All form of activity in a building is in need for a sound platform to be able to operate. The performance of concrete floor in industrial spaces is of importance because there are greater demands on industrial concrete floor.  By making sure that the necessary recommendation regarding casting an industrial concrete floor is followed, the risk for failure is reduced. The Swedish Concrete Association (2008) recommends a w/c ratio of approximately 0.55 for industrial floors. This would result in a concrete strength class of C30/37 with an abrasive resistance adequate for most industrial floors. From an economical perspective an approach for concrete rehabilitation is the bonded overlay, which has been used for many years and has the intension to extend the life of structural concrete slabs. For concrete overlay having a matching material to the substrate is the main recommendation, in addition in a fully bonded overlay to the substrate there is less risk for cracking and edge lifting. From a mechanical perspective a crack develops when the stresses in concrete exceeds the tensile strength. Shrinkage and creep of concrete in both overlays and industrial floors are important factors that contribute in development of cracks which have considerable effect on failure of the structure; therefore it is useful to find an accurate prediction model to predict shrinkage and creep. The literature study that has been carried out in this thesis is mainly about shrinkage, creep, industrial floor, overlays and tensile stress prediction. In addition the following calculation models for prediction of creep and shrinkage of concrete have been reviewed in this paper: Eurocode 2, fib Model Code 2010, ACI 209R-92, Swedish code BBK04 and Swedish concrete manual Material. In order to study the differences between the mentioned models two example cases for calculation of shrinkage and creep in industrial floor and  bonded overlay with the mentioned methods have been carried out, also the tensile stress development in bonded overlay has been calculated according to a method proposed by Prof. Silfwerbrand (1997). Since it was not possible to consider all types of concrete and conditions which will affect the outcome, only one type of concrete C30/37 with w/c ratio of 0.55 for industrial floor and w/c ratio of 0.40 for overlay is taken as an example in this thesis. Some of these methods take only a few factors into consideration; however the others are more detailed and treat numerous factors. The simple methods such as BBK04 or the graph in Eurocode 2 for calculating the creep coefficient can be used in the lack of existence of sufficient input parameters to be able to roughly estimate the final value. The predicted shrinkage did differ by using different models, however the final value of the creep coefficient was quiet similar regardless of the used model. There are some important parameters such as ambient relative humidity, age at loading, duration of drying and duration of loading which should be included in predicting models since these parameters affect shrinkage and creep considerably. Also aggregate type has an important role in both creep and shrinkage; however aggregate type (modulus of elasticity of aggregate) was not included in any of the studied models. Choosing a factor according to the type of aggregate might be helpful for better prediction.

With the recent growth and wide availability of heterogeneous wireless access technologies, inter-vehicle communication systems are expected to culminate in integrating various wireless standards for the next generation of connected and autonomous vehicles. The role of 5G-enabled vehicular networks has become increasingly important, as current Internet clients and providers have urged robustness and effectiveness in digital services over wireless networks to cope with the latest advances in wireless mobile communication. However, to enable 5G wireless technologies' dense diversity, seamless and reliable wireless communication protocols need to be thoroughly investigated in vehicular networks. 5G-enabled vehicular networks applications and services such as routing, mobility management, and service discovery protocols can integrate mobility-based prediction techniques to elevate those applications' performance with various vehicles, applications, and network measurements. In this thesis, we propose a novel suite of 5G-enabled smart mobility prediction and management schemes and design a roadmap guide to mobility-based predictions for intelligent vehicular network applications and protocols. We present a thorough review and classification of vehicular network architectures and components, in addition to mobility management schemes, benchmarks advantages, and drawbacks. Moreover, multiple mobility-based schemes are proposed, in which vehicles' mobility is managed through the utilization of machine learning prediction and probability analysis techniques. We propose a novel predictive mobility management protocol that incorporates a new networks' infrastructure discovery and selection scheme. Next, we design an efficient handover trigger scheme based on time-series prediction and a novel online neural network-based next roadside unit prediction protocol for smart vehicular networks. Then, we propose an original adaptive predictive location management technique that utilizes vehicle movement projections to estimate the link lifetime between vehicles and infrastructure units, followed by an efficient movement-based collision detection scheme and infrastructure units localization strategy. Last but not least, the proposed techniques have been extensively evaluated and compared to several benchmark schemes with various networks' parameters and environments. Results showed the high potentials of empowering vehicular networks' mobility-based protocols with the vehicles' future projections and the prediction of the network's status.

No description available.

No description available.

Steroid hormones confer biological activity to effluents of wastewater treatment plants (WWTPs). The occurrence of estrogen and androgen hormones in addition to their biological effects in the environment have been widely studied and there is a growing consensus that mixtures of steroid hormones; albeit at low ng L-1concentrations, lead to endocrine disruption in some aquatic organisms. These mixtures may also be influenced by the contributions of synthetic estrogens and androgens, which may display either additive or antagonistic activity. In order to measure the ability of a single compound, or complex mixture to influence the function of estrogenic or androgenic signaling pathways bioassays are used. Most commonly, these tests are in vitro and may quantify the ability of a compound to bind and/or (in) activate the steroid receptors. Two commonly used bioassays for estrogenicity detection are the Yeast Estrogen Screen (YES) and the E-Screen assay. The Yeast Androgen Screen (YAS) is commonly used to measure androgenic activity. The yeast (Saccharomyces cerevisiae) are genetically transformed and express either the human Estrogen Receptor (ER) or Androgen Receptor (AR), and contain Estrogen or Androgen Responsive Elements (ERE/ARE) and Lac Z reporting plasmids. Once the receptors become activated, beta-Galactosidase is secreted into the assay medium and the level of beta-Galactosidase secretion relates to the estrogenicity or androgenicity of the sample tested. Due to its simplicity and the moderately fast assay time, the YES and YAS are commonly used assays in the analysis of complex mixtures to identify the major contributors to both estrogenic and (anti)-androgenic activity in environmental water. The effect directed approach combines both chemical methods and bioassays in a chemical fractionation scheme that is directed by the bioassays. In order to confirm the identity of the key contributors, it is important to compare the biological activities that are calculated from the concentrations of the identified hormones (given their individual biological responses) and the total biological activity measured through the use of bioassays, Equation 1. RPsCs+ RP2C2+ ...+RPnCn = IEQ (1) where Cn is the concentration of the nth mixture constituent, RP is the relative (estrogenic or androgenic) potential of the nth mixture constituent as determined in the bioassay, and IEQ is the estimated total induction equivalent concentration of the mixture by chemical methods. Cs and RPs represents the concentration and relative potential of a standard compound respectively. Agreement between the chemically and biologically derived IEQs means that the major contributors to the biological effect have been successfully identified. However, the biological assays measure the contribution of additive, antagonistic and synergistic activity in the mixture; therefore, the biologically derived IEQs represent the net biological activity. Chemical methods are unable to predict these interactions and as such the result of the concentration addition (CA) approach (Equation 1) is often inconclusive and suggestive of interacting components. An interaction model that can estimate the net biological activity of a mixture from the concentrations of individual mixture constituents (chemical methods) is thus necessary. An interaction model that combines both the relative potential (RP) as well as the interaction index (γ) in a parameter called aRP was developed. The aRP is defined by Equation 2 and is used similarly to the CA approach, Equation 3. aRP = interaction index-1RP (2) aRPsCs+ aRP2C2+ ...+aRPnCn = IEQ (3) The aRP can be calculated for any nth mixture constituent by measuring the degree to which the mixture components altered the activity of the standard and assessing those changes as a function of mixture ratios. The interaction method was validated using a mixture of testosterone, with two anti- androgens, di-n-butyl phthalate, and bisphenol A in the YAS. Mixtures of 17ß;-estradiol, estriol, 17α-dihydroequilin and di-n-butyl phthalate were evaluated in the YES assay. Using Equation 3 the net estrogenic and androgenic activity of the mixtures was estimated. There was a significant improvement over the CA based approach in Equation 1. Overall, in 24 out of 32 mixtures tested there was no significant difference between the aRP and observed responses. Large percent errors were observed in the CA model, particularly when the proportion of antagonists was high as the CA model tended to over-predict the responses. On the contrary, only two aRP model predictions exceeded 50% error. Risk assessors should use the CA model with caution as it could over-predict biological responses and an alternative approach such as the aRP model could be used. In this regard, a database of aRP values for identified antagonistic/synergistic compounds could be assembled and estimations of biological activity could be made using these aRP values. The aRP interaction model could also be used to provide fundamental understanding to the behavior of the constituents in a complex mixture. Although the interaction model presented may account for possible deviations from additivity in environmental mixtures, predictions of mixture effects may be complicated by matrix interferences. In this regard, a sensitive bioassay; such as the E-Screen, which is capable of detecting concentrations as low as 0.27 ng L-1 of 17β-estradiol equivalents is beneficial. However, one major drawback to the E-Screen assay is the 6-day analysis time. In order to maintain the sensitivity of the assay and reduce the analysis time, Fourier Transform Infra-red Imaging Spectroscopy (FT-IRIS) was used to probe the bio-molecular level events that occur in single cells prior to a detectable response in cellular proliferation. The investigation revealed that changes occur on the sub-cellular level at 48-hours after incubation which are comparable to the 6 day E-Screen responses (Pearson R = 0.978). The FT-IRIS response appears to be due to the increase in mucins which are known to play a role in cellular signaling and proliferation. The EC50 values for the E-screen and FT-IRIS assay were 2.29 and 2.56 ppt respectively, indicating that the molecular changes, which are observed at the single cell level using FT-IRIS, are reflective of physiological changes that are observed as the cell population responds to 17ß-estradiol. The study indicates that sophisticated imaging and microscopy techniques such as FT-IRIS may play a role in environmental bio-analytical methods. / Civil Engineering

Background Our objective was to identify and validate clinical and continuity of care variables associated with Oral anticoagulant (OAC)-related adverse events within 30 days of hospital discharge amongst seniors. Methods and Analysis This was a population-based retrospective cohort study of all adults aged 66 years or older who were discharged from hospital on an OAC from September 2010 to March 2015 in Ontario, Canada. The primary outcome was a composite of the time to first hospitalization or Emergency Department visit for a hemorrhage or thromboembolic event or mortality within 30 days of hospital discharge. A Cox proportional hazards model was used to determine the association between the composite outcome and a set of prespecified covariates. A split sample method was applied to validate the final model. Results We included 120 721 Ontario seniors of which 5423 suffered one of the primary adverse events. Patients discharged on a direct-acting oral anticoagulant (DOAC); dispensed the same OAC in the past 12 months; who had a history of a thromboembolic event; had a recent joint replacement or major surgery; had a cardiologist, hematologist or orthopedic surgeon as compared to a family medicine physician as the physician prescribing the OAC at discharge had a lower risk for the composite outcome. Though continuity of care was a variable in the final multivariate Cox model, it was not significant. The Cox model was stable with acceptable discrimination but poor goodness-of-fit. Conclusion In this study, we found that continuity of care as measured by outpatient follow-up in the 7 days post-discharge was not significantly associated with the composite outcome. Further exploration to improve the current model’s calibration and interpretation are required. / Thesis / Master of Science (MSc) / Background Oral anticoagulants (OACs) are associated with serious adverse events, with high rates immediately post-hospitalization. We aimed to identify and validate clinical and continuity of care variables in seniors discharged from hospital on an OAC, which are associated with OAC-related harm in the short-term high-risk period following hospitalization. Methods Data from administrative health databases in Ontario were used to identify and validate risk factors associated with time to first OAC-related serious events including hospitalization or emergency department visit for a bleeding or thromboembolic event, and mortality. Cox proportional hazards model and split-sample methods were utilized. Results We included 120,721 seniors of which 5423 suffered one of the primary events. Patient-, physician- and index hospitalization-characteristics were all associated with time to the composite outcome. Though continuity of care risk factor was part of the final model, it was not a significant predictor for the outcome. Conclusion Exploration of this model through sensitivity analysis is required.

Concrete experiences volume changes throughout its service life. When loaded, concrete experiences an instantaneous recoverable elastic deformation and a slow inelastic deformation called creep. Creep of concrete is composed of two components, basic creep, or deformation under load without moisture loss and drying creep, or deformation under drying conditions only. Deformation of concrete in the absence of applied load is often called shrinkage. The deformation due to creep is attributed to the movement of water between the different phases of the concrete. When an external load is applied, it changes the attraction forces between the cement gel particles. This change in the forces causes an imbalance in the attractive and disjoining forces. However, the imbalance is gradually eliminated by the transfer of moisture into the pores in cases of compression, and away from the pores in cases of tension. Designs typically use one of the two code models to estimate creep and shrinkage strain in concrete, ACI 209 model recommended by the American Concrete Institute or the CEB 90 Eurocode 2 model recommended by the Euro-International Committee. The ASSHTO LRFD is based on the ACI 209 model. Three other models are the B3 model, developed by Bazant; the GZ model, developed by Gardner; and the SAK model developed by Sakata. The development of concrete performance specifications that limit the amount of compressive creep of concrete mixtures used by the Virginia Department of Transportation, specifically concrete mixtures used for prestressed members (A-5 Concrete) were assessed, along with determining the accuracy and precision of the creep models presented in the literature. The CEB 90 Eurocode 2 model for creep and shrinkage is the most precise and accurate predictor. The total strain for the VDOT portland cement concrete mixtures discussed in this study were found to be between 1200 ± 110 microstrain at 28 days, and 1600 ± 110 microstrain at 97 days, at a five percent significant level. / Master of Science

Prestressed concrete structural members camber upwards or downwards depending upon the location of application of prestress force. Identical members do not camber equally due to variability of the factors influencing it. Differential camber in the beams, if significant, results in excessively tall haunches or girder top flange extending into the bottom of the slab. For adjacent members like deck bulb-tees and box girders that are to be transversely post-tensioned the differential camber causes problems during the fit up process. This variation is undesirable and hinders the smooth progress of construction work if not properly accounted for at the design stage. Various factors influence camber and camber growth in prestressed members. Some of the factors are concrete strength and modulus, concrete creep and shrinkage properties, curing conditions, maturity of concrete at release of prestress force, initial strand stress, climatic conditions in storage and length of time in storage. Combinations of these variables result in variation of camber of otherwise similar beams at the time they are erected. One way to increase the precision of camber estimation is to use Monte Carlo simulation based upon the randomized parameters affecting the camber and camber growth. In this method, the parameters, in the form of a probability distribution function, are combined and passed through a deterministic model resulting in camber and camber growth prediction with narrowed probability bounds as compared to single definite value given by most contemporary methods. This outcome gives the expected range of cambers for a given girder design. After determining the expected range of camber, the ultimate goal is to provide guidelines for using unbonded monostrands for camber adjustment. / Master of Science

Corrosion of reinforcing steel in concrete is a significant problem around the world. In the United States, there are approximately 600,000 bridges. From those bridges 24% are considered structurally deficient or functionally obsolete based on the latest, December 2010, statistic from the Federal Highway Administration (FHWA). Mainly, this is due to chloride attack present in deicing salts which causes the reinforcing steel to corrode. Different solutions have been developed and used in practice to delay and prevent corrosion initiation. The purpose of this research is to investigate the influence of corrosion on the failure mechanism that occurred on an Interstate 81 bridge deck. After 17 years in service, a 3ft x3ft closure pour section punched through. It was part of the left wheel path of the south bound right lane of the bridge deck. The bridge deck was replaced in 1992 as part of a bridge rehabilitation project, epoxy coated reinforcement were used as the reinforcing steel. Four slabs from the bridge deck, containing the closure, were removed and transported to the Virginia Tech Structures and Materials Research Laboratory for further evaluation. Also, three lab cast slabs were fabricated as part of the assessment program. Corrosion evaluation and concrete shrinkage characterization were conducted in this research. The corrosion evaluation study included visual observation, clear concrete cover depth, concrete resistivity using single point resistivity, half-cell potential, and linear polarization using the 3LP device. Shrinkage characteristics were conducted on the lab cast slabs only, which consisted of monitoring shrinkage behavior of the specimens for 180 days and comparison of the data with five different shrinkage models. Based on the research results, guidance for assessment of other bridge decks with similar conditions will be constructed to avoid similar types of failures in the future. / Master of Science

No / Conflicting rankings corresponding to alternative performance criteria and measures are mostly reported in the mono-criterion evaluation of competing distress prediction models (DPMs). To overcome this issue, this study extends the application of the expert system to corporate credit risk and distress prediction through proposing a Multi-criteria Decision Aid (MCDA), namely PROMETHEE II, which provides a multi-criteria evaluation of competing DPMs. In addition, using data on Chinese firms listed on Shanghai and Shenzhen stock exchanges, we perform an exhaustive comparative analysis of the most popular DPMs; namely, statistical, artificial intelligence and machine learning models under both mono-criterion and multi-criteria frameworks. Further, we address two prevailing research questions; namely, "which DPM performs better in predicting distress?" and "will training models with corporate governance indicators (CGIs) enhance the performance of models?”; and discuss our findings. Our multi-criteria ranking suggests that non-parametric DPMs outperform parametric ones, where random forest and bagging CART are among the best machine learning DPMs. Further, models fed with CGIs as features outperform those fed without CGIs.