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DNMT3A p.R882C driven proliferation and anti-apoptotic effects in pancreatic cancer cells
A field of view-based assessment of soft tissue calcifications in cone beam computed tomography of the maxillofacial region
Evaluating the evolutionary relationship of TATA binding protein (TBP) with various folding patterns of protein domains using support vector machine (SVM)
Techno-economic optimization, sensitivity analysis and stability evaluation of a high-renewable hybrid microgrid for rural Bangladesh
Abstract This study develops and evaluates a high-renewable hybrid microgrid for rural Bangladesh. The objective is to design a reliable, affordable, and grid-compliant system that supports residential, institutional, and irrigation loads. The work integrates techno-economic optimization, sensitivity analysis, and voltage–frequency stability assessment within a single framework. HOMER Pro is used to analyze multiple hybrid configurations, while MATLAB evaluates dynamic stability. The proposed contribution lies in modeling realistic field-based load profiles, incorporating converter constraints, and assessing stability across different operating conditions. A PV–wind–biogas–battery microgrid emerges as the optimal option. It achieves 88.2% renewable penetration with a net present cost of USD 206,841 and a levelized cost of energy of USD 0.0207/kWh. Solar PV and wind provide most of the annual energy, while grid support remains limited. Sensitivity analysis shows that solar and converter costs strongly influence project economics. Dynamic simulations confirm secure voltage–frequency performance and compliance with Bangladesh Grid Code limits. The results demonstrate that the proposed system offers a practical pathway for low-cost, reliable, and sustainable electrification in rural communities. The framework can also be adapted to other locations with similar resource and load characteristics.
Cardiovascular medications and treatment outcomes in multiple myeloma: insights from phase III clinical trials
Species diversity and grass cover change following the invasion of Lantana camara in a woodland ecosystem
Discovery of age and blood group associated variability in nattokinase mediated thrombolysis and its relevance to cardiovascular management
The impact of china’s artificial intelligence pilot policies on enterprise supply chain resilience
Randomized pilot study of camrelizumab with or without autologous cytokine-induced killer cells in refractory clear cell renal cell carcinoma
Microwave reflection and transmission measurements for evaluating water reaction within geopolymers with different precursors
Experimental study on the three-dimensional structural characteristics of bedforms and their relationship with flow intensity
DermaGPT a federated multimodal framework with a meta learned trust function for interpretable dermatology diagnostics
A cognitive internet of things resource allocation method based on multi-agent reinforcement learning algorithm
Estimation of the apparent anisotropic water diffusivity on spruce evaluated with a simplified derivative approach and as a function of the flow rate
Abstract The anisotropic apparent diffusivity as a function of the flow rate was determined in a series of Dynamic Vapor Sorption (DVS) experiments on spruce samples in the three orthotropic directions. Four different fitting procedures were applied for the evaluation of the time-sorption isotherms, i.e. , the double-stretched exponential (DSE), the Ritger-Peppas (RP), and the Fickian and double-Fickian (SUM/DSUM) fitting methods, together with a derivative (DER) method for the determination of the apparent diffusivity. The results confirm that the DER method delivers similar results to the DSE fitting procedure, i.e. , 1.98·10 − 10 , 0.94·10 − 10 and 1.00·10 − 10 m 2 /s for the longitudinal, radial and tangential direction, respectively, with a maximum of 10% deviation, in a much simpler manner.
An improved MobileNet based on a modified poor and rich optimization algorithm for lithium-ion battery state-of-health estimation
DT-aided resource allocation via generative adversarial imitation learning in complex cloud-edge-end scenarios
CDMMM: a comprehensive platform of traditional Indian medicinal plant DNA barcodes and metabolite fingerprints database
Abstract Herbal medicines, derived from medicinal plants, are in high demand due to global population growth and the increasing prevalence of chronic diseases; however, the use of substitutes or adulterants can compromise the quality of these medicines. DNA barcoding and metabolite fingerprinting are used to identify plants and ensure the safety of drugs. The effectiveness of authentication methods depends on the availability and coverage of the reference library. However, reference DNA barcodes and metabolite fingerprint libraries for traditional Indian medicinal plants are lacking, which hinders the authentication of herbal drugs and the elucidation of the therapeutic effects of secondary metabolites. In the present study, we developed a user-friendly ‘Comprehensive Database of Medicinal Plants, Molecular Markers, and Metabolite Fingerprinting (CDMMM)’ that provides extensive details on traditional Indian medicinal plants used in drug formulations, DNA barcode sequences, metabolites, and their therapeutic targets associated with diseases. CDMMM is an expandable data resource comprising 89 experimentally obtained DNA barcode accessions from 67 plant species, 3033 annotated plant metabolites, and 1414 therapeutic targets associated with 441 diseases from 20 plant species. The ever-expanding CDMMM resource is available at https://slsdb.manipal.edu/cdmmm/ . Overall, it is a powerful platform for taxonomy, systematics, species identification, and drug discovery, promoting knowledge and addressing taxonomic uncertainties.