Volume 13 | Issue 12 |

 Abstract

The genus Alcanivorax is a group of marine bacteria that has the capacity to degrade hydrocarbons, and they are important agents in bioremediation in marine oil-polluted environments; once hydrocarbons enter the water column, these bacteria can become numerically dominant in oil-afflicted waters, and use alkanes as their primary source of carbon. This article discusses Alcanivorax taxonomy, hydrocarbon degradation mechanisms, ecological functions, and methods of either stimulating or inhibiting Alcanivorax activity in marine ecosystems. Overall, more knowledge of Alcanivorax species will provide a knowledge base for biotechnological advances for sustainable bioremediation of marine oil spills.

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REVIEW ARTICLE ON ALCANIVORAX BACTERIA: A KEY PLAYER IN MARINE HYDROCARBON DEGRADATION

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The global transition towards electric mobility has created an urgent need for intelligent and efficient electric vehicle (EV) charging infrastructure. Conventional charging systems lack automation, remote monitoring capabilities, and the ability to interact with the power grid, leading to potential grid strain and inefficient energy consumption. This paper presents the design and simulation of a smart, automatic EV charging system leveraging the Internet of Things (IoT). The proposed system utilizes a NodeMCU (ESP8266) microcontroller as its core, integrated with voltage and current sensors to monitor the battery's state of charge (SoC). A relay module is employed to automatically control the charging process, preventing overcharging and enhancing battery longevity. The system communicates with an IoT cloud platform via the MQTT protocol, enabling users to remotely monitor real-time charging parameters and control the charging operation through a web-based dashboard. The complete system architecture, hardware, software logic, and simulation approach are detailed, demonstrating a cost-effective, reliable, and user-friendly solution for modern EV charging.

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Electric Vehicles (EVs), Internet of Things (IoT), Smart Charging, Energy Management System (EMS), NodeMCU, MQTT.

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This study investigated on "Achievement Motivation among undergraduate students". The study was Survey in nature. Achievement motivation tool was used to collect the data and this tool was developed by Prof.Pratibha Deo and Dr.Asha Mohan. For the present study researcher has adopted stratified random sampling technique. Objectives and hypothesis were to study the level of Achievement Motivation. To study the difference in Achievement Motivation among undergraduate students with respect to streams (Arts, Commerce, and Science). To study the difference in Achievement Motivation among Undergraduate Students with respect to Gender. To study the difference in Achievement Motivation among Undergraduate students with respect to type of college. Researcher selected 180 students of undergraduate studying in two colleges. In the present study t-test ANOVA and Correlation was used to analyze the data by using SPSS. The study examined achievement motivation showed significant variation across the three streams (F = 27.742, p < 0.05). This highlights that students from different academic disciplines have different levels of motivation, possibly due to varying academic demands and career prospects. Male students exhibited significantly higher achievement motivation (t=3.988, p < 0.05) compared to female students, indicating that males may be more driven toward academic success than females in this sample. There was no significant difference in achievement motivation between students from government and private colleges (t = 0.734), indicating that institutional type does not have a considerable impact on students' motivation to achieve.

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Motivation, Achievement Motivation and Undergraduate students,

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Energy is a key driver of economic development and social progress. In recent decades, a global transition has occurred from fossil-fuel-based energy sources to renewable alternatives such as solar, wind, hydropower, geothermal energy, and green hydrogen. These resources are considered clean and sustainable as they reduce greenhouse gas emissions and help mitigate climate change while offering significant socio-economic benefits. Rapid population growth and industrial expansion have intensified energy demand, making the adoption of alternative energy sources essential. For India, renewable energy provides a practical solution to its rising energy requirements. Government initiatives such as the Make in India program, along with supportive policies, have encouraged domestic manufacturing and attracted foreign investment, generating employment opportunities across sectors. In 2022, India became the world's fourth-largest producer of renewable energy, strengthening energy security and promoting sustainable development. The target of achieving 500 GW by 2030 further enhances opportunities for private-sector participation and technological advancement.

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Renewable energy, socio-economic, sustainable, greenhouse gas

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Abstract With an emphasis on the Udalguri district, this study investigates the political engagement, awareness, and perspective of the Tea Tribes s community in the Bodoland Territorial Council (BTC) elections within the Bodoland Territorial Region (BTR). One of the most disadvantaged groups in the area is the Tea Tribes, who were first brought to Assam as plantation labourers. One hundred fifty Tea Tribes voters participated in field surveys to gather primary data for the study, which uses a mixed-method approach to incorporate qualitative and quantitative data. The main tool for collecting data was an interview schedule. According to the findings, the percentage of votes cast by Tea Tribes s voters may seem high, but it does not represent meaningful or educated political engagement. Low levels of political awareness and varying perceptions of political engagement indicate that participation is often symbolic rather than substantive. In an area where their identity has long been disputed, some people view voting as a way to establish their citizenship. Participation is a calculated move to assert rights and representation for a community that is more politically unaware. The study highlights the necessity of focused political education and inclusion initiatives to guarantee that Tea Tribes democratic participation is meaningful and well-informed.

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Keywords: Tea Tribes, Political Participation, BTC Election, Political Awareness and Bodoland Territorial Region

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The growing energy demand and environmental concerns have increased interest in renewable sources like solar power However, solar energy is intermittent due to changing weather conditions. This project integrates supercapacitors into solar systems to stabilize power output Supercapacitors provide high power density, fast charge-discharge rates, and long lifespan, making them ideal for storing excess solar energy and supplying it when sunlight decreases. A boost converter regulates voltage, while an Energy Management System (EMS) optimizes charging and discharging cycles This setup ensures stable power delivery, improved efficiency, and system reliability Supercapacitors, known for the rapid charge-discharge cycles, high power density, and long lifespans, outperform conventional batteries in handling quick energy fluctuations and minimizing downtime By connecting supercapacitors in parallel with solar panels and using real-time monitoring for voltage and current, it is possible to smooth out energy supply variations, ensuring a more reliable and optimized solar power output. Such systems enhance energy buffering, enable efficient energy utilization, and improve overall system resilience, making them highly beneficial for both off grid and grid-connected solar installation. This study examines the variation of solar radiation which effect on storage performance, supporting application such as off-grid systems, EV charging.

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Solar photovoltaic system , Supercapacitor, Inverter, Energy storage system, Power management, Optimization, solar panel efficiency, microcontroller based control , Relay switching method DC-DC converter

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Mutual funds have become a fundamental component of contemporary investment portfolios, offering individuals an accessible and professionally managed avenue for wealth creation. By pooling resources and diversifying investments across equities, bonds, and other securities, mutual funds enable investors to achieve an optimal balance between risk and return. Their rapid expansion in recent decades is largely driven by rising financial awareness, technological advancements in online investment platforms, and supportive regulatory frameworks. As participation in mutual funds grows across diverse economic segments, understanding how investment volumes vary among income groups becomes increasingly important. This study examines the growth of investment and engagement levels of mutual fund investors across different income categories.

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Growth, mutual funds, investment, income group

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This research paper examines the transformation in retail investor behaviour due to the unparalleled rise of digital technology and social media in modern India. At over 150 million, the number of demat accounts has surged, with the average age of new investors plummeting as more young people join, mainly those below 35 years of age, who invest through mobile applications and social media platforms. The paper assesses the role of Instagram, YouTube, and Telegram in influencing investment decisions, creating phenomena such as FOMO and herding, which further lead to speculative trading. Although the enthusiasm of young investors has helped make the market more confident during declining trends, the paper also highlights the perils of options trading and the high percentage of retail traders incurring losses. Based on these findings, the study puts forward actionable recommendations to improve financial literacy and encourage responsible trading among the young and new investors. This paper seeks to find an appropriate balance between tapping the potential of the digital natives in the Indian stock market while reducing the risks involved with speculation.

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FOMO, herding, behavioral finance, social media, retail investors, digital natives, and the Indian stock market

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Background:The chronic metabolic disease known as diabetes mellitus (DM) is typified by ongoing hyperglycemia. It could be caused by resistance to insulin's peripheral effects, decreased insulin production, or both. In patients with diabetes mellitus, chronic hyperglycemia can harm several organ systems in concert with other metabolic abnormalities, resulting in the emergence of crippling and potentially fatal health issues. Methods and materials:This study aimed to assess the prevalence of type 2 diabetes mellitus in females aged 35 to 45 at Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences and Hospital is situated in Tamil Nadu, India's Kulasekharam. The study units consisted of women aged 35 to 45. For the study, a questionnaire is employed.When the study's purpose was explained, the women verbally agreed. The study had 30 female participants in total. The questionnaire consists of thirty questions covering topics such as pain, numbness, food cravings, itching in the extremities, medicine, and weight loss.Conclusion:We conclude that the development of comprehensive programs intended to educate people and raise awareness of particular health risks is essential to predictive and preventive healthcare. This emphasizes how crucial awareness is for managing and preventing type 2 diabetes.Adopting a comprehensive awareness and education campaign is crucial to improving predictive and preventive healthcare and eventually lowering morbidity and mortality.

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Diabetes mellitus,hyperglycemia,metabolic disorder,ulcer,blood sugar,itching in extremities

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This paper presents a comprehensive criminal face detection and identification system built using traditional face recognition techniques rather than deep learning or convolutional neural networks (CNNs). The solution is designed for real-time law enforcement assistance, secure access verification, and controlled surveillance environments. The system employs OpenCV's Haar Cascade Classifier for efficient and lightweight face detection, while facial feature extraction and recognition rely on dlib's Histogram of Oriented Gradients (HOG)-based model and 128-dimensional face encodings. The system maintains all identity records inside a local credential database, and facial images are stored securely in a structured local file system, ensuring privacy and data protection without cloud dependency. The proposed approach demonstrates reliable identification accuracy in controlled environments, fast inference speed, and low hardware requirements, making it suitable for organizations with limited computational resources. Experimental evaluations confirm the model's capability to consistently detect and recognize faces under stable lighting conditions and frontal orientations.

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Face recognition, Haar Cascade, HOG, dlib encodings, OpenCV, Criminal identification, Local database, Local file storage.

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