. A novel damage index is proposed, to localize the damage, using the damage features extracted from the fractal dimension, while handling operational and environmental variability (EoV). The proposed algorithm is evaluated through numerical simulations on a typical span of 220 m RCC bridge across river Amaravathi in Tamil Nadu, India and also a 20-story frame structure. Experimental investigations are also carried out by testing a laboratory-scale 10-story frame structure and also an RCC bridge model of a 7.7 m span to evaluate the practical amenability of the proposed algorithm. The experimental and numerical studies carried out in this paper, suggest that the proposed energy-based diagnostic technique can effectively localize the damage even in the presence of confounding factors like EoV. Conclusively, the proposed diagnostic technique can be an effective tool for online SHM, as it is model-free with less tedious computations and can perform well even in the presence of noise. [ABSTRACT FROM AUTHOR]

Under what conditions do policy paradigms succeed in historically weak states? To answer these questions, this paper examines the subnational case of Bihar in India. The existing literature portrays Bihar as lacking capacity. Yet, between 2005 and 2010, astounding improvements have taken place in sectors of transparency and accountability and law & order. How do we explain this? This paper shows that ideas are consequential in initiating changes in policy paradigms. [ABSTRACT FROM AUTHOR]

This paper explains the potential implications of digital interventions for social accountability through the Smart Cities Mission (SCM) in India. The SCM represents India's transition to a new political economy based on rapid urbanization and wide-scale application of digital technology to reform public service delivery while simultaneously creating new markets for urban transformation. Within this wider context, the paper considers the future of democratic practices in urban governance. We argue that while citizen-led accountability practices were trialed by civil society organizations since 1990s, the SCM presented unique opportunity and challenge to institutionalize these tools within the framework of multi-scalar governance — between central-, state- and local-level institutions and between communities, private vendors and public bodies. Zooming into the four smart city projects — Indore, Kakinada, Panaji and Ranchi — we explain how each city engaged with citizen groups, communities and civil society and what their experiences tell us about the prospects and challenges of democratizing digital urban futures. [ABSTRACT FROM AUTHOR]

In this introductory paper of the Special Issue, we explore how India's political economy is moving in a new direction by focusing on three key political economy issues: development, welfare, and governance. India has undergone a substantial political transformation in recent years, especially since Bharatiya Janata Party led by Narendra Modi formed the first majoritarian government in three decades in 2014. In this paper, we first demonstrate that this political transformation has a significant impact on the Indian political economy, given that the country is witnessing the rise of a new developmentalism, a new welfarism, and the new modes of governance. After that, we summarize the collections of articles of the Special Issue and situate them in relation to our central theme, new directions in the Indian political economy. This paper, and this Special Issue more broadly, seeks to contribute to the existing literature by introducing new analytical frameworks to understand recent changes in the Indian political economy and providing new empirical evidence on this topic drawing on content analysis and field research. [ABSTRACT FROM AUTHOR]

COVID-19 outbreaks are the critical challenge to the administrative units of all worldwide nations. India is also more concerned about monitoring the virus's spread to control its growth rate by stringent behaviour. The present COVID-19 situation has huge impact in India, and the results of various preventive measures are discussed in this paper. This research presents different trends and patterns of data sources of States that suffered from the second wave of COVID-19 in India until 3rd July 2021. The data sources were collected from the Indian Ministry of Health and Family Welfare. This work reacts particularly to many research activities to discover the lockdown effects to control the virus through traditional methods to recover and safeguard the pandemic. The second wave caused more losses in the economy than the first wave and increased the death rate. To avoid this, various methods were developed to find infected cases during the regulated national lockdown, but the infected cases still harmed unregulated incidents. The COVID-19 forecasts were made on 3rd July 2021, using exponential simulation. This paper deals with the methods to control the second wave giving various analyses reports showing the impact of lockdown effects. This highly helps to safeguard from the spread of the future pandemic. [ABSTRACT FROM AUTHOR]

Numerous research based on offline Tamil recognition deals only with few Tamil characters since it becomes extremely complicated in distinguishing small variations in large handwritten document. The writer's complexity affects the overall formation of the characters. Such types of complexities are due to discontinuation of structures, unnecessary over loops, variation in shapes as well as irregular curves. This complex issue results in enhanced error value rate. Therefore, to conquer such issues, this paper proposes a novel approach to enhance the offline Tamil handwritten character recognition by utilizing four principal steps: pre-processing, segmentation, feature extraction and classification. For optimal segmentation of Tamil characters, this paper utilizes the Tsallis entropy approach-based atom search (TEAS) optimization algorithm. Then a Newton algorithm based deep convolution extreme learning (DELM) approach is utilized for the extraction and classification of input images. Finally, experiments are carried out for numerous Tamil handwritten recognition-based approaches. The proposed Tamil character recognition utilizes the datasets of isolated Tamil handwritten characters established by HP lab India to evaluate the efficiency of the system. [ABSTRACT FROM AUTHOR]

In this paper, a SEIR epidemic model related to media coverage and exogenous reinfections is established to explore the transmission dynamics of COVID-19. The basic reproduction number is calculated using the next generation matrix method. First, the existence of equilibrium points is investigated, and different kinds of equilibrium points indicate that the disease may disappear, or exist that result in different quantity of susceptible individuals, pre-symptomatic infected individuals and symptomatic infected individuals. The stability of the equilibria is discussed by a geometric approach, and it is found that controlling reproduction number to be lower than 1 is not sufficient for eradication of COVID-19. Second, transcritical bifurcation is explored, and it is found that improving the ratio of exogenous reinfection may lead to backward bifurcation under poor medical conditions, which indicates that two endemic equilibrium points appear. Third, to investigate the influence of parameters on the basic reproduction, sensitivity analysis is done to choose relatively sensitive parameters, and the parameters for treatment and media coverage are selected. An optimal control model is established to balance the treatment and media awareness. By exploring the existence and the uniqueness of the optimal control solution, the optimal control strategies are given. Finally, we run numerical simulations to verify the theoretical analysis on actual data of China, and the data from the four different states of India is used for forecasting the situation of infected individuals in a short period. It is found by the simulation that the co-function of treatment and media coverage results in the reduced number of infectious individuals. [ABSTRACT FROM AUTHOR]

Precision farming makes extensive use of information technology, which also aids agronomists in their work. Weeds typically grow alongside crops, lowering the production of those crops. Weeds are eliminated with the aid of herbicides. Without knowing what kind of weed it is, the pesticide may also harm the crop. The weeds from the farms must be categorized and identified in order to be controlled. Automatic control of weeds is essential to enlarge crop production and also to avoid rigorous hand weeding as labor scarcity has led to a surge in food manufacturing costs, especially in the developed countries such as India. On the other hand, the advancement of an intelligent, reliable automatic system for weed control in real time is still challenging. This paper intends to introduce a new crop/ weed classification model that includes three main phases like pre-processing, feature extraction and classification. In the first phase, the input image is subjected to pre-processing, which deploys a contrast enhancement process. Subsequent to this, feature extraction takes place, where "the features based on gray-level co-occurrence matrix (GLCM) as well as gray-level run-length matrix (GLRM)" are extracted. Then, these extracted features along with the RGB image (totally five channels) are subjected to classification, where "optimized convolutional neural network" (CNN) is employed. In order to make the classification more accurate, the weight and the activation function of CNN are optimally chosen by a new hybrid model termed as the hybridized whale and sea lion algorithm (HW–SLA) model. Finally, the superiority of the adopted scheme is validated over other conventional models in terms of various measures. [ABSTRACT FROM AUTHOR]

This paper intends to explore Magical Realism in the Indian context through O. V. Vijayan's novel, The Legends of Khasak, initially published in Malayalam in 1969; later in 1994, Vijayan himself translated it into English. This regional novel might not have fetched global recognition, but it remains one of the most influential magical realist texts in Malayalam literature. Intriguingly though, the novel was published just two years after García Márquez's magnum opus, One Hundred Years of Solitude, and almost a decade and a half before Rushdie's Midnight's Children. Salman Rushdie's commercial success in this genre popularized South Asian Magical Realism in the West. However, many regional writers from India had employed Magical Realism's stylistic paradox in their works before the term officially originated in the European and Latin American contexts. Through Vijayan's novel, this study explores how, in the Indian context, the paradoxical impulse to naturalize the supernatural deeply exists in realism's stylistic undercurrents. The research further uses the critical framework of trauma and memory to analyze how the author attempts to recuperate the indigenous cultural identity of the natives, lost due to colonialism and capitalism, and simultaneously historicize the onset of colonial modernity and industrialization in India. [ABSTRACT FROM AUTHOR]

Cultural dances are practiced all over the world. The study of various gestures of the performer using computer vision techniques can help in better understanding of these dance forms and for annotation purposes. Bharatanatyam is a classical dance that originated in South India. Bharatanatyam performer uses hand gestures (mudras), facial expressions and body movements to communicate to the audience the intended meaning. According to Natyashastra, a classical text on Indian dance, there are 28 Asamyukta Hastas (single-hand gestures) and 23 Samyukta Hastas (Double-hand gestures) in Bharatanatyam. Open datasets on Bharatanatyam dance gestures are not presently available. An exhaustive open dataset comprising of various mudras in Bharatanatyam was created. The dataset consists of 15 396 distinct single-hand mudra images and 13 035 distinct double-hand mudra images. In this paper, we explore the dataset using various multidimensional visualization techniques. PCA, Kernel PCA, Local Linear Embedding, Multidimensional Scaling, Isomap, t-SNE and PCA–t-SNE combination are being investigated. The best visualization for exploration of the dataset is obtained using PCA–t-SNE combination. [ABSTRACT FROM AUTHOR]

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

In the new paradigm of health-centric governance, policymakers are in constant need of appropriate metrics to determine suitable policies in a non-arbitrary fashion. To this end, in this paper, a compartmentalized model for the transmission of COVID-19 is developed, with a socially distanced compartment added to the model. The modification allows for administrators to quantify the extent to which voluntary social distancing norms are followed, and address restrictions accordingly. Modifications are also made to incorporate inter-region migration, and suitable metrics are proposed to quantify the impact of migration on the rise of cases. The healthcare capacity is modeled and a method is developed to study the consequences of the saturation of the healthcare system. The model and related measures are used to study the nature of the transmission and spread of COVID-19 in India, and appropriate insights are drawn. [ABSTRACT FROM AUTHOR]

In 2017, the Government of India launched the goods and services tax (GST), referred to as "one tax, one nation, one market". This tax all Indian businesses are subject to this tax. GST was framed with the objective of bringing tax handling for all businesses onto a single platform and developing a transparent and effective system in which all businesses will pay taxes. This paper identifies and addresses GST implementation challenges and proposes a solution, GSTChain, using blockchain network technology. Currently, GST is collected at the sellers end and bifurcated between the Indian state and central governments. GSTChain is a blockchain system based on trust and autonomy with the objective of making taxpayers' lives easy and tax collection efficient and transparent for the government. [ABSTRACT FROM AUTHOR]

India is rich in its heritage and culture. It has many historical monuments and temples where the walls are made of inscribed stones and rocks. The stone inscriptions play a vital role in portraying about the ancient incidents. Hence, the digitization of these stone inscriptions is necessary and contributes much for the epigraphers. Recently, the digitizing of these inscriptions began with the binarization process of stone inscriptions. This process mainly depends on the thresholding technique. In this paper, the binarization of terrestrial and underwater stone inscription images is preceded by a contrast enhancement and succeeded by edge-based filtering that minimizes noise and fine points the edges. A new method called modified bi-level thresholding (MBET) algorithm is proposed and compared with various existing thresholding algorithms namely Otsu method, Niblack method, Sauvola method, Bernsen method and Fuzzy C means method. The obtained results are evaluated with the performance metrics such as peak signal-to-noise ratio (PSNR) and standard deviation (SD). It is observed that the proposed method has an improvement of 49% and 39%, respectively, on an average by the metrics considered. [ABSTRACT FROM AUTHOR]

This current research paper measures the performance of Indian private sector banks through various multi-criteria decision-making (MCDM) techniques. To measure the performance of the banks the data about various criteria such as profit after tax, borrowings, advances, adjusted EPS, enterprise value, and NPAs from the Annual reports of the banks were extracted. The MCDM techniques, SDV (standard deviation) CRITIC (CRiteria Importance Through Intercriteria Correlation), ARAS (Additive Ratio Assessment), MOORA (Multi-objective Optimization on the basis of Ratio Analysis) are applied to analyze the data and measure the performance of the banks. In MCDM techniques, different methods provide different weights of the criteria, and also different ranks are obtained by different methods. Sensitivity analysis was carried out by measuring the criteria weights by SDV and CRITIC and the alternatives are ranked using two MCDM techniques, ARAS and MOORA. The results of the study show that among the private banks, HDFC created a benchmark and leading while Yes bank has shown poor performance on the basis of annual reports of 2020. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic has been raging all around the world for almost a year now, as of November 1, 2020. In this paper, we try to analyze the variation of the COVID-19 pandemic in different countries in the light of some modifications to the susceptible-infected-recovered (SIR) model. The SIR model was modified by taking time-dependent rate parameters. From this modified SIR model, the basic reproduction number, effective reproduction number, herd immunity, and herd immunity threshold are redefined. The re-outbreak of the COVID-19 is a real threat to various countries. We have used the above-mentioned quantities to find the reasons behind the re-outbreak of this disease. Also, the effectiveness of herd immunity to prevent an epidemic has been analyzed with respect to this model. We have also tried to show that there are certain universal aspects in the spread and containment of the disease in various countries for a short period of time. Finally, we have also analyzed the current pandemic situation in India and have attempted to discuss the possibilities in order to predict its future behavior using our model. [ABSTRACT FROM AUTHOR]