University of Turku

About: University of Turku is a education organization based out in Turku, Finland. It is known for research contribution in the topics: Population & Galaxy. The organization has 16296 authors who have published 45124 publications receiving 1505428 citations. The organization is also known as: Turun yliopisto & Åbo universitet.

The spitzer survey of stellar structure in galaxies (S^4G): multi-component decomposition strategies and data release

Abstract: The Spitzer Survey of Stellar Structure in Galaxies (S^4G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S(^4)G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sersic fits, and 2-component Sersic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sersic index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G_PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions, as well as our mask editing procedure (MASK_EDIT) used in data preparation. A detailed analysis of the bulge, disk, and bar parameters derived from multi-component decompositions will be published separately.

Seasonal changes in birch leaf chemistry: are there trade-offs between leaf growth and accumulation of phenolics?

Abstract: Several plant-herbivore hypotheses are based on the assumption that plants cannot simultaneously allocate resources to growth and defence. We studied seasonal patterns in allocation to growth and putatively defensive compounds by monitoring several chemical and physical traits in the leaves of mountain birch from early June (budburst) to late September (leaf senescence). We found significant seasonal changes in all measured characteristics, both in terms of concentrations (mg g–1) and amounts (mg leaf–1). Changes were very rapid in the spring, slow in the middle of the season, and there was another period of fast changes in the senescing leaves. Co-occurring changes in physical leaf traits and concentrations of several compounds indicated a seasonal decline in foliage suitability for herbivores. Concentrations of protein and free amino acids declined through the growing season whereas individual sugars showed variable seasonal patterns. The seasonal trends of phenolic groups differed drastically: concentrations of soluble proanthocyanidins increased through the season, whereas cell wall-bound proanthocyanidins, gallotannins and flavonoid glycosides declined after an initial increase in young leaves. We failed to find proof that the seasonal accumulation of phenolics would have been seriously compromised by leaf or shoot growth, as assumed by the growth/differentiation balance hypothesis and the protein competition model hypothesis. On the contrary, there was a steady increase in the total amount of phenolics per leaf even during the most active leaf growth.

Life satisfaction and depression in a 15-year follow-up of healthy adults.

Abstract: The aim of this study was to investigate the cross-sectional and longitudinal relationship between life satisfaction and depressive symptoms in healthy adults. This is a 15-year prospective cohort study with a nationwide sample of healthy Finnish adults (N=9679), aged 18–45, who responded to postal questionnaires in 1975, 1981 and 1990 including a 4-item life satisfaction (LS) scale (range 4–20) and, in 1990, the 21-item Beck Depression Inventory (BDI). A strong linear association was found between concurrent LS and BDI scales (r=0.6). With an LS cut-off point of 11/12, moderate/severe depression (BDI ≥ 19) was detected with 87% sensitivity, 88 % specificity and a 94% area under the ROC curve. Longitudinally, a strongly increased risk of moderate/severe depression in 1990 was observed among the dissatisfied (LS 12–20) compared with the satisfied (LS 4–6) in 1975 (OR=6.7; 95 %CI 4.2–10.9) and in 1981 (OR=10.4; 6.1–17.6). The 4-item LS scale can identify a group of healthy people from the general population with a high risk of having or developing depressive symptoms. Since low life satisfaction also indicates an elevated risk of other adverse health outcomes, the assessment of subjective well-being should be encouraged both in surveys and in clinical practice.

Impact of Online Information on Self-Isolation Intention During the COVID-19 Pandemic: Cross-Sectional Study.

Abstract: Background: During the coronavirus disease (COVID-19) pandemic, governments issued movement restrictions and placed areas into quarantine to combat the spread of the disease. In addition, individuals were encouraged to adopt personal health measures such as social isolation. Information regarding the disease and recommended avoidance measures were distributed through a variety of channels including social media, news websites, and emails. Previous research suggests that the vast amount of available information can be confusing, potentially resulting in overconcern and information overload. Objective: This study investigates the impact of online information on the individual-level intention to voluntarily self-isolate during the pandemic. Using the protection-motivation theory as a framework, we propose a model outlining the effects of cyberchondria and information overload on individuals’ perceptions and motivations. Methods: To test the proposed model, we collected data with an online survey (N=225) and analyzed it using partial least square-structural equation modeling. The effects of social media and living situation were tested through multigroup analysis. Results: Cyberchondria and information overload had a significant impact on individuals’ threat and coping perceptions, and through them on self-isolation intention. Among the appraisal constructs, perceived severity (P=.002) and self-efficacy (P=.003) positively impacted self-isolation intention, while response cost (P<.001) affected the intention negatively. Cyberchondria (P=.003) and information overload (P=.003) indirectly affected self-isolation intention through the aforementioned perceptions. Using social media as an information source increased both cyberchondria and information overload. No differences in perceptions were found between people living alone and those living with their families. Conclusions: During COVID-19, frequent use of social media contributed to information overload and overconcern among individuals. To boost individuals’ motivation to adopt preventive measures such as self-isolation, actions should focus on lowering individuals’ perceived response costs in addition to informing them about the severity of the situation.