Particulate counter electrode system for enhanced light harvesting in dye-sensitized solar cells

A particulate counter electrode with photo scattering and redox catalytic properties is applied to dye sensitized solar cells (DSSCs) in order to improve photo conversion efficiency and simplify the assembly process. Our particulate counter electrode acts as both a photo reflecting layer and a catalyst for reduction of electrolyte. The reflective and catalytic properties of the electrode are investigated through optical and electrochemical analysis, respectively. A short circuit current density enhancement is observed in the DSSCs without the need to add an additional reflecting layer to the electrode. This leads to a simplified assembly process. (C) 2013 Optical Society of Americ

Electrochemical Investigation of High-Performance Dye-Sensitized Solar Cells Based on Molybdenum for Preparation of Counter Electrode

In order to improve the photocurrent conversion efficiency of dye-sensitized solar cells (DSSCs), we studied an alternative conductor for the counter electrode and focused on molybdenum (Mo) instead of conventional fluorine-doped tin oxide (FTO). Because Mo has a similar work function to FTO for band alignment, better formability of platinum (Pt), and a low electric resistance, using a counter electrode made of Mo instead of FTO lead to the enhancement of the catalytic reaction of the redox couple, reduce the interior resistance of the DSSCs, and prevent energy-barrier formation. Using electrical measurements under a 1-sun condition (100 mW/cm(2), AM 1.5), we determined that the fill factor (FF) and photocurrent conversion efficiency (eta) of DSSCs with a Mo electrode were respectively improved by 7.75% and 5.59% with respect to those of DSSCs with an FTO electrode. Moreover, we have investigated the origin of the improved performance through surface morphology analyses such as scanning electron microscopy and electrochemical analyses including cyclic voltammetry and impedance spectroscopy

Role of appetitive phenotype trajectory groups on child body weight during a family-based treatment for children with overweight or obesity.

ObjectiveEmerging evidence suggests that individual appetitive traits may usefully explain patterns of weight loss in behavioral weight loss treatments for children. The objective of this study was to identify trajectories of child appetitive traits and the impact on child weight changes over time.MethodsSecondary data analyses of a randomized noninferiority trial conducted between 2011 and 2015 evaluated children's appetitive traits and weight loss. Children with overweight and obesity (mean age = 10.4; mean BMI z = 2.0; 67% girls; 32% Hispanic) and their parent (mean age = 42.9; mean BMI = 31.9; 87% women; 31% Hispanic) participated in weight loss programs and completed assessments at baseline, 3, 6,12, and 24 months. Repeated assessments of child appetitive traits, including satiety responsiveness, food responsiveness and emotional eating, were used to identify parsimonious grouping of change trajectories. Linear mixed-effects models were used to identify the impact of group trajectory on child BMIz change over time.ResultsOne hundred fifty children and their parent enrolled in the study. The three-group trajectory model was the most parsimonious and included a high satiety responsive group (HighSR; 47.4%), a high food responsive group (HighFR; 34.6%), and a high emotional eating group (HighEE; 18.0%). Children in all trajectories lost weight at approximately the same rate during treatment, however, only the HighSR group maintained their weight loss during follow-ups, while the HighFR and HighEE groups regained weight (adjusted p-value < 0.05).ConclusionsDistinct trajectories of child appetitive traits were associated with differential weight loss maintenance. Identified high-risk subgroups may suggest opportunities for targeted intervention and maintenance programs

Two New Marine Sponges of the Genus Haliclona (Haplosclerida: Chalinidae) from Korea

Two new marine sponges, Haliclona (Haliclona) tonggumiensis n. sp. and H. (Reniera) sinyeoensis n. sp., in the family Chalinidae were collected from Ulleungdo Island and Gageodo Island, Korea from 2007 to 2009. Haliclona (Haliclona) tonggumiensis n. sp. is similar to H. (H.) simulans (Johnston, 1842) in shape, but the former differs in its ectosomal skeleton structure and spicules’ shape and size. The ectosomal skeleton of H. (H.) tonggumiensis n. sp. is absent, but that of H. (H.) simulans is very regularly arranged, and has tangential reticulation with oxea. The spicule shape of H. (H.) tonggumiensis n. sp. is slender, but that of H. (H.) simulans is short and cigar-shape. The new species have two sizes of oxea, but H. (H.) simulans has one size of oxea. Haliclona (Reniera) sinyeoensis n. sp. resembles H. (R.) tubifera (George and Wilson, 1919) in the growth form and choanosomal skeleton structure. However, the new species has two kinds of oxea in size, but H. (R.) tubifera has only one size

CMS endcap RPC gas gap production for upgrade

The CMS experiment will install a RE4 layer of 144 new Resistive Plate Chambers (RPCs) on the existing york YE3 at both endcap regions to trigger high momentum muons from the proton-proton interaction. In this paper, we present the detailed procedures used in the production of new RPC gas gaps adopted in the CMS upgrade. Quality assurance is enforced as ways to maintain the same quality of RPC gas gaps as the existing 432 endcap RPC chambers that have been operational since the beginning of the LHC operation

Progressive gender differences of structural brain networks in healthy adults: A longitudinal, diffusion tensor imaging study

10.1371/journal.pone.0118857PLoS ONE103e011885

Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data

Melt ponds, a common feature on Arctic sea ice, absorb most of the incoming solar radiation and have a large effect on the melting rate of sea ice, which significantly influences climate change. Therefore, it is very important to monitor melt ponds in order to better understand the sea ice-climate interaction. In this study, melt pond retrieval models were developed using the TerraSAR-X dual-polarization synthetic aperture radar (SAR) data with mid-incidence angle obtained in a summer multiyear sea ice area in the Chukchi Sea, the Western Arctic, based on two rule-based machine learning approachesdecision trees (DT) and random forest (RF)in order to derive melt pond statistics at high spatial resolution and to identify key polarimetric parameters for melt pond detection. Melt ponds, sea ice and open water were delineated from the airborne SAR images (0.3-m resolution), which were used as a reference dataset. A total of eight polarimetric parameters (HH and VV backscattering coefficients, co-polarization ratio, co-polarization phase difference, co-polarization correlation coefficient, alpha angle, entropy and anisotropy) were derived from the TerraSAR-X dual-polarization data and then used as input variables for the machine learning models. The DT and RF models could not effectively discriminate melt ponds from open water when using only the polarimetric parameters. This is because melt ponds showed similar polarimetric signatures to open water. The average and standard deviation of the polarimetric parameters based on a 15 x 15 pixel window were supplemented to the input variables in order to consider the difference between the spatial texture of melt ponds and open water. Both the DT and RF models using the polarimetric parameters and their texture features produced improved performance for the retrieval of melt ponds, and RF was superior to DT. The HH backscattering coefficient was identified as the variable contributing the most, and its spatial standard deviation was the next most contributing one to the classification of open water, sea ice and melt ponds in the RF model. The average of the co-polarization phase difference and the alpha angle in a mid-incidence angle were also identified as the important variables in the RF model. The melt pond fraction and sea ice concentration retrieved from the RF-derived melt pond map showed root mean square deviations of 2.4% and 4.9%, respectively, compared to those from the reference melt pond maps. This indicates that there is potential to accurately monitor melt ponds on multiyear sea ice in the summer season at a local scale using high-resolution dual-polarization SAR data.open

Genome-wide saturation mutagenesis of Burkholderia pseudomallei K96243 predicts essential genes and novel targets for antimicrobial development.

UNLABELLED: Burkholderia pseudomallei is the causative agent of melioidosis, an often fatal infectious disease for which there is no vaccine. B. pseudomallei is listed as a tier 1 select agent, and as current therapeutic options are limited due to its natural resistance to most antibiotics, the development of new antimicrobial therapies is imperative. To identify drug targets and better understand the complex B. pseudomallei genome, we sought a genome-wide approach to identify lethal gene targets. As B. pseudomallei has an unusually large genome spread over two chromosomes, an extensive screen was required to achieve a comprehensive analysis. Here we describe transposon-directed insertion site sequencing (TraDIS) of a library of over 10(6) transposon insertion mutants, which provides the level of genome saturation required to identify essential genes. Using this technique, we have identified a set of 505 genes that are predicted to be essential in B. pseudomallei K96243. To validate our screen, three genes predicted to be essential, pyrH, accA, and sodB, and a gene predicted to be nonessential, bpss0370, were independently investigated through the generation of conditional mutants. The conditional mutants confirmed the TraDIS predictions, showing that we have generated a list of genes predicted to be essential and demonstrating that this technique can be used to analyze complex genomes and thus be more widely applied. IMPORTANCE: Burkholderia pseudomallei is a lethal human pathogen that is considered a potential bioterrorism threat and has limited treatment options due to an unusually high natural resistance to most antibiotics. We have identified a set of genes that are required for bacterial growth and thus are excellent candidates against which to develop potential novel antibiotics. To validate our approach, we constructed four mutants in which gene expression can be turned on and off conditionally to confirm that these genes are required for the bacteria to survive