Simulating Space Capsule Water Landing with Explicit Finite Element Method

A study of using an explicit nonlinear dynamic finite element code for simulating the water landing of a space capsule was performed. The finite element model contains Lagrangian shell elements for the space capsule and Eulerian solid elements for the water and air. An Arbitrary Lagrangian Eulerian (ALE) solver and a penalty coupling method were used for predicting the fluid and structure interaction forces. The space capsule was first assumed to be rigid, so the numerical results could be correlated with closed form solutions. The water and air meshes were continuously refined until the solution was converged. The converged maximum deceleration predicted is bounded by the classical von Karman and Wagner solutions and is considered to be an adequate solution. The refined water and air meshes were then used in the models for simulating the water landing of a capsule model that has a flexible bottom. For small pitch angle cases, the maximum deceleration from the flexible capsule model was found to be significantly greater than the maximum deceleration obtained from the corresponding rigid model. For large pitch angle cases, the difference between the maximum deceleration of the flexible model and that of its corresponding rigid model is smaller. Test data of Apollo space capsules with a flexible heat shield qualitatively support the findings presented in this paper

Bio-material polylactic acid/poly(butylene adipate-co-terephthalate) blend developed for extrusion- based additive manufacturing

Bio-material polylactic acid and poly(butylene adipate-co-terephthalate) were blended to achieve increased ductility of the blend. Cloisite was added to improve the stiffness of the blend. The blends were made into filament suitable for extrusion-based additive manufacturing. Melt flow index of the filament and mechanical properties of the printed bars were tested. Preliminary results showed that the melt flow index increases significantly with cloisite and the modulus of polylactic acid/poly(butylene adipate-co-terephthalate) improved slightly. The notched impact strength of the blend increased with increasing content of cloisite, and it increased significantly after annealing, especially for blends without cloisite

Epi-illumination SPIM for volumetric imaging with high spatial-temporal resolution.

We designed an epi-illumination SPIM system that uses a single objective and has a sample interface identical to that of an inverted fluorescence microscope with no additional reflection elements. It achieves subcellular resolution and single-molecule sensitivity, and is compatible with common biological sample holders, including multi-well plates. We demonstrated multicolor fast volumetric imaging, single-molecule localization microscopy, parallel imaging of 16 cell lines and parallel recording of cellular responses to perturbations

Polymorphisms in the SULF1 gene are associated with early age of onset and survival of ovarian cancer

<p>Abstract</p> <p>Background</p> <p>SULF1 (sulfatase 1) selectively removes the 6-O-sulphate group from heparan sulfate, changing the binding sites for extracellular growth factors. <it>SULF1 </it>expression has been reported to be decreased in various cancers, including ovarian cancer. We hypothesized that single nucleotide polymorphisms (SNPs) of <it>SULF1 </it>would impact clinicopathologic characteristics.</p> <p>Methods</p> <p>We genotyped five common (minor allele frequency>0.05) regulatory SNPs with predicted functionalities (rs2623047 G>A, rs13264163 A>G, rs6990375 G>A, rs3802278 G>A, and rs3087714 C>T) in 168 patients with primary epithelial ovarian cancer, using the polymerase chain reaction-restriction fragment length polymorphism method.</p> <p>Results</p> <p>We found that rs2623047 G>A was significantly associated with an early age of onset of ovarian cancer in the G allele dose-response manner (<it>P </it>= 0.027; <it>P_trend</it>= 0.007) and that rs2623047 GG/GA genotypes were associated with longer progression-free survival; rs6990375 G>A was also associated with the early age of onset in the A allele dose-response manner (<it>P </it>= 0.013; <it>P_trend</it>= 0.009). The significant differences in age of disease onset persisted among carriers of haplotypes of rs2623047 and rs6990375 (<it>P </it>= 0.014; <it>P_trend</it>= 0.004). In luciferase reporter gene assays, rs2623047 G allele showed a slightly higher promoter activity than the A allele in the SKOV3 tumorigenic cell line.</p> <p>Conclusions</p> <p>These findings suggest that genetic variations in <it>SULF1 </it>may play a role in ovarian cancer onset and prognosis. Further studies with large sample sizes and of the mechanistic relevance of <it>SULF1 </it>SNPs are warranted.</p

A Socio-Ecological Approach to Addressing Digital Redlining in the United States: A Call to Action for Health Equity

Physical distancing requirements due to the coronavirus (COVID-19) pandemic has increased the need for broadband internet access. The World Health Organization defines social determinants of health as non-medical factors that impact health outcomes by affecting the conditions in which people are born, grow, work, live, and age. By this definition broadband internet access is a social determinant of health. Digital redlining—the systematic process by which specific groups are deprived of equal access to digital tools such as the internet—creates inequities in access to educational and employment opportunities, as well as healthcare and health information. Although it is known that internet service providers systematically exclude low-income communities from broadband service, little has been done to stop this discriminatory practice. In this paper, we seek to amplify the call to action against the practice of digital redlining in the United States, describe how it contributes to health disparities broadly and within the context of the COVID-19 pandemic, and use a socio-ecological framework to propose short- and long-term actions to address this inequity

Small angle neutron scattering from single-wall carbon nanotube suspensions: evidence for isolated rigid rods and rod networks

We report small angle neutron scattering (SANS) from dilute suspensions of purified individual single wall carbon nanotubes (SWNTs) in D2O with added sodium dodecylbenzene sulfonate (NaDDBS) ionic surfactant. The scattered intensity scales as Q-1 for scattered wave vector, Q, in the range 0.005 \u3c Q \u3c 0.02 Å-1. The Q-1 behavior is characteristic of isolated rigid rods. A crossover of the scattered intensity power law dependence from Q-1 to Q-2 is observed at ~0.004 Å-1, suggesting the SWNTs form a loose network at 0.1 wt% with a mesh size of ~160 nm. SANS profiles from several other dispersions of SWNTs do not exhibit isolated rigid rod behavior; evidently the SWNTs in these systems are not isolated and form aggregates

Scalar conservation laws with nonconstant coefficients with application to particle size segregation in granular flow

Granular materials will segregate by particle size when subjected to shear, as occurs, for example, in avalanches. The evolution of a bidisperse mixture of particles can be modeled by a nonlinear first order partial differential equation, provided the shear (or velocity) is a known function of position. While avalanche-driven shear is approximately uniform in depth, boundary-driven shear typically creates a shear band with a nonlinear velocity profile. In this paper, we measure a velocity profile from experimental data and solve initial value problems that mimic the segregation observed in the experiment, thereby verifying the value of the continuum model. To simplify the analysis, we consider only one-dimensional configurations, in which a layer of small particles is placed above a layer of large particles within an annular shear cell and is sheared for arbitrarily long times. We fit the measured velocity profile to both an exponential function of depth and a piecewise linear function which separates the shear band from the rest of the material. Each solution of the initial value problem is non-standard, involving curved characteristics in the exponential case, and a material interface with a jump in characteristic speed in the piecewise linear case

Deep learning in medical imaging and radiation therapy

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146980/1/mp13264_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146980/2/mp13264.pd