Results 211 to 220 of about 4,164,406 (399)
On the (mis)calculation of forensic science error rates. [PDF]
Proc Natl Acad Sci U S A, 2022 Kukucka J.
europepmc +1 more source
Automated processing of shoeprint images based on the Fourier transform for use in forensic science [PDF]
, 2005 Philip de Chazal +2 more
openalex +1 more source
Categorization and Labeling of Red Variations in Lip Makeup
Color Research &Application, EarlyView.ABSTRACT The color cosmetic industry lacks a standardized and universally accepted system for practical color communication, posing significant challenges. This study addresses these challenges by categorizing and labeling variations of red in lip makeup.
Boram Kim +3 more
wiley +1 more source
Теория и практика судебной экспертизы, 2016 Issue 38 of the Information Bulletin presents summaries of methodologies published in 2015–2016 and recommended by the RFCFS Research Methodology Board for use by state forensic experts in their regular practice within the system of forensic science ...
N. V. Mikhaleva
doaj
An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science. [PDF]
Toxics, 2023 Fairman K +6 more
europepmc +1 more source
Application of Mitochondrial DNA for Cytochrome b Gene to Species Identification in Forensic Science
, 1999 Shin‐ichi Nakaki +2 more
openalex +2 more sources
Clinical Pharmacology &Therapeutics, EarlyView.An unimpaired neurological evaluation is essential for detecting delayed cerebral ischemia (DCI) in aneurysmal subarachnoid hemorrhage (aSAH) patients. Nimodipine is currently the only drug approved for DCI prevention. Intravenous nimodipine infusion contains 23.7 vol% ethanol as an excipient, resulting in up to 45 g of ethanol being infused daily ...
Miriam M. Moser +8 more
wiley +1 more source
Broadening the application of forensic science in an era of standardization. [PDF]
Forensic Sci Res, 2022 Congram D, Finegan O.
europepmc +1 more source
Bayesian Networks and Probabilistic Inference in Forensic Science [PDF]
, 2006 Franco Taroni +3 more
openalex +1 more source
The Promise and Pitfalls of Artificial Intelligence in the Evaluation of Synthetic “Greenness”
ChemSusChem, EarlyView.Rapid rise of AI prompts a question whether it can be used to accelerate and standardize assessment of synthetic “greenness.” This perspective argues for the potential of such applications, although it also identifies several hurdles, like the need for extensive training or the creation of “ground truth” datasets.
Paweł Mateusz Nowak +3 more
wiley +1 more source