Blue shift in the luminescence spectra of MEH-PPV films containing ZnO nanoparticles

Luminescence properties of nanocomposites consisting of ZnO nanoparticles in a conjugated polymer, poly [2-methoxy-5-(2′-ethyl hexyloxy)-phenylene vinylene] (MEH-PPV), were investigated. Photoluminescence measurements reveal a blue shift in the emission spectrum of MEH-PPV upon incorporation of ZnO nanoparticles into the polymer film while the emission is increasingly quenched with increasing ZnO concentration. In contrast, the structure of the polymer and its conjugation length are not affected by the presence of ZnO nanoparticles (up to 16 wt% ZnO) as revealed by Raman spectroscopy. The blue shift and photoluminescence quenching are explained by the separation of photogenerated electron-hole pairs at the MEH-PPV/ZnO interface and the charging of the nanoparticles. Crown Copyright © 2008

Prediction of hip fracture in post-menopausal women using artificial neural network approach

© 2017 IEEE. Hip fracture is one of the most serious health problems among post-menopausal women with osteoporosis. It is very difficult to predict hip fracture, because it is affected by multiple risk factors. Existing statistical models for predicting hip fracture risk yield area under the receiver operating characteristic curve (AUC) ∼0.7-0.85. In this study, we trained an artificial neural network (ANN) to predict hip fracture in one cohort, and validated its predictive performance in another cohort. The data for training and validation included age, bone mineral density (BMD), clinical factors, and lifestyle factors which had been obtained from a longitudinal study that involved 1167 women aged 60 years and above. The women had been followed up for up to 10 years, and during the period, the incidence of new hip fractures was ascertained. We applied feed-forward neural networks to learn from the data, and then used the learning for predicting hip fracture. Results of prediction showed that the accuracy of model I (which included only lumbar spine and femoral neck BMD) and model II (which included non-BMD factors) was 82% and 84%, respectively. When both BMD and non-BMD factors were combined (Model III), the accuracy increased to 87%. The AUC for model III was 0.94. These findings indicate that ANNs are able to predict hip fracture more accurately than any existing statistical models, and that ANNs can help stratify individuals for clinical management

Making electrochemistry easily accessible to the synthetic chemist

A significantly renewed interest in synthetic electrochemistry is apparent in the increasing number of publications over the last few years. Electrochemical synthesis offers a mild, green and atom efficient route to interesting and useful molecules, thus avoiding harsh chemical oxidising and reducing agents used in traditional synthetic methods. As such, encouraging broader application of electrochemistry by synthetic chemists should be a priority. Despite the renewed interest there remains a barrier to widespread adoption of this technology derived from the extra knowledge and specialised equipment required. This has led to a knowledge gap between experienced electrochemists and those new in the field. In this tutorial we will bridge the knowledge gap by providing an easily accessible introduction which will enable synthetic chemists new to the field to explore electrochemistry. We will discuss mechanistic considerations, the setup of an electrochemical reaction with all its components, trouble shooting and selected examples from the literature

3D Geometric Analysis of Tubular Objects based on Surface Normal Accumulation

This paper proposes a simple and efficient method for the reconstruction and extraction of geometric parameters from 3D tubular objects. Our method constructs an image that accumulates surface normal information, then peaks within this image are located by tracking. Finally, the positions of these are optimized to lie precisely on the tubular shape centerline. This method is very versatile, and is able to process various input data types like full or partial mesh acquired from 3D laser scans, 3D height map or discrete volumetric images. The proposed algorithm is simple to implement, contains few parameters and can be computed in linear time with respect to the number of surface faces. Since the extracted tube centerline is accurate, we are able to decompose the tube into rectilinear parts and torus-like parts. This is done with a new linear time 3D torus detection algorithm, which follows the same principle of a previous work on 2D arc circle recognition. Detailed experiments show the versatility, accuracy and robustness of our new method.Comment: in 18th International Conference on Image Analysis and Processing, Sep 2015, Genova, Italy. 201

Shallow carrier traps in hydrothermal ZnO crystals

Native and hydrogen-plasma induced shallow traps in hydrothermally grown ZnO crystals have been investigated by charge-based deep level transient spectroscopy, photoluminescence and cathodoluminescence microanalysis. The as-grown ZnO exhibits a trap state at 23 meV, while H-doped ZnO produced by plasma doping shows two levels at 22 meV and 11 meV below the conduction band. As-grown ZnO displays the expected thermal decay of bound excitons with increasing temperature from 7 K, while we observed an anomalous behaviour of the excitonic emission in H-doped ZnO, in which its intensity increases with increasing temperature in the range 140-300 K. Based on a multitude of optical results, a qualitative model is developed which explains the Y line structural defects, which act as an electron trap with an activation energy of 11 meV, being responsible for the anomalous temperature-dependent cathodoluminescence of H-doped ZnO. © 2014 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft

Leukotriene A4 Hydrolase Genotype and HIV Infection Influence Intracerebral Inflammation and Survival From Tuberculous Meningitis.

BACKGROUND: Tuberculous meningitis (TBM) is the most devastating form of tuberculosis, yet very little is known about the pathophysiology. We hypothesized that the genotype of leukotriene A4 hydrolase (encoded by LTA4H), which determines inflammatory eicosanoid expression, influences intracerebral inflammation, and predicts survival from TBM. METHODS: We characterized the pretreatment clinical and intracerebral inflammatory phenotype and 9-month survival of 764 adults with TBM. All were genotyped for single-nucleotide polymorphism rs17525495, and inflammatory phenotype was defined by cerebrospinal fluid (CSF) leukocyte and cytokine concentrations. RESULTS: LTA4H genotype predicted survival of human immunodeficiency virus (HIV)-uninfected patients, with TT-genotype patients significantly more likely to survive TBM than CC-genotype patients, according to Cox regression analysis (univariate P = .040 and multivariable P = .037). HIV-uninfected, TT-genotype patients had high CSF proinflammatory cytokine concentrations, with intermediate and lower concentrations in those with CT and CC genotypes. Increased CSF cytokine concentrations correlated with more-severe disease, but patients with low CSF leukocytes and cytokine concentrations were more likely to die from TBM. HIV infection independently predicted death due to TBM (hazard ratio, 3.94; 95% confidence interval, 2.79-5.56) and was associated with globally increased CSF cytokine concentrations, independent of LTA4H genotype. CONCLUSIONS: LTA4H genotype and HIV infection influence pretreatment inflammatory phenotype and survival from TBM. LTA4H genotype may predict adjunctive corticosteroid responsiveness in HIV-uninfected individuals