Optimized machine learning model for air quality index prediction in major cities in India

Industrial advancements and utilization of large amount of fossil fuels, vehicle pollution, and other calamities increases the Air Quality Index (AQI) of major cities in a drastic manner. Major cities AQI analysis is essential so that the government can take proper preventive, proactive measures to reduce air pollution. This research incorporates artificial intelligence in AQI prediction based on air pollution data. An optimized machine learning model which combines Grey Wolf Optimization (GWO) with the Decision Tree (DT) algorithm for accurate prediction of AQI in major cities of India. Air quality data available in the Kaggle repository is used for experimentation, and major cities like Delhi, Hyderabad, Kolkata, Bangalore, Visakhapatnam, and Chennai are considered for analysis. The proposed model performance is experimentally verified through metrics like R-Square, RMSE, MSE, MAE, and accuracy. Existing machine learning models, like k-nearest Neighbor, Random Forest regressor, and Support vector regressor, are compared with the proposed model. The proposed model attains better prediction performance compared to traditional machine learning algorithms with maximum accuracy of 88.98% for New Delhi city, 91.49% for Bangalore city, 94.48% for Kolkata, 97.66% for Hyderabad, 95.22% for Chennai and 97.68% for Visakhapatnam city

Pyrene-Based Mono- and Di-N-Heterocyclic Carbene Ligand Complexes of Ruthenium for the Preparation of Mixed Arylated/Alkylated Arylpyridines

By using two pyrene-based mono- and di-N-heterocyclic carbene ligands, two ruthenium complexes (one monometallic and the other dimetallic) have been obtained and fully characterized. The molecular structure of the dimetallic complex has been determined by means of X-ray diffraction studies. The electrochemical studies reveal that the metal–metal communication in the dimetallic complex is weak. The catalytic activity of both complexes has been tested in the arylation of arylpyridines with aryl halides and in the hydroarylation of alkenes, where they showed similar activity. The sequential combination of these two catalytic processes (hydroarylation of alkenes followed by arylation of the resulting alkyl-substituted arylpyridine) allowed the preparation of mixed arylated/alkylated arylpyridines. In this tandem process, the dimetallic complex afforded activity higher than that of the monometallic complex. The activity was compared to that shown by the [RuCl2(p-cymene)]2 complex. This reaction constitutes an efficient method for reaching unsymmetrically substituted arylpyridines

Scalable and chromatography-free synthesis of 2-(2-formylalkyl)arenecarboxylic acid derivatives through the supramolecularly controlled hydroformylation of vinylarene-2-carboxylic acids

This protocol describes how to prepare 2-(2-formylalkyl)-arenecarboxylic acid derivatives, common building blocks for the synthesis of various valuable chemicals (e.g., anti-obesity and Alzheimer's disease treatment pharmaceuticals), by using the fully regioselective hydroformylation of vinyl arene derivatives. This catalytic reaction proceeds cleanly with 100% regioselectivity and chemoselectivity. The procedure is reliably scalable and can be efficiently conducted on a multigram scale. The analytically pure product is easily isolated with a nearly quantitative yield by using a simple acid-base extraction workup and avoids any tedious chromatography. This protocol details the synthesis of a bisphosphite ligand (L1) that is a pivotal element of the catalytic system used, Rh(acac)(CO)(2) with ligand L1, starting from commercial building blocks. The protocol also describes a general procedure for the preparative hydroformylation of vinylarene-2-carboxylic acid derivatives to 2-formylalkylarene products, providing a representative example for the hydroformylation of 2-vinylbenzoic acid (1a) to 2-(3-oxopropane)-benzoic acid (2a). The synthesis of L1 (six chemical reactions) uses 2-nitrophenylhydrazine, 4-benzyloxybenzoylchloride and (S)-binol, and takes 5-7 working days. The actual hydroformylation reaction of each vinyl arene derivative takes similar to 4 h of active effort over a period of 1-3 d