Molecular weights and conductance studies of some organic poly(aminiumphosphate)s

Summary Long chain poly(aminiumphosphate)s of general composition (BHPO₃)_n (where BH = organic cations) were prepared by precipitation technique. The composition was established by the analysis of these derivatives for N and P. The polymeric nature was confirmed by their molecular weight determinations by end group titration and viscosity methods. Conductance studies at different concentrations confirmed their polyelectrolytic behaviour.     

Removal of viruses from water by sorption on coal

The objective of this research was to investigate the potential of bituminous coal as sorbent for removing viruses from water and to delineate the sorption mechanism(s). This study was undertaken in view of the increasing use of coal in water and wastewater treatment. Bacteriophage T4 against Escherichia coli BB was used as a model virus and coal samples from Neyveli and Giridih were used as sorbents. A sampling method for rapid separation of unsorbed viruses from the sorbent was standardized which consisted of filtering the sample containing coal and viruses through a Whatman filter paper soaked in beef extract. Effects of the following parameters on virus sorption were investigated: pH, ionic strength, temperature, and presence of proteinaceous matter.Maximum virus sorption (about 70%) was observed at pH 8·0 with input virus concentration 1·44 × 10⁴ PFU ml⁻¹, coal size 350 μm and ionic strength 0·02. Optimum ionic strength for virus sorption was found to be 0·015. Higher temperatures increased the sorption capacity and the activation energy was found to be 30·3 kcal/mole. This and low desorption values (6–10%) suggested irreversible chemisorption. Effect of carbon content of coal on sorption-desorption was studied using pure graphite which showed negligible desorption. Effect of proteinaceous matter was investigated using 5% domestic wastewater and the culture broth. Proteinaceous matter appeared to compete with virus for sorption sites on coal and reduced sorption by about 12%.Kinetics and equilibria of sorption on Neyveli coal at pH values 5·5, 7·1 and 8·0 were studied in a non-flow agitated system. Equilibrium sorption was attained in 90 min, the bulk of it being over in 45 min. Sorption data followed Langmuir type isotherm plots and suggested L2 type plot according to Gile's classification (J. Chem. Soc. Part 3, p. 3973, 1960). Isotherm plot with 5% domestic wastewater gave an S curve, suggesting moderate to large intermolecular attraction and implying strong competition for substrate sites from molecules of the solvent. Monomolecular coverage to the extent of only 0·1% of total surface area agreed with the assumptions of isotherm plot and penetration into micropores and macropores of coal was ruled out.     

Facing the reality of data stream classification: coping with scarcity of labeled data

Recent approaches for classifying data streams are mostly based on supervised learning algorithms, which can only be trained with labeled data. Manual labeling of data is both costly and time consuming. Therefore, in a real streaming environment where large volumes of data appear at a high speed, only a small fraction of the data can be labeled. Thus, only a limited number of instances will be available for training and updating the classification models, leading to poorly trained classifiers. We apply a novel technique to overcome this problem by utilizing both unlabeled and labeled instances to train and update the classification model. Each classification model is built as a collection of micro-clusters using semi-supervised clustering, and an ensemble of these models is used to classify unlabeled data. Empirical evaluation of both synthetic and real data reveals that our approach outperforms state-of-the-art stream classification algorithms that use ten times more labeled data than our approach.     

Recent Advances in Synthesis of CeVO4 Nanoparticles and Their Potential Scaffold for Photocatalytic Applications

Nowadays, modern nanotechnology has played a crucial role in the diverse domains of science and engineering. In this context, we have summarized the present literature and described the synthetic approaches, structural properties, and diverse potential applications of emerging cerium vanadate nanoparticles (CeVO₄ NPs). Since CeVO₄ NPs are an admirable catalytic, electrical, magnetic, and optical feature, they are used as catalysts, electrodes, sensors, lubricants, solar cells, hydrogen storage devices, and supercapacitors. The effect of diverse factors on the synthesis of CeVO₄ NPs, such as time, temperature, pH, solvent, and concentration, have been successfully discussed and highlighted. Moreover, diverse applications of CeVO₄ NPs, including photocatalysis, sensing, energy storage, and biomedical, have been addressed. Furthermore, a possible perspective for further research on CeVO₄ NPs is also suggested. We firmly believe that this review will be an efficient guide for researchers intrigued by the synthesis and multifunctional applications of CeVO₄ NPs.

     

Silver-Nanoparticle-Embedded Short Amphiphilic Peptide Nanostructures and Their Plausible Application to Reduce Bacterial Infections

The microbiota-gut-brain axis (GBA) plays a critical role in the development of neurodegenerative diseases. Dysbiosis of the intestinal microbiome causes a significant alteration in the gut microbiota of Alzheimer's disease (AD) patients, followed by neuroinflammatory processes. Thus, AD beginning in the gut is closely related to an imbalance in gut microbiota, and hence a multidomain approach to reduce this imbalance by exerting positive effects on the gut microbiota is needed. In one example, a tyrosine-based short peptide amphiphile (sPA) was used to synthesize antibacterial AgNPs−sPA nanostructures. Such nanostructures showed high biocompatibility and low cytotoxicity, and therefore work as model drug delivery agents for addressing local bacterial infections. These may have therapeutic value for the treatment of microbiota-triggered progression of neurodegenerative diseases.     

Biopolymer Nanovehicles for Oral Delivery of Natural Anticancer Agents

Cancer is the second leading cause of death throughout the world. Nature-inspired anticancer agents (NAAs) that are a gift of nature to humanity have been extensively utilized in the alleviation/prevention of the disease due to their numerous pharmacological activities. While the oral route is an ideal and common way of drug administration, the application of NAAs through the oral pathway has been extremely limited owing to their inherent features, e.g., poor solubility, gastrointestinal (GI) instability, and low bioavailability. With the development of nano-driven encapsulation strategies, polymeric vehicles, especially those with natural origins, have demonstrated a potent platform, which can professionally shield versatile NAAs against GI barricades and safely deliver them to the site of action. In this review, the predicament of orally delivering NAAs and the encapsulation strategy solutions based on biopolymer matrices are summarized. Proof-of-concept in vitro/in vivo results are also discussed for oral delivery of these agents by various biopolymer vehicles, which can be found so far from the literature. Last but not the least, the challenges and new opportunities in the field are highlighted.     

Effect of Chemicals on the Carbohydrate Contents of Pumpkin (Cucurbita pepo) Seeds During Germination

The effect of pre-soaking treatments of optimum concentration of fertilizers on the carbohydrate contents viz. total sugar, reducing sugars, starch and amylose of Cucurbita pepo (pumpkin) seeds during germination periods up to 12 days were studied. Variations in the contents of carbohydrate during growth periods are explained on the basis of mutual effect of metabolites and of certain related enzymes over and above the effect of method of pre-soaking treatment and of chemicals on the mitochondrial function. It is also reported that the vegetative growth and the nutritive value of mix treatment are higher than in the other cases studied.     

Review:Measurement-Based Monitoring and Fault Identification in Centrifugal Pumps

Condition based maintenance(CBM) is one of the solutions to machinery maintenance requirements. Latest approaches to CBM aim at reducing human engagement in the real-time fault detection and decision making. Machine learning techniques like fuzzy-logic-based systems, neural networks, and support vector machines help to reduce human involvement. Most of these techniques provide fault information with 100% confidence. It is undeniably apparent that this area has a vast application scope. To facili...