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The efficient development of latent fingerprint (LFP) is attractively important for criminal investigation. The low-cost and high-contrast developer is still a challenge. In this study, we designed and synthesized dicyanomethylene-4H-pyran (DCM) derivatives PZ-DCM and Boc-PZ-DCM by introducing of large steric hindrance group Boc, the solid-state fluorescence of DCM derivatives was greatly enhanced. The low-cost fluorescent LFP developers were prepared by blending with different proportion of montmorillonite (MMT). As a result, clear and high contrast fingerprint patterns were obtained with dusting method by the developer with 3% content of Boc-PZ-DCM. Furthermore, we employed the developer with 3% content of Boc-PZ-DCM to develop the sweat latent fingerprints on different substrates by powder dusting, and collected clear fingerprint patterns, indicating that the developer is universal. In a word, the Boc-PZ-DCM/MMT powder is a promising candidate for LFP developer.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315918 | PMC |
http://dx.doi.org/10.3389/fchem.2022.943925 | DOI Listing |
Analyst
September 2025
School of Chemical Sciences, Indian Institute of Technology, Mandi, Himachal Pradesh 175005, India.
An imino-linked dansyl-carbazole molecular system, DASH, is designed and synthesized. This system (DASH) is rationalized in such a way that it works as a suitable template for the detection of date rape drugs, gamma-butyrolactone (GBL) and gamma-valerolactone (GVL), in addition to latent fingerprint detection. Both rape drug and latent fingerprint detection are important aspects of drug abuse-related crimes in forensic analysis.
View Article and Find Full Text PDFJ Forensic Leg Med
August 2025
Laboratory of Criminalistics, Adam Mickiewicz University in Poznań, al. Niepodległości 53, Poznań 61-714, Poland; Center for Advanced Technologies, Adam Mickiewicz University in Poznań, ul. Uniwersytetu Poznańskiego 10, Poznań 61-614, Poland.
This study examines the reliability of fingerprint experts in assessing the individualization value of minutiae during the analysis of latent fingerprint traces. Despite the widespread use of fingerprint evidence in criminal investigations, growing concerns about examiner variability and the lack of verification protocols have prompted critical scrutiny of forensic practices. In this study, 30 Polish fingerprint experts were asked to identify and evaluate seven minutiae in two fingerprint traces of differing quality.
View Article and Find Full Text PDFFront Digit Health
August 2025
Architecture Laboratory, Graduate School of Science, Technology and Innovation, Kobe University, Kobe, Japan.
Background: Microwave Doppler sensors, capable of detecting minute physiological movements, enable the measurement of biometric information, such as walking patterns, heart rate, and respiration. Unlike fingerprint and facial recognition systems, they offer authentication without physical contact or privacy concerns. This study focuses on non-contact seismocardiography using microwave Doppler sensors and aims to apply this technology for biometric authentication.
View Article and Find Full Text PDFMater Horiz
September 2025
College of Science, Henan Agricultural University, 63 Agricultural Road, Zhengzhou 450002, Henan, P. R. China.
Latent fingerprints (LFPs), as critical carriers of personal identification information, present a long-standing challenge for high-resolution imaging in forensic science. Aggregation-induced emission luminogens (AIEgens), known for their superior luminescence in aggregated or high-viscosity environments, have emerged as ideal candidates for high-contrast fingerprint visualization. In this study, we designed a series of novel AIEgens by introducing diphenylamine (DPA) donor groups at the 3- and 11-positions of a quinazolinone core, effectively constructing twisted intramolecular charge transfer (TICT) systems.
View Article and Find Full Text PDFJ Cheminform
August 2025
LAQV and REQUIMTE, Chemistry Department, NOVA School of Science and Technology, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal.
Molecular representations of chirality, derived from latent space vectors (LSVs) of SMILES heteroencoders, were explored to train machine learning models to predict chiral properties, and were compared to conventional circular fingerprints. Latent space arithmetic was applied to enhance the representation of chirality, by calculating differences between the original descriptor of a molecule and the descriptor of its enantiomer, or the difference between the original descriptor and the descriptor obtained with the stereochemistry-depleted SMILES string. Machine learning was performed with the Random Forest algorithm applied to a dataset of 3858 molecules extracted from the literature (1929 pairs of enantiomers) to predict the elution order observed on the Chiralpak® AD-H column, as well as intrinsic structural chirality labels (R/S or canonical SMILES @/@@).
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