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Multimodal data generation and synthesis
Multimodal data generation and synthesis have become new promising directions in artificial intelligence research, making possible the combination and transformation of the different data modalities: text, images, audio, and video. In this chapter a look will be made about the principles, methodologies, applications, and challenges linked with multimodal data, bringing attention to the current trends and needs regarding multimodal systems and systems approaches to tackle complex real-world challenges across the medical and health care, autonomous systems, entertainment, and extended reality (XR) fields. The chapter introduces multimodal data and discusses how the approach differs from unimodal methods, considering the merits of working with multiple data forms. Multimodal systems present richer and more comprehensive representations that lead to better decision-making and provide a better interaction with users. The complexity due to alignment, synchronization, and representation of diverse modes is inherently difficult. This section further discusses state-of-the-art techniques in multimodal synthesis, especially focusing on generative approaches like generative adversarial networks (GANs), variational autoencoders (VAEs), and diffusion models. These methods are shown to facilitate cross-modal transformations, such as text-to-image or audio-to-video synthesis, driving innovation in artificial intelligence and beyond. Applications of multimodal data synthesis are discussed in detail, underscoring its transformative impact. In health care, for instance, synthesizing medical images paired with textual annotations enhances diagnostic accuracy and medical training. Autonomous vehicles benefit from the integration of LiDAR, visual, and auditory data, enabling robust decision-making in real-time environments. Similarly, in entertainment and XR, multimodal synthesis is redefining content creation, making immersive experiences more personalized and dynamic. The chapter also delves into novel applications such as multimodal translation, exemplified by systems that translate sign language into spoken text, fostering inclusivity and accessibility. Despite its potential, multimodal synthesis faces critical challenges, including bias in data and models, privacy concerns, and the ethical implications of creating hyperrealistic synthetic data, such as deepfakes. All these raise pressing concerns, and addressing these requires robust privacy-preserving techniques, bias-mitigation strategies, and stringent ethical guidelines. 2026 Elsevier Inc. All rights reserved. -
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Polymer-nanocarbon composites: a promising strategy for enhanced performance of organic solar cells
The exigency for sustainable and clean energy resources has led to profound research in development of various generations of solar cells, aiming to control the over-exploitation of fossil fuels and subsequently limit environmental degradation. Among the fast-emerging third-generation solar cells, polymer solar cell technology has gained much consideration due to its potential for achieving economically feasible, lightweight, flexible solar energy harvesting devices. As a predominant research area, at present, the major concerns regarding polymer solar cells include improving conversion efficiency, enhancing absorption bandgap in polymers, limiting photochemical degradation, and remediating low dielectric constant. Nanocarbon materials can be effectively blended with polymers and have been widely reported to enhance the performance of polymer solar cells owing to their desirable characteristics like high electrical conductivity, mechanical strength, thermal stability, non-toxicity, large specific surface area, flexibility, and optical transparency. In this review, we briefly discuss various conjugated polymer-nanocarbon composites, including polymer/graphene derivatives, polymer/graphene quantum dots (GQD), and polymer/carbon nanotubes (CNTs), elucidating their roles in the performance enhancement of polymer solar cells (PSCs). Graphical abstract: (Figure presented.). The Author(s) 2023. -
NorBlueNet: Hyperspectral imaging-based hybrid CNN-transformer model for non-destructive SSC analysis in Norwegian wild blueberries
Soluble solids content (SSC) is a vital parameter in blueberries, reflecting the concentration of dissolved sugars (primarily fructose and glucose) and directly influencing the fruit's sweetness, flavour, and ripeness. As part of this study, Norwegian wild blueberries were carefully hand-picked from a forest in Norway and subsequently imaged using a hyperspectral camera to capture their detailed spectral characteristics. This study introduces NorBlueNet, a hybrid CNN-transformer architecture, for accurately predicting SSC in wild blueberries through hyperspectral imaging and deep learning. This hybrid architecture combines CNN layers for local feature extraction and spatial hierarchy representation, followed by transformer layers that capture global relationships and long-range dependencies. The hybrid approach combines the computational advantages of CNNs with the advanced attention mechanisms of transformers, achieving enhanced accuracy while maintaining computational efficiency. A comprehensive evaluation is conducted by comparing the proposed model with two additional deep learning models on the custom dataset. The results indicate that the NorBlueNet achieves the highest prediction accuracy, with an R2 = 0.98, RMSE = 0.0136, and RPD = 9.3759 thereby demonstrating its superior performance. To foster community engagement, collaboration and facilitate re-implementation of our work, we have made our code available at:https://github.com/NorBlueNet. 2025 -
SS-CNN BruiseFinder: Hyperspectral imaging and CNN-driven spatial-spectral fusion for non-destructive plum bruise analysis
Plum fruit is susceptible to damage at various stages, from growth to packaging, and such bruising is often difficult to detect visually due to its subtle surface appearance. This research seeks to develop a convolutional neural network (CNN) model that leverages 3D convolutional layers to integrate spatial and spectral features from hyperspectral data, enabling accurate bruise analysis in plum fruit. In this study, plums sourced from a Norwegian fruit store were intentionally bruised and then imaged using hyperspectral technology at various time intervals (30 min to 48 h post-bruising). A novel CNN model, dubbed SS-CNN BruiseFinder, is developed to harness the spatial and spectral characteristics of these hyperspectral images for accurate bruise detection and classification. The SS-CNN BruiseFinder model demonstrates detection accuracy ranging from 68.5% to 91.5% and categorization accuracy between 67.39% and 98.16%. To further establish the effectiveness of this approach, three additional deep learning models a custom spectral CNN, ResNet 101, and a bidirectional LSTM model are developed and evaluated on the same dataset, providing a comprehensive validation of the proposed method's superiority. Timely detection of bruising helps prevent contaminated plums from entering the supply chain during transportation or storage. By categorizing plums based on bruise age, retailers can offer consumers more accurate freshness and quality information, enabling them to make better-informed purchasing choices and ultimately enhancing the overall shopping experience. To encourage community engagement and re-implementation, our code is available at https://github.com/SS-CNN BruiseFinder. 2025 Elsevier Ltd -
Dynamic linkage among crude oil, exchange rates and P/E ratio: The case of India /
International Journal of Pure And Applied Mathematics, Vol.119, Issue 18, pp.1-14, ISSN No: 1314-3395. -
Between home and enterprise: the Swakruta dilemma of scaling women entrepreneurs
Learning outcomes After completing the case study, the learners will be able to: Analyze how deep-rooted socio-cultural and family expectations create systemic barriers for small women entrepreneurs in India. Apply social identity theory to design interventions that reshape self-perception and entrepreneurial identity among Swakruta women entrepreneurs. Evaluate the influence of loss aversion on womens entrepreneurial decision-making and develop the nudging strategies to encourage women to engage with large opportunities. Case overview/synopsis This case explored the challenges faced by Manik Patwardhan, founder of Swakruta Charitable Trust, which supported over 200 small and marginal women entrepreneurs in Bengaluru. Despite training and opportunities provided, many women were hesitated to accept large, profitable orders due to socio-cultural norms and financial constraints. Using social identity theory, loss aversion and nudging, the case highlighted how strong family responsibilities and societal expectations influenced their cautious approach in scaling up their businesses. The women need to balance family responsibilities with business growth, which restricted their willingness to take risks. Their concerns ranged from balancing family duties and managing time, to addressing uncertainty by hiring staff other than family members, trust issues and difficulties in arranging upfront funds. Upon reviewing their response, Manik realised that these entrepreneurs were hesitant to accept a lucrative order. At this critical point, she had to decide whether to let the order go or encourage and nudge the women to seize a career-transforming opportunity, despite the risks involved. Accepting the order could boost earnings and reputation, but failure could harm the NGOs credibility, and declining the order could jeopardise future prospects. What should she do? Complexity academic level This case is designed for undergraduate and postgraduate courses in entrepreneurship, social entrepreneurship and related business disciplines such as behavioural economics. It focuses on the challenges and barriers faced by women entrepreneurs that limit their growth and ability to scale their businesses. Subject code CSS 3: Entrepreneurship. 2026 Emerald Publishing Limited -
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Microscopic, pharmacognostic and phytochemical screening of Epiphyllum oxypetalum (dc) haw leaves /
Journal of Pharmacognosy And Phytochemistry, Vol.7, Issue 6, pp.972-980, ISSN No: 2349-8234. -
Investigation on the phase transformation and lattice parameters of Sn2+, Cu2+, La3+ and Ce4+ ions doped titania: characterization and solar light activity study /
International Journal For Light And Electron Optics, Vol.183, pp.496-507, ISSN No: 0030-4026. -
FORMATION OF REDDY IDENTITY IN SOUTHERN KARNATAKA 1900-2000 CE
Reddy is the name of a socio-economically and politically dominant community found in Southern India. Today one of the largest single community grouping in south India in general and Andhra Pradesh in particular is Reddy community. They are generally considered traditional village headmen. They had a remarkable history since the period of shatavahanas of 2nd century BCE and the various people from this community have helped people in large way throughout the period and they are socially committed and economically enterprise. Historically the people of the Reddy community had appears some were very wealthy Landowners and Businessmen. Famous Kings, Awardees, Academics, Scientists & Civil Servants, Business Leaders & Entrepreneurs, famous Politicians, Entertainers & Film Professionals, Freedom Fighters, Activists & Philanthropists, Poets and Writers and many more. Though the community regarded their ancestors belongs Andhra Pradesh Telugu as their mother tongue, they assimilated with the regional culture of Karnataka and became proficient in Kannada language too. The community played major role in political arena and became one among the makers of modern Karnataka. Since 1900 their Political identity was expressed through political associations, Freedom movement, and backward class movement and pressurizing for establishment responsible government in Mysore region. Socially the community has been identified as an important caste in south India. The marriage ceremony is sanctified through the authorization of Brahmana, Dasayya. The community has the complex setup within itself because they are in large number. They have peculiar social practices of the appreciation of Brahmanical ideas and process of sankritization is rooted in the original beliefs of Reddy community, The Practice of bride price, widow remarriage, the Brahmin priest not invite to their marriage occasion by some sub castes and many more. The community extended its liberal attitude towards improving the status of women has resulted in arising of many women as industrialists, artists, scientists, physicians, realtors, sports persons and scholars. Economically they are committed to land and agriculture. Culturally the community has predominant followers of the Hinduism with Veerashaiva, Vaishnava and Shaktha sects as the most important faiths. Their annual pilgrimage is to the temple of Shrishaila Mallikarjuna. Yogi VemanaReddy and HemaReddy Mallama were as the legends. The Brahmanical idenitity is not observed and accepted by all denomination of Reddys. The ??Guru Paramapare also exists among the Reddy communities. Each sub caste has to pay their homage to their respective Gurus, who preside over the Matha. The festivals celebrated by the community like Bandi Devara Habba and Makkala Dyavaru are the most specific ones. It has to be accepted as liberation from some hierarchical control and assertion of a community attempting to carve a certain niche status which resulted in a form of monastic tradition or Gurupeeta tradition since the last two decade in Karnataka. Being the promoters of education and literature they established schools, colleges, training centers, hostels and study centers. They are socially advanced, economically developed, politically organized and culturally established. Thus they become influential factor in formation of social-political-economic identity in southern Karnataka. -
Recent trends in the transformative impact of biomass-derived carbon dots in biomedical science
Carbon dots (CDs) have gained significant attention from researchers due to their unique properties, which make them a promising option among nanomaterials for biomedical use. From recent trends, it is confirmed that CDs are the best candidates available among nanomaterials for the treatment of various diseases, including Ulcer, Diabetes, Gout, Wound healing and other syndromes. Semiconductor dots, which dominated in the early days, have been replaced by biomass-derived CDs (BCDs) due to their low toxicity, biocompatibility, and ease of synthesis. Although extensive research has been carried out on the applications of CDs in the biomedical field, the use of biomass as a precursor for CDs in therapeutic and clinical applications remains least explored and has not been systematically reviewed. This review primarily focuses on synthesis strategies, factors influencing the biomedical use of CDs, and recent research in therapeutic and clinical applications. In addition, the earlier trend of employing BCDs in bioimaging, biosensing, and molecular detection is also discussed. By examining the latest research developments, we provide a comprehensive overview of the progress and future prospects of BCDs in healthcare. This exploration highlights not only the potential of these sustainable nanomaterials but also their promise in enabling new breakthroughs in disease treatment. 2025 Elsevier Ltd. -
Spatial analysis of CO poisoning in high temperature polymer electrolyte membrane fuel cells
The improved tolerance of the High Temperature-Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) to CO allows the use of reformate as an anode feed. However, the presence of several per cent of CO in the reformate, which is inevitable particularly in on-board reformation in automobiles, which otherwise demands complex systems to keep the CO level very low, will significantly lower the cell performance, especially when the HT-PEMFC is operated at 160 C or below. In this study, a three-dimensional, non-isothermal numerical model is developed and applied to a single straight-channel HT-PEMFC geometry. The model is validated against the experimental data for a broad range of current densities at different CO concentration and operating temperatures. A significant spatial variation in current density distribution is observed in the membrane because the CO sorption is a spatially non-homogeneous process depending on local operating conditions and dilution of the H2 stream. To investigate the local spatial effects on HT-PEMFC operation, the model is applied to a real cell of size 49.4 cm2 with an 8-pass serpentine flow-field at the anode and the cathode. The membrane and anode catalyst layer are segmented into 5 array to investigate the spatial resolution of the polarization curves, H2 concentration, current density, and anode polarization loss. The simulation results show that the presence of CO in the anode feed reduces cell performance, however, the results reveal that uniformity in current density distribution in the membrane improves when the cell is operated in potentiostatic mode. The results are discussed in detail with the help of several line plots and multi-dimensional contours. The study also emphasizes on the importance of optimizing the reformate anode feed rate to improve cell performance. 2020 Hydrogen Energy Publications LLC -
Optimization of graded catalyst layer to enhance uniformity of current density and performance of high temperature-polymer electrolyte membrane fuel cell
The optimal use of catalyst materials is essential to improve the performance, durability and reduce the overall cost of the fuel cell. The present study is related to spatial distributions of current and overpotential for various graded catalyst structures in a high temperature-polymer electrolyte membrane fuel cell (HT-PEMFC). The effect of catalyst gradient across the catalytic layer (CL) thickness and along the channel and their combination on cell performance and catalyst utilization is investigated. The graded catalytic structure comprises two, three, or multiple layers of catalyst distribution. For a total cathode catalyst loading of 0.35 mg/cm2, higher loading near the membrane presents improved cell performance and catalyst utilization due to reduced limitations caused by oxygen and ion diffusions. However, non-uniformity in the current distribution is significantly increased. The increase in the catalyst loading along the reactant flow provides a substantially uniform current density but lower cell performance. The synergy of varying catalytic profiles across the CL thickness and along the cathode flow direction is investigated. The results emphasize the importance of a rational design of cathode structure and mathematical functions as a strategic tool for functional grading of a CL towards improved uniform current distribution and catalyst utilization. 2021 Hydrogen Energy Publications LLC -
Selective subset of relative density feature extraction algorithm for unconstrained single connected handwritten numeral recognition /
Australian Journal of Basic and Applied Sciences, Vol.8, Issue 6, pp.315-321, ISSN No: 1991-8178. -
Zone based relative density feature extraction algorithm for unconstrained handwritten numeral recognition /
Journal of Theoretical and Applied Information Technology, Vol.64, Issue 1, pp.304-314, ISSN No: 1992-8645 (Print), 1817-3195 (Online) -
EFFECT OF SECOND SOUND ON THE ONSET OF RAYLEIGH-B??NARD-MARANGONI MAGNETO CONVECTION
The effects resulting from the substitution of the classical Fourier law by the non-classical Maxwell-Cattaneo law in Rayleigh-B??nard-Marangoni convection in an electrically conducting Newtonian fluid are studied using the Galerkin technique. In the case of Rayleigh??B??nard convection, the eigenvalue is obtained for free-free, rigid-free and rigid-rigid velocity boundary combinations with isothermal and adiabatic boundaries. In the case of Marangoni and Rayleigh-B??nard-Marangoni convection the eigenvalues are obtained for an upper free / adiabatic and a lower rigid / isothermal boundaries. A linear stability analysis is performed. The influence of various parameters on the onset of convection has been analyzed. The classical approach predicts an infinite speed for the propagation of heat. The present non-classical theory involves a wave type heat transport (SECOND SOUND) and does not suffer from the physically unacceptable drawback of infinite heat propagation speed. It is found that the results are noteworthy at short times and the critical eigenvalues are less than the classical ones. -
An Empirical Analysis of Price Discovery in Spot and Futures Market of Gold in India
The broadest classification of the Indian financial market can be made in terms of commodity market, stock and security markets and foreign exchange market. Commodity markets are markets where raw or primary products are exchanged. These raw commodities are traded on regulated commodity exchanges, in which they are bought and sold in standardized contracts. Gold is a commodity which has been undergoing very serious price fluctuations in recent years. It has had its own impact on commodity trading too. Price discovery process of gold has always been a matter of wide discussion among researchers and policy makers. In this context this study aims at analyzing the price discovery process of Gold in Indian commodity market. It also looks into the volatility impact of futures price on spot price as well as the volatility impact of spot price on futures price. The study is completely based on the secondary data collected from the official website of NCDEX. The data extend for a period ranging from 23rd April 2009 to 29th December 2011. The daily data of spot and futures prices of gold during the period is taken into account. Various econometric tools are employed to test the hypotheses set. The VAR model result confirms the unidirectional relationship runs from the spot market to the futures market of gold in India. It reveals co integration and dynamic relationship between spot and futures markets of gold. The result of GARCH model implies that both futures as well as spot markets do have significant impact in the price volatility of gold in India. The result of VECM tells that spot market is dominant in the price discovery process which is a clear indication of the fact that spot market of gold is information efficient in India. The result is of great significance for the investors who wish to improve portfolio performance. With regard to policy making, a better understanding of the interconnectedness of these markets would be useful for the policy makers who coordinate the stability of financial markets. For marketers, it provides a reliable forecast of spot prices in the future to allow them to effectively manage their risks in the production or marketing process. The unprecedented uptrend in the price of gold and high volatility in recent years provides room for some important social implications. -
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