Piezoresistor-Embedded Multifunctional Magnetic Microactuators for Implantable Self-Clearing Catheter

Indwelling catheters are used widely in medicine to treat various chronic medical conditions. However, chronic implantation of catheters often leads to a premature failure due to biofilm accumulation. Previously we reported on the development of a self-clearing catheter by integrating polymer-based microscale magnetic actuators. The microactuator provides an active anti-biofouling mechanism to disrupt and remove adsorbed biofilm on demand using an externally applied stimulus. During an in vivo evaluation of self-clearing catheter, we realized that it is important to periodically monitor the performance of implanted microactuators. Here we integrate gold-based piezoresistive strain-gauge on our magnetic microactuators to directly monitor the device deflection with good sensitivity (0.035%/Deg) and linear range (±30°). With the integrated strain-gauge, we demonstrate the multi-functional capabilities of our magnetic microactuators that enable device alignment, flow-rate measurement, and obstruction detection and removal towards the development of chronically implantable self-clearing smart catheter

Sharp Interface Limits of the Cahn-Hilliard Equation with Degenerate Mobility

In this work, the sharp interface limit of the degenerate Cahn-Hilliard equation (in two space dimensions) with a polynomial double well free energy and a quadratic mobility is derived via a matched asymptotic analysis involving exponentially large and small terms and multiple inner layers. In contrast to some results found in the literature, our analysis reveals that the interface motion is driven by a combination of surface diffusion flux proportional to the surface Laplacian of the interface curvature and an additional contribution from nonlinear, porous-medium type bulk diffusion, For higher degenerate mobilities, bulk diffusion is subdominant. The sharp interface models are corroborated by comparing relaxation rates of perturbations to a radially symmetric stationary state with those obtained by the phase field model.Comment: 27 pages, 2 figure

Slum health: diseases of neglected populations.

BackgroundUrban slums, like refugee communities, comprise a social cluster that engenders a distinct set of health problems. With 1 billion people currently estimated to live in such communities, this neglected population has become a major reservoir for a wide spectrum of health conditions that the formal health sector must deal with.DiscussionUnlike what occurs with refugee populations, the formal health sector becomes aware of the health problems of slum populations relatively late in the course of their illnesses. As such, the formal health sector inevitably deals with the severe and end-stage complications of these diseases at a substantially greater cost than what it costs to manage non-slum community populations. Because of the informal nature of slum settlements, and cultural, social, and behavioral factors unique to the slum populations, little is known about the spectrum, burden, and determinants of illnesses in these communities that give rise to these complications, especially of those diseases that are chronic but preventable. In this article, we discuss observations made in one slum community of 58,000 people in Salvador, the third largest city in Brazil, to highlight the existence of a spectrum and burden of chronic illnesses not likely to be detected by the formal sector health services until they result in complications or death. Lack of health-related data from slums could lead to inappropriate and unrealistic allocation of health care resources by the public and private providers. Similar misassumptions and misallocations are likely to exist in other nations with large urban slum populations.SummaryContinued neglect of ever-expanding urban slum populations in the world could inevitably lead to greater expenditure and diversion of health care resources to the management of end-stage complications of diseases that are preventable. A new approach to health assessment and characterization of social-cluster determinants of health in urban slums is urgently needed

Applying Graph Theory to Examine the Dynamics of Student Discussions in Small-Group Learning.

Group work in science, technology, engineering, and mathematics courses is an effective means of improving student outcomes, and many different factors can influence the dynamics of student discussions and, ultimately, the success of collaboration. The substance and dynamics of group discussions are commonly examined using qualitative methods such as discourse analysis. To complement existing work in the literature, we developed a quantitative methodology that uses graph theory to map the progression of talk-turns of discussions within a group. We observed groups of students working with peer facilitators to solve problems in biological sciences, with three iterations of data collection and two major refinements of graph theory calculations. Results include general behaviors based on the turns in which different individuals talk and graph theory parameters to quantify group characteristics. To demonstrate the potential utility of the methodology, we present case studies with distinct patterns: a centralized group in which the peer facilitator behaves like an authority figure, a decentralized group in which most students talk their fair share of turns, and a larger group with subgroups that have implications for equity, diversity, and inclusion. Together, these results demonstrate that our adaptation of graph theory is a viable quantitative methodology to examine group discussions