Volume 13 | Issue 6 |

 Abstract

Stevia (Stevia rebaudiana) is a natural sweetener that thrives in subtropical climates with long days and warm temperatures, making it a sustainable crop with high commercial potential. It grows best in well-drained, slightly acidic to neutral soils and requires consistent moisture with proper drainage. Stevia can be propagated via seeds, stem cuttings, or tissue culture, with clonal propagation offering more consistent results. While Stevia does not demand heavy fertilization, balanced nutrient management enhances leaf yield and quality, with special attention to phosphorus and potassium levels. Water management is crucial, and drip irrigation is recommended to avoid waterlogging. Weed control, particularly in the initial stages, is vital for successful cultivation. Pest management may involve treating caterpillar infestations and fungal diseases, with appropriate chemical treatments. Stevia's harvesting typically occurs 90-110 days post-transplantation, with the leaves separated and dried to preserve their sweetness. The plant's primary sweetening compounds--stevioside and rebaudioside A--are extracted for use in food, beverages, and health products. Stevia is known for its medicinal properties, including regulation of blood sugar, support for diabetes management, and potential weight control benefits, making it a valuable alternative to sugar. Its use has grown significantly, especially in the food and beverage industry, where it serves as a low-calorie sweetener. The profitability of stevia farming is promising, with a high benefit-cost ratio and increasing demand for natural sweeteners. Challenges include its bitter aftertaste, which is being addressed through breeding and processing innovations. Stevia's market opportunities are expanding with collaborations across industries, and its sustainability is further enhanced by the utilization of by-products like stems and seeds for animal feed or fertilizer. Stevia is gaining global recognition for its health benefits, affordability, and versatility in food and industrial applications.

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Stevia, scientifically known as "Stevia Rebaudiana Bertoni", it is a naturally sweet plant native to the Rio Monday valley in Paraguay's northeastern highlands. (Goyal et al., 2010). Often called sweet leaf, honey leaf, or candy leaf, this remarkable herb is gaining global popularity as a healthy alternative to sugar, especially for those watching their sugar and carbohydrate intake (Lemus-Mondaca et al., 2012). With zero calories, Stevia is becoming a favorite among health-consci

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Gender perspective in literature has been a great issue which emphasizes the importance of the social construction of the gender and the assignment of specific roles, responsibilities and expectations to men and women. Both the sexes must be given equal importance for a strong social set up but usually women fail to get their own identity in the male dominated society. Since time immemorial they have been relegated to secondary place in relation to male. Man suffers with male superiority that looks down upon the women and makes man 'absolute' and women 'subject', a silent sufferer. A vast majority of women is reconciled to a life of humiliation in the form of gender bias while performing the roles of wives, mothers etc. in the society they live in. In order to establish their identity and keeping in mind their subjugation in the hands of their male counterparts, the women have often tried to do away with supremacy of males; they are more attracted towards the same sex, giving rise to lesbian relationship. Ismat Chughtai, the great name of Urdu fiction is known for her indomitable spirit and other evolving conflicts in modern India, while resolutely refusing to bow to conventional norms, abstinence, and modesty. But Ismat Chughtal's "Lihaaf" foreshadows the idea of exploitations of another corporal body to fulfil one's desires. The story epitomizes the excessive degree of suppression that one undergoes. It aptly suggests how the life of a woman by training is confined to her body; how one's desire are manipulated and how one swings between hopes and ethics. Khurshid Akram belongs to the generation of Urdu writers which came to the fore during the 1990s. His volume of short stories, titled Ek Ghar MashrootMuafinaama contains a number of stories. The story "Coming" is one of the representative stories depicting the state of prostitute in our society. He has portrayed the realities hidden behind the lives of the marginalized women, especially the sex workers. Both the writers have tried to depict objectively the characters in the novel. There is no possibility of reading simply 'what is there' is the texts, for the texts does not have the mode of being of some of neutral object. It is always possible to show that a reading of a text that claims complete objectivity is itself an interpretation. A person reading a text is himself a part of the meaning be apprehends Indeed, Ismat Chaughtai and Khurshid Akram both have tried to analyse the stories critically. The present paper, intends to present a comparative study of Ismat Chughtai's "Lihaaf" and Khurshid Akram's "Coming", related to the writer's points of view about the status of such women as are considered subjugated in our patriarchal social setup. They often suffer from identity crisis and as a result take recourse to such aberrations as are not given social sanction.

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Patriarchal attitude; sexuality; exploitation; identity crisis.

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With the continuous rise in global internet usage, the need for dependable and high-speed connectivity has become more critical. Although Wi-Fi (Wireless Fidelity) is commonly used, it can become expensive and often suffers from reduced speed, especially when more than two routers are connected simultaneously. Light Fidelity (Li-Fi) presents a cutting-edge solution to these issues by enabling wireless communication through visible or infrared light, based on the principle of Visible Light Communication (VLC).This study proposes a system that facilitates the transmission of different data types--such as text, audio and images--using VLC technology. The data is sent via high-intensity LED arrays at the transmitting end, while a photodiode at the receiving end detects and converts the light signals back into data. The system's effectiveness is analyzed under varying conditions, including changes in transmission distance, light intensity, and signal quality.Li-Fi technology can deliver data at rates reaching up to 500 Mbps over short ranges using LED lights, or around 10 Kbps when standard lamps are used. Experimental findings validate the system's ability to transfer data efficiently under different environmental scenarios. Moreover, the concept is extended to demonstrate its potential in indoor location-based services, revealing its wide scope of application

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Li-Fi, Visible Light Communication (VLC), wireless communication, LED transmission, photodiode receiver, high-speed data transfer, indoor positioning, data transmission, light intensity, transmission distance, text/audio/image transfer, Wi-Fi alternative, infrared communication

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ABSTRACT: This study aimed at investigating the effect of Dolomite material as partial replacement of fine aggregate on strength properties of concrete. The conventional concrete is made up of cement, fine aggregate, coarse aggregate and water, and the effect of aggregate in concrete properties are very important. This project attempts to study the use of dolomite Aggregate as fine aggregate replacement to crushed sand considering the increasing demand from construction industry and depleting crushed sand availability, in this regard dolomite Aggregate as fine aggregate (FA)replacement might be a sustainable option. Further dolomite Aggregate was chosen for this study, considering its local availability in abundance in the region of Guntur and its transportation within the region proves to be cost effective in comparison with crushed sand .Concrete design mix were prepared to achieve concrete grades of M30.Hence, in this research, we have proposed an eco-friendly solution by investigating the utilization of Dolomite aggregate with 0, 10, 20 and 30% as fine aggregate in concrete .Dolomite aggregate was characterized to determine its suitability as fine aggregate by determining physical and chemical properties as well as investigating its morphology at micro and macro level. Thereafter, in fresh state, the Dolomite aggregate concrete was tested for slump, shrinkage and density while in hardened state; it was tested for Compressive Strength, Split Tensile Strength, Flexural Strength, Ultrasonic pulse velocity, and Rebound Hammer at the age of 7, and 28 days. At 20% replacement of fine aggregate maximum strength shall be occurred

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Dolomite, Fineaggregate , compressive Strength , Tensile Strength ,Flexural Strength, Rebound Hammer,UPV

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Creative Commons Attribution 4.0 and The Open Definition

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The Real-Time Facial Recognition Electronic Voting System is an advanced solution aimed at improving the security, accuracy, and transparency of electronic voting. It leverages deep learning-powered facial recognition to identify registered voters by analyzing their unique facial characteristics. This reduces the chances of errors, such as mistaken identity, and ensures that only legitimate voters can participate. To add an extra layer of security, the system sends a one-time password (OTP) to the voter's registered mobile number after successful facial recognition. This step helps prevent unauthorized access and minimizes the risk of voter fraud. Once both facial recognition and OTP authentication are verified, the voter gains access to the voting platform, where they can securely cast their vote. Each vote is instantly recorded on a blockchain ledger, making it tamper-proof and ensuring that no one can alter or manipulate the results. Because blockchain is decentralized, it also enhances transparency, allowing voters, election officials, and auditors to verify the election outcomes independently, without relying on a single central authority. With its realtime processing, the system works efficiently with minimal delays, making it an ideal choice for large-scale elections and other real-world voting scenarios.

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Facial Recognition, Electronic Voting, Deep Learning, OTP Security, Blockchain, Cybersecurity, Transparent Elections.

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Cloud computing has emerged as a pivotal technology in modern computing, offering vast resources for computation and storage to users on-demand. However, the substantial energy consumption associated with cloud data centers poses environmental concerns and financial burdens. Addressing this challenge requires the development of energy-efficient mechanisms, particularly in task scheduling, which plays a crucial role in resource allocation and utilization. This paper presents the design and implementation of an energy-efficient task scheduling algorithm tailored for cloud computing environments. The proposed algorithm aims to minimize energy consumption while meeting performance requirements, such as task completion time and resource utilization. Leveraging dynamic voltage and frequency scaling techniques, the algorithm intelligently allocates tasks to virtual machines, considering workload characteristics, resource availability, and energy profiles. To evaluate the effectiveness of the proposed algorithm, extensive experiments are conducted using simulation-based approaches. The results demonstrate significant reductions in energy consumption compared to traditional scheduling approaches, without compromising on performance metrics. Furthermore, sensitivity analysis is performed to assess the algorithm's robustness under varying workload intensities and system configurations. The findings of this study underscore the potential of energy-efficient task scheduling algorithms to mitigate the environmental impact of cloud computing while enhancing cost-effectiveness for service providers and users. The proposed algorithm contributes to the ongoing efforts in green computing and sustainable IT practices, paving the way for more environmentally friendly and economically viable cloud infrastructures.

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Cloud computing, Energy consumption, Energy-efficient, Task scheduling

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Creative Commons Attribution 4.0 and The Open Definition

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The integration of Artificial Intelligence (AI) into recruitment processes has changed traditional hiring methodologies, enabling more subtle assessments of candidates' competencies. This paper presents an AI-driven mock interview system that evaluates both technical proficiencies and soft skills through multimodal analysis. The system employs computer vision techniques to analyse facial expressions and gestures, utilizing datasets like FER+ for emotion recognition. Natural Language Processing (NLP) models, such as BERT, are finetuned to assess the semantic relevance and clarity of candidates' responses. Additionally, computational paralinguistics extract vocal features--intonation, pitch, and speaking rate--to infer affective states and communication effectiveness. By integrating these modalities, the system provides comprehensive feedback, translating complex model outputs into actionable insights, thereby facilitating targeted improvements in interviewee performance. This approach not only enhances the objectivity and efficiency of candidate evaluations but also addresses ethical considerations by ensuring interpretability and transparency in AI-driven assessments.

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Artificial Intelligence, Mock Interview System, Multimodal Analysis, Facial Expression Recognition, Natural Language Processing, BERT, Computational Paralinguistics, Soft Skills Assessment.

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Oils contamination has been a global issue, regionally, pollution from oils spills. Oils contain several compounds which are harmful to the environment, several ways have been implemented to curb the effects of such compounds in the environment. Oil pollution from spills, industrial discharge, and urban runoff poses severe environmental and health risks to human, aquatic life, as well as plants. Microbial degradation has proved to be a more effective and reliable way of remediating polluted environments. Certain Oils like Petrol Gasoline contains Petroleum Hydrocarbons. The study focus on the degradation of Petroleum hydrocarbons by bacteria, the bacteria was extracted from soil from a petrol gasoline pump. The study was to show factors which influence the degradation process, ph. ,oxygen levels, temperature and nutrient availability. The bacteria was able to simplify the harmful compounds into non toxic substances, since it uses Petroleum hydrocarbons as source of carbon. With the presence of oxygen the aerobic mechanism became possible and more effective. The study also indicates factors that could also enhance the efficiency of the biodegrading bacteria in degrading of Petroleum hydrocarbon. Genetic engineering has proved to be an essential tool in modifying and amplifying bacteria on its capability to degrade Oils. Highlighted in the study as well is the issues encountered in the process of bioremediation of environments affected by oil spills, or the existence of Petroleum Hydrocarbon, it is expensive to carry out such bioremediation processes. The paper also discusses future directions in place to enhance biodegradation by microbials, such as synthetic biology on bacteria to make it more effective towards conversion of Petroleum Hydrocarbons. Since this topic has been a sensitive issue ,more resources have been put in place for more research on how to reduce pollution by oil spills.

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Microbes degrading oils

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In current era, Artificial Intelligence (AI) is an emerging, innovative and speedy development digital technology. The application of AI has become more and more obvious technology in education, especially teaching and learning activities. The uses of AI in education can assist teachers to enhancing their teaching efficacy for effective teaching. AI is promoting the teaching efficacy among teachers for meaningful instruction, efficient classroom activities and quality of teaching. Also it helps to improve the students' adaptive learning and online learning activities. The aim of the study is to ascertain the level of use of uses of AI in teaching efficacy of prospective teachers. A survey method was used for data collection through questionnaire (Utilisation of artificial intelligence in teaching efficacy). The samples of 300 prospective teachers were selected by stratified random sampling technique. The samples were studied in B.Ed., colleges of Education of Namakkal district, Tamil Nadu. The questionnaire was consists of 40 statements based on the Likert scale. The responses were 'always' (3), 'often' (2) and 'sometimes' (1). The findings of the results revealed that the prospective teachers have high level of utilisation of AI in teaching efficacy. Also, the study found the results showed that there is no significant difference in utilisation of AI in teaching efficacy among prospective teachers with respect to their categorical variables such as gender, locality of prospective teachers, medium of instruction, stream of subject, age, computer knowledge and AI used in teaching. The suggestion of the study is the prospective teachers are using the AI in teaching it enhance to effective teaching efficacy in their classroom activities.

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 Keywords

Prospective Teacher, Teaching Efficacy, Artificial Intelligence (AI), Utilization.

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Creative Commons Attribution 4.0 and The Open Definition

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India has '140 million hectares' of net cropped area, next only to that of the 'USA'. Similarly, India's irrigated area is also the second largest in the world, next only to 'China'. The country is well-endowed with natural resources and varied climatic circumstances, and much of the land in India can be double cropped. Traditionally, crop production has accounted for over four-fifths of the agricultural output, but over the past two decades or so the condition has changed dramatically. The share of livestock in the agricultural production has risen sharply and now accounts for close to 30 per cent of the total agricultural output. Overall, the composition of agricultural output has gradually been shifting towards high-value crops and animal products, especially milk. The performance of agricultural sector has been quite inspiring, making the country self-reliant in food. The country has even started exporting some food products. This performance is due largely to 'green revolution'. The Present review paper emphasis on trends, challenges, evolution and policy frame work on Agriculture sector in India.

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Agriculture, Animal Products, Climate, Crop, Food, Green revolution and Policy

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Creative Commons Attribution 4.0 and The Open Definition