Synthesis of self-light-scattering wrinkle structured ZnO photoanode by sol-gel method for dye-sensitized solar cells

A special morphological zinc oxide (ZnO) photoanode for dye-sensitized solar cell was fabricated by simple sol-gel drop casting technique. This film shows a wrinkled structure resembling the roots of banyan tree, which acts as an effective self scattering layer for harvesting more visible light and offers an easy transport path for photo-injected electrons. These ZnO electrode of low thickness (similar to 5 mu m) gained an enhanced short-circuit current density of 6.15 mA/cm(2), open-circuit voltage of 0.67 V, fill factor of 0.47 and overall conversion efficiency of 1.97 % under 1 sun illumination. This shows a high conversion efficiency and a superior performance than that of ZnO nanoparticle-based photoanode (eta similar to 1.13 %) of high thickness (similar to 8 mu m).

Tree-Structured Stick Breaking Processes for Hierarchical Data

Many data are naturally modeled by an unobserved hierarchical structure. In this paper we propose a flexible nonparametric prior over unknown data hierarchies. The approach uses nested stick-breaking processes to allow for trees of unbounded width and depth, where data can live at any node and are infinitely exchangeable. One can view our model as providing infinite mixtures where the components have a dependency structure corresponding to an evolutionary diffusion down a tree. By using a stick-breaking approach, we can apply Markov chain Monte Carlo methods based on slice sampling to perform Bayesian inference and simulate from the posterior distribution on trees. We apply our method to hierarchical clustering of images and topic modeling of text data.

Investigation of polymorphism by PCR-RFLP method in Cobia fish Rachycentron canadum in the Persian Gulf and Oman Sea

Cobia is a native fish species in Iranian waters in the Persian Gulf and Sea of Oman and has a good internal and foreign market. This fish is a fast growing species and for this reason Iranian Fisheries is considering to go for it culture practices. To go for any utilization such as fishing from wild stocks or culture activities, needs a better understanding of its peculiarities and genetic characteristics of its natural resources. Therefore, this project was discribed and conducted. In this investigation, cuts 2 or 3 cm of fin tissue of  specimen of Cobia obtained from Sistan and Bluchestan, Hormozgan, Bushehr and Khuzestan water provinces, were collected. DNA was extracted by Phenol-chlorophorm method and produced PCR product in length of 1060 and 1450 base pair of two mitochondrial genes COI and NADH2. Using 13 cutting enzymes (4 enzymes were subscriber for both of genes), 205 base pair (from 2510 base pair, equal with %3.8 from gene regains) were directly investigated. But binding patterns of enzymatic digestion of PCR products of both COI and ND genes from electrophoresis were monomorph in all samples and no polymorphism was observed. This may be attributed to the unsuitable choice of COI and ND2 genes for showing of intra specific divergence. But in general non-existence of genetic diversity or noticeable decrease of that among individuals has been reported in regions were fish migration exist and they can freely move between two regions. Therefore, non-observation of polymorphism in the study area might be the case and indicates represents the area. On the other hand, some scientists believe that the distributions of populations in different regions are greatly affected by environmental and physical and ecological factors. Althoug Cobia is a migratory fish, but with regard to the fact that the environmental conditions are different (specially temperature and salinity) between east and west of Persian Gulf and Oman sea, there is a possibility that different genetic groups of this species exist in the regions. Of course It is clear that using more samples and enzymes from other genetically regions could produce better results. Since none of the two investigated genes didn’t show genetic divergence or polymorphism amongst the individuals of one region or between different regions, therefore, statistic analysis for estimating of haplotype diversity or nucleotide diversity and drawing of relationship tree among individuals using available softwares was not possible.

DT-MRI data visualisation using the dual tree Complex Wavelet transform

In this paper a novel visualisation method for diffusion tensor MRI datasets is introduced. This is based on the use of Complex Wavelets in order to produce "stripy" textures which depict the anisotropic component of the diffusion tensors. Grey-scale pixel intensity is used to show the isotropic component. This paper also discusses enhancements of the technique for 3D visualisation. © 2004 IEEE.

Making a shallow network deep: Conversion of a boosting classifier into a decision tree by boolean optimisation

This paper presents a novel way to speed up the evaluation time of a boosting classifier. We make a shallow (flat) network deep (hierarchical) by growing a tree from decision regions of a given boosting classifier. The tree provides many short paths for speeding up while preserving the reasonably smooth decision regions of the boosting classifier for good generalisation. For converting a boosting classifier into a decision tree, we formulate a Boolean optimization problem, which has been previously studied for circuit design but limited to a small number of binary variables. In this work, a novel optimisation method is proposed for, firstly, several tens of variables i.e. weak-learners of a boosting classifier, and then any larger number of weak-learners by using a two-stage cascade. Experiments on the synthetic and face image data sets show that the obtained tree achieves a significant speed up both over a standard boosting classifier and the Fast-exit-a previously described method for speeding-up boosting classification, at the same accuracy. The proposed method as a general meta-algorithm is also useful for a boosting cascade, where it speeds up individual stage classifiers by different gains. The proposed method is further demonstrated for fast-moving object tracking and segmentation problems. © 2011 Springer Science+Business Media, LLC.

Multiple classifier boosting and tree-structured classifiers

Visual recognition problems often involve classification of myriads of pixels, across scales, to locate objects of interest in an image or to segment images according to object classes. The requirement for high speed and accuracy makes the problems very challenging and has motivated studies on efficient classification algorithms. A novel multi-classifier boosting algorithm is proposed to tackle the multimodal problems by simultaneously clustering samples and boosting classifiers in Section 2. The method is extended into an online version for object tracking in Section 3. Section 4 presents a tree-structured classifier, called Super tree, to further speed up the classification time of a standard boosting classifier. The proposed methods are demonstrated for object detection, tracking and segmentation tasks. © 2013 Springer-Verlag Berlin Heidelberg.

Dense active appearance models using a bounded diameter minimum spanning tree

We present a method for producing dense Active Appearance Models (AAMs), suitable for video-realistic synthesis. To this end we estimate a joint alignment of all training images using a set of pairwise registrations and ensure that these pairwise registrations are only calculated between similar images. This is achieved by defining a graph on the image set whose edge weights correspond to registration errors and computing a bounded diameter minimum spanning tree (BDMST). Dense optical flow is used to compute pairwise registration and we introduce a flow refinement method to align small scale texture. Once registration between training images has been established we propose a method to add vertices to the AAM in a way that minimises error between the observed flow fields and a flow field interpolated between the AAM mesh points. We demonstrate a significant improvement in model compactness using the proposed method and show it dealing with cases that are problematic for current state-of-the-art approaches.

Spectral properties of a double-quantum-dot structure: A causal Green's function approach

Spectral properties of a double quantum dot (QD) structure are studied by a causal Green's function (GF) approach. The double QD system is modeled by an Anderson-type Hamiltonian in which both the intra- and interdot Coulomb interactions are taken into account. The GF's are derived by an equation-of-motion method and the real-space renormalization-group technique. The numerical results show that the average occupation number of electrons in the QD exhibits staircase features and the local density of states depends appreciably on the electron occupation of the dot.

An improved PCR method for direct identification of Porphyra (Bangiales, Rhodophyta) using conchocelis based on a RUBISCO intergenic spacer

An improved method of PCR in which the small segment of conchocelis is amplified directly without DNA extraction was used to amplify a RUBISCO intergenic spacer DNA fragment from nine species of red algal genus Porphyra (Bangiales, Rhodophyta), including Porphyra yezoensis (Jiangsu, China), P. haitanensis (Fujian, China), P. oligospermatangia (Qingdao, China), P. katadai (Qingdao, China), P. tenera (Qingdao, China), P. suborboculata (Fujian, China), P. pseudolinearis (Kogendo, Korea), P. linearis (Devon, England), and P. fallax (Seattle, USA). Standard PCR and the method developed here were both conducted using primers specific for the RUBISCO spacer region, after which the two PCR products were sequenced. The sequencing data of the amplicons obtained using both methods were identical, suggesting that the improved PCR method was functional. These findings indicate that the method developed here may be useful for the rapid identification of species of Porphyra in a germplasm bank. In addition, a phylogenetic tree was constructed using the RUBISCO spacer and partial rbcS sequence, and the results were in concordant with possible alternative phylogenies based on traditional morphological taxonomic characteristics, indicating that the RUBISCO spacer is a useful region for phylogenetic studies.

A hyper-heuristic ensemble method for static job-shop scheduling.

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyperheuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

Retrieval by Shape Population: An Index Tree Approach

Based on our previous work in deformable shape model-based object detection, a new method is proposed that uses index trees for organizing shape features to support content-based retrieval applications. In the proposed strategy, different shape feature sets can be used in index trees constructed for object detection and shape similarity comparison respectively. There is a direct correspondence between the two shape feature sets. As a result, application-specific features can be obtained efficiently for shape-based retrieval after object detection. A novel approach is proposed that allows retrieval of images based on the population distribution of deformed shapes in each image. Experiments testing these new approaches have been conducted using an image database that contains blood cell micrographs. The precision vs. recall performance measure shows that our method is superior to previous methods.

Bivariate distribution modeling with tree diameter and height data

The Logit-Logistic (LL), Johnson's SB, and the Beta (GBD) are flexible four-parameter probability distribution models in terms of the (skewness-kurtosis) region covered, and each has been used for modeling tree diameter distributions in forest stands. This article compares bivariate forms of these models in terms of their adequacy in representing empirical diameter-height distributions from 102 sample plots. Four bivariate models are compared: SBB, the natural, well-known, and much-used bivariate generalization of SB; the bivariate distributions with LL, SB, and Beta as marginals, constructed using Plackett's method (LL-2P, etc.). All models are fitted using maximum likelihood, and their goodness-of-fits are compared using minus log-likelihood (equivalent to Akaike's Information Criterion, the AIC). The performance ranking in this case study was SBB, LL-2P, GBD-2P, and SB-2P

A randomized controlled trial of tea tree oil (5%) body wash versus standard body wash to prevent colonization with methicillin-resistant Staphylococcus aureus (MRSA) in critically ill adults: research protocol

Background
Over the past ten years MRSA has become endemic in hospitals and is associated with increased healthcare costs. Critically ill patients are most at risk, in part because of the number of invasive therapies that they require in the intensive care unit (ICU). Washing with 5% tea tree oil (TTO) has been shown to be effective in removing MRSA on the skin. However, to date, no trials have evaluated the potential of TTO body wash to prevent MRSA colonization or infection. In addition, detecting MRSA by usual culture methods is slow. A faster method using a PCR assay has been developed in the laboratory, but requires evaluation in a large number of patients.

Methods/Design
This study protocol describes the design of a multicentre, phase II/III prospective open-label randomized controlled clinical trial to evaluate whether a concentration of 5% TTO is effective in preventing MRSA colonization in comparison with a standard body wash (Johnsons Baby Softwash) in the ICU. In addition we will evaluate the cost-effectiveness of TTO body wash and assess the effectiveness of the PCR assay in detecting MRSA in critically ill patients. On admission to intensive care, swabs from the nose and groin will be taken to screen for MRSA as per current practice. Patients will be randomly assigned to be washed with the standard body wash or TTO body wash. On discharge from the unit, swabs will be taken again to identify whether there is a difference in MRSA colonization between the two groups.

Discussion
If TTO body wash is found to be effective, widespread implementation of such a simple colonization prevention tool has the potential to impact on patient outcomes, healthcare resource use and patient confidence both nationally and internationally.

Trial Registration
[ISRCTN65190967]

High density mangrove plantation enhances surface accretion, surface elevation change, and tree survival in coastal areas susceptible to sea-level rise

Survival, growth, above ground biomass accumulation, soil surface elevation dynamics and nitrogen accumulation in accreted sediments were studied in experimental treatments planted with four different densities (6.96, 3.26, 1.93 and 0.95 seedlings m-2) of the mangrove Rhizophora mucronata in Puttalam Lagoon, Sri Lanka. Measurements were taken over a period of 1171 days and were compared with those from unplanted controls. Trees at the lowest density showed significantly reduced survival, whilst measures of individual tree growth did not differ significantly among treatments. Rates of surface sediment accretion (means ± S.E.) were 13.0 (±1.3), 10.5 (±0.9), 8.4 (±0.3), 6.9 (±0.5) and 5.7 (±0.3) mm yr-1 at planting densities of 6.96, 3.26, 1.93, 0.95, and 0 (unplanted control) seedlings m-2, respectively, showing highly significant differences among treatments. Mean (± S.E.) rates of surface elevation change were much lower than rates of accretion at 2.8 (±0.2), 1.6 (±0.1), 1.1 (±0.2), 0.6 (±0.2) and -0.3 (±0.1) mm yr-1 for 6.96, 3.26, 1.93, 0.95, and 0 seedlings m-2, respectively. All planted treatments appeared to accumulate greater nitrogen concentrations in the sediment compared to the unplanted control, and suggests one potential causal mechanism for the facilitatory effects observed; high densities of plants potentially contribute to the accretion of greater amounts of nutrient rich sediment. While this potential process needs further study, this study demonstrated how higher densities of mangroves enhance rates of sediment accretion and surface elevation, processes that may be crucial in mangrove ecosystem adaptation to sea level rise. There was no evidence that increasing plant density evoked a trade-off with growth and survival of the planted trees. Rather facilitatory effects enhanced survival at high densities, suggesting that local land managers may be able to take advantage of plantation densities to help mitigate sea-level rise effects by encouraging positive soil surface elevation increment, and perhaps even greater nutrient retention to promote mangrove growth and ameliorate nearshore eutrophication in tropical island environments.

Inferring the conservative causal core of gene regulatory networks

Background
Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.

Results
In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.

Conclusions
For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.