Comparison Of Fingerprints Research Articles

Eco and user–friendly curcumin based nanocomposite forensic powder from coal fly ash for latent fingerprint detection in crime scenes

In this study, the production of an eco-friendly curcumin based nanocomposite fingerprint labeling powder is reported for the first time. This powder was prepared from thermal power plant waste known as coal fly ash. 3-aminopropyltrimethoxysilane (APTMS) was covalently interacted with coal fly ash (CFA/APTMS) and curcumin (CUR) was encapsulated onto CFA/APTMS to give a novel and eco-friendly CFA/APTMS/CUR nanocomposite for LFPs detection with the powder dusting method. Several instrumental techniques including Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), UV–visible spectroscopy, fluorescence spectroscopy (FL), scanning electron microscopy (SEM), energy-dispersive X-ray spectrometry (EDS), and transmission electron microscopy (TEM) were used to characterize this nanocomposite. The CFA/APTMS/CUR nanocomposite was applied as a forensic powder for the development of latent fingerprint (LFPs) images on various porous and non-porous substrates. Level 2 (island, origination, bifurcation, termination, fork, dot, and bridge) and Level 3 (sweat pores and shape of triangles, round, and irregular) were the features of the LFP images. Under visible light conditions, the aging LFPs images were clearly detected on an aluminum foil surface using the nanocomposite powder, which had good sensitivity and minimal background interference. Additionally, LFPs images were developed using CFA/APTMS/CUR nanocomposite on leather substrates for belts and shoes in order to confirm the benefits of the nanocomposite's high sensitivity. This nanocomposite improved LFPs images with unique patterns and showed excellent performance on a variety of surfaces for the development of LFPs. These findings therefore proved that the powdered CFA/APTMS/CUR nanocomposite can be effectively utilized for the development of LFPs images at important crime scenes and for the biometric identification of criminal suspects through fingerprint comparison.

Decreasing the Uncertainty in the Comparison of Molecular Fingerprints of Organic Aerosols with H/D Exchange Mass Spectrometry.

High-resolution mass spectrometry (HRMS) has become an indispensable tool in the characterization of organic aerosols (OA) providing information on air quality, health assessment, climate trends, reactions, and source apportionment. Spectra-derived lists of formulas and their relative abundances are used to compare ambient OA from different sources or to monitor secondary OA formation under controlled laboratory conditions in smog chamber experiments. Various techniques are implemented to visualize common and unique features, series of precursors, and products. The disadvantage of this conventional approach is in associating elemental compositions to specific compounds, while due to several analytical limitations, the structural information remains hidden. We argue that some of the conclusions derived from this data analysis can be misleading. In this study, we applied in-ESI source H/D exchange (HDX), which facilitated enumeration of labile protons in molecules behind elemental compositions of OA. We applied this technique to compare OA from three different locations representing urban, forest, and marine environments and to examine tentative chemical information derived from Kendrick mass defect (KMD) series analysis. Significant discrepancies were found between numbers of labile protons in protogenic functional groups and the stoichiometry of chemical reactions, which are associated with KMD series. Only a portion of chemical pairs matched target stoichiometries, which highlights the existing limitations in environmental applications of conventional formula-based HRMS data interpretation strategies.

Investigation of electrochemical fingerprints for Buzhong Yiqi Tang extract granules using diamond-graphene composite electrode

This study presents a novel electrochemical fingerprinting method for Buzhong Yiqi Tang extract granules using a diamond-graphene composite electrode. The electrode was fabricated through chemical vapor deposition of graphene on high-pressure high-temperature synthetic diamond, resulting in a few-layer graphene coating as confirmed by Raman spectroscopy (I₂D/IG ratio ≈ 1.2) and XPS analysis (78 % sp² C-C signal). Cyclic voltammetry revealed four anodic and three cathodic peaks, while differential pulse voltammetry provided enhanced resolution with eight distinct oxidation peaks. The method demonstrated high sensitivity (LODs 0.08–0.15 mg/mL) and good linearity (R² > 0.995) over a concentration range of 0.5–10 mg/mL. Comparison of fingerprints from individual herb extracts (Astragalus membranaceus, Panax ginseng, and Glycyrrhiza uralensis) elucidated the origins of major peaks in the Buzhong Yiqi Tang profile. Principal component analysis of fingerprints successfully differentiated between samples from three manufacturers, accounting for 87.3 % of total variance. Strong correlations (r > 0.92) were observed between key DPV peak intensities and HPLC-determined concentrations of traditional chemical markers. The rapid analysis time, minimal sample preparation, and holistic representation of multiple electroactive components make this approach a promising complement to existing chromatographic methods for quality assessment of traditional Chinese medicine formulations.

Automated Fingerprint Identification System

Abstract: AFIS is regarded as one of the greatest advancements in biometric systems as it enables fast and efficient identification of an individual by their distinct fingerprint designs. This system employs the use of digital imaging, finger-power techniques and other technologies in the storage and comparison of fingerprints. With AFIS, fingerprint images are all digitized making it easier to carry out crime investigations, border control and general identification of persons. The strength of AFIS systems is evidenced by the increased accuracy levels along with the capacity to accommodate numerous records and still allow for fast searches by fingerprinting matching to existing images for law enforcement on file. Some problems nevertheless persist which include the quality of fingerprints and environmental interferences, however machine learning and artificial intelligence improvements are still being incorporated into the systems to make them work even better. This paper investigates the system architecture and components, operational aspects, and prospects for development of the AFIS technology, which is essential in contemporary informational security

Jack of all trades, master of one: domain-specific and domain-general contributions to perceptual expertise in visual comparison

Perceptual expertise is typically domain-specific and rarely generalises beyond an expert’s domain of experience. Forensic feature-comparison examiners outperform the norm in domain-specific visual comparison, but emerging research suggests that they show advantages on other similar tasks outside their domain of expertise. For example, fingerprint examiners not only outperform novices in fingerprint comparison, but also in face comparison. Yet, the extent to which their skills generalise is poorly understood. In this study, we investigated the generalisability of perceptual expertise amongst forensic examiners by comparing their performance to novices and other examiners within and outside their area of expertise. We recruited 85 experts from three forensic disciplines (face, fingerprint, and firearms) and asked them to complete four different visual comparison tasks: faces, fingerprints, firearms, and novel-objects. Examiners displayed domain-specific expertise: they outperformed novices and other examiners within their domain of visual comparison expertise. Yet, some of their skill also generalised: examiners also outperformed novices outside their area of expertise. However, while individual differences in examiners’ performance within their domain of experience were associated with their performance in a novel comparison task, they were not related to their performance on tasks outside their expert domain. These results provide key insight into the domain-specific and domain-general contributions of forensic examiners’ perceptual expertise. Forensic expertise lends some generalisable skill to other visual comparison tasks, but best performance is still seen within examiners’ domain of expertise.

Examiner consistency in perceptions of fingerprint minutia rarity

Friction ridge examiners (FREs) identify distinctive features (minutiae) in fingerprints and consider how rare these observed minutiae are in their decisions about both the value of a fingerprint and whether there is enough correspondence between two fingerprints to support an “identification” or “exclusion” decision. But subjective perceptions about the frequency of events and features tend to be inconsistent and dynamic, which means that variable perceptions of minutia frequency may contribute to inconsistencies in FREs’ opinions about fingerprint evidence. We surveyed expert FREs at two time points (NTime 1 = 132; NTime 2 = 99) to establish how rare FREs believe different minutia types to be and to determine the variation in examiners’ perceptions—both between different examiners and across time for the same examiner. We observed significantly less variation in FREs’ perceptions of minutia frequency for three minutiae: the two most common minutiae and the minutia perceived to be the least common. We also observed increases in FREs’ estimates of minutia frequency over time and when they reported recent sightings of the rarest minutiae. FREs reported frequently using this information in their fingerprint comparison decisions. We present practical recommendations for using these consensus-based frequency estimates (until more objective data are available) to increase consistency in FREs’ use of base rates when examining fingerprint evidence, which may consequently increase the repeatability and reproducibility of decisions made by FREs.

Assessing the Effect of Shodhana (Purification) Process by Triphala Decoction on Shilajit Using High Performance Thin Layer Chromatography

Standardization of Shodhit Shilajit is a major challenge. Objective: Objective of the present study was to assessing the effect of Shodhana purification process on Shilajit as well as assessing the difference in fingerprint of raw Shilajit and Shodhit Shilajit by HPTLC and physicochemical tests. Methods: The standardization parameters such as appearance, identification of active marker compound Gallic acid and Fingerprint comparison by HPTLC, Physicochemical test parameters like loss on drying, pH value, ash value, water soluble extractive, ethanol soluble extractive and assay of humic acid and fulvic acid were evaluated during the study. Chromatographic separation was achieved by using Toluene: Ethyl acetate: Formic acid (5.0:4.0:1.0 v/v/v) as mobile phase followed by comparing the Rf values. Results: The presence of active marker compound gallic acid in Shodhit Shilajit was confirmed by comparing the Rf value with standard. HPTLC fingerprint also confirmed that constituents from raw Shilajit transferring to the Shodhit Shilajit after the process of Shodhana. Total Ash value and Acid insoluble ash value reduced from 52.95% to 21.67% and 2.35% to 0.39% respectively while Water soluble extractive value increased from 59.33% to 72.13% after Shodhana process. There is also an increase in percentages of humic acid and fulvic acid from 7.10% to 8.23% and 36.91% to 50.12 % in Shodhit Shilajit. Conclusion: All these results showed the significance and effectiveness of Shodhana process in reducing the impurities and ultimately enhancing the therapeutic activity of Shodhit Shilajit. These evaluation parameters can be used for the standardization of Shodhit Shilajit and also can be routinely employed for analysis in Quality Control Lab.

Identification and Comparison of DNA Fingerprinting of Mycobacterium Tuberculosis Isolates from Different Regions by IS 6110 RFLP Patterns

Identification and Comparison of DNA Fingerprinting of Mycobacterium Tuberculosis Isolates from Different Regions by IS 6110 RFLP Patterns

Aromatic Characterization of Graševina Wines from Slavonia and Podunavlje Sub-Regions

This study investigated the chemical aromatic profiles of 60 volatile organic compounds (VOCs), including 21 terpenes, 6 norisoprenoids, 6 volatile phenols, 4 C-6 alcohols, and 23 esters, in Graševina wines originating from Slavonia and Podunavlje sub-regions (Croatia). Headspace solid-phase microextraction gas chromatography coupled with mass spectrometric detection (HS-SPME-GCMS) was used to assess 60 VOCs, and a novel HS-SPME-GCMS method for the determination of terpenes and norisoprenoids was developed and validated. Statistical analysis found no significant differences between VOCs present in Graševina wines and others wines (Chardonnay and Pinot gris); nonetheless, comparison of VOC fingerprints between different wines from the same producer showed that four terpenes (α-terpinene, γ-terpinene, 1,4-cineol, and 4-terpineol) were present in higher amounts in Graševina wines when compared to other wines. By exclusively examining VOCs within Graševina wines through the utilization of a heatmap and hierarchical clustering, a distinct visualization of samples and VOCs emerged, highlighting the vintage effect. Simultaneously, a partial least squares discriminant analysis model was developed with a confidence interval of 95%, demonstrating a noticeable distinction between samples originating from the western and eastern regions. Furthermore, by employing the heatmap using only VOCs from the terpene and norisoprenoidic groups, a clear separation of samples into two groups was observed based on geographical origin; namely, higher concentrations of norisoprenoids and terpenes were observed in the Slavonia sub-region. These results suggest that terpenes and norisoprenoids to a lower extent may be valuable aromatic markers for the regional typicality of Graševina wines.

A guide to measuring expert performance in forensic pattern matching

Decisions in forensic science are often binary. A firearms expert must decide whether a bullet was fired from a particular gun or not. A face comparison expert must decide whether a photograph matches a suspect or not. A fingerprint examiner must decide whether a crime scene fingerprint belongs to a suspect or not. Researchers who study these decisions have therefore quantified expert performance using measurement models derived largely from signal detection theory. Here we demonstrate that the design and measurement choices researchers make can have a dramatic effect on the conclusions drawn about the performance of forensic examiners. We introduce several performance models – proportion correct, diagnosticity ratio, and parametric and non-parametric signal detection measures – and apply them to forensic decisions. We use data from expert and novice fingerprint comparison decisions along with a resampling method to demonstrate how experimental results can change as a function of the task, case materials, and measurement model chosen. We also graphically show how response bias, prevalence, inconclusive responses, floor and ceiling effects, case sampling, and number of trials might affect one’s interpretation of expert performance in forensics. Finally, we discuss several considerations for experimental and diagnostic accuracy studies: (1) include an equal number of same-source and different-source trials; (2) record inconclusive responses separately from forced choices; (3) include a control comparison group; (4) counterbalance or randomly sample trials for each participant; and (5) present as many trials to participants as is practical.

Harnessing fluorescent carbon quantum dots from natural resource for advancing sweat latent fingerprint recognition with machine learning algorithms for enhanced human identification.

Nowadays, it is fascinating to engineer waste biomass into functional valuable nanomaterials. We investigate the production of hetero-atom doped carbon quantum dots (N-S@MCDs) to address the adaptability constraint in green precursors concerning the contents of the green precursors i.e., Tagetes erecta (marigold extract). The successful formation of N-S@MCDs as described has been validated by distinct analytical characterizations. As synthesized N-S@MCDs successfully incorporated on corn-starch powder, providing a nano-carbogenic fingerprint powder composition (N-S@MCDs/corn-starch phosphors). N-S@MCDs imparts astounding color-tunability which enables highly fluorescent fingerprint pattern developed on different non-porous surfaces along with immediate visual enhancement under UV-light, revealing a bright sharp fingerprint, along with long-time preservation of developed fingerprints. The creation and comparison of latent fingerprints (LFPs) are two key research in the recognition and detection of LFPs, respectively. In this work, developed fingerprints are regulated with an artificial intelligence program. The optimum sample has a very high degree of similarity with the standard control, as shown by the program's good matching score (86.94%) for the optimal sample. Hence, our results far outperform the benchmark attained using the conventional method, making the N-S@MCDs/corn-starch phosphors and the digital processing program suitable for use in real-world scenarios.

Comparison of Sn-related granitoids in subduction and collision settings by accessory mineral geochemistry: A case study in the Tengchong-Lianghe tin belt, SW China

Magmatic-hydrothermal Sn deposits can develop in both subduction and collision settings. However, a systematic comparison of the geochemical fingerprints and petrogenetic evolution of Sn-related granitoids from both settings is still lacking. The Tengchong-Lianghe tin belt hosts numerous Sn deposits but of different metallogenic ages, such as the Xiaolonghe and Lailishan Sn deposits, which provide an ideal study area for addressing this issue. Zircon U–Pb dating suggests that the Xiaolonghe and Lailishan Sn-related granitoids were emplaced at 74.2–75.5 and 50.0–51.1 Ma, respectively. Given the initial India-Asia collision commenced at ca. 65–60 Ma, these ages, consistent with available Sn metallogenic ages, suggest the formation of the Xiaolonghe and Lailishan Sn deposits in subduction and collisional settings, respectively. New zircon and apatite compositions, and apatite Sr isotopic data, combined with previously reported whole-rock geochemical results, all indicate that the Xiaolonghe and Lailishan Sn-related granitoids share similar magma sources, evolution processes, redox states, and volatile contents. The presence of hornblende, high apatite NdN/NdN* (mostly > 1), and whole-rock evolutionary trends, together indicate that they represent fractionated I-type granites. Distinctly elevated apatite 87Sr/86Sr ratios (0.70988–0.71430) suggest that they originated from an ancient lower crust. Subsequently, they underwent an extensive fractional crystallization dominated by feldspar, as revealed by whole-rock, apatite, and zircon elemental variation trends. The low zircon CeN/CeN* (mainly < 200) and ΔFMQ (–1.9 to 1.7), together with elevated apatite F content (2.30–3.69 wt%), reveal that they crystallized from reduced and F-rich magmas. The relatively high whole-rock zircon saturation temperatures (mainly > 800 ℃) and Ba/Pb ratios imply that they were produced at a higher temperature by biotite-dehydration melting, which requires additional heat from the mantle. The specific mechanism that triggers mantle upwelling (oceanic slab subduction or break-off) could be the most significant difference between Sn-related granitoids formed during subduction and collision processes.

Multi-Surface Multi-Technique (MUST) Latent Fingerprint Database

Latent fingerprint recognition involves acquisition and comparison of latent fingerprints with an exemplar gallery of fingerprints. The diversity in the type of surface leads to different procedures to recover the latent fingerprint. The appearance of latent fingerprints vary significantly due to the development techniques, leading to large intra-class variation. Due to lack of large datasets acquired using multiple mechanisms and surfaces, existing algorithms for latent fingerprints enhancement and comparison may perform poorly. In this study, we propose a Multi-Surface Multi-Technique (MUST) Latent Fingerprint Database. The database consists of more than 16,000 latent fingerprint impressions from 120 unique classes (120 fingers from 12 participants). Including corresponding exemplar fingerprints (livescan and rolled) and extended gallery, the dataset has nearly 21,000 impressions. It has latent fingerprints acquired under 35 different scenarios and additional four subsets of exemplar prints captured using live scan sensor and inked-rolled prints. With 39 different subsets, the database illustrates intra-class variations in latent fingerprints. The database has a potential usage towards building robust algorithms for latent fingerprint enhancement, segmentation, comparison, and multi-task learning. We also provide annotations for manually marked minutiae, acquisition PPI, and semantic segmentation masks are also provided. We also present the experimental protocol and the baseline results for the proposed dataset. We assert that the availability of the proposed database can encourage research in handling intra-class variation in latent fingerprint recognition.

The influence of growth time on the identification of Bartonella henselae strains by MALDI-TOF mass spectrometry.

Bartonella spp. are bacteria responsible for neglected diseases worldwide. Bartonella henselae is the species most associated with human infections. It is associated with a large spectrum of clinical manifestations and is potentially fatal. The identification of Bartonella spp. is considered a challenge in clinical routine. These bacteria are fastidious, and the time required to isolate them varies from one to six weeks. MALDI-TOF mass spectrometry has emerged as an application for research on Bartonella spp. , and has still been little explored. We investigated whether three different B. henselae strains with different growth times-14 and 28 days-could be correctly identified by MALDI-TOF mass spectra fingerprint comparison and matching. We found that the spectra from strains with different growth times do not match each other, leading to misidentification. We suggest creating database entries with multiple spectra from strains with different growth times to increase the chances of accurate identification of Bartonella spp. by MALD-TOF MS.

A double-blind comparison of morphological and collagen fingerprinting (ZooMS) methods of skeletal identifications from Paleolithic contexts

Modeling the subsistence strategies of prehistoric groups depends on the accuracy of the faunal identifications that provide the basis for these models. However, our knowledge remains limited about the reproducibility of published taxonomic identifications and how they accurately reflect the range of species deposited in the archaeological record. This study compares taxonomic identifications at three Paleolithic sites (Saint-Césaire and Le Piage in France, Crvena Stijena in Montenegro) characterized by high levels of fragmentation. Identifications at these sites were derived using two methods: morphological identification and collagen fingerprinting, the latter a peptide-based approach known as ZooMS. Using a double-blind experimental design, we show that the two methods give taxonomic profiles that are statistically indistinguishable at all three sites. However, rare species and parts difficult to identify such as ribs seem more frequently associated with errors of identification. Comparisons with the indeterminate fraction indicate that large game is over-represented in the ZooMS sample at two of the three sites. These differences possibly signal differential fragmentation of elements from large species. Collagen fingerprinting can produce critical insights on the range distribution of animal prey in the past while also contributing to improved models of taphonomic processes and subsistence behavior.

Geochemical identification of a source rock affected by migrated hydrocarbons and its geological significance: Fengcheng Formation, southern Mahu Sag, Junggar Basin, NW China

The Fengcheng Formation is a crucial source rock and the primary reservoir for oil accumulation in the Mahu Sag. Crude oils are distributed throughout the Fengcheng Formation, ranging from the edge to the interior of the sag in the southern Mahu Sag. These crude oils originate from in-situ source rocks in shallowly buried areas and the inner deep sag. During migration, the crude oil from the inner deep sag affects the source rocks close to carrier beds, leading to changes in the organic geochemical characteristics of the source rocks. These changes might alter source rock evaluations and oil-source correlation. Based on data such as total organic carbon (TOC), Rock-Eval pyrolysis of source rocks, and gas chromatography-mass spectrometry (GC-MS) of the saturated fraction, and considering the geological characteristics of the study area, we define the identification characteristics of source rock affected by migrated hydrocarbons and establish the various patterns of influence that migrated hydrocarbons have on the source rock of the Fengcheng Formation in the southern Mahu Sag. The source rocks of the Fengcheng Formation are mostly fair to good, containing mainly Type II organic matter and being thermally mature enough to generate oil. Source rocks affected by migrated hydrocarbons exhibit relatively high hydrocarbon contents (S1/TOC > 110 mg HC/g TOC, Extract/TOC > 30 %, HC: hydrocarbon), relatively low Rock-Eval Tmax values, and relatively high tricyclic terpane contents with a descending and mountain-shaped distribution. Furthermore, biomarker composition parameters indicate a higher thermal maturity than in-situ source rocks. Through a comparison of the extract biomarker fingerprints of adjacent reservoirs and mudstones in different boreholes, three types of influence patterns of migrated hydrocarbons are identified: the edge-influence of thin sandstone-thick mudstone, the mixed-influence of sandstone-mudstone interbedded, and the full-influence of thick sandstone-thin mudstone. This finding reminds us that the influence of migrated hydrocarbons must be considered when evaluating source rocks and conducting oil-source correlation.

Latent fingerprints identification and ink-free printing of fluorescent lignin-derived CDs/PVA nanocomposite with multi-stimuli responsive shape memory behavior

The development and comparison of latent fingerprint (LFP) are crucial for the detection and identification of LFP. However, research on stable, clear, and no background interference’s fluorescent materials for LFP recognition are scarce. In this study, lignin-derived carbon dots (CDs) with orange red emission were synthesized and combined with polyvinyl alcohol (PVA) matrix for identification of LFP and ink-free printing. The physicochemical and microstructure of the CDs and CDs/PVA nanocomposite have been precisely elucidated by TEM, FT-IR, XPS, SEM, and TGA to verify the reaction of CDs with PVA forming hydrogen bonds. The effect of CDs on the mechanical properties of PVA nanocomposite was studied. The tensile strength and elongation at break of PVA nanocomposite were increased by 113.01 % and 175.26 %, respectively. The shape memory and fluorescence properties of CDs/PVA nanocomposite were studied under different conditions such as water, acid, alkali and heat. The fluorescence intensity of CDs/PVA nanocomposites was enhanced due to the deprotonation of CDs surface under alkaline conditions. By coating CDs/PVA solution on LFP, a stable fluorescent fingerprint with clear ridge details was formed on the composite film, and it is applied to letterpress printing and gravure printing, enabling personal identification and ink-free printing. Obviously, the nanocomposite film prepared herein has multiple functions, providing potential for the design and manufacture of advanced all-round personal information identification and encryption applications in extremely harsh high temperature and strong alkaline environments.

Luminescence fingerprints fluvial sediment transport from the Tibetan Plateau to the Bangladesh Delta

Fluvial sediment fingerprinting employs various methods, directly link sink and source. However, the identification and quantification of the transformation that sediments experience during fluvial transport remain unclear. The luminescence properties of quartz and K-feldspar change during the burial/exposure to sunlight cycles undergone by fluvial sediments, potentially allow scientists to trace fluvial sediment transport. Here, we report on changes in luminescence properties in active river bars from source to sink along the Yarlung Tsangpo-Brahmaputra River system. Optically stimulated luminescence (OSL) sensitivities and residual doses of quartz and K-feldspar within the fluvial sediments are used for the fingerprint method. Source rock is identified as the primary determinant of regional variations in quartz OSL sensitivities within fluvial sediments along the Yarlung Tsangpo River, while transportation distance governs local changes. Samples from narrower river channels with higher normalized channel steepnesses (Ksn) along the Yarlung Tsangpo River exhibit higher residual doses. Furthermore, the Brahmaputra River exhibits higher residual dose values compared to the Old Brahmaputra River. The sediments' residual doses are therefore employed to fingerprint fluvial erosion ability. Our luminescence fingerprint results indicate that coarse-grained fractions experience a “dilution” effect due to the input of new sediments after traveling approximately 50-200 km along the Yarlung Tsangpo River and about 50-100 km along the Brahmaputra-Old Brahmaputra River course. The comparison of luminescence (quartz and feldspar) and detrital zircon fingerprinting within the fluvial sediment holds the potential to trace weathering and erosion cycles during transportation in large river contexts.

Photoluminescence Mapping over Laser Pulse Fluence and Repetition Rate as a Fingerprint of Charge and Defect Dynamics in Perovskites

AbstractDefects in metal halide perovskites (MHP) are photosensitive, making the observer effect unavoidable when laser spectroscopy methods are applied. Photoluminescence (PL) bleaching and enhancement under light soaking and recovery in dark are examples of the transient phenomena that are consequent to the creation and healing of defects. Depending on the initial sample composition, environment, and other factors, the defect nature and evolution can strongly vary, making spectroscopic data analysis prone to misinterpretations. Herein, the use of an automatically acquired dependence of PL quantum yield (PLQY) on the laser pulse repetition rate and pulse fluence as a unique fingerprint of both charge carrier dynamics and defect evolution is demonstrated. A simple visual comparison of such fingerprints allows for assessment of similarities and differences between MHP samples. The study illustrates this by examining methylammonium lead triiodide (MAPbI3) films with altered stoichiometry that just after preparation showed very pronounced defect dynamics at time scale from milliseconds to seconds, clearly distorting the PLQY fingerprint. Upon weeks of storage, the sample fingerprints evolve toward the standard stoichiometric MAPbI3 in terms of both charge carrier dynamics and defect stability. Automatic PLQY mapping can be used as a universal method for assessment of perovskite sample quality.

Edge detection using fast pixel based matching and contours mapping algorithms.

Current methods of edge identification were constrained by issues like lighting changes, position disparity, colour changes, and gesture variability, among others. The aforementioned modifications have a significant impact, especially on scaled factors like temporal delay, gradient data, effectiveness in noise, translation, and qualifying edge outlines. It is obvious that an image's borders hold the majority of the shape data. Reducing the amount of time it takes for image identification, increase gradient knowledge of the image, improving efficiency in high noise environments, and pinpointing the precise location of an image are some potential obstacles in recognizing edges. the boundaries of an image stronger and more apparent locate those borders in the image initially, sharpening it by removing any extraneous detail with the use of the proper filters, followed by enhancing the edge-containing areas. The processes involved in recognizing edges are filtering, boosting, recognizing, and localizing. Numerous approaches have been suggested for the previously outlined identification of edges procedures. Edge detection using Fast pixel-based matching and contours mappingmethods are used to overcome the aforementioned restrictions for better picture recognition. In this article, we are introducing the Fast Pixel based matching and contours mapping algorithms to compare the edges in reference and targeted frames using mask-propagation and non-local techniques. Our system resists significant item visual fluctuation as well as copes with obstructions because we incorporate input from both the first and prior frames Improvement in performance in proposed system is discussed in result section, evidences are tabulated and sketched. Mainly detection probabilities and detection time is remarkably reinforced Effective identification of such things were widely useful in fingerprint comparison, medical diagnostics, Smart Cities, production, Cyber Physical Systems, incorporating Artificial Intelligence, and license plate recognition are conceivable applications of this suggested work.