Completed questionnaires.

<p>Number of questionnaires completed during different days of the week and times of the day.</p

Po\ue9tiques des archives. Gen\ue8se des traductions et communaut\ue9s de pratique [monografico della rivista Transalpina, n. 18 - 2015]

Ce num\ue9ro de Transalpina, n\ue9 de la synergie entre les traductologues de l'\ue9quipe ERLIS et le groupe de recherche \uab Multilinguisme, Traduction, Cr\ue9ation \ubb de l'ITEM, s'interroge sur la po\ue9tique du traducteur en action \ue0 partir de ses archives. Les archives \u2013 m\ue9moire des traductions \ue0 travers les traces de leur gen\ue8se (brouillons, tapuscrits, dialogues \ue9pistolaires...) \u2013 ne sont pas seulement le lieu o\uf9 l\u2019on peut observer le traducteur \ue0 l\u2019\u153uvre, mais aussi un espace heuristique de reconfiguration de notre relation aux savoirs : le lieu et l\u2019espace o\uf9 tradition, traduction et invention nous donnent rendez-vous pour reconstituer \u2013 au plan g\ue9n\ue9tique, philologique et herm\ue9neutique \u2013 le processus traductif en tant que pratique r\ue9flexive et identitaire, collaborative et sociale. Dans un parcours privil\ue9giant les \ue9changes litt\ue9raires franco-italiens \u2013 Bona de Mandiargues et Alberto Savinio, Giorgio Caproni et Andr\ue9 Fr\ue9naud, Camillo Sbarbaro et Gustave Flaubert, Andr\ue9 P\ue9zard et Dante\u2026 \u2013, les contributions ici r\ue9unies prennent en compte la pluritextualit\ue9 et la sp\ue9cificit\ue9 processuelle des pratiques traduisantes : la traduction comme dispositif d\u2019\ue9criture (Nicole Brossard), la relation entre \ue9criture et autotraduction, la traduction \ue0 quatre mains (Amelia Rosselli), la retraduction et ses variantes. Par la richesse de ses approches et de ses analyses, ce volume contribue \ue0 tisser des liens nouveaux entre traductologie, philologie et critique g\ue9n\ue9tique, critique des traductions et historiographie litt\ue9raire, tout en soulignant le r\uf4le jou\ue9 par des dispositifs mat\ue9riels et symboliques dans l\u2019\ue9mergence des communaut\ue9s du traduire

Experience of positive and negative emotions by day of the week.

<p>Experience of positive and negative emotions by day of the week.</p

Emotional experience by time of day per emotion.

<p>Emotional experience by time of day per emotion.</p

QuoidbachSupplementalMaterial_rev – Supplemental material for Happiness and Social Behavior

Supplemental material, QuoidbachSupplementalMaterial_rev for Happiness and Social Behavior by Jordi Quoidbach, Maxime Taquet, Martin Desseilles, Yves-Alexandre de Montjoye and James J. Gross in Psychological Science</p

QuoidbachOpenPracticesDisclosure_rev – Supplemental material for Happiness and Social Behavior

Supplemental material, QuoidbachOpenPracticesDisclosure_rev for Happiness and Social Behavior by Jordi Quoidbach, Maxime Taquet, Martin Desseilles, Yves-Alexandre de Montjoye and James J. Gross in Psychological Science</p

COVID-19 cohort, and for COVID-19 and influenza cohorts after propensity score matching.

Only characteristics with a prevalence higher than 5% in the unmatched COVID-19 cohort are presented here; for additional baseline characteristics and outcomes, see Tables A and B in S1 Tables.</p

Supporting Tables.

Table A. Characteristics of the unmatched COVID-19 cohort and the matched COVID-19 and influenza cohorts. Table B. Contributions of incidence (within 6 months of a diagnosis of COVID-19 vs. influenza) of subcategories making up the clinical features of long-COVID in matched cohorts. Table C. Incidence of long-COVID features in the whole cohort of patients with COVID-19 within the entire follow-up period (0–6 months), the first half of the follow-up period (0–3 months), and the second half of the follow-up period (3–6 months). In the analysis of the 3–6-month follow-up, those who had the long-COVID feature recorded in the first 3 months and then again in the next 3 months were included so that the sum of the incidences in the two-halves of the follow-up window exceeds the total incidence. Table D. Absolute risk increase in COVID-19 vs. influenza (a positive number indicates a higher risk in COVID-19) in the whole 0–6-month period as well as the “long” phase (3–6 months). Table E. 95% CIs corresponding to the entries in Fig 3A of the main manuscript, i.e., for the incidence (on the diagonal) and co-occurrence (off-diagonal) of long-COVID features in the 6 months after a diagnosis of COVID-19. Table F. 95% CIs corresponding to the entries in Fig 3B of the main manuscript, i.e., for the incidence (on the diagonal) and co-occurrence (off-diagonal) of long-COVID features in the period extending from 3 to 6 months after a diagnosis of COVID-19. Table G. 95% CIs corresponding to the entries in Fig 3C of the main manuscript, i.e., for the HRs of the incidence (on the diagonal) and co-occurrence (off-diagonal) of long-COVID features in the 6 months after a diagnosis of COVID-19 vs. influenza. All corresponding p-values were p = 0.0007). Table H. 95% CIs corresponding to the entries in Fig 3D of the main manuscript, i.e., for the HRs of the incidence (on the diagonal) and co-occurrence (off-diagonal) of long-COVID features in the period extending from 3 to 6 months after a diagnosis of COVID-19 vs. influenza. All corresponding p-values were p = 0.1476), myalgia and cognitive symptoms (p = 0.1292), and myalgia and pain (p = 0.0139). Table I. p-values for the test of proportional hazards (obtained using the generalized Schoenfeld test) for the main analysis (1 day to 6 months follow-up) and the analysis restricted to the 3 months–6 months follow-up. A value lower than 0.05 indicates evidence for nonproportional hazards. Table J. Average degrees of the clinical feature networks in the different comparisons between cohorts. p-values were obtained using permutation tests. Table K. 6-month incidence of individual long-COVID features and of any feature in different subgroups of patients (defined by sex, race, or age) diagnosed with COVID-19. Table L. 6-month incidence of individual long-COVID features and of any feature in different subgroups of patients defined by indices of severity of COVID-19 illness. Table M. Characteristics of the female and male COVID-19 cohorts after propensity score matching. Table N. Characteristics of the non-white and white COVID-19 cohorts after propensity score matching. Table O. Characteristics of the age 45+ and age 10–44 COVID-19 cohorts after propensity score matching. Table P. Characteristics of the age 65+ and age 45–64 COVID-19 cohorts after propensity score matching. Table Q. Characteristics of the age 22–44 and age 10–21 COVID-19 cohorts after propensity score matching. Table R. Characteristics of COVID-19 cohorts requiring and not requiring hospitalization, after propensity score matching. Table S. Characteristics of COVID-19 cohorts requiring and not requiring ITU admission, after propensity score matching. Table T. Characteristics of leukocytosis and non-leukocytosis COVID-19 cohorts after propensity score matching. Table U. Mean count number of occurrences of each and any long-COVID feature among patients who have them recorded at least once, in the 6 months after a diagnosis of COVID-19 or influenza (using matched cohorts). The p-value tests the hypothesis that the counts are equal between the cohorts. Table V. Comparison in the 6-month incidence of any pain, between patients with COVID-19 and a matched cohort of patients with influenza. Any pain in this analysis refers to the composite endpoint of chest/throat pain, headache, myalgia, other pain (as defined in Supporting Methods D) or abdominal and pelvic pain (a subcategory of the abdominal symptoms also defined in Supporting Methods D). CI, confidence interval; COVID-19, Coronavirus Disease 2019; HR, hazard ratio; ITU, intensive treatment unit; SMD, standardized mean difference. (DOCX)</p

Supporting Methods.

Supporting Methods A. TriNetX network. Supporting Methods B. Definition of cohorts. Supporting Methods C. Definition of covariates. Supporting Methods D. Definition of outcomes. Supporting Methods E. Details on statistical analyses. Supporting Methods F. Details on secondary analyses. (DOCX)</p

The STROBE Checklist for this manuscript.

(DOCX)</p