Volume 12 | Issue 3 |

 Abstract

The concept of Unpublished Price Sensitive Information (UPSI) is pivotal in understanding and regulating insider trading activities in India. Defined under Rule 2(n) of the SEBI PIT Regulations, 2015, UPSI encompasses a broad spectrum of confidential data pertaining to a company's financial performance, strategic decisions, and other material developments. This paper explores the legal framework surrounding UPSI, landmark judgments, notable observations from insider trading cases, and recent developments in SEBI regulations. Through an analysis of cases such as Mrs. Chandrakala vs. SEBI and PVP Global Ventures, this paper delves into the complexities of proving insider trading violations, emphasizing the interplay between market behaviors, informational dynamics, and legal requirements. Key considerations include the presumption of possession of UPSI, trading patterns based on UPSI, and the distinction between generally available information (GAI) and UPSI. Furthermore, recent developments such as SEBI's consultation paper proposing changes to the definition of UPSI highlight the ongoing efforts to enhance regulatory effectiveness in combating insider trading. The paper also discusses the implications of including material events from Regulation 30 of the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015 within the scope of UPSI, potentially leading to indefinite trading halts for certain individuals. Overall, this paper provides a comprehensive overview of UPSI regulation in India, addressing legal ambiguities, landmark judgments, and evolving regulatory approaches aimed at ensuring market integrity and investor protection.

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 Keywords

Insider Trading, India, Emerging Markets, Indian Judiciary, Emerging Markets, SEBI, PIT Regulations, UPSI, Stock Market.

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Creative Commons Attribution 4.0 and The Open Definition

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This study has been undertaken to the development of a deep learning-based system for predicting tomato leaf diseases, which are particularly significant in the agricultural industry due to the crop's high commercial value and contribution to food security. The proposed system utilizes a deep convolutional neural network (CNN) with transfer learning. The system determines plant health and predicts the specific disease if present.

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 Keywords

Deep learning, Convolutional Neural Network (CNN), Transfer learning,Image Preprocessing, Tomato leaf disease, Early detection, Web application, Agricultural productivity.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents a novel approach to enhance the efficiency of a multiplier for image blending applications by employing the Dadda multiplier architecture. The proposed design incorporates an efficient approximate compressors-based module and integrates an error-correcting module, contributing to a judicious trade-off between computational efficiency and accuracy. Notably, the error-correcting module achieves substantial compensation, reducing errors from 36.30% to 28.69%. Leveraging the inherent high-speed and low-power characteristics of the Dadda multiplier, the proposed architecture optimizes hardware complexity while maintaining an acceptable level of accuracy. Through comprehensive simulations and analysis, this validates the multiplier's effectiveness in real-time image blending scenarios, highlighting its potential for applications where computational speed and precision are critical.

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Dadda multiplier; Approximate Compressors; Error Correcting Module

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Creative Commons Attribution 4.0 and The Open Definition

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Betel leaves, derived from the Piper betle plant, have been utilized for centuries across various cultures for their medicinal, cultural, and social significance. This paper presents a comprehensive review of the bioactive compounds found in betel leaves and their pharmacological properties. Betel leaves contain a plethora of phytochemicals including phenols, alkaloids, tannins, and essential oils, which contribute to their diverse biological activities. These bioactive constituents exhibit antioxidant, antimicrobial, anti-inflammatory, antidiabetic, anticancer, and gastroprotective properties, among others. Additionally, betel leaves possess analgesic, wound healing, and oral hygiene benefits. This review explores the mechanisms of action underlying these pharmacological effects, highlighting their potential therapeutic applications. Furthermore, considerations regarding toxicity, dosage, and formulation strategies are discussed. Overall, betel leaves represent a promising source of natural compounds with significant pharmacological potential, warranting further research to elucidate their mechanisms of action and optimize their therapeutic use.

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piper betle, medicinal use, anti-oxidant, Pharmacological activity, Paan ka patta

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Creative Commons Attribution 4.0 and The Open Definition

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Nanoparticles find wide applications in various fields due to their change in properties from bulk to nanosize. Number of methods are available but green route synthesis finds to be attractive to all researchers. Green methods are preferred over traditional synthetic methods as they are eco friendly, using no carcinogenic solvents, cost effective, use of renewable reactants, use of catalyst. In this study copper nanoparticles are synthesized using green chemistry principles using an aqueous leaf extract of Mangifera leaves. Resultant copper nanoparticles are characterized by UV-Visible spectroscopy. Lambda max value for nanoparticles was obtained at 300 nm. While SEM analysis gives detailed morphology of final nanostructures. This method is effective and shows a futuristic approach as it supports green synthesis, reduces air and water pollution.

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Creative Commons Attribution 4.0 and The Open Definition

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Green chemistry principles, Copper nanoparticles, Mango leaf extract

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Creative Commons Attribution 4.0 and The Open Definition

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Greeva is a Sanskrit term where greeva stands for neck.Greeva means the back (posterior) part of the neck or tendon of the trapezium muscle. Ayurvedic classics in many contexts have collectively taken head & neck as one entity & named it as Sirogreeva & placed them as Urdhvajatrugata organs (e.supraclavicular organs). Acharya Charak has also placed it under "Dash Pranayatana" Although no specific disease has been mentioned with the name Greevashool in our Ayurvedic texts but it can come under the Vata Nanatmaja vikaras and features of Vata Prakopa respectively on the basis of Lakshana Pradhanta. In this paper small attempt has been taken to describe Greevashoola according to Ayurvedic text.

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Greeva, Sirogreeva ,Urdhvajatrugata, Dash Pranayatana and Greevashoola.

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Blockchain technology is an emerging and rapidly growing within recent times. Blockchain technology is popularly used in various industries across the globe. The reason behind the usage of this technology is because it is very versatile, secure and globally accessible. The trend of blockchain was introduced with the introduction of cryptocurrencies. The concept of blockchain saw a major surge with the introduction of NFTs along with the usage cryptocurrencies. Empowering the authorization and security provided by Blockchain, we have implemented a voting system using Cryptocurrencies and Ganache.

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Cryptography, Blockchain, MetaMask, Ganache, Voting System

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Creative Commons Attribution 4.0 and The Open Definition

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Artificial Intelligence (AI) and robotics stand at the forefront of technological evolution. The amalgamation of AI with robotics has led to transformative breakthroughs, altering the way tasks are performed, bringing precision, efficiency, and intelligence to automation. This paper explores the intersection of AI and robotics, its evolution, current applications, and the profound impact on various sectors. Through case studies and analysis of current research trends, we highlight the transformative impact of coordinated AI in various domains such as transportation, health care, manufacturing.

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Artificial intelligence, Robotics, Machine learning, Human-robot interaction, Humanoid robots, Applications of AI in robotics, Algorithms, SlAM, Deep learning, Convolutional Neural Networks (CNNs).

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This research paper presents the development of a landmine detection system employing the STM32 microcontroller platform. Landmines pose a significant threat to civilian populations and military personnel in conflict zones worldwide. Traditional methods of detection are often slow, inaccurate, and hazardous. Thus, there is a pressing need for efficient, reliable, and cost-effective landmine detection technologies. The proposed system utilizes an STM32 microcontroller along with appropriate sensors and signal-processing techniques to detect the presence of buried landmines. The paper discusses the design, implementation, and evaluation of the landmine detector, highlighting its potential for real-world deployment in humanitarian and military applications.

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Landmine detection, STM32 microcontroller, Sensor technology, Signal processing, Humanitarian demining.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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