Volume 13 | Issue 8 |

 Abstract

The Solar flares are sudden powerful explode of energy from the Sun spread across the space that can seriously disturb Earth's magnetic shield, the magnetosphere. This unwanted energy can cause for real problems in our daily lives, such as interrupting satellite communications, GPS signals, and even causing power outages on the ground. This research our aim is to focuses on understanding and predicting how solar flares can Earth's magnetosphere by studying the powerful superstorm which happened in May 2024. The protective boundary of the magnetosphere was pushed unusually close to Earth, putting satellites and other systems at risk during this storm. We may be able to recreate how the magnetosphere responded during this event by using advanced computer models which simulate the movement of charged particles and magnetic fields. We also used machine learning tools to predict when solar storms would hit Earth and how strong they would be. The machine learning model may warn with impressive accuracy, giving us valuable time to protect our technology. This study shows that forecasting systems combined with detailed physical models can helps us better prepare for space weather events that could disrupt modern life. The storm raised in MAY 2024 had real impacts, including affecting airline routes, causing satellite glitches, and challenging power grid operators. As the Sun becomes more active in the coming years, therefore it is essential to keep improving our ability to predict and respond to these space weather events to protect both our technology and our daily activities.

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 Keywords

Solar Flares, Magnetosphere, Space Weather, Geomagnetic Storms, MHD Modeling, AI Forecasting, CMEs, Ionosphere

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Purpose: We recommend employing project management to manage sports events. To this purpose, we recommend an adaptation of the PM² project management methodology, which was developed inside the European Commission, to manage sports projects. Design/methodology/approach: We offer theoretical analyses arguing about what is a project in sport, the roles of event and sport management, and a theoretical adaptation of PM² methodology to sport management. While this study presents a tailored PM² approach designed for sports events, it also presents structured frameworks to incorporate two key dimensions (Risk Management and Sustainability Practices) to consider operational vulnerabilities and environmental accountabilities in sports events management. Results: We demonstrate that event management could be improved by PM² methodology with several adjustments. The primary adjustment involves splitting the original project execution phase into two distinct phases - the deployment phase and the project execution phase (stricto sensu). The first narrowly encompasses all the activities carried out in preparation for the sports competition, while the latter addresses the complexity of the precise dates of the competition in question, which includes simultaneous presence, mass participation of participants, and mass presence of spectators for this event. We also suggest changes to the original PM² governance model, to allow for a market orientation in order to maximize economic return of the event and why it includes the idea of the "extended customer," which includes the event owner, the participants and the spectators, as well as a risk management system across all phases of the PM² lifecycle framework and sustainability practice suggestions, in particular the minimization of waste and energy usage, and environmental impact assessments (ensuring events are not just well-managed, but resilient and environmentally friendly). Research limitations/implications: There needs to be more empirical research to examine how this adaptation of PM² gets implemented, especially the risk frameworks and sustainability impact indicators prescribed. Practical implications: We provide an adaptation of PM² methodology for the event managers enabling them to use project management standards in their respective events. Our adapted version reflects the marketing mix and market orientation, often referred to by event managers along with new tools and techniques to mitigate and manage risks and sustainable choices during the lifecycle of the project. Social implications: As an outcome, the rethinking of the role of sports events and managers to a project management perspective, will allow the use of cost-benefit analysis when developing a sport event which enables sports events to be not only successful but also profitable, sustainable or responsible and efficient. Moreover, the integration of sustainability principals and rigorous risk management, increases stakeholder trust in a future focused approach aligning with growing environmental and social governance (ESG) expectations globally. Originality/value: PM² is being applied for the first time to events, specifically sport events. The specific unique aspects of PM² make it useful in any sector, such as sport events where the manager may not have the project management standards and methodologies transferable experience. This extension proposal takes a progressive step in aligning project governance with newer imperatives of resilience to risk and sustainable development.

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 Keywords

Sports Management, Sports, Event Management, Management

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 Abstract

?? ??? ???? ????? ????? ???????????? (Information and Communication Technology - ICT) ?? ?????? ?? ??????? ?? ??? ??? ??????? ?? ?????? ?? ????????????? ???????? ???????? ???? ??, ??????? ???????? ?? ???????? ????? ?? ?????? ???? ????? ???????????? ?? ????? ?????? ?? ???? ?????? ?? ?????? ????? ?? ?????? ?? ???? ??, ???? ???? ?????????? ????? ?? ????? ?????, ?????? ?????? ?????, ???? ?????? ????????, ?????? ??????? ?? ????? ???? ????? ??????? ??????? ?? ???? ???? ??? ?? ?????? ?? ???????, ?????????, ?????? ?? ???????????? ?????? ?? ????? ???? ?? ?? ICT ?? ?????? ?? ?????? ?? ????? ?? ?? ?? ???? ???? ?????? ?? ??????? 20 ??? ????????? ?? ??? ????? ? ???????? ?? ?? ???????? ?????? ??? ?? ?? ???? ??? ICT ?? ?????? ?? ??????? ????, ???????? ?????? ??? ??????? ????? ?? ????? ???? ?? ?????? ???????? ???

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????? ????? ???????????? (ICT), ??? ????? (Juvenile Delinquency), ????? ????? (Cyber Crime),???? ??????, ????? ????? (Juvenile Justice), ?????? ??????, ?????? ????? ,????? ??????? (Adolescent Behavior)

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This work presents the design and implementation of an All-Digital Phase-Locked Loop (ADPLL) on the PYNQ-Z2 FPGA platform. The proposed system addresses limitations of traditional analog PLLs by utilizing fully digital components, enabling higher precision, scalability, and seamless integration with modern digital systems. The ADPLL architecture integrates a Time-to-Digital Converter (TDC), a Proportional-Integral Digital Loop Filter, a Digitally Controlled Oscillator (DCO), and a Frequency Divider. A normal filter is employed to improve noise immunity and enhance loop stability. The design is implemented in Verilog, synthesized, and deployed on the PYNQ-Z2 FPGA. Simulation and hardware tests validate the system's ability to achieve minimal jitter, zero steady-state phase error, and high synchronization accuracy, making it suitable for communication, signal processing, and clock synchronization applications.

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All-Digital Phase-Locked Loop (ADPLL), PYNQ-Z2 FPGA, Time-to-Digital Converter (TDC), Digital Loop Filter, Digitally Controlled Oscillator (DCO), Frequency Divider, Phase Synchronization.

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This study evaluates the cognitive level of textual questions in the Algebra unit of the Class X Mathematics textbook prescribed by the Mizoram Board of School Education, using Revised Bloom's Taxonomy (RBT). A content analysis of end-of-chapter questions across five chapters (Polynomials, Linear Equations in Two Variables, Quadratic Equations, Arithmetic Progression, and Sets) was conducted. Results indicate a predominant focus on lower-order thinking skills (LOTS), with 81.9% of questions categorized as "Applying" (C3), while higher-order thinking skills (HOTS) such as "Analyzing" (C4) and "Evaluating" (C5) constituted only 18.1%. Notably, "Creating" (C6) questions were absent. The findings highlight an imbalance in cognitive demand, underscoring the need for curriculum revisions to incorporate more HOTS-based questions to foster critical thinking and problem-solving abilities among students.

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Algebra, Cognitive Level, Revised Bloom's Taxonomy, Mathematics Textbook, Mizoram Board.

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This paper analyzes N.K. Jemisin's Broken Earth trilogy as a feminist ecopolitical allegory that links environmental injustice to systemic oppression. Drawing on ecofeminist theory, postcolonial critique, and narrative analysis, the study explores how Jemisin's depiction of the Anthropocene foregrounds the intertwined exploitation of the Earth and marginalized bodies, particularly women and orogenes. The Sanzed Empire's extractive systems mirror real-world structures of capitalism, colonialism, and racial hierarchy, while the trilogy's resistance movements center care, reciprocity, and community-based governance. Through narrative strategies such as second-person perspective and the reimagining of the Earth as an active political subject, Jemisin reframes liberation as ecological as well as social. The analysis argues that the trilogy's vision resonates with contemporary climate justice movements, calling for the dismantling of intersecting systems of domination and the cultivation of sustainable, reciprocal relationships with the planet.

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Keywords: Feminist Ecopolitics, Environmental justice, Political allegory, Anthropocene, Ecofeminism, Climate justice, Postcolonial critique, Speculative fiction Resistance, Narrative perspective

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The monetary growth of a country mainly depends upon the agricultural conditions of that country. Meeting the food needs of the current population is becoming more difficult due to population growth, climatic fluctuations, and resource inadequacy. Smart farming, additionally referred to as precision agriculture, and has appeared as an advanced technique to tackle modern difficulties in order to provide agricultural sustainability. Precision agriculture (PA) is a cutting-edge farming method for maximizing crop yield, minimizes waste, and enhances sustainability by utilizing technology. PA increases productivity and resource efficiency by endowing farmers to make knowledgeable decisions that are customized to individual areas within their fields through the use of data from soil sensors, satellite imagery, and drones. The shift is greatly aided by machine learning (ML), which analyzes and discerns patterns in enormous amounts of agricultural data to provide useful insights. An orderly analysis on the applications of machine learning has been presented by the author in this article. Various ML algorithms like deep learning, regressions analysis, CNN have been applied to monitor the crop health and its yield prediction. It also includes the crop disease prediction at earlier stage. In order to predict outcomes like when to plant, when to water, and whether to apply pesticides, these algorithms can process inputs from a variety of sources, including climatic data, soil composition, and real-time sensor data. They do this by learning from past trends. Farmers can apply site-specific management techniques with the integration of ML, optimizing crop yield while reducing environmental impact. This article examines the limitations and challenges encountered by precision agriculture regarding management of data, technology adoption, and cost-effectiveness.

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Precision Agriculture, Machine Learning, Smart Farming, Artificial Intelligence

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Creative Commons Attribution 4.0 and The Open Definition

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This literature review examines the integration of artificial intelligence (AI), sensor networks, and IoT technologies in modern agriculture, with a focus on weed detection, animal intrusion prevention, irrigation automation, and soil health monitoring. It analyzes recent journal publications (2020-2025) that utilize deep learning models such as CNN and YOLOv5/YOLOv8 for real-time object detection, along with smart sensors for environmental data collection. Mobile applications and microcontrollers like Raspberry Pi and NodeMCU are also evaluated for automation and farmer interaction. The review highlights the limitations of existing systems--including poor cross-domain performance, reliance on internet connectivity, and lack of regional language support--and identifies the need for an integrated, edge-based, multi-functional solution like the Krishi ????? - The AgriFusion project. This study is intended to guide future work on accessible and sustainable smart farming platforms for smallholder farmers.

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Weed Detection, IoT in Agriculture, Smart Irrigation, Animal Intrusion Detection, CNN

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Sphaeranthus Indicus Linn or East Indian Globe Thistle is a multi-branched aromatic herb consisting of various medicinal properties, and is used in the treatment of skin conditions, as an antimicrobial, immunomodulator, immunostimulant and in wound healing traditionally.[9] All the parts of the Sphaeranthus Indicus have been utilized for the treatment of various disease conditions out of which the marketed herbal formulations of Sphaeranthus Indicus were investigated for its toxicity profile which showed dose dependent toxicity. Toxicity profile of this marketed formulation was not investigated in previous studies Aim: - Explore the acute and subacute toxicity profile of the following two marketed herbal formulation of Sphaeranthus indicus linn for the safe use of traditional medicine and explore its potential for further effectiveness. Method: - In Acute toxicity study of both herbal formulations, Total no. of animals used were 24 male Swiss albino mice, weighing 25-30g, randomly assigned to experimental groups of 5mg/kg,50mg/kg, 300mg/kg and 1000mg/kg with 3 mice each and receiving single dose of the extract at 5mg/kg b.w,50mg/kg,300mg/kg and 1000mg/kg b.w respectively. Animals were monitored for 14 days for signs of toxicity, behavioral changes, mortality etc. In Sub-acute toxicity study, Total no of animals used were 70 Swiss albino mice weighing 25-30 g consisting of male and female Swiss albino mice randomly assigned to experimental groups of 50mg/kg, 1000mg/kg ,2000mg/kg with control group been given distilled water. The extract of herbal formulation of Sphaeranthus indicus was given at the doses of 50mg/kg,1000mg/kg,2000mg/kg per body weight of the mice for 28 consecutive days. The studies were conducted in compliance with OECD guidelines 423 and 407. Results: - Acute toxicity study showed no mortality up to the dose of 1000mg/kg, but mortality rates increase with higher doses. In subacute toxicity study, there was no mortality, up to the dose of 2000mg/kg with increase in deaths at higher doses. The hematological and biochemical analysis of the blood parameters don't show much significant differences. The histopathological analysis of liver shows marked lesions at higher doses. Conclusion: - It is concluded that the oral administration of doses of herbal formulation of Sphaeranthus indicus in acute study don't cause any mortality or other changes up to the level of 1000mg/kg. At higher doses there are possibilities of finding gross changes. In subacute study, no significant changes in the hematological, biochemical, and histopathological parameters were observed. There is mild grade of lesion with repeated and daily dosing of the drug at higher dose of 2000mg/kg indicating that at higher doses with repeated dosing there is mild level development of toxicity signs.

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Sphaeranthus indicus Linn, Hematology, Biochemical, Histopathology, toxicity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Integrating IoT, Blockchain, and Deep Neural Networks (DNNs) creates a secure, intelligent, and decentralized data ecosystem. IoT devices collect real-time data, while blockchain ensures tamper-proof, transparent, and trusted data exchange. DNNs analyze this data to extract insights and enable predictive decision-making. Blockchain smart contracts automate secure communication and access control, while federated learning allows DNNs to train without exposing raw data. This synergy enhances scalability, privacy, and resilience, making it ideal for applications like smart cities, healthcare, and industrial automation. The model overcomes traditional ML limitations by distributing intelligence and trust across the network.

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 Keywords

IoT, Blockchain, Deep learning, Deep Neural Network, ML, Edge Computing, Federated Learning

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Creative Commons Attribution 4.0 and The Open Definition