Novel Models for Accurate Estimation of Air-Blood Partitioning: Applications to Individual Compounds and Complex Mixtures of Neutral Organic Compounds.

The air-blood partition coefficient () is extensively employed in human health risk assessment for chemical exposure. However, current estimation approaches either require an extensive number of parameters or lack precision. In this study, we present two novel and parsimonious models to accurately estimate values for individual neutral organic compounds, as well as their complex mixtures.

Reliable prediction of sensory irritation threshold values of organic compounds using new models based on linear free energy relationships and GC×GC retention parameters.

The human sensory irritation threshold (SIT) is an important biochemical parameter for the exposure assessment of organic air pollutants. First, we recalibrated the Abraham solvation models (ASMs) for 9 SIT endpoints by curating 720 individual experimental SIT values to find an accurate and parsimonious ASM variant, which exhibited root mean square error (RMSE) = 0.174-0.

Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques.

In this modern world, we are accustomed to a constant stream of data. Major social media sites like Twitter, Facebook, or Quora face a huge dilemma as a lot of these sites fall victim to spam accounts. These accounts are made to trap unsuspecting genuine users by making them click on malicious links or keep posting redundant posts by using bots.

Quality of Life and Community Wellbeing of Members Associated With Village Savings and Loans Associations as a Model of Sharing Economy in the Least Developing Countries: A Case of Mzuzu City in Northern Malawi, Southern Africa.

This study was aimed at examining the impacts of the Sharing economy on the individual and community Quality of Life (QOL) and wellbeing by looking at their associated influencing factors using Village Savings and Loans Associations as a model of sharing economy in Malawi. An online community-based cross-sectional study design was conducted from November 2020 through January 2021. In the survey, 402 Village Savings and Loans Associations (VSLAs) members from the Mzuzu City area participated, recruited using snowball and respondent-driven sampling techniques.