Network Segregation Predicts Processing Speed in the Cognitively Healthy Oldest-old

AbstractFunctional connections among groups of brain areas give insight into the brain’s organization. The cognitive effects of aging may relate to the brain’s large-scale organization. Examining the relationship between individual differences in brain organization and cognitive function in healthy older adults can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry. We found that the segregation of the cortical association system and the segregation of individual networks within that system [the fronto-parietal network (FPN), cingulo-opercular network (CON) and default mode network (DMN)], were strong predictors of overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals experiencing successful cognitive aging.</jats:p

Wettability of Aqueous Rhamnolipids Solutions Produced by Pseudomonas aeruginosa LBI

The wetting behavior of rhamnolipids produced by Pseudomonas aeruginosa LBI strain grown on waste oil substrate and sodium dodecyl sulfate (SDS) on glass, polyethylene terephthalate (PET), poly(vinyl chloride) (PVC), poly(epsilon-caprolactone) (PCL) and polymer blend (PVC-PCL) was investigated by the measuring contact angle of sessile drops, to determine the wetting characteristics of rhamnolipids. The comparison of the wetting profiles showed that at low SDS and rhamnolipid concentrations, the contact angle increased and when the concentration of the surfactant increased further, the contact angle decreased. The blend surface (PVC-PCL) showed better wettability than the homopolymers themselves and the blend changed the surface hydrophobicity of the polymer, making it more hydrophilic. The rhamnolipids produced by the LBI strain exhibited superior wetting abilities than the chemical surfactant SDS one. This is the first work that evaluates the wetting properties of rhamnolipids on polymer blends.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

The impact of big data on world-class sustainable manufacturing

Big data (BD) has attracted increasing attention from both academics and practitioners. This paper aims at illustrating the role of big data analytics in supporting world-class sustainable manufacturing (WCSM). Using an extensive literature review to identify different factors that enable the achievement of WCSM through BD and 405 usable responses from senior managers gathered through social networking sites (SNS), we propose a conceptual framework using constructs obtained using reduction of gathered data that summarizes this role; test this framework using data which is heterogeneous, diverse, voluminous, and possess high velocity; and highlight the importance for academia and practice. Finally, we conclude our research findings and further outlined future research directions