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Search Results: 1 - 10 of 43958 matches for " Chensheng Wu "
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Determining the Phase and Amplitude Distortion of a Wavefront using a Plenoptic Sensor
Chensheng Wu,Jonathan Ko,Christopher C. Davis
Physics , 2015,
Abstract: We have designed a plenoptic sensor to retrieve phase and amplitude changes resulting from a laser beam's propagation through atmospheric turbulence. Compared with the commonly restricted domain of (-pi, pi) in phase reconstruction by interferometers, the reconstructed phase obtained by the plenoptic sensors can be continuous up to a multiple of 2pi. When compared with conventional Shack-Hartmann sensors, ambiguities caused by interference or low intensity, such as branch points and branch cuts, are less likely to happen and can be adaptively avoided by our reconstruction algorithm. In the design of our plenoptic sensor, we modified the fundamental structure of a light field camera into a mini Keplerian telescope array by accurately cascading the back focal plane of its object lens with a microlens array's front focal plane and matching the numerical aperture of both components. Unlike light field cameras designed for incoherent imaging purposes, our plenoptic sensor operates on the complex amplitude of the incident beam and distributes it into a matrix of images that are simpler and less subject to interference than a global image of the beam. Then, with the proposed reconstruction algorithms, the plenoptic sensor is able to reconstruct the wavefront and a phase screen at an appropriate depth in the field that causes the equivalent distortion on the beam. The reconstructed results can be used to guide adaptive optics systems in directing beam propagation through atmospheric turbulence. In this paper we will show the theoretical analysis and experimental results obtained with the plenoptic sensor and its reconstruction algorithms.
Using Graph Theory and a Plenoptic Sensor to Recognize Phase Distortions of a Laser Beam
Chensheng Wu,Jonathan Ko,Christopher C. Davis
Physics , 2015,
Abstract: Atmospheric turbulence causes fluctuations in the local refractive index of air that accumulatively disturb a wave's phase and amplitude distribution as it propagates. This impairs the effective range of laser weapons as well as the performance of free space optical (FSO) communication systems. Adaptive optics (AO) can be applied to effectively correct wavefront distortions in weak turbulence situations. However, in strong or deep turbulence, where scintillation and beam breakup are common phenomena, traditional wavefront sensing techniques such as the use of Shack-Hartmann sensors lead to incorrect results. Consequently, the performance of AO systems will be greatly compromised. We propose a new approach that can determine the major phase distortions in a beam instantaneously and guide an AO device to compensate for the phase distortion in a few iterations. In our approach, we use a plenoptic wavefront sensor to image the distorted beam into its 4D phase space. A fast reconstruction algorithm based on graph theory is applied to recognize the phase distortion of a laser beam and command the AO device to perform phase compensation. As a result, we show in our experiments that an arbitrary phase distortion with peak to peak value up to 22{\pi} can be corrected within a few iteration steps. Scintillation and branch point problems are smartly avoided by the plenoptic sensor and its fast reconstruction algorithm. In this article, we will demonstrate the function of the plenoptic sensor, the fast reconstruction algorithm as well as the beam correction improvements when our approach is applied to an AO system.
Using an incoherent target-return to adaptively focus through atmospheric turbulence
William Nelson,John P. Palastro,Chensheng Wu,Christopher C. Davis
Physics , 2015,
Abstract: A laser beam propagating to a remote target through atmospheric turbulence acquires intensity fluctuations. If the target is cooperative and provides a coherent return beam, the phase measured near the beam transmitter and adaptive optics can, in principle, correct these fluctuations. Generally, however, the target is uncooperative. In this case, we show that an incoherent return from the target can be used instead. Using the principle of reciprocity, we derive a novel relation between the field at the target and the reflected field at a detector. We simulate an adaptive optics system that utilizes this relation to focus a beam through atmospheric turbulence onto the incoherent surface.
Do scientists trace hot topics?
Tian Wei,Menghui Li,Chensheng Wu,XiaoYong Yan,Ying Fan,Zengru Di,Jinshan Wu
Computer Science , 2013, DOI: 10.1038/srep02207
Abstract: Do scientists follow hot topics in their scientific investigations? In this paper, by performing analysis to papers published in the American Physical Society (APS) Physical Review journals, it is found that papers are more likely to be attracted by hot fields, where the hotness of a field is measured by the number of papers belonging to the field. This indicates that scientists generally do follow hot topics. However, there are qualitative differences among scientists from various countries, among research works regarding different number of authors, different number of affiliations and different number of references. These observations could be valuable for policy makers when deciding research funding and also for individual researchers when searching for scientific projects.
Interrelations among scientific fields and their relative influence revealed by input-output analysis
Zhesi Shen,Liying Yang,Jiansuo Pei,Menghui Li,Chensheng Wu,Jianzhang Bao,Tian Wei,Zengru Di,Ronald Rousseau,Jinshan Wu
Physics , 2015,
Abstract: In this paper, we try to answer two questions about any given scientific discipline: First, how important is each subfield and second, how does a specific subfield influence other subfields? We modify the well-known open-system Leontief Input-Output Analysis in economics into a closed-system analysis focusing on eigenvalues and eigenvectors and the effects of removing one subfield. We apply this method to the subfields of physics. This analysis has yielded some promising results for identifying important subfields (for example the field of statistical physics has large influence while it is not among the largest subfields) and describing their influences on each other (for example the subfield of mechanical control of atoms is not among the largest subfields cited by quantum mechanics, but our analysis suggests that these fields are strongly connected). This method is potentially applicable to more general systems that have input-output relations among their elements.
From sparse to dense and from assortative to disassortative in online social networks
Menghui Li,Shuguang Guan,Chensheng Wu,Xiaofeng Gong,Kun Li,Jinshan Wu,Zengru Di,Choy-Heng Lai
Computer Science , 2013, DOI: 10.1038/srep04861
Abstract: Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.
Reconstructing Organophosphorus Pesticide Doses Using the Reversed Dosimetry Approach in a Simple Physiologically-Based Pharmacokinetic Model
Chensheng Lu,Leo Andres
Journal of Toxicology , 2012, DOI: 10.1155/2012/131854
Abstract: We illustrated the development of a simple pharmacokinetic (SPK) model aiming to estimate the absorbed chlorpyrifos doses using urinary biomarker data, 3,5,6-trichlorpyridinol as the model input. The effectiveness of the SPK model in the pesticide risk assessment was evaluated by comparing dose estimates using different urinary composite data. The dose estimates resulting from the first morning voids appeared to be lower than but not significantly different to those using before bedtime, lunch or dinner voids. We found similar trend for dose estimates using three different urinary composite data. However, the dose estimates using the SPK model for individual children were significantly higher than those from the conventional physiologically based pharmacokinetic (PBPK) modeling using aggregate environmental measurements of chlorpyrifos as the model inputs. The use of urinary data in the SPK model intuitively provided a plausible alternative to the conventional PBPK model in reconstructing the absorbed chlorpyrifos dose. 1. Introduction A physiologically based pharmacokinetic (PBPK) model would allow for simulating the dynamics of pesticide absorption, distribution, metabolism, and elimination (ADME) from different routes of exposures and, in theory, could be used as a tool for evaluating biomarker measurements (e.g. blood or urine levels) associated with the exposures [1–4]. The mechanistic representation of biological processes embedded in the PBPK model allows systematic route, dose, and species extrapolation, and for these reasons, PBPK models have been applied in pesticide risk assessments that are relevant for the interpretation of biomarker data [5–12]. Although the interpretation of PBPK model outputs could provide a link to the regulatory metrics in the form of reference dose, its application remains problematic due to the fundamental limitations resulting from the potential measurement errors associated with the aggregate exposure measurements [11, 13]. Although those aggregate exposure data are needed in order to simulate the dynamics of ADME for a specific pesticide, the uncertainties, mainly the temporal and spatial variations, associated with the measurements may inadvertently be carried over to the model outcomes. Those uncertainties, however, are merely explicit statements of underlying assumption applied in the analysis of urinary biomarker data. A simple pharmacokinetic (SPK) model incorporating reverse dosimetry and PBPK modeling approach, on the other hand, only requires urinary biomarker data as inputs and the a-priori knowledge of
Adaptive Linear Filtering Design with Minimum Symbol Error Probability Criterion
Sheng ChenSheng Chen,
Sheng
,Chen

国际自动化与计算杂志 , 2006,
Abstract: Adaptive digital filtering has traditionally been developed based on the minimum mean square error (MMSE) criterion and has found ever-increasing applications in communications. This paper presents an alternative adaptive filtering design based on the minimum symbol error rate (MSER) criterion for communication applications. It is shown that the MSER filtering is smarter, as it exploits the non-Gaussian distribution of filter output effectively. Consequently, it provides significant performance gain in terms of smaller symbol error over the MMSE approach. Adopting Parzen window or kernel density estimation for a probability density function, a block-data gradient adaptive MSER algorithm is derived. A stochastic gradient adaptive MSER algorithm, referred to as the least symbol error rate, is further developed for sample-by-sample adaptive implementation of the MSER filtering. Two applications, involving single-user channel equalization and beamforming assisted receiver, are included to demonstrate the effectiveness and generality of the proposed adaptive MSER filtering approach.
FOLDNA, a Web Server for Self-Assembled DNA Nanostructure Autoscaffolds and Autostaples
Chensheng Zhou,Heng Luo,Xiaolu Feng,Xingwang Li,Jie Zhu,Lin He,Can Li
Journal of Nanotechnology , 2012, DOI: 10.1155/2012/453953
Abstract: DNA self-assembly is a nanotechnology that folds DNA into desired shapes. Self-assembled DNA nanostructures, also known as origami, are increasingly valuable in nanomaterial and biosensing applications. Two ways to use DNA nanostructures in medicine are to form nanoarrays, and to work as vehicles in drug delivery. The DNA nanostructures perform well as a biomaterial in these areas because they have spatially addressable and size controllable properties. However, manually designing complementary DNA sequences for self-assembly is a technically demanding and time consuming task, which makes it advantageous for computers to do this job instead. We have developed a web server, FOLDNA, which can automatically design 2D self-assembled DNA nanostructures according to custom pictures and scaffold sequences provided by the users. It is the first web server to provide an entirely automatic design of self-assembled DNA nanostructure, and it takes merely a second to generate comprehensive information for molecular experiments including: scaffold DNA pathways, staple DNA directions, and staple DNA sequences. This program could save as much as several hours in the designing step for each DNA nanostructure. We randomly selected some shapes and corresponding outputs from our server and validated its performance in molecular experiments. 1. Introduction When Watson and Crick discovered the nucleic acid pairing rules in 1953, the theoretical foundation of self-assembled DNA was established. In 1982, Seeman laid the foundation of “structural DNA Nanotechnology” by folding DNA into lattices [1]. Later in 2006, Rothemund initiated spatially restricted 2D self-assembled DNA structure by using a bottom-up method, which is also known as DNA origami [2, 3]. In the same year, asymmetric self-assembled DNA nanostructure was folded by Qian et al. [4]. Since then, applications of DNA nanostructures in research and diagnosis have been continuously developed, such as methods to examine single nucleotide polymorphism on flat DNA origami, to attach antibodies onto tiles and to perform RNA hybridization assays [5–8]. Self-assembled DNA is built by a long single strand scaffold DNA and a lot of short single strand DNA known as staples. The number of staples is decided by the length of the scaffold DNA, which is typically 7 kilobase-long. Using bottom-up fabrication methods, the scaffold DNA is folded to form the shape of the nanostructure, while the staple DNA fix the scaffold DNA, thus forming the two-dimensional DNA nanostructure. With the development of DNA nanotechnology, software
VEZT, a Novel Putative Tumor Suppressor, Suppresses the Growth and Tumorigenicity of Gastric Cancer
Ruizhen Miao, Xiaobo Guo, Qiaoming Zhi, Yulong Shi, Leping Li, Xuehui Mao, Li Zhang, Chensheng Li
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0074409
Abstract: Vezatin (VEZT), an adherens junctions transmembrane protein, was identified as a putative tumor suppressor in our previous study. However, the role of VEZT in tumorigenesis remains elusive. We aimed to clarify its epigenetic regulation and biological functions in gastric cancer. In this study, we show that the expression level of VEZT is involved in lymphatic metastasis, depth of cancer invasion and TNM stage in 104 gastric cancer patients. Bisulfate sequencing polymerase chain reaction (BSP) methods showed that VEZT was hypermethylated in tissues and corresponding blood of gastric cancer patients compared with healthy controls. Helicobacter pylori (H. pylori) infection induces the methylation and silencing of VEZT in GES-1 cells. Restoring VEZT expression in MKN-45 and NCI-N87 gastric cancer cells inhibited growth, invasion and tumorigenesis in vitro and in vivo. Global microarray analysis was applied to analyze the molecular basis of the biological functions of VEZT after VEZT transfection combined with real-time PCR and chromatin immunoprecipitation assay. G protein-coupled receptor 56(GPR56), cell growth, cell division cycle 42(CDC42), migration/invasion and transcription factor 19(TCF19), cell cycle progression, were identified as direct VEZT target genes. TCF19, a novel target of VEZT, was functionally validated. Overexpression of TCF19 in MKN-45 cells increased cell cycle progress and growth ability. This study provides novel insight into the regulation of the VEZT gene, which could represent a potential target for therapeutic anti-cancer strategies.
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