Prediction of welding distortion in butt joint of thin plates

This paper investigates distortions and residual stresses induced in butt joint of thin plates using Metal Inert Gas welding. A moving distributed heat source model based on Goldak's double-ellipsoid heat flux distribution is implemented in Finite Element (FE) simulation of the welding process. Thermo-elastic-plastic FE methods are applied to modelling thermal and mechanical behaviour of the welded plate during the welding process. Prediction of temperature variations, fusion zone and heat affected zone as well as longitudinal and transverse shrinkage, angular distortion, and residual stress is obtained. FE analysis results of welding distortions are compared with existing experimental and empirical predictions. The welding speed and plate thickness are shown to have considerable effects on welding distortions and residual stresses. © 2009 Elsevier Ltd. All rights reserved.

AllerTOP - a server for in silico prediction of allergens

Background: Allergy is a form of hypersensitivity to normally innocuous substances, such as dust, pollen, foods or drugs. Allergens are small antigens that commonly provoke an IgE antibody response. There are two types of bioinformatics-based allergen prediction. The first approach follows FAO/WHO Codex alimentarius guidelines and searches for sequence similarity. The second approach is based on identifying conserved allergenicity-related linear motifs. Both approaches assume that allergenicity is a linearly coded property. In the present study, we applied ACC pre-processing to sets of known allergens, developing alignment-independent models for allergen recognition based on the main chemical properties of amino acid sequences.Results: A set of 684 food, 1,156 inhalant and 555 toxin allergens was collected from several databases. A set of non-allergens from the same species were selected to mirror the allergen set. The amino acids in the protein sequences were described by three z-descriptors (z1, z2 and z3) and by auto- and cross-covariance (ACC) transformation were converted into uniform vectors. Each protein was presented as a vector of 45 variables. Five machine learning methods for classification were applied in the study to derive models for allergen prediction. The methods were: discriminant analysis by partial least squares (DA-PLS), logistic regression (LR), decision tree (DT), naïve Bayes (NB) and k nearest neighbours (kNN). The best performing model was derived by kNN at k = 3. It was optimized, cross-validated and implemented in a server named AllerTOP, freely accessible at http://www.pharmfac.net/allertop. AllerTOP also predicts the most probable route of exposure. In comparison to other servers for allergen prediction, AllerTOP outperforms them with 94% sensitivity.Conclusions: AllerTOP is the first alignment-free server for in silico prediction of allergens based on the main physicochemical properties of proteins. Significantly, as well allergenicity AllerTOP is able to predict the route of allergen exposure: food, inhalant or toxin. © 2013 Dimitrov et al.; licensee BioMed Central Ltd.

Review on protection issues of low-voltage distribution network with multiple powerelectronic-converter-interfaced distribution energy resources

The realisation of an eventual low-voltage (LV) Smart Grid with a complete communication infrastructure is a gradual process. During this evolution the protection scheme of distribution networks should be continuously adapted and optimised to fit the protection and cost requirements at the time. This paper aims to review practices and research around the design of an effective, adaptive and economical distribution network protection scheme. The background of this topic is introduced and potential problems are defined from conventional protection theories and new Smart Grid technologies. Challenges are identified with possible solutions defined as a pathway to the ultimate flexible and reliable LV protection systems.

Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Towards the prediction of mutations in genomic sequences

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Changes of 5-hydroxymethylcytosine distribution during myeloid and lymphoid differentiation of CD34+ cells

BACKGROUND: Hematopoietic stem cell renewal and differentiation are regulated through epigenetic processes. The conversion of 5-methylcytosine into 5-hydroxymethylcytosine (5hmC) by ten-eleven-translocation enzymes provides new insights into the epigenetic regulation of gene expression during development. Here, we studied the potential gene regulatory role of 5hmC during human hematopoiesis.

RESULTS: We used reduced representation of 5-hydroxymethylcytosine profiling (RRHP) to characterize 5hmC distribution in CD34+ cells, CD4+ T cells, CD19+ B cells, CD14+ monocytes and granulocytes. In all analyzed blood cell types, the presence of 5hmC at gene bodies correlates positively with gene expression, and highest 5hmC levels are found around transcription start sites of highly expressed genes. In CD34+ cells, 5hmC primes for the expression of genes regulating myeloid and lymphoid lineage commitment. Throughout blood cell differentiation, intragenic 5hmC is maintained at genes that are highly expressed and required for acquisition of the mature blood cell phenotype. Moreover, in CD34+ cells, the presence of 5hmC at enhancers associates with increased binding of RUNX1 and FLI1, transcription factors essential for hematopoiesis.

CONCLUSIONS: Our study provides a comprehensive genome-wide overview of 5hmC distribution in human hematopoietic cells and new insights into the epigenetic regulation of gene expression during human hematopoiesis.

An evaluation of trace metal distribution, enrichment factors and risk in sediments of a coastal lagoon (Ria de Aveiro, Portugal)

This paper describes a sediment survey undertaken to unravel patterns of distribution and dispersion of trace metals in an Iberian Peninsula northwestern coastal lagoon (Ria de Aveiro). Cadmium, lead, chromium, copper and zinc were analyzed in bottom sediments. Geochemical normalization is performed and two different regression models for each metal versus aluminum are tested and compared using the respective enrichment factors (EF), an estimation of the relative importance of anthropogenic contributions to the studied sediments. Mean sediment quality guideline quotients (mSQGQ) are used to evaluate sediment quality and associated potential risk to biota with effects range low as empirical sediment quality guideline (SQG) in the basis for mSQGQ calculation. Additionally, the geoaccumulation index is calculated to compare studied sediment levels to global baseline levels. The application of SQGs revealed insufficient characterization capability, especially when contrasted to EF calculated from the regression methods. These pointed a mildly enriched system with localized “hot spot” areas. Therefore, it can be considered that bottom sediments in the Ria de Aveiro system are in their majority unpolluted, zinc being the only metal of concern, presenting enrichment in all four main channels. The major rivers outlets (Caster, Antuã, and Vouga) constitute point sources, thus presenting potential risk for biota. Yet, the strong tidal influence creates a damping effect by efficiently redistributing sediment bound metals.

Did the 2011 Tohoku Tsunami increase the risk of species invasions along the Gulf of Alaska?

Thesis (Master's)--University of Washington, 2016-06

Restoration ecology of coastal lagoons: new methods for the prediction of ecological trajectories and economic valuation

Conservation of the seven lagoons of the Palavas complex (southern France) has been severely impaired by nutrient over-enrichment during at least four decades. The effluents of the Montpellier wastewater treatment plant (WWTP) represented the main nutrient input. To improve the water quality of these lagoons, this WWTP was renovated and upgraded and, since the end of 2005, its effluents have been discharged 11 km offshore into the Mediterranean (total investment €150 M). Possibilities of ecosystem restoration as part of a conservation programme were explored by a focus group of experts. Their tasks were: (i) to evaluate the impact of the reduction of the nutrient input; (ii) if necessary, to design additional measures for an active restoration programme; and (iii) to predict ecosystem trajectories for the different cases. Extension of Magnoliophyta meadows can be taken as a proxy for ecosystem restoration as they favour the increase of several fish (seahorse) and bird (ducks, swans, herons) species, albeit they represent a trade-off for greater flamingos. Additional measures for active ecosystem restoration were only recommended for the most impaired lagoon Méjean, while the least impaired lagoon Ingril is already on a trajectory of spontaneous recovery. A multiple contingent valuation considering four different management options for the Méjean lagoon was used in a pilot study based on face-to-face interviews with 159 respondents. Three levels of ecosystem restoration were expressed in terms of recovery of Magnoliophyta meadows, including their impact on emblematic fish and avifauna. These were combined with different options for access (status quo, increasing access, increasing access with measures to reduce disturbance). The results show a willingness of local populations to pay per year about €25 for the highest level of ecological restoration, while they were only willing to allocate about €5 for additional footpaths and hides.

TESTING THE JOINT ROLES OF CAREER DECISION SELF-EFFICACY AND PERSONALITY TRAITS IN THE PREDICTION OF CAREER INDECISION

Career decision-making self-efficacy and the Big Five traits of neuroticism, extraversion, and conscientiousness were examined as predictors of career indecision in a sample of 181 undergraduates. Participants completed an online survey. I predicted that the Big Five traits and career decision-making self-efficacy would (a) interrelate moderately and (b) each relate significantly and moderately to career indecision. In addition, I predicted that career decision-making self-efficacy would partially mediate the relationships between the Big Five traits and career indecision, while the Big Five traits were predicted to moderate the relationship between career decision-making self-efficacy and career indecision. Finally, I predicted that career decision-making self-efficacy would account for a greater amount of unique variance in career indecision than the Big Five traits. All predicted correlations were significant. Career decision-making self-efficacy fully mediated the relationship of Extraversion to career indecision and partially mediated the relationships of Neuroticism and Conscientiousness to career indecision. Conscientiousness was found to moderate the relationship of career decision-making self-efficacy to career indecision such that the negative relation between self-efficacy and career indecision was stronger in the presence of high conscientiousness. This study builds upon existing research on the prediction of career indecision by examining potential mediating and moderating relationships.

An Ecological Analysis of the Potential for Moss-Based Green Roof Design

Green roofs are a maturing application of best management practices for controlling urban stormwater runoff. The majority of green roofs are planted with drought resistant, higher plant species, such as the genus Sedum. However, other plant varieties, such as mosses, may be equally applicable. Residential roofs and natural terrestrial communities were sampled in both Maryland and Tennessee to determine moss community structure and species water composition. This served as a natural analog for potential green roof moss communities. During sampling, 21 species of moss were identified throughout the 37 total sites. The average percent moss cover and water composition across all roof sites was 40.7% and 38.6%, respectively and across all natural sites, 76.7% and 47.7%, respectively. Additional maximum water holding capacity procedures were completed on sedum and 19 of the 21 sampled moss species to assess their individual potential for stormwater absorption. Sedum species on average held 166% of their biomass in water, while moss species held 732%. The results of this study are used as a basis to propose moss species that will improve green roof performance.

The role of the Indian Ocean sector and sea surface salinity for prediction of the coupled Indo-Pacific system

The purpose of this dissertation is to evaluate the potential downstream influence of the Indian Ocean (IO) on El Niño/Southern Oscillation (ENSO) forecasts through the oceanic pathway of the Indonesian Throughflow (ITF), atmospheric teleconnections between the IO and Pacific, and assimilation of IO observations. Also the impact of sea surface salinity (SSS) in the Indo-Pacific region is assessed to try to address known problems with operational coupled model precipitation forecasts. The ITF normally drains warm fresh water from the Pacific reducing the mixed layer depths (MLD). A shallower MLD amplifies large-scale oceanic Kelvin/Rossby waves thus giving ~10% larger response and more realistic ENSO sea surface temperature (SST) variability compared to observed when the ITF is open. In order to isolate the impact of the IO sector atmospheric teleconnections to ENSO, experiments are contrasted that selectively couple/decouple the interannual forcing in the IO. The interannual variability of IO SST forcing is responsible for 3 month lagged widespread downwelling in the Pacific, assisted by off-equatorial curl, leading to warmer NINO3 SST anomaly and improved ENSO validation (significant from 3-9 months). Isolating the impact of observations in the IO sector using regional assimilation identifies large-scale warming in the IO that acts to intensify the easterlies of the Walker circulation and increases pervasive upwelling across the Pacific, cooling the eastern Pacific, and improving ENSO validation (r ~ 0.05, RMS~0.08C). Lastly, the positive impact of more accurate fresh water forcing is demonstrated to address inadequate precipitation forecasts in operational coupled models. Aquarius SSS assimilation improves the mixed layer density and enhances mixing, setting off upwelling that eventually cools the eastern Pacific after 6 months, counteracting the pervasive warming of most coupled models and significantly improving ENSO validation from 5-11 months. In summary, the ITF oceanic pathway, the atmospheric teleconnection, the impact of observations in the IO, and improved Indo-Pacific SSS are all responsible for ENSO forecast improvements, and so each aspect of this study contributes to a better overall understanding of ENSO. Therefore, the upstream influence of the IO should be thought of as integral to the functioning of ENSO phenomenon.

Correction of the misclassification of species in the Portuguese collection of Cucurbita pepo L. using DNA markers

In this study, the genetic variability among 130 accessions of the Portuguese germplasm collection of Cucurbita pepo L. maintained at the Banco Portugues de Germoplasma Vegetal was assessed using AFLP (amplified fragment length polymorphism) and RAPD (random amplified polymorphic DNA) techniques for the identification of a genetically diverse core group of accessions for field phenotypic analysis. The surprisingly completely different molecular patterns exhibited by multiple accessions was later confirmed in the distribution of the putative C. pepo plants into two clusters drastically separated at a very low level of genetic similarity (DICE coefficient = 0.37). Additional analyses with RAPD and ISSR (inter single sequence repeat) markers and the introduction of standard genotypes of C. maxima L. and C. moschata L. into the analyses allowed the identification of multiple accessions of the last species wrongly included in the C. pepo collection. This study is a good example of the usefulness of DNA markers in the establishment and management of plant germplasm collections.

Correction of the misclassification of species in the Portuguese collection of Cucurbita pepo L. using DNA markers

In this study, the genetic variability among 130 accessions of the Portuguese germplasm collection of Cucurbita pepo L. maintained at the Banco Portugues de Germoplasma Vegetal was assessed using AFLP (amplified fragment length polymorphism) and RAPD (random amplified polymorphic DNA) techniques for the identification of a genetically diverse core group of accessions for field phenotypic analysis. The surprisingly completely different molecular patterns exhibited by multiple accessions was later confirmed in the distribution of the putative C. pepo plants into two clusters drastically separated at a very low level of genetic similarity (DICE coefficient = 0.37). Additional analyses with RAPD and ISSR (inter single sequence repeat) markers and the introduction of standard genotypes of C. maxima L. and C. moschata L. into the analyses allowed the identification of multiple accessions of the last species wrongly included in the C. pepo collection. This study is a good example of the usefulness of DNA markers in the establishment and management of plant germplasm collections.