What Twitter Profile and Posted Images Reveal About Depression and Anxiety

Previous work has found strong links between the choice of social media images and users' emotions, demographics and personality traits. In this study, we examine which attributes of profile and posted images are associated with depression and anxiety of Twitter users. We used a sample of 28,749 Facebook users to build a language prediction model of survey-reported depression and anxiety, and validated it on Twitter on a sample of 887 users who had taken anxiety and depression surveys. We then applied it to a different set of 4,132 Twitter users to impute language-based depression and anxiety labels, and extracted interpretable features of posted and profile pictures to uncover the associations with users' depression and anxiety, controlling for demographics. For depression, we find that profile pictures suppress positive emotions rather than display more negative emotions, likely because of social media self-presentation biases. They also tend to show the single face of the user (rather than show her in groups of friends), marking increased focus on the self, emblematic for depression. Posted images are dominated by grayscale and low aesthetic cohesion across a variety of image features. Profile images of anxious users are similarly marked by grayscale and low aesthetic cohesion, but less so than those of depressed users. Finally, we show that image features can be used to predict depression and anxiety, and that multitask learning that includes a joint modeling of demographics improves prediction performance. Overall, we find that the image attributes that mark depression and anxiety offer a rich lens into these conditions largely congruent with the psychological literature, and that images on Twitter allow inferences about the mental health status of users.Comment: ICWSM 201

Medium Modifications of Hadron Properties and Partonic Processes

Chiral symmetry is one of the most fundamental symmetries in QCD. It is closely connected to hadron properties in the nuclear medium via the reduction of the quark condensate , manifesting the partial restoration of chiral symmetry. To better understand this important issue, a number of Jefferson Lab experiments over the past decade have focused on understanding properties of mesons and nucleons in the nuclear medium, often benefiting from the high polarization and luminosity of the CEBAF accelerator. In particular, a novel, accurate, polarization transfer measurement technique revealed for the first time a strong indication that the bound proton electromagnetic form factors in 4He may be modified compared to those in the vacuum. Second, the photoproduction of vector mesons on various nuclei has been measured via their decay to e+e- to study possible in-medium effects on the properties of the rho meson. In this experiment, no significant mass shift and some broadening consistent with expected collisional broadening for the rho meson has been observed, providing tight constraints on model calculations. Finally, processes involving in-medium parton propagation have been studied. The medium modifications of the quark fragmentation functions have been extracted with much higher statistical accuracy than previously possible.Comment: to appear in J. Phys.: Conf. Proc. "New Insights into the Structure of Matter: The First Decade of Science at Jefferson Lab", eds. D. Higinbotham, W. Melnitchouk, A. Thomas; added reference

Early treatment with ambrisentan of mildly elevated mean pulmonary arterial pressure associated with systemic sclerosis: a randomized, controlled, double-blind, parallel group study (EDITA study)

OBJECTIVE: The objective of this randomized, placebo-controlled, double-blind, parallel group, trial was to assess the effect of ambrisentan on mean pulmonary arterial pressure (mPAP) in patients with systemic sclerosis (SSc) and mildly elevated pulmonary hypertension (PH). METHODS: Thirty-eight SSc patients with mildly elevated mPAP at rest between 21 and 24 mmHg and/or > 30 mmHg during low-dose exercise were randomly assigned to treatment with either ambrisentan 5-10 mg/day or placebo. Right heart catheterization and further clinical parameters were assessed at baseline and after 6 months. The primary endpoint was the difference of mPAP change at rest between groups. RESULTS: After 6 months, the two groups did not differ in the primary endpoint (ambrisentan mPAP - 1 ± 6.4 mmHg vs. placebo - 0.73 ± 3.59 mmHg at rest, p = 0.884). However, three patients from the placebo group but none of the ambrisentan group progressed to SSc-associated pulmonary arterial hypertension. Furthermore, ambrisentan treatment showed significant improvements in the secondary endpoints cardiac index (CI) and pulmonary vascular resistance (PVR) at rest (CI 0.36 ± 0.66 l/min/m2 vs. - 0.31 ± 0.71 l/min/m2, p = 0.010; PVR - 0.70 ± 0.78 WU vs. 0.01 ± 0.71 WU, p = 0.012) and during exercise (CI 0.7 ± 0.81 l/min/m2 vs. - 0.45 ± 1.36 l/min/m2, p = 0.015; PVR - 0.84 ± 0.48 WU vs. - 0.0032 ± 0.34 WU, p < 0.0001). CONCLUSION: This is the first randomized, double-blind, placebo-controlled study testing the effect of ambrisentan in patients with mildly elevated mPAP and/or exercise PH. The primary endpoint change in mPAP did only tendentially improve in the ambrisentan group, but the significant improvement of other hemodynamic parameters points to a possible benefit of ambrisentan and will be helpful to design future trials. TRIAL REGISTRATION: www.ClinicalTrials.gov, unique identifier NCT: NCT02290613 , registered 14th of November 2014

Global transpiration data from sap flow measurements: The SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN. © 2021 Rafael Poyatos et al.This research was supported by the Minis-terio de Economía y Competitividad (grant no. CGL2014-55883-JIN), the Ministerio de Ciencia e Innovación (grant no. RTI2018-095297-J-I00), the Ministerio de Ciencia e Innovación (grant no. CAS16/00207), the Agència de Gestió d’Ajuts Universitaris i de Recerca (grant no. SGR1001), the Alexander von Humboldt-Stiftung (Humboldt Research Fellowship for Experienced Researchers (RP)), and the Institució Catalana de Recerca i Estudis Avançats (Academia Award (JMV)). Víctor Flo was supported by the doctoral fellowship FPU15/03939 (MECD, Spain)

Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts

Objective: The abundance of text available in social media and health related forums along with the rich expression of public opinion have recently attracted the interest of the public health community to use these sources for pharmacovigilance. Based on the intuition that patients post about Adverse Drug Reactions (ADRs) expressing negative sentiments, we investigate the effect of sentiment analysis features in locating ADR mentions. Methods: We enrich the feature space of a state-of-the-art ADR identification method with sentiment analysis features. Using a corpus of posts from the DailyStrength forum and tweets annotated for ADR and indication mentions, we evaluate the extent to which sentiment analysis features help in locating ADR mentions and distinguishing them from indication mentions. Results: Evaluation results show that sentiment analysis features marginally improve ADR identification in tweets and health related forum posts. Adding sentiment analysis features achieved a statistically significant F-measure increase from 72.14% to 73.22% in the Twitter part of an existing corpus using its original train/test split. Using stratified 10 10-fold cross-validation, statistically significant F-measure increases were shown in the DailyStrength part of the corpus, from 79.57% to 80.14%, and in the Twitter part of the corpus, from 66.91% to 69.16%. Moreover, sentiment analysis features are shown to reduce the number of ADRs being recognized as indications. Conclusion: This study shows that adding sentiment analysis features can marginally improve the performance of even a state-of-the-art ADR identification method. This improvement can be of use to pharmacovigilance practice, due to the rapidly increasing popularity of social media and health forums

Global transpiration data from sap flow measurements : the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr" R package - designed to access, visualize, and process SAPFLUXNET data - is available from CRAN.Peer reviewe