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Due to their user-friendliness and reliability, biometric systems have taken a central role in everyday digital identity management for all kinds of private, financial and governmental applications with increasing security requirements. A central security aspect of unsupervised biometric authentication systems is the presentation attack detection (PAD) mechanism, which defines the robustness to fake or altered biometric features. Artifacts like photos, artificial fingers, face masks and fake iris contact lenses are a general security threat for all biometric modalities. The Biometric Evaluation Center of the Institute of Safety and Security Research (ISF) at the University of Applied Sciences Bonn-Rhein-Sieg has specialized in the development of a near-infrared (NIR)-based contact-less detection technology that can distinguish between human skin and most artifact materials. This technology is highly adaptable and has already been successfully integrated into fingerprint scanners, face recognition devices and hand vein scanners. In this work, we introduce a cutting-edge, miniaturized near-infrared presentation attack detection (NIR-PAD) device. It includes an innovative signal processing chain and an integrated distance measurement feature to boost both reliability and resilience. We detail the device’s modular configuration and conceptual decisions, highlighting its suitability as a versatile platform for sensor fusion and seamless integration into future biometric systems. This paper elucidates the technological foundations and conceptual framework of the NIR-PAD reference platform, alongside an exploration of its potential applications and prospective enhancements.
In this work, the surface reactions of the homemade explosive triacetone triperoxide on tungsten oxide (WO3) sensor surfaces are studied to obtain detailed information about the chemical reactions taking place. Semiconductor gas sensors based on WO3 nanopowders are therefore produced and characterized by scanning electron microscopy, X-ray diffraction, and Raman spectroscopy. To analyze the reaction mechanisms at the sensor surface, the sensor is monitored online under operation conditions using Raman spectroscopy, which allows to identify the temperature-dependent sensor reactions. By combining information from the Raman spectra with data on the changing resistivity of the underlying semiconductor, it is possible to establish a correlation between the adsorbed gas species and the physical properties of the WO3 layer. In the results, it is indicated that a Lewis acid–base reaction is the most likely mechanism for the increase in resistance observed at temperatures below 150 °C. In the results, at higher temperatures, the assumption of a radical mechanism that causes a decrease in resistance is supported.
The human gut microbiota harbors untapped potential for biotechnological applications. Within the phylum of Bacteroidota, Phocaeicola vulgatus stands out as a promising candidate for sustainable production of key platform chemicals like succinate. However, genetic engineering of Phocaeicola sp. remains challenging due to its intricate molecular landscape. This study lays the groundwork for manipulating the central carbon pathways in Phocaeicola vulgatus, offering insights into overcoming genetic hurdles for increased succinate yields.
A Fourier scatterometry setup is evaluated to recover the key parameters of optical phase gratings. Based on these parameters, systematic errors in the printing process of two-photon polymerization (TPP) gray-scale lithography three-dimensional printers can be compensated, namely tilt and curvature deviations. The proposed setup is significantly cheaper than a confocal microscope, which is usually used to determine calibration parameters for compensation of the TPP printing process. The grating parameters recovered this way are compared to those obtained with a confocal microscope. A clear correlation between confocal and scatterometric measurements is first shown for structures containing either tilt or curvature. The correlation is also shown for structures containing a mixture of tilt and curvature errors (squared Pearson coefficient r2 = 0.92). This compensation method is demonstrated on a TPP printer: a diffractive optical element printed with correction parameters obtained from Fourier scatterometry shows a significant reduction in noise as compared to the uncompensated system. This verifies the successful reduction of tilt and curvature errors. Further improvements of the method are proposed, which may enable the measurements to become more precise than confocal measurements in the future, since scatterometry is not affected by the diffraction limit.
The development of whole-genome amplification (WGA) techniques has opened up new avenues for genetic analysis and genome research, in particular by facilitating the genome-wide analysis of few or even single copies of genomic DNA, such as from single cells (prokaryotic or eukaryotic) or virions. Using WGA, the few copies of genomic DNA obtained from such entities are unspecifically amplified using PCR or PCR-related processes in order to obtain higher DNA quantities that can then be successfully analysed further.
Forensic DNA profiles are established by multiplex PCR amplification of a set of highly variable short tandem repeat (STR) loci followed by capillary electrophoresis (CE) as a means to assign alleles to PCR products of differential length. Recently, CE analysis of STR amplicons has been supplemented by high-throughput next generation sequencing (NGS) techniques that are able to detect isoalleles bearing sequence polymorphisms and allow for an improved analysis of degraded DNA. Several such assays have been commercialised and validated for forensic applications. However, these systems are cost-effective only when applied to high numbers of samples. We report here an alternative, cost-efficient shallow-sequence output NGS assay called maSTR assay that, in conjunction with a dedicated bioinformatics pipeline called SNiPSTR, can be implemented with standard NGS instrumentation. In a back-to-back comparison with a CE-based, commercial forensic STR kit, we find that for samples with low DNA content, with mixed DNA from different individuals, or containing PCR inhibitors, the maSTR assay performs equally well, and with degraded DNA is superior to CE-based analysis. Thus, the maSTR assay is a simple, robust and cost-efficient NGS-based STR typing method applicable for human identification in forensic and biomedical contexts.
Robust Identification and Segmentation of the Outer Skin Layers in Volumetric Fingerprint Data
(2022)
Despite the long history of fingerprint biometrics and its use to authenticate individuals, there are still some unsolved challenges with fingerprint acquisition and presentation attack detection (PAD). Currently available commercial fingerprint capture devices struggle with non-ideal skin conditions, including soft skin in infants. They are also susceptible to presentation attacks, which limits their applicability in unsupervised scenarios such as border control. Optical coherence tomography (OCT) could be a promising solution to these problems. In this work, we propose a digital signal processing chain for segmenting two complementary fingerprints from the same OCT fingertip scan: One fingerprint is captured as usual from the epidermis (“outer fingerprint”), whereas the other is taken from inside the skin, at the junction between the epidermis and the underlying dermis (“inner fingerprint”). The resulting 3D fingerprints are then converted to a conventional 2D grayscale representation from which minutiae points can be extracted using existing methods. Our approach is device-independent and has been proven to work with two different time domain OCT scanners. Using efficient GPGPU computing, it took less than a second to process an entire gigabyte of OCT data. To validate the results, we captured OCT fingerprints of 130 individual fingers and compared them with conventional 2D fingerprints of the same fingers. We found that both the outer and inner OCT fingerprints were backward compatible with conventional 2D fingerprints, with the inner fingerprint generally being less damaged and, therefore, more reliable.
The following work presents algorithms for semi-automatic validation, feature extraction and ranking of time series measurements acquired from MOX gas sensors. Semi-automatic measurement validation is accomplished by extending established curve similarity algorithms with a slope-based signature calculation. Furthermore, a feature-based ranking metric is introduced. It allows for individual prioritization of each feature and can be used to find the best performing sensors regarding multiple research questions. Finally, the functionality of the algorithms, as well as the developed software suite, are demonstrated with an exemplary scenario, illustrating how to find the most power-efficient MOX gas sensor in a data set collected during an extensive screening consisting of 16,320 measurements, all taken with different sensors at various temperatures and analytes.
Modern PCR-based analytical techniques have reached sensitivity levels that allow for obtaining complete forensic DNA profiles from even tiny traces containing genomic DNA amounts as small as 125 pg. Yet these techniques have reached their limits when it comes to the analysis of traces such as fingerprints or single cells. One suggestion to overcome these limits has been the usage of whole genome amplification (WGA) methods. These methods aim at increasing the copy number of genomic DNA and by this means generate more template DNA for subsequent analyses. Their application in forensic contexts has so far remained mostly an academic exercise, and results have not shown significant improvements and even have raised additional analytical problems. Until very recently, based on these disappointments, the forensic application of WGA seems to have largely been abandoned. In the meantime, however, novel improved methods are pointing towards a perspective for WGA in specific forensic applications. This review article tries to summarize current knowledge about WGA in forensics and suggests the forensic analysis of single-donor bioparticles and of single cells as promising applications.
Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy
(2022)
As the identification of microorganisms becomes more significant in industry, so does the utilization of microspectroscopy and the development of effective chemometric models for data analysis and classification. Since only microorganisms cultivated under laboratory conditions can be identified, but they are exposed to a variety of stress factors, such as temperature differences, there is a demand for a method that can take these stress factors and the associated reactions of the bacteria into account. Therefore, bacterial stress reactions to lifetime conditions (regular treatment, 25 °C, HCl, 2-propanol, NaOH) and sampling conditions (cold sampling, desiccation, heat drying) were induced to explore the effects on Raman spectra in order to improve the chemometric models. As a result, in this study nine food-relevant bacteria were exposed to seven stress conditions in addition to routine cultivation as a control. Spectral alterations in lipids, polysaccharides, nucleic acids, and proteins were observed when compared to normal growth circumstances without stresses. Regardless of the involvement of several stress factors and storage times, a model for differentiating the analyzed microorganisms from genus down to strain level was developed. Classification of the independent training dataset at genus and species level for Escherichia coli and at strain level for the other food relevant microorganisms showed a classification rate of 97.6%.