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Phytochemicals and Biological Activities of Ceriops tagal (Perr.). C. B. Rob.
Plants have been used for medicines since ancient times as they serve critical needs and are easily accessible. In recent years, various nations have seen a major increase in the use of plant-based treatments, resulting in a significant rise in the global demand for herbal products. This chapter describes Ceriops tagal, a mangrove species with excellent potential for bioactive components and biological activity. The majority of the distinctive secondary metabolites and their analogs reported in this plant are di-, tri-, and tetra-terpenoids (dolabrane, lupane, oleanane, dammarane, and pimarane), phenolics, and steroids from the hypocotyls, roots, and aerial parts. Various studies reported 97 terpenoids and 14 other metabolites. Many biological activities have already been identified from various extracts, including anticancer, antidiabetic, antioxidant, anti-inflammatory, antibacterial, and neurotrophic activities. In this chapter, we explored the biological potential of C. tagal, particularly its anticancer and neuroprotective activities, and it may be valuable for young researchers looking into the potential drug for chemotherapeutic and neurotrophic properties for the treatment and prevention of cancerous and neurological disorders. Springer Nature Switzerland AG 2026. -
Phytochemicals and Biological Activities of Flowers of Clitoria ternatea (Butterfly Pea)
In recent years, many countries have witnessed a significant rise in the adoption of plant-based remedies, leading to a substantial increase in the global demand for herbal resources. This chapter explores Clitoria ternatea, a species with remarkable potential due to its bioactive constituents and diverse biological activities. Most of the unique secondary metabolites and their analogues identified in this plant are anthocyanins, including ternatins, preternatins, cyanidin, and delphinidin, along with phenolic acids, terpenoids, and phytosterols derived from the flowers. Altogether, 32 anthocyanins and 19 additional metabolites have been documented across various studies. Different extracts of C. ternatea have demonstrated a wide range of biological properties, notably antioxidant, antimicrobial, anti-inflammatory, antidiabetic, cytotoxic, and anticancer activities. To support young researchers investigating potential chemotherapeutic agents for the treatment and prevention of cancer and other diseases, this chapter focuses on the biological functions of C. ternatea, with particular emphasis on its anticancer and antidiabetic benefits. 2026 Hosakatte Niranjana Murthy. -
Patriarchal Constraints in Everyday Lives: Gender Roles, Matrilineality, and the Status of Contemporary Khasi Women
The Khasi tribe from Meghalaya in northeast India practices a matrilineal system, which is believed to be more egalitarian than patrilineal systems. The women of the Khasi tribe are often regarded as having a higher status than other women in India. However, despite belonging to a matrilineal society, Khasi women still face challenges in their social lives stemming from patriarchal constructs. This qualitative study examines the social status and subsequent challenges faced by Khasi women in contemporary India. Using in-depth interviews and observations of thirty urban and rural Khasi women in the East Khasi Hills District of Meghalaya, the study reveals how Khasi women experience contradictory and challenging roles, relationship dynamics, and gender stereotypes in their lives. More studies should examine the problems and challenges that Khasi women face in their society despite the benefits of a matrilineal system. 2026 Bridgewater State College. All rights reserved. -
Analysis of an Existing Method for Detecting Adversarial Attacks on Deep Neural Networks
Analyzes the existing method of detecting adversarial attacks on deep neural networks, proposed by researchers from Carnegie Mellon University and the Korean Institute of Advanced Technologies (KAIST) Ko, G. and Lim, G in 2021. Examines adversarial attacks, as well as the history of research on the topic. The paper considers the concepts of interpreted and not interpreted neural networks and features of methods of protection of the types of neural networks considered. The method for protecting against adversarial attacks is also considered to be applicable to both types of neural networks. An example of an attack simulation is given, which makes it possible to identify a sign showing that an attack has been committed. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Gamification and Game-Based Learning: A Systematic Review and Comparative Analysis
In the modern world, characterized by the rapid development of technology and digitalization of almost all spheres of life, it is necessary to keep up with the times and gradually introduce information technology into our lives. This will allow us to remain competitive in a changing world, take advantage of new opportunities and improve our quality of life. It is important to understand that information technology is not just a fashion trend, but a necessary tool for successful development and progress. The paper examines the very concept of gamification, the main methods of introducing gamification into education, highlights the advantages of learning with the addition of gamification, and also works on comparing learning with and without gamification elements. The introduction of game elements into the educational process helps to improve the perception of educational material, as well as increase the level of motivation of the students themselves. It is worth noting that the learning process with the addition of game elements helps to improve attention, develop logical thinking, as well as analyze various situations. Gamification can be viewed from several angles. For a teacher, this teaching method will help to capture the attention of children, which will help create a working atmosphere in the classroom. And for students, gamification is a great opportunity to explore really important topics in game mode. They will have an increased interest in learning, which will have a beneficial effect on their further academic performance and learning. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Machine Learning Research Methods for Identifying Inaccurate Content
Social media, especially when disseminating news, is a valuable information resource. The paper presents methods for detecting fake news, comparing their effectiveness, identifying existing problems, and describes the vectors of further development of this research area. The paper begins with a description of the relevance of the Fake News problem, which clearly describes the negative impact of false news on all spheres of human life. The following is a description of methods for detecting false news, starting from the usual rules of text analysis and ending with complex ML algorithms. In this paper, a comparative analysis of detection methods is carried out, which is based on criteria of efficiency and accuracy. The author identifies the main problems of existing methods related to data quality, changing Fake News formats and the difficulties of automatically determining the reliability of information. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Development of a Comprehensive Technology for Analyzing Data on the Used Car Market
In today's information society, organizations face a huge amount of data that requires analysis and intelligent technologies to make informed decisions. In this paper, the authors consider the problem of analyzing the used car market using big and open data technologies. The used car market has characteristics characterized by heterogeneity and dynamic demand depending on the region. This problem is relevant and important not only for companies involved in producing and selling cars but also for potential buyers. The authors developed a comprehensive data analysis technique based on the Python programming language and the K-means clustering algorithm in the research process. In the article, the authors described a comprehensive technology for analyzing the used car market, including various analysis methods, such as prices, offers, and competition. The proposed comprehensive technology includes various tools and programs for collecting, processing, and analyzing data. These methods can be combined into a single system, providing a more complete picture of the market and making more informed decisions. The structure of the study reflects an independent approach to the topic under study based on open data and research by Russian and foreign scientists. It should be noted that the study is based on a large amount of analytical data obtained from reliable sources and tools that confirm the conclusions formulated in this study. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Research of Prospects and Challenges in Artificial Intelligence Technology Teaching and Learning
Recently, knowledge in the field of artificial intelligence in order to modernize various aspects of human activity has played a significant role. The exploration of the opportunities and difficulties associated with the development of artificial intelligence technologies is becoming an important area of research, as it profoundly affects our perception of work, education, medicine and other spheres of existence. New methods of machine learning, deep learning and reinforcement learning are being developed. These technologies are changing our understanding of how machines can learn and adapt to the world around them. The application of artificial intelligence covers many areas, including healthcare, finance, education and industry. In medicine, for example, AI can improve diagnostic accuracy and develop customized treatments. In education, it is possible to create personalized learning plans for each student. While in industry, artificial intelligence technologies are able to optimize production processes and increase business efficiency. However, despite the potential benefits associated with learning artificial intelligence technologies, there are serious challenges that require careful analysis. These challenges include ethical dilemmas, such as issues of algorithm transparency and responsibility for making principled decisions. Data security and privacy are also among the key aspects that require innovative approaches to AI technology training. The main purpose of the research is to deeply analyze the prospects and challenges in the field of artificial intelligence technology training, provide a comprehensive understanding of the current state of this field, identify key areas of development and propose practical strategies for effectively overcoming challenges. Taking into account both positive and negative aspects, it is necessary to have a meaningful look at the future of artificial intelligence technology education, taking into account social, ethical and technical aspects. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Gamification and Game-Based Learning: A Systematic Review and Comparative Analysis
In the modern world, characterized by the rapid development of technology and digitalization of almost all spheres of life, it is necessary to keep up with the times and gradually introduce information technology into our lives. This will allow us to remain competitive in a changing world, take advantage of new opportunities and improve our quality of life. It is important to understand that information technology is not just a fashion trend, but a necessary tool for successful development and progress. The paper examines the very concept of gamification, the main methods of introducing gamification into education, highlights the advantages of learning with the addition of gamification, and also works on comparing learning with and without gamification elements. The introduction of game elements into the educational process helps to improve the perception of educational material, as well as increase the level of motivation of the students themselves. It is worth noting that the learning process with the addition of game elements helps to improve attention, develop logical thinking, as well as analyze various situations. Gamification can be viewed from several angles. For a teacher, this teaching method will help to capture the attention of children, which will help create a working atmosphere in the classroom. And for students, gamification is a great opportunity to explore really important topics in game mode. They will have an increased interest in learning, which will have a beneficial effect on their further academic performance and learning. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
A Software Package for Detecting Anomalies in User Authentication
Anomaly detection is a very important tool for various applications such as intrusion detection, fraud, malfunction, system health monitoring and event detection in IoT devices. Recently, user authentication has become an extremely popular topic in information security research environments. The definition of user authentication is formulated as the process of verifying the identity declared by the user for a system object. Authentication is a method used to distinguish between true or false authentication requests. There are many methods used to authenticate a user that can identify valid users in protected resources. This article discusses various methods for analyzing abnormal user behavior in information systems, namely such methods as machine learning, neural networks, hybrid methods. Based on the analysis of system logs in the Astra Linux operating system, a software package has been developed to identify anomalies when trying to authenticate users. 2025 IEEE. -
Growth, survival and haemato-biochemical profiles of the freshwater catfish, Pangasius sutchi (Fowler, 1937) fingerlings fed with Tinospora cordifolia leaf extract supplemented diet
The present study documents the possible effects of Tinospora cordifolia leaf extract supplemented diets on growth, survival and haemato-biochemical profiles of the catfish, Pangasius sutchi fingerlings. P. sutchi fingerlings were fed with formulated diets, supplemented with four different concentrations of T. cordifolia leaf extract (viz. 100, 200, 400 and 800 mg kg-1 of feed) for 45 days. Fingerlings fed with basal diet served as control. Various parameters of serum biochemical and haematology such as serum total protein content, albumin content, globulin content, albumin globulin ratio, glucose, erythrocytes count, leucocytes count were evaluated along with growth parameters. The results indicated that Specific Growth Rate (SGR), Feed Conversion Ratio (FCR), Protein Efficiency Ratio (PER), survival and Haemato-biochemical profiles such as total serum protein, albumin, globulin, albumin globulin ratio and serum glucose were high in the fingerlings fed with T. cordifolia leaf extract supplemented diets, irrespective of dosage, compared to control. Among the four concentrations of T. cordifolia leaf extract used, 400 mg/kg of feed group showed increased growth, survival and enhanced the health status of P. sutchi fingerlings. 2020, Egyptian Society for the Development of Fisheries and Human Health. All rights reserved. -
Micro grid Communication Technologies: An Overview
Micro grid is a small-scale power supply network designed to provide electricity to small community with integrated renewable energy sources. A micro grid can be integrated to the utility grid. Due to lack of computerized analysis, mechanical switches causing slow response time, poor visibility and situational awareness blackouts are caused due to cascading of faults. This paper presents a brief survey on communication technologies used in smart grid and its extension to micro grid. By integration of communication network, device control, information collection and remote management an intelligent power management system can be achieved 2022 IEEE. -
Power Line Communication Parameters in Smart Grid for Different Power Transmission Lines
In an electrical power system smart grid is a network that renewable energy sources along with smart devices. Communication capabilities of the conventional grid can be improved by the inclusion of superior sensing and computing abilities. Device control, remote management, information collection, intelligent power management is achievable by using communication networks. Wired communication technology is used because of its advantages like reliable connection, free from interference, and faster speed. In this paper, the data communication parameters have been analyzed using Power Line Communication (PLC) with various lengths of transmission lines. An orthogonal Frequency Modulation scheme is used to obtain the minimum BER.MATLAB Programming has been carried out and the results have been compared with the standards and found to be satisfactory. 2021 IEEE. -
Design of digital filters for multi-standard transceivers
This paper addresses on three different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area, delay and dynamic power consumption. The proposed decimation filter architectures reflect the considerable reduction in area and dynamic power consumption without degradation of performance. The filter coefficients are derived from MATLAB, the filter architectures are implemented and tested using Xilinx SPARTAN FPGA.First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the two different encoding schemesi.e. Canonic Signed Digit (CSD) and Minimum Signed Digit (MSD) are used for filter coefficients and then the architecture performances are tested.The results of CSD and MSD based architectures show a considerable reduction in the area and power against the conventional number system based filter design implementation. The implementation results reflect that considerable reduction in area of 47.89% and dynamic power reduction of 28.64% are achieved using hybrid architecture. 2015 School of Electrical Engineering and Informatics. All rights reserved. -
Hybrid architecture of digital filter for multi-standard transceivers
This paper addresses on three different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area and power. The proposed decimation filter architectures reflect the considerable reduction in area & power consumption without degradation of performance. First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the two different encoding schemes i. e. Canonic Signed Digit (CSD) and Minimum Signed Digit (MSD) are used for filter coefficients and then the architecture performances are tested using FPGA. The results of CSD and MSD based architectures show a considerable reduction in the area & power against the conventional number system based filter design implementation. The implementation results reflect that considerable reduction in area of 25. 64% and power reduction of 16. 45% are achieved using hybrid architecture. Research India Publications. -
Digital filter architectures for multi-standard wireless transceivers
This paper addresses on two different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area and power. The proposed decimation filter architectures reflect the considerable reduction in area & power consumption without degradation of performance. The filter coefficients are derived from MATLAB , the filter architectures are implemented and tested using Xilinx SPARTAN FPGA . The Xilinx ISE 9.2i tool is used for logic synthesis and the Xpower analysis tool is used for estimating the power consumption. First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the different encoding scheme i.e. Canonic Signed Digit (CSD) representation is used for filter coefficients and then the architecture performance is tested .The results of CSD based architecture shows a considerable reduction in the area & power against the conventional number system based filter design implementation. -
Impact of lockdown during COVID-19 pandemic on the learning status of undergraduate and postgraduate students of Bangalore
Background: The COVID 19 pandemic has created various impacts on every human's life. COVID 19 lockdown has provoked enormous changes in the education sector which in turn influences the student's life in many aspects. The scope of this study is to understand the impact in both undergraduate and postgraduate students. Aim: This study aims at incisively analyzing the impact of lockdown imposed due to the COVID-19 pandemic on graduate students of Bangalore. Method: It is an online survey that encompasses a structural questionnaire with open-ended questions created using Google Forms, which were sent across the students through social media platforms. Results: A total of 115 students from both undergraduate and postgraduate programs have participated in this survey. Simple percentage distribution was estimated to evaluate the pedagogy, opinion on educational decisions, modes of learning, socio-economic conditions, and problems pertaining to academia because of this pandemic. As per this analysis, 80.9% of students faced difficulty due to lockdown. 67% of students thought that their family's income will be affected by this pandemic. 68.7% of students felt stressed, depressed and 52.3% of students could not find a suitable environment in their home to study during this lockdown. When we see this pandemic in an optimistic light, it has created various opportunities such as Digital learning and adoption of new health habits. 2021. RIGEO. All Rights Reserved. -
A Scoping Review of Formal Care to Children with Special Needs during the Covid-19 Pandemic
The Covid-19 pandemic caused an unprecedented closure of direct service for children with special needs (CSNs), which shifted service to remote mode. This scoping review analyzed the strategies adopted by different formal care services for CSNs, their strengths and weaknesses, and the challenges faced by the formal care providers (FCPs). This study identified relevant articles through academic databases and Google searches using appropriate search strings and keywords. It included ten journal articles (n=10) and eight pieces (n=8) of grey literature through a meticulous selection process and extracted data. This review drew results by collating the descriptive numerical data analysis and qualitative thematic analysis and interpreting them. Reporting incor-porated all the possible items recommended by the PRISMA-ScR guidelines. This review demonstrated that pediatric rehabilitation adopted the telehealth approach and that special education changed to remote learning. When childcare programs in the USA functioned according to specific guidelines, residential care in South Asian countries faced a financial crunch. FCPs faced personal and professional challenges that required systematic training to deal with pandemic situations. This scoping review made suggestions for relevant policy formulations for equitable and effective service delivery to CSNs during pandemic situations, and it exposed new avenues for research. 2022 Authors. -
Deep Learning Approaches for Environmental Monitoring in Smart Cities
It introduces a novel integrated environmental monitoring system capable of doing on-the-go measurements. In metropolitan settings, air pollution is one of the most serious environmental threats to human health. The widespread use of automobiles, emissions from manufacturing processes, and the use of fossil fuels for propulsion and power generation have all contributed to this issue. Air quality predictions in smart cities may now be made using deep learning methods, thanks to the widespread adoption of these tools and their continued rapid growth. Particulate Matter (PM) with a width of less than 2.5 m (PM2.5) is one of the most perilous kinds of air pollution. To anticipate the hourly gauge of PM2.5 focus in Delhi, India, we utilized verifiable information of poisons, meteorological information, and PM2.5 fixation in the adjoining stations to make a spatial-worldly element for our CNN-LSTM-based deep learning arrangement. According to our experiments, our 'hybrid CNN-LSTM multivariate' method outperforms all of the above conventional models and allows for more precise predictions. 2024 IEEE. -
Web mining patterns discovery and analysis using custombuilt Apriori Algorithm
International Journal of Engineering Inventions Vol.2, Issue 5,pp.16-21 ISSN No. 2278-7461