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This work highlights the potential of corncob biochar (CCBC) and Brevibacillus parabrevis for the decolorization of brilliant green (BG) dye from synthetically prepared contaminated wastewater. The CCBC was characterized by proximate, Fourier-transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction, and Brunauer-Emmett-Teller analysis, respectively. Different parameters affecting the adsorption process were evaluated. The experimental results were analyzed by the Langmuir and Freundlich isotherm models. Kinetic results were examined by different models; pseudo-second-order model has shown the best fit to the experimental data. Anew positive values of ΔH o (172.58 kJ/mol) and ΔS o (569.97 J/K/mol) in the temperature range of 303-318 K revealed that the adsorption process was spontaneous and endothermic. The present investigation showed that the bacteria immobilized with CCBC showed better BG dye degradation. The kinetic parameters, μ max , Ks, and μ max , were found to be 0.5 per day, 39.4 mg/day, and 0.012 L/ mg/day using Monod model, respectively. The adsorbent with bacteria showed good potential for the removal of cationic BG dye and can be considered for the remediation of industrial effluent.

At the beginning and end of each session, attendance is an important aspect of the daily classroom evaluation. When using traditional methods such as calling out roll calls or taking a student's signature, managing attendance can be a time-consuming task. The teacher normally checks it, although it's possible that a teacher will miss someone or some students' answers many times. Face recognition-based attendance system is a solution to the problem of recognizing faces for the purpose of collecting attendance by utilizing face recognition technology based on high-definition monitor video and other information technology. Instead of depending on time-consuming approaches, we present a real-time Face Recognition System for tracking student attendance in class in this work. The suggested method included identifying human faces from a webcam using the Viola-Jones technique, resizing the identified face to the desired size, and then processing the resized face using a basic Local Binary Patterns Histogram algorithm. After the recognition is completed, the attendance will be immediately updated in a SQLite database with the relevant information. Many institutions will profit greatly from this endeavor. As a result, the amount of time it takes and the number of human errors it makes are minimized, making it more efficient.

Aim:The study aims to correlate salivary glucose, blood glucose levels and oral colony forming units of Candida albicans and to evaluate whether saliva can be used as noninvasive means to measure glycemic status in type II diabetics without the need for the invasive procedure. Materials and methods:The study included 100 type II diabetic patients (group I) of both genders with age 40 years and above and100 healthy patients (group II), age and sex matched with the study group. Group I includes uncontrolled and controlled diabetics as groups IA and IB, respectively. Salivary glucose measurement was done using the enzymatic colorimetric method and blood glucose levels measured by doing venepuncture and centrifuged. The oral candidal carriage was calculated by incubation in Sabouraud's dextrose agar supplemented with chloramphenicol and incubated aerobically for 48 hours. To compare the mean values Z test was applied. To determine the relationship between two variables Pearson's correlation coefficient was used. Results: The salivary glucose levels showed a significant correlation with blood glucose levels. The salivary candida carriage was higher in uncontrolled as compared to controlled diabetics and healthy individuals. Conclusion: Positive correlation was obtained between salivary glucose and blood glucose in diabetics and candidal carriage has a positive correlation with blood glucose levels. This salivary glucose and blood glucose levels correlation confirms its use to find glycemic status in diabetic patients. Clinical significance: The positive correlation of salivary glucose with blood glucose shows that it can be utilized as a noninvasive tool for monitoring glycemic status in diabetic patients.

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