Development of a Database for Drilled Shaft Foundation Testing (DSHAFT), June 2012

Drilled shafts have been used in the US for more than 100 years in bridges and buildings as a deep foundation alternative. For many of these applications, the drilled shafts were designed using the Working Stress Design (WSD) approach. Even though WSD has been used successfully in the past, a move toward Load Resistance Factor Design (LRFD) for foundation applications began when the Federal Highway Administration (FHWA) issued a policy memorandum on June 28, 2000.The policy memorandum requires all new bridges initiated after October 1, 2007, to be designed according to the LRFD approach. This ensures compatibility between the superstructure and substructure designs, and provides a means of consistently incorporating sources of uncertainty into each load and resistance component. Regionally-calibrated LRFD resistance factors are permitted by the American Association of State Highway and Transportation Officials (AASHTO) to improve the economy and competitiveness of drilled shafts. To achieve this goal, a database for Drilled SHAft Foundation Testing (DSHAFT) has been developed. DSHAFT is aimed at assimilating high quality drilled shaft test data from Iowa and the surrounding regions, and identifying the need for further tests in suitable soil profiles. This report introduces DSHAFT and demonstrates its features and capabilities, such as an easy-to-use storage and sharing tool for providing access to key information (e.g., soil classification details and cross-hole sonic logging reports). DSHAFT embodies a model for effective, regional LRFD calibration procedures consistent with PIle LOad Test (PILOT) database, which contains driven pile load tests accumulated from the state of Iowa. PILOT is now available for broader use at the project website: http://srg.cce.iastate.edu/lrfd/. DSHAFT, available in electronic form at http://srg.cce.iastate.edu/dshaft/, is currently comprised of 32 separate load tests provided by Illinois, Iowa, Minnesota, Missouri and Nebraska state departments of transportation and/or department of roads. In addition to serving as a manual for DSHAFT and providing a summary of the available data, this report provides a preliminary analysis of the load test data from Iowa, and will open up opportunities for others to share their data through this quality–assured process, thereby providing a platform to improve LRFD approach to drilled shafts, especially in the Midwest region.

Maintenance Asset Management Project -- Phase II, July 31, 2013

Expanded abstract: Iowa Department of Transportation (IA DOT) is finalizing research to streamline field inventory/inspection of culverts by Maintenance and Construction staff while maximizing the use of tablet technologies. The project began in 2011 to develop some new best practices for field staff to assist in the inventory, inspection and maintenance of assets along the roadway. The team has spent the past year working through the complexities of identifying the most appropriate tablet hardware for field data collection. A small scale deployment of tablets occurred in spring of 2013 to collect several safety related assets (culverts, signs, guardrail, and incidents). Data can be collected in disconnected or connected modes and there is an associated desktop environment where data can be viewed and queried after being synced into the master database. The development of a deployment plan and related workflow processes are underway; which will eventually feed information into IA DOTs larger asset management system and make the information available for decision making. The team is also working with the IA DOT Design Office on Computer Aided Drafting (CAD) data processing and the IA DOT Construction office with a new digital As-Built plan process to leverage the complete data life-cycle so information can be developed once and leveraged by the Maintenance staff farther along in the process.

Genome-wide association for abdominal subcutaneous and visceral adipose reveals a novel locus for visceral fat in women.

Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots quantified using computed tomography (CT) to uncover novel loci for body fat distribution among participants of European ancestry. Subcutaneous and visceral fat were quantified in 5,560 women and 4,997 men from 4 population-based studies. Genome-wide genotyping was performed using standard arrays and imputed to ~2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), VAT adjusted for body mass index, and VAT/SAT ratio (a metric of the propensity to store fat viscerally as compared to subcutaneously) in the overall sample and in women and men separately. A weighted z-score meta-analysis was conducted. For the VAT/SAT ratio, our most significant p-value was rs11118316 at LYPLAL1 gene (p = 3.1 × 10E-09), previously identified in association with waist-hip ratio. For SAT, the most significant SNP was in the FTO gene (p = 5.9 × 10E-08). Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, rs1659258 near THNSL2 (p = 1.6 × 10-08), but not men (p = 0.75). Validation of this SNP in the GIANT consortium data demonstrated a similar sex-specific pattern, with observed significance in women (p = 0.006) but not men (p = 0.24) for BMI and waist circumference (p = 0.04 [women], p = 0.49 [men]). Finally, we interrogated our data for the 14 recently published loci for body fat distribution (measured by waist-hip ratio adjusted for BMI); associations were observed at 7 of these loci. In contrast, we observed associations at only 7/32 loci previously identified in association with BMI; the majority of overlap was observed with SAT. Genome-wide association for visceral and subcutaneous fat revealed a SNP for VAT in women. More refined phenotypes for body composition and fat distribution can detect new loci not previously uncovered in large-scale GWAS of anthropometric traits.

An integrated encyclopedia of DNA elements in the human genome.

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

ABS: a database of Annotated regulatory Binding Sites from orthologous promoters

Information about the genomic coordinates and the sequence of experimentally identified transcription factor binding sites is found scattered under a variety of diverse formats. The availability of standard collections of such high-quality data is important to design, evaluate and improve novel computational approaches to identify binding motifs on promoter sequences from related genes. ABS (http://genome.imim.es/datasets/abs2005/index.html) is a public database of known binding sites identified in promoters of orthologous vertebrate genes that have been manually curated from bibliography. We have annotated 650 experimental binding sites from 68 transcription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. A simple and easy-to-use web interface facilitates data retrieval allowing different views of the information. In addition, the release 1.0 of ABS includes a customizable generator of artificial datasets based on the known sites contained in the collection and an evaluation tool to aid during the training and the assessment of motif-finding programs.

First genome size estimations for some eudicot families and genera

First genome size estimations for some eudicot families and genera.- Genome size diversity in angiosperms varies roughly 2400-fold, although approximately 45% of angiosperm families lack a single genome size estimation, and therefore, this range could be enlarged. To contribute completing family and genera representation, DNA C-Values are here provided for 19 species from 16 eudicot families, including first values for 6 families, 14 genera and 17 species. The sample of species studied is very diverse, including herbs, weeds, vines, shrubs and trees. Data are discussed regarding previous genome size estimates of closely related species or genera, if any, their chromosome number, growth form or invasive behaviour. The present research contributes approximately 1.5% new values for previously unreported angiosperm families, being the current coverage around 55% of angiosperm families, according to the Plant DNA C-Values Database.

CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature.

The main goal of CleanEx is to provide access to public gene expression data via unique gene names. A second objective is to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and cross-data set comparisons. A consistent and up-to-date gene nomenclature is achieved by associating each single experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of human genes and genes from model organisms. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing cross-references to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resource, such as cDNA clones or Affymetrix probe sets. The web-based query interfaces offer access to individual entries via text string searches or quantitative expression criteria. CleanEx is accessible at: http://www.cleanex.isb-sib.ch/.

Indexing strategies for rapid searches of short words in genome sequences.

Searching for matches between large collections of short (14-30 nucleotides) words and sequence databases comprising full genomes or transcriptomes is a common task in biological sequence analysis. We investigated the performance of simple indexing strategies for handling such tasks and developed two programs, fetchGWI and tagger, that index either the database or the query set. Either strategy outperforms megablast for searches with more than 10,000 probes. FetchGWI is shown to be a versatile tool for rapidly searching multiple genomes, whose performance is limited in most cases by the speed of access to the filesystem. We have made publicly available a Web interface for searching the human, mouse, and several other genomes and transcriptomes with oligonucleotide queries.

Development of LRFD Procedures for Bridge Pile Foundations in Iowa, Volume I: An Electronic Database for PIle LOad Tests (PILOT), TR-573, 2011

For well over 100 years, the Working Stress Design (WSD) approach has been the traditional basis for geotechnical design with regard to settlements or failure conditions. However, considerable effort has been put forth over the past couple of decades in relation to the adoption of the Load and Resistance Factor Design (LRFD) approach into geotechnical design. With the goal of producing engineered designs with consistent levels of reliability, the Federal Highway Administration (FHWA) issued a policy memorandum on June 28, 2000, requiring all new bridges initiated after October 1, 2007, to be designed according to the LRFD approach. Likewise, regionally calibrated LRFD resistance factors were permitted by the American Association of State Highway and Transportation Officials (AASHTO) to improve the economy of bridge foundation elements. Thus, projects TR-573, TR-583 and TR-584 were undertaken by a research team at Iowa State University’s Bridge Engineering Center with the goal of developing resistance factors for pile design using available pile static load test data. To accomplish this goal, the available data were first analyzed for reliability and then placed in a newly designed relational database management system termed PIle LOad Tests (PILOT), to which this first volume of the final report for project TR-573 is dedicated. PILOT is an amalgamated, electronic source of information consisting of both static and dynamic data for pile load tests conducted in the State of Iowa. The database, which includes historical data on pile load tests dating back to 1966, is intended for use in the establishment of LRFD resistance factors for design and construction control of driven pile foundations in Iowa. Although a considerable amount of geotechnical and pile load test data is available in literature as well as in various State Department of Transportation files, PILOT is one of the first regional databases to be exclusively used in the development of LRFD resistance factors for the design and construction control of driven pile foundations. Currently providing an electronically organized assimilation of geotechnical and pile load test data for 274 piles of various types (e.g., steel H-shaped, timber, pipe, Monotube, and concrete), PILOT (http://srg.cce.iastate.edu/lrfd/) is on par with such familiar national databases used in the calibration of LRFD resistance factors for pile foundations as the FHWA’s Deep Foundation Load Test Database. By narrowing geographical boundaries while maintaining a high number of pile load tests, PILOT exemplifies a model for effective regional LRFD calibration procedures.

GIS-Based Accident Location and Analysis System (GIS-ALAS) Project Report: Phase 1, 1998

This report summarizes progress made in Phase 1 of the GIS-based Accident Location and Analysis System (GIS-ALAS) project. The GIS-ALAS project builds on several longstanding efforts by the Iowa Department of Transportation (DOT), law enforcement agencies, Iowa State University, and several other entities to create a locationally-referenced highway accident database for Iowa. Most notable of these efforts is the Iowa DOT’s development of a PC-based accident location and analysis system (PC-ALAS), a system that has been well received by users since it was introduced in 1989. With its pull-down menu structure, PC-ALAS is more portable and user-friendly than its mainframe predecessor. Users can obtain accident statistics for locations during specified time periods. Searches may be refined to identify accidents of specific types or involving drivers with certain characteristics. Output can be viewed on a computer screen, sent to a file, or printed using pre-defined formats.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data.

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. AVAILABILITY: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Implementation of an Integrated Activity-Based Costing in a Holistic Database Management System and its Implications for Operations Management

Diplomityössä on tutkittu reaaliaikaisen toimintolaskennan toteuttamista suomalaisen lasersiruja valmistavan PK-yrityksen tietojärjestelmään. Lisäksi on tarkasteltu toimintolaskennan vaikutuksia operatiiviseen toimintaan sekä toimintojen johtamiseen. Työn kirjallisuusosassa on käsitelty kirjallisuuslähteiden perusteella toimintolaskennan teorioita, laskentamenetelmiä sekä teknisessä toteutuksessa käytettyjä teknologioita. Työn toteutusosassa suunniteltiin ja toteutettiin WWW-pohjainen toimintolaskentajärjestelmä case-yrityksen kustannuslaskennan sekä taloushallinnon avuksi. Työkalu integroitiin osaksi yrityksen toiminnanohjaus- sekä valmistuksenohjausjärjestelmää. Perinteisiin toimintolaskentamallien tiedonkeruujärjestelmiin verrattuna case-yrityksessä syötteet toimintolaskentajärjestelmälle tulevat reaaliaikaisesti osana suurempaa tietojärjestelmäintegraatiota.Diplomityö pyrkii luomaan suhteen toimintolaskennan vaatimusten ja tietokantajärjestelmien välille. Toimintolaskentajärjestelmää yritys voi hyödyntää esimerkiksi tuotteiden hinnoittelussa ja kustannuslaskennassa näkemällä tuotteisiin liittyviä kustannuksia eri näkökulmista. Päätelmiä voidaan tehdä tarkkaan kustannusinformaatioon perustuen sekä määrittää järjestelmän tuottaman datan perusteella, onko tietyn projektin, asiakkuuden tai tuotteen kehittäminen taloudellisesti kannattavaa.

PhylomeDB v4: zooming into the plurality of evolutionary histories of a genome

Phylogenetic trees representing the evolutionary relationships of homologous genes are the entry point for many evolutionary analyses. For instance, the use of a phylogenetic tree can aid in the inference of orthology and paralogy relationships, and in the detection of relevant evolutionary events such as gene family expansions and contractions, horizontal gene transfer, recombination or incomplete lineage sorting. Similarly, given the plurality of evolutionary histories among genes encoded in a given genome, there is a need for the combined analysis of genome-wide collections of phylogenetic trees (phylomes). Here, we introduce a new release of PhylomeDB (http://phylomedb.org), a public repository of phylomes. Currently, PhylomeDB hosts 120 public phylomes, comprising >1.5 million maximum likelihood trees and multiple sequence alignments. In the current release, phylogenetic trees are annotated with taxonomic, protein-domain arrangement, functional and evolutionary information. PhylomeDB is also a major source for phylogeny-based predictions of orthology and paralogy, covering >10 million proteins across 1059 sequenced species. Here we describe newly implemented PhylomeDB features, and discuss a benchmark of the orthology predictions provided by the database, the impact of proteome updates and the use of the phylome approach in the analysis of newly sequenced genomes and transcriptomes.

Genome-wide transcriptional responses to shade: Linking shade avoidance and auxin

Plants have the ability to use the composition of incident light as a cue to adapt development and growth to their environment. Arabidopsis thaliana as well as many crops are best adapted to sunny habitats. When subjected to shade, these plants exhibit a variety of physiological responses collectively called shade avoidance syndrome (SAS). It includes increased growth of hypocotyl and petioles, decreased growth rate of cotyledons and reduced branching and crop yield. These responses are mainly mediated by phytochrome photoreceptors, which exist either in an active, far-red light (FR) absorbing or an inactive, red light (R) absorbing isoform. In direct sunlight, the R to FR light (R/FR) ratio is high and converts the phytochromes into their physiologically active state. The phytochromes interact with downstream transcription factors such as PHYTOCHROME INTERACTING FACTOR (PIF), which are subsequently degraded. Light filtered through a canopy is strongly depleted in R, which result in a low R/FR ratio and renders the phytochromes inactive. Protein levels of downstream transcription factors are stabilized, which initiates the expression of shade-induced genes such as HFR1, PIL1 or ATHB-2. In my thesis, I investigated transcriptional responses mediated by the SAS in whole Arabidopsis seedlings. Using microarray and chromatin immunoprecipitation data, we identified genome-wide PIF4 and PIF5 dependent shade regulated gene as well as putative direct target genes of PIF5. This revealed evidence for a direct regulatory link between phytochrome signaling and the growth promoting phytohormone auxin (IAA) at the level of biosynthesis, transport and signaling. Subsequently, it was shown, that free-IAA levels are upregulated in response to shade. It is assumed that shade-induced auxin production takes predominantly place in cotyledons of seedlings. This implies, that IAA is subsequently transported basipetally to the hypocotyl and enhances elongation growth. The importance of auxin transport for growth responses has been established by chemical and genetic approaches. To gain a better understanding of spatio-temporal transcriptional regulation of shade-induce auxin, I generated in a second project, an organ specific high throughput data focusing on cotyledon and hypocotyl of young Arabidopsis seedlings. Interestingly, both organs show an opposite growth regulation by shade. I first investigated the spatio-transcriptional regulation of auxin re- sponsive gene, in order to determine how broad gene expression pattern can be explained by the hypothesized movement of auxin from cotyledons to hypocotyls in shade. The analysis suggests, that several genes are indeed regulated according to our prediction and others are regulated in a more complex manner. In addition, analysis of gene families of auxin biosynthetic and transport components, lead to the identification of essential family members for shade-induced growth re- sponses, which were subsequently experimentally confirmed. Finally, the analysis of expression pattern identified several candidate genes, which possibly explain aspects of the opposite growth response of the different organs.