Browse Items (16481 total)
Sort by:
-
Investigating the heterogeneity of ESG investors: evidence from emerging economies
Purpose This study aims to examine the heterogeneity in behavioural characteristics of retail investors regarding sustainable investments, identifying patterns of convergence and divergence in sustainability-oriented market behaviours. By developing and validating specialized indices for environmental, social and governance (ESG) preferences, investor sentiments, performance perceptions, investment intentions, subjective norms, cognitive biases and greenwashing concerns, this research investigates how socio-demographic factors influence these indices through assessing heterogeneity across investor segments. Design/methodology/approach The authors develop and validate five ESG behavioural indices capturing multiple dimensions of sustainable investment behaviour. Data were collected through a comprehensive survey of 511 active retail investors in the Indian stock market. Heterogeneity analysis was conducted to identify variations in behavioural characteristics across the sample. The authors use quantile regression analysis to assess heterogeneity across demographic segments (age, income, gender, employment, education and investment experience), examining how relationships vary across the conditional distribution of ESG behavioural dimensions. Findings The analysis reveals heterogeneity in ESG investment behaviour across demographic segments. Age consistently reduces ESG engagement across all dimensions, while higher income enables selective sustainability preferences but increases investment irrationality. Gender creates divergent ESG orientations, with distinct patterns in environmental versus social priorities. Employment status and education facilitate ESG adoption through stability and social learning mechanisms, whereas investment experience paradoxically generates both sophisticated awareness and fundamental skepticism. Critically, performance perceptions emerge as the primary determinant mediating demographic influences on ESG preferences, establishing that sustainability investment behaviour is instrumentally rational rather than value-expressive in emerging markets. Practical implications The findings provide insights for enhancing sustainable investment participation. Financial institutions should develop targeted educational programmes to address knowledge gaps, as awareness significantly influences ESG preferences. Recognizing investor heterogeneity is essential younger, high-income investors respond to performance narratives, while older investors seek transparency. Addressing greenwashing concerns through standardized reporting and third-party certifications builds trust. Leveraging social influence through choice architecture and behavioural nudges can overcome decision-making barriers. Income-based strategies should include structured ESG portfolios for high-income investors prone to impulsivity, while providing educational support on stable returns for price-sensitive retail investors in emerging markets. Social implications The identified behavioural market failure in sustainable investing has important implications for the development of sustainable finance policies in emerging markets. Addressing the divergence in sustainability views could accelerate the transition towards more sustainable capital markets and contribute to broader sustainability goals. The findings highlight the need for targeted initiatives and policy interventions to bridge the gap between ESG preferences and actual investment behaviour. Originality/value This study advances sustainable finance through three contributions. First, the authors develop and validate multidimensional ESG behavioural indices capturing preferences, sentiments, perceptions, intentions and irrationality among retail investors. Second, the authors establish demographic heterogeneity as a structural market characteristic challenging the homogeneous investor assumption. Third, the authors theorize performance primacy as the fundamental mechanism driving ESG preference formation, demonstrating instrumental rationality rather than value-expression. These frameworks, validated through quantile regression analysis, provide actionable insights for policymakers and practitioners designing targeted interventions across demographically diverse investor segments in emerging markets. 2026 Emerald Publishing Limited -
Machine learning and deep learning techniques for breast cancer detection using ultrasound imaging
One of the greatest causes leading to death in women is breast cancer. Its prompt and precise identification can reduce the mortality risk associated with the disease. With the help of computer-based detection, radiologists can identify irregularities. To identify and diagnose numerous illnesses and anomalies, medical photographs are sources of important information. Various techniques help radiographers to examine the internal system, and these techniques have generated a significant amount of attention across several fields of research. Each of these approaches holds a great deal of relevance in many healthcare sectors. Using artificial intelligence techniques, this article aims to present a study that highlights current developments in the detection and classification of breast cancer. The categorization of breast cancer using many medical imaging modalities is discussed in this article. It initially offers a summary of the various machine learning methodologies, followed by a summary of the various deep learning algorithms used in the detection and characterization of metastatic breast tumors. To give an insight into the field, we also give a quick summary of the various imaging techniques. The chapter concludes by summarizing the upcoming developments and difficulties in the diagnosis and classification of breast cancer. 2024 Elsevier Inc. All rights reserved. -
Impact of AI in Financial Technology- A Comprehensive Study and Analysis
Presently across the world, financial institutions strive tremendously hard to make financial services smarter to benefit from the advantages of digitization. To enhance client services, financial technology (Fintech) uses a variety of modern breakthrough technologies, including Artificial Intelligence (AI), 5G/6G, Blockchain, Metaverse, IoT, and others, in the financial sector. Many important financial services and procedures, including loans, authentication, fraud detection, quality control, creditworthiness, and several more, would be streamlined and improved by the adoption of technology. However, a need exists for the development of innovative financial products as well as the corresponding technological ecosystem. To launch Information and Communication Technology (ICT) alternatives, various major tech companies have placed their emphasis on Fintech. In this paper, we first explore the latest opportunities in Fintech. Furthermore, we also attempt to present a foundation of the Fintech accelerators, such as IoT, 5G, Digital twins, and Metaverse. Additionally, we also outline recommendations for future research directions in Fintech while looking forwards to potential difficulties. 2023 IEEE. -
Click, Trap, Repeat: Dark Patterns and the Illusion of Choice in the Digital Market
This chapter will look into how AI has transformed the traditional methods of dark patterns, which are deceptive, manipulative designs used to trick users into decisions that wouldnt have been made if such patterns were not introduced. It will analyse how such patterns use predictive reasonings across e-commerce, social media, and fintech platforms, influencing consumer behavior and their decision-making. The chapter highlights the wide regulatory gap in addressing the manipulations and ethical implications by drawing on global developments from the European Union, the United States, and Asia. The study aims to provide a multidisciplinary understanding of how AI boosts digital deception and to propose a legal framework that safeguards user autonomy, promotes transparency, and ensures accountability in an AI-mediated consumer environment Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development. -
Climate Performance and Firm Valuation: A Meta-Analysis of Tobins Q in the Post-IPCC AR6 Era
This study examines whether corporate climate performance is reflected in firm valuation by synthesising recent empirical evidence, using Tobins Q as a forward-looking indicator of market expectations. Employing a random-effects meta-analysis of 30 peer-reviewed studies published between 2020 and 2025 across multiple industries and regions, the findings reveal a modest yet statistically significant positive association between stronger climate performance and higher market valuations, suggesting that investors increasingly incorporate climate-related information into firm pricing. Contrary to prevailing assumptions in the literature, proactive climate strategies, such as emissions-reduction initiatives, do not systematically generate greater valuation benefits than disclosure-oriented approaches; both exhibit comparable positive effects. Similarly, valuation outcomes do not differ materially between self-reported and externally verified climate data. Meta-regression analysis identifies data source as the only statistically significant moderator, although its influence remains nuanced. Overall, the results indicate that climate performance enhances firm valuation in a context-dependent manner, challenging the view that only proactive strategies or externally verified data are uniquely rewarded by financial markets. The study contributes to the sustainable and corporate finance literature by clarifying how capital markets price climate-related corporate behaviour under heterogeneous strategic responses. 2026 by the authors. -
Mediating Effect of Digital Literacy Between Attitude Towards AI and Job Insecurity Among HR Professionals
As businesses continue to incorporate technologies that use AI into a variety of business processes, the connection between employee attitudes towards AI and job insecurity has attracted some attention. However, a critical aspect that has not been covered in the existing literature is the potential mediating role of digital literacy in shaping this relationship. This study investigates the interplay between attitudes towards AI, job insecurity, and digital literacy among HR employees through an online survey. Utilizing established scales, including Attitudes Towards AI (ATAI), Job Insecurity, and Digital Literacy, significant results reveal a substantial mediated relationship. Finding also states a significant impact of attitudes towards AI on job insecurity. Acceptance AI attitude indirectly reduce job insecurity through heightened digital literacy. Also, the pivotal role of digital literacy as a mediator, emphasizing its importance in alleviating job insecurity concerns amidst AI integration. These findings offer practical insights for organizations seeking to foster employee confidence in AI-rich workplaces. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Analysis of Blockchain Transaction Patterns and Risk Assessment in the Open Metaverse
This research explores the use of an ensemble comprising Random Forest, XG-Boost, and Isolation Forest algorithms for anomaly detection and risk analysis of blockchain transactions in the Open Metaverse. We created a multi-phase strategy using temporal feature engineering, risk assessment frameworks, and behavioral pattern analysis using an extensive dataset of 78,600 transactions. The ensemble model achieved 99% classification accuracy and zero false positives for valid transactions, while effectively detecting phishing (84% precision, 68% recall) and scam activities (81% precision, 91% recall). With 56.19% of the categorization, risk assessment measures were the most important predictive indicators, followed by transaction patterns and behavioral attributes. Our cross-validation analysis resulted exceptional stability in performance, with standard deviation of 0.0004 across diverse transaction scenarios. This confirms that our methodology can reliably detect intricate risk patterns, playing a crucial role in strengthening transaction security as the Open Metaverse continues to evolve. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Impact of chitosan and chitosan-based nanoparticles on genetic transformation: an overview
Currently, the primary challenge to modern agricultural science is to meet the global demand for products and ensure food security for the growing population. No doubt the conventional plant breeding techniques and use of agrochemicals to obtain greater crop productivity and variety have been established to fight against biotic and abiotic stress in plants for better yield of agricultural products. The scientific community is exploring better techniques that can satisfy the need of mankind without affecting the ecosystem. Genetic engineering in plants is a recent advancement in the field of plant biotechnology and is more precise and can quickly obtain the desired trait in plants. This technology majorly focuses on improving the crop yield and quality by expressing desirable genes that are responsible for desirable traits such as tolerance to extreme conditions, herbicide, pest resistance, and enhanced secondary metabolite production, which is of medical importance. Nanomaterial-mediated genetic transformation is one reliable and efficient means of crop improvement for sustainable development in agricultural science. This technology has revolutionized modern agriculture as they are used as an effective delivery system to plants. Chitosan-based nanoparticles find their best application as nano-carrier due to their intrinsic properties such as cationic, biocompatible, high loading capacity, and good penetration potential with good release kinetics. Thus chitosan nanoparticles are used to deliver different types of genetic materials such as DNA, RNA, miRNA, siRNA, pDNA, CRISPR/Cas9 single guide RNA for plant transformation. This chapter provides an overview of chitosan nanoparticles as a delivery system and with a focus on their application as a safe genetic delivery system in plants. 2022 Elsevier Inc. All rights reserved. -
Convective instability in a horizontal porous layer saturated with a chemically reacting Maxwell fluid
The problem of onset of convective instability in a horizontal inert porous layer saturated with a Maxwell viscoelastic fluid subject to zero-order chemical reaction is investigated by linear stability analysis. Modified Darcy-Maxwell model is used to describe the fluid motion. The horizontal porous layer is cooled from the upper boundary while an isothermal boundary condition is imposed at the lower boundary. Closed form solution pertaining to the basic quiescent state is obtained. The resulting eigenvalue problem is solved approximately using the Galerkin method. The Rayleigh number, characterizing the stability of the system, is calculated as a function of viscoelastic parameter, Darcy-Prandtl number, normalized porosity, and the Frank-Kamenetskii number. The possibility of oscillatory instability is discussed. 2013 AIP Publishing LLC. -
Convective instability in a horizontal porous layer saturated with a chemically reacting viscoelastic fluid
The thesis is concerned with Rayleigh-Benard convection in a horizontal porous layer saturated with a viscoelastic fluid subject to a zero order exothermic chemical reaction. Modified Darcy law is employed to describe the fluid motion. The effect of viscoelasticity, chemical reaction, and rotation on the onset of convection is considered. The findings of the problems investigated in the thesis may prove useful in heat transfer application situations with viscoelastic fluids as working medium. -
Deciphering the properties of UV upturn galaxies in the Virgo cluster
The UV upturn refers to the increase in UV flux at wavelengths shorter than 3000 observed in quiescent early-type galaxies (ETGs), which still remains a puzzle. In this study, we aim to identify ETGs showing the UV upturn phenomenon within the Virgo galaxy cluster. We utilized a colourcolour diagram to identify all potential possible UV upturn galaxies. The spectral energy distributions (SED) of these galaxies were then analysed using the CIGALE software; we confirmed the presence of UV upturn in galaxies within the Virgo cluster. We found that the SED fitting method is the best tool to visualize and confirm the UV upturn phenomenon in ETGs. Our findings reveal that the population distributions regarding stellar mass and star formation rate properties are similar between UV upturn and red sequence galaxies. We suggest that the UV contribution originates from old stellar populations and can be modelled effectively without a burst model. Moreover, by estimating the temperature of the stellar population responsible for the UV emission, we determined it to be 13 000 K to 18 000 K. These temperature estimates support the notion that the UV upturn likely arises from the contribution of low mass evolved stellar populations (extreme horizontal branch stars). Furthermore, the Mg2 index, a metallicity indicator, in the confirmed upturn galaxies shows higher strength and follows a similar trend to previous studies. This study sheds light on the nature of UV upturn galaxies within the Virgo cluster and provides evidence that low-mass evolved stellar populations are the possible mechanisms driving the UV upturn phenomenon. 2024 The Author(s). -
Beyond the rings: Polar ring galaxy NGC 4262 and its globular cluster system
In the context of the hierarchical model of galaxy evolution, polar ring galaxies (PRGs) are considered the intermediate phase between ongoing mergers and quiescent galaxies. This study explores the globular cluster system (GCS) and its properties in the nearest PRG, NGC4262, serving as a pilot investigation to study GCS in nearby PRGs. We utilize wide and deep-field observations of the CFHT as part of the NGVS to investigate the GCS of NGC4262. We presented the first optical image of NGC4262 with an optically faint ring component. The photometric analysis of the GCS displays a distinct colour bimodality. We estimate the total number of GCs for NGC4262 to be 266 16 GCs with a specific frequency of 4.2 0.8 and a specific mass of 0.23 0.01, which is relatively high compared to other galaxies of similar mass and environmental conditions. The spatial and azimuthal distributions of subpopulations reveal strong evidence of previous interactions within the host galaxy. The colour distribution of GCS in NGC4262 shows a gradient of 0.05 0.01 within 5.5, supporting the notion of past interactions and evolutionary transitions. PRG NGC4262 conforms to the overall trend of the GCS mass with respect to the halo mass. Furthermore, our investigation of the global scaling relations between GCS and host galaxy parameters provides further support for the hypothesis that PRGs are an intermediate phase connecting ongoing mergers and quiescent galaxies. 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. -
DES J024008.08-551047.5: A new member of the polar ring galaxy family
Aims. This study presents the discovery of a new polar ring galaxy (PRG) candidate and highlights its unique features and characteristics. We provide evidence from photometric analysis that supports the inclusion of galaxy DES J024008.08-551047.5 (DJ0240) in the PRG catalogue. Methods. During the visual observations of optical imaging data obtained from the Dark Energy Camera Legacy Survey, a serendipitous discovery was made of a ringed galaxy, DJ0240. We conducted a one-dimensional isophotal analysis to determine the position angle of the ring component and its relative orientation to the host galaxy. A two-dimensional GALFIT analysis was performed to confirm the orthogonal nature of the ring galaxy and identify distinct components within the host galaxy. We compared the photometric properties of the host and ring components of DJ0240 with PRGs and other ring-type galaxies (RTGs), finding that DJ0240 shares similar properties with both of these galaxy types. Results. We have discovered the galaxy DJ0240, a PRG candidate with a ring component positioned almost perpendicular to the host galaxy. The position angles of the ring and host components are ?80 and ?10, respectively, indicating that they are nearly orthogonal to each other. The extension of the ring component is three times greater than that of the host galaxy and shows a distinct colour separation, being bluer than the host. The estimated g-r colour values of the host and ring components are 0.86 0.02 and 0.59 0.10 mag, respectively. The colour value of the ring component is similar to those of typical spiral galaxies. The host galaxy's colour and the presence of a bulge and disc components indicate that the host galaxy may be lenticular. Our findings reveal a subtle yet noticeable colour difference between the host and ring components of PRGs and RTGs. We observe that both the host and ring components of DJ0240 align more closely with PRGs than with RTGs. Furthermore, we compared the Sersic index values of the ring component (nring) of galaxy DJ0240 with a selected sample of PRGs and Hoag-type galaxies. The results show that DJ0240 has a remarkably low nring value of 0.13, supporting the galaxy's classification as a PRG. Hence, we suggest that the ring galaxy DJ0240 is a highly promising candidate for inclusion in the family of PRGs. 2024 The Authors. -
Role of biosynthesized silver nanoparticles in environmental remediation: a review
Nanoscience and nanotechnology have made remarkable advances that have significantly altered the environmental remediation process. Silver nanoparticles (AgNPs) are an essential and remarkable nanomaterial in environmental remediation. The potential of AgNPs in biomedical applications is well explored compared to their environmental applications. This review explores the biosynthesis and application of AgNPs in environmental remediation. The discussion continues with the challenges of using AgNPs for environmental remediation and concludes with the prospects of AgNPs. The review will be beneficial to all researchers and professionals who are starting their journey with AgNP synthesis. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Connecting the dots: Tracing the evolutionary pathway of polar ring galaxies in the cases of NGC 3718, NGC 2685, and NGC 4262
Polar ring galaxies (PRGs) are a unique class of galaxies characterised by a ring of gas and stars orbiting nearly orthogonal to the main body. This study delves into the evolutionary trajectory of PRGs using the exemplary trio of NGC 3718, NGC 2685, and NGC 4262. We investigate the distinct features of PRGs by analysing their ring and host components to reveal their unique characteristics through spectral energy distribution (SED) fitting. Using CIGALE, we performed SED fitting to independently analyse the ring and host spatially resolved regions, marking the first decomposed SED analysis for PRGs, which examines stellar populations using high-resolution observations from AstroSat UVIT at a resolved scale. The UV-optical surface profiles provide an initial idea that distinct patterns in the galaxies, with differences in FUV and NUV, suggest three distinct stages of ring evolution in the selected galaxies. The study of resolved-scale stellar regions reveals that the ring regions are generally younger than their host galaxies, with the age disparity progressively decreasing along the evolutionary sequence from NGC 3718 to NGC 4262. Star formation rates (SFR) also exhibit a consistent pattern, with higher SFR in the ring of NGC 3718 compared to the others, and a progressive decrease through NGC 2685 and NGC 4262. Finally, the representation of the galaxies in the HI gas fraction versus the NUV- plane supports the idea that they are in three different evolutionary stages of PRG evolution, with NGC 3718 in the initial stage, NGC 2685 in the intermediate stage, and NGC 4262 representing the final stage. This study concludes that PRGs undergo various evolutionary stages, as evidenced by the observed features in the ring and host components. NGC 3718, NGC 2685, and NGC 4262 represent different stages of this evolution, highlighting the dynamic nature of PRGs and emphasising the importance of studying their evolutionary processes to gain insights into galactic formation and evolution. The Author(s), 2025. -
Long Term X-Ray Spectral Variations of the Seyfert-1 Galaxy Mrk 279
We present the results from a long term X-ray analysis of Mrk 279 during the period 2018-2020. We use data from multiple missions - AstroSat, NuSTAR and XMM-Newton, for the purpose. The X-ray spectrum can be modeled as a double Comptonization along with the presence of neutral Fe K? line emission, at all epochs. We determined the sources X-ray flux and luminosity at these different epochs. We find significant variations in the sources flux state. We also investigate the variations in the sources spectral components during the observation period. We find that the photon index and hence the spectral shape follow the variations only over longer time periods. We probe the correlations between fluxes of different bands and their photon indices, and found no significant correlations between the parameters. 2024. National Astronomical Observatories, CAS and IOP Publishing Ltd. -
Modelling the energy dependent X-ray variability of Mrk 335
We present a technique which predicts the energy dependent fractional r.m.s. for linear correlated variations of a pair of spectral parameters and apply it to an XMM-Newton observation of Mrk 335. The broadband X-ray spectrum can be interpreted as a patchy absorber partially covering the primary emission, a warm and hot coronal emission or a relativistically blurred reflection along with the primary emission. The fractional r.m.s. has a non-monotonic behaviour with energy for segments of lengths 3 and 6 ksecs. For each spectral model, we consider every pair of spectral parameters and fit the predicted r.m.s. with the observed ones, to get the pair which provides the best fit. We find that a variation in at least two parameters is required for all spectral interpretations. For both time segments, variations in the covering fraction of the absorber and the primary power law index gives the best result for the partial covering model, while a variation in the normalization and spectral index of the warm component gives the best fit in the two corona interpretation. For the reflection model, the best fit parameters are different for the two time segment lengths, and the results suggests that more than two parameters are required to explain the data. This, combined with the extreme values of emissivity index and reflection fraction parameters obtained from the spectral analysis, indicates that the blurred reflection model might not be a suitable explanation for the Mrk 335 spectrum. We discuss the results as well as the potential of the technique to be applied to other data sets of different AGN. 2025 Elsevier B.V. -
Analysis of forbidden neon emission lines in HAeBe stars using Spitzer IRS spectra
We analysed high-resolution mid-infrared spectra of 78 well-known Herbig Ae/Be (HAeBe) stars using Spitzer InfraRed Spectrograph data, focusing on the detection of [Ne ii] and [Ne iii] emission lines as indicators of ionized outflows or disc winds. Emission from [Ne ii] at 12.81 m or [Ne iii] at 15.55 m was identified in 25 sources, constituting the largest sample of HAeBe stars with these detected lines. Our analysis revealed a higher detection frequency of [Ne ii] in sources with lower relative accretion luminosity (Lacc/L?< 0.1), suggesting a connection to the disc dispersal phase. We examined correlations between neon lines and various spectral features and investigated [Ne iii]-to-[Ne ii] line flux ratios to explore potential emission mechanisms. Neon emission is predominantly observed in Group I sources (75 per cent), where their flared disc geometry likely contributes to the observed emission, potentially originating from the irradiated disc atmosphere. Interestingly, we also find that Group II sources exhibit a higher median relative [Ne ii] line luminosity (L/L), suggesting enhanced photoevaporation rates possibly associated with their more settled disc structures. However, larger samples and higher-resolution spectra are required to confirm this trend definitively. The high detection rate of the [Fe ii] and [S iii] lines, commonly associated with EUV-dominated regions, alongside a [Ne iii]-to-[Ne ii] emission ratio greater than 0.1 in sources where both lines detected, suggests that EUV radiation is the primary driver of neon emission in our sample. 2025 The Author(s). -
Modelling the energy dependent X-ray variability of Mrk 335
We present a technique which predicts the energy dependent fractional r.m.s. for linear correlated variations of a pair of spectral parameters and apply it to an XMM-Newton observation of Mrk 335. The broadband X-ray spectrum can be interpreted as a patchy absorber partially covering the primary emission, a warm and hot coronal emission or a relativistically blurred reflection along with the primary emission. The fractional r.m.s. has a non-monotonic behaviour with energy for segments of lengths 3 and 6 ksecs. For each spectral model, we consider every pair of spectral parameters and fit the predicted r.m.s. with the observed ones, to get the pair which provides the best fit. We find that a variation in at least two parameters is required for all spectral interpretations. For both time segments, variations in the covering fraction of the absorber and the primary power law index gives the best result for the partial covering model, while a variation in the normalization and spectral index of the warm component gives the best fit in the two corona interpretation. For the reflection model, the best fit parameters are different for the two time segment lengths, and the results suggests that more than two parameters are required to explain the data. This, combined with the extreme values of emissivity index and reflection fraction parameters obtained from the spectral analysis, indicates that the blurred reflection model might not be a suitable explanation for the Mrk 335 spectrum. We discuss the results as well as the potential of the technique to be applied to other data sets of different AGN. 2025 Elsevier B.V.