Integrated AHP – TOPSIS Approach for Optimization of Coolant with Nanoparticles in PVT-Based Hydrogen Production System

The production of hydrogen using photovoltaic–thermal (PVT) solar collectors with minimal environmental impact is a significant issue that necessitates a methodical approach.  The selection of an appropriate nanofluid is essential in a thermal collector to optimize the performance of the photovoltaic-thermal (PVT) system and increase the rate of hydrogen production. This study analyzes several nanofluids in terms of viscosity, thermal conductivity, density, specific heat, pumping power, and fluid cost. This study discovered a nanofluid that may significantly enhance the rate of hydrogen generation. To achieve this objective, the analytical hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods were used to identify the appropriate choice and assess the hydrogen production rate. First, the AHP technique was used to determine the required weights, followed by sorting the alternatives using the TOPSIS technique. The findings indicate that a hybrid nanofluid consisting of a 0.2% volume concentration of Al2O3–CuO in water exhibits the most favourable heat transfer characteristics and is considered the best option for improving heat transfer efficiency and boosting the rate of hydrogen generation

Preliminary studies on cytotoxic effect of fungal taxol on cancer cell lines

Taxol is an important anticancer drug used widely in the clinical field. Some endophytic fungi were isolated from selected medicinal plants and screened for the production of taxol. The effect of cytotoxicity of fungal taxol isolated from fungal endophytes was investigated by apoptosis method. Thepresence of taxol in the culture filtrate of endophytic fungi was determined by thin layer chromatography. The fungal taxol isolated from the organic extract of six fungal cultures, had strong cytotoxic activity towards BT 220, H116, Int 407, HL 251 and HLK 210 human cancer cells in vitro

A comparative study of synbiotic as an add on therapy to standard treatment in patients with aggressive periodontitis.

AIM: To evaluate the efficacy and safety of Synbiotic as an add on therapy to Standard treatment inthe management of patients with Aggressive Periodontitis compared to Standardtreatment alone. METHODOLOGY This was arandomized, prospective, placebo controlledstudy.60 patients with Aggressive Periodontitis wererandomized and blinded into two groups of 30 each. Control group received Scaling and Root planing [SRP] +Cap.Doxycycline 100mg twice daily for one week +Placebo one lozengetwice daily for 8 weeks andStudy group receivedScaling and Root planing [SRP] +Cap.Doxycycline 100mg twice daily for one week +Synbioticone lozenge twice daily for 8 weeks.The clinical parameters were recorded at baseline, 4,8 and 12 weeks.Oral hygiene index[OHI],Gingival bleeding index[GBI],Probing depth[PD] and Clinical attachment loss[CAL] were assessedat baseline and at the end of the study. RESULTS 106patients were screened out of which 60 patients were included in the study.All patients completed the study and were included in analysis.On comparing the groups at the end of12weeks there was a statistically significant reduction (P<0.01) inOHI,GBI,PD & CALin Study group. No significant difference in the incidence of adverse events noted between the two groups. CONCLUSION Synbioticalong with standard therapy is highly efficacious in reducingOHI,GBI,PD & CALinpatients with Aggressive Periodontitis

Reliable water quality prediction and parametric analysis using explainable AI models

The consumption of water constitutes the physical health of most of the living species and hence management of its purity and quality is extremely essential as contaminated water has to potential to create adverse health and environmental consequences. This creates the dire necessity to measure, control and monitor the quality of water. The primary contaminant present in water is Total Dissolved Solids (TDS), which is hard to filter out. There are various substances apart from mere solids such as potassium, sodium, chlorides, lead, nitrate, cadmium, arsenic and other pollutants. The proposed work aims to provide the automation of water quality estimation through Artificial Intelligence and uses Explainable Artificial Intelligence (XAI) for the explanation of the most significant parameters contributing towards the potability of water and the estimation of the impurities. XAI has the transparency and justifiability as a white-box model since the Machine Learning (ML) model is black-box and unable to describe the reasoning behind the ML classification. The proposed work uses various ML models such as Logistic Regression, Support Vector Machine (SVM), Gaussian Naive Bayes, Decision Tree (DT) and Random Forest (RF) to classify whether the water is drinkable. The various representations of XAI such as force plot, test patch, summary plot, dependency plot and decision plot generated in SHAPELY explainer explain the significant features, prediction score, feature importance and justification behind the water quality estimation. The RF classifier is selected for the explanation and yields optimum Accuracy and F1-Score of 0.9999, with Precision and Re-call of 0.9997 and 0.998 respectively. Thus, the work is an exploratory analysis of the estimation and management of water quality with indicators associated with their significance. This work is an emerging research at present with a vision of addressing the water quality for the future as well

A Friendly Relationship between Endophytic Fungi and Medicinal Plants: A Systematic Review

Endophytic fungi or endophytes exist widely inside the healthy tissues of living plants, and are important components of plant micro-ecosystems. Over the long period of evolution, some co-existing endophytes and their host plants have established a special relationship with one and another, which can significantly influence the formation of metabolic products in plants, then affect quality and quantity of crude drugs derived from medicinal plants. This paper will focus on the increasing knowledge of relationships between endophytic fungi and medicinal plants through reviewing of published research data obtained from the last 30 years. The analytical results indicate that the distribution and population structure of endophytes can be considerably affected by factors, such as the genetic background, age, and environmental conditions of their hosts. On the other hand, the endophytic fungi can also confer profound impacts on their host plants by enhancing their growth, increasing their fitness, strengthening their tolerances to abiotic and biotic stresses, and promoting their accumulation of secondary metabolites. All the changes are very important for the production of bioactive components in their hosts. Hence, it is essential to understand such relationships between endophytic fungi and their host medicinal plants. Such knowledge can be well exploited and applied for the production of better and more drugs from medicinal plants

Pharmacokinetics of First-Line Antituberculosis Drugs in HIV-Infected Children with Tuberculosis Treated with Intermittent Regimens in India

The objective of this report was to study the pharmacokinetics of rifampin (RMP), isoniazid (INH), and pyrazinamide (PZA) in HIV-infected children with tuberculosis (TB) treated with a thrice-weekly anti-TB regimen in the government program in India. Seventy-seven HIV-infected children with TB aged 1 to 15 years from six hospitals in India were recruited. During the intensive phase of TB treatment with directly observed administration of the drugs, a complete pharmacokinetic study was performed. Drug concentrations were measured by high-performance liquid chromatography. A multivariable regression analysis was done to explore the factors impacting drug levels and treatment outcomes. The proportions of children with subnormal peak concentrations (C(max)) of RMP, INH, and PZA were 97%, 28%, and 33%, respectively. Children less than 5 years old had a lower median C(max) and lower exposure (area under the time-concentration curve from 0 to 8 h [AUC(0–8)]) of INH (C(max), 2.5 versus 5.1 μg/ml, respectively [P = 0.016]; AUC(0–8), 11.1 versus 22.0 μg/ml · h, respectively [P = 0.047[) and PZA (C(max), 34.1 versus 42.3 μg/ml, respectively [P = 0.055]; AUC(0–8), 177.9 versus 221.7 μg/ml · h, respectively [P = 0.05]) than those more than 5 years old. In children with unfavorable versus favorable outcomes, the median C(max) of RMP (1.0 versus 2.8 μg/ml, respectively; P = 0.002) and PZA (31.9 versus 44.4 μg/ml, respectively; P = 0.045) were significantly lower. Among all factors studied, the PZA C(max) influenced TB treatment outcome (P = 0.011; adjusted odds ratio, 1.094; 95% confidence interval, 1.021 to 1.173). A high proportion of children with HIV and TB had a subnormal RMP C(max). The PZA C(max) significantly influenced treatment outcome. These findings have important clinical implications and emphasize that drug doses in HIV-infected children with TB have to be optimized