Range Queries on Uncertain Data

Given a set $P$ of $n$ uncertain points on the real line, each represented by its one-dimensional probability density function, we consider the problem of building data structures on $P$ to answer range queries of the following three types for any query interval $I$: (1) top-$1$ query: find the point in $P$ that lies in $I$ with the highest probability, (2) top-$k$ query: given any integer $k\leq n$ as part of the query, return the $k$ points in $P$ that lie in $I$ with the highest probabilities, and (3) threshold query: given any threshold $\tau$ as part of the query, return all points of $P$ that lie in $I$ with probabilities at least $\tau$. We present data structures for these range queries with linear or nearly linear space and efficient query time.Comment: 26 pages. A preliminary version of this paper appeared in ISAAC 2014. In this full version, we also present solutions to the most general case of the problem (i.e., the histogram bounded case), which were left as open problems in the preliminary versio

Interaction between Gut Microbiota and Toll-like Receptor: from Immunity to Metabolism

The human gut contains trillions of commensal bacteria, and similar to pathogenic bacteria, the gut microbes and their products can be recognized by toll-like receptors (TLRs). It is well acknowledged that the interaction between gut microbiota and the local TLRs help to maintain the homeostasis of intestinal immunity. High-fat intake or obesity can weaken gut integrity leading to the penetration of gut microbiota or their bacterial products into the circulation, leading to the activation of TLRs on immune cells and subsequently low-grade systemic inflammation in host. Metabolic cells including hepatocytes and adipocytes also express TLRs. Although they are able to produce and secrete inflammatory molecules, the effectiveness remains low compared with the immune cells embedded in liver and adipose tissue. The interaction of TLRs in these metabolic cells or organs with gut microbiota remains unclear, but a few studies have suggested that the functions of these TLRs are related to metabolism. Alteration of the gut microbiota is associated with body weight change and adiposity in human, and the interaction between the commensal gut microbiota and TLRs may possibly involve both metabolic and immunological regulation. In this review, we will summarize the current findings on the relationship between TLRs and gut microbiota with a focus on metabolic regulation, and discuss how such interaction participates in host metabolism.published_or_final_versio

Evaluation of cross-beam vector Doppler ultrasound systems for accurate 3-D velocity measurements

Vector Doppler ultrasound (VDUS) systems offer the potential for improved accuracy in mapping of complex flow parameters, such as recirculation, turbulence, and shear stress which are probable risk factors leading to vascular disease and stroke. Cross-beam VDUS systems were evaluated for velocity accuracy to optimize the number of receivers for the inter-beam angle, wall filter, system orientation, and complexity of flow seen in a stenosed carotid artery. Preliminary results for velocity estimation show promise for validation of numerical results. © 2012 IEEE.published_or_final_versio

The automorphism group of separable states in quantum information theory

We show that the linear group of automorphism of Hermitian matrices which preserves the set of separable states is generated by \emph{natural} automorphisms: change of an orthonormal basis in each tensor factor, partial transpose in each tensor factor, and interchanging two tensor factors of the same dimension. We apply our results to preservers of the product numerical range.Comment: 15 page

Stationary Localized States Due to a Nonlinear Dimeric Impurity Embedded in a Perfect 1-D Chain

The formation of Stationary Localized states due to a nonlinear dimeric impurity embedded in a perfect 1-d chain is studied here using the appropriate Discrete Nonlinear Schr$\ddot{o}$dinger Equation. Furthermore, the nonlinearity has the form, $\chi |C|^\sigma$ where $C$ is the complex amplitude. A proper ansatz for the Localized state is introduced in the appropriate Hamiltonian of the system to obtain the reduced effective Hamiltonian. The Hamiltonian contains a parameter, $\beta = \phi_1/\phi_0$ which is the ratio of stationary amplitudes at impurity sites. Relevant equations for Localized states are obtained from the fixed point of the reduced dynamical system. $|\beta|$ = 1 is always a permissible solution. We also find solutions for which $|\beta| \ne 1$. Complete phase diagram in the $(\chi, \sigma)$ plane comprising of both cases is discussed. Several critical lines separating various regions are found. Maximum number of Localized states is found to be six. Furthermore, the phase diagram continuously extrapolates from one region to the other. The importance of our results in relation to solitonic solutions in a fully nonlinear system is discussed.Comment: Seven figures are available on reques

Characterization and classification of whole-grain rice based on rapid visco analyzer (RVA) pasting profile

Classification of whole grain rice using only amylose content is not practical to predict starch viscosity for end product recommendation. This study aims to characterize and categorize whole-grain rice based on pasting profile of Rapid Visco Analyzer (RVA). The rice cultivars showed a wide range of peak viscosity (89.98 to 280.95 RVU), hold viscosity (59.97 to 211.56 RVU), breakdown viscosity (-0.33 to 130.67 RVU), final viscosity (111.25 to 390.75 RVU), setback viscosity (-44.47 to 205.67 RVU) and pasting temperature (74.17 - 91.15oC). Stability ratio and final viscosity explained 68.8% of total variance in the RVA profiles. The rice cultivars could be grouped into high (> 0.95), medium (0.65-0.95) and low ( 300 RVU), medium (140 - 250 RVU) and low (< 140 RVU) final viscosity. The classification could serve as a basis for effective rice selection according to functional properties of whole grain rice

PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach

Since the read lengths of high throughput sequencing (HTS) technologies are short, de novo assembly which plays significant roles in many applications remains a great challenge. Most of the state-of-the-art approaches base on de Bruijn graph strategy and overlap-layout strategy. However, these approaches which depend on k-mers or read overlaps do not fully utilize information of paired-end and single-end reads when resolving branches. Since they treat all single-end reads with overlapped length larger than a fix threshold equally, they fail to use the more confident long overlapped reads for assembling and mix up with the relative short overlapped reads. Moreover, these approaches have not been special designed for handling tandem repeats (repeats occur adjacently in the genome) and they usually break down the contigs near the tandem repeats. We present PERGA (Paired-End Reads Guided Assembler), a novel sequence-reads-guided de novo assembly approach, which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds using paired-end reads and different read overlap size ranging from Omax to Omin to resolve the gaps and branches. By constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. When the correct extension cannot be determined, PERGA will try to extend the contig by all feasible extensions and determine the correct extension by using look-ahead approach. Many difficult-resolved branches are due to tandem repeats which are close in the genome. PERGA detects such different copies of the repeats to resolve the branches to make the extension much longer and more accurate. We evaluated PERGA on both Illumina real and simulated datasets ranging from small bacterial genomes to large human chromosome, and it constructed longer and more accurate contigs and scaffolds than other state-of-the-art assemblers. PERGA can be freely downloaded at https://github.com/hitbio/PERGA.published_or_final_versio

Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers

BACKGROUND: With the rapid development of genome sequencing techniques, traditional research methods based on the isolation and cultivation of microorganisms are being gradually replaced by metagenomics, which is also known as environmental genomics. The first step, which is still a major bottleneck, of metagenomics is the taxonomic characterization of DNA fragments (reads) resulting from sequencing a sample of mixed species. This step is usually referred as 'binning'. Existing binning methods are based on supervised or semi-supervised approaches which rely heavily on reference genomes of known microorganisms and phylogenetic marker genes. Due to the limited availability of reference genomes and the bias and instability of marker genes, existing binning methods may not be applicable in many cases. RESULTS: In this paper, we present an unsupervised binning method based on the distribution of a carefully selected set of l-mers (substrings of length l in DNA fragments). From our experiments, we show that our method can accurately bin DNA fragments with various lengths and relative species abundance ratios without using any reference and training datasets. Another feature of our method is its error robustness. The binning accuracy decreases by less than 1% when the sequencing error rate increases from 0% to 5%. Note that the typical sequencing error rate of existing commercial sequencing platforms is less than 2%. CONCLUSIONS: We provide a new and effective tool to solve the metagenome binning problem without using any reference datasets or markers information of any known reference genomes (species). The source code of our software tool, the reference genomes of the species for generating the test datasets and the corresponding test datasets are available at http://i.cs.hku.hk/alse/MetaCluster/.published_or_final_versio

Multi-channel pre-beamformed data acquisition system for research on advanced ultrasound imaging methods

The lack of open access to the pre-beamformed data of an ultrasound scanner has limited the research of novel imaging methods to a few privileged laboratories. To address this need, we have developed a pre-beamformed data acquisition (DAQ) system that can collect data over 128 array elements in parallel from the Ultrasonix series of research-purpose ultrasound scanners. Our DAQ system comprises three system-level blocks: 1) a connector board that interfaces with the array probe and the scanner through a probe connector port; 2) a main board that triggers DAQ and controls data transfer to a computer; and 3) four receiver boards that are each responsible for acquiring 32 channels of digitized raw data and storing them to the on-board memory. This system can acquire pre-beamformed data with 12-bit resolution when using a 40-MHz sampling rate. It houses a 16 GB RAM buffer that is sufficient to store 128 channels of pre-beamformed data for 8000 to 25 000 transmit firings, depending on imaging depth; corresponding to nearly a 2-s period in typical imaging setups. Following the acquisition, the data can be transferred through a USB 2.0 link to a computer for offline processing and analysis. To evaluate the feasibility of using the DAQ system for advanced imaging research, two proof-of-concept investigations have been conducted on beamforming and plane-wave B-flow imaging. Results show that adaptive beamforming algorithms such as the minimum variance approach can generate sharper images of a wire cross-section whose diameter is equal to the imaging wavelength (150 μm in our example). Also, planewave B-flow imaging can provide more consistent visualization of blood speckle movement given the higher temporal resolution of this imaging approach (2500 fps in our example). © 2012 IEEE.published_or_final_versio