Elsevier COVID-19 Research Environment Showcase

My data

This article discusses new innovative technologies, the role and ways of their implementation and application in the tourism activities of the Republic of Kazakhstan. Opportunities raised of artificial intelligence (AI) the mentioned, both in hotel and in tourism enterprises. Artificial intelligence and Chatbots help predict process and analyze data on personalized requests, recommendations and customer service. The implementation of smart technologies in hotels, automation of registration processes, the use of chatbots, voice assistants and mobile applications for ordering services helps tourists plan trips, book hotels, search for routes in real time for a comfortable trip. Virtual reality (VR), taking into account the preferences of tourists, allows you to create virtual tours and enrich real trips with digital elements that are more educational and exciting. A brief overview of the existing innovations in the tourism industry of our country and foreign countries. The statistics of the goals of tourists visiting Kazakhstan are given. Proposed to create an application that displays all existing tourist routes in one place.

We selected datasets that are indexed by the Data Monitor search engine on the 2022 monkeypox outbreak. The aim was to make it easier to find potentially relevant datasets for this specific topic

In the initial testing phase, I administered the DPSS-24 to a sample of 21 participants to evaluate its reliability, validity, and practical application. This small yet insightful sample provided preliminary data, highlighting response patterns that helped refine the scale’s structure and effectiveness. I analyzed each participant’s responses, comparing them with established psychopathy measures to ensure that the DPSS-24 could offer a nuanced, comprehensive assessment. My goal with the DPSS-24 is to provide a reliable tool for both research and clinical settings, contributing to a deeper understanding of psychopathy and supporting psychological evaluation and intervention strategies. The dataset contains sample responses for the Deenz Psychopathy Spectrum Scale (DPSS-24), collected from 21 participants. Each participant responded to 24 items on a Likert scale ranging from 1 to 5, where 1 indicates low agreement and 5 indicates high agreement with psychopathy-related traits (such as impulsivity, emotional detachment, and interpersonal challenges). Each item reflects a specific aspect of psychopathy, and responses are aggregated to provide an overall psychopathy score for each participant. This dataset serves as a preliminary evaluation tool to assess the scale’s consistency, reliability, and initial descriptive patterns. Overall Psychopathy Score: For each participant, scores across the 24 items were summed, resulting in a total psychopathy score. Higher scores suggest a greater presence of psychopathy traits. Score Range: The psychopathy scores in this sample of 21 participants range from approximately 24 (minimal psychopathy traits) to 120 (maximum psychopathy traits). Mean Score: The average psychopathy score for this sample was calculated to provide a central measure. Standard Deviation: This was used to observe the variability in psychopathy scores among participants. Item-level Analysis: Responses for each of the 24 items were analyzed individually to detect any trends in specific traits that appeared more consistently across participants. Initial Reliability Check: Cronbach’s alpha was calculated to assess internal consistency across items, which is a preliminary indicator of the scale’s reliability. A Cronbach’s alpha value close to or above 0.7 is generally considered acceptable in psychometric research. Interpretation: The sample data suggests that the DPSS-24 can differentiate between varying levels of psychopathy traits.

A set of four nested PySpark notebooks on Elsevier’s cloud-based computational platform powered by Databricks that constitute a customisable research tool for studying researcher mobility.

Elsevier's 2024 Gender Report tracks and analyzes data across 18 countries and 2 regions (EU 27 and the world) examining women’s performance in research and innovation across disciplines and career stages. Our Report provides new insights into interdisciplinarity, multidisciplinarity, grant recipients, patent applications, open access, UN Sustainable Development Goals (SDG) research areas, as well as alternative metrics including policy and media citations. More information at https://www.elsevier.com/en-au/insights/gender-and-diversity-in-research

The current report presents the first results of the International survey “Covid-19 Student Well-Being Study” carried out by EKKE (National Centre for Social Research) between 13 May-12 June 2020 with the participation of students enrolled in Greece’s higher education institutions. The survey was designed by the University of Antwerp in collaboration with the University of Ghent in Belgium. A total of 27 European and North American countries, as well South-Africa participated in the study.

HW_NoVPN_NMLSC_02Sep2020(DT1.1)

Archivos en Excel de aplicación a expertos para validación de instrumento de evaluación. Uno de los instrumentos es aplicado para validez aparente (VALIDACIÓN-UNIMINUTO SECCIONAL ANTIOQUIA-CHOCÓ) y otro instrumento es de validez de constructo (VALIDACIÓN-UNIMINUTO SECCIONAL ANTIOQUIA-CHOCÓ - Segunda Parte).

The global research community is making progress, albeit slowly, towards the full and equal participation of women. This webinar recording presents highlights from a major new data-driven analysis of gender diversity in research. Building on prior work by Elsevier, this analysis draws on Scopus data stretching back more than two decades to assess the representation of women in research and changes over time, in a global context and for 18 countries. Beyond examining men’s and women’s research participation and research footprint, new insights will be presented on gender participation across career stages, in areas such as interdisciplinarity and multidisciplinarity, open access publication, SDGs, mentorship contribution, and alternative metrics, to paint a fuller picture of the state of gender equity in the global research ecosystem and inform evidence-based policy and interventions. You will learn about: The benefits of adopting a longer time frame for academic evaluation and assessments; The impact of hiring and retaining senior women researchers; The importance of including societal impact metrics in evaluations or career assessments, and more. The webinar can be visioned at : https://researcheracademy.elsevier.com/communicating-research/inclusion-diversity-researchers/progress-toward-gender-equality-research