Design and Testing of Novel Mouthguard with Intermediate Nitinol and Foam Layers

It is the aim of this study to investigate a novel mouthguard design that incorporates the use of a nickel-titanium (Nitinol) layer and thin foam layer in addition to EVA layers. It is thought that the Nitinol layer can distribute the force of an impact and that the thin foam layer may absorb this distributed force better than a solid EVA mouthguard of the same thickness. Rectangular, flat coupons representative of several mouthguard configurations were constructed for testing using an instrumented drop-weight impact tower. The coupon configurations include a control made of laminated EVA, a group of laminated EVA and Nitinol, laminated EVA and foam, and a group of laminated EVA with foam and Nitinol. Several thicknesses of EVA were used in each configuration as well as three different Nitinol insert designs. The construction and subsequent testing of the coupons was performed in conjunction with the UNLV School of Dental Medicine. Two test methods were used to evaluate the coupons using the drop tower machine. The first test involved dropping a mass onto the coupon supported by a flat plate attached to a load cell. The second test involved dropping the mass onto the coupon resting on a simply supported beam attached to a load cell. The metric by which the coupons are evaluated are peak forces transmitted to the load cell, and strain (or deflection) experienced by the simply supported beam in the case of the second test. The energy absorbed by the coupon was calculated using the strain energy in the beam at the moment of peak force and deflection and performing an energy balance on the system. Measurements were normalized by thickness and compared to the control group. While there were some improvements in performance with the novel design, these were only modest, and the group of designs using only Nitinol (no foam) actually performed worse than the control

Leveraging mobile health technology and multidisciplinary methodology to optimize self-management education for advanced cancer pain : Development of stamp

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Bilateral Luxatio Erecta Humeri With Acute Anterior-inferior Re-dislocation

Luxatio erecta is a description for a specific and rare type of shoulder dislocation where the humeral head dislocates directly inferior. This rare form of glenohumeral dislocation accounts for only 0.5% of shoulder dislocations. It is even less common for both shoulders to be bilaterally dislocated inferiorly with the characteristic “hands up” posture. A limited number of these bilateral occurrences are described in the literature to date and most have been from higher energy trauma. We have described a low energy case of bilateral luxatio erecta and the reduction method used and the continued instability following successful reduction under procedural anesthesia

Characterizing the contaminating distance distribution for Bayesian supernova cosmology

Measurements of the equation of state of dark energy from surveys of thousands of Type Ia Supernovae (SNe Ia) will be limited by spectroscopic follow-up and must therefore rely on photometric identification, increasing the chance that the sample is contaminated by Core Collapse Supernovae (CC SNe). Bayesian methods for supernova cosmology can remove contamination bias while maintaining high statistical precision but are sensitive to the choice of parameterization of the contaminating distance distribution. We use simulations to investigate the form of the contaminating distribution and its dependence on the absolute magnitudes, light curve shapes, colors, extinction, and redshifts of core collapse supernovae. We find that the CC luminosity function dominates the distance distribution function, but its shape is increasingly distorted as the redshift increases and more CC SNe fall below the survey magnitude limit. The shapes and colors of the CC light curves generally shift the distance distribution, and their effect on the CC distances is correlated. We compare the simulated distances to the first year results of the SDSS-II SN survey and find that the SDSS distance distributions can be reproduced with simulated CC SNe that are ~1 mag fainter than the standard Richardson et al. (2002) luminosity functions, which do not produce a good fit. To exploit the full power of the Bayesian parameter estimation method, parameterization of the contaminating distribution should be guided by the current knowledge of the CC luminosity functions, coupled with the effects of the survey selection and magnitude-limit, and allow for systematic shifts caused by the parameters of the distance fit.Comment: 17 pages, 5 figures; accepted for publication in the Astrophysical Journa

Frictional resistance of aesthetic orthodontic arch wires compared to traditional arch wires before and after toothbrush abrasion

Our objective was to compare frictional resistance evident in aesthetic archwires to traditional (non-aesthetic) archwires. Methods: Archwires ligated with elasatics to fixed brackets were pulled through these brackets while frictional resistance (in lbf) was measured. Results: There were no confirmed significant differences between the frictional resistance of the aesthetic arch wires compared to the traditional non-coated wires for all wire sizes tested Conclusions: Our data suggests that a sacrifice of clinical performance with these aesthetic archwires as compared to traditional archwires is not likel

A comprehensive evaluation of the activity and selectivity profile of ligands for RGD-binding integrins

Integrins, a diverse class of heterodimeric cell surface receptors, are key regulators of cell structure and behaviour, affecting cell morphology, proliferation, survival and differentiation. Consequently, mutations in specific integrins, or their deregulated expression, are associated with a variety of diseases. In the last decades, many integrin-specific ligands have been developed and used for modulation of integrin function in medical as well as biophysical studies. The IC50-values reported for these ligands strongly vary and are measured using different cell-based and cell-free systems. A systematic comparison of these values is of high importance for selecting the optimal ligands for given applications. In this study, we evaluate a wide range of ligands for their binding affinity towards the RGD-binding integrins avß3, avß5, avß6, avß8, a5ß1, aIIbß3, using homogenous ELISA-like solid phase binding assay.Postprint (published version

On sequential Bayesian inference for continual learning

Sequential Bayesian inference can be used for continual learning to prevent catastrophic forgetting of past tasks and provide an informative prior when learning new tasks. We revisit sequential Bayesian inference and assess whether using the previous task’s posterior as a prior for a new task can prevent catastrophic forgetting in Bayesian neural networks. Our first contribution is to perform sequential Bayesian inference using Hamiltonian Monte Carlo. We propagate the posterior as a prior for new tasks by approximating the posterior via fitting a density estimator on Hamiltonian Monte Carlo samples. We find that this approach fails to prevent catastrophic forgetting, demonstrating the difficulty in performing sequential Bayesian inference in neural networks. From there, we study simple analytical examples of sequential Bayesian inference and CL and highlight the issue of model misspecification, which can lead to sub-optimal continual learning performance despite exact inference. Furthermore, we discuss how task data imbalances can cause forgetting. From these limitations, we argue that we need probabilistic models of the continual learning generative process rather than relying on sequential Bayesian inference over Bayesian neural network weights. Our final contribution is to propose a simple baseline called Prototypical Bayesian Continual Learning, which is competitive with the best performing Bayesian continual learning methods on class incremental continual learning computer vision benchmarks

Specific neural correlates of successful learning and adaptation during social exchanges

Cooperation and betrayal are universal features of social interactions, and knowing who to trust is vital in human society. Previous studies have identified brain regions engaged by decision making during social encounters, but the mechanisms supporting modification of future behaviour by utilizing social experience are not well characterized. Using functional magnetic resonance imaging (fMRI), we show that cooperation and betrayal during social exchanges elicit specific patterns of neural activity associated with future behaviour. Unanticipated cooperation leads to greater behavioural adaptation than unexpected betrayal, and is signalled by specific neural responses in the striatum and midbrain. Neural responses to betrayal and willingness to trust novel partners both decrease as the number of individuals encountered during repeated social encounters increases. We propose that, as social groups increase in size, uncooperative or untrustworthy behaviour becomes progressively less surprising, with cooperation becoming increasingly important as a stimulus for social learning. Effects on reputation of non-trusting decisions may also act to drive pro-social behaviour. Our findings characterize the dynamic neural processes underlying social adaptation, and suggest that the brain is optimized to cooperate with trustworthy partners, rather than avoiding those who might betray us

Cancer pain self-management in the context of a national opioid epidemic : Experiences of patients with advanced cancer using opioids

Acknowledgments: The authors would like the thank the participants, and Dr. Anna Revette for her guidance on the interview guide. Funding Support: National Institutes of Health grant no. R21 NR017745 to Andrea C. EnzingerPeer reviewedPostprin