The study of A-genome Asian cotton as a potential fiber donor in Gossypium species may offer an enhanced understanding of complex genetics and novel players related to fiber quality traits. Assessment of individual fibers providing classified fiber quality information to the textile industry is Advanced Fiber Information System (AFIS) in the recent technological era. Keeping the scenario, a diverse collection of 215 Asiatic cotton accessions were evaluated across three agro-ecological zones of China. Genome-Wide Association Studies (GWAS) was performed to detect association signals related to 17 AFIS fiber quality traits grouped into four categories viz: NEPs, fiber length, maturity, and fineness. Significant correlations were found within as well as among different categories of various traits related to fiber quality. Fiber fineness has shown a strong correlation to all other categories, whereas these categories are shown interrelationships via fiber-fineness. A total of 7,429 SNPs were found in association with 17 investigated traits, of which 177 were selected as lead SNPs. In the vicinity of these lead SNPs, 56 differentially expressed genes in various tissues/development stages were identified as candidate genes. This compendium connecting trait-SNP-genes may allow further prioritization of genes in GWAS loci to enable mechanistic studies. These identified quantitative trait nucleotides (QTNs) may prove helpful in fiber quality improvement in Asian cotton through marker-assisted breeding as well as in reviving eroded genetic factors of G. hirsutum via introgression breeding.

Automatic Latent Fingerprint Identification Systems (AFIS) are most widely used by forensic experts in law enforcement and criminal investigations. One of the critical steps used in automatic latent fingerprint matching is to automatically extract reliable minutiae from fingerprint images. Hence, minutiae extraction is considered to be a very important step in AFIS. The performance of such systems relies heavily on the quality of the input fingerprint images. Most of the state-of-the-art AFIS failed to produce good matching results due to poor ridge patterns and the presence of background noise. To ensure the robustness of fingerprint matching against low quality latent fingerprint images, it is essential to include a good fingerprint enhancement algorithm before minutiae extraction and matching. In this paper, we have proposed an end-to-end fingerprint matching system to automatically enhance, extract minutiae, and produce matching results. To achieve this, we have proposed a method to automatically enhance the poor-quality fingerprint images using the \"Automated Deep Convolutional Neural Network (DCNN)\" and \"Fast Fourier Transform (FFT)\" filters. The Deep Convolutional Neural Network (DCNN) produces a frequency enhanced map from fingerprint domain knowledge. We propose an \"FFT Enhancement\" algorithm to enhance and extract the ridges from the frequency enhanced map. Minutiae from the enhanced ridges are automatically extracted using a proposed \"Automated Latent Minutiae Extractor (ALME)\". Based on the extracted minutiae, the fingerprints are automatically aligned, and a matching score is calculated using a proposed \"Frequency Enhanced Minutiae Matcher (FEMM)\" algorithm. Experiments are conducted on FVC2002, FVC2004, and NIST SD27 latent fingerprint databases. The minutiae extraction results show significant improvement in precision, recall, and F1 scores. We obtained the highest Rank-1 identification rate of 100% for FVC2002/2004 and 84.5% for NIST SD27 fingerprint databases. The matching results reveal that the proposed system outperforms state-of-the-art systems.

Scholarship on the latent print comparison process has expanded in recent years, responsive to the call for rigorous research by scholarly groups (e.g., National Academy of Sciences, 2009; President\'s Council of Advisors on Science and Technology, 2016). Important to the task of ultimately improving accuracy, consistency, and efficiency in the field is understanding different workflows and case outcomes. The current study describes the casework completed by a latent print unit in a large laboratory during one calendar year (2018), including a unique workflow that involves Preliminary AFIS Associations reported out as investigative leads. Approximately 45% of all examined prints were deemed to be of sufficient quality to enter into AFIS, and 22% of AFIS entries resulted in potential identifications. But examiner conclusions and AFIS outcomes (across three AFIS databases) varied according to case details, print source, and AFIS database. Moreover, examiners differed in case processing, sufficiency determinations, and AFIS conclusions. Results are discussed with respect to implications for future research (e.g., comparing these data to case processing data for other laboratories) and ultimately improving the practice of latent print examination.

Fingermarks that have insufficient characteristics for identification often have discernible characteristics that could form the basis for lesser degrees of correspondence or probability of occurrence within a population. Currently, those latent prints that experts judge to be insufficient for identification are not used as associative evidence. How often do such prints occur and what is their potential value for association? The answers are important. We could be routinely setting aside a very important source of associative evidence, with high potential impact, in many cases; or such prints might be of very low utility, adding very little, or only very rarely contributing to cases in a meaningful way. The first step is to better understand the occurrence and range of associative value of these fingermarks. The project goal was to explore and test a theory that in large numbers of cases fingermarks of no value for identification purposes occur and are readily available, though not used, and yet have associative value that could provide useful information. Latent fingermarks were collected from nine state and local jurisdictions. Fingermarks included were those (1) collected in the course of investigations using existing jurisdictional procedures, (2) originally assessed by the laboratory as of no value for identification (NVID), (3) re-assessed by expert review as NVID, but with least three clear and reliable minutiae in relationship to one another, and (4) determined to show at least three auto-encoded minutiae. An expected associative value (ESLR) for each mark was measured, without reference to a putative source, based on modeling within-variability and between-variability of AFIS scores. This method incorporated (1) latest generation feature extraction, (2) a (minutiae-only) matcher, (3) a validated distortion model, and (4) NIST SD27 database calibration. Observed associative value distributions were determined for violent crimes, property crimes, and for existing objective measurements of latent print quality. 750 Non Identifiable Fingermarks (NIFMs) showed values of Log10 ESLR ranging from 1.05-10.88, with a mean value of 5.56 (s.d. 2.29), corresponding to an ESLR of approximately 380,000. It is clear that there are large numbers of cases where NIFMs occur that have high potential associative value as indicated by the ESLR. These NIFMs are readily available, but not used, yet have associative value that could provide useful information. These findings lead to the follow-on questions, \"How useful would NIFM evidence be in actual practice?\" and, \"What developments or improvements are needed to maximize this contribution?\"

Fingerprints have been used with considerable success over the past century in multiple civil government, law enforcement and criminal investigation applications. Since the 1970s, computer assisted systems (AFIS - Automated Fingerprint Identification System) have been increasingly used to automatically compare fingerprints and propose associations between multiple friction ridge impressions of known or unknown sources. AFIS were initially entirely subordinated to human examiners. Improvements in the matching algorithms and workload considerations have pushed agencies to implement completely automated processes, known as \"Lights-out\" modes, where AFIS\'s render unsupervised conclusions on the donors of the queries. Such fully automated process is common for tenprint-to-tenprint comparisons; however it is currently not being widely adopted for other types of comparisons, such as latent print-to-tenprint comparisons. In this paper, we explore a statistical model that can be used to facilitate the latent print examination workflow by predicting whether any latent print should be searched in AFIS. In particular, we are interested in preventing poor quality latent prints to be searched in vain, and thus unnecessarily consume resources. Ultimately, we show that our model could be used to efficiently manage workflow and workload by categorizing latent prints as a function of the quality and quantity of information that can be observed on them, which enables examiners to select the most appropriate examination and quality assurance processes for each print.

Fingerprints present in false identity documents were found on the web. In some cases, laterally reversed (mirrored) images of a same fingerprint were observed in different documents. In the present work, 100 fingerprints images downloaded from the web, as well as their reversals obtained by image editing, were compared between themselves and against the database of the Brazilian Federal Police AFIS, in order to better understand trends about this kind of forgery in Brazil. Some image editing effects were observed in the analyzed fingerprints: addition of artifacts (such as watermarks), image rotation, image stylization, lateral reversal and tonal reversal. Discussion about lateral reversals\' detection is presented in this article, as well as suggestion to reduce errors due to missed HIT decisions between reversed fingerprints. The present work aims to highlight the importance of the fingerprints\' analysis when performing document examination, especially when only copies of documents are available, something very common in Brazil. Besides the intrinsic features of the fingermarks considered in three levels of details by ACE-V methodology, some visual features of the fingerprints images can be helpful to identify sources of forgeries and modus operandi, such as: limits and image contours, fails in the friction ridges caused by excess or lack of inking and presence of watermarks and artifacts arising from the background. Based on the agreement of such features in fingerprints present in different identity documents and also on the analysis of the time and location where the documents were seized, it is possible to highlight potential links between apparently unconnected crimes. Therefore, fingerprints have potential to reduce linkage blindness and the present work suggests the analysis of fingerprints when profiling false identity documents, as well as the inclusion of fingerprints features in the profile of the documents.

Thanatopractical processing allows morphological reconstruction of even advanced decayed bodies. By extracting fluids from the body\'s tissue antemortem tenseness and volume can be restored. If bodies are partly subject to thanatopractical processing in the hand region (\"Thanatoprint\"), fingerprints of high quality can be gathered even in cases of advanced decay. Without this treatment fingerprinting can be extremely difficult, if not impossible. Thanatopractical processing could be applied successfully in cases of partial to subtotal detachment of the epidermis as well. In an interdisciplinary study 400 fingerprints of bodies in various states of decay were examined after application of Thanatoprint. In 76.75% fingerprints were applicable for data entry into AFIS (Automated Fingerprint Identification System); another 11.00% of the fingerprints could be used for the process of non-elimination. Further advantages of the method are low invasivity while maintaining the integrity of the corpse, less time- and material requirement as well as its long-lasting effect.
Thanatopraktische Verfahren ermöglichen eine morphologische Rekonstruktion auch bei hochgradig postmortal veränderten Leichen. Dem Gewebe wird Feuchtigkeit entzogen, seine ursprüngliche Spannung und sein Volumen werden wiederhergestellt. Werden Leichen auf diese Weise partiell im Bereich der Hände behandelt (Thanatoprint-Verfahren), können selbst in Fällen fortgeschrittener Fäulnis gute bis sehr gute Fingerabdrücke gewonnen werden. Ohne diese Behandlung ist die Fingerabdrucknahme oft erheblich erschwert, wenn nicht gar unmöglich. Das Verfahren ließ sich auch bei teilweiser bis subtotaler Ablösung der Oberhaut erfolgreich anwenden. In einer interdisziplinären Studie wurden 400 Fingerabdrücke von Leichen verschiedener Fäulnisstadien nach der Anwendung von Thanatoprint untersucht. In 76,75% waren die Fingerabdrücke für eine AFIS (Automated Fingerprint Identification System)-Recherche geeignet, weitere 11,00% ließen sie sich für ein Nichtausschlussverfahren nutzen. Als Vorteile der Methode zeigten sich ferner die geringe Invasivität mit erhaltener Integrität der Leiche, der geringe Zeit- und Materialaufwand sowie die anhaltende Wirkung.

The nature of crime scene palmar images (CSPI) or factors affecting search parameters using a palm-enabled AFIS system have not been investigated. A questionnaire-based survey, undertaken by U.K. fingerprint experts utilizing the U.K.\'s IDENT-1 system during the period January to July 2010, of CSPI marks has been conducted to provide descriptive statistical data on the nature of CSPI and some aspects of the ACE-V process. 45 scene-recovered marks were analyzed for part of the CSPI recovered, friction ridge detail, and process times. U.K. population handedness was different from recovered CSPI. Most and least frequently recovered regions were hypothenar pad B and the central pad, respectively. There was a nonsignificant association between palm region and number of palm regions recovered, as well as identification rate and analysis times and characteristics. The number of CSPI regions was significantly related to time for analysis, identification, and comparison.

We propose the use of correlation mapping optical coherence tomography (cmOCT) to deliver additional biometrics associated with the finger that could complement existing fingerprint technology for law enforcement applications. The current study extends the existing fingerprint paradigm by measuring additional biometrics associated with sub-surface finger tissue such as sub-surface fingerprints, sweat glands, and the pattern of the capillary bed to yield a user-friendly cost effective and anti-spoof multi-mode biometric solution associated with the finger. To our knowledge no other method has been able to capture sub-surface fingerprint, papillary pattern and horizontal vessel pattern in a single scan or to show the correspondence between these patterns in live adult human fingertip. Unlike many current technologies this approach incorporates \'liveness\' testing by default. The ultimate output is a biometric module which is difficult to defeat and complements fingerprint scanners that currently are used in border control and law enforcement applications.