Improving out-domain PLDA speaker verification using unsupervised inter-dataset variability compensation approach

Experimental studies have found that when the state-of-the-art probabilistic linear discriminant analysis (PLDA) speaker verification systems are trained using out-domain data, it significantly affects speaker verification performance due to the mismatch between development data and evaluation data. To overcome this problem we propose a novel unsupervised inter dataset variability (IDV) compensation approach to compensate the dataset mismatch. IDV-compensated PLDA system achieves over 10% relative improvement in EER values over out-domain PLDA system by effectively compensating the mismatch between in-domain and out-domain data.

Influence of pollutant build-up on variability in wash-off from urban road surfaces

Variability in the pollutant wash-off process is a concept which needs to be understood in-depth in order to better assess the outcomes of stormwater quality models, and thereby strengthen stormwater pollution mitigation strategies. Current knowledge about the wash-off process does not extend to a clear understanding of the influence of the initially available pollutant build-up on the variability of the pollutant wash-off load and composition. Consequently, pollutant wash-off process variability is poorly characterised in stormwater quality models, which can result in inaccurate stormwater quality predictions. Mathematical simulation of particulate wash-off from three urban road surfaces confirmed that the wash-off load of particle size fractions <150µm and >150µm after a storm event vary with the build-up of the respective particle size fractions available at the beginning of the storm event. Furthermore, pollutant load and composition associated with the initially available build-up of <150µm particles predominantly influence the variability in washed-off pollutant load and composition. The influence of the build-up of pollutants associated with >150µm particles on wash-off process variability is significant only for relatively shorter duration storm events.

Robust design and optimisation of a radial turbine within a supercritical CO2 solar Brayton Cycle

The generation of solar thermal power is dependent upon the amount of sunlight exposure,as influenced by the day-night cycle and seasonal variations. In this paper, robust optimisation is applied to the design of a power block and turbine, which is generating 30 MWe from a concentrated solar resource of 560oC. The robust approach is important to attain a high average performance (minimum efficiency change) over the expected operating ranges of temperature, speed and mass flow. The final objective function combines the turbine performance and efficiency weighted by the off-design performance. The resulting robust optimisation methodology as presented in the paper gives further information that greatly aids in the design of non-classical power blocks through considering off-design conditions and resultant performance.

The solar capital: Canberra, clean tech, and climate change

There has been an increasing focus upon the role of cities and local government in respect of action upon climate change...

Mapping the regional influence of genetics on brain structure variability - A Tensor-Based Morphometry study

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

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.

Incorporating process variability into stormwater quality modelling

Process variability in pollutant build-up and wash-off generates inherent uncertainty that affects the outcomes of stormwater quality models. Poor characterisation of process variability constrains the accurate accounting of the uncertainty associated with pollutant processes. This acts as a significant limitation to effective decision making in relation to stormwater pollution mitigation. The study undertaken developed three theoretical scenarios based on research findings that variations in particle size fractions <150µm and >150µm during pollutant build-up and wash-off primarily determine the variability associated with these processes. These scenarios, which combine pollutant build-up and wash-off processes that takes place on a continuous timeline, are able to explain process variability under different field conditions. Given the variability characteristics of a specific build-up or wash-off event, the theoretical scenarios help to infer the variability characteristics of the associated pollutant process that follows. Mathematical formulation of the theoretical scenarios enables the incorporation of variability characteristics of pollutant build-up and wash-off processes in stormwater quality models. The research study outcomes will contribute to the quantitative assessment of uncertainty as an integral part of the interpretation of stormwater quality modelling outcomes.

Rainfall variability drives interannual variation in N2O emissions from a humid, subtropical pasture

Variations in interannual rainfall totals can lead to large uncertainties in annual N2O emission budget estimates from short term field studies. The interannual variation in nitrous oxide (N2O) emissions from a subtropical pasture in Queensland, Australia, was examined using continuous measurements of automated chambers over 2 consecutive years. Nitrous oxide emissions were highest during the summer months and were highly episodic, related more to the size and distribution of rain events than soil water content. Over 48% of the total N2O emitted was lost in just 16% of measurement days. Interannual variation in annual N2O estimates was high, with cumulative emissions increasing with decreasing rainfall. Cumulative emissions averaged 1826.7 ± 199.9 g N2O-N ha−1 yr−1 over the two year period, though emissions from 2008 (2148 ± 273 g N2O-N ha−1 yr−1) were 42% higher than 2007 (1504 ± 126 g N2O-N ha−1 yr−1). This increase in annual emissions coincided with almost half of the summer precipitation from 2007 to 2008. Emissions dynamics were chiefly driven by the distribution and size of rain events which varied on a seasonal and annual basis. Sampling frequency effects on cumulative N2O flux estimation were assessed using a jackknife technique to inform future manual sampling campaigns. Test subsets of the daily measured data were generated for the pasture and two adjacent land-uses (rainforest and lychee orchard) by selecting measured flux values at regular time intervals ranging from 1 to 30 days. Errors associated with weekly sampling were up to 34% of the sub-daily mean and were highly biased towards overestimation if strategically sampled following rain events. Sampling time of day also played a critical role. Morning sampling best represented the 24 hour mean in the pasture, whereas sampling at noon proved the most accurate in the shaded rainforest and lychee orchard.

Bias-dependent effects in planar perovskite solar cells based on CH3NH3PbI3−xClx films

A unique bias-dependent phenomenon in CH3NH3PbI3−xClx based planar perovskite solar cells has been demonstrated, in which the photovoltaic parameters derived from the current–voltage (I–V) curves are highly dependent on the initial positive bias of the I–V measurement. In FTO/CH3NH3PbI3−xClx/Au devices, the open-circuit voltage and short-circuit current increased by ca. 337.5% and 281.9% respectively, by simply increasing the initial bias from 0.5 V to 2.5 V.

An efficient hole transport material composite based on poly(3-hexylthiophene) and bamboo-structured carbon nanotubes for high performance perovskite solar cells

In this work, we have developed a new efficient hole transport material (HTM) composite based on poly(3- hexylthiophene) (P3HT) and bamboo-structured carbon nanotubes (BCNs) for CH3NH3PbI3 (MAPbI3) based perovskite solar cells. Compared to pristine P3HT, it is found that the crystallinity of P3HT was significantly improved by addition of BCNs, which led to over one order of magnitude higher conductivity for the composite containing 1–2 wt% BCNs in P3HT. In the meantime, the interfacial charge transfer between the MAPbI3 light absorbing layer and the HTM composite layer based on P3HT/BCNs was two-fold faster than pristine P3HT. More importantly, the HTM film with a superior morphological structure consisting of closely compact large grains was achieved with the composite containing 1 wt% BCNs in P3HT. The study by electrochemical impedance spectroscopy has confirmed that the electron recombination in the solar cells was reduced nearly ten-fold with the addition of 1 wt% carbon nanotubes in the HTM composite. Owing to the superior HTM film morphology and the significantly reduced charge recombination, the energy conversion efficiency of the perovskite solar cells increased from 3.6% for pristine P3HT to 8.3% for P3HT/(1 wt% BCNs) with a significantly enhanced open circuit voltage (Voc) and fill factor (FF). The findings of this work are important for development of new HTM for high performance perovskite solar cells.

Designs and architectures for the next generation of organic solar cells

Organic solar cells show great promise as an economically and environmentally friendly technology to utilize solar energy because of their simple fabrication processes and minimal material usage. However, new innovations and breakthroughs are needed for organic solar cell technology to become competitive in the future. This article reviews research efforts and accomplishments focusing on three issues: power conversion efficiency, device stability and processability for mass production, followed by an outlook for optimizing OSC performance through device engineering and new architecture designs to realize next generation organic solar cells.

Optimization of organic solar cells with thin film Au as anode

Optical transmittance and conductivity for thin metallic films, such as Au, are two inversely related and extremely important parameters for its application in organic photovoltaics as the front electrode. We report our findings on how these parameters have been optimized to attain maximum possible efficiencies by fabricating organic solar cells with thin Au film anodes of differing optical transmittances and consequently due to scaling at the nanolevel, varying electrical conductivities. There was an extraordinary improvement in the overall solar cell efficiency (to the order of 49%) when the Au thin film transmittance was increased from 38% to 54%. Surface morphologies of these thin films also have an effect on the critical parameters including, Voc, Jsc and FF.

Enhanced electron lifetime of CdSe/CdS quantum dot (QD) sensitized solar cells using ZnSe core–shell structure with efficient regeneration of quantum Ddots

Research on development of efficient passivation materials for high performance and stable quantum dot sensitized solar cells (QDSCs) is highly important. While ZnS is one of the most widely used passivation material in QDSCs, an alternative material based on ZnSe which was deposited on CdS/CdSe/TiO2 photoanode to form a semi-core/shell structure has been found to be more efficient in terms of reducing electron recombination in QDSCs in this work. It has been found that the solar cell efficiency was improved from 1.86% for ZnSe0 (without coating) to 3.99% using 2 layers of ZnSe coating (ZnSe2) deposited by successive ionic layer adsorption and reaction (SILAR) method. The short circuit current density (Jsc) increased nearly 1-fold (from 7.25 mA/cm2 to13.4 mA/cm2), and the open circuit voltage (Voc) was enhanced by 100 mV using ZnSe2 passivation layer compared to ZnSe0. Studies on the light harvesting efficiency (ηLHE) and the absorbed photon-to-current conversion efficiency (APCE) have revealed that the ZnSe coating layer caused the enhanced ηLHE at wavelength beyond 500 nm and a significant increase of the APCE over the spectrum 400−550 nm. A nearly 100% APCE was obtained with ZnSe2, indicating the excellent charge injection and collection process in the device. The investigation on charge transport and recombination of the device has indicated that the enhanced electron collection efficiency and reduced electron recombination should be responsible for the improved Jsc and Voc of the QDSCs. The effective electron lifetime of the device with ZnSe2 was nearly 6 times higher than ZnSe0 while the electron diffusion coefficient was largely unaffected by the coating. Study on the regeneration of QDs after photoinduced excitation has indicated that the hole transport from QDs to the reduced species (S2−) in electrolyte was very efficient even when the QDs were coated with a thick ZnSe shell (three layers). For comparison, ZnS coated CdS/CdSe sensitized solar cell with optimum shell thickness was also fabricated, which generated a lower energy conversion efficiency (η = 3.43%) than the ZnSe based QDSC counterpart due to a lower Voc and FF. This study suggests that ZnSe may be a more efficient passivation layer than ZnS, which is attributed to the type II energy band alignment of the core (CdS/CdSe quantum dots) and passivation shell (ZnSe) structure, leading to more efficient electron−hole separation and slower electron recombination.

Vertically stacked photovoltaic and thermal solar cell

According to some embodiments, the present invention provides a novel photovoltaic solar cell system from photovoltaic modules that are vertically arrayed in a stack format using thin film semiconductors selected from among org. and inorg. thin film semiconductors. The stack cells may be cells that are produced in a planar manner, then vertically oriented in an angular form, also termed herein tilted, to maximize the light capturing aspects. The use of a stack configuration system as described herein allows for the use of a variety of electrode materials, such as transparent materials or semitransparent metals. Light concn. can be achieved by using fresnel lens, parabolic mirrors or derivs. of such structures. The light capturing can be controlled by being reflected back and forth in the photovoltaic system until significant quantities of the resonant light is absorbed. Light that passes to the end and can be reflected back through the device by beveling or capping the end of the device with a different refractive index material, or alternatively using a reflective surface. The contacting between stacked cells can be done in series or parallel. According to some embodiments, the present invention uses a concentrator architecture where the light is channeled into the cells that contain thermal fluid channels (using a transparent fluid such as water) to absorb and hence reduce the thermal energy generation.

Conjoint use of Dibenzosilole and Indan-1,3-dione Functionalities to Prepare an Efficient Non-Fullerene Acceptor for Solution-Processable Bulk-Heterojunction Solar Cells

A solution-processable, non-fullerene electron acceptor, 2,2′-(((5,5-dioctyl-5 H-dibenzo[b,d]silole-3,7-diyl)bis(thiophene-5,2-diyl))bis(methanylylidene))bis(1 H-indene-1,3(2 H)-dione) (called N5) comprised of dibenzosilole and 1,3-indanedione building blocks was designed, synthesized, and fully characterized. N5 is highly soluble in various organic solvents, has high thermal stability, and has energy levels matching those of archetypal donor poly(3-hexylthiophene). Solution-processable, bulk-heterojunction solar cells afforded promising power conversion efficiency of 2.76 % when N5 was used as a non-fullerene electron acceptor along with the conventional donor polymer poly(3-hexylthiophene). As per our knowledge, the material reported herein is the first example in the literature where synchronous use of such building blocks is demonstrated in the design an efficient, non-fullerene acceptor.