This paper deals with the approximate controllability of impulsive neutral fuzzy stochastic differential equations with nonlocal conditions in a Banach space by using the concept of fuzzy numbers whose values are normal, convex, upper semicontinuous and compact. The hypotheses are obtained by Schauder's and Banach fixed point theorems. The results are obtained by the evolution operator.MSC: 34A07; 39A70; 93B05; 49N25

Objective: The aim of this study is to evaluate the anti-inflammatory activity of Nigella sativa silver nanoparticles (NS AgNPs). Methods: Fourier transform infrared analysis was used to characterize the NS AgNPs and the extract. 2,2-diphenylpicrylhydrazyl assay was done to test the antioxidant potency of NS AgNP. Furthermore, in vitro anti-inflammatory activity of the extract and the NS AgNP was determined by red blood cell (RBC) membrane stabilization assay, protein inhibition assay, and interleukin-1 (IL-1) beta assay. Results: The NS AgNP exhibited dose-dependent antioxidant property. At the concentration 0.01 mg/ml 80% of radical was scavenged by NS AgNP. Inhibition of protein denaturation assay also suggests that NS AgNP shows the highest activity (70%) when compared with the standard drug aspirin (65%). RBC assay suggests that NS AgNP stabilizes the RBC membrane and prevents leaking. In the enzyme-linked immunosorbent assay method the NS AgNP showed better IL-1 beta inhibition activity when compared to aqueous extract. Conclusion: From the study, it was inferred that NS AgNPs are more effective when compared to the extract. These results suggest that NS AgNP can be used to treat inflammatory disorders.

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In this paper, a brief introduction to Machine Learning and its Tools are studied. In the recent developments, most of the Machine learning tools are more advanced and efficient. The various tools learn the machine by using a training set, which predicts the output correctly and efficiently. Machine Learning is applied in different applications such as Agriculture, Data Quality, Information Retrieval, Financial Market Analysis etc.., In this paper, we have discussed few tools like Scikit learn, Pytorch, Tensor flow, Amazon Machine Learning, KNIME, Rapid Miner, Keras, and Shogun with its features and its advantages.

Document Clustering is the process of segmenting a particular collection of text into subgroups. Nowadays all documents are in electronic form, because of the issue to retrieve relevant document from the large database. The goal is to transform text composed of daily language in a structured, database format. In this way, different documents are summarized and presented in a uniform manner. The challenging problem of document clustering are big volume, high dimensionality and complex semantics. The objective of this paper is mainly focused on clustering multi-sense word embeddings using three different algorithms(K-means, DBSCAN, CURE). Among these three algorithm CURE gives better accuracy and it can handle large databases efficiently.</p>