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Some New Results on Non-zero Component Graphs of Vector Spaces Over Finite Fields
The non-zero component graph of a vector space with finite dimension over a finite field F is the graph G=(V,E), where vertices of G are the non-zero vectors in V, two of which are adjacent if they have at least one basis vector with non-zero coefficient common in their basic representation. In this paper, we discuss certain properties of the non-zero component graphs of vector spaces with finite dimension over finite fields and their graph invariants. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
New results on orthogonal component graphs of vector spaces over Zp
A new concept known as the orthogonal component graph associated with a finite-dimensional vector space over a finite field has been recently added as another class of algebraic graphs. In these types of graphs, the vertices will be all the possible non-zero linear combinations of orthogonal basis vectors, and any two vertices will be adjacent if the corresponding vectors are orthogonal. In this paper, we discuss the various colorings and structural properties of orthogonal component graphs. 2024 Azarbaijan Shahid Madani University. -
Electrospinning of polyetheretherketone-based homopolymers and block copolymers
Electrospinning involves the fabrication of ultrafine fibers, typically ranging in diameter from nanometers to micrometers. This process entails applying a high voltage to a polymer solution or melt, resulting in the production of fibers that can be collected on a designated surface. Polyetheretherketone (PEEK) is a semicrystalline linear polycyclic aromatic polymer with high thermal stability. It is a high-performance thermoplastic known for its mechanical strength, thermal stability, and chemical resistance. The rigid radiolucency, stable physicochemical properties, and biocompatibility of electrospun PEEK homopolymer fibers make them suitable reinforcements in composite materials, medical sutures, removable prosthetics, vertebral surgery, orthopedics, and scaffolds for tissue engineering. PEEK homopolymers offer a wide range of advantages; however, they have a high melting temperature, high viscosity in the molten state, and a low glass transition temperature. Blending PEEK with other polymers and the formation of block copolymers introduces an additional set of functionalities by combining the properties of PEEK and other polymers. PEEK block copolymers can be electrospun with tailored properties and diverse morphologies, resulting in enhanced processability and compatibility for broad applications, including medical implants, filtration membranes, and reinforcing materials. This chapter discusses the principles and parameters of electrospinning, the factors responsible for the electrospinning of PEEK-based homopolymers and block copolymers, issues such as solubility, spinnability, and related costs, and possible solutions for overcoming these issues. Various applications of electrospun PEEK homopolymers and block copolymers are also discussed in this chapter. 2026 Elsevier Inc. All rights reserved. -
Ion-imprinted carbon dots: rationally designed fluorescent probes for the detection of selected metal ions from aqueous solutions
Photoluminescence properties of Carbon Dots (CDs) have been leveraged for their use as sensors for a variety of analytes, including inorganic ions, organic molecules, and biomolecules. The selective fluorescence response of CDs to specific analytes is generally not pre-designed. Rationally designed synthesis of CDs with pre-defined selectivity to specific analytes is a less explored avenue. This study presents a novel method for the customized synthesis of CD fluorescent probes and an ion-imprinting-based selective detection of metal ions using these CDs. Poly(sodium 4-styrenesulfonate) [PSS] treated with Cd(ii) ions was used as the precursor for preparing Cd-imprinted CDs, and a modified form of these CDs was used for the sensing of Cd(ii) in aqueous solutions. As synthesized CDs have Cd(ii) ions on their surface, which were subsequently removed through appropriate chemical treatment. This removal results in binding sites of Cd(ii) ions on the CDs. Formation of such binding sites results in alterations of the fluorescence of CDs. Exposure of these particles to analytes containing Cd(ii) ions leads to the re-occupation of the binding sites by the metal ions, resulting in a distinct fluorescence response, which serves as the sensing readout. Effectiveness of this ion-imprinting approach is demonstrated by the selective and sensitive fluorescence response of the CDs towards Cd(ii) ions, with a limit of detection (LOD) of 3.62 nM. This strategy of Cd(ii) detection using ion-imprinted CDs represents a novel effort in CD-based sensors, and this can be extended to the sensing of other cations also. This journal is The Royal Society of Chemistry, 2025 -
Ultrafast nonreciprocal transmission modulation in metasurfaces with epsilon-near-zero materials
Nonreciprocity refers to the difference in received to transmitted ratio when the source and detector are interchanged [1]. Optical isolator - component which allows transmission in one direction - is a canonical example of a nonreciprocal device. Nonreciprocity can be achieved through three known pathways; (i) materials with asymmetric permittivity or permeability tensors, such as ferrites; (ii) nonlinear light-matter interactions[2-4]; and (iii) time-varying systems[5]. While traditionally nonreciprocal components are quite large in size, nanofabrication of metasurfaces has enabled their miniaturisation to the nanoscale. However, ultrafast nonreciprocal responses at the nanoscale remain still a challenge. Here we design and study metasurface with an epsilon near zero material indium tin oxide (ITO) that enables ultrafast switching of refractive index via Kerr nonlinearity, in order to achieve optical isolation. 2025 IEEE. -
Phytochemical screening, GC-MS profiling and in vitro antioxidant activity of leaves of Dysoxylum malabaricum Bedd. ex C. DC.
Plants are a rich source of phytocompounds, have remained an integral part of traditional medicine and serve as alternativesto modern medical treatments. They are powerful sources of antioxidants and the bioactive compounds in plants are associated with a wide range of pharmacological activities. Dysoxylum malabaricum is a species of medium to large-sized trees from the Meliaceae family that is widely found in the Southern Western Ghats and its bark and fruits are used in traditional medicine. Even though it is widely used as ethnomedicinal plant, limited research has been done on its phytochemical constituents, especially the phytocompounds presentin the leaves. Therefore, this study aims to extensively explore and identify the phytocompounds and bioactive elements found in the leaf extracts of D. malabaricum. Extract was prepared from leaves of D. malabaricum using soxhlet extraction method in different solvents (methanol, water and chloroform). Quantitative estimation of phytochemicals and in vitro antioxidant assays were carried out, followed by chemical profiling of the extracts using GC-MS, which revealed the presence of many important secondary bioactive compounds. The methanolic extract showed a higher concentration of phenolics (67.88 0.26 mg GAE/g) and flavonoids (57.55 0.23 mg QE/g) when compared to aqueous and chloroform extracts. The methanolic extract also demonstrated remarkable DPPH scavenging (with IC50value 32.45 0.22 g/mL) and ferric reduction activities. The results demonstrate that D. malabaricum is an effective source of bioactive and antioxidant compounds. 2025 Horizon e-Publishing Group. All rights reserved. -
IoT Based Bus Identification and Distance Notifier for the Visually Impaired
Public transport is a major obstacle for the visually impaired, and it tends to limit their independence and mobility. To overcome this problem, the current project presents an IoT-based bus identification and distance notification system that is meant to offer real-time support and improve the traveling experience of the visually impaired commuters. The system uses a Raspberry Pi controller in combination with an RFID reader and several RFID cards, each one of which is designated for a particular bus, to detect oncoming vehicles. A GPS unit monitors the position of the bus at all times, so it is possible to calculate exact distances to any of the stops. For additional convenience, the system includes three push-button switches programmed to three predetermined bus stops. Users may pick their destination stop, and the system will offer auditory feedback in terms of distance to the selected destination. Feedback is offered by an earphone, providing hands-free use and receiving instructions without visual interaction. The integration of RFID-based bus identification, GPS location, and voice guidance provides smooth real-time information, less reliant on outside help. The system increases mobility confidence through accurate, timely, and convenient information, enabling blind travelers to make use of public transport independently. Through the combination of IoT technology and assistive technologies, the project enables enhanced accessibility and inclusion in urban mobility systems. 2025 IEEE. -
A comparative study of machine learning: Models for web tracker detection
Web trackers, used by websites, collect user data and monitor online activity, often with or without explicit consent. With concerns for online privacy, there is a growing need to detect these web trackers. This study evaluates several machine learning (ML) techniques for detecting web trackers, focusing on evaluating their performance from the key metrics such as accuracy, precision, and recall. We analyzed supervised methods, such as random forest, support vector machines (SVM), neural networks, gradient boosting, and unsupervised methods, including DBSCAN and isolation forest. Models were trained on a comprehensive dataset extracted from URLs with feature engineering, and data preprocessing techniques were applied to enhance model performance and detect both known and unknown trackers and normal traffic. Our results indicate that supervised models outperform unsupervised methods, demonstrating their superior ability in distinguishing web trackers from normal traffic. This work highlights the effectiveness of ML-based tracker detection and outlines opportunities for improving privacy protection through adaptive supervised learning methods. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Effect of functionalization on the energy storage performance of super capacitors derived from wood charcoal
The electrochemical performance of wood charcoal is investigated with respect to the disorders in the system after subjecting to oxidation and exfoliation conditions. The Cyclic voltammetry and galvanostatic charge discharge curves indicate an improvement in the electrochemical behavior, resulting in a marginal increase in the specific capacitance values at higher exfoliation temperatures. The improvement is predominantly due to the change in the structural disorder in the system accompanied by the incorporation of oxygen functional groups which act as electrochemical active species. The exfoliation of wood charcoal at 160 and 200C yield a specific capacitance of 6.23 and 12.24 F/g at a current density of 0.01 A/g. The ESR values representing the overall resistance of the system are observed to be 6.07 ? for 200C as opposed to 10.41 ? of the bare material, making the material more conducting. The drastic change in the structural morphology along with the optimal amount of oxygen functional groups can be the reason for this behavior. The acquired results offer useful information for investigating the possibilities of fabricating supercapacitors with wood charcoal by tuning the defects of the system. 2024 American Institute of Chemical Engineers. -
Evaluating the electrochemical performance of single and multiple heteroatom doped carbon black from waste tires for supercapacitor application
With the growing emphasis laid on the research related to energy storage systems, the need for cost-effective and efficient materials is quintessential. The present work reports a comprehensive study and a promising strategy to enhance the electrochemical behaviour of Carbon Black derived from waste tires by the incorporation of heteroatoms such as Nitrogen and Sulfur into the system. The study investigates the electrochemical performance of Carbon Black with single doping, and further examines the enhanced performance with co-doping. While the Nitrogen-doped Carbon Black exhibits a specific capacitance of 97.63F/g, the Sulfur doped Carbon Black exhibits 141.8F/g and the co-doped Carbon Black exhibits an enhanced specific capacitance of 233F/g at a current density of 1 A/g in the two-electrode system. A significant improvement in the specific surface area is achieved in the materials with post-doping techniques. Furthermore, the co-doped Carbon Black provides superior electrochemical behaviour with sustained energy density of 30Wh/kg even at a higher power density of 5.6kW/kg with an improved cyclic stability of 91% over 5000 cycles. Thus, effective valorization of Carbon Black recovered from waste tires enables the development of efficient and affordable electrode material for the fabrication of supercapacitors. 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Nanoarchitechtonics of high surface area carbon material for coin cell supercapacitor application
Advancing energy storage systems thrive on innovative electrode materials, balancing sustainable synthesis with enhanced electrochemical performance. In the present work, a feasible approach for developing a carbon derivative exhibiting all the promising features of a superior electrode material is reported. Nitrogen and Sulfur are strategically incorporated into the carbonaceous material along with Potassium-based activation, such that additional pseudocapacitance, along with an enhanced surface area are achieved. Carbon derived from charcoal is co-functionalised with Nitrogen and Sulfur via a two-step pyrolysis technique, resulting in a material that exhibits improved surface area of 1488.8m2g?1 and enhanced electrochemical performance. It showcases a gravimetric capacitance of 689Fg?1 and 295Fg?1 at 1Ag?1, corresponding to the three and two-electrode setups respectively. A gravimetric capacitance of 425Fg?1 is maintained at a high current density of 50Ag?1 with a capacitance retention of 61.6 %. A sustained energy density of 20.50W h kg?1 at a power density of 3.1kWkg?1 is achieved by this material with a stability of 94 % for 5000 cycles at 2Ag?1. In addition, coin cells fabricated with the as-prepared material demonstrated the real-world feasibility by illuminating LEDs of different colors. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Chitosan Coated-Liposomal Microencapsulation of Fucoidan Extracted from Marine Sargassum wightii: Assessment of Its Biofunctional and Therapeutic Properties
Fucoidan, a sulphated polysaccharide derived from Sargassum wightii, holds significant therapeutic potential due to its antioxidant, antimicrobial, and wound-healing properties. Despite its therapeutic properties, its clinical efficacy is limited by poor bioavailability and instability. This study reports the successful encapsulation of fucoidan in liposomes employing the thin-film hydration technique, followed by chitosan coating to enhance its stability and biological activity. Structural integrity and successful encapsulation were confirmed through FTIR and UVVis spectroscopy. Antioxidant activity assessed via DPPH and hydrogen peroxide scavenging assays demonstrated concentration-dependent radical scavenging, with chitosan-coated formulations exhibiting superior efficacy. The formulation was reported to exhibit strong antioxidant potential, as indicated by DPPH (38.65% at 500?g/ml) and H?O? (40.707% at 400 ?g/ml). Antimicrobial testing revealed notable activity against the Gram-negative bacterium Escherichia coli, but not against the Gram-positive bacterium Bacillus subtilis, suggesting a narrow-spectrum antibacterial potential. The antimicrobial assays conducted reported a zone of inhibition of 11.4mm for a concentration of 2mg/ml. Furthermore, scratch wound assays and MTT-based cytotoxicity analysis on L929 fibroblast cells indicated promising wound-healing activity, with a wound closure of 92.72% observed 72h after treatment with the sample. The IC?? value of 100?g/ml was also reported to have high cell viability of 84.22%. These findings underscore the potential of chitosan-coated liposomal fucoidan as a multifunctional bioactive system for pharmaceutical and biomedical applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026. -
Designing culture through the human resource functions
Human resource management now plays an active strategic partner role instead of being a passive observer. Today, the HR department of an organization is expected to drive organization performance through the biggest strength of the firm; its people. It is expected that all HR functions will contribute to the company's strategic goals and foster an inclusive and productive work environment. The current study is based on data gathered from the hotel industry and aims to comprehend how HR functions impact various aspects of organisational culture. The findings point to important connections between specific HR procedures and cultural elements. The results offer insight into how HR specialists can use their roles to establish the ideal atmosphere within the company. 2025, IGI Global Scientific Publishing. -
Ethnographic research on primary education of tribals: a scoping review
Ethnographic research offers comprehensive learning outcomes by examining the socio-emotional, economic and cultural components crucial for comprehending marginalized groups experiences. This study aims to examine the methodologies used in studies and the gaps in the literature on the primary education of tribal communities, highlighting the limitations of the current research approaches. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) of Arksey and OMalleys six-step framework, the scoping review has considered 19 studies of 406 research articles published from 2015 to 2024 across the databases Scopus, JSTOR, and ERIC. The review highlights that most of these studies used descriptive survey design, mixed-method research design, and ethnographic research design. While the first two document barriers, the ethnographic studies provide richer cultural in-depth also. However, gaps in the literature include a lack of interventions for specific tribes, such as the Mannan community in Kerala, India, and the integration of indigenous knowledge, which is only possible through cultural inclusiveness. The findings suggest that future research should prioritize interdisciplinary collaboration and teacher training in multilingual education (MLE) through ethnographic methods for developing culturally sensitive interventions. These recommendations aim to contribute to developing more culturally inclusive educational practices and policies in the primary education curricula. 2026, Intelektual Pustaka Media Utama. All rights reserved. -
Graph Convolutional Networks for Predicting Postpartum Depression: A Symptom-Based Analysis
Postpartum Depression (PPD) is a serious mental health condition affecting new mothers and aligns with the United Nations Sustainable Development Goal (SDG) 3: Good Health and Well-being, which stresses early detection and intervention. This research investigates the use of Graph Neural Networks (GNNs)specifically, Graph Convolutional Networks (GCNs)to predict PPD by modeling the interdependencies among symptoms. A preprocessed dataset of 1,503 records was utilized, involving categorical encoding, missing value imputation, and feature standardization to enhance model reliability. The GCN model was built using a K-Nearest Neighbors (KNN)-based graph structure, enabling the network to learn intricate relationships between symptoms. Experimental results showed that the GCN achieved an accuracy of 89%, identifying key predictors such as trouble sleeping, guilt, irritability, difficulty concentrating, and anxiety. The use of SHAP explainability tools further validated these predictors, enhancing interpretability and revealing the models decision-making process. While traditional models like Random Forest achieved higher classification accuracy (95%), GCN offered valuable insights into the underlying structure and relationships among symptoms, supporting its potential in mental health diagnostics. Future work may explore hybrid architectures and larger datasets to further improve the models predictive performance and contribute to AI-driven early screening strategies for PPD. 2025 IEEE. -
The Impact of Government Initiatives on Sustainable Business Practices
This paper examines the evolving role of government initiatives in fostering sustainable business practices, with a focus on Corporate Social Responsibility (CSR) as a critical tool for aligning economic growth, social equity, and environmental sustainability. By analyzing the historical evolution of CSR and its current framework in India, including its mandatory implementation under the Companies Act, 2013, this study highlights the multidimensional aspects of CSR: environmental, ethical, philanthropic, and economic responsibilities. It also explores the strategic integration of CSR to meet stakeholder expectations, enhance competitiveness, and mitigate risks, illustrating its potential as a driver for sustainable development. The research further addresses mechanisms for legal compliance, inspection, and enforcement, offering insights into the challenges and opportunities for businesses in adhering to CSR norms while contributing to broader societal goals. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Womens Economic Empowerment and Domestic Violence: Evidence from the Indian State of Kerala
Domestic violence is a serious issue that affects countless women around the world. Kerala boasts an admirable history of high literacy rates, good health and sanitation standards, low infant mortality rates and impressive average life expectancy. Despite these advancements, enduring social problems such as gender discrimination and domestic violence still exist. Over the last two decades, domestic violence has been a significant issue for women in Kerala. The basic objective of this study is to assess the impact of womens economic empowerment on domestic violence. This study employed stratified sampling methods to gather household-level data using pre-designed questionnaires. The study found a weak link between economic empowerment and domestic violence. Womens education and husbands characteristics, notably alcohol usage, have a significant impact. This emphasises the importance of interventions that promote collaborative decision-making in order to combat domestic abuse effectively. 2026 selection and editorial matter, Samapti Guha and Chirodip Majumdar; individual chapters, the contributors. All rights reserved. -
Examining the Relationship Between Acceptance of Technology Integration and Dimensions of TPACK Among Higher Secondary School Teachers in Kerala
The study uses the Unified Theory of Adoption and Use of Technology (UTAUT) to investigate how higher secondary school teachers in Kerala, India, connect to Technological Pedagogical Content Knowledge (TPACK) and technology adoption. Using 496 teachers from diverse backgrounds, the study revealed some important positive correlations between TPACK characteristics and UTAUT results. Strong technologically minded teachers are interested in incorporating technology into the classroom. Crucially for the quality of education, PK, PCK, and CK have a modest influence on technology acceptance. The study emphasises the need for specific professional development and supportive policies to fit Kerala's unique educational scene. With consequences for the whole educational scene, TPACK can encourage improved technology acceptance, particularly in sectors connected to technology. Future research should look at long-term changes in technology use, geographical comparisons, and how new technologies impact teaching approaches. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Monitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection
Skip to main content Taylor & Francis Group Logo T&F eBooks ? Search for keywords, authors, titles, ISBN Advanced Search About Us Subjects Browse Products Request a trial Librarian Resources What's New!! HomeComputer ScienceArtificial IntelligenceApplying Metaverse Technologies to Human-Computer Interaction for HealthcareMonitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection Monitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection Chapter Monitoring the Virtual Realm: Ethical Dilemmas and Connotations in the Metaverse?Artificial Intelligence Connection ByMeera Mathew Book Applying Metaverse Technologies to Human-Computer Interaction for Healthcare Edition1st Edition First Published2025 ImprintAuerbach Publications Pages18 eBook ISBN9781003491668 Share Share ABSTRACT The virtual world will be altered significantly as a result of the incorporation of metaverses into digital communication. Immersive, cooperative, and resilient 3D cybernetic environments that surpass conventional web surfing define the metaverse. Modern technology and dynamic forces that fortify the metaverse are what propel this advancement, since they allow its hybrid virtual-physical nature to be effortlessly integrated. The development and fulfilment of virtual world technologies require core capabilities including blockchain, artificial intelligence (AI), cloud computing, and 5G and 6G connection. Web3, which uses blockchain technology and smart contracts to create a decentralized, user-centric Internet, is all about the practical and geographical visibility of metaverses. Nonetheless, these ideas are connected to the broader evolution and do not conflict with one another. Because of its multiple functions, the metaverse may be used for a wide range of tasks. The gaming and entertainment sectors employ the metaverse in some of its most well-known uses. Users may enjoy a vibrant and imaginative setting in the metaverse where they can play games, watch films, go to concerts, etc. Because it may offer instructors and students a virtual environment where it is feasible to conduct training and experiments that cannot be experienced in the actual world owing to potential hazards or expenses, the metaverse can have various applications and consequences in the field of education. The metaverse will also benefit corporate growth, employee cooperation and communication, the creation of more realistic simulation models for urban development, process optimization, and many other areas. However, there are drawbacks to the metaverse as well. These include addictiveness, impairment of the ability of the mind to discriminate between actual reality and augmented or virtual reality, privacy protection, safeguarding people's digital identities, information confidentiality, and the requirement for sophisticated hardware and software infrastructure in order to receive, send, simulate, and process information in real time. The Indian Information Technology Act of 2000 and its implementing rules created India's current data protection system, which places requirements on businesses managing sensitive and personal data. Businesses must create organizational safeguards to protect data and get consent before processing any data. As the metaverse integrates more deeply into our digital world, a single legal framework is critical for managing the convergence of artificial intelligence and citizen privacy. In the light of newly introduced Indian Digital Personal Data Protection Act (DPDP Act) of 2023, data fiduciaries, data holders, and data processors have to be cautious of data collection and dissemination, and for this reason, metaverse app developers, app retainers, and app disseminators need special attention. Companies that employ moral artificial intelligence strategies are more prepared to navigate moral and societal traps associated with conducting business in the metaverse. 2025 selection and editorial matter, B. Sundaravadivazhagan, Balasubramaniam S, Pethuru Raj, and K. Shantha Kumari. -
Implementing smart cyber-physical systems in industrial and urban applications: A practical approach
World urbanization, at an accelerated rate, leads to a growing need for innovative cities that consider advances in AI and cyber-physical systems (CPS). A smart city is a development of a traditional environment of an urban setting, enhancing it with information and communication technology (ICT) and CPS to improve the quality of life, sustainability, and efficiency of the inhabitants. This chapter will cover the major constituents, challenges, and opportunities associated with the development of smart cities from the historically congested and ad hoc planned cities. A smart city connects a digitally empowered environment through sensors, processors, and communication systems integrated into urban infrastructures, allowing continuous monitoring of public health, mobility, energy consumption, and so on. The combination of AI and data analytics with smart city technologies will help optimize services in cities, reduce environmental effects, and accelerate socioeconomic development and decision-making. Improvement to cities is still a debatable issue, and there are additional obstacles to be overcome, such as infrastructural inadequacy, budgetary constraints, and technical issues. Realization of the full potential of smart cities will occur through successful resolution of the aforementioned issues. All the issues of this chapter can be addressed by adopting a multidisciplinary approach emphasizing sustainable designs, publicprivate sector partnerships, and regulatory frameworks. If ignored, such problems will definitely lead to adverse effects on implementation, an increase in socioeconomic inequality, and damage to the environment. This chapter relies on the secondary methodology of research and assimilates knowledge from journal articles, literature, and earlier research regarding smart cities, CPS, and AI applications. It defines current trends, recognizes long-standing problems, and suggests ways to bridge them, along with some directions for future research. This will help in understanding the ability of AI to make smart city adaptation strong concerning population growth, health crises, and climate change. It will also strengthen and connect the urban landscape of the future. Thus, by solving these problems and their consequent impacts, smart cities can totally transform urban life. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors.