Realization of generalized quantum searching using nuclear magnetic resonance

According to the theoretical results, the quantum searching algorithm can be generalized by replacing the Walsh-Hadamard(W-H) transform by almost any quantum mechanical operation. We have implemented the generalized algorithm using nuclear magnetic resonance techniques with a solution of chloroform molecules. Experimental results show the good agreement between theory and experiment.Comment: 11 pages,3 figure. Accepted by Phys. Rev. A. Scheduled Issue: 01 Mar 200

Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel image captions. It directly models the probability distribution of generating a word given previous words and an image. Image captions are generated according to this distribution. The model consists of two sub-networks: a deep recurrent neural network for sentences and a deep convolutional network for images. These two sub-networks interact with each other in a multimodal layer to form the whole m-RNN model. The effectiveness of our model is validated on four benchmark datasets (IAPR TC-12, Flickr 8K, Flickr 30K and MS COCO). Our model outperforms the state-of-the-art methods. In addition, the m-RNN model can be applied to retrieval tasks for retrieving images or sentences, and achieves significant performance improvement over the state-of-the-art methods which directly optimize the ranking objective function for retrieval.This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 1231216

Simulation of a Heisenberg XY- chain and realization of a perfect state transfer algorithm using liquid nuclear magnetic resonance

The three- spin chain with Heisenberg XY- interaction is simulated in a three- qubit nuclear magnetic resonance (NMR) quantum computer. The evolution caused by the XY- interaction is decomposed into a series of single- spin rotations and the $J$- coupling evolutions between the neighboring spins. The perfect state transfer (PST) algorithm proposed by M. Christandl et al [Phys. Rev. Lett, 92, 187902(2004)] is realized in the XY- chain

Application of change point analysis to daily influenza-like illness emergency department visits

Background: The utility of healthcare utilization data from US emergency departments (EDs) for rapid monitoring of changes in influenza-like illness (ILI) activity was highlighted during the recent influenza A (H1N1) pandemic. Monitoring has tended to rely on detection algorithms, such as the Early Aberration Reporting System (EARS), which are limited in their ability to detect subtle changes and identify disease trends. Objective: To evaluate a complementary approach, change point analysis (CPA), for detecting changes in the incidence of ED visits due to ILI. Methodology and principal findings Data collected through the Distribute project (isdsdistribute.org), which aggregates data on ED visits for ILI from over 50 syndromic surveillance systems operated by state or local public health departments were used. The performance was compared of the cumulative sum (CUSUM) CPA method in combination with EARS and the performance of three CPA methods (CUSUM, structural change model and Bayesian) in detecting change points in daily time-series data from four contiguous US states participating in the Distribute network. Simulation data were generated to assess the impact of autocorrelation inherent in these time-series data on CPA performance. The CUSUM CPA method was robust in detecting change points with respect to autocorrelation in time-series data (coverage rates at 90% when −0.2≤ρ≤0.2 and 80% when −0.5≤ρ≤0.5). During the 2008–9 season, 21 change points were detected and ILI trends increased significantly after 12 of these change points and decreased nine times. In the 2009–10 flu season, we detected 11 change points and ILI trends increased significantly after two of these change points and decreased nine times. Using CPA combined with EARS to analyze automatically daily ED-based ILI data, a significant increase was detected of 3% in ILI on April 27, 2009, followed by multiple anomalies in the ensuing days, suggesting the onset of the H1N1 pandemic in the four contiguous states. Conclusions and significance As a complementary approach to EARS and other aberration detection methods, the CPA method can be used as a tool to detect subtle changes in time-series data more effectively and determine the moving direction (ie, up, down, or stable) in ILI trends between change points. The combined use of EARS and CPA might greatly improve the accuracy of outbreak detection in syndromic surveillance systems

Molecular Analysis of Sarcoidosis Tissues for Mycobacterium Species DNA

We performed polymerase chain reaction analysis, for Mycobacterium species 16S rRNA, rpoB, and IS6110 sequences, on 25 tissue specimens from patients with sarcoidosis and on 25 control tissue specimens consisting of mediastinal or cervical lymph nodes and lung biopsies. Mycobacterium species 16S rRNA sequences were amplified from 12 (48%) rpoB sequences from 6 (24%) of the sarcoidosis specimens. In total, 16S rRNA or rpoB sequences were amplified from 15 sarcoidosis specimens (60%) but were not detected in any of the control tissues (p=0.00002, Chi square). In three specimens, the sequences resembled Mycobacterium species other than M. tuberculosis. All specimens with sequences consistent with M. tuberculosis were negative for IS6110. We provide evidence that one of a variety of Mycobacterium species, especially organisms resembling M. tuberculosis, is found in most patients with sarcoidosis

Modularization of multi-qubit controlled phase gate and its NMR implementation

Quantum circuit network is a set of circuits that implements a certain computation task. Being at the center of the quantum circuit network, the multi-qubit controlled phase shift is one of the most important quantum gates. In this paper, we apply the method of modular structuring in classical computer architecture to quantum computer and give a recursive realization of the multi-qubit phase gate. This realization of the controlled phase shift gate is convenient in realizing certain quantum algorithms. We have experimentally implemented this modularized multi-qubit controlled phase gate in a three qubit nuclear magnetic resonance quantum system. The network is demonstrated experimentally using line selective pulses in nuclear magnetic resonance technique. The procedure has the advantage of being simple and easy to implement.Comment: to appear in Journal of Optics B: Quantum and Semiclassical Optic

Simrank: Rapid and sensitive general-purpose k-mer search tool

Terabyte-scale collections of string-encoded data are expected from consortia efforts such as the Human Microbiome Project (http://nihroadmap.nih.gov/hmp). Intra- and inter-project data similarity searches are enabled by rapid k-mer matching strategies. Software applications for sequence database partitioning, guide tree estimation, molecular classification and alignment acceleration have benefited from embedded k-mer searches as sub-routines. However, a rapid, general-purpose, open-source, flexible, stand-alone k-mer tool has not been available. Here we present a stand-alone utility, Simrank, which allows users to rapidly identify database strings the most similar to query strings. Performance testing of Simrank and related tools against DNA, RNA, protein and human-languages found Simrank 10X to 928X faster depending on the dataset. Simrank provides molecular ecologists with a high-throughput, open source choice for comparing large sequence sets to find similarity

Self-Reported Fever and Measured Temperature in Emergency Department Records Used for Syndromic Surveillance

Many public health agencies monitor population health using syndromic surveillance, generally employing information from emergency department (ED) visit records. When combined with other information, objective evidence of fever may enhance the accuracy with which surveillance systems detect syndromes of interest, such as influenza-like illness. This study found that patient chief complaint of self-reported fever was more readily available in ED records than measured temperature and that the majority of patients with an elevated temperature recorded also self-reported fever. Due to its currently limited availability, we conclude that measured temperature is likely to add little value to self-reported fever in syndromic surveillance for febrile illness using ED records

Foregut microbiome in development of esophageal adenocarcinoma

Esophageal adenocarcinoma (EA), the type of cancer linked to heartburn due to gastroesophageal reflux diseases (GERD), has increased six fold in the past 30 years. This cannot currently be explained by the usual environmental or by host genetic factors. EA is the end result of a sequence of GERD-related diseases, preceded by reflux esophagitis (RE) and Barrett’s esophagus (BE). Preliminary studies by Pei and colleagues at NYU on elderly male veterans identified two types of microbiotas in the esophagus. Patients who carry the type II microbiota are >15 fold likely to have esophagitis and BE than those harboring the type I microbiota. In a small scale study, we also found that 3 of 3 cases of EA harbored the type II biota. The findings have opened a new approach to understanding the recent surge in the incidence of EA. 

Our long-term goal is to identify the cause of GERD sequence. The hypothesis to be tested is that changes in the foregut microbiome are associated with EA and its precursors, RE and BE in GERD sequence. We will conduct a case control study to demonstrate the microbiome disease association in every stage of GERD sequence, as well as analyze the trend in changes in the microbiome along disease progression toward EA, by two specific aims. Aim 1 is to conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD sequence. Furthermore, spatial relationship between the esophageal microbiota and upstream (mouth) and downstream (stomach) foregut microbiotas as well as temporal stability of the microbiome-disease association will also be examined. Aim 2 is to define the distal esophageal metagenome and demonstrate its association with GERD sequence. Detailed analyses will include pathway-disease and gene-disease associations. Archaea, fungi and viruses, if identified, also will be correlated with the diseases. A significant association between the foregut microbiome and GERD sequence, if demonstrated, will be the first step for eventually testing whether an abnormal microbiome is required for the development of the sequence of phenotypic changes toward EA. If EA and its precursors represent a microecological disease, treating the cause of GERD might become possible, for example, by normalizing the microbiota through use of antibiotics, probiotics, or prebiotics. Causative therapy of GERD could prevent its progression and reverse the current trend of increasing incidence of EA

Oral Microbiome Profiles: 16S rRNA Pyrosequencing and Microarray Assay Comparison

The human oral microbiome is potentially related to diverse health conditions and high-throughput technology provides the possibility of surveying microbial community structure at high resolution. We compared two oral microbiome survey methods: broad-based microbiome identification by 16S rRNA gene sequencing and targeted characterization of microbes by custom DNA microarray.Oral wash samples were collected from 20 individuals at Memorial Sloan-Kettering Cancer Center. 16S rRNA gene survey was performed by 454 pyrosequencing of the V3–V5 region (450 bp). Targeted identification by DNA microarray was carried out with the Human Oral Microbe Identification Microarray (HOMIM). Correlations and relative abundance were compared at phylum and genus level, between 16S rRNA sequence read ratio and HOMIM hybridization intensity.; Correlation = 0.70–0.84).Microbiome community profiles assessed by 16S rRNA pyrosequencing and HOMIM were highly correlated at the phylum level and, when comparing the more commonly detected taxa, also at the genus level. Both methods are currently suitable for high-throughput epidemiologic investigations relating identified and more common oral microbial taxa to disease risk; yet, pyrosequencing may provide a broader spectrum of taxa identification, a distinct sequence-read record, and greater detection sensitivity