Optical Delay Interferometers and their Application for Self-coherent Detection

Self-coherent receivers are promising candidates for reception of 100 Gbit/s data rates in optical networks. Self-coherent receivers consist of multiple optical delay interferometers (DI) with high-speed photodiodes attached to the outputs. By DSP of the photo currents it becomes possible to receive coherently modulated optical signals. Especially promising for 100 Gbit/s networks is the PolMUX DQPSK format, the self-coherent reception of which is described in detail

Plastic Revolution: Reuse of Marine Plastic Garbage

The Great Pacific Garbage Patch, also described as the Pacific trash vortex, has been getting more and more attention recently. It is a gyre of marine debris particles in the north central Pacific Ocean, with an estimated size range from 700,000 square kilometers (about the size of Russia). In 1992, 28,000 rubber ducks were plunged into the ocean after a shipping crate was lost at sea on its way to the US from Hong Kong. Many years later, the rubber ducks have become a vital tool in our understanding of ocean currents, as well as teaching us about ocean pollution. This proposal uses abandoned offshore oil rigs as a starting point. By reducing and adding structure and equipment to the oil rigs, they become trash traps and giant 3d building printing facilities. The new structures will float on the water and collect plastic garbage, which will be sorted into two kinds: re-usable, or not re-usable. The re-usable group will be reproduced as 3d-printing materials, which will be used to print a new structure around the original oil rigs. The new structure is also a floating laboratory for collecting ocean and climate data. The floating laboratory will travel all over the world by following the ocean\u27s currents. Some of the new structures will travel randomly; others will be operated by people-they could attach to a harbor and stay for a period. Scientists can access the structures to obtain the information they have collected. The structure could serve as temporary exhibition space for communities around the world. The self-growth floating structure is thus not only a laboratory, but also a form of media that tells people: here is the problem-we have lots of garbage

Layer-by-layer nanoassembly combined with microfabrication techniques for microelectronics and microelectromechanical systems

The objective of this work is to investigate the combination of layer-by-layer self-assembly with microfabrication technology and its applications in microelectronics and MEMS. One can assemble, on a standard silicon wafer, needed multilayers containing different nanoparticles and polymers and then apply various micromanufacturing techniques to form microdevices with nanostructured elements. Alternate layer-by-layer self-assembly of linear polyions and colloidal silica at elevated temperatures have been firstly studied by QCM and SEM. LbL self-assembly and photolithography were combined to fabricate an indium resistor. The RTA method was employed in the fabrication. Hot-embossing technique as a reasonably fast and moderately expensive technique was used to replicate mold structures into thermoplastics. Microstamps with nanofeatures formed by this method can be applied on LbL nanoassembled multilayers. Finally, multiple ultrathin microcantilevers were developed by integrating LbL self-assembly, photolithography, wet etching, and ICP techniques. The purpose is to develop chemical/biosensor arrays for parallel, massive data gathering

Horizontal inverse mean curvature flow in the Heisenberg group

Huisken and Ilmanen in [25] created the theory of weak solutions for inverse mean curvature flows (IMCF) of hypersurfaces on Riemannian manifolds, and proved successfully a Riemannian version of the Penrose inequality. In this paper we investigate and construct the sub-Riemannian version of the theory of weak solutions for inverse mean curvature flows of hypersurfaces in sub-Riemannian Heisenberg groups. We extend the weak solution theory in [25] to the first Heisenberg group and prove the existence, uniqueness and basic geometric properties of horizontal inverse mean curvature flows (HIMCF). By a Heisenberg dilation on HIMCF, we find a horizontal perimeter preserving flow (1.7) in the first Heisenberg group, and prove the existence and uniqueness of weak solutions to (1.7). Using this existential result, the present paper gives a positive answer to an open problem: Heintze-Karcher type inequality in the Heisenberg group. At the same time, this article also proves a Minkowski type formula in the first Heisenberg group

Michael-Simon type inequalities in hyperbolic space

In the present paper, we first establish and verify a new sharp hyperbolic version of the Michael-Simon inequality for mean curvatures in hyperbolic space $\mathbb{H}^{n+1}$ based on the locally constrained inverse curvature flow introduced by Brendle, Guan and Li, provided that $M$ is $h$-convex and $f$ is a positive smooth function, where $\lambda^{'}(r)=\rm{cosh}$$r$. In particular, when $f$ is of constant, (0.1) coincides with the Minkowski type inequality stated by Brendle, Hung, and Wang. Further, we also establish and confirm a new sharp Michael-Simon inequality for the $k$-th mean curvatures in $\mathbb{H}^{n+1}$ by virtue of the Brendle-Guan-Li's flow, provided that $M$ is $h$-convex and $\Omega$ is the domain enclosed by $M$. In particular, when $f$ is of constant and $k$ is odd, (0.2) is exactly the weighted Alexandrov-Fenchel inequalities proven by Hu, Li, and Wei.Comment: 13 page

Credit Risk Measurement and Application based on BP Neural Networks

The emergence of P2P(Peer-to-peer) lending has opened up a popular way for micro-finance, and the financial lending industry in many countries is growing rapidly. While it facilitates lending to individuals and small and medium-sized enterprises, improving the risk identification capability of the P2P platform is vitally necessary for the sustainable development of the platform. Especially the potential credit risk caused by information asymmetry, this may be fatal to this industry. In order to alleviate the adverse effects of this problem, this paper takes Lending Club’s real loan data as the empirical research object. The random forest is used to screen the importance of features, and backpropagation neural network approach is used to establish a credit risk classification model. Before loaning, the loan applicants can be divided into default and non-default. The results show that the credit risk measurement model is effective in predicting whether the lender will default

Degradation of Contaminated Air Streams Containing Toluene, Ethylbenzene and O-Xylene by Biofiltration

Civil Engineerin

An atomic decomposition of variable Besov and Triebel-Lizorkin spaces

An atomic decomposition of variable Besov and Triebel-Lizorkin spaces is given