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Driving better health outcomes for gig workers through strategic health initiatives
The gig economy offers flexibility and autonomy to workers but also presents significant challenges related to health and well-being, especially for delivery professionals who face irregular hours, physical strain, and limited access to healthcare. Immersive technologies, such as virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), present innovative solutions to bridge these gaps. However, gig workers' adoption of these technologies remains underexplored. This paper applied the diffusion of innovation (DOI) theory to analyse the adoption patterns of immersive technologies within the gig economy and identified barriers, such as digital literacy and cost, alongside facilitators, like perceived usefulness and ease of integration. The paper provides insights into how these technologies can be effectively implemented in the gig workforce. The study highlights the role of platform policies and the broader regulatory landscape in shaping technology adoption, offering valuable recommendations for policymakers and technology developers. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Driving customer brand engagement through augmented reality-induced influencer content among Gen Z: The moderating role of credibility
The present study investigates the impact of Augmented reality-induced influencer content moderated by the influencers credibility, steering to word of mouth trailed by purchase intentions of Gen Z in the fashion industry. This study employs a conceptual model grounded on the theory of social power and the S-O-R model with the moderating role of credibility. Data was gathered from 423 samples. To test the dimensionality of Augmented reality-induced influencer content, exploratory factor analysis with principal component analysis and Varimax orthogonal rotation was adopted. SPSS version 22.0 and AMOS version 20 were used for data analysis. The studys findings indicate that following influencers generates favorable brand effects, such as increased social power and higher purchase intentions, by fostering familiarity and internalizing behavioral intents. Credibility is vital in influencing views and promoting electronic word-of-mouth through interactions between audiences and influencers. Brands have significant chances to engage Generation Z with genuine content by utilizing influencer marketing facilitated by augmented reality. Therefore, the study concludes that Augmented reality-induced influencer content encourages consumers to engage actively and positively drives them toward brand outcomes. 2025 Korean Scholars of Marketing Science. -
Driving Financial Inclusion: Technology as an Indicator of Financial Ecosystem Development During the COVID-19 Pandemic in India
This paper examines Indias level of digital access to financial services as compared to other Asian countries. The study also intends to analyse whether COVID-19 has influenced the usage trend of the selected digital payment indicators in India. Data has been collected from the World Bank Global Findex Database and RBI bulletins. Cross country descriptive analysis was used for studying Indias digital financial access against the other Asian countries. Event study methodology followed by trend analysis was employed to examine whether COVID-19 has impacted the digital payment indicators usage in India. The findings of the study indicated that Indias position in digital financial access needs to be improved. It was further identified that COVID-19 has increased the usage of digital modes for financial transactions in India. There has been a significant increase in the usage volume of mobile banking after the declaration of the pandemic. Govt. can frame its action plans to make use of the opportunity created through the pandemic to improve digital financial access in India. 2022 IGI Global. All rights reserved. -
Driving profitable business growth through economical optimization, energy management, and industrial 5.0 innovations
The chapter emphasizes the significance of economic optimization, energy efficiency, and Industrial 5.0 innovations in driving sustainable growth and profitability in today's business landscape. It highlights the strategic allocation of resources to maximize efficiency and minimize costs, using lean management principles, automation, and data analytics. Energy management is crucial for reducing operational costs and mitigating environmental impact, using renewable energy sources and smart technologies. Industrial 5.0, a new era of industrial transformation, combines automation, connectivity, and data exchange, with technologies like artificial intelligence, IoT, and blockchain. 2024, IGI Global. -
Driving purchase intentions through visual storytelling: a study of social media platform reels sponsored advertising
This study explores how social media platforms (for example, Instagram) and Reels-sponsored ads influence what makes consumers stop, watch and decide to buy. Using Consumer Engagement Theory (CET) as a lens, it looks at how people emotionally, cognitively and behaviourally respond to short-form video content. Four key factors were examined: engaging content, scenario-based experiences, user participation and perceived usefulness. Data from 393 active social media platform users in Indias National Capital Region revealed that all four elements positively shaped consumer attitudes, significantly influencing purchase intentions. Notably, relatable and emotionally engaging content had the most substantial impact. Attitude played a central role, bridging how consumers feel about a Reel and what they choose to do next. For marketers, the takeaway is clear: Reels that are visually appealing, useful and invite interaction are more likely to turn engagement into action. The study offers timely insights into how brands can connect meaningfully through short-form video. 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Driving sustainable development through climate finance in India: A case study of the National Clean Energy Fund (NCEF)
This case study examines the national clean energy fund (NCEF) as a climate finance policy in India. The NCEF was established with the objective of promoting renewable energy projects and sustainable development in the country. The study explores the background and context of climate finance, providing an overview of the NCEF's goals and implementation. The case study analyzes the impact of the NCEF by examining its funding allocations and utilization over the years. It highlights the challenges faced in effectively utilizing the funds, such as administrative hurdles, limited capacity, policy uncertainties, project development barriers, financial constraints, and governance issues. Furthermore, the case study discusses the socio-economic impacts of the NCEF, including job creation, clean energy adoption, and environmental benefits. It also explores the lessons learned from the NCEF implementation, identifying areas for improvement and providing recommendations for enhancing climate finance mechanisms in India. This chapter creates a contribution to renewable energy development in India. 2023, IGI Global. All rights reserved. -
Drone Surveillance: Ethical Considerations for a Sustainable Future
The evolution of drones underlines the 20th-century scientific and technological progress. They evolved within the military context and remained within that circle for almost a century. The 21st century has increased the possibilities and opportunities of drones by incorporating Artificial Intelligence and machine learning technologies. Accordingly, drones are widely used in almost all fields of human inter-action. Among them, the use of drones for surveillance stands out due to its advantages and potential risks. The built-in cameras of the automated drones used not only by law enforcement agencies but also by private actors can collect personal information, raising serious ethical concerns. Although drone surveillance is beneficial to society, as it can restrict illegal activities and violations of human rights, it poses apprehensions concerning the privacy and security of people. From this perspective, this chapter examines the vital ethical considerations essential for realizing a sustainable future while using the method of drone surveillance. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Drones for Crop Monitoring and Analysis
Drones are becoming a vital tool for crop monitoring and analysis in contemporary agriculture. With the use of sophisticated sensors, these unmanned aerial vehicles (UAVs) can gather high-resolution pictures and data, giving farmers real-time insights into the growth and health of their crops. Thanks to technological advancements, drones can now more reliably and effectively collect a variety of data points than previous techniques, including plant health, moisture levels, and insect infestations. Drones are a useful tool for crop monitoring because they enable farmers to identify problems early on, such as nutrient deficits, water stress, and disease outbreaks, and take prompt action to optimize yields and avoid losses. Drones can also swiftly and affordably cover vast tracts of agriculture, giving a thorough picture of crop conditions. Farmers may use the information that drones gather to make educated decisions by choices about fertilization plans, pest control techniques, and irrigation schedules, eventually enhancing crop sustainability and output. Drone technology is projected to play an increasingly bigger role in agriculture as it develops, completely changing how farmers monitor and assess their crops. (Publisher name) (publishing year) all right reserved. -
Drones for Transportation Logistics and Disaster Management
Explore the future of logistics and disaster management with this essential guide to the design, applications, and challenges of integrating advanced drone technology into intelligent transportation systems. Drones are quickly becoming an essential technology for navigating inaccessible areas, especially during emergency situations. However, the implementation of these drones requires strict standards, policies, and procedures. Currently, drones are being used in several industrial and service sectors, extending the possibilities of handling transportation and logistics. The future of transportation is based on unmanned vehicles, and it is important to identify their challenges and futuristic applications. Drones for Transportation Logistics and Disaster Management introduces the essential aspects of the technological advancement of drones, the challenges faced in current practices, and their advanced applications. The book describes future intelligent and resilient transportation systems backed by the Internet of Vehicle Things, the problems of big data analytics, and optimization techniques for in-house supply-chain management. Using a global multi-sector perspective, this volume will comprehensively cover essential components of drone systems, including their modeling, design, and maintenance, making it an essential guide for anyone looking to the future of disaster management. 2026 Scrivener Publishing LLC. -
DROUGHT MITIGATION THROUGH HYDROGEL APPLICATION IN RICE (Oryza sativa L.) CULTIVATION
Sustainability in irrigation is an essential step towards responsible water consumption. In recent years, many studies have sketched climate-resilient agricultural practices to fight drought and uncertain rainfall patterns. Major rain-fed crops such as paddy and wheat require aid when there are abnormal dry spells. To mitigate the loss of crops from such events, superabsorbent polymers can be used. Soils amended with hydrogel or Superabsorbent polymer (SAP) retain moisture during drought to prevent loss of water through evaporation and percolation. This allows the crop to grow with less shock from drought. This study compares rice (Oryza sativa L.) growth rate under application (treatment groups) and non-application (control groups) of hydrogel, considering their high-water requirement. NDLR07 (recently developed) and BPT5204 (local variety) rice varieties were chosen for the current study. Randomized controlled trials were performed for each variety on a control group (NC & BC) and 3 treatment groups with 20% (NT20 & BT20), 40% (NT40 & BT40), and 60% (NT60 & BT60) deficit water supplies respectively. N, T, C refers to seed type, treatment group, control group respectively. Intermittent drought condition was imposed for 14 days to assess the resilience of crops. The water retention capacity of the sandy loam soil was better for treatment groups by 20% than control groups even at an average temperature of 40 ?. Treatment groups continued growing through the drought phase and after, while control groups showed stagnation. Among the tested treatment groups, NT20 had the highest growth among all trials. The results of the study suggested that hydrogel application can help to combat droughts and thereby contribute to sustainable agricultural production by restricting the involvement of climate changes. 2021, Editorial board of Journal of Experimental Biology and Agricultural Sciences. All rights reserved. -
Drought PredictionA Comparative Analysis of Supervised Machine Learning Techniques
Drought is a natural phenomenon that puts many lives at risk. Over the last decades, the suicide rate of farmers in the agriculture sector has increased due to drought. Water shortage affects 40% of the world's population and is not to be taken lightly. Therefore, prediction of drought places a significant role in saving millions of lives on this planet. In this research work, six different supervised machine learning (SML) models namely support vector machine (SVM), K-nearest neighbor (KNN), decision tree (DT), convolutional neural networks (CNNs), long short-term memory (LSTM), and recurrent neural networks (RNNs) are compared and analyzed. Three dimensionality reduction techniques principal component analysis (PCA), linear discriminant analysis (LDA), and random forest (RF) are applied to enhance the performance of the SML models. During the experimental process, it is observed that RNN model yielded better accuracy of 88.97% with 11.26% performance enhancement using RF dimensionality reduction technique. The dataset has been modeled using RNN in such a way that each pattern is reliant on the preceding ones. Despite the greater dataset, the RNN model size did not expand, and the weights are observed to be shared between time steps. RNN also employed its internal memory to process the arbitrary series of inputs, which helped it outperform other SML models. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Dry Sliding Friction and Wear Performance of HVOF Sprayed WCCo Coatings Deposited on Aluminium Alloy
The tribological behaviour of WCCo Cermet coatings coated on Al6061 alloy was studied in this work. WCCo Cermet coatings have been coated with different thicknesses by changing the amount of the cobalt using HVOF (High velocity oxy fuel technique). The coatings produced have been subjected to microhardness, friction and wear testing. A disc and pin type machine has been used for assessing friction and wears characteristics. The influence on tribological performance of coating thickness and cobalt levels was examined and compared with aluminium alloy. WCCo coating enhanced hardness by 34% and 42% in 100 and 200 micron thicknesses respectively, compared to aluminium alloy. The wear rate and the coefficient of friction are decreased by 48 and 12%, respectively, compared to uncoated aluminium alloy. Both coatings and substrates increase their wear rate and friction coefficient (COF) with the increase in load and sliding speed. Scanning Electron and Confocal microscopy examinations of worn surfaces were carried out to evaluate coating wear processes. 2021, The Institution of Engineers (India). -
DTDO: Driving Training Development Optimization enabled deep learning approach for brain tumour classification using MRI
A brain tumour is an abnormal mass of tissue. Brain tumours vary in size, from tiny to large. Moreover, they display variations in location, shape, and size, which add complexity to their detection. The accurate delineation of tumour regions poses a challenge due to their irregular boundaries. In this research, these issues are overcome by introducing the DTDO-ZFNet for detection of brain tumour. The input Magnetic Resonance Imaging (MRI) image is fed to the pre-processing stage. Tumour areas are segmented by utilizing SegNet in which the factors of SegNet are biased using DTDO. The image augmentation is carried out using eminent techniques, such as geometric transformation and colour space transformation. Here, features such as GIST descriptor, PCA-NGIST, statistical feature and Haralick features, SLBT feature, and CNN features are extricated. Finally, the categorization of the tumour is accomplished based on ZFNet, which is trained by utilizing DTDO. The devised DTDO is a consolidation of DTBO and CDDO. The comparison of proposed DTDO-ZFNet with the existing methods, which results in highest accuracy of 0.944, a positive predictive value (PPV) of 0.936, a true positive rate (TPR) of 0.939, a negative predictive value (NPV) of 0.937, and a minimal false-negative rate (FNR) of 0.061%. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Dual drug co-encapsulation of bevacizumab and pemetrexed clocked polymeric nanoparticles improves antiproliferative activity and apoptosis induction in liver cancer cells
Nanoparticle (NP) enabled approaches have been employed for chemotherapeutic administration due to their capacity to regulate drug release and reduce side effects. Additionally, these methods can use several drugs concurrently and impede the proliferation of cancer cells that have developed resistance. Bevacizumab (BVZ) and pemetrexed (PEM) have demonstrated encouraging outcomes in the treatment and management of cancer. This work investigates the combined antiproliferative efficacy of BVZ and PEM co-loaded PLGA-PEG NPs (BVZ/PEM@PLGA-PEG NPs) against HepG2 liver cancerous cells. The BVZ/PEM@PLGA-PEG exhibited a sphere-shaped and consistent nanosized distribution. In addition, we evaluated the potential mechanisms for inhibiting cell growth and inducing apoptosis using DAPI staining and cell cycle study. The beneficial combined antiproliferative activity and the apoptosis pathway were detected in the HepG2 cells exposed to BVZ/PEM@PLGA-PEG NPs. Our study determined that the combinational drug treatment of BVZ/PEM@PLGA-PEG NPs has a significant effect on promoting the effectiveness of liver cancer treatment. 2024 Wiley Periodicals LLC. -
Dual ion specific electrochemical sensor using aminothiazole-engineered carbon quantum dots
A novel electrochemical sensor capable of concurrently detecting Pb2+ and Hg2+ ions has been innovatively engineered. This sensor utilizes the anodic stripping voltammetry technique (ASV) with a composite consisting of carbon quantum dots and aminothiazole (CQD-AT). In this composite, both the carbon quantum dots and aminothiazole contribute significantly to the electroactive surface area, boasting an abundance of functional groups that include oxygen and nitrogen atoms. These functional groups serve as active sites that enhance sensor sensitivity by facilitating the electrostatic interaction-based adsorption of heavy metal ions. Aminothiazole surface is evenly covered with CQDs, which are essential for metal gets reoxidized into metal ions for stripping analysis. Due to this unique modification, the Pb2+ and Hg2+ electrochemical sensor using the CQD-AT composite coated on carbon fiber paper electrode (CQD-AT/CFP) exhibits superior analysis performance such as wide linear range (0.6 1011160 106 M) for Pb2+ and Hg2+ with a limit of detection (LOD) of 3.0 pM and 6.2 pM for Pb2+ and Hg2+. CQD-AT/CFP modified electrode can be considered as a potential material for electrochemical simultaneous determination of Pb2+ and Hg2+ in different water samples. 2023 Elsevier B.V. -
Dual ion-imprinted chitosan-stabilized platinum nanoparticles for simultaneous electrochemical detection of Cd2? and Pb2? in water samples
The development of highly selective and ultrasensitive electrochemical sensors for trace-level heavy metal monitoring remains a critical challenge in environmental analysis. In this work, a novel dual ion-imprinted, chitosan-stabilized platinum nanoparticle (PtNP)modified glassy carbon electrode (GCE) is reported for the simultaneous electrochemical detection of Cd2? and Pb2? in aqueous media. The synthesized PtNPs provide a large electroactive surface area and are uniformly stabilized within a chitosan matrix enriched with oxygen- and nitrogen-containing functional groups, which act as selective coordination sites for target metal ions. The incorporation of dual ion-imprinting generates specific recognition cavities that promote selective adsorption of Cd2? and Pb2? through electrostatic and coordination interactions, leading to significantly enhanced sensitivity and selectivity. Under optimized conditions, the sensor exhibits wide linear detection ranges of 44.04pM0.18nM for Pb2? and 79.4pM0.18nM for Cd2?, with remarkably low detection limits of 13.2pM and 23.83pM, respectively. The proposed sensing platform demonstrates excellent anti-interference capability and reliable performance in real water samples, confirming its applicability for practical environmental monitoring. This study highlights the synergistic effect of dual ion-imprinting and chitosan-stabilized PtNPs, offering a robust and efficient strategy for multi-ion electrochemical sensing of toxic heavy metals. The Author(s), under exclusive licence to Springer Nature B.V. 2026. -
Dual purpose behavior of Ni-PTC MOF for high performance supercapacitor and water splitting applications
Metal-organic frameworks (MOFs) have elicited significant interest as next-generation materials for storing and converting energy, owing to their structural versatility and tunable physicochemical properties. In the present work, a nickel-based MOF, referred to as Ni-PTC, was synthesized via a straightforward method and explored for its dual functionality as a supercapacitor electrode and an electrocatalyst for overall water splitting. Structural and morphological analyses confirmed the materials high surface area, hierarchical porosity, and excellent crystallinity. As a supercapacitor electrode, Ni-PTC delivered a high specific capacitance of 953.86 F g?1 at 1 A g?1 and demonstrated superior cycling durability, retaining 92 % of its initial capacitance after 5000 cycles. Its electrocatalytic performance was assessed for both hydrogen (HER) and oxygen evolution reactions (OER), exhibiting overpotentials of 241 mV and 400 mV, respectively, at a current density of 10 mA cm?2. The catalyst also showed excellent operational stability, underscoring its potential in energy-related applications. 2026 Elsevier B.V. -
Dual solutions for unsteady stagnation-point flow of prandtl nanofluid past a stretching/shrinking plate
Dual solutions for the time-dependent flow of a Prandtl fluid containing nanoparticles along a stretching/shrinking surface are presented. The nano Prandtl fluid fills the porous stretching/shrinking surface. The Buongiorno model is employed by accounting Brownian motion and thermophoresis slip mechanisms in the analysis. The relevant nonlinear problem is treated numerically via Runge-Kutta-Fehlberg scheme. The flow profiles are scrutinized with respect to the different governing parameters. Results of this study indicate that the temperature boundary layer thickness increased due to the influence of nanoparticles. 2018 Trans Tech Publications, Switzerland. -
Dual strategy for enhanced photocatalytic degradation of tetracycline: Phosphorus doping and cobalt boride co-catalyst loading on g-C3N4
Despite being promising for the removal of ever-growing pharmaceutical contamination from water, the g-C3N4 photocatalyst still faces roadblocks to implementation due to its intrinsic properties, for example, the limited visible light absorption, reduced charge separation capacity, and low mobility of photo-excited electrons. Doping with non-metals and loading with the co-catalyst is an effective approach to overcome the abovementioned limitations for the g-C3N4 photocatalyst. Herein, both these strategies are integrated in cobalt-boride loaded on phosphorous-doped g-C3N4 (CoB/P-g-C3N4) by facile chemical fabrication routes. Detailed morphological, structural, chemical, and spectroscopic analyses demonstrated that phosphorus doping effectively reduces the bandgap of g-C3N4 to absorb more visible light. Uniformly distributed CoB-nanoparticles create local Schottky barriers that trap photo-generated electrons from g-C3N4 to suppress charge carrier recombination. The optimized CoB/P-g-C3N4 photocatalyst produces ~35 times higher degradation rate constant than the pristine g-C3N4 for the photocatalytic removal of tetracycline antibiotics from water under visible light irradiation. Combining these advantageous features with cost-effective and stable elements, CoB/P-g-C3N4 offers an optimal solution for tuning the intrinsic electronic structure and surface reactivity of g-C3N4, making it highly effective for various photocatalytic applications. 2025 Elsevier Ltd