Temporal Coding of Volumetric Imagery

'Image volumes' refer to realizations of images in other dimensions such as time, spectrum, and focus. Recent advances in scientific, medical, and consumer applications demand improvements in image volume capture. Though image volume acquisition continues to advance, it maintains the same sampling mechanisms that have been used for decades; every voxel must be scanned and is presumed independent of its neighbors. Under these conditions, improving performance comes at the cost of increased system complexity, data rates, and power consumption.

This dissertation explores systems and methods capable of efficiently improving sensitivity and performance for image volume cameras, and specifically proposes several sampling strategies that utilize temporal coding to improve imaging system performance and enhance our awareness for a variety of dynamic applications.

Video cameras and camcorders sample the video volume (x,y,t) at fixed intervals to gain understanding of the volume's temporal evolution. Conventionally, one must reduce the spatial resolution to increase the framerate of such cameras. Using temporal coding via physical translation of an optical element known as a coded aperture, the compressive temporal imaging (CACTI) camera emonstrates a method which which to embed the temporal dimension of the video volume into spatial (x,y) measurements, thereby greatly improving temporal resolution with minimal loss of spatial resolution. This technique, which is among a family of compressive sampling strategies developed at Duke University, temporally codes the exposure readout functions at the pixel level.

Since video cameras nominally integrate the remaining image volume dimensions (e.g. spectrum and focus) at capture time, spectral (x,y,t,\lambda) and focal (x,y,t,z) image volumes are traditionally captured via sequential changes to the spectral and focal state of the system, respectively. The CACTI camera's ability to embed video volumes into images leads to exploration of other information within that video; namely, focal and spectral information. The next part of the thesis demonstrates derivative works of CACTI: compressive extended depth of field and compressive spectral-temporal imaging. These works successfully show the technique's extension of temporal coding to improve sensing performance in these other dimensions.

Geometrical optics-related tradeoffs, such as the classic challenges of wide-field-of-view and high resolution photography, have motivated the development of mulitscale camera arrays. The advent of such designs less than a decade ago heralds a new era of research- and engineering-related challenges. One significant challenge is that of managing the focal volume (x,y,z) over wide fields of view and resolutions. The fourth chapter shows advances on focus and image quality assessment for a class of multiscale gigapixel cameras developed at Duke.

Along the same line of work, we have explored methods for dynamic and adaptive addressing of focus via point spread function engineering. We demonstrate another form of temporal coding in the form of physical translation of the image plane from its nominal focal position. We demonstrate this technique's capability to generate arbitrary point spread functions.

Organizing and Interpreting Unstructured Qualitative Data

In the last several years there has been an increase in the amount of qualitative research using in-depth interviews and comprehensive content analyses in sport psychology. However, no explicit method has been provided to deal with the large amount of unstructured data. This article provides common guidelines for organizing and interpreting unstructured data. Two main operations are suggested and discussed: first, coding meaningful text segments, or creating tags, and second, regrouping similar text segments,or creating categories. Furthermore, software programs for the microcomputer are presented as away to facilitate the organization and interpretation of qualitative data

Coding Manuals

The VRAG-R is designed to assess the likelihood of violent or sexual reoffending among male offenders. The data set comprises demographic, criminal history, psychological assessment, and psychiatric information about the offenders gathered from institutional files together with post-release recidivism information. The VRAG-R is a twelve-item actuarial instrument and the scores on these items form part of the data set. Because one of the goals of the VRAG-R development project was to compare the VRAG-R to the VRAG, subjects' VRAG scores are included in this data set. Access to the VRAG-R dataset is restricted. Contact Data Services, Queen's University Library (academic.services@queensu.ca) for access.

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease.

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1, 2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case–control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer’s disease in seven independent case–control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer’s disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer’s disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer’s disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

Data Processing Systems Manual: Highway Noise Prediction, 1972

The Data Processing Department of ISHC has developed coding forms to be used for the data to be entered into the program. The Highway Planning and Programming and the Design Departments are responsible for coding and submitting the necessary data forms to Data Processing for the noise prediction on the highway sections.

Investigation of the role of long non-coding RNAs in oncogene induced cellular senescence

Cellular senescence is a stable arrest of cell proliferation induced by several factors such as activated oncogenes, oxidative stress and shortening of telomeres. Senescence acts as a tumour suppression mechanism to halt the progression of cancer. However, senescence may also impact negatively upon tissue regeneration, thus contributing to the effects of ageing. The eukaryotic genome is controlled by various modes of transcriptional and translational regulation. Focus has therefore centred on the role of long non- coding RNAs (lncRNAs) in regulating the genome. Accordingly, understanding how lncRNAs function to regulate the senescent genome is integral to improving our knowledge and understanding of tumour suppression and ageing. Within this study, I set out to investigate the expression of lncRNAs’ expression within models of senescence. Through a custom expression array, I have shown that expression of multiple different lncRNAs is up-regulated and down regulated in IMR90 replicative senescent fibroblasts and oncogene-induced senescent melanocytes. LncRNA expression was determined to be specific to stable senescence-associated cell arrest and predominantly within the nucleus of senescent cells. In order to examine the function of lncRNA expression in senescence, I selected lncRNA transcript ENST0000430998 (lncRNA_98) to focus my investigations upon. LncRNA_98 was robustly upregulated within multiple models of senescence and efficiently depleted using anti-sense oligonucleotide technology. Characterisation and unbiased RNA-sequencing of lncRNA_98 deficient senescent cells highlighted a list of genes that are regulated by lncRNA_98 expression in senescent cells and may regulate aspects of the senescence program. Specifically, the formation of SAHF was impeded upon depletion of lncRNA_98 expression and levels of total pRB protein expression severely decreased. Validation and recapitulation of consequences of pRB depletion was confirmed through lncRNA_98 knock-out cells generated using CRISPR technology. Surprisingly, inhibition of ATM kinase functions permitted the restoration of pRB protein levels within lncRNA_98 deficient cells. I propose that lncRNA_98 antagonizes the ability of ATM kinase to downregulate pRB expression at a post-transcriptional level, thereby potentiating senescence. Furthermore, lncRNA expression was detected within fibroblasts of old individuals and visualised within senescent melanocytes in human benign nevi, a barrier to melanoma progression. Conversely, mining of 337 TCGA primary melanoma data sets highlighted that the lncRNA_98 gene and its expression was lost from a significant proportion of melanoma samples, consistent with lncRNA_98 having a tumour suppressor functions. The data presented in this study illustrates that lncRNA_98 expression has a regulatory role over pRB expression in senescence and may regulate aspects of tumourigenesis and ageing.

RICH AND EFFICIENT VISUAL DATA REPRESENTATION

Increasing the size of training data in many computer vision tasks has shown to be very effective. Using large scale image datasets (e.g. ImageNet) with simple learning techniques (e.g. linear classifiers) one can achieve state-of-the-art performance in object recognition compared to sophisticated learning techniques on smaller image sets. Semantic search on visual data has become very popular. There are billions of images on the internet and the number is increasing every day. Dealing with large scale image sets is intense per se. They take a significant amount of memory that makes it impossible to process the images with complex algorithms on single CPU machines. Finding an efficient image representation can be a key to attack this problem. A representation being efficient is not enough for image understanding. It should be comprehensive and rich in carrying semantic information. In this proposal we develop an approach to computing binary codes that provide a rich and efficient image representation. We demonstrate several tasks in which binary features can be very effective. We show how binary features can speed up large scale image classification. We present learning techniques to learn the binary features from supervised image set (With different types of semantic supervision; class labels, textual descriptions). We propose several problems that are very important in finding and using efficient image representation.

Phylodynamic modelling of foot-and-mouth disease virus sequence data

The under-reporting of cases of infectious diseases is a substantial impediment to the control and management of infectious diseases in both epidemic and endemic contexts. Information about infectious disease dynamics can be recovered from sequence data using time-varying coalescent approaches, and phylodynamic models have been developed in order to reconstruct demographic changes of the numbers of infected hosts through time. In this study I have demonstrated the general concordance between empirically observed epidemiological incidence data and viral demography inferred through analysis of foot-and-mouth disease virus VP1 coding sequences belonging to the CATHAY topotype over large temporal and spatial scales. However a more precise and robust relationship between the effective population size (

Analyzing downloaded data from road side units

En el contexto de las redes vehiculares, analizamos una aplicación de descarga de mapas, donde cada vehículo descarga datos de mapas relevantes según su posición. Entre las estrategias propuestas está la de utilizar las redes con infraestructura (I2V) además de las redes vehículo a vehículo (V2V). En este trabajo comparamos dos métodos de fragmentación de archivos, para el segmento I2V; los métodos son Random Sort Strategy (RSS) y Network Coding (NC). Encontramos que: cuando se utiliza NC la distribución de los diferentes fragmentos recibidos es independiente del tamaño del archivo. Cuando se utiliza RSS, la media y la desviación estándar dependen del tamaño del archivo. Estos resultados serán utilizados para el análisis del segmento V2V de la red.

Identifying cancer-related microRNAs based on gene expression data

International audience

Coding Manuals

The VRAG-R is designed to assess the likelihood of violent or sexual reoffending among male offenders. The data set comprises demographic, criminal history, psychological assessment, and psychiatric information about the offenders gathered from institutional files together with post-release recidivism information. The VRAG-R is a twelve-item actuarial instrument and the scores on these items form part of the data set. Because one of the goals of the VRAG-R development project was to compare the VRAG-R to the VRAG, subjects' VRAG scores are included in this data set. Access to the VRAG-R dataset is restricted. Contact Data Services, Queen's University Library (academic.services@queensu.ca) for access.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

[gait Speed, Grip Strength And Self-rated Health Among The Elderly: Data From The Fibra Campinas Network, São Paulo, Brazil].

The article seeks to investigate patterns of performance and relationships between grip strength, gait speed and self-rated health, and investigate the relationships between them, considering the variables of gender, age and family income. This was conducted in a probabilistic sample of community-dwelling elderly aged 65 and over, members of a population study on frailty. A total of 689 elderly people without cognitive deficit suggestive of dementia underwent tests of gait speed and grip strength. Comparisons between groups were based on low, medium and high speed and strength. Self-related health was assessed using a 5-point scale. The males and the younger elderly individuals scored significantly higher on grip strength and gait speed than the female and oldest did; the richest scored higher than the poorest on grip strength and gait speed; females and men aged over 80 had weaker grip strength and lower gait speed; slow gait speed and low income arose as risk factors for a worse health evaluation. Lower muscular strength affects the self-rated assessment of health because it results in a reduction in functional capacity, especially in the presence of poverty and a lack of compensatory factors.

Correlation Between Cephalometric Data And Severity Of Sleep Apnea.

Obstructive sleep apnea syndrome has a high prevalence among adults. Cephalometric variables can be a valuable method for evaluating patients with this syndrome. To correlate cephalometric data with the apnea-hypopnea sleep index. We performed a retrospective and cross-sectional study that analyzed the cephalometric data of patients followed in the Sleep Disorders Outpatient Clinic of the Discipline of Otorhinolaryngology of a university hospital, from June 2007 to May 2012. Ninety-six patients were included, 45 men, and 51 women, with a mean age of 50.3 years. A total of 11 patients had snoring, 20 had mild apnea, 26 had moderate apnea, and 39 had severe apnea. The distance from the hyoid bone to the mandibular plane was the only variable that showed a statistically significant correlation with the apnea-hypopnea index. Cephalometric variables are useful tools for the understanding of obstructive sleep apnea syndrome. The distance from the hyoid bone to the mandibular plane showed a statistically significant correlation with the apnea-hypopnea index.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.