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Unveiling the realm of AI governance in outer space and its importance in national space policy
This article explores the notable legal concerns that may arise from the growing utilisation of artificial intelligence and machine learning in outer space. Whether it is conducting space exploration, clearing orbital debris, or extracting resources from specific areas in space, these activities are becoming more popular. Therefore, it is necessary to establish a regulatory framework to ensure consistency and objective standards. In order for national space legislation to effectively address the challenges presented by activities involving robots with different levels of autonomy and numerous objectives, it is essential to appraise the nature of these challenges. The article aims to investigate the relationship between the Montreal Declaration for a Responsible Development of Artificial Intelligence, 2017, and outer space laws and principles. It also examines the legal status of autonomous space objects, such as planetary rovers that are currently in operation or will be in the near future. Ultimately, the article highlights the importance of national space policy in addressing the appropriate regulation of artificial intelligence in outer space. In conclusion, this article has also discussed the potential effectiveness of utilising artificial intelligence-based methodologies and strategies to enhance current space policy. 2024 IAA -
Unveiling the realm of AI governance in outer space and its importance in national space policy
This article explores the notable legal concerns that may arise from the growing utilisation of artificial intelligence and machine learning in outer space. Whether it is conducting space exploration, clearing orbital debris, or extracting resources from specific areas in space, these activities are becoming more popular. Therefore, it is necessary to establish a regulatory framework to ensure consistency and objective standards. In order for national space legislation to effectively address the challenges presented by activities involving robots with different levels of autonomy and numerous objectives, it is essential to appraise the nature of these challenges. The article aims to investigate the relationship between the Montreal Declaration for a Responsible Development of Artificial Intelligence, 2017, and outer space laws and principles. It also examines the legal status of autonomous space objects, such as planetary rovers that are currently in operation or will be in the near future. Ultimately, the article highlights the importance of national space policy in addressing the appropriate regulation of artificial intelligence in outer space. In conclusion, this article has also discussed the potential effectiveness of utilising artificial intelligence-based methodologies and strategies to enhance current space policy. 2024 IAA -
Unveiling the Quassia indica derived synthesis of Co3O4/ZnO nanohybrids for efficient dye degradation and cytotoxicity assessment
While there are exciting possibilities in nanotechnology, creating environmentally safe nanoparticles with a variety of uses in photocatalysis and biomedicine continues to be a significant issue. This work addresses the gap by introducing Quassia indica leaf extract as a bio reductant and stabilizer in the green synthesis of cobalt oxide-zinc oxide nanoparticles (QI: Co3O4/ZnO NP). The synthesized nanoparticles were characterized using various techniques, including UVvisible spectroscopy, X-ray diffraction (XRD), dynamic light scattering (DLS), high resolution transmission electron microscopy (HR-TEM), selected area electron diffraction (SAED), Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FE-SEM), and energy dispersive X-ray spectroscopy (EDX). The existence of hexagonal zinc oxide and cubic cobalt oxide phases in the synthesized nanoparticles was verified by XRD analysis. The elemental composition was confirmed by EDX, which showed that oxygen, zinc, and cobalt were present. The average hydrodynamic diameter of 244.5 d. nm was found via DLS measurements, indicating well dispersed nanoparticles. Under UV light irradiation, photocatalytic activity of QI: Co3O4/ZnO NP was assessed for the degradation of textile dyes (Reactive Blue-222, Reactive Blue-220, Reactive Red-120, and Reactive Yellow-145). Phytotoxicity tests were conducted to examine the possible environmental impact of the deteriorated dye solution, revealing promising results in mitigating the detrimental impact of industrial dyes. QI: Co3O4/ZnO NP was also assessed for cytotoxicity studies in DLA and EAC cells which showed a concentration-dependent cytotoxic effect. The research outcomes emphasize the significant potential of these nanoparticles in diverse arena by offering a sustainable and efficacious resolution to the present-day problems. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025. -
Unveiling the potential: iodide-infused nickel-enhanced MXene composite for high-performance sodium ion hybrid capacitors
2D-MXenes have gained much popularity for energy storage applications such as hybrid capacitors, and they have shown very competitive performance, especially as electrode materials for sodium ion hybrid capacitors. However, they suffer from various problems, such as morphology distortion and fast capacity fading, which results in the poor performance of the battery. As a result, researchers have focused more on MXene-based composite materials to address these issues. In this work, we report a sodium iodide and nickel-decorated MXene-based composite (Ti2C/Ni/NaI) material as an electrode for a sodium ion hybrid capacitor. Ti2C MXene and Ni were able to provide physical and mechanical strength, and iodine was able to produce redox activity. The composite had a rough surface with readily aggregated 2D-MXene sheets and was uniformly covered with Ni, Na, and I atoms. Several vibrational bands and peaks associated with Ti, Ni, Na, C and O in the Raman while XPS spectra confirmed the effective incorporation of dopants into the MXene sheets and successful synthesis of the Ti2C/Ni/NaI composite. The fabricated hybrid capacitor exhibited good capacity retention of 59% after 10,000 cycles at a current density of 0.5 mA g?1; thus, the Ti2C/Ni/NaI composite can be a promising electrode material for sodium-based hybrid capacitors. 2025 The Author(s). Published by IOP Publishing Ltd. -
Unveiling the potential: iodide-infused nickel-enhanced MXene composite for high-performance sodium ion hybrid capacitors
2D-MXenes have gained much popularity for energy storage applications such as hybrid capacitors, and they have shown very competitive performance, especially as electrode materials for sodium ion hybrid capacitors. However, they suffer from various problems, such as morphology distortion and fast capacity fading, which results in the poor performance of the battery. As a result, researchers have focused more on MXene-based composite materials to address these issues. In this work, we report a sodium iodide and nickel-decorated MXene-based composite (Ti2C/Ni/NaI) material as an electrode for a sodium ion hybrid capacitor. Ti2C MXene and Ni were able to provide physical and mechanical strength, and iodine was able to produce redox activity. The composite had a rough surface with readily aggregated 2D-MXene sheets and was uniformly covered with Ni, Na, and I atoms. Several vibrational bands and peaks associated with Ti, Ni, Na, C and O in the Raman while XPS spectra confirmed the effective incorporation of dopants into the MXene sheets and successful synthesis of the Ti2C/Ni/NaI composite. The fabricated hybrid capacitor exhibited good capacity retention of 59% after 10,000 cycles at a current density of 0.5 mA g?1; thus, the Ti2C/Ni/NaI composite can be a promising electrode material for sodium-based hybrid capacitors. 2025 The Author(s). Published by IOP Publishing Ltd. -
Unveiling the potential of large language models: Redefining learning in the age of generative AI
Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are transforming industries by fostering innovation, automating tasks, and enhancing creativity. By enabling personalized user interactions, sophisticated content creation, and advanced data analytics, they are revolutionizing industries such as healthcare, education, and customer service. As these technologies evolve, they can fundamentally change communication and decision-making processes and incorporate AI into everyday life. The objective of this book chapter is to examine the architecture and components, features, functionality, domain-specific applications, recent advances, and future developments of LLMs. Ongoing research aims to reduce biases, increase energy efficiency, and facilitate interpretation. As LLMs continue to evolve, they have the potential to transform many industries, including education, customer service, content creation, and more. As a result, they will be essential for the development of future AI-powered applications. 2024, IGI Global. All rights reserved. -
Unveiling the Potential of Bacillus paramycoides, a Halotolerant Endophytic Bacterium with Heavy Metal Tolerance and Plant Growth Promotion Properties
The use of heavy metal resistant plant growth promoting endophytes is an effective method for improving crop yield and cleaning up contaminated sites. In our study, we have isolated thirteen bacterial endophytes from the shoots of Alternanthera philoxeroides, an aquatic plant from Bellandur lake, Bangalore, India. Among the isolates, Bacillus paramycoides showed significant plant growth promotion properties including an extortionate amount of indole acetic acid (IAA) production (144.69 1.01 g/mL) along with other plant growth promoting attributes like ammonia production, nitrogen fixation, phosphate, potassium solubilization, 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase and siderophore production. The isolate also demonstrated the ability to resist pathogen attacks by producing extracellular enzymes, which could have potential industrial uses. Furthermore, it displayed resistance to multiple heavy metals like chromium (Cr), copper (Cu), lead (Pb), zinc (Zn) and cadmium (Cd) as well as the ability to tolerate high salt concentrations (up to 7% NaCl). These characteristics make it an ideal candidate for promoting plant growth in stressful environments and as an effective bioremediation agent. 2024 World Researchers Associations. All rights reserved. -
Unveiling the pattern of PhishingAttacks using the Machine Learning approach
This study introduces a unique approach to strengthening cybersecurity by combining advanced models for real-time detection of phishing websites. A classifier is trained to discern patterns associated with legitimate and phishing URLs, leveraging a carefully organized labeled dataset. The model in this paper forms the foundation for a real-time detection system, providing users with real-time information on potential phishing threats. Integrating an adaptive decision-making algorithm improves decision-making adaptability, particularly in scenarios challenging the model's confidence. A user feedback loop ensures the continuous learning and refinement of the system, aligning it more closely with user expectations. The future scope of this research involves exploring advanced models, improving explainability, and incorporating dynamic features for enhanced detection. Adaptive policies, large-scale deployment, and ethical implications are pivotal for real-world applicability. In conclusion, this study contributes to advancing phishing detection methodologies and lays the groundwork for future innovations in cybersecurity. The collaborative efforts of academia, industry, and cybersecurity stakeholders arenecessaryfor realizing the full potential of this paper and ensuring a safer online platform for users. 2024 IEEE. -
Unveiling the Necropolitics of Oil on Migrant Bodies in Deepak Unnikrishnans Birds
Oil played a significant role in fuelling the sociopolitical and economic development of Middle Eastern nations, attracting mass migration from South Asian nations. The article draws a nexus between the energy dynamics and labour exploitation within these petroleum-rich nations. It undertakes a close reading of the text Birds from Deepak Unnikrishnans novel Temporary People as it depicts the lives of migrant labourers who navigate an exploitative petro-capitalist system. The fictional text employs a narrative strategy juxtaposing elements of magic and realism, opening up a space for multilayered marginalised voices. The article engages with energy theories and interweaves Mbembes theory on necropolitics to grasp oils sovereign influence in delineating the boundaries between life and death in migrant lives. The surplus energy generated through fossil fuel extraction contributes to notions of boundless growth, coupled with technical and economic progress, which conceals the intensive manual labour underpinning these petrocultures. The magical property alluded to oil and the spectral absence of labour in the socio-cultural imagination co-constructs an exploitative and dehumanising labour regime for migrants. The migrant body is kept alive, and their existence is contingent upon the instrumental value of their labouring body, which constructs them as easily disposable and expendable as they are positioned outside the formal boundaries of citizenship. 2024 South Asian University. -
Unveiling the Motivation Drivers in Start-Up Workspace
This article delves into the relationship between workplace happiness and productivity in startup settings. Its primary objective is to dissect the multifaceted factors impacting employee well-being, aiming to enhance overall efficiency by customizing the work environment in myriad ways. For this study, a descriptive causal methodology was employed to investigate the impact of workplace happiness on productivity within start-up companies. A carefully structured questionnaire was administered to 256 employees within well-established organisations in Bangalore, India. Participants were selected through a Judgement sampling process to ensure impartial and unbiased representation. Survey respondents preferred the pre-COVID working conditions, acknowledging their advantages. However, the increased autonomy and flexibility in work arrangements have led to enhanced productivity under the new hybrid model. Notably, when employees are entrusted with greater responsibility, their job satisfaction rises, resulting in increased work output. organizations are now tasked with offering additional incentives to remote employees, thereby elevating the satisfaction and job fulfilment experienced by these individuals. Effectively tackling challenges necessitates the alignment of learning and development objectives with the internal business processes that maximize each employee's abilities and potential. This involves meeting the criteria outlined in the balanced scorecard components. 2024, Iquz Galaxy Publisher. All rights reserved. -
Unveiling the Landscape: A Comparative Study of U-Net Models for Geographical Features Segmentation
Geographical features segmentation is a critical task in remote sensing and earth observation applications, enabling the extraction of valuable information from satellite imagery and aiding in environmental analysis, urban planning, and disaster management. The U-Net model, a deep learning architecture, has proven its efficacy in image segmentation tasks, including geographical feature analysis. In this research paper, a comparative study of various U-Net models customized explicitly for geographical features segmentation is presented. The study aimed to evaluate the performance of these U-Net variants under diverse geographical contexts and datasets. Their strengths and limitations were assessed, considering factors such as accuracy, robustness, and generalization capabilities. The efficacy of integrated components, such as skip connections, attention mechanisms, and multi-scale features, in enhancing the models performance was analyzed. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Unveiling the kinetics of oxygen evolution reaction in defect-engineered B/P-incorporated cobalt-oxide electrocatalysts
Defect-rich transition-metal oxide electrocatalysts hold great promise for alkaline water electrolysis due to their enhanced activity and stability. This study presents a new strategy that significantly improve the OER activity of Co-oxide nanosheets through incorporation of B and P (B/P-CoOx NS), eventually leading to abundant surface defects and oxygen vacancies. The B/P-CoOx NS demonstrates low overpotential of 220 mV to achieve 10 mA/cm2. The electrochemical and kinetic studies coupled with conventional morphological and structural characterizations, reveal that various crystalline defects like vacancies, dislocations, twin planes, and grain boundaries play crucial roles in promoting the OH? ion adsorption, the formation of intermediates, and the desorption of oxygen molecules. The industrial viability of the developed electrocatalyst is substantiated through assessments under harsh industrial conditions of 6 M KOH at 60 C in a zero-gap single-cell alkaline electrolyzer which achieves 1 A/cm2 at 1.95 V. Chronoamperometry tests (100 h) highlight remarkable robustness of the electrocatalyst. This work establishes a new strategy to fabricate defect-rich OER electrocatalysts, setting a precedent to achieve better OER rates with non-noble materials. 2024 -
Unveiling the Indian REIT narrative-qualitative insights intoretail investors perspectives
Purpose: The present study delves into the causes of relatively lower retail participation in the Indian REIT market. Specifically, it investigates investors' attitudes and perceptions towards REITs as a unique asset class. This paper provides a comprehensive understanding of the perception and factors influencing Indian retail investors' reluctance to participate in the REIT market. Design/methodology/approach: Qualitative research was conducted through semi-structured interviews to gather insights from non-investors in REITs. The data were transcribed and analyzed using content analysis techniques. Finally, coding techniques were used to identify broad study themes. Findings: According to the study results, many retail investors are unfamiliar with REITs. Even among those knowledgeable about REITs and with a favorable view, it is not commonly seen as a feasible investment option due to its early stage, unattractive returns and limited number of REITs. Practical implications: Developed countries have established REIT markets, while it is still in its infancy in developing countries such as India. Financial advisors, fund houses and the media should focus on educating investors to increase awareness. Originality/value: The study is the first qualitative investigation into the perception of retail investors to understand the reasons for lower retail engagement in the Indian REIT market. 2024, Emerald Publishing Limited. -
Unveiling the Impact of Adverse Childhood Experiences on Adult Criminal Behavior: A Qualitative Enquiry
This qualitative study explored how adverse childhood experiences contribute to criminal behavior among 20 male prisoners (aged 2040) in Kerala. Using semi-structured interviews, thematic analysis revealed seven key themes: family dysfunction, emotional struggle, abuse, economic struggle, peer pressure, coping mechanisms, and sensation seeking. Findings showed that family dysfunction creates baseline trauma, fostering emotional voids and maladaptive coping. The study emphasizes the interconnectedness of multiple adversities in shaping criminality. It highlights the need for early interventions addressing trauma, emotional dysregulation, and unhealthy coping patterns through supportive networks to prevent criminal behavior later in life. 2025 Taylor & Francis Group, LLC. -
Unveiling the Future: Exploring Stock Price Prediction in the Finance Sector through Machine Learning and Deep Learning - A Comprehensive Bibliometric Analysis
The investigation of predicting share prices is a captivating and beneficial area of study within the realm of economic research. precise projections and findings can potentially benefit shareholders by reducing the risk of making suboptimal investment selections. The objective of this investigation is to examine the present state of research pertaining to the prognostication of share price predictions through the utilization of Machine Learning (ML) and Deep Learning techniques. The present study examined the existing body of scientific works on methods involving DL and ML in the context of predicting the value of stocks. This study presents a comprehensive overview of research trends, methodologies, and applications in a particular field by conducting a bibliometric analysis of publications indexed in the Scopus database. Drawing from the presented data, recommendations for optimal methodologies can be formulated. The data was visually represented through the utilization of the R programming language and Vos Viewer software. The investigation additionally discerns the primary authors, institutions, and nations that are making contributions to this particular field of research. The outcomes of this investigation possess the potential to guide future research trajectories and offer significant perspectives for professionals and policymakers who are keen on utilizing machine learning and deep learning in the financial sector. 2024 IEEE. -
Unveiling the Future of Business Success: Integrating Environmental and Sustainable Criteria through Business Cases
This chapter explores how environmental and sustainable criteria can enhance organizational success in rapidly changing economic and societal trends. It also focuses on future value creation. The continuing fight is leading to the obsolescence of traditional tools for management due to the increased level of competition, rapid rates of change, and time compression in society. To address urgent demands for sustainability, this research examines the blending of ecological and sustainable standards with corporate objectives, illustrating how businesses can benefit from such integration. The existing business practices are presented with evidence showing their impact on the environment and society, thereby stressing the need for sustainability measures that ensure long-term success. Through an exploration of peer-reviewed literature on this topic, a variety of ways are examined. Different companies can incorporate these criteria into their operations by an analysis of best practice followed by market leaders that involve setting clear objectives and identifying key performance indicators (KPIs) to measure progress. In addition, the chapter investigates the strategies that corporations need to implement in order to adopt environmental integrity principles within their company policies, such as renewable energy sources, intelligent buildings and circular economy models, as well as other solutions that can reduce their ecological footprints, leading to organizational excellence. 2026 selection and editorial matter, Sonal Trivedi, Balamurugan Balusamy, Krishnaraj Nagappan, Dinesh Krishnan Subramaniam and Daniel Arockiam; individual chapters, the contributors. All rights reserved. -
Unveiling the Factors of Women Entrepreneurs on Social Media to Achieve Enterprise Sustainability
The research studies in the area of womens entrepreneurship (WE) has received more attention in the last decade due to its impact on bringing balanced development. On one hand, the growth of digital innovation has changed the landscape of entrepreneurship in emerging markets and on the other hand, the advocacy on business sustainability has increased. Prior studies are limited to understand the role of WE in this changing landscape. This study aims to identify the most relevant factors that influence the women entrepreneurs on social media to develop sustainable enterprise. An extensive literature review has been conducted to advance the knowledge on the WE and has been presented in form of a conceptual model to present a comprehensive perspective. Further, the research identifies social factors, psychological factors, resource factors, financial factor, firm-performance related factors, and technological factors. These factors are linked with entrepreneurial orientation among women on social media and therefore this helps in gaining sustainability. These study further present implications, strategies and agenda for future research in the area of WE. 2025 selection and editorial matter, Esra Sipahi Dongul, Serife Uguz Arsu, Richa Goel, and Tilottama Singh; individual chapters, the contributors. -
Unveiling the Emotions: A Sentiment Analysis of Amazon Customer Feedback
This study explores sentiment analysis in the context of diverse regions and contemporary customer feedback, aiming to address research questions related to consolidation based on polarity scores and sentiments. The research utilizes multinomial regression for a comprehensive analysis of customer feedback worldwide. The investigation incorporates confusion matrices, statistics, and class-specific metrics to evaluate the models performance. Results indicate a highly accurate model with perfect sensitivity, specificity, and overall accuracy. The analysis further includes a breakdown of key metrics such as accuracy, confidence intervals, no information rate, p-value, kappa, and prevalence, emphasizing the models robustness. In conclusion, the multinomial logistic regression model demonstrates exceptional performance in predicting sentiment across diverse classes, highlighting its effectiveness in sentiment analysis on a global scale. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Unveiling The Effects of Heavy Metals : A Comprehensive Study On Physiological, Phytochemical, and Anatomical Responses in Jacobaea Maritima (L.) Pelser and Meijden
Modernization and industrialization have been of great importance in the recent past, yet newlinethere are a few disadvantages including the release of harmful effluents into the environment. The medicinal plants that are found in these heavy metal polluted soils can have positive and negative effects as well. In this study the plant Jacobaea maritima (L.) Pelser and Meijden an important medicinal plant in the field of homeopathy was subjected to three different heavy metalscadmium, chromium and lead at a concentration range of 50, 100, 150, 200 and 250ppm.The morphological parameters, shoot length and root length reduced more than 50% and 25% incase of shoot and root respectively. Phytochemical analysis shows significant variation inchlorophyll. newlineThe highest of protein was found in Cr 100ppm (7.47mg) and the least was found inCd 250ppm newline(0.38mg). Proline was found to be high in Pb 200ppm (1.242mg/ml) and least in Cr50ppm newline(0.368mg/ml). The Total Phenolic Content (TPC) was found to be highest in Cr 250ppm newline(3.229mg/g) and least in control (0.57mg/g) and Total Flavonoid Content (TFC) was found to be highest in Cd 100 ppm and least in Control (0.04mg/g) plant which include root, shoot and leaf. The growth of the plant was observed along with a few parameters like net photosynthetic rate (Pn), transpiration rate (E), leaf stomatal conductance (C), and the photosynthetic active radiation (PAR). It has been found that the chlorophyll values in the Cr 150 (5.470.4) concentration are high. The chlorophyll values in Pb100 (9.40.35) and Pb250 (9.80.26) are in close proximity to newlineeach other. The highest chlorophyll was found in Cd100 concentration. The net photosynthetic rate was less affected in Pb150 (30.980.75), and most in Cr100 (4.050.09). The Cr 50 (0.190.02) showed the least. The Leaf stomatal conductance was drastically reduced in all the treated plants only Cr 100 (2298.251.85) showed minimal variation. In morphology shoot length newlineand root length were reduced more than 50% and 25% in case of shoot and root respectively. -
Unveiling the Ecological and Geopolitical Contradictions of Large-Scale Development Initiatives: A Critical Analysis of the Belt and Road Initiative
This chapter critically examines the ecological and geopolitical contradictions within large-scale development initiatives, focusing on China's Belt and Road Initiative (BRI) as a paradigmatic case. While framed as a vehicle for sustainable growth, the BRI often instrumentalizes sustainability discourse to legitimize extractive development, suppress dissent, and extend geopolitical influence. Using interdisciplinary approaches from political economy, post-development theory, and critical discourse analysis, the chapter deconstructs narratives such as 'Green BRI,' ecological civilization, and win-win cooperation. Case studies from Southeast Asia and Africa expose a stark contrast between rhetorical commitments and realities of environmental degradation, displacement, and debt dependency. The chapter advocates for an eco-centric, justice-oriented development paradigm and offers policy recommendations that emphasize accountability, participation, and ecological integrity in future infrastructure planning. 2026, IGI Global Scientific Publishing. All rights reserved.