270 research outputs found

    Beauty and the Flirt: Male Physical Attractiveness and Approaches to Relationship Initiation

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    This multi-study investigation explored how women evaluate men’s approach strategies. In Study 1, 330 participants generated 546 verbal strategies used in courtship initiation. Strategies were rated on three dimensions that define relationships: affiliation, dominance, and explicitness. Affiliation and explicitness were related to strategy flirtatiousness. In Study 2, 361 females participated in an experiment that explored the effects of four approach strategies used by an attractive or unattractive man on conversation continuance and future interaction. Attractive men using inviting, playful, and less annoying messages were most successful. Study 3 (N = 398) replicated Study 2 using different approach strategies, and also demonstrated male attractiveness, affiliation and explicitness inform message flirtatiousness and influence courtship outcomes. Results suggest approach strategy, but not male attractiveness, influence perceived first date goals

    Enacting a Culture of Access in Our Conference Spaces

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    The article offers information on periodical\u27s rhetoric and writing studies conference held in September 2020. Topics discussed include prioritizing access in the service of love, justice, connection and liberation; proposing expansive frameworks for access in designing accessible writing classrooms and professional events; and major principles of definition of access, which reflect access\u27s complexity and liberatory potential such as dynamic, relational and intersectional

    Assessment of burnout in veterinary medical students using the Maslach Burnout Inventory-Educational Survey: a survey during two semesters

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    BACKGROUND: Burnout among veterinary students can result from known stressors in the absence of a support system. The objectives of this study were to evaluate use of the Maslach Burnout Inventory-Educator Survey (MBI-ES) to assess burnout in veterinary students and evaluate the factors that predict the MBI-ES scores. METHODS: The MBI-ES was administered to first (Class of 2016) and second year (Class of 2015) veterinary medical students during the 2012-2013 academic year in the fall and spring semesters. Factor analysis and test reliability for the survey were determined. Mean scores for the subscales determining burnout namely emotional exhaustion (EE), depersonalization (DP) and lack of personal accomplishment (PA) were calculated for both classes in the 2 semesters. Multiple regression analysis was performed to evaluate other factors that predict the MBI-ES scores. RESULTS: A non-probability sampling method was implemented consisting of a voluntary sample of 170 and 123 students in the fall and spring semesters, respectively. Scores for EE, DP and PA were not different between the 2 classes within the same semester. Mean ± SD scores for EE, DP and PA for the fall semester were 22.9 ± 9.6, 5.0 ± 4.8 and 32.3 ± 6.7, respectively. Mean ± SD scores for EE, DP and PA the spring semester were 27.8 ± 10.7, 6.5 ± 6.1and 31.7 ± 6.8, respectively. The EE score was higher in spring compared to fall while DP and PA scores were not different between the 2 semesters. Living arrangements specifically as to whether or not a student lived with another veterinary medical students was the only variable significantly associated with the MBI-ES scores. Students in this study had moderate levels of burnout based on the MBI-ES scores. CONCLUSIONS: The MBI-ES was an acceptable instrument for assessing burnout in veterinary medical students. The EE scores were higher in the spring semester as compared to the fall semester. Thus students in the first and second years of veterinary school under the current curriculum experience the greatest levels of emotional exhaustion during the spring semester. This has administrative implications for the school, when considering the allocation and use of resources for student support systems during each semester

    Prebiotic synthesis of phosphoenol pyruvate by α-phosphorylation-controlled triose glycolysis

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    Phosphoenol pyruvate is the highest-energy phosphate found in living organisms and is one of the most versatile molecules in metabolism. Consequently, it is an essential intermediate in a wide variety of biochemical pathways, including carbon fixation, the shikimate pathway, substrate-level phosphorylation, gluconeogenesis and glycolysis. Triose glycolysis (generation of ATP from glyceraldehyde 3-phosphate via phosphoenol pyruvate) is among the most central and highly conserved pathways in metabolism. Here, we demonstrate the efficient and robust synthesis of phosphoenol pyruvate from prebiotic nucleotide precursors, glycolaldehyde and glyceraldehyde. Furthermore, phosphoenol pyruvate is derived within an α-phosphorylation controlled reaction network that gives access to glyceric acid 2-phosphate, glyceric acid 3-phosphate, phosphoserine and pyruvate. Our results demonstrate that the key components of a core metabolic pathway central to energy transduction and amino acid, sugar, nucleotide and lipid biosyntheses can be reconstituted in high yield under mild, prebiotically plausible conditions

    A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis

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    Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4% and 25.2%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≄4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches

    Expert range maps of global mammal distributions harmonised to three taxonomic authorities

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    Aim: Comprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW). Location: Global. Taxon: All extant mammal species. Methods: Range maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species). Results: Range maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use. Main conclusion: Expert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control.Fil: Marsh, Charles J.. Yale University; Estados UnidosFil: Sica, Yanina. Yale University; Estados UnidosFil: Burguin, Connor. University of New Mexico; Estados UnidosFil: Dorman, Wendy A.. University of Yale; Estados UnidosFil: Anderson, Robert C.. University of Yale; Estados UnidosFil: del Toro Mijares, Isabel. University of Yale; Estados UnidosFil: Vigneron, Jessica G.. University of Yale; Estados UnidosFil: Barve, Vijay. University Of Florida. Florida Museum Of History; Estados UnidosFil: Dombrowik, Victoria L.. University of Yale; Estados UnidosFil: Duong, Michelle. University of Yale; Estados UnidosFil: Guralnick, Robert. University Of Florida. Florida Museum Of History; Estados UnidosFil: Hart, Julie A.. University of Yale; Estados UnidosFil: Maypole, J. Krish. University of Yale; Estados UnidosFil: McCall, Kira. University of Yale; Estados UnidosFil: Ranipeta, Ajay. University of Yale; Estados UnidosFil: Schuerkmann, Anna. University of Yale; Estados UnidosFil: Torselli, Michael A.. University of Yale; Estados UnidosFil: Lacher, Thomas. Texas A&M University; Estados UnidosFil: Wilson, Don E.. National Museum of Natural History; Estados UnidosFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Centro de Estudios ParasitolĂłgicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios ParasitolĂłgicos y de Vectores; ArgentinaFil: Aguirre, Luis F.. Universidad Mayor de San SimĂłn; BoliviaFil: Arroyo Cabrales, JoaquĂ­n. Instituto Nacional de AntropologĂ­a E Historia, Mexico; MĂ©xicoFil: AstĂșa, Diego. Universidade Federal de Pernambuco; BrasilFil: Baker, Andrew M.. Queensland University of Technology; Australia. Queensland Museum; AustraliaFil: Braulik, Gill. University of St. Andrews; Reino UnidoFil: Braun, Janet K.. Oklahoma State University; Estados UnidosFil: Brito, Jorge. Instituto Nacional de Biodiversidad; EcuadorFil: Busher, Peter E.. Boston University; Estados UnidosFil: Burneo, Santiago F.. Pontificia Universidad CatĂłlica del Ecuador; EcuadorFil: Camacho, M. Alejandra. Pontificia Universidad CatĂłlica del Ecuador; EcuadorFil: de Almeida Chiquito, Elisandra. Universidade Federal do EspĂ­rito Santo; BrasilFil: Cook, Joseph A.. University of New Mexico; Estados UnidosFil: CuĂ©llar Soto, Erika. Sultan Qaboos University; OmĂĄnFil: Davenport, Tim R. B.. Wildlife Conservation Society; TanzaniaFil: Denys, Christiane. MusĂ©um National d'Histoire Naturelle; FranciaFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Eldridge, Mark D. B.. Australian Museum; AustraliaFil: Fernandez Duque, Eduardo. University of Yale; Estados UnidosFil: Francis, Charles M.. Environment And Climate Change Canada; CanadĂĄFil: Frankham, Greta. Australian Museum; AustraliaFil: Freitas, Thales. Universidade Federal do Rio Grande do Sul; BrasilFil: Friend, J. Anthony. Conservation And Attractions; AustraliaFil: Giannini, Norberto Pedro. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico - TucumĂĄn. Unidad Ejecutora Lillo; ArgentinaFil: Gursky-Doyen, Sharon. Texas A&M University; Estados UnidosFil: HacklĂ€nder, Klaus. Universitat Fur Bodenkultur Wien; AustriaFil: Hawkins, Melissa. National Museum of Natural History; Estados UnidosFil: Helgen, Kristofer M.. Australian Museum; AustraliaFil: Heritage, Steven. University of Duke; Estados UnidosFil: Hinckley, Arlo. Consejo Superior de Investigaciones CientĂ­ficas. EstaciĂłn BiolĂłgica de Doñana; EspañaFil: Holden, Mary. American Museum of Natural History; Estados UnidosFil: Holekamp, Kay E.. Michigan State University; Estados UnidosFil: Humle, Tatyana. University Of Kent; Reino UnidoFil: Ibåñez Ulargui, Carlos. Consejo Superior de Investigaciones CientĂ­ficas. EstaciĂłn BiolĂłgica de Doñana; EspañaFil: Jackson, Stephen M.. Australian Museum; AustraliaFil: Janecka, Mary. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Jenkins, Paula. Natural History Museum; Reino UnidoFil: Juste, Javier. Consejo Superior de Investigaciones CientĂ­ficas. EstaciĂłn BiolĂłgica de Doñana; EspañaFil: Leite, Yuri L. R.. Universidade Federal do EspĂ­rito Santo; BrasilFil: Novaes, Roberto Leonan M.. Universidade Federal do Rio de Janeiro; BrasilFil: Lim, Burton K.. Royal Ontario Museum; CanadĂĄFil: Maisels, Fiona G.. Wildlife Conservation Society; Estados UnidosFil: Mares, Michael A.. Oklahoma State University; Estados UnidosFil: Marsh, Helene. James Cook University; AustraliaFil: Mattioli, Stefano. UniversitĂ  degli Studi di Siena; ItaliaFil: Morton, F. Blake. University of Hull; Reino UnidoFil: Ojeda, Agustina Alejandra. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Ordóñez Garza, NictĂ©. Instituto Nacional de Biodiversidad; EcuadorFil: Pardiñas, Ulises Francisco J.. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Centro Nacional PatagĂłnico. Instituto de Diversidad y EvoluciĂłn Austral; ArgentinaFil: Pavan, Mariana. Universidade de Sao Paulo; BrasilFil: Riley, Erin P.. San Diego State University; Estados UnidosFil: Rubenstein, Daniel I.. University of Princeton; Estados UnidosFil: Ruelas, Dennisse. Museo de Historia Natural, Lima; PerĂșFil: Schai-Braun, StĂ©phanie. Universitat Fur Bodenkultur Wien; AustriaFil: Schank, Cody J.. University of Texas at Austin; Estados UnidosFil: Shenbrot, Georgy. Ben Gurion University of the Negev; IsraelFil: Solari, Sergio. Universidad de Antioquia; ColombiaFil: Superina, Mariella. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Mendoza. Instituto de Medicina y BiologĂ­a Experimental de Cuyo; ArgentinaFil: Tsang, Susan. American Museum of Natural History; Estados UnidosFil: Van Cakenberghe, Victor. Universiteit Antwerp; BĂ©lgicaFil: Veron, Geraldine. UniversitĂ© Pierre et Marie Curie; FranciaFil: Wallis, Janette. Kasokwa-kityedo Forest Project; UgandaFil: Whittaker, Danielle. Michigan State University; Estados UnidosFil: Wells, Rod. Flinders University.; AustraliaFil: Wittemyer, George. State University of Colorado - Fort Collins; Estados UnidosFil: Woinarski, John. Charles Darwin University; AustraliaFil: Upham, Nathan S.. University of Yale; Estados UnidosFil: Jetz, Walter. University of Yale; Estados Unido

    Expert range maps of global mammal distributions harmonised to three taxonomic authorities

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    AimComprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW).LocationGlobal.TaxonAll extant mammal species.MethodsRange maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species).ResultsRange maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use.Main conclusionExpert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control
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