Life Sciences Discovery and Technology Highlights

Latent fingerprints are one of the most valuable and unique biometric attributes that are extensively used in forensic and law enforcement applications. Compared to rolled/plain fingerprint, latent fingerprint is of poor quality in term of friction ridge patterns, hence a more challenging for automatic fingerprint recognition systems. Considering the difficulties of dusting, lifting, and recovery of latent fingerprint, this type of fingerprints remain expensive to develop and collect. In this paper, we present a novel approach for synthetic latent fingerprint generation using Generative Adversarial Network (GAN). Our proposed framework, named mask to latent fingerprint (Mask2LFP), uses binary mask of distorted fingerprint-like shapes as input, and outputs a realistic latent fingerprint. This work focuses on the generation of synthetic latent fingerprints. The aim is to alleviate the scarcity issue of latent fingerprint data and serve the increasing need for developing, evaluating, and enhancing fingerprint-based identification systems, especially in forensic applications.

Fingerprints generally deposited involuntarily on a surface and that usually require special chemical procedures to become visible are called latent fingerprints. These fingerprints have a relevant role in identifying individuals in forensic applications. In many cases, latent fingerprint images are inherently noisy, exhibit perturbations produced by their forming mechanism, and convey limited information, which requires enhancement procedures to improve the identification result. However, most existing methods successfully used to enhance fingerprints collected in controlled environments do not perform as well on latent fingerprints. In this research, we propose a latent fingerprint enhancement method based on a deep learning model that consists of a residual encoder-decoder architecture that optimizes a frequency-domain loss function during training. In addition, a procedure for synthetically generating a large set of labeled training data has been developed. Experiments with the MOLF database have shown that our proposed method improved the quality of fingerprints and resulted in better minutiae extraction, thus improving fingerprint identification performance. Compared with other methods published in the literature, the proposed method achieved better accuracies in ranks 1 to 30 according to CMC curves.

Latent fingerprint identification is a challenging task in criminal investigation due to the poor quality of ridge impressions and less region of interest on the fingerprint. In this paper, we propose a semi-automated latent fingerprint identification to markup fingerprint landmarks manually using the image enhancement filters which will improve the identification performance in lights-out mode. It uses the global and local adaptive binarization, and global minutia features with ISO/IEC 19794-2 standard fingerprint templates. In the latent fingerprint identification, the fingerprints are matched with rolled fingerprint database from standard law enforcement database. Also, the latent fingerprints are matched with the plain fingerprints database from the data collected using three different live-scanners. The efficacy of the proposed latent fingerprint identification systems is demonstrated on the standard NIST SD-27 (special database-27) latent prints database.

Evaluation of DFO/PVP and its application to latent fingermarks development on thermal paper

Optically-encoded probes have great potential for applications in the fields of biosensing and imaging. By employing specific encoding methods, these probes enable the detection of multiple target molecules and high-resolution imaging within the same sample. Among the various encoding methods, surface-enhanced Raman scattering (SERS) spectral encoding stands out due to its extremely narrow linewidth. Compared to fluorescence spectral encoding, SERS encoding significantly reduces crosstalk between adjacent peaks, thereby achieving a larger encoding capacity and enabling multi-channel parallel analysis. This article presents the design and construction of two novel sets of SERS-encoded probes based on noble metal core-shell nanostructures. Two different encoding strategies are successfully applied to encode the SERS spectra of the probes: 1D encoding based on the wavenumber of characteristic peaks in the SERS spectrum, and 2D encoding combining both wavenumber and intensity of characteristic peaks in the SERS spectrum. In addition, this study also demonstrates the potential application of 1D encoded probes in cell sorting. These studies verify the feasibility of applying these two encoding methods to SERS core-shell probes and provide new insights into the construction of optically encoded probes.

Sample preparation is often the most tedious and demanding step in an assay, but it also plays an essential role in determining the quality of results. As biological questions and analytical methods become increasingly sophisticated, there is a rapidly growing need for systems that can reliably and reproducibly separate cells and particles with high purity, throughput and recovery. Microfluidics technology represents a compelling approach in this regard, allowing precise control of separation forces for high performance separation in inexpensive, or even disposable, devices. In addition, microfluidics technology enables the fabrication of arrayed and integrated systems that operate either in parallel or in tandem, in a capacity that would be difficult to achieve in macro-scale systems. In this report, we use recent examples from our work to illustrate the potential of microfluidic cell- and particle-sorting devices. We demonstrate the potential of chip-based high-gradient magnetophoresis that enable high-purity separation through reversible trapping of target particles paired with high-stringency washing with minimal loss. We also describe our work in the development of devices that perform simultaneous multi-target sorting, either through precise control of magnetic and fluidic forces or through the integration of multiple actuation forces into a single monolithic device. We believe that such devices may serve as a powerful "front-end" module of highly integrated analytical platforms capable of providing actionable diagnostic information directly from crude, unprocessed samples - the success of such systems may hold the key to advancing point-of-care diagnostics and personalized medicine.

Copper vapor lasers are being used in forensic applications at more than thirty regional, state and national level forensic science laboratories (crime labs) in the United States, Israel and Japan. These high gain lasing medium systems provide desirable operational and maintenance features. The green line produced by copper vapor lasers allows use of latent fingerprint inherent and chemically induced luminescence techniques developed for argon ion lasers. The yellow line has developed latent fingerprints which would not luminesce at blue-green wavelengths, and is better suited for some forensic examinations such as ink differentiation involving forgeries and document alterations.

Exposure to light or heat, or simply a dearth of fingerprint material, renders some latent fingerprints undetectable using conventional methods. We begin to address such elusive fingerprints using detection targeting photo- and thermally stable fingerprint constituents: surface-enhanced Raman spectroscopy (SERS). SERS can give descriptive vibrational spectra of amino acids, among other robust fingerprint constituents, and good sensitivity can be attained by improving metal-dielectric nanoparticle substrates. With SERS chemical imaging, vibrational bands' intensities recreate a visual of fingerprint topography. The impact of nanoparticle synthesis route, dispersal methodology-deposition solvent, and laser wavelength are discussed, as are data from enhanced vibrational spectra of fingerprint components. SERS and Raman chemical images of fingerprints and realistic contaminants are shown. To our knowledge, this represents the first SERS imaging of fingerprints. In conclusion, this work progresses toward the ultimate goal of vibrationally detecting latent prints that would otherwise remain undetected using traditional development methods.

A novel method for improving the detection limit of normal Raman spectra of chemicals using a micro-Raman system and pico-liters volume is presented. A micro-cavity substrate uses various mechanisms that collectively improve the normal Raman signal from the sample without surface-enhanced Raman scattering (SERS) enhancement. The microcavity substrate enhances the entire Raman spectra of the molecules under investigation and maintains the relative intensity ratios of the various Raman bands. This feature of maintaining the overall integrity of the Raman features during signal enhancement makes the micro-cavity substrate ideal for forensic science applications requiring chemical detection of residual traces and other applications requiring low sample volumes and concentrations. It will be further shown that micro-cavities coated with nano films of gold and silver takes advantage of both SERS and micro-cavity method and significantly improve the detection limits of samples.

In this work the highly sensitive molecule recognition performance of a specially designed surface enhanced Raman scattering (SERS) substrate was demonstrated. The general inverse pyramid structures were modified to be able to perform as cavities in perforated membrane applicable for particle and cell filtering, sorting and trapping. In the voids of the gold covered substrate size compatible particles functionalised by different molecules were trapped, their SERS signal was detected and the different molecules were recognised.

Development of highly thermal-stable blue emitting Y4Al2O9:Bi3+ phosphors for w-LEDs, fingerprint and data security applications

Development of reddish orange-emitting Y2Sn2O7:Eu3+phosphors for latent fingerprint detection and anti-counterfeit security ink

Latent fingerprint detection and visualization remains a challenge especially where problems of poor contrast, auto-fluorescent surfaces and patterned backgrounds are encountered. As a result there is an increasing interest in the development of simple, cost effective, rapid and yet accurate methods for latent fingerprint detection and recovery. Herein, this paper reports the synthesis of bright blue photoluminescent carbon dots (C-dots) via an eco-friendly and simple one-step microwave-assisted carbonization of potato peels’ biomass. The C-dots were prepared in only 3 min and ground into powder and used without any further treatment. The as-prepared C-dots were characterized using atomic force microscope, Fourier transform infra-red spectroscopy and X-ray diffraction with an average size of 1.0[Formula: see text]nm. The optical properties of the as-prepared C-dots were studied by UV-Vis spectroscopy and spectrofluorometer which established an excitation and emission wavelengths of 390[Formula: see text]nm and 480[Formula: see text]nm, respectively. Owing to their strong solid state fluorescence, the as-prepared C-dots’ powder was successfully used in latent fingerprint detection and imaging on porous and nonporous surfaces. Latent fingerprints were recovered with high resolution and excellent quality providing sufficient details for individual identification. These findings demonstrate that C-dots derived from biomass have a great potential in latent fingerprint analysis for forensic applications.

Cell elasticity measurement and sorting based on microfluidic techniques: advances and applications

SATS@CdTe hierarchical structures emitting green to red colors developed for latent fingerprint applications