Partner phubbing: portuguese validation partner phubbing

O presente estudo tem como objetivo traduzir e validar a escala de Partner Phubbing para a população portuguesa. O Phubbing é definido como o comportamento ou a ação de ignorar o outro no contacto presencial para se focar nas suas comunicações através do smartphone. Este comportamento está cada vez mais presente nas relações socias, um estudo anterior indicou que 14% dos participantes apresentavam padrões de dependência ao smartphone. Através de questionários online foram recrutados 351 participantes com mais de 16 anos (M=32.8 SD=11.78). A escala Pphubbing mostrou ter uma fiabilidade adequada (α=.861), todos os itens apresentaram distribuição normal e através da análise fatorial confirmatória foi obtido um modelo com ajustamento adequado (x2 /df=2.979, RMSEA= 0.081, NFI= 0.964, CFI= 0.976). Contudo o item 7 não contribuiu significativamente para a escala (-.016). O item 7, o único item criado na negativa precisa de ser reavaliado. Deste modo, em estudos futuros deverá ser usado na mesma direção que os restantes itens da escala ou deverá ser alterada a sua posição na mesma. Apesar desta limitação, a escala Pphubbing é um instrumento válido para ser utilizado na população portuguesa e para ser utilizado neste novo campo de investigação.info:eu-repo/semantics/publishedVersio

Study of the gastroprotective action and healing effects of Kalanchoe pinnata (Lam.) against acidified ethanol- and acetic acid-induced gastric ulcers in rats / Estudo da acção gastroprotectora e dos efeitos curativos de Kalanchoe pinnata (Lam.) contra úlceras gástricas induzidas por etanol acidificado e ácido acético em ratos

Kalanchoe pinnata (Lam.) Pers. (Crassulaceae) is a commonly used species in traditional medicine in Brazil for the treatment of various diseases, including gastric ulcers. This research aims to evaluate the antiulcer aspects of Kalanchoe pinnata leaves. The LD50 value of the hydroethanolic extract (HE) of K. pinnata was 1341.46 mg/kg, after the in vitro cytotoxicity assay. In the phytochemical analysis, several flavonoids were identified in the HE and ethyl acetate fraction (EAF) of K. pinnata. It was verified that the gastroprotective activity of the HE of K. pinnata involved prostaglandins and sulfhydryl compounds. However, the mechanism of gastroprotection of the EAF of K. pinnata is dependent on prostaglandins and nitric oxide. The ulcer healing activity of the HE of K. pinnata was also evaluated. According to the macroscopic results, doses of 200 mg/kg and 400 mg/kg reduced the injury area, with rates of 33% and 39%, respectively, after 7 days of treatment (p <0.05). Histological analysis showed regeneration of the gastric mucosa and re-establishment of the glandular architecture in groups treated with the HE (200 and 400 mg/kg). Antioxidant enzymes (CAT, SOD and GPx) were evaluated in the mechanism of gastric ulcer healing. The results showed that the antiulcerogenic activity was mediated by SOD. The anti-Helicobacter pylori activity was also evaluated; however, the HE did not show anti-H. pylori activity. Analysis of the results suggests that K. pinnata has therapeutic potential against gastric ulcers and that the flavonoids may be linked to the biological effects

Heavy quarkonium: progress, puzzles, and opportunities

A golden age for heavy quarkonium physics dawned a decade ago, initiated by the confluence of exciting advances in quantum chromodynamics (QCD) and an explosion of related experimental activity. The early years of this period were chronicled in the Quarkonium Working Group (QWG) CERN Yellow Report (YR) in 2004, which presented a comprehensive review of the status of the field at that time and provided specific recommendations for further progress. However, the broad spectrum of subsequent breakthroughs, surprises, and continuing puzzles could only be partially anticipated. Since the release of the YR, the BESII program concluded only to give birth to BESIII; the $B$-factories and CLEO-c flourished; quarkonium production and polarization measurements at HERA and the Tevatron matured; and heavy-ion collisions at RHIC have opened a window on the deconfinement regime. All these experiments leave legacies of quality, precision, and unsolved mysteries for quarkonium physics, and therefore beg for continuing investigations. The plethora of newly-found quarkonium-like states unleashed a flood of theoretical investigations into new forms of matter such as quark-gluon hybrids, mesonic molecules, and tetraquarks. Measurements of the spectroscopy, decays, production, and in-medium behavior of c\bar{c}, b\bar{b}, and b\bar{c} bound states have been shown to validate some theoretical approaches to QCD and highlight lack of quantitative success for others. The intriguing details of quarkonium suppression in heavy-ion collisions that have emerged from RHIC have elevated the importance of separating hot- and cold-nuclear-matter effects in quark-gluon plasma studies. This review systematically addresses all these matters and concludes by prioritizing directions for ongoing and future efforts.Comment: 182 pages, 112 figures. Editors: N. Brambilla, S. Eidelman, B. K. Heltsley, R. Vogt. Section Coordinators: G. T. Bodwin, E. Eichten, A. D. Frawley, A. B. Meyer, R. E. Mitchell, V. Papadimitriou, P. Petreczky, A. A. Petrov, P. Robbe, A. Vair

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost