AIMC Topic: Benzene

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Design and Performance Evaluation of Machine Learning-Based Terahertz Metasurface Chemical Sensor.

IEEE transactions on nanobioscience Mar 26, 2025
This paper presents a terahertz metasurface based sensor design incorporating graphene and other plasmonic materials for highly sensitive detection of different chemicals. The proposed sensor employs the combination of multiple resonator designs - in...
Machine Learning Benzene Ethanol Graphite Terahertz Spectroscopy Equipment Design Surface Plasmon Resonance
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Genomic and algorithm-based predictive risk assessment models for benzene exposure.

Frontiers in public health Jan 21, 2025
AIM: In this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.
Benzene Occupational Exposure Genomics Animals Risk Assessment Mice Humans Machine Learning Algorithms
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The Influence of Blood Titanium Levels on DNA Damage in Brazilian Workers Occupationally Exposed to Different Chemical Agents.

Biological trace element research Dec 18, 2024
Occupational exposure to pollutants may cause health-damaging effects in humans. Genotoxicity assays can be used to detect the toxic effects of pollutants. In the present study, we evaluated genetic damage in three populations occupationally exposed ...
Male Middle Aged Brazil Humans Biomarkers Adult Titanium Sorbic Acid Comet Assay Pyrenes Benzene Occupational Exposure DNA Damage
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Data-driven predictive modeling of PM concentrations using machine learning and deep learning techniques: a case study of Delhi, India.

Environmental monitoring and assessment Nov 3, 2022
The present study intends to use machine learning (ML) and deep learning (DL) models to forecast PM concentration at a location in Delhi. For this purpose, multi-layer feed-forward neural network (MLFFNN), support vector machine (SVM), random forest ...
Machine Learning Air Pollutants Air Pollution Particulate Matter Deep Learning Benzene Environmental Monitoring
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Kriging-Based Land-Use Regression Models That Use Machine Learning Algorithms to Estimate the Monthly BTEX Concentration.

International journal of environmental research and public health Sep 23, 2020
This paper uses machine learning to refine a Land-use Regression (LUR) model and to estimate the spatial-temporal variation in BTEX concentrations in Kaohsiung, Taiwan. Using the Taiwanese Environmental Protection Agency (EPA) data of BTEX (benzene, ...
Machine Learning Algorithms Benzene Humans Toluene Xylenes Benzene Derivatives Environmental Monitoring Taiwan Air Pollutants
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Mesoporous cobalt monoxide-supported platinum nanoparticles: Superior catalysts for the oxidative removal of benzene.

Journal of environmental sciences (China) Dec 9, 2019
Mesoporous CoO (meso-CoO)-supported Pt (0.53 wt.% Pt/meso-CoO) was synthesized via the KIT-6-templating and polyvinyl alcohol (PVA)-assisted reduction routes. Mesoporous CoO (meso-CoO) was fabricated through in situ reduction of meso-CoO with glycero...
Platinum Metal Nanoparticles Cobalt Models, Chemical Oxidative Stress Benzene
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Bluetooth gas sensing module combined with smartphones for air quality monitoring.

Chemosphere Apr 26, 2018
This study addresses the development of a miniaturized (60 × 60 mm) Wireless Sensing Module (WSM) for environmental application and air quality detection. The proposed prototype has six sensors: one for humidity, one for ambient temperature (SHT21 fr...
Gases Xylenes Smartphone Benzene Environmental Monitoring Acetone Toluene Air Pollution Formaldehyde Neural Networks, Computer Algorithms
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Self-Taught Learning Based on Sparse Autoencoder for E-Nose in Wound Infection Detection.

Sensors (Basel, Switzerland) Oct 7, 2017
For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning comb...
Diagnostic Equipment Acetone Wound Infection Electronic Nose Machine Learning Reproducibility of Results Formaldehyde Discriminant Analysis Benzene Ethanol
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Classification of nervous system withdrawn and approved drugs with ToxPrint features via machine learning strategies.

Computer methods and programs in biomedicine Feb 9, 2017
BACKGROUND AND OBJECTIVES: Early-phase virtual screening of candidate drug molecules plays a key role in pharmaceutical industry from data mining and machine learning to prevent adverse effects of the drugs. Computational classification methods can d...
Humans Safety-Based Drug Withdrawals Area Under Curve Algorithms Drug Monitoring Pharmaceutical Preparations Product Surveillance, Postmarketing Linear Models Nervous System Pattern Recognition, Automated Benzene Ethylamines Data Mining Support Vector Machine False Positive Reactions Toluene Carbon Drug Approval Patient Safety Risk Computer Simulation Sensitivity and Specificity
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[Establishment of New Zealand rabbit models of aplastic anemia].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Dec 20, 2017
OBJECTIVE: To screen for the optimal dose of benzene and cyclophosphamide using an orthogonal design for establishment of New Zealand rabbit models of aplastic anemia.
Benzene Disease Models, Animal Bone Marrow Animals Blood Cell Count Anemia, Aplastic Bone Marrow Examination Rabbits Cyclophosphamide
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