Prenatal Vitamin D deficiency induces an early and more severe experimental autoimmune encephalomyelitis in the second generation

In a previous study, we demonstrated that mouse adult F(1) offspring, exposed to a vitamin d deficiency during pregnancy, developed a less severe and delayed Experimental Autoimmune Encephalomyelitis (EAE), when compared with control offspring. We then wondered whether a similar response was observed in the subsequent generation. To answer this question, we assessed F(2) females whose F(1) parents (males or females) were vitamin d-deprived when developing in the uterus of F(0) females. Unexpectedly, we observed that the vitamin d deficiency affecting the F(0) pregnant mice induced a precocious and more severe EAE in the F(2) generation. This paradoxical finding led us to assess its implications for the epidemiology of Multiple Sclerosis (MS) in humans. Using the REFGENSEP database for MS trios (the patient and his/her parents), we collected the parents' dates of birth and assessed a potential season of birth effect that could potentially be indicative of the vitamin d status of the pregnant grandmothers. A trend for a reduced number of births in the Fall for the parents of MS patients was observed but statistical significance was not reached. Further well powered studies are warranted to validate the latter finding.

Stability and convergence of a finite volume method for the space fractional advection-dispersion equation

We consider the space fractional advection–dispersion equation, which is obtained from the classical advection–diffusion equation by replacing the spatial derivatives with a generalised derivative of fractional order. We derive a finite volume method that utilises fractionally-shifted Grünwald formulae for the discretisation of the fractional derivative, to numerically solve the equation on a finite domain with homogeneous Dirichlet boundary conditions. We prove that the method is stable and convergent when coupled with an implicit timestepping strategy. Results of numerical experiments are presented that support the theoretical analysis.

Brokering innovation to better leverage R&D investment

What is the contribution of innovation brokers in leveraging research and development (R&D) investment to enhance industry-wide capabilities? The case of the Australian Cooperative Research Centre for Construction Innovation (CRC CI) is considered in the context of motivating supply chain firms to improve their organizational capabilities in order to acquire, assimilate, transfer and exploit R&D outcomes to their advantage, and to create broader industry and national benefits. A previous audit and analysis has shown an increase in business R&D investment since 2001. The role of the CRC CI in contributing to growth in the absorptive capacity of the Australian construction industry as a whole is illustrated through two programmes: digital modelling building information modelling (BIM) and construction site safety. Numerous positive outcomes in productivity, quality, improved safety and competitiveness were achieved between 2001 and 2009.

Recruitment and results of a pilot trial of vitamin D supplementation in the general population of Australia

Context: The benefits of high serum levels of 25-hydroxyvitamin D [25(OH)D] are unclear. Trials are needed to establish an appropriate evidence base. Objective: We plan to conduct a large-scale trial of vitamin D supplementation for the reduction of cancer incidence and overall mortality and report here the methods and results of a pilot trial established to inform its design. Design: Pilot D-Health was a randomized trial carried out in a general community setting with 12 months intervention and follow-up. Participants: Participants were 60- to 84-yr-old residents of one of the four eastern Australian states who did not have any vitamin D-related disorders and who were not taking more than 400 IU supplementary vitamin D per day. A total of 644 participants were randomized, and 615 completed the study (two persons withdrew because of nonserious adverse events). Interventions: The interventions were monthly doses of placebo or 30,000 or 60,000 IU vitamin D3. Main Outcomes: The main outcomes were the recruitment rate and changes in serum 25(OH)D. Results: Ten percent of those approached were recruited. At baseline, the mean 25(OH)D was 42 nmol/liter in all three study arms. The mean change in 25(OH)D in the placebo group was 0.12 nmol/liter, compared with changes of 22 and 36 nmol/liter in the 30,000- and 60,000-IU groups, respectively. Conclusions: The D-Health pilot has shown that a large trial is feasible in Australia and that a dose of 2000 IU/d will be needed to ensure that a large proportion of the population reaches the target serum 25(OH)D level. Copyright © 2012 by The Endocrine Society.

Power system stability enhancement in a deregulated environment using FACTS devices

In deregulated versions of free-market electricity, producers will be free to send power along other utilities. The price of power strongly depends and fluctuates according to mutual benefit index of both supplier and consumer. In such a situation, strong interaction among utilities may cause instabilities in the system. As the frequency of market-based dispatch increases market forces tend to destabilize the stable system dynamics depending on the value of Ks/τλ(market dependent parameter) ratio. This tends to destabilize the coupled dynamics. The implementation of TCSC can effectively damp the inter area modes of oscillations of the coupled market system.

Small signal stability analysis of a DFIG based wind power system with tuned damping controller under super/sub-synchronous mode of operation

This paper focuses on the super/sub-synchronous operation of the doubly fed induction generator (DFIG) system. The impact of a damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using bacteria foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The robustness issue of the damping controller is also investigated

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

Numerical solutions of stochastic differential equations – implementation and stability issues

Stochastic differential equations (SDEs) arise fi om physical systems where the parameters describing the system can only be estimated or are subject to noise. There has been much work done recently on developing numerical methods for solving SDEs. This paper will focus on stability issues and variable stepsize implementation techniques for numerically solving SDEs effectively.

Factors affecting the stability analysis of earth dam slopes subjected to reservoir drawdown

The drawdown of reservoirs can significantly affect the stability of upstream slopes of earth dams. This is due to the removal of the balancing hydraulic forces acting on the dams and the undrained condition within the upstream slope soils. In such scenarios, the stability of the slopes can be influenced by a range of factors including drawdown rates, slope inclination and soil properties. This paper investigates the effects of drawdown rate, saturated hydraulic conductivity and unsaturated shear strength of dam materials on the stability of the upstream slope of an earth dam. In this study, the analysis of pore-water pressure changes within the upstream slope during reservoir drawdown was coupled with the slope stability analysis using the general limit equilibrium method. The results of the analysis suggested that a decrease in the reservoir water level caused the stability of the upstream slope to decrease. The dam embankment constructed with highly permeable soil was found to be more stable during drawdown scenarios, compared to others. Further, lower drawdown rates resulted in a higher safety factor for the upstream slope. Also, the safety factor of the slope calculated using saturated shear strength properties of the dam materials was slightly higher than that calculated using unsaturated shear strength properties. In general, for all the scenarios analysed, the lowest safety factor was found to be at the reservoir water level of about 2/3 of drawdown regime.

Preliminary study on the stability of highly sensitive fiber Bragg grating temperature sensors [对高灵敏光纤光栅温度传感器的稳定性的初探]

As a novel sensitive element and due to its advantages of immunity to electrical interference, distributed measurement, etc., fiber Bragg grating (FBG) has been researched widely. To realize the substitution of high accurate electronic temperature sensors, high sensitive FBG temperature sensors can be made by taking advantage of its characters of being sensitive to both temperature and strain. Although there are reports about high sensitive FBG temperature sensors, however, few about their stability have been done. We manufactured a high sensitive FBG temperature sensor, and put it together with an average FBG temperature sensor and an electronic crystal temperature sensor into a stainless steel container filled by water to observe the room temperature change. By comparing their results in two weeks, we have found out that: although the high sensitive FBG temperature sensor is in much better agreement with the electronic crystal sensor than the average FBG sensor is, it has occurred some small drifts. Because the drifts appeared in the process of further pulling the FBG, it might be a result of the slip of the FBG fixing points. This contributes some good experiences to the application of FBG in high accuracy temperature measurement.

An in-vitro 3-D cell culture model for studying pathomechanisms in AMD

Purpose To develop a novel 3-D cell culture model with the view to studying the pathomechanisms underlying the development of age-related macular degeneration (AMD). Our central hypothesis is that the silk structural protein fibroin used in conjunction with cultured human cells can be used to mimic the structural relationships between the RPE and choriocapillaris in health and disease. Methods Co-cultures of human RPE cells (ARPE-19 cells grown in Miller’s medium) and microvascular endothelial cells (HMEC-1 cells grown in endothelial culture medium) were established on opposing sides of a synthetic Bruch’s membrane (3 microns thick) constructed from B mori silk fibroin. Cell attachment was facilitated by pre-coating the fibroin membrane with vitronectin (for ARPE-19 cells) and gelatin (for HMEC-1 cells) respectively. The effects of tropoelastin on attachment of ARPE-19 cells was also examined. Barrier function was examined by measurement of trans-epithelial resistance (TER) using a voltohmmeter (EVOM-2). The phagocytic activity of the synthetic RPE was tested using vitronectin-coated microspheres (2 micron diameter FluoSpheres). In some cultures, membrane defects were created by puncturing within a 24 G needle. The architecture of the synthetic tissue before and after wounding was examined by confocal microscopy after staining for ZO-1 and F-actin. Results The RPE layer of the 3D model developed a cobblestoned morphology (validated by staining for ZO-1 and F-actin), displayed barrier function (validated by measurement of TER) and demonstrated cytoplasmic uptake of vitronectin-coated microspheres. Attachment of ARPE-19 cells to fibroin was unaffected by tropoelastin. Microvascular endothelial cells attached well to the gelatin-coated surface of the fibroin membrane and remained physically separated from the overlaying RPE layer. The fibroin membranes were amenable to puncturing without collapse thus providing the opportunity to study transmembrane migration of the endothelial cells. Conclusions Synthetic Bruch’s membranes constructed from silk fibroin, vitronectin and gelatin, support the co-cultivation of RPE cells and microvascular endothelial cells. The resulting RPE layer displays functions similar to that of native RPE and the entire tri-layered structure displays potential to be used as an in vitro model of choroidal neovascularization.

Fast exact nearest neighbour matching in high dimensions using d-D Sort

Data structures such as k-D trees and hierarchical k-means trees perform very well in approximate k nearest neighbour matching, but are only marginally more effective than linear search when performing exact matching in high-dimensional image descriptor data. This paper presents several improvements to linear search that allows it to outperform existing methods and recommends two approaches to exact matching. The first method reduces the number of operations by evaluating the distance measure in order of significance of the query dimensions and terminating when the partial distance exceeds the search threshold. This method does not require preprocessing and significantly outperforms existing methods. The second method improves query speed further by presorting the data using a data structure called d-D sort. The order information is used as a priority queue to reduce the time taken to find the exact match and to restrict the range of data searched. Construction of the d-D sort structure is very simple to implement, does not require any parameter tuning, and requires significantly less time than the best-performing tree structure, and data can be added to the structure relatively efficiently.

An ensemble method for predicting subnuclear localizations from primary protein structures

Background Predicting protein subnuclear localization is a challenging problem. Some previous works based on non-sequence information including Gene Ontology annotations and kernel fusion have respective limitations. The aim of this work is twofold: one is to propose a novel individual feature extraction method; another is to develop an ensemble method to improve prediction performance using comprehensive information represented in the form of high dimensional feature vector obtained by 11 feature extraction methods. Methodology/Principal Findings A novel two-stage multiclass support vector machine is proposed to predict protein subnuclear localizations. It only considers those feature extraction methods based on amino acid classifications and physicochemical properties. In order to speed up our system, an automatic search method for the kernel parameter is used. The prediction performance of our method is evaluated on four datasets: Lei dataset, multi-localization dataset, SNL9 dataset and a new independent dataset. The overall accuracy of prediction for 6 localizations on Lei dataset is 75.2% and that for 9 localizations on SNL9 dataset is 72.1% in the leave-one-out cross validation, 71.7% for the multi-localization dataset and 69.8% for the new independent dataset, respectively. Comparisons with those existing methods show that our method performs better for both single-localization and multi-localization proteins and achieves more balanced sensitivities and specificities on large-size and small-size subcellular localizations. The overall accuracy improvements are 4.0% and 4.7% for single-localization proteins and 6.5% for multi-localization proteins. The reliability and stability of our classification model are further confirmed by permutation analysis. Conclusions It can be concluded that our method is effective and valuable for predicting protein subnuclear localizations. A web server has been designed to implement the proposed method. It is freely available at http://bioinformatics.awowshop.com/snlpr​ed_page.php.

Studies on self-assembly hydrothermal fabrication and thermal stability of Chromium oxyhydroxide nanomaterials synthesised from Chromium oxide colloids

Chromium oxyhydroxide nanomaterials with narrow size-distribution were synthesised through a simple hydrothermal method. Experimental conditions, such as reaction duration and pH values of the precipitation process and hydrothermal treatment played important roles in determining the nature of the final product chromium oxyhydroxide nanomaterials. The effect of these synthesis parameters were studied with the assistance of X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy and thermogravimetric analyses. This research has developed a controllable synthesis of Chromium oxyhydroxide nanomaterials from Chromium oxide colloids.