Multiple SNP Markers Reveal Fine-Scale Population and Deep Phylogeographic Structure in European Anchovy (Engraulis encrasicolus L.)

10 p.

GFAP Isoforms in Adult Mouse Brain with a Focus on Neurogenic Astrocytes and Reactive Astrogliosis in Mouse Models of Alzheimer Disease

24 p.

Angela Carter's focus on celluloid dreams

Santamaría, José Miguel; Pajares, Eterio; Olsen, Vickie; Merino, Raquel; Eguíluz, Federico (eds.)

Black Holes, Cosmological Solutions, Future Singularities, and Their Thermodynamical Properties in Modified Gravity Theorie

54 p.

Religious Coping, Social Support and Subjective Severity as Predictors of Posttraumatic Growth in People Affected by the Earthquake in Chile on 27/2/2010

The aim of this research is to study the impact of religious coping, social support and subjective severity on Posttraumatic Growth (PTG) in people who lost their homes after the earthquake in Chile in 2010 and who now live in transitional shelters. One hundred sixteen adult men and women were evaluated using a subjective severity scale, the Posttraumatic Growth Inventory (PTGI), the Multidimensional Scale of Perceived Social Support (MSPSS) scale of social support and the Brief RCOPE scale of religious coping. The multiple linear regression analysis shows that social support and positive religious coping have an impact on PTG. On using a bootstrap estimate, it was found that positive religious coping fully mediates the relationship between subjective severity and PTG.

Deep learning review and its applications

Deep neural networks have recently gained popularity for improv- ing state-of-the-art machine learning algorithms in diverse areas such as speech recognition, computer vision and bioinformatics. Convolutional networks especially have shown prowess in visual recognition tasks such as object recognition and detection in which this work is focused on. Mod- ern award-winning architectures have systematically surpassed previous attempts at tackling computer vision problems and keep winning most current competitions. After a brief study of deep learning architectures and readily available frameworks and libraries, the LeNet handwriting digit recognition network study case is developed, and lastly a deep learn- ing network for playing simple videogames is reviewed.

Bipolar disorder comorbid with alcohol use disorder: Focus on neurocognitive correlates

Bipolar disorder (BD) and alcohol use disorders (AUDs) are usually comorbid, and both have been associated with significant neurocognitive impairment. Patients with the BD-AUD comorbidity (dual diagnosis) may have more severe neurocognitive deficits than those with a single diagnosis, but there is paucity of research in this area. To explore this hypothesis more thoroughly, we carried out a systematic literature review through January 2015. Eight studies have examined the effect of AUDs on the neurocognitive functioning of BD patients. Most studies found that BD patients with current or past history of comorbid AUDs show more severe impairments, especially in verbal memory and executive cognition, than their non-dual counterparts. Greater neurocognitive dysfunction is another facet of this severe comorbid presentation. Implications for clinical practice and research are discussed. Specifically, the application of holistic approaches, such as clinical staging and systems biology, may open new avenues of discoveries related to the BD-AUD comorbidity.