Photon and vibration synergism on planar defects induced 2D-graphitic carbon nitride for ultrafast remediation of dyes and antibiotic ampicillin

Journal of Materials Science - Hybrid oxidation methodologies (HOMs) and active site enrichment of 2D nanocatalyst through defects induction are ubiquitously used for generating adequate reactive...     

Imaging of follicular dendritic cell tumours of the liver

Follicular dendritic cell tumour of the liver is a recently recognized entity. To date, only two cases have been described, both in the pathology literature. Histologically, it resembles an inflammatory pseudotumour and immunohistochemical and ultrastructural studies are required for its diagnosis. The ultrasound, computed tomography and angiographic features of two cases of follicular dendritic cell tumour of the liver are described in detail. One of the patients had multiple recurrences of this tumour. The imaging features are very similar to those of hepatocellular carcinoma. As follicular dendritic cell tumour is considered to be of low-grade malignant potential, in contrast to the dismal prognosis for hepatocellular carcinoma, it is important to be able to accurately distinguish between the two types of tumour prior to initiating definitive therapy.     

HLA-B27-restricted antigen presentation in the absence of tapasin reveals polymorphism in mechanisms of HLA class I peptide loading

Tapasin is a resident ER protein believed to be critical for antigen presentation by HLA class I molecules. We demonstrate that allelic variation in MHC class I molecules influences their dependence on tapasin for peptide loading and antigen presentation. HLA-B*2705 molecules achieve high levels of surface expression and present specific viral peptides in the absence of tapasin. In contrast, HLA-B*4402 molecules are highly dependent upon human tapasin for these functions, while HLA-B8 molecules are intermediate in this regard. Significantly, HLA-B*2705 like HLA-B*4402, requires tapasin to associate efficiently with TAP (transporters associated with antigen processing). The unusual ability of HLA-B*2705 to form peptide complexes without associating with TAP or tapasin confers flexibility in the repertoire of peptides presented by this molecule. We speculate that these properties might contribute to the role of HLA-B27 in conferring susceptibility to inflammatory spondyloarthropathies.     

Dual-Metal Double-Gate with Low-k/High-k Oxide Stack Junctionless MOSFET for a Wide Range of Protein Detection: a Fully Electrostatic Based Numerical Approach

Silicon - We investigate the performance of a dielectric modulated dual-metal double-gate with low-k/high-k oxide stack junctionless MOSFET (DM-DG-LK/HK-S JL-MOSFET) based sensor device for...     

Artificial Neural Network and Grey Wolf Optimizer Based Surrogate Simulation-Optimization Model for Groundwater Remediation

We herein propose a simulation-optimization model for groundwater remediation, using PAT (pump and treat), by coupling artificial neural network (ANN) with the grey wolf optimizer (GWO). The input and output datasets to train and validate the ANN model are generated by repetitively simulating the groundwater flow and solute transport processes using the analytic element method (AEM) and random walk particle tracking (RWPT). The input dataset is the different realization of the pumping strategy and output dataset are hydraulic head and contaminant concentration at predefined locations. The ANN model is used to approximate the flow and transport processes of two unconfined aquifer case studies. The performance evaluation of the ANN model showed that the value of mean squared error (MSE) is close to zero and the value of the correlation coefficient (R) is close to 0.99. These results certainly depict high accuracy of the ANN model in approximating the AEM-RWPT model. Further, the ANN model is coupled with the GWO and it is used for remediation design using PAT. A comparison of the results of the ANN-GWO model with solutions of ANN-PSO (ANN-Particle Swarm Optimization) and ANN-DE (ANN-Differential Evolution) models illustrates the better stability and convergence behaviour of the proposed methodology for groundwater remediation.

     

Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique

This paper proposed a Neuro-Genetic technique to optimize the multi-response of wire electro-discharge machining (WEDM) process. The technique was developed through hybridization of a radial basis function network (RBFN) and non-dominated sorting genetic algorithm (NSGA-II). The machining was done on 5 vol% titanium carbide (TiC) reinforced austenitic manganese steel metal matrix composite (MMC). The proposed Neuro-Genetic technique was found to be potential in finding several optimal input machining conditions which can satisfy wide requirements of a process engineer and help in efficient utilization of WEDM in industry.     

Antineoplastic and antioxidant potential of phycofabricated silver nanoparticles using microalgae Chlorella minutissima

This study for the first time reports on fresh water microalgae Chlorella minutissima aqueous extract (CmAe) which was utilized for the biogenic synthesis of silver nanoparticles and tested their antineoplastic potential against Liver Hepatocellular Carcinoma (HepG2) cell line. The characteristic colour change of the reaction mixture from greenish yellow to yellowish brown confirmed the synthesis of Chlorella minutissima silver nanoparticles (CmAgNPs). Microscopic analysis revealed CmAgNPs to be spherical‐shaped with particle size ranging from 10 to 30 nm. The carbohydrates and proteins distinctive peaks were observed in Fourier transform infrared spectroscopy (FTIR) spectra which suggested these biomolecules acted as reducing and capping agents. Further, the crystalline nature of CmAgNPs was confirmed by X‐ray diffraction (XRD) analysis. CmAgNPs showed maximum free radical scavenging proving it to be more potent antioxidant agent as compared to CmAe. The mortality rate of HepG2 cells treated with CmAgNPs was found to be 91.8 % at 120 μg/ml with IC₅₀ value 12.42 ± 1.096 μg/ml after 48 h whereas no effect was observed on normal Human Embryonic Kidney (HEK 293) cells. Fluorescent images of the treated HepG2 cells revealed the formation of apoptotic bodies, condensed nuclei and cell shrinkage indicating their effectiveness against the cancer cells.Inspec keywords: silver, nanoparticles, nanomedicine, microorganisms, cellular biophysics, nanofabrication, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, proteins, Fourier transform infrared spectra, molecular biophysics, X‐ray chemical analysis, X‐ray diffraction, kidney, cancer, biomedical materialsOther keywords: antineoplastic potential, antioxidant potential, phycofabricated silver nanoparticle, Chlorella minutissima, freshwater microalgae, aqueous extract, liver hepatocellular carcinoma cell line, CmAgNP synthesis, field emission scanning electron microscopy, high‐resolution transmission electron microscopy, atomic force microscopy, dynamic light scattering, carbohydrate, protein, Fourier transform infrared spectroscopy, biomolecule, energy‐dispersive X‐ray spectroscopy, elemental silver signal, CmAgNP crystalline, X‐ray diffraction analysis, antioxidant agent, HepG2 cell mortality rate, human embryonic kidney, HEK 293 cell, fluorescent image, apoptotic body formation, condensed nuclei, cell shrinkage, cancer cell, antineoplastic agent, Ag     

Green biosynthesis,characterisation and antimicrobial activities of silver nanoparticles using fruit extract of Solanum viarum

Green synthesis of nanoparticles is considered an efficient method when compared with chemical and physical methods because of its bulk production, eco‐friendliness and low cost norms. The present study reports, for the first time, green synthesis of silver nanoparticles (AgNPs) at room temperature using Solanum viarum fruit extract. The visual appearance of brownish colour with an absorption band at 450 nm, as detected by ultraviolet‐visible spectrophotometer analysis, confirmed the formation of AgNPs. X‐ray diffraction confirmed the AgNPs to be crystalline with a face‐centred lattice. The transmission electron microscopy‐energy dispersive X‐ray spectroscopy image showed the AgNPs are poly‐dispersed and are mostly spherical and oval in shape with particle size ranging from 2 to 40 nm. Furthermore, Fourier transform‐infrared spectra of the synthesised AgNPs confirmed the presence of phytoconstituents as a capping agent. The antimicrobial activity study showed that the AgNPs exhibited high microbial activity against Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus susp. aureus, Aspergillus niger, and Candida albicans. The highest antimicrobial activity of AgNPs synthesised by S. viarum fruit extract was observed in P. aeruginosa, S. aureus susp. aureus and C. albicans with zone of inhibition, 26.67 mm.Inspec keywords: nanomedicine, antibacterial activity, X‐ray chemical analysis, nanoparticles, transmission electron microscopy, particle size, infrared spectra, microorganisms, X‐ray diffraction, Fourier transform spectra, ultraviolet spectra, scanning electron microscopy, visible spectra, nanofabricationOther keywords: green biosynthesis, antimicrobial activities, silver nanoparticles, green synthesis, physical methods, study reports, solanum viarum fruit, ultraviolet‐visible spectrophotometer analysis, high microbial activity, highest antimicrobial activity, s. viarum fruit, transmission electron microscopy, energy dispersive X‐ray spectroscopy image     

Multi-item inventory model of breakable items with stock-dependent demand under stock and time dependent breakability rate

Items made of glass, ceramic, etc. are normally stored in stacks and get damaged during the storage due to the accumulated stress of heaped stock. These items are known as breakable items. Here a multi-item inventory model of breakable items is developed, where demands of the items are stock dependent, breakability rates increase linearly with stock and nonlinearly with time. Due to non-linearity and complexity of the problem, the model is solved numerically and final decisions are made using Genetic Algorithm (GA). In a particular case, model is solved analytically as well as numerically and results are compared. Models are developed with both crisp and uncertain inventory costs. For uncertain inventory costs both fuzzy and stochastic parameters are considered. A chance constrained approach is followed to deal with simultaneous presence of stochastic and fuzzy parameters. Different numerical examples are used to illustrate the problem for different cases.