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Oxygen surface-functionalized carbon dots derived from waste cassava peel for UV shielding applications
UV radiation, falling in the wavelength range between 290nm and 400nm, which reaches the Earth's surface, is capable of causing potential damage to human cells, especially the skin. Sun protection products, which were earlier treated as skincare utilities, have now become indispensable and fall under the category of healthcare commodities. The requirement for skin- and environment-friendly UV absorbers that are reliable enough to substitute synthetic ones is spiking day by day. In this work, we report the conversion of waste cassava peels into UV-absorbing carbon dots through a facile one-step microwave-assisted solvothermal route. The as-synthesized carbon dots, when dispersed in NMP, show intense absorption in the UVA and UVB region, which can be effectively used for UV shielding applications. In-vitro studies based on transmittance data show that dispersion is capable of blocking 90% of the UV rays at a concentration of 0.2mg/mL, and at 0.5mg/mL, an SPF of 35+ was obtained, corresponding to a shielding capability of more than 97%. The conversion of cassava peel waste into UV-absorbing carbon dots adds to the value of this agricultural waste and, on crossing the compatibility standards, would provide a suitable alternative for existing synthetic UV shielding materials. 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Modulating Electrochemical Energy Storage Properties of Cassava Peel-Derived Carbon Dots Via Solvent Engineering
Despite their small size, constrained within a few nanometers, Carbon dots, the tiny 0D materials, have the potential to revolutionize the realm of materials, design, and technology. The elemental composition of carbon dots, more specifically, the non-carbon elements forming functional groups, has crucial roles in determining the structure and properties, opening a wide scope for tailoring through compositional engineering. In this work, tuned carbon dots derived from waste Cassava peel, synthesized by applying solvent engineering strategy in facile single-step microwave-assisted solvothermal treatment, are reported. The proportion of charge accumulation mechanisms is found to be highly dependent on the elemental composition of oxygen and nitrogen in the carbon dots, evidencing the pivotal role of functional groups. Among the carbon dots synthesized using three different solvents. Ethylenediamine based ones show highest energy storage capability (114.57Fg?1 at 0.1Ag?1) owing to nitrogen-oxygen co-functionalization. Though these carbon dots have low storage capabilities as such, they have potential prospects to be incorporated into electrode materials to tune charge storage mechanisms desirably, often with the added advantage of enhanced stability and performance. Additionally, the redox properties exhibited by the tuned samples give promising prospects toward applications like electrochemical sensing and electrolyte engineering for energy storage. 2025 Wiley-VCH GmbH. -
Nitrogen-Oxygen Co-Functionalized Waste Cassava Peel-Derived Carbon Dots for White Led
White light emitting diodes (WLEDs)are most sought after, with the broad spectra ranging from cool to warm white light being skillfully utilized to create various modes of lighting effects. The fabrication of WLEDs is generally sophisticated, involving either multiple components emitting in different regions or single-component phosphors with complex elemental compositions. In the present work, WLEDs utilizing solvent-tuned carbon dots derived from waste cassava peel are reported through a facile one-step microwave-assisted solvothermal method. The carbon dots show evident UV absorption and correspondingly emit broad visible light spectra when dispersed in a dimethylformamide (DMF)-polyvinyl alcohol (PVA)blend, making themselves suitable white lightemitting down conversion materials. The successful transformation of a 400nm UV LED into a WLED with a general colour rendering index (CRI) of 83 and colour correlation temperature (CCT) of 4426 K gives a promising future outlook toward developing eco and economic-friendly WLEDs. 2025 Wiley-VCH GmbH. -
Innovative Hybrid Models for Predicting Diabetes: CNN-LSTM Hybrid and Calibrated Soft Voting Model
This study assesses four ensemble techniques - stacking, soft voting, hard voting, and calibrated soft voting - for predicting diabetes onset using the Pima Indians Diabetes dataset. Traditional single-model methods are contrasted with these advanced ensemble approaches, which integrate multiple models to enhance predictive accuracy. The evaluation included metrics such as accuracy, precision, recall, F1 score, and AUC. The CNN-LSTM model was also examined, achieving an accuracy of 75%, precision of 70%, recall of 69%, and an F1 score of 72%. Among the suggested methods, the calibrated soft vote model was the most effective, with improved performance compared to the rest of the techniques. Upcoming studies will address the combination of these models with real-time monitoring systems and deploying their use across a broad range of datasets and medical conditions. 2025 IEEE. -
AI in creating inclusive work environments for neurodiverse employees
Purpose This study aims to examine the increased focus on neurodiversity in contemporary businesses. It shows how inclusive policies can capitalize on the special abilities of people with neurodiverse backgrounds, including their extraordinary problem-solving abilities, meticulous attention to detail and creative thinking. These policies benefit the individuals and contribute to a more diverse and innovative workplace. Design/methodology/approach Data was collected through semistructured interviews with HR experts and neurodivergent employees. The qualitative data were manually analyzed and coded, and themes were identified. Findings The results highlight the significant benefits of accepting neurodiversity in the workplace, enlightening the audience about its potential. For instance, artificial intelligence (AI) can be used to anonymize resumes, removing potential biases related to gender, ethnicity or age. In addition, AI can help in identifying the unique skills and strengths of neurodivergent employees, enhancing the fit between job responsibilities and their abilities. This study also emphasizes the wider effects of accepting neurodiversity on employee satisfaction, productivity and organizational innovation. This study promotes a deep learning framework that combines human-centered strategy with strategic methods to maximize the participation of neurodiverse workers and foster a more creative and dynamic corporate culture, convincing the audience of its benefits. Research limitations/implications This study is limited by its qualitative nature and relatively small sample size, comprising 15 HR professionals and 20 neurodivergent employees, which restricts generalizability. The sensitive nature of neurodiversity also made participant recruitment challenging, with some individuals hesitant to disclose their condition. In addition, companies were reluctant to share internal AI practices due to confidentiality concerns. The research focused on a select set of organizations, primarily from specific regions, limiting cross-cultural applicability. Furthermore, the absence of AI developers in the sample means insights into technical tool design and implementation remain unexplored, suggesting a gap for future multidisciplinary research. Practical implications This study provides actionable insights for HR professionals and organizational leaders aiming to improve neurodiverse hiring and support systems. It identifies specific AI tools such as Grammarly, Otter.ai and Pymetrics, that can be integrated into recruitment and workplace settings to enhance communication, reduce sensory overload and match roles to individual strengths. Organizations can use the deep learning framework proposed to design more inclusive policies and infrastructure. Training managers and customizing AI-driven accommodations can improve retention, engagement and performance among neurodiverse talent. This research supports firms in developing more equitable, adaptive and innovative environments aligned with diversity and inclusion goals. Social implications This study promotes a societal shift in how neurodivergent individuals are perceived and supported in the workforce. By emphasizing ability over deficit and proposing inclusive AI integration, it helps reduce stigma and encourages broader acceptance of cognitive diversity. The findings advocate for universal accommodations that do not require self-disclosure, promoting dignity and equity. Improved employment outcomes for neurodiverse individuals contribute to economic inclusion, reduce unemployment rates and challenge ableist norms. The research also aligns with broader Diversity Equity and Inclusion (DEI) movements, inspiring organizations and policymakers to build socially responsible frameworks that reflect the value of every individual, regardless of neurological difference. Originality/value This paper offers original value by exploring the underresearched intersection of AI and neurodiversity inclusion in the workplace. It contributes novel insights through qualitative analysis of HR professionals and neurodivergent employees, highlighting the role of AI in reducing hiring bias, customizing work environments and enhancing employee well-being. By proposing a deep learning framework and cataloging AI tools matched to neurodiverse conditions, this study bridges theory and practice. It uniquely positions AI as both a technological and ethical enabler for inclusive employment, making it highly relevant for scholars, practitioners and policymakers aiming to foster equitable, future-ready workplaces. 2025 Emerald Publishing Limited -
A Study on the Role of Tea Tourism in Assam
Tourism Development Journal Vol. 10, Issue 1, pp. 1-14, ISSN No. 0975-7376 -
Antecedents and Outcomes of Employee Engagement : A Study on Employees in Travel Organizations
Employee engagement is becoming very vital in the recent years because organizations with engaged employees tend to out-perform than employees who are disengaged. The outcomes of engaged employees are higher performance, lower turnover, increased profitability and many more. However there are some industries ignorant and neglect the importance of having engaged employees. Hence it is necessary to conduct more research on employee engagement which create more awareness to the organizations about the prominence of focusing on employee engagement and also augment to the existing literature. The study was conducted on a sample size of 433 employees working in travel organizations set up in Bengaluru and tested the relationship of psychological climate and psychological capital (antecedent variables) has on employee engagement and in turn its newlinerelationship with organizational citizenship behavior and intent to stay (outcome newlinevariables). The study also tested the mediating relationship of employee engagement newlinebetween the antecedent and outcome variables. Results indicated that psychological newlineclimate and psychological capital has a significant and positive relationship on employee engagement and with respect to outcome variables it was determined that higher the engagement level it leads to higher level of organizational citizenship behavior and intent to stay. Results of the study also indicated that employee engagement mediates the relationship between the antecedent and outcome variables. -
A Study on the Effect of Food Advertisements on Children and their influence on Parents Buying Decision
International Journal of Research in Commerce and Management Vol. 3, No. 7, pp 92-104, ISSN No. 0976-2183 -
Thematic Analysis of Quality Assurance Tools in Higher Education Institutions
Quality assurance tools are crucial in maintaining and improving higher education institutions standards, credibility and effectiveness. They ensure standardisation, institutional credibility, competitiveness, academic rigour and research quality, enhancing the teaching and learning experience. This article aims to qualitatively analyse various quality measurement tools, such as accreditation, ranking, peer review and student-led evaluation, used in the context of higher education institutions. Various qualitative analysis tools such as content analysis, thematic analysis and grounded theory approach were analysed first. Out of this, thematic analysis was selected for the qualitative analysis as the data and analysis are from literature and expert opinion, which lack primary data. The codes for the thematic analysis were taken from previous literature. The codes have operational definitions and are categorised into Input, Process and Output themes. Code values were assigned for the quality assurance tools for each code. The code count for the various themes helped to identify the usability of various tools. The study was based on Ludwigs theme generated from the Input, Process and Output system theory. The study found that accreditation is the best tool for qualitatively and quantitatively analysing an institution. It can be an ideal tool for quality assurance for an institution. Peer review, ranking and student-led evaluation ranked next in the quality assurance tool. This study aids organisations, governmental agencies and other educational institution stakeholders to select the best method for comparing institutions during admissions, grants processing and other processes. The study adopted the qualitative analysis tool thematic analysis. Hence, the study has subjective bias and is not free from the limitation of thematic analysis. The modelling approach is directed towards prediction rather than casualty. The study has taken the literature reviews and expert opinion into account. However, structured questionnaires and unstructured interviews helped better categorise the various codes into the respective themes. The statistical analysis would have made the observation more robust. This article fulfils an identified need to analyse the ideal quality assurance tool for quality assurance and measurement for institutions. This helps institutions meet national and international accreditation standards, policy formulation, strategic planning, continuous improvement, faculty workload distribution, accountability and boosts institutional reputation. 2026 Unisa Press. -
Comparative study of benchmarking models for higher education institutions
Benchmarking is a systematic and ongoing process of assessing an organisations business processes against those of business process leaders to obtain data that will enable the firm to take corrective action to enhance performance (Pattison, 1993). Eight benchmarking models, namely the European Foundation for Quality Management (EFQM) excellence model, American Productivity and Quality Centre (APQC) consortium framework, Commonwealth Higher Education Management Service (CHEMS) model, Mckinnon model, Henderson-Smart et al. model, educational development efficiency (EDE) model, Tee benchmarking model, and fourth generation balanced scorecard method are being studied, analysed, evaluated and compared. While most models effectiveness depends on the cooperation and participation of benchmarking partners, few depends on secondary data are an exception. Most benchmarking models lack the implementation and are fluid and flexible models. This comparative benchmarking study helps an institution understand which benchmarking model needs to be used, as the study details each models essential features, advantages, and limitations. Copyright 2025 Inderscience Enterprises Ltd. -
Posture Classification Using a Hybrid Deep Learning Model
Automated posture detection is a critical task in ergonomics and healthcare, yet it presents significant challenges for standard computer vision models, particularly in handling class imbalance and understanding geometric constraints. This paper proposes an enhanced hybrid deep learning model that synergizes the feature extraction power of a pre-trained ResNet50 architecture with engineered geometric features derived from the Radon Transform and pre-calculated joint angles. Our approach utilizes a dual-balancing strategy, combining data upsampling with a custom weighted loss function, to effectively address the problem of underrepresented classes. By processing visual and geometric data streams in parallel and fusing them within a deep architecture, our model achieves a holistic understanding of the subject's posture. The fine-tuned model demonstrates strong performance on an unseen test set, achieving a final accuracy of 92% for wrist posture and 92% for neck posture. Crucially, it attains a robust F1-score of 0.74 for the challenging 'Bad Wrist Posture' minority class, a significant improvement compared to the ResNet50-only baseline (F1=0.24) and achieves excellent ROC-AUC scores of 0.9859 for wrist and 0.9838 for neck, proving the efficacy of our hybrid, dual-balancing methodology for realworld application. 2026 IEEE. -
Womens perceived social support through self-help group: case study of Kudumbashree from capital district of Kerala
This study examines Kudumbashree, a womens self-help group (SHG) with a strong emphasis on microcredit, in Thiruvananthapuram, the capital of Kerala state in India. It is a valuable program because it provides access to credit and savings mechanisms, fosters a sense of agency, decision-making power, and social support among women in these areas. The study explores the demographic characteristics of members, their involvement in SHGs, and compares perceived social support levels across different demographic groups. The study uses a cross-sectional survey of 502 women using an extensive demographic questionnaire and Multidimensional Scale of Perceived Social Support (MSPSS) questionnaire. The study participants were mostly older, married women who were primarily housewives from both nuclear and joint families, predominantly in rural areas. Many women had been SHG members for over a decade and actively participated in meetings and decision-making. The study revealed that women with lower education levels, rural and those saving more than 300 INR monthly perceived higher social support from family and overall. Considering that women in rural India averaged around 250 INR in daily earnings from casual labor during 2022, the fact that a substantial number of participants saved more than 300 INR monthly highlights the significance of their savings. The study contributes to the understanding of Kudumbashree SHGs and emphasizes their role in providing social support, financial empowerment, and a sense of community. The study also highlights the need for ongoing support and capacity building to further enhance their impact. 2025 Taylor & Francis Group, LLC. -
A Systematic Review on Traffic Management System and Security Flaws: Analysis Research
The number of cars on our roads has significantly increased in recent years, surpassing the advancement of our traffic and road infrastructure. Due to the ineffective traffic management caused by this imbalance, there have been noticeable increases in traffic jams, congestion, and pollution. Addressing the problem of growing traffic has become urgent on a global scale. By using cutting-edge technology, Intelligent Transportation Systems (ITSs) provide a viable solution for addressing these issues. This research explores the development of traffic control systems as well as the cutting-edge innovations that have revolutionized this field. Furthermore, it examines various techniques based on traffic signals, primarily focusing on scrutinizing their security vulnerabilities and the measures taken to enhance system performance. The review acknowledges significant strides made in implementing security measures, assessing their effectiveness through both qualitative and quantitative metrics. Additionally, this study delves into key discoveries and explores the rationale behind lessons learned, serving as a roadmap for future research endeavors. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Biocontrol potential of Flemingia wightiana: A natural weapon against Culex quinquefasciatus
Globally, mosquito-borne diseases, particlulalry those transmitted by Culex quincquefasciatus pose a significant public health challenge. Traditional methods of eradication using synthetic insecticides pose environmental concerns and a risk of developing insecticide-resistant varieties. Here, the use of plant-based biopesticides offers a safer and sustainable alternative. The study aimed to investigate the insecticidal properties of Flemingia wightiana (FW) leaves by synthesising leaf extracts and silver nano-particles. The toxicity of the test samples was tested on Oreochromis niloticus at concentrations of 0.1, 0.5, and 1 mg/L. Furthermore, the test samples were subjected to lethality assay on C. quinquefasciatus. Laboratory bioassays were conducted to evaluate the efficacy of crude extract and silver nanoparticles of F. wightiana at varying concentrations, specifically 0.5, 1, 2, and 4 mg/L. Ovicidal, emergency and larvicidal activity were studied. The results indicated significant larvicidal activity and exhibited better potential for toxicity against Culex larvae treated with AgNPs. FW-AgNPs have substantial effect in delaying the hatching of mosquito eggs. Moulting of larvae from one instar to the next was also delayed by treatment with AgNPs. The findings demonstrated that FW-AgNPs play a significant role in controlling C. quinquefasciatus populations. : Author (s). Publishing rights and ANSF. -
Sustainable mosquito control: A tool in the fight against Aedes aegypti using Flemingia wightiana
Mosquito-borne diseases, particularly those transmitted by Aedes aegypti, have been proven to be a global health challenge. A. aegypti, a major vector of Zika virus, Dengue virus, Chikungunya, is traditionally controlled through synthetic insecticides. However, the factor of environmental issues and rising insecticide resistant breeds have prompted the exploration of eco-friendly and sustainable alternatives. Here, we attempt to use the leaf extract of Flemingia wightiana to produce silver nanoparticles (FWAgNP). The construct of AgNPs was first indicated by UV-Vis spectroscopy, with a peak at 461 nm. NP was then characterized by SEM, EDX and functional groups were analyzed using FTIR spectroscopy. Safety assessments of synthesized NP were carried out on Oreochromis niloticus. Percentage mortality was studied on A. Aegypti with both test samples, FWAgNP and FWME. FWAgNP were found to be effective; the lowest percentage mortality of 70 % was recorded for forth instar larvae and 100 % mortality was observed in the first and second instar larvae. Oxidative stress assays such as AChe, SOD, CAT, GSH and GST were carried out. SOD, CAT and GSH showed significant elevated levels. GST and AChe levels reduced as the concentration increased, indicating the role of test samples in oxidative stress. Antiviral assay was conducted to check the effect of AgNPs in inhibiting the growth and infection of Zika virus (ZIKV) on Vero cells. The percentage inhibition property of AgNP was found to be 25 %. In conclusion, the developed FWAgNPs have significant potential in the control of vectors and a limited inhibitory activity on Zika virus. The Author(s). -
Assessing the role and effectiveness of NGOs in enhancing elementary education in government primary schools in Karnataka: A SWOT analysis
Elementary education in Karnatakas government schools faces several challenges, including inadequate infrastructure and a shortage of human resources. Non-Governmental Organizations (NGOs) have emerged as pivotal players in addressing these gaps. This research paper conducts a comprehensive SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of NGOs involved in elementary education across Karnataka. Drawing on interviews with 50 NGOs across four revenue districts in Karnataka, the paper explores their internal strengths, challenges, and potential areas for increasing their impact. The findings highlight key strengths of NGOs including their strong relationships with stakeholders as well as their innovative and flexible approaches to implementing educational programs. However, weaknesses include limited funding and organizations heavy reliance on volunteers. Despite these challenges, opportunities exist to run more development programs and leverage technological advancements. At the same time, threats such as frequent changes in laws and regulations, resistance from authorities, and rigid teacher and parent mindsets pose barriers to the effective and efficient running of NGOs educational programs in Karnataka. The Author(s) 2026 -
Artificial Intelligence and Machine Learning in Educational Apps
The integration of Artificial Intelligence (AI) and Machine Learning (ML) in educational applications is transforming higher education by enhancing personalized learning, intelligent tutoring, and predictive analytics. This chapter explores AI-driven functionalities, including adaptive learning, NLP, and automated assessments, while addressing challenges such as data privacy, algorithmic bias, and accessibility. Through case studies, it highlights AIs transformative potential in shaping future education, offering insights for educators, researchers, and developers interested in AI-driven learning innovations. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Fairness-Aware and Interpretable Depression Detection on Social Media Using BERT with Gender Bias Mitigations
Reddit and similar social media platforms offer substantial information regarding mental health issues. The automatic detection of depression raises different issues pertaining to fairness and transparency. This paper presents a Fairness Aware and Interpretable Depression Detection framework that utilizes BERT and incorporates an explicit gender bias mitigation mechanism. Data were obtained from gender-specific forums on Reddit. The Mistral language model based classifier was used to set a high confidence threshold, which helped in inferring gender labels while both depressed and non-depressed were among the patients assigned the labels. A balanced dataset with four groups (Depressed-Male, Depressed-Female, NonDepressed-Male, NonDepressed-Female) was prepared. Two pipelines were carried out where one involved a baseline BERT classifier while the other employed a fairness aware BERT model that incorporated gender embeddings during the training phase. The models were assessed using accuracy, precision, recall, F1 score, and confusion matrices and the fairness metrics applied were Demographic Parity Difference (DPD) and Equal Opportunity Difference (EOD). To enhance the model's reasoning transparency, SHAP was applied due to its capability to provide clear and comprehensive explanations. The results indicated that the fairness centered model effectively reduced gender biasness and equalized error rates among the different groups without losing its original accuracy. The essential point is that the model had learned to give precedence to clinical indicators over gender specific language. This study suggests a roadmap for the creation of ethical AI by combining fairness, interpretability and high performance into a seamless framework. 2025 IEEE. -
Synthesis and Characterixation of Fluorinated Superconducting Y3Ba5Cu8Oy Compound
International Journal of Engineering Research and Applications, Vol-3 (1), pp. 927-930. ISSN-2248-9622 -
60Co gamma irradiation and annealing effects on transport properties of antimony telluride platelets grown by physical vapor deposition
Physical vapor deposition method was employed to deposit antimony telluride (Sb2Te3) crystals in a dual-zone furnace. The microstructure, surface topography and composition of samples were characterized using X-ray diffraction, atomic force and scanning electron microscopy. Seebeck coefficient (S?c), electrical conductivity (??c) as well as power factor (PF) were enhanced for pure Sb2Te3 samples upon annealing, and the samples annealed at 473 K exhibited the highest PF of 3.16 10-3 W m-1K-2 with an enhancement of 22% in the figure of merit (Z). When the delivered dose of 60Co gamma radiation was increased from 0 to 30 kGy in the stoichiometric crystals, ??c decreased due to the decrease in mobility. As a result of the increase in S, PF and Z improved by 12.11 and 13.7%, respectively, in the 30 kGy gamma-irradiated crystals. Both RH (B?c) and S?c were positive, suggesting that the prepared Sb2Te3 crystals retained the p-type semiconductivity after these treatments. The Chinese Society for Metals and Springer-Verlag 2015.