NEW FIXED POINT RESULTS FOR T-CONTRACTIVE MAPPING WITH c-DISTANCE IN CONE METRIC SPACES

In this article, we generalize and improve the results of Fadail et al.[Z. M. Fadail and S. M. Abusalim, Int. Jour. of Math. Anal., Vol. 11, No. 8(2017), pp. 397-405.] and Dubey et al.[AnilKumar Dubey and Urmila Mishra, Non. Func. Anal. Appl., Vol. 22, No. 2(2017), pp 275-286.] under the concept of a c-distance in cone metric spaces. We prove the existence and uniqueness of the fixed point for T -contractive type mapping under the concept of c-distance in cone metric spaces

Phishing Detection using Base Classifier and Ensemble Technique

Phishing attacks continue to pose a significant threat in today's digital landscape, with both individuals and organizations falling victim to these attacks on a regular basis. One of the primary methods used to carry out phishing attacks is through the use of phishing websites, which are designed to look like legitimate sites in order to trick users into giving away their personal information, including sensitive data such as credit card details and passwords. This research paper proposes a model that utilizes several benchmark classifiers, including LR, Bagging, RF, K-NN, DT, SVM, and Adaboost, to accurately identify and classify phishing websites based on accuracy, precision, recall, f1-score, and confusion matrix. Additionally, a meta-learner and stacking model were combined to identify phishing websites in existing systems. The proposed ensemble learning approach using stack-based meta-learners proved to be highly effective in identifying both legitimate and phishing websites, achieving an accuracy rate of up to 97.19%, with precision, recall, and f1 scores of 97%, 98%, and 98%, respectively. Thus, it is recommended that ensemble learning, particularly with stacking and its meta-learner variations, be implemented to detect and prevent phishing attacks and other digital cyber threats

EVALUATION OF ANTIMICROBIAL ACTIVITY, GC-MS AND FT-IR PROFILE OF COW URINE DISTILLATES PREPARED FROM FRESH URINE OF INDIGENOUS COW BREEDS

The present study was undertaken to explore the antimicrobial potential of cow urine distillate (gomutra ark) against pathogenic microorganisms of medical and veterinary significance. Cow urine distillates (CUDs) were prepared from fresh cow urine of three Indian breeds viz. Sahiwal, Tharparkar, and Vrindavani. CUDs obtained from two goshalas and one commercially available CUD were also tested for antimicrobial activity for comparison. Minimal inhibitory concentration (MIC) of CUD, antimicrobial activity of concentrated CUD, bacteriostatic and bactericidal potential as well as vapor phase activity were also determined. FT-IR and GC-MS analysis of the selected CUDs was performed to detect the surface functional groups and chemical composition. No antimicrobial activity was detected in the CUDs by disc diffusion and agar well diffusion methods. However, antimicrobial activity was observed in the microtitre Plate (MTP) assay as evidenced by inhibition of visible growth (turbidity) or measuring optical density (OD595). CUDs prepared from indigenous cows (Sahiwal and Tharparkar) exhibited superior antimicrobial activity compared to CUDs from crossbred cows (Vrindavani) or commercial CUDs. In general, CUDs were bactericidal for Gram-negative bacteria but bacteriostatic for Gram-positive bacteria. The MIC of CUDs was found to be in the range of 1:4 to 1:8 dilution. The concentrated CUDs exhibited a relatively lesser antimicrobial effect. CUDs exhibited antifungal activity against Candida albicans and Malassezia furfur. CUDs also exhibited antimicrobial activity in the vapor phase. FT-IR spectra of selected CUDs exhibited bending vibrations at 1633.5 cm-1 due to N-H groups resembling N-H bonding in the structure of urea and stretching vibrations at 3330. 10 cm-1 due to C-H group. GC-MS analysis of selected CUDs exhibited many compounds that may be responsible for the antimicrobial activity. The results of the study confirm the antimicrobial potential of CUD as reported in ancient literature

A study on effect of eWOM information on purchase intention for electric vehicles

Purpose- Today, customers play an active role in creating, generating, and sharing the electronic Word of mouth (eWOM). As a result, attracting customers through recommendations and WOM has become an important goal for businesses. In addition, Social Networking Sites (SNSs) have created valuable opportunities for eWOM. As a result, the development of Electric Vehicles (EVs) is essential. This study shows how eWOM information affects customers' purchase intention for EVs on social networking sites. Design/methodology/approach- This study employed the Information Adoption Model (IAM). Data was collected using a self-administered questionnaire from 266 respondents in Hyderabad and Secunderabad to evaluate the proposed model using SmartPLS software. Findings –The findings show that information quality and Credibility positively affect the usefulness of the information. Furthermore, information adoption determines purchasing intentions, with information usefulness as a predictor for adoption.  Research limitations/implications- This study aims to fill a gap in the research on SNSs, specifically in the context of eWOM information. The study proposes the IAM model and statistically confirms the hypothesized relationship. This study can be used as a platform for further studies. Practical implications-&nbsp

-an experience of two cases

ABSTRACT Tongue abscess is a rare entity, despite exposure to large number of potential pathogen, relatively resistant to infection. Here in this article we were discussed the two cases of tongue abscess in a young females, with their clinical presentation, differential diagnoses, management and a review of literature