13 Hydrogen safety, state of the art, perspectives, risk assessment, and engineering solutions

2021 ◽  
pp. 433-450
Author(s):  
Ciro Caliendo ◽  
Paola Russo ◽  
Paolo Ciambelli
Keyword(s):  
Risk Assessment ◽  
State Of The Art ◽  
Hydrogen Safety

scholarly journals PAH biomarkers for human health risk assessment: a review of the state-of-the-art

2008 ◽  
Vol 24 (suppl 4) ◽  
pp. a569-s580 ◽  
Author(s):  
Sérgio Silveira Franco ◽  
Adelaide Cássia Nardocci ◽  
Wanda Maria Risso Günther
Keyword(s):  
Risk Assessment ◽  
Health Risk ◽  
Human Health ◽  
Health Risk Assessment ◽  
State Of The Art ◽  
Human Health Risk ◽  
The State ◽  
Human Health Risk Assessment ◽  
Human Beings ◽  
Polycyclic Aromatic

Polycyclic aromatic hydrocarbons (PAH) are widely distributed in the environment, and some are carcinogenic to human beings. The study of biomarkers has helped clarify the nature and magnitude of the human health risks posed by such substances. This article provides a review of the state-of-the-art on PAH biomarkers for human health risk assessment and also discusses their applicability within the context of environmental management in Brazil. The article discusses the methodologies for determination of some biomarkers such as 1-hydroxypyrene and PAH-DNA adducts. Cytogenetic markers, frequency of chromosomal aberrations, and micronucleus induction were considered for the evaluation of cancer risk. The current stage of studies on validation of such biomarkers was also approached.

Conducting a state-of-the-art risk assessment of 1,3-butadiene

Toxicology ◽  
1996 ◽  
Vol 113 (1-3) ◽  
pp. 212-214
Author(s):  
Dennis J. Paustenbach
Keyword(s):  
Risk Assessment ◽  
State Of The Art

scholarly journals Suicide Risk Assessment via Temporal Psycholinguistic Modeling (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13873-13874
Author(s):  
Puneet Mathur ◽  
Ramit Sawhney ◽  
Rajiv Ratn Shah
Keyword(s):  
Risk Assessment ◽  
Suicide Risk ◽  
State Of The Art ◽  
Contextual Information ◽  
Suicide Risk Assessment ◽  
Automated Identification ◽  
Suicidal Intent ◽  
Social Media Platforms ◽  
Linguistic Phenomenon ◽  
Yield State

Social media platforms are increasingly being used for studying psycho-linguistic phenomenon to model expressions of suicidal intent in tweets. Most recent work in suicidal ideation detection doesn't leverage contextual psychological cues. In this work, we hypothesize that the contextual information embedded in the form of historical activities of users and homophily networks formed between like-minded individuals in Twitter can substantially improve existing techniques for automated identification of suicidal tweets. This premise is extensively tested to yield state of the art results as compared to linguistic only models, and the state-of-the-art model.

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