Higher Colleges of Technology

Rice, the staple food for more than half of the world’s population, is predominantly consumed in polished form, which lacks essential micronutrients and contributes to hidden hunger. This review examines biofortification and functional rice development as sustainable methods to improve the nutritional and health-enhancing attributes of rice. Evidence from conventional breeding, genetic engineering, agricultural practices, and microbiological interventions is consolidated, focusing on the biofortification of iron, zinc, and vitamin A. Functional rice enriched with anthocyanins, resistant starch, proteins, and prebiotic or probiotic traits is also discussed, alongside nutrient bioavailability and the influence of processing methods such as fermentation, germination, and parboiling. Findings indicate that biofortified rice can helps mitigate micronutrient deficiencies, while functional rice provides additional advantages for the management of diabetes, cardiovascular disease, and gastrointestinal health. Nonetheless, challenges persist, particularly in nutrient absorption, regulatory approval, and consumer acceptance. Current evidence is restricted by insufficient biomarkers, contradictory findings in zinc studies, and an absence of long-term intervention trials, underscoring the need for further research and socio-economic integration.

Purpose This study examines how digital platforms (DPs) can drive social sustainability (SS) by influencing user behaviour in the context of sustainable mobility. While DPs have been widely discussed for economic and environmental outcomes, their role in fostering SS through user engagement remains underexplored. Design/methodology/approach A behavioural model was developed by integrating the Theory of Planned Behaviour (TPB), Technology Acceptance Model (TAM) and Equity Theory. This study used a time-lagged survey of 406 users of a DP for SS based in a major city in central in India, which incentivises responsible traffic behaviour. Confirmatory factor analysis was employed to validate the measurement model, and ridge regression was used to test the proposed hypotheses. Findings Attitude, captured through belief- and affect-based evaluations of social responsibility, along with perceived ease of use and effort fairness, significantly predicted intention to use the platform. Social norms were non-significant, suggesting that normative pressure plays a limited role in this mobility setting. Intention, in turn, predicted socially sustainable mobility behaviour. Overall, the results show that users respond more strongly to their own perceptions, usability and fairness than to social expectations, emphasising the personal agentic role of DPs in supporting socially sustainable practices. Research limitations/implications This study opens new pathways for platforms and sustainability research by demonstrating how user engagement can facilitate socially sustainable behaviours through incentivisation, It encourages scholars to expand behavioural models beyond traditional constructs by incorporating perceived fairness, emotional alignment and usability in the digital context. Although limited to one platform and cultural setting, the findings provide a replicable model for exploring user behaviour in digital ecosystems. Future research should adopt longitudinal and cross-cultural designs to assess habit formation, test the framework in varied policy environments and examine how DPs can be co-designed with communities to embed SS into everyday mobility behaviours. Practical implications DPs aiming to promote socially sustainable mobility must go beyond superficial incentives. Designing user engagement strategies that align with individuals’ beliefs and emotions around social responsibility can strengthen behavioural intention. Platforms should ensure that rewards are perceived as fair and proportional to effort, and streamline ease of use to reduce participation barriers. Public–private collaborations can integrate such platforms into mobility governance, using data-driven, user-centred design to complement weak institutional enforcement. By embedding sustainability into everyday interactions, DPs can become powerful tools for shaping long-term, pro-social behaviours in transport and beyond. Social implications This study emphasises the role of DPs as enablers of socially sustainable behaviour. By linking individual actions to collective outcomes through incentives, platforms can foster safer, more equitable mobility systems. The findings highlight the importance of fairness, accessibility and emotional engagement in driving participation, suggesting that digital interventions can build civic responsibility from the ground up. As platforms increasingly mediate everyday life, their design choices hold significant social power, shaping norms, enabling inclusive participation and addressing systemic gaps in public governance and infrastructure through bottom-up engagement. Originality/value The study develops and tests a behavioural framework based on the TPB-TAM-Equity theory in the often-overlooked dimension of SS. The study incorporates the personal agentic role of DPs in influencing SS behaviour in the specific context of sustainable mobility. It goes on to identify drivers of SS behaviour and how designing DPs for SS can use these to address systemic social issues like road safety. The findings enrich platform, behavioural and sustainability literature, and point to practical strategies for DPs.

Abstract Decentralized blockchain oracles are critical for bridging on-chain smart contracts with off-chain real-world data. However, existing reputation systems often rely on static cumulative profiling, leading to a phenomenon we define as Reputation Inertia. In this state, an oracle's accumulated historical honesty acts as a buffer that masks potential malicious behavior (Whitewashing attacks). It simultaneously fails to account for benign disagreement during market volatility (Flash Crash scenarios). To address this dilemma, this paper proposes a novel graph-based profiling mechanism utilizing an Adaptive Exponential Weighted Moving Average (AEWMA). Unlike typical static models, our approach introduces a Dynamic Trust Decay factor that regulates the weight of historical reputation based on real-time network volatility. This allows the system to act in a highly sensitive manner to deviations during stable market conditions in order to rapidly detect sleeper cells, whilst also dampening penalty mechanisms during high-volatility events to prevent false positives. We provide a complete Solidity smart contract implementation demonstrating the on-chain feasibility of the AEWMA mechanism with $O(1)$ storage per edge. We validated the proposed method through discrete-event simulations using historical cryptocurrency market data. Experimental results demonstrate that our dynamic approach reduces the Time-to-Detection (TtD) for whitewashing attacks by approximately \textbf{81\%} compared to static baseline (from 9.0 to 1.7 rounds). It also maintained a False Positive Rate (FPR) of near \textbf{0.4\%} even under extreme volatility conditions ($5\times$ standard deviation), compared to 7.1\% for the static approach. These findings suggest that volatility-aware profiling significantly enhances the security and incentive compatibility of decentralized oracle networks.

Purpose The use of service-oriented artificial intelligence-powered virtual agents (VAs) in higher education is expanding, particularly in academic advising. However, their adoption is hindered by challenges such as a lack of transparency, trust, system capability and organisational readiness. This study aims to investigate the factors influencing students’ behavioural intention to adopt academic advising VAs in Higher education. Design/methodology/approach This study applies an extended Fit–Viability Model (FVM) to investigate the fit requirements and viability of the advising VA system. The model incorporates perceived risk as a key predictor and examines the moderating role of demographic variables for this model. Survey data were collected from 239 students and analysed using partial least squares structural equation modelling to test the extended FVM framework. Findings The findings showed that both perceived fit and perceived risk significantly impact students’ behavioural intention to use advising VAs. Moreover, the study revealed that gender influences the relationship between risk and student intention, highlighting demographic influences on adoption. Practical implications This study provides practical implications for academic institutions seeking to enhance student adoption of advising VAs by addressing system fit and risk concerns. Theoretically, it contributes to adoption research by extending the FVM model with risk considerations and demographic moderators, offering a more comprehensive framework for future studies. Originality/value Unlike prior academic advising studies that rely primarily on acceptance-based models, this study extends the FVM by incorporating perceived risk and demographic moderators.

Aerodynamic drag is a dominant factor affecting the efficiency and driving range of electric trucks, especially at high speeds. Although previous studies have mainly focused on external drag-reduction devices, internal airflow control strategies such as integrated ducts have received limited attention. This study addresses that gap by analyzing how placing an internal duct in the truck body affects drag and power efficiency. A simplified two-dimensional computational fluid dynamics (CFD) approach was employed using ANSYS Fluent to evaluate and compare a baseline truck model and a modified configuration featuring a central internal duct. The simulations assessed the drag coefficient, drag force, propulsion power, and energy consumption over a wide range of inlet velocities (50–140 km/h). The results show that the ducted configuration consistently outperforms the baseline model, achieving up to a 7.5% reduction in drag force, 7.53% savings in energy consumption per kilometer, and an 8.2% extension in driving range at 140 km/h. These findings confirm the aerodynamic and energy-saving potential of internal ducting as a passive design strategy for heavy-duty electric vehicles.

Food security is highly reliant on agricultural activity to drive the world economy. However, this activity is in great danger due to climatic changes and improper use of irrigation techniques. Consequently, the lives of numerous individuals worldwide are in jeopardy. In light, this paper investigates the promise of smart irrigation systems based on new technology. To meet the growing demand for water in agriculture, this study presents an intelligent irrigation system that uses cutting-edge technologies of (1) cloud computing, (2) embedded systems, and (3) Internet-of- Things (IoT). The main objective is to demonstrate how this innovative strategy can effectively manage water resources, supporting food security through cutting-edge agricultural technology. This paper proposes a smart irrigation system based on cutting-edge technologies like the embedded system, Internet of Things (IoT), and cloud computing as a groundbreaking strategy to improve food security through the implementation of advanced agricultural technology. This system supervises real-time monitoring of crucial environmental factors such as (1) moisture, (2) humidity, (3) temperature, and (4) water levels, in smart agriculture practices. In addition, this system employs the latest sensors, including the module (DHT22), water level sensor, and moisture sensors, which are connected to the widely used embedded system (ESP32). The system uses the ThingSpeak cloud and ThingView app to enable wireless communication between the device and the farm owner, enhancing their interaction. The automated control of the two water pumps is based on the readings of various environmental factors. Moreover, this will also present a mathematical-driven function known as linear interpolation to calibrate the water level sensor in percentage. This system was created using the V-model software development approach. and conclusion. Farmers can access comprehensive farm data from anywhere in the world as the sensor data is transmitted in real-time to both the ThingSpeak cloud and the ThingView. This capability allows for more precise crop irrigation and increased production. The study’s findings demonstrate a striking 70% reduction in water consumption for soil irrigation when utilizing the proposed smart irrigation system. This paper underscores the significant promise of smart irrigation systems, driven by IoT, embedded systems, and cloud computing, to conserve water resources and advance food security. This article proposes an innovative solution that reduces soil irrigation water consumption by 70% compared to traditional methods. It explores how smart irrigation can improve the sustainability of agriculture and positively influence food security.

This study examines how innovation capacity influences market performance among small and medium enterprises (SMEs) in the UAE and offers both theoretical and practical contributions. Data from 133 SMEs were analyzed using Structural Equation Modeling to assess the effects of five innovation dimensions, namely knowledge management, creativity, collaboration (COL), leadership, and organizational learning (OL), on quick response (QR), product differentiation (PDIF), and market share. The results show that OL and COL play central roles in strengthening SMEs’ ability to respond quickly to customer and market requirements, as well as supporting greater PDIF. Practically, the findings assist SMEs in leveraging innovation capabilities to enhance competitiveness and sustain growth in dynamic market environments. The analysis proceeded in three stages. First, correlation analysis explored relationships among the five innovation capacity dimensions and the three performance indicators. Second, the relationships between QR, PDIF, and overall market performance were examined. Third, the influence of the innovation capacity dimensions on the performance variables was tested. Model fit was evaluated using maximum likelihood estimates and standard fit indices (Chi-square, Goodness-of-Fit Index, Adjusted GFI, Normed Fit Index, Relative Fit Index, Incremental Fit Index, Tucker–Lewis Index, Comparative Fit Index, and the Root Mean Square Error of Approximation). The model results confirm the adequacy of the proposed framework.

IntroductionThe anticipated rise in dementia cases across the Middle East and North Africa (MENA) region, particularly the staggering 1795% projected increase in the United Arab Emirates by 2050, underscores an urgent need for community-based training for informal caregivers and professional training for formal caregivers. This scoping review mapped the evidence on dementia caregiving training for informal and formal caregivers in this region.MethodsThe Joanna Briggs Institute methodology for scoping reviews was adopted. Four electronic databases were searched from inception to April 2025. Two authors independently screened and extracted data. The PAGER framework was employed to collate and critique the findings, identify advances and gaps, discuss evidence for practice, and suggest recommendations for practice and research.ResultsTen included studies reported training for informal caregivers, including educational programs (n = 5) and psychosocial trainings (n = 7) (i.e., psychoeducation, counselling and psychotherapy, multicomponent interventions, and miscellaneous interventions). Only two included studies reported training (i.e., educational program) for formal caregivers. There appeared to be a scarcity of evidence on dementia caregiving training for informal and formal caregivers in the MENA region, and the training was skewed toward educational programs. The evaluations focused on a deficit-based perspective (i.e., burden and stress, depressive symptoms, and anxiety) that primarily focused on the caregivers.DiscussionThe findings provided insights into dementia caregiving training for informal and formal caregivers in the MENA region. Further research on systematic reviews to evaluate overall training effectiveness is warranted. Additionally, studies evaluating culturally relevant psychosocial interventions, particularly those focus on strength-based outcomes (e.g., positive aspects of caregiving, caregiving confidence, and social support) to inform practice, are highly recommended. Furthermore, validation of region-specific measurement tools should be a priority.Systematic review registrationhttps://doi.org/10.17605/OSF.IO/UA9E3