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Border Region Railway Development in Sino- Indian Geopolitical Competition
India and China share about 3,488 km long International Boundary, which has three sectors: Western, Middle and Eastern. The Eastern sector comprises two Northeastern states, that is, Arunachal Pradesh measuring 1,124 kms and Sikkim measuring 219 kms, respectively. Due to recent changes in the geopolitical relationship with China, border management and transport infrastructure development have occupied centre stage. In recent years, the Government of India has taken initiatives to develop railway infrastructure in Northeast India. The study will focus on the role of railway transportation in Sino-Indian geopolitical competition. The study is based on secondary data collected from the office of General Manager, Northeast Frontier Railway, the Census of India and reports of Memorandums of Understanding between India and China. The study reveals that railway infrastructure along the border creates geo-psychological pressures on both countries, influencing the divergent geopolitical relationship between India and China. Railway diplomacy is a tool kit of critical geopolitics which reveals the contours of geopolitical competition in borderlands. 2023 Indian Council of World Affairs(ICWA). -
Border Collie Optimization
In recent times, several metaheuristic algorithms have been proposed for solving real world optimization problems. In this paper, a new metaheuristic algorithm, called the Border Collie Optimization is introduced. The algorithm is developed by mimicking the sheep herding styles of Border Collie dogs. The Border Collie's unique herding style from the front as well as from the sides is adopted successfully in this paper. In this algorithm, the entire population is divided into two parts viz., dogs and sheep. This is done to equally focus on both exploration and exploitation of the search space. The Border Collie utilizes a predatory move called eyeing. This technique of the dogs is utilized to prevent the algorithm from getting stuck into local optima. A sensitivity analysis of the proposed algorithm has been carried out using the Sobol's sensitivity indices with the Sobol g-function for tuning of parameters. The proposed algorithm is applied on thirty-five benchmark functions. The proposed algorithm provides very competitive results, when compared with seven state-of-the-art algorithms like Ant Colony optimization, Differential algorithm, Genetic algorithm, Grey-wolf optimizer, Harris Hawk optimization, Particle Swarm optimization and Whale optimization algorithm. The performance of the proposed algorithm is analytically and visually tested by different methods to judge its supremacy. Finally, the statistical significance of the proposed algorithm is established by comparing it with other algorithms by employing Kruskal-Wallis test and Friedman test. 2013 IEEE. -
BORCAE: Bayesian Optimized Residual Convolutional Autoencoder for Efficient Feedback Compression in RIS-Assisted Time-Varying IoT Networks
Reconfigurable Intelligent Surfaces (RIS) have strong potential to improve the performance of time-varying Internet of Things (IoT) networks. However, a major challenge in operating RIS effectively is the need for frequent Quantized Phase Configuration (QPC) feedback bits from the Base Station (BS) to the controller. This challenge becomes more serious asthe RIS size grows, since the feedback bandwidth is limited. As a result, efficient compression of control signals is crucial for the practical deployment of RIS. In this work, we propose Bayesian Optimized Residual Convolutional AutoEncoder (BORCAE), a lightweight and noise-resilient feedback compression framework based on a 1D Convolutional Autoencoder with residual connections. The model is designed to reduce QPC feedback size while preserving high reconstruction fidelity. To ensure adaptability across varying deployment conditions, we employ Bayesian hyperparameter optimization using Optuna, which enables automatic tuning of key architectural hyperparameters. This optimization ensures that the architecture generalizes effectively across a wide range of operating scenarios. Additionally, we integrate the Limited Memory Broyden Fletcher Goldfarb Shanno (LBFGS) optimizer during the final training epochs, which accelerates convergence and improves stability. For performance evaluation, we use Normalized Mean Squared Error (NMSE) as the reconstruction metric. Extensive testing across different Signal-to-Interference-plus-Noise Ratio (SINR) levels demonstrates that BORCAE consistently achieves lower NMSE compared to DL-CsiNet and CsiNet. The results highlight the practical viability of BORCAE for RIS-assisted communication, offering improved efficiency, and scalability for real-world IoT and Sixth-Generation (6G) applications. 2020 IEEE. -
Boosting Surface Coverage of CO Intermediates through Multimetallic Interface Interactions for Efficient CO2 Electrochemical Reduction
Given the inherent challenges of the CO2 electroreduction (CO2ER) reaction, solely from CO2 and H2O, it is desirable to develop selective product formation pathways. This can be achieved by designing multimetallic nanocomposites that provide optimal CO coverage, allowing for tunability in the product formation. In this work, Ag and Zn codoped-SrTiO3 (ZAST) composite immobilized carbon black (CB)-modified GCE working electrode (ZAST@CB/GCE) was developed for the electrochemical conversion of CO2 to multicarbon products. The complete reaction was carried out in a CO2-saturated aqueous system of 0.5 M KHCO3 electrolyte. A potential-dependent product selectivity was suggested based on the NMR results, wherein raising the potential value enhanced the formation of liquid products such as acetone and alcohols while suppressing competitive HER. The total Faradaic efficiency for liquid products reached an impressive 97% at a potential of ?0.6 V vs. RHE. This represents a significant advancement in acetone production pathways and valorization of CO2ER technology. 2025 American Chemical Society. -
Boosting Surface Coverage of CO Intermediates through Multimetallic Interface Interactions for Efficient CO2 Electrochemical Reduction
Given the inherent challenges of the CO2 electroreduction (CO2ER) reaction, solely from CO2 and H2O, it is desirable to develop selective product formation pathways. This can be achieved by designing multimetallic nanocomposites that provide optimal CO coverage, allowing for tunability in the product formation. In this work, Ag and Zn codoped-SrTiO3 (ZAST) composite immobilized carbon black (CB)-modified GCE working electrode (ZAST@CB/GCE) was developed for the electrochemical conversion of CO2 to multicarbon products. The complete reaction was carried out in a CO2-saturated aqueous system of 0.5 M KHCO3 electrolyte. A potential-dependent product selectivity was suggested based on the NMR results, wherein raising the potential value enhanced the formation of liquid products such as acetone and alcohols while suppressing competitive HER. The total Faradaic efficiency for liquid products reached an impressive 97% at a potential of ?0.6 V vs. RHE. This represents a significant advancement in acetone production pathways and valorization of CO2ER technology. 2025 American Chemical Society. -
Boosting productive capacity in OECD countries: Unveiling the roles of geopolitical risk and globalization
This study examines the intertwined effects of geopolitical risk and globalization on productive capacity (the measure of economic cycles) in 20 Organisation for Economic Cooperation and Development (OECD) countries from 2000 to 2021. The panel threshold regression and Driscoll-Kraay standard error estimations highlight the positive impact of globalization on productive capacity. Still, they are underscored by the negative effect of geopolitical risk. The study also unveils a synergistic relationship, demonstrating that the combined influence of globalization and geopolitical risk can amplify productive capacity under specific conditions. Government effectiveness and innovation have positive effects on productive capacities. These findings underscore the need for balanced policies that leverage global economic integration while ensuring geopolitical stability, and offering nuanced insights to guide strategic decision-making for sustained economic cycles. 2024 Elsevier Inc. -
Boosting enabled efficient machine learning technique for accurate prediction of crop yield towards precision agriculture
Due to the limited availability of natural resources, it is essential that agricultural productivity keep pace with population growth. Despite unfavorable weather circumstances, this project's major objective is to boost production. As a consequence of technological advancements in agriculture, precision farming as a way for enhancing crop yields is gaining appeal and becoming more prevalent. When it comes to predicting future data, machine learning employs a number of methods, including the creation of models and the acquisition of prediction rules based on past data. In this manuscript, we examine various techniques to machine learning, as well as an automated agricultural yield projection model based on selecting the most relevant features. For the purpose of selecting features, the Grey Level Co-occurrence Matrix method is utilised. For classification, we make use of the AdaBoost Decision Tree, Artificial Neural Network (ANN), and K-Nearest Neighbour (KNN) algorithms. The data set that was used in this study is simply a compilation of information about a variety of topics, including yield, pesticide use, rainfall, and average temperature. This data collection consists of 33 characteristics or qualities in total. The crops soya beans, maze, potato, rice, paddy, wheat, and sorghum are included in this data collection. This data collection was made possible through the collaboration of the Food and Agriculture Organisation (FAO) and the World Data Bank, both of which make their data available to the public. The AdaBoost decision tree has achieved the highest level of accuracy possible when used to anticipate agricultural yield. Both the accuracy rate and the recall rate are quite high at 99 percent. The Author(s) 2024. -
Boosting DSSC Performance: Co-Sensitization With Morinda citrifolia-Derived Carbon Dots for Enhanced Light Harvesting
This study explores a novel co-sensitization architecture utilizing carbon dots (CDs) derived from Morinda citrifolia in combination with the N719 dye to enhance the light-harvesting efficiency of dye-sensitized solar cells (DSSCs). The CDs were synthesized through a hydrothermal process using an aqueous extract of Morinda citrifolia fruit juice, resulting in a material with broad optical absorption properties. To investigate their effectiveness in DSSCs, the synthesized CDs were incorporated and used with two different co-sensitization strategies. In the first approach (DN), the CDs were initially adsorbed onto the photoanode, followed by sensitization with N719 dye. The second configuration (DND) employed a sandwich structure where the photoanode was sequentially sensitized with CDs, N719 dye, and an additional layer of CDs. In this study, TiO2 was used as the photoanode material, with N719 and CD-modified N719 acting as sensitizers, Iodolyte HI-30 as the electrolyte, and Platisol T/sp as the counter electrode. Among the two configurations, the DND structure exhibited the highest power conversion efficiency (PCE) of 5.3%, demonstrating the potential of this co-sensitization approach. The significant enhancement in DSSC performance highlights the effectiveness of Morinda citrifolia-derived carbon dots as a promising, cost-effective strategy for improving the efficiency of next-generation DSSCs. 2026 Wiley-VCH GmbH. -
Boosting Competitiveness Through Data: How Online Procurement Drives Data-Driven Decision-Making in Traditional Kirana Shops
Integrating traditional and modern elements presents significant challenges, yet when successful, the synergy can be immense. Onboarding Indian Kirana shopssmall, unorganized mom-and-pop storesinto a comprehensive digital infrastructure is crucial given the current retail landscape and evolving consumer demands. These shops are vital to the countrys food and grocery ecosystem but face disruption from the rise of e-commerce and organized retail. By adapting new business models and technologies, Kirana shops can enhance their competitiveness. This study highlights the critical role of digitalization and data-driven decision-making in small scale retail formats. Researchers collected primary data from Kirana shops doing online procurement and those relying on traditional methods like purchasing from distributors. Analysis of primary data shows that shops utilizing online procurement platforms demonstrate superior performance, attributed to factors like competitive pricing and timely delivery. Most importantly, the insights and analytics provided by eB2B platforms are game changers. Data emerges as the key differentiator; digitalization enables access to critical analytics, allowing for informed business decisions that improve success rates and provide a competitive edge. Consequently, this study propose an ideal digital end-to-end model designed to enhance operational efficiency and drive growth for unorganized Kirana shops. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Bookstagrammers vs. BookTubers: A comparative study on readers' preferred social media book influencer
As the Internet has become a part of many people's daily lives, it has led to the growth of a reading culture influenced by book bloggers on different social media platforms. This chapter identifies two social media platforms that the readers utilize to share about the books they have read. While readers have found their reading space on social media platforms, some have become book influencers. This chapter identifies two categories of prominent literary influencers i.e., Bookstagrammers and BookTubers. Since the readers follow book influencers to learn about the latest books and to read their reviews before making their purchase decision. This chapter aims to compare and analyse the prominent categories of book influencers focusing on knowing more about the preferred book influencers from the readers' point of view. 2024, IGI Global. All rights reserved. -
Bone Abnormality Detection Using RMSprop Optimizer in VGG16
The advent of deep learning has revolutionized medical imaging, enhancing diagnostic precision, treatment planning, and patient care. This study leverages deep learning, specifically employing the VGG16 model optimized with RMSprop, to automate bone abnormality detection. Methodologically, the research encompasses data acquisition, preprocessing, and model training with RMSprop optimization. Results highlight the efficacy of this approach, showcasing RMSprops ability to detect various bone abnormalities. These findings underscore deep learnings potential in medical imaging, emphasizing its applicability beyond bone abnormality detection. The study illuminates the transformative impact of RMSprop-optimized deep learning models in medical imaging, promising advancements in automated diagnosis and treatment planning. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Bombay High Court (re)assures that copyright registration is not required to remedy infringement
Sanjay Soya Private Limited v. Narayani Trading Company, Interim Application (L) No. 5011 of 2020 and Commercial IP Suit No. 2 of 2021, High Court of Bombay, Maharashtra, judgment of 9 March 2021, by Mr. Justice G.S. Patel The Bombay High Court, in the case of Sanjay Soya Private Limited v. Narayani Trading Company, held that copyright registration is not a prerequisite to claiming relief in copyright infringement cases. The judgment clarifies the dubiety created previously by a contrary judicial opinion and aligns the Indian position with international copyright principles. 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. -
Bollywood, biopics and biographies: Understanding the transmutation of narratives /
A biopic or a biographical motion picture, that charts the lifetime of a person featured in that film, is not a trend or fad that came about in recent years. One could start with arguing upon the stance of the biopics of actually being a genre of itself, despite having been the part of earliest days of silent cinema. The paper studies three biopics in Bollywood along with the biographies/autobiographies that have been used as the background source for the film‘s narration. -
Body mass index implications using data analysis in the soccer sports
Soccer is considered among the most popular sports in the world among the last few years. At the same time, it has become a prime target in developing countries like India and other Asian countries. As science and technology grow, we can see that sports also grow with science, and hence technology being used to determine the results sometime or sometimes it is used to grow the overall effect. This paper presents the attributes and the qualities which are necessary to develop in a player in order to play for the big-time leagues called Premier League, La Liga, Serie A, German Leagues and so on. Simple correlation and dependence techniques have been used in this paper in order to get proper relationship among the attributes. This paper also examines how the body mass index plays an effect on the presentation of soccer players with respect to their speed, increasing speed, work rate, aptitude moves and stamina. The point is likewise to discover the connection of the above credits concerning body mass index. As in universal exchange, football clubs can profit more in the event that they have practical experience in what they have or can make a similar bit of room to maneuver. In a universe of rare assets, clubs need to recognize what makes them effective and contribute in like manner. Springer Nature Singapore Pte Ltd 2021. -
Body image issues and self-concept dilemmas in adolescents living with thalassemia
Thalassemia, a genetic blood disorder, involves an inability to produce sufficient hemoglobin and comprises two types: alpha thalassemia and beta thalassemia. Beta thalassemias immediate treatment measures include frequent blood transmissions, stem cell and bone marrow transplants; all capable of altering an individuals idea of body image, self-concept, growth, and socialization, resulting in several emotional, psychological, and behavioral concerns. This study aimed at comprehending the dilemmas of body image and self-concept encountered by adolescents with thalassemia, particularly the resulting influence on physical development and socialization. Using the phenomenological interpretivism approach of qualitative research, data was collected using purposive-convenient sampling from 11 adolescents, both boys and girls ranging from ages 12 to 18, living with thalassemia and undergoing treatment. The research highlights adolescent concerns with body image, specifically with complexion, facial features, being either underweight or overweight, all amalgamating into a self-concept dilemma. Moreover, results point to the significant influence of experiences with family, peers, educational institutions, and hospital staff. Therapeutic attention, through regular screening and counselling, should be provided to adolescent thalassemia patients to address the psychological aspects of the chronic illness. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
Bob Dylan: Poet of disruption, dissonance and an aesthetic of dissent
This paper is a brief study of the pivotal figure of folk rock, Bob Dylan. Acclaimed as a songwriter and singer, he was also the poetic voice of the counter culture of the nineteen sixties in America. The counter culture sought to unseat the mainstream establishment that seemed obsessed with war, conservative ideals and religious nationalism. Dylan burst onto this scene 'already a legend' and 'the unwashed phenomenon' (Baez, 1975) projecting the image of the original vagabond and troubadour. A glance at a selection of some of his best known lyrics disabuses one of the notions of his being uninitiated into the discourse of philosophy and literature. He draws freely on and engages with ideas from texts that are sometimes even obscure. The Nobel he was awarded in October 2016 recognized his art for evolving new modes of poetic expression. This paper studies Dylan, the performer and the writer who has masterfully disrupted most accepted literary modes using the dissonance-rich space of Rock music while retaining some of the traditional forms of poetic utterance. AesthetixMS 2016. -
Blurred Image Processing and IoT Action Recognition in Academy Training Sport
Smart wearable technologies utilising devices connected to the web (IoT) are on the rise, and many of these new applications involve the identification of athletic performance. Many people across the world participate in soccer, also called football in some regions. Soccer players practise discrete actions (like shooting and passing) in order to ingrain them in muscle memory and speed up their reflexes during actual games. There is always a compromise between blur and noise when processing images. Denoising naturally softens an image because noise is high-frequency information. Deblurring, on the other hand, causes additional noise in the final product. The need to brighten an image in low-light conditions only adds to the difficulty. Noise is introduced into the image during the brightening process itself. Images taken while moving, especially those of wildlife (though not exclusively), will have more blur than those taken while still. Many previous projects have focused on a single problem, but very few have attempted to address the entire set of problems simultaneously. So, we set out to make a way to turn these lowlight, fuzzy images into high-contrast, clear images. A fuzzy invariant space is the result of the union of several fuzzy invariant spaces. After numerous iterations of processing a blurred image, the final stage is to utilise a progressive restoration procedure. The experimental findings demonstrate the effectiveness of the suggested technique in reducing calculation error, improving the recovery effect, and avoiding the noise caused by numerous deconvolutions. This work introduces new concepts and methods for recognition research by applying fuzzy image processing to the study being human mobility and the detection of activities in the realm of IoT. Using the Kinect, an IoT somatosensory camera, we are able to collect 15 3D skeletal elements via its software development kit (SDK). This led to the study of kinesiology and the creation of a motion resolution model that works well with the Internet of Things. 2022 IEEE. -
Blue ocean marketing- A promising strategy /
Vol. 7 No. 1 (2013) ISSN: 2278-5612 -
Blue LED photolytic method for the synthesis of 1,4-dihydropyridine derivatives from benzo [b]thiophene-2-carbaldehyde
This study presents a highly efficient and operationally simple protocol for synthesizing 1,4-dihydropyridine derivatives. The protocol uses an inexpensive and readily available photocatalyst Mn2(CO)10, which plays a crucial role in the single-pot, four-component reaction involving benzo [b]thiophene-2-carbaldehyde, malononitrile, dialkyl acetylene dicarboxylate, and anilines in a blue LED (400500 nm) photocatalytic technique. The reaction conditions include the use of blue LEDs, a lower catalyst load, and green solvents like dimethyl sulfoxide (DMSO) and water in a 1:1 ratio. The multicomponent photocatalytic approach negates the use of expensive catalysts and the necessity of multi-step routes, in addition to providing better atom economy and an easy work-up process, and it is environmentally benign. The derivatives were effectively synthesized in higher yields and characterized using 1H NMR, 13C NMR, and ESI-MS. The obtained 1,4 dihydropyridines also have tremendous capability for biological and pharmacological activities, opening exciting possibilities for future research and applications. 2025 -
Blue Economy, Maritime Law, and SDGs: Converging AI and Climate-Smart Policies for a Sustainable Future
Oceans cover 72% of the Earths surface, constituting 99% of the living space by volume. By absorbing almost 25% of the carbon dioxide, it tries to prevent global warming. Oceans and maritime resources are becoming key players in international economic interactions, which has developed the idea of the blue economy. However, the increased economic interactions cause various insecurities, like interstate disputes, maritime zone confusions, piracy, terrorism, pollution, and illegal and unregulated exploitation of marine resources. This necessitated the advancement of maritime law with more possibilities and enforcement mechanisms. The interplay between the blue economy and maritime law is essential to realize Sustainable Development Goal No. 14. Their mutual dependence and empowerment are vital for conserving and promoting marine resources. From this perspective, this chapter, using qualitative methodologys critical analytical method, explores the possibilities of converging AI and climate-smart policies with the blue economy and maritime law framework to realize a sustainable future. Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development.