One-click device for rapid visualization and extraction of latent evidence through multi-moding light source integration and light-guiding technology.

Visualizing latent evidence at a crime scene has gained popularity in the field of forensic science during the past few years. Thus, this study designs and develops a one-click device for the rapid visualization and extraction of latent evidence through multimodal light source integration and light-guiding technology. Our device exhibits multispectral and angle timing functions for storing the captured evidence images. Furthermore, the geometric registration, feature extraction, feature optimization, and feature integration of the evidence images are processed by a backend system, and the images are then presented. Overall, this study enhances the standard and the technical content of evidence extraction and simplifies the evidence extraction process. In addition to the rapid handling of the scenes captured at a crime scene, the one-click device has other notable advantages, such as fast imaging, portability, being independent of the environmental conditions and the operator's technical capabilities, and zero pollution to ensure the repeatability of material evidence extraction. Compared with the original optical forensics equipment, the spectrum and angle of our system are more extensive.

Classification modeling method for hyperspectral stamp-pad ink data based on one-dimensional convolutional neural network.

In the questioned document, the examination of stamp-pad ink is crucial scientific evidence to discern the difference between genuine and forged documents. In this study, a new method for rapid and non-destructive identification of types of stamp-pad inks by combining hyperspectral imaging (HSI) technology and deep learning was developed. Twenty stamp-pad inks of different brands and models were collected and numbered in turn, and then, each of them was sealed six times repeatedly on the A4 printing paper for the test. After that, the hyperspectral imager was used to collect the hyperspectral images and the reflectance spectral data were obtained after pixel fusion. Principal component analysis (PCA) and non-negative matrix factorization (NMF) were used to deal with the dataset, but visual results were not good. Then, back propagation neural network (BPNN) and one-dimensional convolutional neural network (1D-CNN) were constructed and their merits and drawbacks were compared. The final loss function of the BPNN of training set and validation set was stable at 0.27 and 0.42, and the classification accuracy of the training set and validation set reached 90.02% and 83.99%, respectively. Compared with the BPNN, the 1D-CNN had better stability and efficiency for the classification. The loss function of the training set and validation set was as low as 0.068 and 0.075, and the final classification accuracy reached 98.30% and 97.94%, respectively. Therefore, the combination of hyperspectral imaging technology and 1D-CNN represents a potentially simple, non-destructive, and rapid method for stamp-pad inks detection and classification.

Detection of morphine in urine based on a surface plasmon resonance imaging immunoassay.

Based on the surface plasmon resonance imaging (SPRi) technique, a new detection method for morphine in urine samples was developed. Sample labelling was not required, and qualitative and quantitative analysis could be completed in 20 minutes. According to an indirect competitive immunoassay, the mixture of morphine at different concentrations and morphine antibody at a certain concentration as the mobile phase was reacted with morphine BSA fixed on a chip surface in a competitive way. A calibration curve was obtained by correlating the signals generated from SPRi with the concentrations of morphine. By the addition of morphine to a blank urine sample, this method was confirmed to be feasible for the detection of morphine in actual urine. The limit of detection was as low as 9.59 ng mL-1. This method is fast and sensitive and can be applied in many fields.

[Research on Identification of Organic Gunshot Residue with Micro-Raman Spectroscopy].

A rapid approach for the nondestructive, accurate detection of organic gunshot residue was investigated. Raman microscopy was used to identify organic gunshot residue and the propellant in ammunition. The optimal excitation wavelength for the detection of organic particles using Raman spectroscopy was 473 nm. The Raman spectra of organic gunshot residue obtained using 473 nm laser excitation can effectively avoid the interference of fluorescence. The results demonstrated that the organic particles were mainly from the partially burned propellant particles. Meanwhile it was proved that the main component was basically consistent with the propellant except somehow damage in chemical structure or degree of crystallization with Raman spectra. The surface color of organic particles was mainly brassiness, dark gray. A lot of craters were distributed on the surface of organic particles. Spherical inorganic particles with metallic luster attached to the surface of organic particles can be regarded as the typical characteristics of gunshot residue.

Inherent Fluorescence Detection of Latent Fingermarks by Homemade Shortwave Ultraviolet Laser.

Detection of latent fingermarks on various substrates is critical in crime investigations. Conventional chemical methods using reagents could contaminate or even destruct biological information of samples. Here, an optical method and successful case application of detecting latent fingermarks through long-wave ultraviolet (UV) fluorescence (300-400 nm) by shortwave UV laser excitation is reported. Experimental results indicate that the recovery rate of the latent fingermarks on various paper items is in the range of 70-80% without chemical treatments. Moreover, the optical method allows for the preservation of samples for further examination, such as polymerase chain reaction (PCR) testing. The technique has also been successfully applied to a criminal case in identifying the suspect, which, to the best of our knowledge, has never been reported in real crime investigations. Therefore, such a method as UV-excited UV fluorescence in detecting latent fingermarks may be better for examination in cases where biological information of samples is needed for consequent testing.