Identification Aid Research Articles

An annotated checklist of the lichen biodiversity at two Mars analog sites: The Mars Desert Research Station (Utah, USA) and The Flashline Mars Arctic Research Station (Nunavut, Canada) recorded during the Mars 160 Mission

During the Mars 160 Mission in 2016 and 2017, crews at the Mars Desert Research Station (MDRS) in Utah, USA and the Flashline Mars Arctic Research Station (FMARS) on Tallurutit (Devon Island), Nunavut, Canada, conducted a collections‑based survey of lichen biodiversity at each of these Martian planetary analogs. Here we present the results of these studies as two annotated checklists, including 35 lichen spe‑ cies from MDRS and 13 species from FMARS, alongside details on the distribution of these species, relevant taxonomic notes, and photos of each species as an identification aid. This work adds to our knowledge of the biodiversity of these unique sites and provides an important baseline for future analog research at these stations.

The effect of Clusterin level as a potential marker in women with polycystic ovary syndrome

An organ with high metabolic activity, adipose tissue secretes a variety of adipocytokines that control the metabolism of fats and carbohydrates and advance insulin resistance (IR). It is currently unclear what pathophysiological mechanism underlies PCOS. In most cases, IR and metabolic abnormalities coexist with PCOS, a chronic endocrine and metabolic illness. Prompt identification and intervention aid in enhancing patients' quality of life while delaying the development of associated issues. Adipokine clusterin (encoded by CLU) is new. Diabetes and obesity-related populations have higher serum clusterin levels. In order to establish a foundation for early PCOS screening, diagnosis, and therapy, the current study examined variations in serum CLU levels in PCOS patients along with their relationships to sex hormones and metabolic markers. A case-control study design consisting of ninety newly diagnosed PCOS patients of ages ranging between (18-42) years have been recruited according to the Rotterdam criteria of PCOS diagnosis. To compare the results, 90 apparently healthy women of age were matched with the patients' group as a control group. Serum clusterin, fasting insulin (FIN), and fertile hormones have been measured in sera using the enzyme-linked immune sorbent assay (ELISA) technique. An independent t-test analysis was performed on the data. Pearson correlation was utilized to evaluate the relationship between the variables. It was found that the PCOS patients had considerably greater serum CLU (41.672± 3.85 vs. 28.5845± 3.01 μg/ml, P < 0.001) than healthy women. A multiple stepwise linear regression analysis showed that HOMA-IR was separately linked with BMI, and HOMA-IR were independently associated with CLU (P < 0.05). Serum CLU exhibited a positive connection (P < 0.05) with BMI, FSG, FINS, and HOMA-IR. Serum CLU in the PCOS group correlated well with TG, CLU, HOMA-IR, FSH, FSG, and FINS. The PCOS women group significantly outperformed the fertile, healthy women group regarding BMI, LH, FSH, FSG, FIN, HOMA-IR, TC, TG, and LDL-C levels. They also had lower levels of HDL-C and QUICKI values. Additionally, serum clustrein levels. 31.68 A cut-off value of CLU as a marker for diagnosing PCOS with a sensitivity of 90.0% and a specificity of 87.5% (AUC: P value = ˂0.0001, 0.887-1.000.

Near field communication tag to provide a unique identification aid for custom ocular prostheses

This technique describes a smartphone-enabled near field communication tag used as an identification aid for a custom ocular prosthesis for a pediatric patient. Near field communication tags are straightforward to read, can be readily connected to smartphone devices without the need for specialized equipment, store data in a variety of ways, are inexpensive, exceptionally thin, and flexible, and tolerate resin polymerization temperatures, making them suitable as an identification aid for an ocular prosthesis.

Curating an online checklist for Erica L. (Ericaceae): contributing to and supporting global conservation through the World Flora Online.

To support the work of the Global Conservation Consortium for Erica and update the Erica checklist in the World Flora Online (WFO), we have curated the taxonomic backbone in the WFO by expanding it to include updated nomenclatural information from the International Plant Name Index, missing names present in the World Checklist of Vascular Plants (WCVP), the Botanical Database of Southern Africa (BODATSA), and from the "International register of heather names" database, a data source not readily available online. The result is the most robust database of Erica names to date, including 851 species, 111 subspecies, 244 varieties, and 2787 synonyms, which is a reliable reference for initiatives such as the Erica identification aid, conservation prioritisation, and gap analyses. We disambiguate common orthographic variants within the database and present an overview of these. We also comment on the correct orthography of E.heleophila Guthrie & Bolus and E.michellensis Dulfer and the validity of E.tegetiformis E.G.H.Oliv. are discussed, and the use of E.adunca Benth. for a South African species rather than E.triceps Link, which is here regarded as insufficiently known and of uncertain application, is clarified.

Systematic analysis of jellyfish galaxy candidates in Fornax, Antlia, and Hydra from the S-PLUS survey: a self-supervised visual identification aid

ABSTRACT We study 51 jellyfish galaxy candidates in the Fornax, Antlia, and Hydra clusters. These candidates are identified using the JClass scheme based on the visual classification of wide-field, twelve-band optical images obtained from the Southern Photometric Local Universe Survey. A comprehensive astrophysical analysis of the jellyfish (JClass > 0), non-jellyfish (JClass = 0), and independently organized control samples is undertaken. We develop a semi-automated pipeline using self-supervised learning and similarity search to detect jellyfish galaxies. The proposed framework is designed to assist visual classifiers by providing more reliable JClasses for galaxies. We find that jellyfish candidates exhibit a lower Gini coefficient, higher entropy, and a lower 2D Sérsic index as the jellyfish features in these galaxies become more pronounced. Jellyfish candidates show elevated star formation rates (including contributions from the main body and tails) by $\sim$1.75 dex, suggesting a significant increase in the SFR caused by the ram-pressure stripping phenomenon. Galaxies in the Antlia and Fornax clusters preferentially fall towards the cluster’s centre, whereas only a mild preference is observed for Hydra galaxies. Our self-supervised pipeline, applied in visually challenging cases, offers two main advantages: it reduces human visual biases and scales effectively for large data sets. This versatile framework promises substantial enhancements in morphology studies for future galaxy image surveys.

Genus Erica: An identification aid version 4.00.

Species identification is fundamental to all aspects of biology and conservation. The process can be challenging, particularly in groups including many closely related or similar species. The problem is confounded by the absence of an up-to-date taxonomic revision, but even with such a resource all but professional botanists may struggle to recognise key species, presenting a substantial barrier to vital work such as surveys, threat assessments, and seed collection for ex situ conservation. Genus Erica: An Identification Aid is a tool to help both amateurs and professionals identify (using a limited number of accessible characteristics) and find information about the 851 species and many subspecific taxa of the genus Erica. We present an updated version 4.00, with new features including integrating distribution data from GBIF and iNaturalist, links to taxonomic resources through World Flora Online, and a probability function for identifications, that is freely available for PCs. It remains a work in progress: We discuss routes forward for collaboratively improving this resource.

Squished Bugs

Field guides have been a vital part of biology disciplines for centuries. This article focuses on recent pedagogical innovations in biological fieldwork, in fields such as entomology and ecology—specifically, the creation of informal field guide photographs that depict insects as ecologists-in-training are most likely to encounter them: dead and squished on cards, in nets, and on other types of insect traps. This article examines the training of ecology technicians to identify collected insects in the field and the laboratory. Technicians (whether students or volunteers) are trained to the squished reference images, with the goal of improving their insect identification skills and aid in ecological knowledge production. Using this empirical example, the article argues that squished bugs more importantly represent a pedagogical opportunity to instill an ethical reflexivity in field technicians operating well outside of academic environmental humanities circles. Drawing on multispecies studies’ (and its animal studies antecedents’) focus on environmental ethics, as well as the scant but growing attention to “unloved others” like invertebrates, squished bugs are used as a way of reckoning with the destruction and deformation of life for the sake of conservation knowledge and, as Donna Haraway has suggested, “staying with the trouble” of killing insects.

Mood Disorder Severity and Subtype Classification Using Multimodal Deep Neural Network Models.

The subtype diagnosis and severity classification of mood disorder have been made through the judgment of verified assistance tools and psychiatrists. Recently, however, many studies have been conducted using biomarker data collected from subjects to assist in diagnosis, and most studies use heart rate variability (HRV) data collected to understand the balance of the autonomic nervous system on statistical analysis methods to perform classification through statistical analysis. In this research, three mood disorder severity or subtype classification algorithms are presented through multimodal analysis of data on the collected heart-related data variables and hidden features from the variables of time and frequency domain of HRV. Comparing the classification performance of the statistical analysis widely used in existing major depressive disorder (MDD), anxiety disorder (AD), and bipolar disorder (BD) classification studies and the multimodality deep neural network analysis newly proposed in this study, it was confirmed that the severity or subtype classification accuracy performance of each disease improved by 0.118, 0.231, and 0.125 on average. Through the study, it was confirmed that deep learning analysis of biomarker data such as HRV can be applied as a primary identification and diagnosis aid for mental diseases, and that it can help to objectively diagnose psychiatrists in that it can confirm not only the diagnosed disease but also the current mood status.

Artificial Intelligence in Laboratory Technologies for Early Detection and Prognostication of Sepsis: A Systematic Review

Background: Sepsis: a complex clinical syndrome--represents life-threatening organ dysfunction instigated by an infection's dysregulated host response. Early detection and accurate prognostication of sepsis are crucial; they pave the way for timely intervention, ultimately enhancing patient outcomes. The rise in interest towards Artificial Intelligence (AI) applications within laboratory technologies is directly related to its potential for improving early detection and prognosis forecasting in sepsis cases; this interest comes as AI continues its advancement. Methods: We conducted a systematic review of studies utilizing AI algorithms in laboratory settings for early sepsis detection and prognostication: our methods entailed searching relevant databases for research published until October 2023. Our inclusion criteria spanned original articles; these applied machine learning (ML) and deep learning (DL) techniques to laboratory data--with the aim being sepsis prediction. We assessed the quality of the studies, extracted and synthesized data on AI model performance metrics - including: area under receiver operating characteristic curve (AUROC), sensitivity, specificity, and accuracy. Results: The review encompassed eight studies meeting the inclusion criteria; AI models showcased exceptional predictive capabilities--evidenced by a range of AUROC values from 0.799 to 0.9213, signifying noticeably acceptable performance. However, there was wide variation in sensitivity and specificity among these analyses: an indicator of heterogeneity in model performance. Superior prognostic accuracy and potential for real-time monitoring of patients' early sepsis signs emerged in several models: notably, within the first 12 hours of patient admission - their highest predictive period. The models frequently outperformed traditional scoring systems. Conclusion: Laboratory technology's AI applications significantly promise sepsis' early detection and prognostication. Reviewed studies suggest AI models may surpass traditional methods, offering potential integration into clinical workflows for rapid sepsis identification aid. Nevertheless, we also acknowledged both the variability in model performance and necessity of additional validation across diverse clinical settings. Future research: it must concentrate on two key aspects--the refinement of AI algorithms to enhance sensitivity and precision; furthermore, it should delve into evaluating the clinical impact of tools for sepsis prediction that are assisted by AI.

Multi-Head CNN-based Software Development Risk Classification

Agile methodology for software development has been in vogue for a few decades, notably among small and medium enterprises. The omission of an explicit risk identification approach turns a blind eye to a range of perilous risks, thus dumping the management into strenuous situations and precipitating dreadful issues at the crucial stages of the project. To overcome this drawback a novel Agile Software Risk Identification using Deep learning (ASRI-DL) approach has been proposed that uses a deep learning technique along with the closed fishbowl strategy, thus assisting the team in finding the risks by molding them to think from diverse perspectives, enhancing wider areas of risk coverage. The proposed technique uses a multi-head Convolutional Neural Network (Multihead-CNN) method for classifying the risk into 11 classes such as over-doing, under-doing, mistakes, concept risks, changes, differences, difficulties, dependency, conflicts, issues, and challenges in terms of producing a higher number of risks concerning score, criticality, and uniqueness of the risk ideas. The descriptive statistics further demonstrate that the participation and risk coverage of the individuals in the proposed methodology exceeded the other two as a result of applying the closed fishbowl strategy and making use of the risk identification aid. The proposed method has been compared with existing techniques such as Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Generalized Linear Models (GLM), and CNN using specific parameters such as accuracy, specificity, and sensitivity. Experimental findings show that the proposed ASRI-DL technique achieves a classification accuracy of 99.16% with a small error rate with 50 training epochs respectively.

Host range and virulence diversity of Pectobacterium carotovorum subsp. brasiliense strain RDKLR infecting radish in India, and development of a LAMP-based diagnostics.

This work aimed at determining the pathogenicity, molecular characterization, host range and rapid detection of Pectobacterium carotovorum subsp. brasiliense (Pcb) causing soft rot disease in radish. The four isolated isolates were inoculated to radish, typical soft rot symptoms were observed and Koch's postulates were proved. The most virulent strain RDKLR was morphologically and biochemically distinct. Pcb showed a positive potato soft rot test and elicited hypersensitivity response on Nicotiana tobaccum. The genes Pel2 and pmrA were used for subspecies characterization of Pcb. It has a wide host range and infection was observed on slices of carrot, tomato, radish, potato, cauliflower, cabbage, chilli, knol-khol, bell pepper and cucumber. Infectivity was also seen in seedlings under glasshouse conditions. Pcb produced cell wall degrading enzymes in semi-quantification assay and is a strong biofilm producer. The LAMP technique was standardized to help rapid detection and take prophylactic measures to manage the disease. This work reports Pcb as a new soft rot causing organism of radish in India. Pcb is highly virulent with a broad host range. The LAMP technique helps in rapid detection. Pcb-induced soft rot causes significant yield loss, decreased market value, damage in transit, storage and the market. Disease characterization and early identification aid in disease management and prevention in the field.

Osobní hesla humanistů, jejich funkce, formy a využití v provenienčním výzkumu

The personal mottos of intellectuals, called symbola, came into greater use under the influence of the Italian Renaissance and its ideas of true nobility, which is not acquired by descent but by education and virtue. Inspired by noblemen, scholars created their own personal representations, among the most common being personal devices, followed by emblems and portraits. The first symbols in the Czech lands are known to have appeared at the beginning of the 16th century, but their use truly developed in the Rudolphine period. Court intellectuals, university professors, teachers, clergymen and educated burghers had their own symbols at that time. Symbola were usually in Latin, with rare appearances in Czech and Old Greek, and sporadically in Hebrew and German. Twothirds of the contents were religious; other motifs concerned the way of life or Christian and ancient virtues. The content of personal mottos was most often inspired by Satellitium animi by Juan Luis Vives, Adagia by Erasmus of Rotterdam and other collections of sentences and proverbs or emblem books. The form was sometimes emblematic; among burghers, the so-called symbola cephalonomatica were common. These were personal mottos in which the first letters of the words formed the initials of the personal name and title of the Humanist. The symbols appear in the form of ownership marks in books as initial supralibros or handwritten ex-libris; in both forms, i.e. as the initials or the entire mottos, they were also used as pseudonyms. A provisional online inventory has been compiled as an identification aid for provenance research and authorship identification, and it will be expanded in future.

Integrating UCE Phylogenomics With Traditional Taxonomy Reveals a Trove of New WorldSysciaSpecies (Formicidae: Dorylinae)

AbstractThe ant genus Syscia Roger, 1861 is part of the cryptic ant fauna inhabiting leaf litter and rotten wood in the Asian and American tropics. It is a distinct clade within the Dorylinae, the subfamily from which army ants arose. Prior to this work, the genus comprised seven species, each known from a single or very few collections. Extensive collecting in Middle America revealed an unexpected and challenging diversity of morphological forms. Locally distinct forms could be identified at many sites, but assignment of specimens to species spanning multiple sites was problematic. To improve species delimitation, Ultra-Conserved Element (UCE) phylogenomic data were sequenced for all forms, both within and among sites, and a phylogeny was inferred. Informed by phylogeny, species delimitation was based on monophyly, absence of within-clade sympatry, and a subjective degree of morphological uniformity. UCE phylogenomic results for 130 specimens were complemented by analysis of mitochondrial COI (DNA barcode) data for an expanded taxon set. The resulting taxonomy augments the number of known species in the New World from 3 to 57. We describe and name 31 new species, and 23 species are assigned morphospecies codes pending improved specimen coverage. Queens may be fully alate or brachypterous, and there is a wide variety of intercaste female forms. Identification based on morphology alone is very difficult due to continuous character variation and high similarity of phylogenetically distant species. An identification aid is provided in the form of a set of distribution maps and standard views, with species ordered by size.

Constructing identifiable composite faces: The importance of cognitive alignment of interview and construction procedure.

We investigated the impact of congruency between the witness interview and method used to construct a composite face. Experiment 1, using a typical feature-by-feature composite method, revealed that aligning cognitive processes during interview and face construction enhanced the effectiveness of composites compared with composites produced following unaligned (incongruent) procedures. Experiment 2 revealed that incorporating character judgments in the witness interview substantially enhanced identification of feature-based composites when constructing the central (internal) features first, suggesting that such judgments focus attention on this region of the face. Experiment 3 explored alignment of processes using an approach based on an evolutionary algorithm, a method requiring witnesses to create a composite by selecting from arrays based on the eye-region. A combination of character judgments, first for the whole face and then for the eye region, led to best-identified composites. Overall, results indicate that more effective composites are produced when both interview and construction procedures are aligned cognitively. Results are discussed with relevance to the theory of transfer-appropriate processing (Morris, Bransford, & Franks, 1977). (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Benefits of a comprehensive COPD inhaler identification aid

A vast number of inhalers are available to treat COPD, and it is extremely difficult for both healthcare professionals and patients to keep track of them all. Karen Lee and Kamal Ibrahim from Bolton Hospital NHS Foundation Trust have therefore helped to develop a comprehensive COPD inhaler identification poster and here they discuss its usefulness in a range of clinical settings.

Differentiation of Bifidobacterium longum subspecies longum and infantis by quantitative PCR using functional gene targets.

BackgroundMembers of the genus Bifidobacterium are abundant in the feces of babies during the exclusively-milk-diet period of life. Bifidobacterium longum is reported to be a common member of the infant fecal microbiota. However, B. longum is composed of three subspecies, two of which are represented in the bowel microbiota (B. longum subsp. longum; B. longum subsp. infantis). B. longum subspecies are not differentiated in many studies, so that their prevalence and relative abundances are not accurately known. This may largely be due to difficulty in assigning subspecies identity using DNA sequences of 16S rRNA or tuf genes that are commonly used in bacterial taxonomy.MethodsWe developed a qPCR method targeting the sialidase gene (subsp. infantis) and sugar kinase gene (subsp. longum) to differentiate the subspecies using specific primers and probes. Specificity of the primers/probes was tested by in silico, pangenomic search, and using DNA from standard cultures of bifidobacterial species. The utility of the method was further examined using DNA from feces that had been collected from infants inhabiting various geographical regions.ResultsA pangenomic search of the NCBI genomic database showed that the PCR primers/probes targeted only the respective genes of the two subspecies. The primers/probes showed total specificity when tested against DNA extracted from the gold standard strains (type cultures) of bifidobacterial species detected in infant feces. Use of the qPCR method with DNA extracted from the feces of infants of different ages, delivery method and nutrition, showed that subsp. infantis was detectable (0–32.4% prevalence) in the feces of Australian (n = 90), South-East Asian (n = 24), and Chinese babies (n = 91), but in all cases at low abundance (<0.01–4.6%) compared to subsp. longum (0.1–33.7% abundance; 21.4–100% prevalence).DiscussionOur qPCR method differentiates B. longum subspecies longum and infantis using characteristic functional genes. It can be used as an identification aid for isolates of bifidobacteria, as well as in determining prevalence and abundance of the subspecies in feces. The method should thus be useful in ecological studies of the infant gut microbiota during early life where an understanding of the ecology of bifidobacterial species may be important in developing interventions to promote infant health.

Gender determination using barr bodies from teeth exposed to high temperatures.

Context:Gender determination forms a prime step in the forensic identification process. Teeth form a very important identification aid in forensic studies because they are protected by oral tissues and dental pulp is further protected by the mineralized constituents of the teeth. This allows the conservation and sustainable production of dental pulp to help sex determination in circumstances where other tissues cannot be analyzed like victims when exposed to high temperatures during fire accidents, explosions, and other mass disasters.Aim:The present study aimed at gender determination from pulpal tissue extirpated from teeth exposed to high temperatures.Materials and Methodology:The study consisted of sixty teeth samples, thirty male and thirty female. The teeth have been subjected to a series of temperatures of 37°C, 100°C, 200°C, 300°C, 400°C, 500°C, 600°C, 800°C, and 1000°C. The dental pulp is then obtained from these teeth, processed, stained, and checked for Barr bodies.Statistical Analysis Used:Descriptive statistical analysis has been used.Results:The results showed that pulp from the female teeth showed the presence of Barr bodies up to a maximum of 400°C, whereas the male pulpal tissue did not show the presence of any Barr bodies. With increase in temperatures, the cellularity of the connective tissue decreased but the average number of Barr body positive cells remained constant within the range of 19–20.Conclusions:Dental pulp acts as a potential source of gender determination when no other means of identification are available.

Target Detection and Identification Performance Using an Automatic Target Detection System.

We investigated the effects of automatic target detection (ATD) on the detection and identification performance of soldiers. Prior studies have shown that highlighting targets can aid their detection. We provided soldiers with ATD that was more likely to detect one target identity than another, potentially acting as an implicit identification aid. Twenty-eight soldiers detected and identified simulated human targets in an immersive virtual environment with and without ATD. Task difficulty was manipulated by varying scene illumination (day, night). The ATD identification bias was also manipulated (hostile bias, no bias, and friendly bias). We used signal detection measures to treat the identification results. ATD presence improved detection performance, especially under high task difficulty (night illumination). Identification sensitivity was greater for cued than uncued targets. The identification decision criterion for cued targets varied with the ATD identification bias but showed a "sluggish beta" effect. ATD helps soldiers detect and identify targets. The effects of biased ATD on identification should be considered with respect to the operational context. Less-than-perfectly-reliable ATD is a useful detection aid for dismounted soldiers. Disclosure of known ATD identification bias to the operator may aid the identification process.

Communicating Emotions: How Commercial Manga for Women Approaches 3.11

Hagio Moto’s manga series Nanohana was one of the first attempts in female-oriented mainstream manga to depict the 3.11 tragedy and its aftermath. However, it appears to lack in overt social critique, providing instead a highly emotional story about overcoming hardship and maturing. Via a close-reading of Nanohana this article analyzes the modus operandi of social critique in popular manga highlighting the visual conventions of female manga genres and thereby going beyond the plotlines, which have been at the center of critical attention so far. The article contrasts the initial one-shot “Nanohana,” which directly addresses 3.11, with the subsequent three one-shots that anthropomorphize nuclear elements. Leaning on Thomas LaMarre’s theory of plastic and structural lines, Nanohana is analyzed in regard to signification and affect by correlating the manga’s varying line work with issues of gender, especially the dynamics of the gaze, as theoretically developed by Oshiyama, Nagaike, Ōgi and Ishida. Respectively, the visualization of popular gender stereotypes in shōjo and josei manga comes to the fore. Special attention is paid to how visual gender constructs help the reader to differentiate between “self” and “other” on the levels of signification and affect, and how the resulting identification and dissociation aid in approaching the traumatic nuclear accident.

Virtual autopsy

Forensic odontology has been emerging as a major branch of the forensic science as an identification aid. Teeth by its resistant nature to degradative forces offer us an identification tool. Virtual autopsy is a virtual dissection of the human body through imaging to analyze the internal aspects of the body. This article speaks on the applications of virtual autopsy in forensic science.