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Additive manufacturing technologies have become increasingly prevalent in recent years and, with their abundance, have opened many doors in the field of manufacturing and design. The field of medicine has always been in high demand for new manufacturing techniques to create medical prostheses, devices, and trainers. With this increased need, 3D printing has become the obvious solution, and with it, a major problem has arisen. The lack of material property data on 3D printing filament post extrusion leaves designers and engineers having to perform extraneous tests to create accurate models. This paper summarizes an analyses of a common 3D printing filament known as Thermoplastic Polyurethane (TPU). The analysis included tensile testing in accordance with ASTM D638-14 and preliminary FEA based on the material properties found. It was found that TPU is a material that behaves in a similar manner to an elastomer with a low ultimate stress (50% infill yields 23.92 MPa +1.38 −1.12) and relatively low moduli of elasticity (50% infill sample 23.13 MPa +0.91 −0.87). TPU’s material characteristics change in respect to its infill percentage. A preliminary FEA analysis was also performed with results that agree with the material testing. Overall, the results from the physical testing and the FEA analysis were in agreement and allows for the creation of a foundation to extend the FEA validation with complex geometric models modeled after organic biomedical components.

The authors sought to identify brain regions whose frequency-specific, orthogonalized resting-state EEG power envelope connectivity differs between combat veterans with posttraumatic stress disorder (PTSD) and healthy combat-exposed veterans, and to determine the behavioral correlates of connectomic differences.The authors first conducted a connectivity method validation study in healthy control subjects (N=36). They then conducted a two-site case-control study of veterans with and without PTSD who were deployed to Iraq and/or Afghanistan. Healthy individuals (N=95) and those meeting full or subthreshold criteria for PTSD (N=106) underwent 64-channel resting EEG (eyes open and closed), which was then source-localized and orthogonalized to mitigate effects of volume conduction. Correlation coefficients between band-limited source-space power envelopes of different regions of interest were then calculated and corrected for multiple comparisons. Post hoc correlations of connectomic abnormalities with clinical features and performance on cognitive tasks were conducted to investigate the relevance of the dysconnectivity findings.Seventy-four brain region connections were significantly reduced in PTSD (all in the eyes-open condition and predominantly using the theta carrier frequency). Underconnectivity of the orbital and anterior middle frontal gyri were most prominent. Performance differences in the digit span task mapped onto connectivity between 25 of the 74 brain region pairs, including within-network connections in the dorsal attention, frontoparietal control, and ventral attention networks.Robust PTSD-related abnormalities were evident in theta-band source-space orthogonalized power envelope connectivity, which furthermore related to cognitive deficits in these patients. These findings establish a clinically relevant connectomic profile of PTSD using a tool that facilitates the lower-cost clinical translation of network connectivity research.

When individuals learn from observing the behavior of others, they deploy at least two distinct strategies. Choice imitation involves repeating other agents’ previous actions, while emulation proceeds from inferring their goals and intentions. Despite the prevalence of observational learning in humans and other social animals, a fundamental question remains unaddressed: how does the brain decide which strategy to use in a given situation? In two fMRI studies (the second a pre-registered replication of the first), we identify a neuro-computational mechanism underlying arbitration between choice imitation and goal emulation. Computational modelling, combined with a behavioral task that dissociated the two strategies, revealed that control over behavior was adaptively and dynamically weighted toward the most reliable strategy. Emulation reliability, the model’s arbitration signal, was represented in the ventrolateral prefrontal cortex, temporoparietal junction and rostral cingulate cortex. Our replicated findings illuminate the computations by which the brain decides to imitate or emulate others.

Humans have a remarkable ability to infer and represent others’ mental states such as their beliefs, goals, desires, intentions, and feelings. In this chapter, we review some of the innovations that have developed in economics, computer science, and cognitive neuroscience in modeling the computations underlying several mentalizing operations. Broadly, this involves building models of how agents infer the mental states of other agents within constrained environments. These models include modules for representing the goals and desires of an agent (e.g., maximize reward, or minimize embarrassment), inferring the mental states of other agents (e.g., beliefs, goals, desires, intentions, and feelings), and integrating these goals and mentalizing computations to produce optimal behavioral policies to navigate the environment. The mathematical operationalization of these constructs provides a general framework that can be validated by behavior and neural recording techniques and extended in the future by contributions from multiple scientific disciplines.

Humans have a remarkable ability to infer and represent others’ mental states such as their beliefs, goals, desires, intentions, and feelings. In this chapter, we review some of the innovations that have developed in economics, computer science, and cognitive neuroscience in modeling the computations underlying several mentalizing operations. Broadly, this involves building models of how agents infer the mental states of other agents within constrained environments. These models include modules for: representing the goals and desires of an agent (e.g., maximize reward, or minimize embarrassment), inferring the mental states of other agents (e.g., beliefs, goals, desires, intentions, and feelings), and integrating these goals and mentalizing computations to produce optimal behavioral policies to navigate the environment. The mathematical operationalization of these constructs provides a general framework that can be validated by behavior and neural recording techniques and extended in the future by contributions from multiple scientific disciplines.

A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.

Increasingly, geospatial web applications such as www.fixmystreet.com or www.seeclickfix.com are being integrated within citizen participation processes in spatial planning and the provision of communal services. Recently, several of these platforms have been launched in Latin America and other countries of the Global South. This development raises the questions of whether citizens with low ICT-skills can fully access and use these tools, and hence whether they are empowered to participate in related community management processes. The GeoCitizen framework (www.geocitizen.org) has been designed specifically to address citizens who tend to be excluded from established planning processes, providing them with accessible and easy-to-use online tools to make their voice heard through the public space of the internet. This paper describes the set-up and results of a Human Computer Interaction (HCI) Evaluation carried out for the GeoCitizen-reporting application amongst members of marginalized communities in Cali, Colombia. It investigates whether spatially illiterate users with low ICT-skills can access and use this application to its full extent. It analyses the most common usability issues that were identified by the test user group and gives indications as to how geospatial web applications should be designed in order to meet the challenges that come along with its use.