Studies on Rat Ovarian Receptors for Lutropin (Luteinizing Hormone): Applicability of radioimmunoassay to measure lutropin bound to receptors.

Measurement of receptor-bound unlabelled physiologically active lutropin (luteinizing hormone, LH) was possible by a modified radioimmunoassay. The conventional radioimmunoassayconducted at 4°C was inadequate, whereas the modified assay performed at 37'C could measure receptor-bound lutropin. The radioimmunoassay at 37'C takes only 36h for completion compared with 5-7 days at 4°C. The sensitivity and range of dose-response curves are, however, unaltered. The validity of the technique was established by a number of criteria.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Impact of hysterectomy or levonorgestrel-releasing intrauterine system on ovarian function, bone, and sexual functioning in menorrhagic patients

The `VuoKKo` trial consisted of 236 women referred and randomised due to menorrhagia in the five university hospitals of Finland between November 1994 and November 1997. Of these women, 117 were randomised to hysterectomy and 119 to use levonorgestrel-releasing intrauterine system (LNG-IUS) to treat this complaint. Their follow-up visits took place six and twelve months after the treatment and five years after the randomisation. The first aim in the primary trial was quality-of-life and monetary aspects, and secondly in the present study to compare ovarian function, bone mineral density (BMD) and sexual functioning after these two treatment options. Ovarian function seemed to decrease after hysterectomy, demonstrated by increased hot flashes and serum follicle-stimulating hormone concentrations twelve months after the operation. Such an increase was not seen among LNG-IUS users. The pulsatility index of intraovarian arteries measured by two-dimensional ultrasound decreased in the hysterectomy group, but not in the LNG-IUS group. The decrease in serum inhibin B concentrations was similar in both groups, while ovarian artery circulation remained unchanged. BMD of the women measured by dual x-ray absorptiometry (DXA) at the lumbar spine and femoral neck at baseline and at five years after treatment showed BMD decrease at the lumbar spine among hysterectomised women, but not among LNG-IUS users. In both groups, BMD at the femoral neck had decreased. Differences between the groups were not, however, significant. Sexual functioning assessed by McCoy s sexual scale showed that sexual satisfaction as well as intercourse frequency had increased and sexual problems decreased among hysterectomised women six months after treatment. Among LNG-IUS users, sexual satisfaction and sexual problems remained unchanged. Although, the two groups did not differ in terms of sexual satisfaction or sexual problems at one-year and five-year follow-ups, LNG-IUS users were less satisfied with their partners than hysterectomised women.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.

CAE-based prediction of projectile residual velocity for impact on single and multi-layered metallic armour plates

The present, paper deals with the CAE-based study Of impact of jacketed projectiles on single- and multi-layered metal armour plates using LS-DYNA. The validation of finite element modelling procedure is mainly based on the mesh convergence study using both shell and solid elements for representing single-layered mild steel target plates. It, is shown that the proper choice of mesh density and the strain rate-dependent material properties are essential for all accurate prediction of projectile residual velocity. The modelling requirements are initially arrived at by correlating against test residual velocities for single-layered mild steel plates of different depths at impact velocities in the ran.-c of approximately 800-870 m/s. The efficacy of correlation is adjudged, in terms of a 'correlation index', defined in the paper: for which values close to unity are desirable. The experience gained for single-layered plates is next; used in simulating projectile impacts on multi-layered mild steel target plates and once again a high degree of correlation with experimental residual velocities is observed. The study is repeated for single- and multi-layered aluminium target plates with a similar level of success in test residual velocity prediction. TO the authors' best knowledge, the present comprehensive study shows in particular for the first time that, with a. proper modelling approach, LS-DYNA can be used with a great degree of confidence in designing perforation-resistant single and multi-layered metallic armour plates.

Long-term effects of physical activity level on changes in healthy body mass index over 12 years in young adult women

Objectives To examine the effects of overall level and timing of physical activity (PA) on changes from a healthy body mass index (BMI) category over 12 years in young adult women. Patients and Methods Participants in the Australian Longitudinal Study on Women's Health (younger cohort, born 1973-1978) completed surveys between 2000 (age 22-27 years) and 2012 (age 34-39 years). Physical activity was measured in 2000, 2003, 2006, and 2009 and was categorized as very low, low, active, or very active at each survey, and a cumulative PA score for this 9-year period was created. Logistic regression was used to examine relationships between PA accumulated across all surveys (cumulative PA model) and PA at each survey (critical periods PA model), with change in BMI category (from healthy to overweight or healthy to obese) from 2000 to 2012. Results In women with a healthy BMI in 2000, there were clear dose-response relationships between accumulated PA and transition to overweight (P=.03) and obesity (P<.01) between 2000 and 2012. The critical periods analysis indicated that very active levels of PA at the 2006 survey (when the women were 28-33 years old) and active or very active PA at the 2009 survey (age 31-36 years) were most protective against transitioning to overweight and obesity. Conclusion These findings confirm that maintenance of very high PA levels throughout young adulthood will significantly reduce the risk of becoming overweight or obese. There seems to be a critical period for maintaining high levels of activity at the life stage when many women face competing demands of caring for infants and young children.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Robust prediction of residual velocities and ballistic limits of projectiles for impact on thin aluminium plates

This paper deals with the simulation-driven study of the impact of hardened steel projectiles on thin aluminium target plates using explicit finite element analysis as implemented in LS-DYNA. The evaluation of finite element modelling includes a comprehensive mesh convergence study using shell elements for representing target plates and the solid element-based representation of ogivalnosed projectiles. A user-friendly automatic contact detection algorithm is used for capturing interaction between the projectile and the target plate. It is shown that the proper choice of mesh density and strain rate-dependent material properties is crucial as these parameters significantly affect the computed residual velocity. The efficacy of correlation with experimental data is adjudged in terms of a 'correlation index' defined in the present study for which values close to unity are desirable.By simulating laboratory impact tests on thin aluminium plates carried out by earlier investigators, extremely good prediction of experimental ballistic limits has been observed with correlation indices approaching unity. Additional simulation-based parametric studies have been carried out and results consistent with test data have been obtained. The simulation procedures followed in the present study can be applied with confidence in designing thin aluminium armour plates for protection against low calibre projectiles.

Ability of human chorionic gonadotropin beta-subunit to inhibit the steroidogenic response to lutropin

Ability of the beta-subunit of human chorionic gonadotropin to inhibit the response to lutropin (luteinizing hormone, LH) was tested in the immature rat ovarian system and pregnant-mare-serum-gonadotropin-primed rat ovarian system with progesterone production being used as the response. Human chorionic gonadotropin beta-subunit was found to inhibit human and ovine lutropin-stimulated progesterone production. At a constant dose of lutropin, inhibition was dependent on the concentration of beta-subunit. When concentration of the beta-subunit was kept constant at 5.0 microgram/ml and the concentration of lutropin was varied, the inhibition was maximum at the saturating concentration of the native hormone. The alpha-subunit of the human chorionic gonadotropin did not inhibit the response to lutropin. The lutropin/beta-subunit ratio required to produce an inhibition of response was much lower than that required to bring about an observable inhibition of binding.

Gonadotropin regulation of rat ovarian lysosomes: Existence of a hormone specific dual control mechanism

Gonadotropic hormones PMSG (15 IU/rat), FSH (3 mgrg/rat), LH (9 mgrg/rat) and hCG (3 mgrg/rat) were shown to decrease the free cytosolic lysosomal enzymes during the acute phase of hormone action in rat ovaries. When isolated cells from such rats were analyzed for the cathepsin-D activity, the granulosa cells of the ovary showed a reduction in the free as well as in the total lysosomal enzyme activities in response to FSH/PMSG; the stromal and thecal compartment of the ovary showed a reduction only in the free activity in response to hCG/PMSG. The results suggest the presence of two distinct, target cell specific, mechanisms by which the lysosmal activity of the ovary is regulated by gonadotropins.

Correlation of helicopter rotor aeroelastic response with HART-II wind tunnel test data

Purpose - This paper aims to validate a comprehensive aeroelastic analysis for a helicopter rotor with the higher harmonic control aeroacoustic rotor test (HART-II) wind tunnel test data. Design/methodology/approach - Aeroelastic analysis of helicopter rotor with elastic blades based on finite element method in space and time and capable of considering higher harmonic control inputs is carried out. Moderate deflection and coriolis nonlinearities are included in the analysis. The rotor aerodynamics are represented using free wake and unsteady aerodynamic models. Findings - Good correlation between analysis and HART-II wind tunnel test data is obtained for blade natural frequencies across a range of rotating speeds. The basic physics of the blade mode shapes are also well captured. In particular, the fundamental flap, lag and torsion modes compare very well. The blade response compares well with HART-II result and other high-fidelity aeroelastic code predictions for flap and torsion mode. For the lead-lag response, the present analysis prediction is somewhat better than other aeroelastic analyses. Research limitations/implications - Predicted blade response trend with higher harmonic pitch control agreed well with the wind tunnel test data, but usually contained a constant offset in the mean values of lead-lag and elastic torsion response. Improvements in the modeling of the aerodynamic environment around the rotor can help reduce this gap between the experimental and numerical results. Practical implications - Correlation of predicted aeroelastic response with wind tunnel test data is a vital step towards validating any helicopter aeroelastic analysis. Such efforts lend confidence in using the numerical analysis to understand the actual physical behavior of the helicopter system. Also, validated numerical analyses can take the place of time-consuming and expensive wind tunnel tests during the initial stage of the design process. Originality/value - While the basic physics appears to be well captured by the aeroelastic analysis, there is need for improvement in the aerodynamic modeling which appears to be the source of the gap between numerical predictions and HART-II wind tunnel experiments.

Analytical prediction of break-out noise from a reactive rectangular plenum with four flexible walls

This paper describes an analytical calculation of break-out noise from a rectangular plenum with four flexible walls by incorporating three-dimensional effects along with the acoustical and structural wave coupling phenomena. The breakout noise from rectangular plenums is important and the coupling between acoustic waves within the plenum and structural waves in the flexible plenum walls plays a critical role in prediction of the transverse transmission loss. The first step in breakout noise prediction is to calculate the inside plenum pressure field and the normal flexible plenum wall vibration by using an impedance-mobility approach, which results in a compact matrix formulation. In the impedance-mobility compact matrix (IMCM) approach, it is presumed that the coupled response can be described in terms of finite sets of the uncoupled acoustic subsystem and the structural subsystem. The flexible walls of the plenum are modeled as an unfolded plate to calculate natural frequencies and mode shapes of the uncoupled structural subsystem. The second step is to calculate the radiated sound power from the flexible walls using Kirchhoff-Helmholtz (KH) integral formulation. Analytical results are validated with finite element and boundary element (FEM-BEM) numerical models. (C) 2010 Acoustical Society of America. DOI: 10.1121/1.3463801]

Methods and applications for improving parameter prediction models for stand structures in Finland

This thesis report attempts to improve the models for predicting forest stand structure for practical use, e.g. forest management planning (FMP) purposes in Finland. Comparisons were made between Weibull and Johnson s SB distribution and alternative regression estimation methods. Data used for preliminary studies was local but the final models were based on representative data. Models were validated mainly in terms of bias and RMSE in the main stand characteristics (e.g. volume) using independent data. The bivariate SBB distribution model was used to mimic realistic variations in tree dimensions by including within-diameter-class height variation. Using the traditional method, diameter distribution with the expected height resulted in reduced height variation, whereas the alternative bivariate method utilized the error-term of the height model. The lack of models for FMP was covered to some extent by the models for peatland and juvenile stands. The validation of these models showed that the more sophisticated regression estimation methods provided slightly improved accuracy. A flexible prediction and application for stand structure consisted of seemingly unrelated regression models for eight stand characteristics, the parameters of three optional distributions and Näslund s height curve. The cross-model covariance structure was used for linear prediction application, in which the expected values of the models were calibrated with the known stand characteristics. This provided a framework to validate the optional distributions and the optional set of stand characteristics. Height distribution is recommended for the earliest state of stands because of its continuous feature. From the mean height of about 4 m, Weibull dbh-frequency distribution is recommended in young stands if the input variables consist of arithmetic stand characteristics. In advanced stands, basal area-dbh distribution models are recommended. Näslund s height curve proved useful. Some efficient transformations of stand characteristics are introduced, e.g. the shape index, which combined the basal area, the stem number and the median diameter. Shape index enabled SB model for peatland stands to detect large variation in stand densities. This model also demonstrated reasonable behaviour for stands in mineral soils.