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Design, synthesis, single-crystal X-ray and docking studies of imidazopyridine analogues as potent anti-TB agents
With the intent to discover new anti-TB compounds, new imidazopyridine analogues were synthesized through Schiff-base reaction. The newly developed imidazopyridines (I1-I8) were characterized using spectroscopic and elemental analysis. In addition the structure of compound I3 was elucidated by the single crystal X-ray diffraction technique. The global chemical reactivity descriptor parameter was calculated using theoretically DFT-B3LYP-631G(d) basis set which estimated HOMO-LUMO value and results are discussed. All the newly synthesized compounds were screened for their in vitro anti-tubercular activity, while the most active compounds were subjected to a cytotoxicity assay on Vero cell lines. Most of the tested compounds exhibited significant anti-TB activity with MIC in the range 3.12 12.5 ?g/mL. Among the synthesized, compound I2 and I7 were found to be more active than the standard anti-TB drug streptomycin and comparable activity to pyrazinamide. A cytotoxicity study on Vero-cell lines confirmed the nontoxic nature of compound I2 and I7 indicating good safety profile. The molecular docking studies on PDB IB: 4ED4 enzyme of Mycobacterium tuberculosis was conducted to investigate mechanisms of anti-TB activity. The compounds displayed excellent hydrogen binding interactions and docking scores against MTB, which were in accordance with the results and further supported its credibility. 2023 -
Surveillance system based on raspberry pi for monitoring a location through a mobile device /
International Journals of Advanced Multidisciplinary Research, Vol.2, Issue 3, pp.75-79, ISSN No: 2393-8870. -
Relationship Between Socio-Cultural Environment and Creativity of Secondary School Pupils of Bengarpet Taluk
Indian Streams Research Journal Vol. 2, Issue 9, PP. 138-142, ISSN No. 2230-7850 -
Enhanced mother optimization algorithm-based optimal reconfiguration to accommodate emerging electric vehicle demand
Radial configuration and high x/r ratio branches in electrical distribution systems (EDSs) result in significant power losses and diminished stability margins. Optimal network reconfiguration (ONR) is a highly flexible solution methodology for addressing these challenges. The identification of optimal branches or tie lines to modify their on/off status in relation to multiple objectives under radial constraints constitutes a complex optimization challenge. This paper presents a novel variant of the mother optimization algorithm (MOA) that incorporates dynamic learning techniques for the optimal placement and sizing of electric vehicle (EV) charging stations to enhance distribution system loadability. The proposed modifications enhanced the overall performance of the algorithm by improving the exploration and exploitation characteristics. This leads to superior global best results and faster convergence than with other competitive algorithms when addressing complex optimization problems. In addition, an enhanced mother optimization algorithm (EMOA) is employed to address the ONR problem in 7-, 12-, 33-, 69-, and 118-bus IEEE radial systems. The losses are reduced by 44.15%, 30.07%, 33.87%, 55.72%, and 33.04% when compared to the base case across the respective test systems. Moreover, the loadability is increased in the 33-bus and 69-bus configurations by 208.75% and 177.07% for the base and optimal configurations, respectively. The results indicate the appropriateness of the ONR for enhancing the loadability to accommodate the rising penetration levels of electric vehicles (EVs) in support of sustainability. The Author(s) 2025. -
Cryptocurrency Conundrum: Understanding the Dynamics of Indian Consumer Intentions using an Extended UTAUT Model
This study aims to identify what drives cryptocurrency usage in Indian consumers. At a time when the whole world is warming up to the idea of cryptocurrencies, India has only recently come on the map after demonetization. This has left Indian cryptocurrency companies groping in the dark regarding truly understanding Indian consumers and their preference for cryptocurrencies. Thus, to achieve the purpose of this study, we administered an online survey and studied only those respondents who were Indian citizens and had ever bought or sold cryptocurrencies before. Then, we performed factor analysis by analyzing responses to the questions of our UTAUT model using SPSS and PLS Smart. The results showed that the best predictor of cryptocurrency was using the construct Access to Knowledge/News, implying that Indian consumers use of cryptocurrencies was directly proportional to the ease and availability of accurate information about cryptocurrencies. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte. Ltd. -
Response Surface Methodology-Optimized FL0.1@ZIF-8 Fluorescent Probe for High-Throughput Capsaicin Analysis in Chili Products
Capsaicinoids are a group of naturally occurring organic compounds responsible for the pungency of chili. This study aimed at exploring a novel approach with multivariate-assisted Response Surface MethodologyBox Behnken Design (RSM-BBD) optimized fluorescent probe (FL0.1@ZIF-8) for the detection of capsaicin. The probe was solvothermally synthesized and characterized using XRD, FTIR, and SEM to confirm the successful incorporation of fluorescein (FL) into ZIF-8. The experimental parameters, including pH, concentration of the probe, and reaction time, were systematically optimized via RSM-BBD to enhance the sensitivity of FL0.1@ZIF-8. The results demonstrated a quenching response of FL0.1@ZIF-8 emission with capsaicin. The limit of detection (LOD) and limit of quantification (LOQ) were calculated and found to be 1.5 ?M and 4.9 ?M, respectively. The outcome of the study identifies efficient electronic factors as major contributors to the development of FL0.1@ZIF-8 with promising possibilities for the detection of chili hotness for food pungency evaluation, quality control, and assurance in the food industry. 2026 American Chemical Society -
Integrated Effect of Flow Field Misalignment and Gas Diffusion Layer Compression/Intrusion on High Temperature - Polymer Electrolyte Membrane Fuel Cell Performance
Misalignment in the flow field plates of High-Temperature Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) due to manufacturing tolerances, assembly process, or unavoidable vibration during the cell operation is contemplated its performance and durability. This study investigates the effect of flow field plate misalignment and its concomitant impact with varying the clamping pressures on HT-PEMFC operation. The study considers six degrees of cathode flow field misalignment, varying from 0% to 100% with respect to the anode flow field. Clamping pressures ranging from 1 to 2 MPa are applied to the various cases of misalignment to study their effect on GDL deformation and intrusion into the channels. The structural analysis shows that as the misalignment increases from 0 to 100%, the GDL compression increases from 26.72% to 37.75% for 1 MPa, 40.07% to 56.63% for 1.5 MPa, and 53.43% to 75.51% for 2 MPa, owing to the increase in compression approximately by 41% from their base cases and it is also crucial to note that GDL compression exaggerates at higher clamping pressures. The misalignment results in the sagging of Membrane Electrode Assembly (MEA), and the amplitude of wave nature is proportional to the degree of misalignment and clamping pressure, indicating the misalignment is the sole factor for structural changes. As a result, considerable variance in current distribution and average value is observed, i.e., at operating voltage 0.5 V, the current density drops from 4472.7 to 4264.4, 4420.7 to 4211.8, and 4374.1 to 4161.3 A m?2 from cases 1 to 6 for clamping pressures 1, 1.5, and 2 MPa, respectively, resulting in a 4.7% loss in performance. According to the observations, a misalignment of 60% is tolerable, with minimal performance loss and negligible non-uniformity in cell distributions. 2022 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
Biogenic synthesis of g-C3N4/Bi2O3 heterojunction with enhanced photocatalytic activity and statistical optimization of reaction parameters /
Applied Surface Science, Vol.494, pp.465-476, ISSN No: 0169-4332. -
Review on persistent challenges of perovskite solar cells stability
Today Perovskite solar cell (PSC) has achieved efficiency close to 26%, surpassing the efficiencies of well- known Dye-Sensitized Solar cells (DSSC), CdTe-based solar cells, etc. Ease of preparing perovskite solutions and convenient deposition technique has given them added advantage over other contemporary competitors. This has also made them an economically feasible option. Since the inception of PSCs in 2009, a lot of improvements have been done in various aspects like composition, synthesis technique, fabrication method, and interface study. However, today it is crucial to think about the commercialization of PSCs. In this direction, the stability of PSCs has been a long-standing question. This review focuses on the key aspects of perovskite stability. Challenges posed by environmental factors like moisture, oxygen, temperature, and light are still unanswered. The lead toxicity of PSCs demands a potential substitute of lead with no compromise in their efficiency. The lead-free approach of PSCs and their commercialization has been discussed separately. A suitable emphasis has been given to the encapsulation of solar cells, as we find it a necessary part of the future commercialization process. This review has been addressed with an ideology to provide overall knowledge on the stability issues and challenges concerned with the PSCs, to attract young research community towards this emerging field. 2021 International Solar Energy Society -
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) -
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. -
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 -
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 -
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. -
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. -
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. -
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 -
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. -
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 -
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