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A bibliometric analysis of sustainability and organizations performance
The incorporation of sustainability into an organizations performance is becoming an emerging topic to work upon. Moreover, conventional economic systems have had significant negative consequences for sustainable management, as well as imbalanced wealth distribution, which has resulted in natural catastrophes and population disparity. Sustainability practices in the current environment represent better quality performances and affect organizations performance. This research highlights the key areas and current evolution in the notion of sustainable development and organizational performance, as well as recommendations for further studies. Using the bibliometric analysis we examine a sample of 1442 articles published in Scopus between 1994 till 2021. The researcher identifies prominent authors, publications, and journals by employing a variety of network analysis techniques such as term co-occurrence, co-citation, and bibliography coupling with the help of VOS viewer. To the best of the authors knowledge, no other study has examined bibliographic data on sustainability and organizations performance; hence, this research is a one-of-a-kind addition to the literature. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Successful AI integration in branding: Leveraging innovation to enhance brand identity and market impact
In the contemporary business landscape, branding extends beyond mere logos and slogans, evolving into a strategic tool that defines consumer perception, fosters engagement, and solidifies market positioning. The increasing integration of Artificial Intelligence (AI) in branding is revolutionizing the way businesses interact with consumers, enabling unprecedented personalization, predictive insights, and operational efficiency. This chapter explores the transformative role of AI in branding, examining its impact on consumer behavior, brand storytelling, and marketing effectiveness. 2025 by IGI Global Scientific Publishing. All rights reserved. -
DESI DR2 meets cosmography: a comparative study of Pad Chebyshev, and Taylor expansions
We perform a comprehensive cosmographic analysis of the late-time Universe using the latest Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) baryon acoustic oscillation (BAO) measurements, comparing Taylor, Pad and Chebyshev expansions as model-independent reconstructions of the background expansion. We consider Padapproximants of order (2,1) and (2,2), a Chebyshev expansion, and a third-order Taylor series. Due to its limited radius of convergence, the Taylor expansion is constrained using only the low-redshift DESI sub-set (z < 1), while the rational Padforms and the Chebyshev expansion are applied over the full DESI DR2 redshift range. Cosmographic parameters are inferred through a Bayesian Markov chain Monte Carlo (MCMC) analysis, and the resulting best-fitting reconstructions of H(z), dL(z), and BAO distance indicators are compared with the predictions of the Lambda cold dark matter (CDM) model. All methods are consistent with CDM at low redshift, but the Chebyshev expansion exhibits noticeable deviations at higher redshifts, while the Pad2,1) and Pad2,2) reconstructions remain closely aligned with CDM across the DESI DR2 range. A model-selection analysis based on Akaike Information Criterion and Bayesian Information Criterion shows a clear statistical preference for the Taylor expansion over low-zCDM, and a strong preference for Padcosmography over CDM when the full DESI DR2 data set is used. These results demonstrate the constraining power of DESI DR2 for cosmographic studies and highlight the utility of rational approximants, especially Padforms, in extending cosmography reliably to higher redshifts beyond the domain of traditional Taylor series. The Author(s) 2026. Published by Oxford University Press on behalf of Royal Astronomical Society. -
Padcosmography and its insights into teleparallel gravity
We investigate the viability of a modified teleparallel gravity model, specifically within the framework of gravity, by implementing two complementary approaches for cosmological parameter estimation. In the first approach, we incorporate the model into a Pad(2,1) parametrization of the Luminosity distance, enabling a stable and accurate description of the cosmic expansion history across redshift. In the second, we directly solve the modified first Friedmann equation arising from the same model. Both approaches are subjected to a comprehensive Markov Chain Monte Carlo analysis using the latest cosmological observations, including cosmic chronometers, gravitational wave standard sirens, DESI BAO DR2, the Pantheon + SH0ES compilation, and Union3. We find that the parameter constraints obtained from the Padbased formulation are in close agreement with those from the direct dynamical method, highlighting the internal consistency of the scenario and the effectiveness of Padexpansions in confronting modified gravity theories with data. In fact, both methods exhibit a better fit than the standard lambda cold dark matter (CDM) model in light of the DESI DR2 and Union3 observations. In addition, we present a detailed account of the Bayesian analysis methodology and compile a comprehensive set of the most recent and relevant cosmological data sets used in our study. 2025 The Author(s). -
Enhancing Angle Modulation Using Fractional Calculus: Theory and Performance Analysis
Angle modulation originally forms part of the backbone of the telecommunication and signal processing, where current studies are being carried out to improve its susceptibility to noise interference. This paper aims to analyze the possibility of the application of fractional calculus for optimization of angle modulation, as a requirement for development of enhanced and flexible communication networks. The main purpose of this study is to design and model new angle modulation technique which are Fractional Phase Modulation (FPM) and Fractional Frequency Modulation (FFM) by using fractional calculus. A generalized form of angle modulation and an introduction to the use of fractional calculus was proposed and a mathematical analysis of FM and FFM detectors was done. In evaluating the findings, the interaction between the fractional order of ? and some performance parameters like Signal-to-Noise Ratio (SNR) and Figure of Merit (FoM) was also considered. It has been shown that FPM and FFM detectors also show high SNR and FOM performance, and when ? is replaced. The FPM detector demonstrated a steady trend and increased from SNR 0 to 1 when the ? was diverse, while the FFM detector had a huge increase in SNR from ?=-0.9 to 0. These results indicate that the angle provides additional benefits in partial stones, signaling purity and system flexibility for the modulation technique. Thus, the ability to achieve better stability in communication for modulation techniques indicates the ability to achieve better stone purity and system flexibility for modulation techniques. Since partial order ? can be adjusted to fit the application, the proposed method shows interesting applications in many communication settings, especially when the signal is noisy or dynamic. 2025, School of Electrical Engineering and Informatics. All rights reserved. -
Association Between Early Maladaptive Schemas and Developmental Crisis Among Young Adults: Mediating Role of Cognitive Flexibility
Background: Analysing the relationship between early maladaptive schemas (EMSs) and developmental crises is critical for advancing targeted interventions; however, the psychological mechanisms underpinning these processes remain largely unexplored. Growing evidence indicates that cognitive flexibility potentially acts as a mediator in this relationship. Purpose: Grounded in the schema therapy conceptual model by Young et al. (2003), the present study investigates the mediating effect of cognitive flexibility between EMS and developmental crisis, offering insights for cognitive-based interventions. Method: A total sample of 200 participants (male = 87, female = 113), aged 1825 years (M = 20.4, SD = 1.84), were recruited using purposive sampling. The Young Schema QuestionnaireShort Form (YSQ-S2), the Developmental Crisis Questionnaire (DCQ) and the Cognitive Flexibility Scale (CFS) were administered. Result: Pearson productmoment correlation revealed a positive association between EMS and developmental crises, with the most robust relationship observed for the Disconnection and Rejection domain of EMS. Mediation analysis revealed that cognitive flexibility partially mediates the relationship between EMS 1 and developmental crises, while fully mediates the relationship for EMS 2 and 5 with developmental crises, buffering their impact, thereby reducing developmental crises among young adults. Conclusion: These findings deepen our knowledge of how cognitive patterns influence developmental challenges, delivering practical implications for creating targeted, schema incorporated interventions to strengthen resilience and support mental health in young adults. The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). -
Removal of high concentration Cr (VI) through the synergetic effect of CuInS?/Ni-MoS?/NrGO Z-scheme heterojunction and Deinococcus radiodurans R1 nano-biohybrid system
The efficient removal of high-strength hexavalent chromium [Cr (VI)] from industrial effluents continues to be a significant challenge. This study introduces a nano-biohybrid approach that combines a CuInS?/Ni-MoS?/NrGO Z-scheme heterojunction with live biomass of Deinococcus radiodurans R1 under anaerobic conditions. This combination aims to enhance the reductive sorption of Cr (VI). A Z-scheme heterojunction composed of CuInS?, Ni-MoS?, and NrGO was synthesized using the hydrothermal technique. The structural and morphological properties of the synthesized nanomaterials (NMs) were examined through various techniques, including XRD, FT-IR, UV-VIS DRS, FE-SEM, EDX, PL, XPS, Raman spectroscopy, and Mott-Schottky analysis. The CuInS?-Ni-MoS?-NrGO nanocomposite achieved nearly 97% removal of Cr (VI) at an initial dose of 50 mg/L within 3 h, which is almost three times more effective than the individual NMs CuInS?, Ni-MoS?, and NrGO. Further, applying the nano-biohybrid synergetic system enabled complete removal of Cr (VI) even at 200 mg/L, enhancing its removal capacity by 2.5-fold higher than the bare nanocomposite. The Langmuir isotherm model fits well with the experimental data, confirming homogeneous monolayer adsorption with a maximum Cr (VI) reductive sorption capacity of 333 mg/g. The intra-particle diffusion model analysis indicated that external mass transfer plays a dominant role in controlling the overall Cr (VI) sorption process. Furthermore, kinetic studies revealed that the Cr (VI) removal follows a pseudo-second-order model, suggesting chemisorption as the primary mechanism. The nanocomposite exhibited strong reusability, maintaining 86.5% Cr (VI) removal efficiency over 4 cycles. These results highlight the potential of nano-biohybrid systems as an efficient strategy for Cr (VI) remediation from contaminated wastewater. 2026 Elsevier B.V. -
AeroGlan: A Smart and Sustainable Plant Species Estimator For Organic And Localized Air Filtering
Introduction: Human health is significantly compromised by air pollution, especially by local air quality. The majority of our society spends their lives in a confined geographical location, which if subjected to air pollution can expose them to long-term air contamination. It is also possible that poor air quality can pose serious health risks, especially to susceptible individuals thereby impacting their lifestyle. Air quality can be improved with appropriate plantation, but they are underutilized. Various air purification devices have been developed in response to the ever-increasing air pollution level. Methods: However, artificial means of air purification are not very viable in terms of cost, accessibility to society, and reliable tools to purify air. This research integrates traditional solutions with modern technology to counter air purification by selectively using plant species and placing them in desired locations suitable for urban settings. The study aims to measure the constituents of various air pollutants spanning across regions to identify and accumulate pollution data using IoT-based smart devices, remit, and feed this information to cloud-based storage for further processing. In addition, advanced predictive intelligence is utilized to determine the plant species that can suffice the need for air purification through organic means in a given geographical zone resulting in enhancement of Air Quality (AQ), with minimal cost, prolonged shelf life, future proof and non-detrimental consequences. Results: Implementation outcome gives a promising outcome. Accurate readings of various air pollutants are aggregated. Suitable trees are identified to tackle these pollutants and their absorbing capacity is determined. Various predictive methods are employed and the random forest model recorded the best results. The sensory units of the model successfully captured the pollutant data and any major fluctuations were reported. The prediction pipeline recorded a mean precision, recall, and f-score value of about 0.95, 0.92, and 0.94 respectively while the mean accuracy of 0.965 was also noted. The observed training and validation accuracy with our model were 0.96 and 0.93 respectively. Conclusion: Hence, the proposed AeroGlan model may be locally applied as an air pollutants monitoring device and also to suggest suitable plant species required to counter air contamination in that locality. 2025, Bentham Science Publishers -
A study on remote sensing image segmentation and classification
The image is a composition of many pixels. These pixels include two pieces of information: coordinate or position and intensity value. The image includes several objects; extracting the crucial objects from the image is critical. Based on the similarity of patterns, classes, groups, and segments of contained objects in the image can be created. Assigning the labels to the pixels is necessary to make the image more informative for analyzing features and decision-making. This study addresses segmentation techniques and classifying images pertaining to remote sensing images. Thereafter, Land Use Land Cover (LULC) mapping is discussed, which classifies the remote sensing images. 2025 Bentham Science Publishers. All rights reserved. -
Inhibitory potential of ferula assafoetida extract on L-type calcium channel protein revealed by zebrafish studies and molecular docking
Ferula assafoetida is a part of many herbal formulations and hence it is pertinent to check the safety of its components specially to growing embryos. Zebrafish (Danio rerio) is considered to be one of the best models to study human embryonic development and metabolic pathways as its genome is fully sequenced and it possesses easily detectable developmental properties. In present study, the embryos of Danio rerio were treated with different concentrations of methanolic extract of Ferula assafoetida (MEFA) and its effects were checked at different post fertilization periods. Decreased heart beat rates, shrinkage of the chorion wall and other developmental abnormalities leading to the death of the embryos were observed. The methanolic extract of Ferula assafoetida was subjected to GC-MS to determine the different compounds present. Cardiotoxicity of these compounds were studied as it is one of the important factors for the retraction of a drug from the market. Molecular docking studies with L-type calcium channel (LTCC), a protein important for cardiac functioning, showed strong binding to the phytochemicals in the extract, with the maximum binding affinity observed with 26-hydroxycholesterol. The study proves that the methanolic extract of Ferula assafoetida contains phytochemicals which have the potential to cause cardiotoxicity in zebrafish embryos by interfering with the functions of LTCC possibly leading to arrhythmia. Altogether, our data suggest that the usage of these extracts in drug formulations should be done with caution. This is also indicative of the possible cytotoxic effect of the extract which could be tapped in the search for anticancer drugs. 2021 Chemical Publishing Co.. All rights reserved. -
Decolonizing Counselling: Integrating Non-Western Perspectives in Mental Health Intervention
This paper discusses the need to decolonize mainstream counseling practices, predominantly influenced by Eurocentric perspectives, by incorporating non-Western views and experiences. It highlights the importance of recognizing the fluidity of self and identity within diverse social and ecological contexts, particularly in countries like India, where mental health issues are on the rise. The paper critiques the limitations of Western therapeutic approaches in non-Western cultures. It emphasizes the significance of integrating local knowledge systems, such as indigenous healing traditions like the Siri cult, which promotes communal healing and addresses the spiritual dimensions of mental health. It advocates for a holistic approach to therapy that incorporates spiritual elements, encouraging self-transcendence and interconnectedness, and ultimately challenges the individualistic focus of Western psychotherapy. Integrating traditional practices and philosophies, such as Bhakti and mindfulness, is essential for fostering a more inclusive and effective mental health framework. The Author(s) 2025 -
Evaluation of web applications based on UX parameters
The objective of evaluating User Experience (UX) in this era of technology is to enhance the user satisfaction. Earlier applications were built with the aim of reducing the work of users. But with the evolution of the technology, the emergence of new gadgets and new trends in the information technology, the applications had to be more user-centric. The primary objective of this research is to evaluate the user experience of web applications based on different UX parameters using different techniques and given a rating. Each of these ratings are combined to determine the overall rating of UX for the web application. Also, the secondary objective of this research is to provide suggestions or recommendations based on the ratings to improve the UX of the web applications. An experimental study was conducted and the results show a significant improvement. Areas of further enhancements have also been identified and presented. 2019 Institute of Advanced Engineering and Science. -
Analysis of students' preferences for teachers based on performance attributes in higher education
Faculty evaluation is widely used not only for the appraisal of their performance, but also for curriculum innovation and development. There are many techniques to perform faculty evaluation. But these techniques do not address all the factors essential for evaluating a faculty. These evaluations are subjective in nature and found to be controversial as students' expectations vary. This hinders the main motive of faculty evaluation. To overcome this problem, there is a need to identify a suitable method to perform faculty evaluation. In this paper, the Conjoint Analysis, a mathematical statistics technique is used to analyze the major aspects that the students are expecting from their faculty. This technique increases the fairness in the appraisal process so that teaching can be made fun and effective. This research is a novel attempt that applies conjoint analysis to identify the major aspects of teaching in students' perspective. The proposed idea can be adapted to any domain where the customers' choice is valued particularly in Cloud computing services. 2019 Mithula G P, Arokia Paul Rajan R. -
Fake News Detection and Classify the Category
A new type of disinformation has emerged: fake news, or untrue stories that have been presented as actual occurrences. We can no longer tell whether the information is true from fraudulent since so much information is published on social media these days. Artificial intelligence algorithms are helpful in resolving the fake news identification issue. In the field of natural language processing, fake news identification is a crucial yet difficult issue (NLP). In this article, we discuss similar duties as well as the difficulties associated with finding bogus news. Based on these findings, we suggest intriguing avenues for future study, such as developing more accurate, thorough, fair, and useful detection models. The average public's life is impacted by mass media since it happens regularly. Because of this, news stories are written that are somewhat true or even entirely untrue. Using online social networking sites, people deliberately promote these fake goods. It is crucial to decide whether the news is false owing to its potential to have detrimental social and national effects. The false news identification process made use of many criteria, including the headline and body content of the news piece. The suggested method works effectively in terms of producing results with excellent accuracy, precision, and memory. Comparing all the models employed in this study, it was discovered that Distillbert and multinomial nae bayes models perform better than Logistic and others ml models. The credibility of the story may be evaluated using a larger dataset for better results and additional variables like the author and publisher of the news. Grenze Scientific Society, 2023. -
Fake News Detection and Classify the Category
Everyone depends on numerous sources of E-news in today's world when the internet is ubiquitous. Online content abounds, especially social media feeds, many of which are unreliable and may not always be factual. For people to utilise social media platforms like Facebook, Twitter, and others, fake news is a topic that may be studied through Natural Language Processing techniques. Using ideas from natural language processing and machine learning applied to social media, our goal in this work is to conduct categorization of different news items that are available online. Our intention is to empower the user to utilise NLP (Natural Language Processing) methods to identify 'fake news,' which refers to misinformed material that may be categorised as genuine or false using software like Python. The model focuses on identifying false news sources based on several articles from a website, categorising the news as false or true, and determining its veracity using unreliable sources like scikit-learn and NLP for textual analysis of the website distributing the news. When a source is identified as a publisher of false news, which can be predicted with high vectorization and also suggested using the Python scikit-learn module to do tokenization and feature development, biased viewpoints may be identified and categorised in any subsequent articles from that source. 2022 IEEE. -
Cultivating Digital Fields: A Cloud-Centric Blueprint for Stakeholder Engagement in the Indian Agriculture
This paper examines the potential of cloud computing to revolutionize the Indian agricultural sector, government operations, and rural connectivity. It highlights the benefits and challenges associated with cloud computing in agriculture and proposes a structured model to implement it effectively. Cloud computing allows farmers to access real-time information, make informed decisions, and improve access to markets. The paper examines the difficulties and advantages of cloud computing for the government in transitioning to a cloud-based version of itself for its operations. Additionally, it draws attention to specific areas related to the agricultural sector in India and certain applications offered by the government to enhance the consumer experience for stakeholders. The Government of India has demonstrated its commitment to developing technology-driven agriculture through e-NAM, Kisan Suvidha, and Agri-market initiatives. However, some challenges must be addressed to ensure the successful adoption of cloud computing in the agricultural sector. The proposed implementation model outlines the essential stages of the process, including the needs assessment, the selection of cloud providers, the automation of workflow, the modernization of applications, the implementation of security measures, and the implementation of continuous improvement. The model emphasizes the importance of training, feedback mechanisms, and collaboration. Furthermore, the paper underscores the need for a specific feedback system and grievance redress for agricultural cloud applications to enhance user experiences. To reap the full benefits of cloud computing in the Indian agricultural sector, a comprehensive strategy is necessary. This strategy necessitates technology adoption, awareness-raising, education, and stakeholder engagement. Utilizing cloud technologies, the Indian agricultural sector can realize sustainable growth, increased efficiency, and equitable development. This paper emphasizes the importance of cloud computing in transforming the Indian agrarian landscape. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Adsorption and storage of hydrogen- A computational model approach
Due to the imperative global energy transition crisis, hydrogen storage and adsorption technologies are becoming popular with the growing hydrogen economy. Recently, complex hydrides have been one of the most reliable materials for storing and transporting hydrogen gas to various fuel cells to generate clean energy with zero carbon emissions. With the ever-increasing carbon emissions, it is necessary to substitute the current energy sources with green hydrogen-based efficient energy-integrated systems. Herein, we propose an input-output model that comprehends complex hydrides such as lithium and magnesium alanates, amides and borohydrides to predict, estimate, and directly analyse hydrogen storage and adsorption. A critical and thorough comparative analysis of the respective complex hydrides for hydrogen adsorption and storage is discussed, elucidating the storage applications in water bodies. Several industrial scale-up processes, economic analysis, and plant design of hydrogen storage and adsorption approaches are suggested through volumetric and gravimetric calculations. 2024 Elsevier Inc. -
Financial inclusion of rural sector: Imperative for sustainable economic growth of India
This research paper aimed to take a look on the present status of financial inclusion in the Indian economy, especially in the rural sector. It also suggested few measures to be taken by the government and banking sector to enhance the inclusion of deprived sections of our country in the financial ecosystem. The data was collected from various secondary sources to depict the present level of financial inclusion, primarily after the implementation of various government policies. The suggested measures mainly included financial literacy and awareness campaign to be implemented at the grass root level along with a robust infrastructure to increase the telephone and internet connectivity in the rural sector. The researchers also analysed that the financial inclusion of the rural sector is imperative for the sustainable economic growth of an agricultural driven economy like India. 2021 Ecological Society of India. All rights reserved. -
A Qualitative Enquiry of the Experience of Music Professionals during the COVID-19 Pandemic
Introduction: The COVID-19 pandemic became a new normal in todays world and has changed the consumption pattern and absorption of music and music apps in India. The music industry is relatively non-telecommutable, making working from home difficult during the imposed lockdown and social distancing norms. These conditions had adverse effects on the physical and mental health of music professionals. Therefore, it was crucial to understand the differential impact of COVID-19 on music professionals to find effective solutions and plan for future careers in a changed music industry. Method: The current paper qualitatively explored the experiences of the music professionals participating in this research during the COVID-19 pandemic in India. Twelve participants having 8 years of average professional experience (comprising singers, instrumentalists, music teachers, composers, YouTube content creators) were telephonically interviewed during the second wave of COVID-19 in India. The interviews were analysed using thematic content analysis. Results: The thematic content analysis resulted in the emergence of two major themes identified from the participants narratives were impact on participating music professionals and coping reactions. Conclusion: The themes emerged from analysis highlighted the impact of COVID-19 on these music professionals and the coping reactions utilized by them. 2025 selection and editorial matter, Dr Uzaina, Dr Rajesh Verma with Dr Ruchi Pandey; individual chapters, the contributors. -
Impact of COVID-19 and Social Distancing Measures on Married Women: A Qualitative Enquiry
Considering the World Health Organizations declaration of COVID-19 as a pandemic, governments worldwide implemented lockdowns and social distancing measures to contain the spread. Despite these critical measures, the pandemic exacerbated gender inequality, particularly impacting women. With schools and workplaces closed and heightened concerns for family members health, women shouldered increased family responsibilities, leading to numerous physical and psychological health challenges. Married women, in particular, faced amplified burdens. This study aims to delve into the experiences of married women during the pandemic. Twenty married women within the age range of 2245 years residing in the northern part of India were telephonically interviewed about their experiences during the COVID-19-induced lockdown. The interviews recordings were transcribed manually and analysed using thematic content analysis. The emerging themes -emotional and psychological impact, social impact, workload impact, and coping mechanisms -shed light on both the positive and negative outcomes of the pandemic. The results revealed that both working and non-working married women encountered emotional, psychological, and social challenges such as anxiety, social isolation, increased intimacy, and workfamily conflict due to heightened domestic responsibilities resulting from the confinement of each family member at home. However, women reported that habituation and forced adjustments became their primary coping mechanisms. 2025 selection and editorial matter, Shalini Mittal, Tushar Singh, Harleen Kaur, Rahul Varma, Sreeja Das, Yogesh Kumar Arya, Sunil K. Verma, Shivantika Sharad, Divya Bhanot, Udisha Merwal, Aishwarya Jaiswal, Benkat Krishna Bharti, and Bhawna Tushir.