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We present a novel approach to genome-wide association studies (GWAS) by leveraging unstructured, spoken phenotypic descriptions to identify genomic regions associated with maize traits. Utilizing the Wisconsin Diversity panel, we collected spoken descriptions of Zea mays ssp. mays traits, converting these qualitative observations into quantitative data amenable to GWAS analysis. First, we determined that visually striking phenotypes could be detected from unstructured spoken phenotypic descriptions. Next, we developed two methods to process the same descriptions to derive the trait plant height, a well-characterized phenotypic feature in maize: (1) a semantic similarity metric that assigns a score based on the resemblance of each observation to the concept of 'tallness' and (2) a manual scoring system that categorizes and assigns values to phrases related to plant height. Our analysis successfully corroborated known genomic associations and uncovered novel candidate genes potentially linked to plant height. Some of these genes are associated with gene ontology terms that suggest a plausible involvement in determining plant stature. This proof-of-concept demonstrates the viability of spoken phenotypic descriptions in GWAS and introduces a scalable framework for incorporating unstructured language data into genetic association studies. This methodology has the potential not only to enrich the phenotypic data used in GWAS and to enhance the discovery of genetic elements linked to complex traits but also to expand the repertoire of phenotype data collection methods available for use in the field environment.

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This paper argues that one aspect of re-imagining evaluation in health planning and management is for leaders and clinicians to develop comfort with vulnerability when engaging in service evaluations. Starting with an exploration of how the service user voice is traditionally expressed in healthcare evaluation, the paper then proceeds to explore the particular role and challenges faced by clinician-evaluators, including their role as 'privileged interlocutors' in conversations with service users. The tensions in reconciling the role of the clinician as an expert, with the related but different skills needed for effective discourse in qualitative evaluation are explored, and it is asserted that it is important for clinicians and leaders to be comfortable in showing and working with vulnerability when evaluating healthcare interventions. Clinicians are already skilled in holding discourse with service users, and extending the communication repertoire to include the management of emotion and expression of vulnerability is achievable and rewarding. The paper concludes that the ability to hold a vulnerable stance when conducting evaluation can have benefits in reducing defensiveness, encouraging a truer sense of enquiry and amplifying the service user voice.

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The way caregivers think of their infants and young children may impact caregiving behavior. One way to assess caregivers' thoughts of their young children is to prompt them to describe the child's personality. Popular methods to analyzing valenced language include the use of software approaches, which have limitations in scoring and application. The present investigation offers an alternative scoring system for the emotional tone of words and phrases relevant to descriptions of infants and children. Using a database of personality descriptions provided by pregnant people and parents to describe their child's personality, we asked experts in infant mental health and related disciplines (N = 51) to rate the words/phrases with regard to the emotional tone or connotation of the descriptive words provided (e.g., positive, neutral, or negative). Experts (i.e., participants) were individuals with self-reported expertise in infants and young children via their profession. Participants were recruited via email to known infant and early childhood mental health practicians and researchers and through participant referral. A total of 496 unique words or phrases were rated by the experts, and in order to reduce participant burden, experts were randomly assigned approximately half of the words. From these ratings, we computed a continuous measure of average valence score across all raters and a categorical variable representing expert consensus (i.e., if ≥80 % of experts agreed it was positive or negative it was assigned that category, otherwise it was assigned neutral). As such, the data provided include caregiver adjectives used to describe their young children, expert ratings of the emotional tone of the provided description, average emotional tone for each word, and expert consensus for each word.

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This chapter discusses methods for incorporating DNA barcode information into formal taxonomic descriptions. We first review what a formal description entails and then discuss previous attempts to incorporate barcode information into taxonomic descriptions. Several computer programs are listed that extract diagnostics from DNA barcode data. Finally, we examine a test case (Astraptes taxonomy).

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Being able to represent and remember verbally-encoded information about spatial environments from different perspectives is important for numerous daily activities. The present study examined how frequently individuals spontaneously engage in visual mental imagery and verbal rehearsal strategies in memory recall of spatial descriptions, and whether using certain strategies is associated with better recall performance. Memory recall for route (person-centred) and survey (object-centred) spatial descriptions was examined in a sample of 105 neurotypical individuals, who also reported to what extent they used route- and survey-based mental imagery and verbal rehearsal strategies in each description. Results showed that participants favoured a path visualisation strategy to recall the route description and a map visualisation strategy to recall the survey description. Regression models further showed that employing both imagery and verbal strategies was associated with better recall for both route and survey descriptions, although imagery strategies held a higher predictive power. The present findings highlight the fact that the spontaneous use of internal strategies in the form of visual imagery and verbal rehearsal is ubiquitous when recalling spatial descriptions and a core part of efficient spatial memory functioning.

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Fungi are among the least known organisms on earth, with an estimated number of species between 1.5 and 10 million. This number is expected to be refined, especially with increasing knowledge about microfungi in undersampled habitats and increasing amounts of data derived from environmental DNA sequencing. A significant proportion of newly generated sequences fail to match with already named species, and thus represent what has been referred to as fungal "dark taxa". Due to the challenges associated with observing, identifying, and preserving sporophores, many macro- and microfungal species are only known from a single collection, specimen, isolate, and/or sequence-a singleton. Mycologists are consequently used to working with "rare" sequences and specimens. However, rarity and singleton phenomena lack consideration and valorization in fungal studies. In particular, the practice of publishing new fungal species names based on a single specimen remains a cause of debate. Here, we provide some elements of reflection on this issue in the light of the specificities of the fungal kingdom and global change context. If multiple independent sources of data support the existence of a new taxon, we encourage mycologists to proceed with formal description, irrespective of the number of specimens at hand. Although the description of singleton-based species may not be considered best practice, it does represent responsible science in the light of closing the Linnean biodiversity shortfall.

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PURPOSE: To develop a Korean version of simple, intuitive descriptions (SIDs) for clinical use of the generic functioning domains in the International Classification of Disease 11th revision (ICD-11) Chapter V. METHODS: The initial Korean SID version proposal for the International Classification of Functioning, Disability, and Health (ICF) Rehabilitation set was translated following the Italian version. The remaining 17 codes were developed using original ICF descriptions; WHO Disability Assessment Schedule, Model Disability Survey, Korean Classification of Functioning, Disability, and Health; and previous studies. The final proposal for the Korean version of SIDs was selected through virtual conferences and three rounds of voting. RESULTS: This study developed SIDs for the 47 generic functioning domains in the Chapter V of ICD-11. However, the SID for 20 of the 47 codes was confirmed in vote A, for 23 codes in vote B and for the remaining 4 in the final vote. All experts agreed with the final SID proposal. CONCLUSIONS: This is the first study in South Korea to attempt the development of SIDs for ICD-11 Chapter V. Therefore, the findings of this study could be used to evaluating of disability, functioning when ICD-11 is adopted for use in Korean clinical settings.

Simple, intuitive descriptions (SIDs) highlight the core concepts of the ICF category definitions in a user-friendly manner and enhance the utility of the ICF for routine clinical practice.The 11^th revision of the International Classification of Disease (ICD-11) was developed in 2019 with the addition of Chapter V which reflects functioning domains and better explains the association between functioning and disease.In addition, Chapter V is based on ICF, so the concept of ICF must be included, and concept definition is required for use in clinical practice.This study developed a Korean version of SIDs for clinical use of the generic functioning domains in the ICD-11 Chapter V.

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The family Peptostreptococcaceae, which contains 15 genera including Clostridioides, presently lacks proper circumscription. Using 52 available genomes for Peptostreptococcaceae species, we report comprehensive phylogenomic and comparative analyses to reliably discern their evolutionary relationships. In phylogenetic trees based on core genome proteins and 16S rRNA gene sequences, the examined species formed a strongly supported clade designated as Peptostreptococcaceae sensu stricto. This clade encompassed the genera Peptostreptococcus (type genus), Asaccharospora, Clostridioides, Intestinibacter, Paeniclostridium, Paraclostridium, Peptacetobacter, Romboutsia and Terrisporobacter, and two misclassified species (viz. Eubacterium tenue and 'Clostridium dakarense'). The distinctness of this clade is strongly supported by eight identified conserved signature indels (CSIs), which are specific for the species from this clade. Based on the robust evidence provided by presented studies, we are proposing the emendment of family Peptostreptococcaceae to only the genera within the Peptostreptococcaceae sensu stricto clade. We also report 67 other novel CSIs, which reliably demarcate different Peptostreptococcaceae species clades and clarify the classification of some misclassified species. Based on the consistent evidence obtained from different presented studies, we are making the following proposals to clarify the classification of Peptostreptococcaceae species: (i) transfer of Eubacterium tenue, Paeniclostridium ghonii and Paeniclostridium sordellii as comb. nov. into the genus Paraclostridium; (ii) transfer of Clostridioides mangenotii as a comb. nov. into Metaclostridioides gen. nov.; (iii) classification of 'Clostridium dakarense' as a novel species Faecalimicrobium dakarense gen. nov., sp. nov. (type strain FF1T; genome and 16S rRNA accession numbers GCA_000499525.1 and KC517358, respectively); (iv) transfer of two misclassified species, Clostridium paradoxum and Clostridium thermoalcaliphilum, into Alkalithermobacter gen. nov.; and (v) proposals for two novel families, Peptoclostridiaceae fam. nov. and Tepidibacteraceae fam. nov., to accommodate remaining unclassified Peptostreptococcaceae genera. The described CSIs specific for different families and genera provide novel and reliable means for the identification, diagnostics and biochemical studies on these bacteria.

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PURPOSE: Shoulder dystocia is an obstetric emergency with severe complications. Our objective was to evaluate the major pitfalls in the diagnostics of shoulder dystocia, diagnostic descriptions documented in medical records, use of obstetric maneuvers, and their correlations to Erb's and Klumpke's palsy and the use of ICD-10 code 066.0. METHODS: A retrospective, register-based case-control study included all deliveries (n = 181 352) in Hospital District of Helsinki and Uusimaa (HUS) area in 2006-2015. Potential shoulder dystocia cases (n = 1708) were identified from the Finnish Medical Birth Register and the Hospital Discharge Register using ICD-10 codes O66.0, P13.4, P14.0, and P14.1. After thorough assessment of all medical records, 537 shoulder dystocia cases were confirmed. Control group consisted of 566 women without any of these ICD-10 codes. RESULTS: The pitfalls in the diagnostic included suboptimal following of guidelines for making the diagnosis of shoulder dystocia, subjective interpretation of diagnostic criteria, and inexact or inadequate documentation in medical records. The diagnostic descriptions in medical record were highly inconsistent. The use of obstetric maneuvers was suboptimal among shoulder dystocia cases (57.5%). Overall, the use of obstetric maneuvers increased during the study period (from 25.7 to 97.0%, p < 0.001), which was associated with decreasing rate of Erb's palsy and increasing use of ICD-10 code O66.0. CONCLUSION: There are diagnostic pitfalls, which could be addressed by education regarding shoulder dystocia guidelines, by improved use obstetric maneuvers, and more precise documentation. The increased use of obstetric maneuvers was associated with lower rates of Erb's palsy and improved coding of shoulder dystocia.

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In this study, we investigate the application of generative models to assist artificial agents, such as delivery drones or service robots, in visualising unfamiliar destinations solely based on textual descriptions. We explore the use of generative models, such as Stable Diffusion, and embedding representations, such as CLIP and VisualBERT, to compare generated images obtained from textual descriptions of target scenes with images of those scenes. Our research encompasses three key strategies: image generation, text generation, and text enhancement, the latter involving tools such as ChatGPT to create concise textual descriptions for evaluation. The findings of this study contribute to an understanding of the impact of combining generative tools with multi-modal embedding representations to enhance the artificial agent's ability to recognise unknown scenes. Consequently, we assert that this research holds broad applications, particularly in drone parcel delivery, where an aerial robot can employ text descriptions to identify a destination. Furthermore, this concept can also be applied to other service robots tasked with delivering to unfamiliar locations, relying exclusively on user-provided textual descriptions.

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Nereididae is among the most familiar of marine annelid families, common and well-studied in most marine environments but paradoxically no recent key or identification guide exists to the world's genera. Here updated generic descriptions, a list of characters, a linear key to genera, and minimal diagnoses that distinguish each genus from all others in the family are provided. This information is generated from a Delta database of 186 morphological characters and a link is provided to downloadable software allowing the same data to be interrogated using the open-source Delta program Intkey - a nonlinear multiple entry point computerised interactive key. For each genus the recent literature is also summarised, comments on taxonomic status provided, and published keys to species cited. Nexus format matrices are provided for all 45 genera and 158 Nereididae species, representing all genera, scored for 146 multistate characters from the same character list to facilitate future phylogenetic studies.

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Many original descriptions of beetles were published in Latin with specific idioms and technical terms, which are sometimes difficult to understand. The exact meaning of these descriptions is necessary for taxonomic and systematic research. Of the ten Palaearctic Plateumaris species regarded as valid three were described in English, the remaining seven in Latin, French, or German: P.amurensis Weise, 1898, P.bracata (Scopoli, 1772), P.consimilis (Schrank, 1781), P.roscida Weise, 1912, P.rustica (Kunze, 1818), P.sericea (Linnaeus, 1758), and P.weisei (Duvivier, 1885). These seven non-English original descriptions and their translations into English are presented here. Additionally, the translations of the first descriptions of the genus Plateumaris and of its 19 synonyms (some were described in Russian, also) are given.

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The present study examined the effects of study schedule (interleaving vs. blocking) and feature descriptions on category learning and metacognitive predictions of learning. Across three experiments, participants studied exemplars from different rock categories and later had to classify novel exemplars. Rule-based and information-based categorization was also manipulated by selecting rock sub-categories for which the optimal strategy was the one that aligned with the extraction of a simple rule, or the one that required integration of information that may be difficult to describe verbally. We observed consistent benefits of interleaving over blocking on rock classification, which generalized to both rule-based (Experiment 1) and information-integration learning (Experiments 1-3). However, providing feature descriptions enhanced classification accuracy only when the stated features were diagnostic of category membership, indicating that their benefits were limited to rule-based learning (Experiment 1) and did not generalize to information-integration learning (Experiments 1-3). Furthermore, our examination of participants' metacognitive predictions demonstrated that participants were not aware of the benefits of interleaving on category learning. Additionally, providing feature descriptions led to higher predictions of categorization even when no significant benefits on actual performance were exhibited.

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The family Staphylococcacae and genus Gemella contain several organisms of clinical or biotechnological importance. We report here comprehensive phylogenomic and comparative analyses on 112 available genomes from species in these taxa to clarify their evolutionary relationships and classification. In a phylogenomic tree based on 678 core proteins, Gemella species were separated from Staphylococcacae by a long branch indicating that they constitute a distinct family (Gemellaceae fam. nov.). In this tree, Staphylococcacae species formed two main clades, one encompassing the genera Aliicoccus, Jeotgalicoccus, Nosocomiicoccus and Salinicoccus (Family "Salinicoccaceae"), while the other clade consisted of the genera Macrococcus, Mammaliicoccus and Staphylococcus (Family Staphylococcaceae emend.). In this tree, species from the genera Gemella, Jeotgalicoccus, Macrococcus and Salinicoccus each formed two distinct clades. Two species clades for these genera are also observed in 16S rRNA gene trees and supported by average amino acid identity analysis. We also report here detailed analyses on protein sequences from Staphylococcaceae and Gemella genomes to identify conserved signature indels (CSIs) which are specific for different genus and family-level clades. These analyses have identified 120 novel CSIs robustly demarcating different proposed families and genera. The identified CSIs provide independent evidence that the genera Gemella, Jeotgalicoccus, Macrococcus and Salinicoccus consist of two distinct clades, which can be reliably distinguished based on multiple exclusively shared CSIs. We are proposing transfers of the species from the novel clades of the above four genera into the genera Gemelliphila gen. nov., Phocicoccus gen. nov., Macrococcoides gen. nov. and Lacicoccus gen. nov., respectively. The identified CSIs also provide strong evidence for division of Staphylococcaceae into an emended family Staphylococcaceae and two new families, Abyssicoccaceae fam. nov. and Salinicoccaceae fam. nov. All of these families can be reliably demarcated based on several exclusively shared CSIs.

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The taxonomy of the potamid genus Lacunipotamon Dai, Song, He, Cao, Xu & Zhong, 1975, is revised. Three species are known from southern China: L. albusorbitum Dai, Song, He, Cao, Xu & Zhong, 1975 (type species); L. yuanshi Huang, Shih & Ahyong, 2020; and L. cymatile Huang, Shih & Ahyong, 2020. Eight new species are here described from northern Vietnam: L. globus, L. panda, L. contrastum, L. sublividum, L. mimicum, L. thuanchau, L. pectum and L. purpureum. This is the first record of the genus in Vietnam, with all the new species obtained from karst formations. The species are differentiated by the characters of carapace shape, anterolateral armature, posterior margin of the epistome, male sternopleonal cavity, chelipeds, ambulatory legs, male thoracic sternum, male pleon, and structures of the male first gonopods and vulvae.

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Structuring jobs into occupations is the first step for analysis tasks in many fields of research, including economics and public health, as well as for practical applications like matching job seekers to available jobs. We present a data resource, derived with natural language processing techniques from over 42 million unstructured job postings in the National Labor Exchange, that empirically models the associations between occupation codes (estimated initially by the Standardized Occupation Coding for Computer-assisted Epidemiological Research method), skill keywords, job titles, and full-text job descriptions in the United States during the years 2019 and 2021. We model the probability that a job title is associated with an occupation code and that a job description is associated with skill keywords and occupation codes. Our models are openly available in the sockit python package, which can assign occupation codes to job titles, parse skills from and assign occupation codes to job postings and resumes, and estimate occupational similarity among job postings, resumes, and occupation codes.

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Research on video anomaly detection has mainly been based on video data. However, many real-world cases involve users who can conceive potential normal and abnormal situations within the anomaly detection domain. This domain knowledge can be conveniently expressed as text descriptions, such as "walking" or "people fighting", which can be easily obtained, customized for specific applications, and applied to unseen abnormal videos not included in the training dataset. We explore the potential of using these text descriptions with unlabeled video datasets. We use large language models to obtain text descriptions and leverage them to detect abnormal frames by calculating the cosine similarity between the input frame and text descriptions using the CLIP visual language model. To enhance the performance, we refined the CLIP-derived cosine similarity using an unlabeled dataset and the proposed text-conditional similarity, which is a similarity measure between two vectors based on additional learnable parameters and a triplet loss. The proposed method has a simple training and inference process that avoids the computationally intensive analyses of optical flow or multiple frames. The experimental results demonstrate that the proposed method outperforms unsupervised methods by showing 8% and 13% better AUC scores for the ShanghaiTech and UCFcrime datasets, respectively. Although the proposed method shows -6% and -5% than weakly supervised methods for those datasets, in abnormal videos, the proposed method shows 17% and 5% better AUC scores, which means that the proposed method shows comparable results with weakly supervised methods that require resource-intensive dataset labeling. These outcomes validate the potential of using text descriptions in unsupervised video anomaly detection.

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Physalis (Solanaceae, Solanoideae) is an American genus of ca. 90 species, with its diversity centered on Mexico. We recognize 61 species within the country, for which we provide a generic morphological description, an artificial key to determine species, and brief descriptions. We include distributions, habitats, diagnostic characters, phenology, and uses. Distribution maps and field photographs are also provided. We include conservation status as evaluated by the IUCN.

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Introduction: Increasing obesity rates around the globe have challenged policymakers to find strategies to prompt healthier eating habits. While unhealthy eating takes place in many different contexts, dining out is a context where individuals often choose an unhealthy option despite the availability of healthier alternatives. One possible explanation for this behavior is the unhealthy-tasty intuition, which refers to the belief that unhealthy food is tastier than healthy food. Nevertheless, many policymakers and restaurant managers follow the - in this context - counterintuitive approach of using health claims to nudge people towards more healthy eating choices or habits. Methods: The current research employs an online experiment with 137 participants and investigates how health claims and sensory claims impact on the purchase intention of healthy options for desserts. Furthermore, it explores how health inferences and taste expectations mediate the intention to purchase. Results and discussion: Findings from the online experiment confirm that health claims prompt positive health inferences, while also stimulating unfavorable taste expectations, resulting in a lower intention to purchase. Surprisingly, we found no effect of a sensory claim on taste expectations. The findings of our experiment contradict the unhealthy-tasty intuition by revealing a significant positive correlation between taste expectations and health inferences. While both health inferences and taste expectations impact positively on purchasing intentions for the health-claim condition, the indirect effect of taste expectations was stronger than the indirect effect of health inferences.

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