Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Continuous VM-ADCP (vessel-mounted acoustic Doppler current profiler) profiles of horizontal velocities and raw acoustic gain control data during Polarstern cruise ANT-XVIII/2

The mixing regime of the upper 180 m of a mesoscale eddy in the vicinity of the Antarctic Polar Front at 47° S and 21° E was investigated during the R.V. Polarstern cruise ANT-XVIII/2 within the scope of the iron fertilization experiment EisenEx. On the basis of hydrographic CTD and ADCP profiles we deduced the vertical diffusivity Kz from two different parameterizations. Since these parameterizations bear the character of empirical functions, based on theoretical and idealized assumptions, they were inter alia compared with Cox-number and Thorpe-scale related diffusivities deduced from microstructure measurements, which supplied the first direct insights into turbulence of this ocean region. Values of Kz in the range of 10**-4 - 10**-3 m**2/s appear as a rather robust estimate of vertical diffusivity within the seasonal pycnocline. Values in the mixed layer above are more variable in time and reach 10**-1 m**2/s during periods of strong winds. The results confirm a close agreement between the microstructure-based eddy diffusivities and eddy diffusivities calculated after the parameterization of Pacanowski and Philander [1981, Journal of Physical Oceanography 11, 1443-1451, doi:10.1175/1520-0485(1981)011<1443:POVMIN>2.0.CO;2].

Inhibitory Control is a Rate-Limiting Factor to Preschoolers' Use of Irregular Inflection

We investigated whether children’s inhibitory control is associated with their ability to produce irregular verb forms as well as learn from corrective feedback following their use of an over-regularized form. Forty-eight 3.5 to 4.5 year old children were tested on the irregular past tense and provided with adult corrective input via models of correct use or recasts of errors following ungrammatical responses. Inhibitory control was assessed with a three-item battery of tasks that required suppressing a prepotent response in favor of a non-canonical one. Results showed that inhibitory control was predictive of children’s initial production of irregular forms and not associated with their post-feedback production of irregulars. These findings show that children’s executive functioning skills may be a rate-limiting factor on their ability to produce correct forms, but might not interact with their ability to learn from input in this domain. Findings are discussed in terms of current theories of past-tense acquisition and learning from input more broadly.

Karst hazard analysis towards the development of predictive karst models for southern Ontario

An investigation into karst hazard in southern Ontario has been undertaken with the intention of leading to the development of predictive karst models for this region. The reason these are not currently feasible is a lack of sufficient karst data, though this is not entirely due to the lack of karst features. Geophysical data was collected at Lake on the Mountain, Ontario as part of this karst investigation. This data was collected in order to validate the long-standing hypothesis that Lake on the Mountain was formed from a sinkhole collapse. Sub-bottom acoustic profiling data was collected in order to image the lake bottom sediments and bedrock. Vertical bedrock features interpreted as solutionally enlarged fractures were taken as evidence for karst processes on the lake bottom. Additionally, the bedrock topography shows a narrower and more elongated basin than was previously identified, and this also lies parallel to a mapped fault system in the area. This suggests that Lake on the Mountain was formed over a fault zone which also supports the sinkhole hypothesis as it would provide groundwater pathways for karst dissolution to occur. Previous sediment cores suggest that Lake on the Mountain would have formed at some point during the Wisconsinan glaciation with glacial meltwater and glacial loading as potential contributing factors to sinkhole development. A probabilistic karst model for the state of Kentucky, USA, has been generated using the Weights of Evidence method. This model is presented as an example of the predictive capabilities of these kind of data-driven modelling techniques and to show how such models could be applied to karst in Ontario. The model was able to classify 70% of the validation dataset correctly while minimizing false positive identifications. This is moderately successful and could stand to be improved. Finally, suggestions to improving the current karst model of southern Ontario are suggested with the goal of increasing investigation into karst in Ontario and streamlining the reporting system for sinkholes, caves, and other karst features so as to improve the current Ontario karst database.

The development of dynamic CFD model of the magnetic semi-levitation of liquid metals

In the casting of reactive metals, such as titanium alloys, contamination can be prevented if there is no contact between the hot liquid metal and solid crucible. This can be achieved by containing the liquid metal by means of high frequency AC magnetic field. A water cooled current-carrying coil, surrounding the metal can then provide the required Lorentz forces, and at the same time the current induced in the metal can provide the heating required to melt it. This ‘attractive’ processing solution has however many problems, the most serious being that of the control and containment of the liquid metal envelope, which requires a balance of the gravity and induced inertia forces on the one side, and the containing Lorentz and surface tension forces on the other. To model this process requires a fully coupled dyna ic solution of the flow fields, magnetic field and heat transfer/melding process to account for. A simplified solution has been published previously providing quasi-static solutions only, by taking the irrotational ‘magnetic pressure’ term of the Lorentz force into account. The authors remedy this deficiency by modelling the full problem using CFD techniques. The salient features of these techniques are included in this paper, as space allows.

Development of a model to predict the life of pneumatic conveyor bends subject to erosive wear

The erosion processes resulting from flow of fluids (gas-solid or liquid-solid) are encountered in nature and many industrial processes. The common feature of these erosion processes is the interaction of the fluid (particle) with its boundary thus resulting in the loss of material from the surface. This type of erosion in detrimental to the equipment used in pneumatic conveying systems. The puncture of pneumatic conveyor bends in industry causes several problems. Some of which are: (1) Escape of the conveyed product causing health and dust hazard; (2) Repairing and cleaning up after punctures necessitates shutting down conveyors, which will affect the operation of the plant, thus reducing profitability. The most common occurrence of process failure in pneumatic conveying systems is when pipe sections at the bends wear away and puncture. The reason for this is particles of varying speed, shape, size and material properties strike the bend wall with greater intensity than in straight sections of the pipe. Currently available models for predicting the lifetime of bends are inaccurate (over predict by 80%. The provision of an accurate predictive method would lead to improvements in the structure of the planned maintenance programmes of processes, thus reducing unplanned shutdowns and ultimately the downtime costs associated with these unplanned shutdowns. This is the main motivation behind the current research. The paper reports on two aspects of the first phases of the study-undertaken for the current project. These are (1) Development and implementation; and (2) Testing of the modelling environment. The model framework encompasses Computational Fluid Dynamics (CFD) related engineering tools, based on Eulerian (gas) and Lagrangian (particle) approaches to represent the two distinct conveyed phases, to predict the lifetime of conveyor bends. The method attempts to account for the effect of erosion on the pipe wall via particle impacts, taking into account the angle of attack, impact velocity, shape/size and material properties of the wall and conveyed material, within a CFD framework. Only a handful of researchers use CFD as the basis of predicting the particle motion, see for example [1-4] . It is hoped that this would lead to more realistic predictions of the wear profile. Results, for two, three-dimensional test cases using the commercially available CFD PHOENICS are presented. These are reported in relation to the impact intensity and sensitivity to the inlet particle distributions.

Using electroencephalography signals to control acoustical processing

Current hearing-assistive technology performs poorly in noisy multi-talker conditions. The goal of this thesis was to establish the feasibility of using EEG to guide acoustic processing in such conditions. To attain this goal, this research developed a model via the constructive research method, relying on literature review. Several approaches have revealed improvements in the performance of hearing-assistive devices under multi-talker conditions, namely beamforming spatial filtering, model-based sparse coding shrinkage, and onset enhancement of the speech signal. Prior research has shown that electroencephalography (EEG) signals contain information that concerns whether the person is actively listening, what the listener is listening to, and where the attended sound source is. This thesis constructed a model for using EEG information to control beamforming, model-based sparse coding shrinkage, and onset enhancement of the speech signal. The purpose of this model is to propose a framework for using EEG signals to control sound processing to select a single talker in a noisy environment containing multiple talkers speaking simultaneously. On a theoretical level, the model showed that EEG can control acoustical processing. An analysis of the model identified a requirement for real-time processing and that the model inherits the computationally intensive properties of acoustical processing, although the model itself is low complexity placing a relatively small load on computational resources. A research priority is to develop a prototype that controls hearing-assistive devices with EEG. This thesis concludes highlighting challenges for future research.

MOTION - A New On-line Model for Urban Traffic Signal Control.

This paper presents MOTION, a modular on-line model for urban traffic signal control. It consists of a network and a local level and builds on enhanced traffic state estimation. Special consideration is given to the prioritization of public transit. MOTION provides possibilities for the interaction with integrated urban management systems.

Biological control of weeds in the 22 Pacific island countries and territories: current status and future prospects

Biological control of introduced weeds in the 22 Pacific island countries and territories (PICTs) began in 1911, with the lantana seed-feeding fly introduced into Fiji and New Caledonia from Hawaii. To date, a total of 62 agents have been deliberately introduced into the PICTs to control 21 weed species in 17 countries. A further two agents have spread naturally into the region. The general impact of the 36 biocontrol agents now established in the PICTs ranges from none to complete control of their target weed(s). Fiji has been most active in weed biocontrol, releasing 30 agents against 11 weed species. Papua New Guinea, Guam, and the Federated States of Micronesia have also been very active in weed biocontrol. For some weeds such as Lantana camara, agents have been released widely, and can now be found in 15 of the 21 PICTs in which the weed occurs. However, agents for other commonly found weeds, such as Sida acuta, have been released in only a few countries in which the weed is present. There are many safe and effective biocontrol agents already in the Pacific that could be utilised more widely, and highly effective agents that have been released elsewhere in the world that could be introduced following some additional host specificity testing. This paper discusses the current status of biological control efforts against introduced weeds in the 22 PICTs and reviews options that could be considered by countries wishing to initiate weed biological control programmes.

Dissecting signaling pathways that control glia migration in the developing Drosophila retina

The function of a complex nervous system relies on an intricate interaction between neurons and glial cells. However, as glial cells are generally born distant from the place where they settle, molecular cues are important to direct their migration. Glial cell migration is important in both normal development and disease, thus current research in the laboratory has been focused on dissecting regulatory events underlying that crucial process. With this purpose, the Drosophila eye imaginal disc has been used as a model. In response to neuronal photoreceptor differentiation, glial cells migrate from the CNS into the eye disc where they act to correctly wrap axons. To ensure proper development, attractive and repulsive signals must coordinate glial cell migration. Importantly, one of these signals is Bnl, a Fibroblast Growth Factor (FGF) ligand expressed by retinal progenitor cells that was suggested to act as a non-autonomous negative regulator of excessive glial cell migration (overmigration) by binding and activating the Btl receptor expressed by glial cells. Through the experimental results described in chapter 3 we gained a detailed insight into the function of bnl in eye disc growth, photoreceptor development, and glia migration. Interestingly, we did not find a direct correlation between the defects on the ongoing photoreceptors and the glia overmigration phenotype; however, bnl knockdown caused apoptosis of eye progenitor cells what was strongly correlated with glia migration defects. Glia overmigration due to Bnl down-regulation in eye progenitor cells was rescued by inhibiting the pro-apoptotic genes or caspases activity, as well as, by depleting JNK or Dp53 function in retinal progenitor cells. Thus, we suggest a cross-talk between those developmental signals in the control of glia migration at a distance. Importantly, these results suggest that Bnl does not control glial migration in the eye disc exclusively through its ability to bind and activate its receptor Btl in glial cells. We also discuss possible biological roles for the glia overmigration in the bnl knockdown background. Previous results in the lab showed an interaction between dMyc, a master regulator of tissue growth, and Dpp, a Transforming Growth Factor-β important for retinal patterning and for accurate glia migration into the eye disc. Thus, we became interested in understanding putative relationships between Bnl and dMyc. In chapter 4, we show that they positively cooperate in order to ensure proper development of the eye disc. This work highlights the importance of the FGF signaling in eye disc development and reveals a signaling network where a range of extra- and intra-cellular signals cooperate to non-autonomously control glial cell migration. Therefore, such inter-relations could be important in other Drosophila cellular contexts, as well as in vertebrate tissue development.

A decrease in dkk1, a Wnt inhibitor, contributes to placental and fetal lipid accumulation in an obesity-prone rat model

Placenta, as the sole transport mechanism between mother and fetus, links the maternal physical state and the immediate and life-long outcomes of the offspring. The present study examined the mechanisms behind the effect of maternal obesity on placental lipid accumulation and metabolism. Pregnant Obese Prone (OP) and Obese Resistant (OR) rat strains were fed a control diet throughout gestation. Placentas were collected on gestational d21 for analysis and frozen placental sections were analyzed for fat accumulation as well as β-Catenin and Dkk1 localization. Additionally, DKK1 was overexpressed in JEG3 trophoblast cells, followed by treatment with NEFA and Oil Red O stain quantification and mRNA analysis to determine the relationship between placental DKK1 and lipid accumulation. Maternal plasma and placental NEFA and TG were elevated in OP dams, and offspring of OP dams were smaller than OR. Placental Dkk1 mRNA content was 4-fold lower in OP placentas, and there was a significant increase in β-Catenin accumulation as well as mRNA content of fat transport and TG synthesis enzymes, including Ppar-delta, Fatp1, Fat/Cd36, Lipin1, and Lipin3. There was significant lipid accumulation within the decidual zones in OP but not OR placentas, and the thickness of the decidual and junctional zones was significantly smaller in OP than OR placentas. Overexpression of DKK1 in JEG3 cells decreased lipid accumulation and the mRNA content of PPAR-Delta, FATP1, FAT/CD36, LIPIN1, and LIPIN3. Our results indicate that Dkk1 may be regulating placental lipid metabolism through Wnt-mediated mechanisms. Additionally, recent studies have suggested that maternal obesity may also program early development of non-alcoholic fatty liver disease (NAFLD), rates of which have correlated with the increase in the obesity epidemic. In the current study, livers of OP offspring had significantly increased TG content (P<0.05) and lipid accumulation when compared to offspring of OR dams. Additionally, hepatic Dkk1 mRNA content was significantly decreased in OP livers when compared to OR (P<0.05), and treating H4IIECR rat hepatocyte cells with NEFA showed that Dkk1 mRNA was also decreased in NEFA-treated cells (P<0.05) that also had lipid accumulation. Chromatin Immunoprecipitation (ChIP) analysis of the Dkk1 promoter in fetal livers showed a pattern of histone modifications associated with decreased gene transcription in OP offspring, which agrees with our gene expression data. These results demonstrate that the hepatic Dkk1 gene is epigenetically regulated via histone modification in neonatal offspring in the current model of gestational obesity, and future studies will be needed to determine whether these changes contribute to excessive hepatic lipid accumulation in offspring of obese dams.

Oil spill environmental risk assessment of stationary sources in offshore zones (Innovating a mathematical model)

Nowadays, risks arising from the rapid development of oil and gas industries are significantly increasing. As a result, one of the main concerns of either industrial or environmental managers is the identification and assessment of such risks in order to develop and maintain appropriate proactive measures. Oil spill from stationary sources in offshore zones is one of the accidents resulting in several adverse impacts on marine ecosystems. Considering a site's current situation and relevant requirements and standards, risk assessment process is not only capable of recognizing the probable causes of accidents but also of estimating the probability of occurrence and the severity of consequences. In this way, results of risk assessment would help managers and decision makers create and employ proper control methods. Most of the represented models for risk assessment of oil spills are achieved on the basis of accurate data bases and analysis of historical data, but unfortunately such data bases are not accessible in most of the zones, especially in developing countries, or else they are newly established and not applicable yet. This issue reveals the necessity of using Expert Systems and Fuzzy Set Theory. By using such systems it will be possible to formulize the specialty and experience of several experts and specialists who have been working in petroliferous areas for several years. On the other hand, in developing countries often the damages to environment and environmental resources are not considered as risk assessment priorities and they are approximately under-estimated. For this reason, the proposed model in this research is specially addressing the environmental risk of oil spills from stationary sources in offshore zones.

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.

Intelligent pipeline control - a simulation study in the automotive sector

Automotive producers are aiming to make their order fulfilment processes more flexible. Opening the pipeline of planned products for dynamic allocation to dealers/ customers is a significant step to be more flexible but the behaviour of such Virtual-Build-To-Order systems are complex to predict and their performance varies significantly as product variety levels change. This study investigates the potential for intelligent control of the pipeline feed, taking into account the current status of inventory (level and mix) and of the volume and mix of unsold products in the planning pipeline, as well as the demand profile. Five ‘intelligent’ methods for selecting the next product to be planned into the production pipeline are analysed using a discrete event simulation model and compared to the unintelligent random feed. The methods are tested under two conditions, firstly when customers must be fulfilled with the exact product they request, and secondly when customers trade-off a shorter waiting time for compromise in specification. The two forms of customer behaviour have a substantial impact on the performance of the methods and there are also significant differences between the methods themselves. When the producer has an accurate model of customer demand, methods that attempt to harmonise the mix in the system to the demand distribution are superior.

Inverted decoupling internal model control for square stable multivariable time delay systems

This paper presents a new tuning methodology of the main controller of an internal model control structure for n×n stable multivariable processes with multiple time delays based on the centralized inverted decoupling structure. Independently of the system size, very simple general expressions for the controller elements are obtained. The realizability conditions are provided and the specification of the closed-loop requirements is explained. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response. The effectiveness of the method is illustrated through different simulation examples in comparison with other works.