Brain energy metabolism: A roadmap for future research

Although we have learned much about how the brain fuels its functions over the last decades, there remains much still to discover in an organ that is so complex. This article lays out major gaps in our knowledge of interrelationships between brain metabolism and brain function, including biochemical, cellular, and subcellular aspects of functional metabolism and its imaging in adult brain, as well as during development, aging, and disease. The focus is on unknowns in metabolism of major brain substrates and associated transporters, the roles of insulin and of lipid droplets, the emerging role of metabolism in microglia, mysteries about the major brain cofactor and signaling molecule NAD+, as well as unsolved problems underlying brain metabolism in pathologies such as traumatic brain injury, epilepsy, and metabolic downregulation during hibernation. It describes our current level of understanding of these facets of brain energy metabolism as well as a roadmap for future research

Factors contributing to posttraumatic growth and its buffering effect in adult chidren of cancer patients undergoing treatment

This study examined relationships among demographic, clinical, and psychosocial variables in adult children of cancer patients. Two hundred and fourteen participants completed measures of posttraumatic growth (PTG), distress, posttraumatic stress disorder (PTSD) symptoms, social support, and family functioning. Significant gender differences in all PTG dimensions were found, as well as associations among PTG, gender, parental dependency, distress, PTSD, and family functioning. Social support was not a mediator in the relationship between gender and PTG. Gender, education, disease duration, dependency, distress, and family flexibility predicted PTG. Finally, PTG had amoderating effect in the relationship between distress and PTSD/social support. These results may guide psychosocial interventions in this population.Fundação para a Ciência e Tecnologia (FCT

Purpose in life and reasons for living as mediators of the relationship between stress, coping, and suicidal behavior

Positive psychological factors that help protect vulnerable persons from suicidal behavior are vital in understanding resiliency and suicide prevention. The purpose of the current study was to examine whether positive factors (including purpose in life, reasons for living, and coping styles) mediate the relationship between stressful life events and suicidal behaviors among 416 college student volunteers. Reasons for living inversely predicted suicidal behavior and thoughts directly as well as indirectly via an inverse relationship with depression. Purpose in life indirectly predicted suicidal behavior and thoughts via an inverse effect on depression, whereas emotion-focused coping indirectly predicted suicidal behavior and thoughts both through an effect on depression and an inverse effect on reasons for living. In addition, avoidant coping indirectly predicted suicidal behavior via a direct, positive effect on reasons for living. Reasons for living and emotion-oriented coping had the largest effects in the model. Results of this study underscore the importance of augmenting reasons for living and purpose in life among suicidal or potentially suicidal persons

Mobile robot scheduling for cycle time optimization in flow-shop cells, a case study

The typical production system in carton box production companies is cell-production. These cells normally benefit from a mobile robot which serves the machines according to a given schedule. One of the main problems of such companies is finding the order of robot moves in a way that the time required for completing all jobs is minimized. In the studied case in this research, each cell contains three machines of which, two or three of them might be activated for production process depending on the product type. These machines are equipped with a one-capacitated input and output buffer. Considering the fact that the machines are capable of performing any operation, the assignments of the jobs to them may have several alternatives. The one-capacitated buffers make the robot scheduling more complex as they act as extra stations to be served by the robot (contribute to exponential increase in job assignments permutation). This study aims to deal with this complexity and provide a decision-making toolbox for business owners to determine and employ the best robot moving schedule according to the characteristics of the problem. The mentioned approach significantly contributes to decision-maker’s effective time management and results in adopting a better production scheme for each production cycle. In line with this prospect, this research proposes a sequential part production matrix (SPPM) to determine feasible robot move strategies through which the best scheduling scheme is introduced for different problem configurations. Additionally, a metaheuristic algorithm is proposed to determine the best robot move strategy for cases with more active machines in a cell as manual determination of the robot move strategies becomes exhaustive in such cases.</p