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Benzene

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Genomic and algorithm-based predictive risk assessment models for benzene exposure.

Frontiers in public health
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.

Mesoporous cobalt monoxide-supported platinum nanoparticles: Superior catalysts for the oxidative removal of benzene.

Journal of environmental sciences (China)
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...

[Establishment of New Zealand rabbit models of aplastic anemia].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
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.

Self-Taught Learning Based on Sparse Autoencoder for E-Nose in Wound Infection Detection.

Sensors (Basel, Switzerland)
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...

Bluetooth gas sensing module combined with smartphones for air quality monitoring.

Chemosphere
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...

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
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, ...

Data-driven predictive modeling of PM concentrations using machine learning and deep learning techniques: a case study of Delhi, India.

Environmental monitoring and assessment
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 ...

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

IEEE transactions on nanobioscience
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...