Resonant electron-lattice cooling in graphene

Controlling energy flows in solids through switchable electron-lattice cooling can grant access to a range of interesting and potentially useful energy transport phenomena. Here we discuss a unique switchable electron-lattice cooling mechanism arising in graphene due to phonon emission mediated by resonant scattering on defects in crystal lattice, which displays interesting analogy to the Purcell effect in optics. This mechanism strongly enhances the electron-phonon cooling rate, since non-equilibrium carriers in the presence of momentum recoil due to disorder can access a larger phonon phase space and emit phonons more effciently. Resonant energy dependence of phonon emission translates into gate-tunable cooling rates, exhibiting giant enhancement of cooling occurring when the carrier energy is aligned with the electron resonance of the defect

Slip of fluid molecules on solid surfaces by surface diffusion

The mechanism of fluid slip on a solid surface has been linked to surface diffusion, by which mobile adsorbed fluid molecules perform hops between adsorption sites. However, slip velocity arising from this surface hopping mechanism has been estimated to be significantly lower than that observed experimentally. In this paper, we propose a re-adsorption mechanism for fluid slip. Slip velocity predictions via this mechanism show the improved agreement with experimental measurements

Image Registration-Based Bolt Loosening Detection of Steel Joints

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Self-loosening of bolts caused by repetitive loads and vibrations is one of the common defects that can weaken the structural integrity of bolted steel joints in civil structures. Many existing approaches for detecting loosening bolts are based on physical sensors and, hence, require extensive sensor deployment, which limit their abilities to cost-effectively detect loosened bolts in a large number of steel joints. Recently, computer vision-based structural health monitoring (SHM) technologies have demonstrated great potential for damage detection due to the benefits of being low cost, easy to deploy, and contactless. In this study, we propose a vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera. Two images of the monitored steel joint are first collected during different inspection periods and then aligned through two image registration processes. If the bolt experiences rotation between inspections, it will introduce differential features in the registration errors, serving as a good indicator for bolt loosening detection. The performance and robustness of this approach have been validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web. The bolt loosening detection results are presented for easy interpretation such that informed decisions can be made about the detected loosened bolts

Demystifying Advertising Campaign Bid Recommendation: A Constraint target CPA Goal Optimization

In cost-per-click (CPC) or cost-per-impression (CPM) advertising campaigns, advertisers always run the risk of spending the budget without getting enough conversions. Moreover, the bidding on advertising inventory has few connections with propensity one that can reach to target cost-per-acquisition (tCPA) goals. To address this problem, this paper presents a bid optimization scenario to achieve the desired tCPA goals for advertisers. In particular, we build the optimization engine to make a decision by solving the rigorously formalized constrained optimization problem, which leverages the bid landscape model learned from rich historical auction data using non-parametric learning. The proposed model can naturally recommend the bid that meets the advertisers' expectations by making inference over advertisers' historical auction behaviors, which essentially deals with the data challenges commonly faced by bid landscape modeling: incomplete logs in auctions, and uncertainty due to the variation and fluctuations in advertising bidding behaviors. The bid optimization model outperforms the baseline methods on real-world campaigns, and has been applied into a wide range of scenarios for performance improvement and revenue liftup

Do not Waste Money on Advertising Spend: Bid Recommendation via Concavity Changes

In computational advertising, a challenging problem is how to recommend the bid for advertisers to achieve the best return on investment (ROI) given budget constraint. This paper presents a bid recommendation scenario that discovers the concavity changes in click prediction curves. The recommended bid is derived based on the turning point from significant increase (i.e. concave downward) to slow increase (convex upward). Parametric learning based method is applied by solving the corresponding constraint optimization problem. Empirical studies on real-world advertising scenarios clearly demonstrate the performance gains for business metrics (including revenue increase, click increase and advertiser ROI increase).Comment: 10 page

Management of an incidental finding of right internal jugular vein agenesis

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Heterologous protein display on the cell surface of lactic acid bacteria mediated by the s-layer protein

<p>Abstract</p> <p>Background</p> <p>Previous studies have revealed that the C-terminal region of the S-layer protein from <it>Lactobacillus </it>is responsible for the cell wall anchoring, which provide an approach for targeting heterologous proteins to the cell wall of lactic acid bacteria (LAB). In this study, we developed a new surface display system in lactic acid bacteria with the C-terminal region of S-layer protein SlpB of <it>Lactobacillus crispatus </it>K2-4-3 isolated from chicken intestine.</p> <p>Results</p> <p>Multiple sequence alignment revealed that the C-terminal region (LcsB) of <it>Lb. crispatus </it>K2-4-3 SlpB had a high similarity with the cell wall binding domains S_Aand CbsA of <it>Lactobacillus acidophilus </it>and <it>Lb. crispatus</it>. To evaluate the potential application as an anchoring protein, the green fluorescent protein (GFP) or beta-galactosidase (Gal) was fused to the N-terminus of the LcsB region, and the fused proteins were successfully produced in <it>Escherichia coli</it>, respectively. After mixing them with the non-genetically modified lactic acid bacteria cells, the fused GFP-LcsB and Gal-LcsB were functionally associated with the cell surface of various lactic acid bacteria tested. In addition, the binding capacity could be improved by SDS pretreatment. Moreover, both of the fused proteins could simultaneously bind to the surface of a single cell. Furthermore, when the fused DNA fragment of <it>gfp:lcsB </it>was inserted into the <it>Lactococcus lactis </it>expression vector pSec:Leiss:Nuc, the GFP could not be secreted into the medium under the control of the <it>nisA </it>promoter. Western blot, in-gel fluorescence assay, immunofluorescence microscopy and SDS sensitivity analysis confirmed that the GFP was successfully expressed onto the cell surface of <it>L. lactis </it>with the aid of the LcsB anchor.</p> <p>Conclusion</p> <p>The LcsB region can be used as a functional scaffold to target the heterologous proteins to the cell surfaces of lactic acid bacteria <it>in vitro </it>and <it>in vivo</it>, and has also the potential for biotechnological application.</p