Mangalore University

Abstract In this study, a poly-glycine (PG)-modified carbon paste electrode (PGMCPE) is proposed as a highly sensitive electrochemical sensor for the determination of caffeic acid (CFA). To compare PGMCPE with BCPE, cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and differential pulse voltammetry (DPV) were used. The scan rate, pH, and concentration of the analyte were also optimized to enhance the efficiency of the sensor. In addition to CFA, the electrode was tested for its ability to act as a multi-analyte sensor by detecting riboflavin (RF) simultaneously. The sensor was able to detect up to 0.105 µM of limit of detection (LOD) and 0.350 µM of limit of quantification (LOQ) in the linear range of 0.2–6.5 µM. The sensitivity of the sensor was then tested using an apple juice sample, and the recovery rates were high. These results indicate that PGMCPE is a suitable and effective electrochemical electrode for the analysis of CFA in real samples. Graphical Abstract

In the era of globalization and rapid digital transformation, e-commerce has emerged as a significant driver of business expansion by enabling producers and sellers to access markets beyond geographical boundaries. Micro, Small and Medium Enterprises (MSMEs), which contribute nearly 40 percent to India’s GDP and rank as the second-largest source of employment after agriculture, play a pivotal role in promoting inclusive economic growth. In Karnataka, particularly in Dakshina Kannada district, MSMEs constitute the backbone of rural industrialization and employment generation. This study examines the role of e-commerce in promoting rural MSMEs in Dakshina Kannada district and further analyzes how digital platforms enhance market access, improve price realization, encourage women-led entrepreneurship, and foster financial inclusion. The major findings indicate that e-commerce has significantly expanded market reach, strengthened rural producer networks, and generated new employment opportunities through digital engagement and supply chain integration. The study concludes that e-commerce represents a transformative instrument for rural economic development in Dakshina Kannada. With coordinated support from government agencies, digital platforms, and local institutions, rural MSMEs can leverage digital markets to achieve sustainable growth, enhance competitiveness, and contribute more effectively to regional and state economic development. Keywords: E-commerce, MSMEs, Dakshina Kannada, and Karnataka

The demand for sustainable energy storage systems has intensified interest in gel polymer electrolytes (GPEs) that are biodegradable, efficient, and thermally stable. In this study, a novel GPE was developed using a xanthan gum (XG)/polyvinyl alcohol (PVA) blend embedded with carbon quantum dots (CQDs), magnesium chloride (MgCl 2 ), and the ionic liquid (IL) 1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([BMIM][NTf 2 ]). This work introduces a novel gel polymer electrolyte system, wherein the combined incorporation of an ionic liquid, MgCl 2 salt, and carbon quantum dots into a biopolymer matrix synergistically enhances ionic conductivity, thermal stability and electrochemical performance. The CQDs were synthesized hydrothermally via xanthan gum and characterized via photoluminescence (PL) spectroscopy, dynamic light scattering (DLS) and transmission electron microscopy (TEM), which were employed to evaluate the optical properties, size distribution, and morphology of the synthesized carbon quantum dots, respectively. The structural, thermal, and morphological properties of the GPE films were evaluated via Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). Electrochemical impedance spectroscopy revealed enhanced ionic conductivity in the optimized GPE (P5), which was attributed to synergistic interactions between the IL, salt and CQDs, with a maximum conductivity of 4.0 mS/cm at 60 °C. The supercapacitor device fabricated via this GPE (AC ∣ P5 ∣ AC) demonstrated superior performance, delivering a specific capacitance of 124 F/g, an energy density of 11.1 W h/kg, and a power density of 266.6 W/kg from galvanostatic charge‒discharge measurements. Additionally, it retained 88.8 % of its capacitance after 1000 cycles, outperforming its IL-free counterpart. Overall, the integration of ionic liquids into biodegradable GPEs presents a viable pathway towards environmentally sustainable and high-performing supercapacitor systems. • Biodegradable GPEs developed using xanthan gum, PVA, CQDs, MgCl 2 , and ionic liquids. • Monodispersed carbon dots (∼11 nm) synthesized from xanthan gum. • The optimized GPE achieved 4.0 mS/cm conductivity and enhanced stability. • The supercapacitor had a capacitance of 124 F/g and 88.8 % retention after 1000 cycles. • Sustainable electrolyte system proposed for advanced energy storage applications.

Guppies are considered as a good model for studying pesticide toxicity because of their sensitivity to various pollutants. Pesticides can affect the behavior of guppies, including their locomotor activity and avoidance responses. Guppy studies can help assess the impact of pesticide contamination on aquatic ecosystems. Since urea (carbonyl diamide) is a widely used in agriculture industry, rain fall leads loss of urea content into river or stream which causes production of ammonia in water. The high concentration of urea may cause physiological disruptions, behavioral change and even death in fishes. Pesticide contamination in aquatic environments can also pose risks to human health through the consumption of contaminated fish. The objective of this study is assessment of toxicity of urea on guppy fish (Poecilia reticulata). Different concentration of urea solution was added to the four experimental sets. One control set is maintained to analyse the effect of urea. It is clearly seen that at higher concentrations, the number of fish died is more. Observation of behavioral response of Guppy were conducted in control set and experimental sets throughout the experimental period. Numbers of fish died in the time period prescribed by the test were used to determine the mortality percent and lethal concentration. The acute toxicity of urea at relatively low concentrations highlights the need for careful management of fertilizer near aquaculture sites.

Stroke remains one of the leading causes of death and long-term disability worldwide, demanding rapid and accurate diagnosis through brain CT imaging. Deep learning can assist in stroke detection; however, class imbalance between normal and stroke-positive images presents a major challenge. This study investigates how different loss functions handle this imbalance by comparing Focal Loss and Binary Cross-Entropy (BCE) in training an Xception convolutional neural network on the TEKNOFEST-2021 brain stroke CT dataset comprising 6,653 images. The model trained with Focal Loss achieved 99.08% accuracy, 100% sensitivity, and AUC <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$=0.9996$</tex>, outperforming the BCE model, which reached 98.40% accuracy and AUC = 0.9994. An additional experiment using test-time augmentation (TTA) unexpectedly reduced accuracy to about 86%, indicating that augmentations applied during testing must align with those used in training. The findings demonstrate that Focal Loss effectively improves sensitivity in imbalanced datasets by reducing missed detections without compromising precision. This approach can strengthen the reliability of AI-based stroke screening tools. Future work will focus on adaptive focal parameters and advanced data-balancing techniques to improve generalization across diverse clinical datasets.