An Evaluation of the COVID-19 Pandemic and Perceived Social Distancing Policies in Relation to Planning, Selecting, and Preparing Healthy Meals: An Observational Study in 38 Countries Worldwide

Objectives: To examine changes in planning, selecting, and preparing healthy foods in relation to personal factors (time, money, stress) and social distancing policies during the COVID-19 crisis. Methods: Using cross-sectional online surveys collected in 38 countries worldwide in April-June 2020 (N = 37,207, Mage 36.7 SD 14.8, 77% women), we compared changes in food literacy behaviors to changes in personal factors and social distancing policies, using hierarchical multiple regression analyses controlling for sociodemographic variables. Results: Increases in planning (4.7 SD 1.3, 4.9 SD 1.3), selecting (3.6 SD 1.7, 3.7 SD 1.7), and preparing (4.6 SD 1.2, 4.7 SD 1.3) healthy foods were found for women and men, and positively related to perceived time availability and stay-at-home policies. Psychological distress was a barrier for women, and an enabler for men. Financial stress was a barrier and enabler depending on various sociodemographic variables (all p < 0.01). Conclusion: Stay-at-home policies and feelings of having more time during COVID-19 seem to have improved food literacy. Stress and other social distancing policies relate to food literacy in more complex ways, highlighting the necessity of a health equity lens. Copyright 2021 De Backer, Teunissen, Cuykx, Decorte, Pabian, Gerritsen, Matthys, Al Sabbah, Van Royen and the Corona Cooking Survey Study Group.This research was funded by the Research Foundation Flanders (G047518N) and Flanders Innovation and Entrepreneurship (HBC.2018.0397). These funding sources had no role in the design of the study, the analysis and interpretation of the data or the writing of, nor the decision to publish the manuscript.Scopu

An Original UWB Radar Platform Based on Coherent Interleaving Sampling Technique

International audienc

Radar ULB fondé sur la Technique de Sous-Echantillonnage Cohérent

International audienceUne architecture originale de système de radar Ultra Large Bande (ULB) est présentée. Elle est fondée sur une technique de sous-échantillonnage entrelacé cohérent (Coherent interleaving sampling (CIS)) grâce à l'utilisation d'un récepteur à base d'échantillonneur-bloqueur large-bande (Track and Hold Amplifier (THA)). Le récepteur de ce radar ULB possède une bande passante RF très large [DC-5] GHz. Dans la maquette de démonstration de ce radar, un générateur d'impulsions ultra courtes (100 ps) à base de portes logiques a été conçu. Dans un souci d'intégration, la maquette fonctionne aussi avec une horloge commune qui assure la cohérence entre l'émission et la réception. Une démonstration de type radar SAR (Synthetic Aperture Radar) est réalisée avec cette architecture. Elle permet l'obtention d'images et la détection d'échos faibles avec une dynamique d'environ 40 dB et une résolution en profondeur de l'ordre du centimètre

Interpreting overlaps in business process mapping via organisational soft knowledge flows

Knowledge Management (KM) as the term implies, is broadly about improving knowledge use within an organisation. At a lower level, Business Process Management (BPM) is the set of management activities related to business processes that can ideally be arranged in a life cycle. Social Network Analysis (SNA) is a technique enabling the researcher to better understand interactions between people. Relatively little research has been conducted with regard to the crossover of social networks and workflows, with the aim of examining workflows as management views them, as opposed to the actual social interactions of staff. Improvements in the overlay of management interpretations of work and real social networks could potentially lead to improvements in business process efficacy. In this study SNA diagrams are examined in order to implement executable models and potentially enable automated analysis of workflows. A means of converting SNA data to Business Process workflows is presented and an example provided.14 page(s

Synthetic event logs for multi-perspective trace clustering

The data set contains a set of event logs for evaluating multi-perspective trace clustering approaches in process mining. Event logs were randomly generated from 5 different process models of different complexity levels. The attribute "cluster" refers to the ground truth label. Clusters can only be correctly identified when considering both, the data and the control flow perspective (attributes and trace)