QSAR modeling of chronic rat toxicity of diverse organic chemicals

A Kumar, PK Ojha, K Roy - Computational Toxicology, 2023 - Elsevier
Chronic toxicity is one of the most important toxicological endpoints related to human health.
Since experimental tests are costly and difficult, in silico methods are crucial to assessing …

A machine learning study on a municipal solid waste-to-energy system for environmental sustainability in a multi-generation energy system for hydrogen production

Y Zhang, AJ Aldosky, V Goyal, MN Meqdad… - Process Safety and …, 2024 - Elsevier
Municipal solid waste (MSW)-to-energy systems have gained significant attention in recent
years for their potential to produce renewable energy from waste. These systems involve the …

First report on ecotoxicological QSTR and I-QSTR modeling for the prediction of acute ecotoxicity of diverse organic chemicals against three protozoan species

A Kumar, V Kumar, T Podder, PK Ojha - Chemosphere, 2023 - Elsevier
The recent years have witnessed an upsurge of interest to assess the toxicity of organic
chemicals exhibiting harmful impacts on the environment. In this investigation, we have …

Chronic aquatic toxicity assessment of diverse chemicals on Daphnia magna using QSAR and chemical read-across

A Kumar, V Kumar, PK Ojha, K Roy - Regulatory Toxicology and …, 2024 - Elsevier
We have modeled here chronic Daphnia toxicity taking pNOEC (negative logarithm of no
observed effect concentration in mM) and pEC 50 (negative logarithm of half-maximal …

The first report on the assessment of maximum acceptable daily intake (MADI) of pesticides for humans using intelligent consensus predictions

A Kumar, PK Ojha, K Roy - Environmental Science: Processes & …, 2024 - pubs.rsc.org
Direct or indirect consumption of pesticides and their related products by humans and other
living organisms without safe dosing may pose a health risk. The risk may arise after a …

Chemometric modeling of the lowest observed effect level (LOEL) and no observed effect level (NOEL) for rat toxicity

A Kumar, PK Ojha, K Roy - Environmental Science: Advances, 2024 - pubs.rsc.org
Humans and other living species of the ecosystem are constantly exposed to a wide range
of chemicals of natural as well as synthetic origin. A multitude of compounds exert profound …

Using data-driven learning methodology for a solid waste-to-energy scheme and developed regression analyses for performance prediction

L Peng, TR Alsenani, M Li, H Lin, HN Sabeh… - Process Safety and …, 2023 - Elsevier
Adopting innovative technologies like machine learning is crucial for achieving our
sustainability goals. It has great potential for improving waste management and energy …

Research on the effect of environmental regulation to the green water resource efficiency in China—based on the perspectives of high pressure and low suction

Z Pan, L Fu, XX Li, J Li, X Li, Y Peng, X Fu - Environmental Science and …, 2024 - Springer
Environmental regulation with spatial spillover effect is an important way to accelerate the
transformation and upgrading of modern water resources structure, and then achieve …

Purification and characterization of catechol 1, 2-dioxygenase (EC 1.13. 11.1; catechol-oxygen 1, 2-oxidoreductase; C12O) using the local isolate of phenol-degrading …

HR Tawfeeq, SS Al-Jubori, AH Mussa - Folia Microbiologica, 2024 - Springer
The purpose of the present study was to purify and characterize the catechol 1, 2-
dioxygenase (EC 1.13. 11.1; catechol-oxygen 1, 2-oxidoreductase; C12O) enzyme from the …

Application of Machine Learning Methods to Predict the Air Half-Lives of Persistent Organic Pollutants

Y Zhang, L Xie, D Zhang, X Xu, L Xu - Molecules, 2023 - mdpi.com
Persistent organic pollutants (POPs) are ubiquitous and bioaccumulative, posing potential
and long-term threats to human health and the ecological environment. Quantitative …