Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.

Gene network effects on brain microstructure and intellectual performance identified in 472 twins

A major challenge in neuroscience is finding which genes affect brain integrity, connectivity, and intellectual function. Discovering influential genes holds vast promise for neuroscience, but typical genome-wide searches assess approximately one million genetic variants one-by-one, leading to intractable false positive rates, even with vast samples of subjects. Even more intractable is the question of which genes interact and how they work together to affect brain connectivity. Here, we report a novel approach that discovers which genes contribute to brain wiring and fiber integrity at all pairs of points in a brain scan. We studied genetic correlations between thousands of points in human brain images from 472 twins and their nontwin siblings (mean age: 23.7 2.1 SD years; 193 male/279 female).Wecombined clustering with genome-wide scanning to find brain systems withcommongenetic determination.Wethen filtered the image in a new way to boost power to find causal genes. Using network analysis, we found a network of genes that affect brain wiring in healthy young adults. Our new strategy makes it computationally more tractable to discover genes that affect brain integrity. The gene network showed small-world and scale-free topologies, suggesting efficiency in genetic interactions and resilience to network disruption. Genetic variants at hubs of the network influence intellectual performance by modulating associations between performance intelligence quotient and the integrity of major white matter tracts, such as the callosal genu and splenium, cingulum, optic radiations, and the superior longitudinal fasciculus.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects

Deficits in lentiform nucleus volume and morphometry are implicated in a number of genetically influenced disorders, including Parkinson's disease, schizophrenia, and ADHD. Here we performed genome-wide searches to discover common genetic variants associated with differences in lentiform nucleus volume in human populations. We assessed structural MRI scans of the brain in two large genotyped samples: the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 706) and the Queensland Twin Imaging Study (QTIM; N = 639). Statistics of association from each cohort were combined meta-analytically using a fixed-effects model to boost power and to reduce the prevalence of false positive findings. We identified a number of associations in and around the flavin-containing monooxygenase (FMO) gene cluster. The most highly associated SNP, rs1795240, was located in the FMO3 gene; after meta-analysis, it showed genome-wide significant evidence of association with lentiform nucleus volume (PMA = 4. 79 × 10-8). This commonly-carried genetic variant accounted for 2. 68 % and 0. 84 % of the trait variability in the ADNI and QTIM samples, respectively, even though the QTIM sample was on average 50 years younger. Pathway enrichment analysis revealed significant contributions of this gene to the cytochrome P450 pathway, which is involved in metabolizing numerous therapeutic drugs for pain, seizures, mania, depression, anxiety, and psychosis. The genetic variants we identified provide replicated, genome-wide significant evidence for the FMO gene cluster's involvement in lentiform nucleus volume differences in human populations.

Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure

Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

Incentivizing innovation: A review of the Brazilian federal innovation support programs

Innovation is the transformation of knowledge of any kind into new products or services in the market. Its importance as a production factor is widely acknowledged. In the age of the knowledge-based economy innovation became critical for any company or even country to compete globally. Many countries are encouraging innovation through various mechanisms, and one of the most widely used is the provision of special incentives for innovation. This paper investigates incentive systems for the growth of technology companies as a strategy to promote knowledge-based economic development. As for the case investigations the study focuses on an emerging economy, Brazil. The research is based upon the available literature, best practices, government policy and review of incentive systems. The findings provide insights from the case study in a country context and some lessons learned for other countries using incentive systems to boost the innovation capabilities of their technology companies.

Novel window coupler for the detection of partial discharge activity in GIS

This work investigates the feasibly in using a low noise “C” Band block down-converter as a Ultra High Frequency window coupler for the detection of partial discharge activity from free conducting practices and a protrusion on the high voltage conductor in Gas Insulated Switchgear. The investigated window coupler has a better sensitivity than the internal Ultra High Frequency couplers fitted to the system. The investigated window couplers however are sensitive to changes in the frequency content of the discharge signals and appear to be less sensitive to negative discharges signals produced by a protrusion than the positive discharge signals.

Advances in solid-catalytic and non-catalytic technologies for biodiesel production

The insecure supply of fossil fuel coerces the scientific society to keep a vision to boost investments in the renewable energy sector. Among the many renewable fuels currently available around the world, biodiesel offers an immediate impact in our energy. In fact, a huge interest in related research indicates a promising future for the biodiesel technology. Heterogeneous catalyzed production of biodiesel has emerged as a preferred route as it is environmentally benign needs no water washing and product separation is much easier. The number of well-defined catalyst complexes that are able to catalyze transesterification reactions efficiently has been significantly expanded in recent years. The activity of catalysts, specifically in application to solid acid/base catalyst in transesterification reaction depends on their structure, strength of basicity/acidity, surface area as well as the stability of catalyst. There are various process intensification technologies based on the use of alternate energy sources such as ultrasound and microwave. The latest advances in research and development related to biodiesel production is represented by non-catalytic supercritical method and focussed exclusively on these processes as forthcoming transesterification processes. The latest developments in this field featuring highly active catalyst complexes are outlined in this review. The knowledge of more extensive research on advances in biofuels will allow a deeper insight into the mechanism of these technologies toward meeting the critical energy challenges in future.

Application of power electronics in improving power quality and supply efficiency of AC traction networks

Major advances in power electronics during recent years have prompted considerable interest within the traction community. The capability of new technologies to reduce the AC railway networks' effect on power quality and improve their supply efficiency is expected to significantly decrease the cost of electric rail supply systems. Of particular interest are Static Frequency Converter (SFC), Rail Power Conditioner (RPC), High Voltage Direct Current (HVDC) and Energy Storage Systems (ESS) solutions. Substantial impacts on future feasibility of railway electrification are anticipated. Aurizon, Australia's largest heavy haul railway operator, has recently commissioned the world's first 50Hz/50Hz SFC installation and is currently investigating SFC, RPC, HVDC and ESS solutions. This paper presents a summary of current and emerging technologies with a particular focus on the potential techno-economic benefits.

Microgrid frequency control using multiple battery energy storage system (BESSs)

The work is a report of research on using multiple inverters of Battery Energy Storage Systems with angle droop controllers to share real power in an isolated micro grid system consisting of inertia based Distributed Generation units and variable load. The proposed angle droop control method helps to balance the supply and demand in the micro grid autonomous mode through charging and discharging of the Battery Energy Storage Systems while ensuring that the state of charge of the storage devices is within safe operating conditions. The proposed method is also studied for its effectiveness for frequency control. The proposed control system is verified and its performance validated with simulation software MATLAB/SIMULINK.

Age and leadership: The moderating role of legacy beliefs

Age and age-related motivations have been neglected in leadership research. This study examined the moderating influence of legacy beliefs on the relationships between age and transformational, transactional, and passive-avoidant leadership behaviors. Legacy beliefs involve individuals' convictions about whether they and their actions will be remembered, have an enduring influence, and leave something behind after death. It was expected that at higher ages, low legacy beliefs impede transformational and transactional leadership behaviors and boost passive-avoidant leadership behaviors. One hundred and six university professors, between 30 and 70 years old, provided ratings of their legacy beliefs; each professor's leadership behaviors were evaluated by one of his or her employees. Results confirmed the assumptions for overall transformational leadership and its charisma subdimension as well as for overall transactional leadership and its active management-by-exception subdimension but not for passive-avoidant leadership.

Phase accumulated carrier pulse width modulation

An alternative approach to digital PWM generation uses an accumulator rather than a counter to generate the carrier. This offers several advantages. The resolution and gain of the pulse width modulator remain constant regardless of the module clock frequency and PWM output frequency. The PWM resolution also becomes fixed at the register width. Even at high PWM frequencies, the resolution remains high when averaged over a number of PWM cycles. An inherent dithering of the PWM waveform introduced over successive cycles blurs the switching spectra without distorting the modulating waveform. The technique also lends itself to easily generating several phase shifted PWM waveforms suitable for multilevel converter modulation. Several example waveforms generated using both simulation and FPGA hardware are presented.

Novel modulation strategy for a CLC resonant dual active bridge

This paper proposes a novel modulation strategy for a phase controlled Capacitor-Inductor-Capacitor (CLC) Resonant Dual Active Bridge (RDAB). The proposed modulation strategy improves the soft turn-on, Zero-Current-Switching (ZCS) and Zero-Voltage-Switching (ZVS) range of the converter while only minimally increasing the required reactive currents in the ac link. A mathematical analysis of the proposed modulation scheme is presented along with a theoretical loss comparison between several modulation strategies. The proposed modulation strategy was implemented and the experimental results are presented.