The need to design low-cost adsorbents for the detoxification of industrial effluents has been a growing concern for most environmental researchers. So modelling of experimental data from adsorption processes is a very important means of predicting the mechanisms of various adsorption systems. Therefore, this paper presents an overall review of the applications of adsorption isotherms, the use of linear regression analysis, nonlinear regression analysis, and error functions for optimum adsorption data analysis.

Oriental Journal of Chemistry is a peer reviewed quarterly research journal of pure and applied chemistry. It publishes standard research papers in almost all thrust areas of current chemistry of academic and commercial importance. It provides a platform for rapid publication of quality research papers, reviews and chemistry letters. Oriental Journal of Chemistry is abstracted and indexed in almost all reputed National and International agencies.

Hepatitis B is a potentially deadly liver infection caused by the hepatitis B virus. It is a serious public health problem globally. Substantial efforts have been made to apply machine learning in detecting the virus. However, the application of model interpretability is limited in the existing literature. Model interpretability makes it easier for humans to understand and trust the machine-learning model. Therefore, in this study, we used SHapley Additive exPlanations (SHAP), a game-based theoretical approach to explain and visualize the predictions of machine learning models applied for hepatitis B diagnosis. The algorithms used in building the models include decision tree, logistic regression, support vector machines, random forest, adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost), and they achieved balanced accuracies of 75%, 82%, 75%, 86%, 92%, and 90%, respectively. Meanwhile, the SHAP values showed that bilirubin is the most significant feature contributing to a higher mortality rate. Consequently, older patients are more likely to die with elevated bilirubin levels. The outcome of this study can aid health practitioners and health policymakers in explaining the result of machine learning models for health-related problems.

As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, and surveillance. Meanwhile, fast and efficient point-of-care (POC) testing and self-testing kits have become necessary in the fight against COVID-19 and to assist healthcare personnel and governments curb the spread of the virus. This paper presents a review of the various types of COVID-19 detection methods, diagnostic technologies, and surveillance approaches that have been used or proposed. The review provided in this article should be beneficial to researchers in this field and health policymakers at large.

Fullerenes were initially found to be inert, but their unique cage structure and solubility in organic solvents opened up their susceptibility to functionalization via addition and redox reactions. Endohedral and exohedral derivatives of Buckminster fullerene [C60] have created a niche in the application of carbon nanomaterials in the medical, electronics, energy and water treatment/conservation sectors.

Adsorption processes are among the most patronized applications of Metal-Organic Frameworks. Through adsorption MOFs have found usefulness in diverse sectors of human endeavors such as; removal of noxious and harmful substances (dyes and heavy metals from liquid/gaseous media discharged from industries), storage and sequestration of gases (carbon dioxide, methane and hydrogen), separation and purification of gases/petroleum products, catalytic processes and drug delivery. Functionalized MOFs can indeed show spectacular effects owing to the introduction of more active functional groups. Therefore, the performance and applicability of MOFs as sorbents in industrial processes depends on the degree of introduced functionality, high surface area and enhanced porosity.