Social and Psychological Features of Hardiness in Personality of Students of Higher Education Institutions

The topicality and significance of the study is determined by the fact that life and activity of a person in contemporary socio-economic conditions are inextricably connected with the constant impact of adverse social, political, economic and other factors on him. These factors are accompanied by the emergence of various kinds of difficult life situations, as a result of which stress develops in a person. In the student milieu, stress arises under the influence of difficulties associated with both the learning process and life circumstances. The paper presents the results of an empirical study of socio-psychological features of hardiness in students of higher educational institutions. The methods of research comprised: theoretical analysis, empirical research (testing), qualitative analysis of the obtained data, mathematical and statistical data processing (SPSS Statistics, Excel). Testing included the following psycho-diagnostic tools: the author’s questionnaire for assessing stressful situations; McCrae-Costa Five-Factor Personality Questionnaire (The Big Five dimensions); “Hardiness test”; Self-attitude technique. The validity and reliability of the study results was ensured by the initial methodological positions, the use of proven tools, sample representativeness of the research, as well as mathematical processing of data with the use of a software package for statistical analysis. As a result of the study, it was proved that emotion-focused ways of overcoming stress associated with a decrease in tension and a change in attitude to emerging difficulties prevail among the students of both the experimental and control groups. A high level of stress was found in the majority of subjects. In order to reduce this stress, it is necessary for students to form special skills to overcome it. In addition, an analysis of the psychological factors of students’ hardiness made it possible to determine the main areas of their psychological support in overcoming difficult life situations (development of qualities that form the core of students’ personal adaptive potential, the formation of their social competency, enrichment of social networks, as well as learning ways to find and accept social support)

Six pelagic seabird species of the North Atlantic engage in a fly-and-forage strategy during their migratory movements

Bird migration is commonly defined as a seasonal movement between breeding and non-breeding grounds. It generally involves relatively straight and directed large-scale movements, with a latitudinal change, and specific daily activity patterns comprising less or no foraging and more traveling time. Our main objective was to describe how this general definition applies to seabirds. We investigated migration characteristics of 6 pelagic seabird species (little auk Alle alle, Atlantic puffin Fratercula arctica, common guillemot Uria aalge, Brünnich’s guillemot U. lomvia, black-legged kittiwake Rissa tridactyla and northern fulmars Fulmarus glacialis). We analysed an extensive geolocator positional and saltwater immersion dataset from 29 colonies in the North-East Atlantic and across several years (2008-2019). We used a novel method to identify active migration periods based on segmentation of time series of track characteristics (latitude, longitude, net-squared displacement). Additionally, we used the saltwater immersion data of geolocators to infer bird activity. We found that the 6 species had, on average, 3 to 4 migration periods and 2 to 3 distinct stationary areas during the non-breeding season. On average, seabirds spent the winter at lower latitudes than their breeding colonies and followed specific migration routes rather than non-directionally dispersing from their colonies. Differences in daily activity patterns were small between migratory and stationary periods, suggesting that all species continued to forage and rest while migrating, engaging in a ‘fly-and-forage’ migratory strategy. We thereby demonstrate the importance of habitats visited during seabird migrations as those that are not just flown over, but which may be important for re-fuelling.publishedVersio

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Vertical Cylinder-to-Lamella Transition in Thin Block Copolymer Films Induced by In-Plane Electric Field

Morphological transition between hexagonal and lamellar patterns in thin polystyrene–block–poly(4-vinyl pyridine) films simultaneously exposed to a strong in-plane electric field and saturated solvent vapor is studied with atomic force and scanning electron microscopy. In these conditions, standing cylinders made of 4-vinyl pyridine blocks arrange into threads up to tens of microns long along the field direction and then partially merge into standing lamellas. In the course of rearrangement, the copolymer remains strongly segregated, with the minor component domains keeping connectivity between the film surfaces. The ordering tendency becomes more pronounced if the cylinders are doped with Au nanorods, which can increase their dielectric permittivity. Non-selective chloroform vapor works particularly well, though it causes partial etching of the indium tin oxide cathode. On the contrary, 1,4-dioxane vapor selective to polystyrene matrix does not allow for any morphological changes

Ultrathin Polydiacetylene-Based Synergetic Composites with Plasmon-Enhanced Photoelectric Properties

Fabricating plasmon-enhanced organic nanomaterials with technologically relevant supporting architectures on planar solids remains a challenging task in the chemistry of thin films and interfaces. In this work, we report a bottom-up assembly of ultrathin layered composites of conductive polymers with photophysical properties enhanced by gold nanoparticles. The polydiacetylene component was formed by photopolymerization of a catanionic mixture of pentacosadiynoic surfactants on a surface of citrate-stabilized gold hydrosol monitored by a fiber optic spectrometer. Microscopic examination of the 3 nm thick solid-immobilized film showed that gold nanoparticles (AuNPs) do not aggregate within the monolayer upon polymerization. This polydiacetylene/AuNPs monolayer was coupled with 60 nm thick polyaniline-based layer deposited atop. The resulting polymer composite with an integrated 4-stripe electric cell showed nonadditive electric behavior due to the formation of electron–hole pairs with increased charge carrier mobility at the interface between the polymer layers. Under visible light irradiation of the composite film, a plasmonic effect of the gold nanoparticles was observed at the onset of photoconductivity, although neither polydiacetylene nor the polyaniline component alone are photoconductive polymers. The results indicate that our bottom-up strategy can be expanded to design other plasmon-enhanced ultrathin polymer composites with potential applications in optoelectronics and photovoltaics