Reproducibility and Characterization of Head Kinematics During a Large Animal Acceleration Model of Traumatic Brain Injury

Acceleration parameters have been utilized for the last six decades to investigate pathology in both human and animal models of traumatic brain injury (TBI), design safety equipment, and develop injury thresholds. Previous large animal models have quantified acceleration from impulsive loading forces (i.e., machine/object kinematics) rather than directly measuring head kinematics. No study has evaluated the reproducibility of head kinematics in large animal models. Nine (five males) sexually mature Yucatan swine were exposed to head rotation at a targeted peak angular velocity of 250 rad/s in the coronal plane. The results indicated that the measured peak angular velocity of the skull was 51% of the impulsive load, was experienced over 91% longer duration, and was multi- rather than uni-planar. These findings were replicated in a second experiment with a smaller cohort (N = 4). The reproducibility of skull kinematics data was mostly within acceptable ranges based on published industry standards, although the coefficients of variation (8.9% for peak angular velocity or 12.3% for duration) were higher than the impulsive loading parameters produced by the machine (1.1 vs. 2.5%, respectively). Immunohistochemical markers of diffuse axonal injury and blood–brain barrier breach were not associated with variation in either skull or machine kinematics, suggesting that the observed levels of variance in skull kinematics may not be biologically meaningful with the current sample sizes. The findings highlight the reproducibility of a large animal acceleration model of TBI and the importance of direct measurements of skull kinematics to determine the magnitude of angular velocity, refine injury criteria, and determine critical thresholds

Towards Real-Life Facial Expression Recognition Systems

Facial expressions are a set of symbols of great importance for human-to-human communication. Spontaneous in their nature, diverse and personal, facial expressions demand for real-time, complex, robust and adaptable facial expression recognition (FER) systems to facilitate the human-computer interaction. The last years' research efforts in the recognition of facial expressions are preparing FER systems to step into the real-life. In order to meet the before-mentioned requirements, this article surveys the work in FER since 2008, particularly adopting the discrete states emotion model in a quest for the most valuable FER work/systems. We first present the new spontaneous facial expression databases and then organize the real-time FER solutions grouped by spontaneous and posed facial expression databases. Then automatic FERs are compared and the cross-database validation method is presented. Finally, we outline FER system open issues to meet real-life challenges

Contextualizing citizenship in Tanzania

This chapter describes selected features of the contemporary Tanzania that form the context for learning of citizenship in civil society. The chapter grasps the contextual conditions and circumstances of citizenship in Tanzania by looking at historical evolvement of the notion of development, maendeleo, over the period from colonial eras to the postcolonial single-party system to the contemporary multiparty democracy. The chapter continues with analyses of the moments of donor enthusiasm for civil society and NGOs and the recent debates on the shrinking space of civil society. Essentially, different stages presents different idea of an ideal citizen and also different efforts in order to shape citizens by state and civil society organizations. It further reflects on how the traces of these developments might show in today’s citizenship habits including patterns of participation and citizenship identities, not only vis-á-vis the state but also other groups and forums where rights and responsibilities are negotiated, and thus, active citizenship is constructed.peerReviewe