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Navigating uncharted desires: a qualitative inquiry into bicurious identity conflicts among young women in 21st-century post-colonial India
Bicuriosity, often considered a fluid space of sexual identity questioning and same-gender exploration, is frequently framed as a transitional phase, especially in heteronormative cultures. This study focuses specifically on young Indian women, whose experiences are shaped by both heteronormativity and gendered expectations that intensify identity conflict and social scrutiny. Using reflexive thematic analysis, this qualitative study examined the narratives of twelve urban women aged 1825 who self-identified as bicurious. Four key themes were constructed: Wrestling with Ambiguity and Self-Doubt, Encountering Invalidation and Monosexism, Journey Towards Self-Validation, and Finding Strength in Community. Participants described emotional turmoil arising from limited representation of plurisexual identities, fear of marginalisation, and cultural expectations of heterosexuality. Yet, the process of questioning also fostered resilience, self-acceptance, and the pursuit of affirming spaces, often online. The study emphasises how cultural collectivism, familial dynamics, and gender shape identity navigation and advocating for inclusive, gender-sensitive interventions in post-colonial India. 2026 Informa UK Limited, trading as Taylor & Francis Group. -
Silicene and Germanene for Biosensing and Imaging Application
The discovery of two-dimensional materials creates an immense effect in the field of biomedicine especially in sensing applications. Silicene and germanene are group 14 elements, analogs of graphene. Several experiments and theoretical information have proven the excellent properties of silicene and germanene as semiconductors, capacitors, photocatalysts, and sensors. Computational and other studies show the ability of these two-dimensional materials in biosensing applications. These graphene analogs have fascinating characteristics there are no band gaps in the semiconductors which leads to a lack of stability and is liable to oxidation. Since there is an essentiality of band gap for biosensing applications which can be corrected by making some modifications in these analogs using certain metal substrates. In this chapter, we will summarize silicene and germanene elements, their various properties and their applications in biosensing and bioimaging. This suggests silicene and germaneneas promising nanoelements for the evolution of new electronic equipment for biosensing and other uses in future. 2025 Scrivener Publishing LLC. -
Silicene and Germanene for Biosensing and Imaging Application
The discovery of two-dimensional materials creates an immense effect in the field of biomedicine especially in sensing applications. Silicene and germanene are group 14 elements, analogs of graphene. Several experiments and theoretical information have proven the excellent properties of silicene and germanene as semiconductors, capacitors, photocatalysts, and sensors. Computational and other studies show the ability of these two-dimensional materials in biosensing applications. These graphene analogs have fascinating characteristics there are no band gaps in the semiconductors which leads to a lack of stability and is liable to oxidation. Since there is an essentiality of band gap for biosensing applications which can be corrected by making some modifications in these analogs using certain metal substrates. In this chapter, we will summarize silicene and germanene elements, their various properties and their applications in biosensing and bioimaging. This suggests silicene and germaneneas promising nanoelements for the evolution of new electronic equipment for biosensing and other uses in future. 2025 Scrivener Publishing LLC. -
Navigating Post-Pandemic Mental Health Challenges: Unleashing the Potential of Artificial Intelligence
In the wake of the COVID-19 pandemic, the landscape of healthcare, particularly in the realm of mental health, has undergone unprecedented shiftsThis chapter delves into the pivotal role of artificial intelligence (AI) in shaping post-pandemic mental healthcare deliveryThis chapter comprehensively explores AI-driven solutions, including predictive modeling, sentiment analysis, and virtual assistants; this chapter underscores how AI technologies can revolutionize mental health diagnosis, treatment, digitalized psychometric assessment and support care websites, and automated consultation or recommendation of specific mental issuesAdditionally, it discusses integrating AI-powered tools in remote monitoring, teletherapy, and digital interventions to address the increasing demand for mental health services and bridge existing gaps in accessibility and conversion of digital platforms to provide mental health services and appointments, case records, and easy accessibilityMoreover, ethical considerations, data privacy concerns, and the importance of maintaining human-centric approaches in AI-enabled mental healthcare are examined per the Information Act and Mental Healthcare ActBy shedding light on the transformative potential of AI, this chapter aims to empower healthcare stakeholders to leverage cutting-edge technologies in fostering resilience and recovery in the post-pandemic era. 2025 selection and editorial matter, Philip Eappen and Narasimha Rao Vajjhala; individual chapters, the contributors. -
Revolutionizing Mental Health Care: The Transformative Power of Internet of Medical Things (IoMT): A Comprehensive Overview and Case Studies
This study proposes the detection of humans in disaster-affected areas from the images obtained from unmanned aerial vehicle (UAV). Specialized rescue teams do such search and rescue operations to search a vast area for missing persons. The degrading effect of blur induced by camera movement during image capture is one of the primary difficulties in data processing of UAV photography. This can be caused by the UAVs natural flying movement, severe winds, turbulence, or unexpected operator inputs, all of which reduce accuracy. This blur disturbs the visual analysis and interpretation of the data, causes errors, and can degrade the accuracy. As a result, this approach proposes a method based on contrast-limited adaptive histogram equalization (CLAHE) and deblurring using Gaussian blur kernel as the solution. A variety of UAV datasets were used to verify the methods speed and reliability. This method proves to be fast and efficient, making the algorithm applicable for UAV dataset. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
Revolutionizing Mental Health Care: The Transformative Power of Internet of Medical Things (IoMT): A Comprehensive Overview and Case Studies
This study proposes the detection of humans in disaster-affected areas from the images obtained from unmanned aerial vehicle (UAV). Specialized rescue teams do such search and rescue operations to search a vast area for missing persons. The degrading effect of blur induced by camera movement during image capture is one of the primary difficulties in data processing of UAV photography. This can be caused by the UAVs natural flying movement, severe winds, turbulence, or unexpected operator inputs, all of which reduce accuracy. This blur disturbs the visual analysis and interpretation of the data, causes errors, and can degrade the accuracy. As a result, this approach proposes a method based on contrast-limited adaptive histogram equalization (CLAHE) and deblurring using Gaussian blur kernel as the solution. A variety of UAV datasets were used to verify the methods speed and reliability. This method proves to be fast and efficient, making the algorithm applicable for UAV dataset. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. -
Development of Mindfulness Based Solution Focused Brief Therapy for Children (MBSFT-C): An International Delphi Study
Internalizing and externalizing behavioral issues among children tend to appear together and are often interrelated. A combination of Solution-focused brief therapy (SFBT) and Mindfulness is theoretically promising in reducing the co-occurrences of internalizing and externalizing issues. In this study, we developed and validated MBSFT-C, which addresses internalizing and externalizing behavioral issues. Preliminary components of MBSFT-C were developed, integrating the philosophies of Mindfulness and Solution Focused Brief Therapy. We used a two-round Delphi survey to finalize and validate these components. In the first round, the experts provided a free-text review of the initial components of MBSFT-C, which were then analyzed thematically using QDA Miner v2.0.9 software. In the second round, the experts evaluated the final components of MBSFT-C and reached a consensus using a 10-point visual analog scale. Thematic analysis of review 1 revealed three themes, Validation, Additions, and Modifications, based on which the final draft of MBSFT-C was developed. The final draft included two major components, Mindful Solution Focused Engagement and Family Mindfulness Skills. All the components of MBSFT-C achieved international expert consensus with a 70% agreement in review 2. The mean score for components by the experts ranged between 7.50 and 8.00 out of 10 on a visual analog scale, with a standard deviation ranging from 1.94 to 2.95. MBSFT-C will provide clinicians with a well suited, empirically developed, manualized comprehensive therapy that meets the special requirements of children. 2025 Taylor & Francis Group, LLC. -
EVALUATING THE ELEMENTS IN THE RECREATIONAL SPACE OF AN INSTITUTION
The concept of 'Recreation' justifies the human need for satisfaction, leisure, and a state of pleasure. The elements involved in a recreational space impact the activities of the user in that space. Recreational spaces act as the in-between sojourns for formal pedagogy or andragogy. Spaces of recreation are essential, especially in educational institutions, where students spend most of their time. Public, semi-public, and private spaces are all included in the institutional design, with a large percentage used by students. Open public spaces, including recreational places, are measured in terms of their physical characteristics and connections to nature. The components of a recreational area influence the activities that users engage in there. This paper seeks to list and assess the many components that are present in a recreational space. This study will evaluate those elements and their types. Informal outdoor areas or other breakout areas promote interaction and provide the students with refreshments and leisure. The focus of this paper is to draw out the quality of leisure space synonymous with a productive environment for the student, where they feel rejuvenated. Five recreational spaces of CHRIST University were studied, and the elements that combine to form this place were also observed. A survey among the students who are frequent users of these spaces was conducted, and their responses were evaluated. The elements that majorly help students go to a place were assessed, and the element's significant role was concluded. The result of this study to design professionals is to understand the need to incorporate recreational spaces while designing an educational institution and design a student-oriented space. ZEMCH Network. -
Structural and morphological characterization of hydrothermally synthesized N-Carbon Dot @ Fe3O4 composites for heavy metal ion detection
Heavy Metal-ion contamination is one of the most serious issues facing day-to-day life. To address this issue, sensing and removal of heavy metal ions in contaminated water become indispensable. Carbon Dots are hydrophilic in nature with magnificent electron acceptor and electron donator and hence it has been used as fluorescent probes for sensing applications. The present study deals with the synthesis of N-Carbon Dot (N-CD) @ Fe3O4 composite which was successfully fabricated via the hydrothermal method. The surface structure and morphology of the synthesized composite were characterized using X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). The elemental analysis of a sample was characterized using Energy Dispersive Spectroscopy (EDS). Further, the phase occurrence and the molecular vibration were analysed using XRD and Fourier Transform Infra-Red Spectroscopy (FTIR). Finally, the optical studies were measured using Ultravioletvisible Spectroscopy (UV Vis) and Photoluminescence Spectroscopy (PL). The prepared composite exhibited noticeable fluorescence properties and has promising potential for the detection and removal of toxic heavy metal ions in water. 2022 -
Nitrogen doped carbon quantum dots@?-Fe2O3/PANI nanocomposite based electrochemical sensor for cadmium ion detection
Cadmium (Cd2+) ions pose significant risks due to their toxic effects even at low concentrations. By integrating nitrogen-doped carbon quantum dots (N-CQDs) with ?-Fe2O3 and polyaniline (PANI), we have engineered a nanocomposite that demonstrates a remarkably high sensitivity and selectivity in detecting Cd2+ ions. The NCQDs@?-Fe2O3/PANI nanocomposite was prepared by using hydrothermal and in-situ polymerization methods. The characterization techniques for an eco-friendly polymer nanocomposite confirm the interactions between N-CQDs, ?-Fe2O3, and PANI. X-ray diffraction analysis shows the nanocomposite possesses a crystal size of 24 0.03 nm. Field-emission scanning electron microscope and high-resolution transmission electron microscope images showed that the spherical N-CQDs are enclosed by irregular ?-Fe2O3 nanoparticles, which are dispersed on the PANI sheets. Further, the particle size distribution analysis indicates an average size of 5.8 nm for the N-CQDs. The electrochemical sensing result suggests that the nanocomposite is effective in sensing the Cd2+ ions with a detection limit of 750 nm. 2025 -
Streamlined Deployment and Monitoring of Cloud-Native Applications on AWS with Kubernetes Prometheus Grafana
As organizations increasingly move their applications to the cloud, it becomes essential to have an efficient and cost-effective method for deploying and managing those applications. Manual deployment can be time-consuming, error-prone, and expensive. Additionally, managing logs and monitoring resources for each deployment can lead to even greater costs. To address these challenges, we propose implementing an automation strategy for deployment in the cloud. With automation, the deployment process can be streamlined and standardized across different cloud providers, reducing the potential for errors and saving time and resources. Furthermore, a central log system can be implemented to manage logs from different deployments in one location. This provides a unified view of all logs and allows for easier troubleshooting and analysis. Automation can also be used to set up monitoring resources, such as alerts and dashboards, across different deployments. Overall, implementing an automation strategy for deployment in the cloud can help organizations save time and resources while improving their ability to manage and monitor their applications. A centralized log management system can further enhance these benefits by providing a unified view of logs from all deployments 2023 IEEE. -
Predictors of emotional and behavioral problems among Indian adolescents: A clinic-based study
Background: Emotional and behavioral problems place a heavy burden on the adolescents and their families. Many factors are known to influence adolescent mental health. The current study was designed to determine the predictors of emotional and behavioral problems among Indian adolescents. Methods: The parents of adolescents in the age group of 10 to 18 (N = 81) were recruited from the National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka, India. Alabama Parenting Questionnaire (Parent version), Strength and Difficulty Questionnaire (Parent version) and, the Parent Interview Schedule (PIS) were used to assess the parental practices, emotional and behavioral problems and abnormal psychosocial environment of the adolescents. The data were analyzed with stepwise multiple linear and Quantile regression to find out significant predictors of emotional and behavioral problems among adolescents. Results: Adolescent's age, parental involvement, and paternal age are the significant predictors of emotional problems. Parental mental disorder or deviance, gender, and inconsistent discipline are the significant predictors for conduct problems. Poor monitoring and supervision, paternal and maternal age are statistically significant predictors of prosocial skills among the adolescents. Inadequate or distorted intrafamilial communication and parental mental disorder are the significant predictors of total difficulties among the adolescents. Conclusion: The study validates the role of abnormal psychosocial environments and negative parenting practices as risk factors for emotional and behavioral problems among the adolescents. A comprehensive analysis which covers all possible variables related to adolescent mental health is mandatory for the health professionals before planning the intervention. 2018 Elsevier B.V. -
Exploring Social Cues and Engagement in Humanoid Robots: A Robosen K1 Case Study
With the increase adoption of humanoid robots in today's world, the need to understand the ways through which these robots communicate social cues has become indispensable for effective human-robot interaction (HRI) in everyday life. The focus of this study is on the examination of the influence of nonverbal behaviour of Robosen K1 (a humanoid robots) on human perceptions and emotional responses. K1 was programmed to perform expressive full-body movements, due its lack of facial expressions, such as dancing, push-ups, and standing on its head. The research design was a mixed-method approach, which combined behavioural observations from live interactions with data from an online survey. Findings from the study revealed positive emotional reactions from participants, most of which described the robot as 'impressive', 'curious', and 'amusing'. Also, results indicated that 89.8% of participants were favourably disposed to engaging with similar robots in the future. Finally, it was found that the robot's gestures, being highly expressive, contributed to perceived personality traits such as 'playful' and 'friendly'. The study, therefore, concluded that a well-designed non-verbal cues would play critical role in enhancing emotional connection, engagement, and trust in humanoid robots, hence, their importance for successful HRI design. 2025 IEEE. -
Media and Urban Governance: The Quest for Sustainable Cities and Communities
Connectivity becomes the hallmark of network society facilitated by digital technologies. Cities are fundamentally well-connected, fast-growing, communicative, and global in outlook. Cities are also known for media concentration, as the structures and people there extensively create and exchange messages - social, political, economic, and cultural. The urban communication landscape is very complex, and therefore, a robust media and communication infrastructure is required to form, reform, and transform urban communities from a sustainable development perspective. Media not only perform the responsibilities of information dissemination and community building but also facilitate urban governance and public discourses on policies. The policy-making process that consists of policy inputs, policy processes, and policy outputs - is heavily influenced by the public discourses triggered by the media. Media can establish a policy issue at the center of the public sphere, set the policy agenda, and create public opinion. It inevitably leads to the mediatization of public policy. Media can effectively place SDGs at the center of the policy discourse and serve as a tool for urban governance by enhancing citizens' participation and helping to solve complex urban problems. This research paper explores various aspects of the governance-media interface in an urban landscape to create sustainable cities and communities. The Electrochemical Society -
A Particle Swarm Optimization-Backpropagation (PSO-BP) Model for the Prediction of Earthquake in Japan
Japan is a country that suffers a lot of earthquakes and disasters because it lies across four major tectonic plates. Subduction zones at the Japanese island curves are geologically complex and create various earthquakes from various sources. Earthquake prediction helps in evacuating areas, which are suspected and could save the lives of people. Artificial neural network is a computing model inspired by biological neurons, which learn from examples and can be able to do predictions. In this paper, we present an artificial neural network with PSO-BP model for the prediction of an earthquake in Japan. In PSO-BP model, particle swarm optimization method is used to optimize the input parameters of backpropagation neural network. Information regarding all major, minor and aftershock earthquake is taken into account for the input of backpropagation neural network. These parameters are taken from Japan seismic catalogue provided by USGS (United States Geological Survey) such as latitude, longitude, magnitude, depth, etc., of earthquake. 2019, Springer Nature Singapore Pte Ltd. -
Real time conversion of sign language to speech and prediction of gestures using artificial neural network
Sign language is generally used by the people who are unable to speak, for communication. Most people will not be able to understand the Universal Sign Language (unless they have learnt it) and due to this lack of knowledge about the language, it is very difficult for them to communicate with mute people. A device that helps to bridge a gap between mute persons and other people forms the crux of this paper. This device makes use of an Arduino Uno board, a few flex sensors and an Android application to enable effective communication amongst the users. Using the flex sensors, gestures made by the wearer is detected and then according to various pre-defined conditions for the numerous values generated by the flex sensors, corresponding messages are sent using a Global System for Mobile(GSM) module to the wearer?s android device, which houses the application that has been designed to convert text messages into speech. The GSM module is also used to send the sensor inputs to a cloud server and these values are taken as input parameters into the neural network for a time series based prediction of gestures. The system is designed to be a continually learning device and improve reliability by monitoring every individual?s behaviour at all times. 2018 The Authors. Published by Elsevier B.V. -
MOF derived cobalt-phospho-boride for rapid hydrogen generation via NaBH4 hydrolysis
Developing effective transition metal catalysts that can replace precious metal-based catalysts for hydrogen generation from the hydrolysis of chemical hydride has attracted extensive interest. This study focuses on synthesizing cobalt phospho-boride (CoPB) within a metal-organic framework (MOF) framework using hydrothermal and chemical reduction methodologies. Incorporating boron and phosphorous into Co-MOF enhances the hydrogen generation rate, reaching 1.8 L/min/g and 3.6 L/min/g for CoB-MOF and CoPB-MOF, respectively, during NaBH4 hydrolysis. Along with the nanostructured morphology of MOF, the electron modulation around Co-sites due to the presence of P and B creates a synergic effect to produce this high H2 generation rate and very low activation energy of 20.7 kJ/mol. The kinetic studies on NaBH4 hydrolysis reaction revealed zero-order kinetics with respect to NaBH4 concentration for CoPB-MOF, where porous morphology renders facile movement of BH4? ions to the active sites. The heat treatment at 773 K in the N2 atmosphere did not show any significant fall in the activity of CoPB-MOF, thus showcasing its robust nature. Moreover, the present catalyst also displayed recycling behavior with no signs of deactivation. 2024 Hydrogen Energy Publications LLC -
Lignin nanoparticles from Ayurvedic industry spent materials: Applications in Pickering emulsions for curcumin and vitamin D3 encapsulation
Lignin nanoparticles (LNP), extracted from spent materials of Dashamoola Arishta (Ayurvedic formulation), shared a molecular weight of 14.42 kDa with commercial lignin. Processed into LNPs (496.43 0.54 nm) via planetary ball milling, they demonstrated stability at pH 8.0 with a zeta potential of ?32 0.27 mV. Operating as Pickering particles, LNP encapsulated curcumin and vitamin D3 in sunflower oil, forming LnE + Cu + vD3 nanoemulsions (particle size: 347.40 0.71 nm, zeta potential: ?42.27 0.72 mV) with high encapsulation efficiencies (curcumin: 87.95 0.21%, vitamin D3: 72.66 0.11%). The LnE + Cu + vD3 emulsion exhibited stability without phase separation over 90 days at room (27 2 C) and refrigeration (4 1 C) temperatures. Remarkably, LnE + Cu + vD3 exhibited reduced toxicity, causing 29.32% and 34.99% cell death in L6 and RAW264.7 cells respectively, at the highest concentration (50 ?g/mL). This underscores the potential valorization of Ayurvedic industry spent materials for diverse industrial applications. 2024 Elsevier Ltd -
Lignin-based nanomaterials for food and pharmaceutical applications: Recent trends and future outlook
Small particles of size ranging from 1 to 100 nm are referred to as nanoparticles. Nanoparticles have tremendous applications in various sectors, including the areas of food and pharmaceutics. They are being prepared from multiple natural sources widely. Lignin is one such source that deserves special mention due to its ecological compatibility, accessibility, abundance, and low cost. This amorphous heterogeneous phenolic polymer is the second most abundant molecule in nature after cellulose. Apart from being used as a biofuel source, lignin is less explored for its potential at a nano-level. In plants, lignin exhibits cross-linking structures with cellulose and hemicellulose. Numerous advancements have taken place in synthesizing nanolignins for manufacturing lignin-based materials to benefit from the untapped potential of lignin in high-value-added applications. Lignin and lignin-based nanoparticles have numerous applications, but in this review, we are mainly focusing on the applications in the food and pharmaceutical sectors. The exercise we undertake has great relevance as it helps scientists and industries gain valuable insights into lignin's capabilities and exploit its physical and chemical properties to facilitate the development of future lignin-based materials. We have summarized the available lignin resources and their potential in the food and pharmaceutical industries at various levels. This review attempts to understand various methods adopted for the preparation of nanolignin. Furthermore, the unique properties of nano-lignin-based materials and their applications in fields including the packaging industry, emulsions, nutrient delivery, drug delivery hydrogels, tissue engineering, and biomedical applications were well-discussed. 2023 Elsevier B.V. -
A Methodological Framework for Descriptive Phenomenological Research
Background: Descriptive phenomenological research is crucial in nursing for understanding individuals experiences, perceptions, and relationships, which are essential for person-centered healthcare. However, a common critique is that researchers often use phenomenological methods without fully comprehending their historical and philosophical foundations. Existing literature highlights discrepancies in the application of phenomenological principles by nurse researchers, particularly in their presentation of philosophical underpinnings and methodological details. Aim: This article aims to provide a comprehensive methodological framework for descriptive phenomenological research in nursing, addressing both theoretical and practical aspects to guide novice researchers. Data Sources: This framework synthesizes existing scholarship on descriptive phenomenology. Discussion: Starting from Husserl, this article provides a detailed overview of the history, foundations, and philosophical assumptions of the methodology. It also includes key terms and a comprehensive detailing of all aspects of the research process. Conclusion: This framework enriches existing scholarship by offering a streamlined, step-by-step methodological guide for researchers embarking on descriptive phenomenological studies. It emphasizes the importance of establishing minimum, yet critical criteria for publishing research employing this methodology. Implications for Research: Future nurse researchers are encouraged to enhance methodological transparency in their descriptive phenomenological studies to facilitate rigorous evaluation of method effectiveness and study quality. This framework aims to alleviate potential apprehensions and provide clarity and structure to novice researchers in the field. The Author(s) 2024.