idmTPreg: Regression Model for Progressive Illness Death Data

The progressive illness-death model is frequently used in medical applications. For example, the model may be used to describe the disease process in cancer studies. We have developed a new R package called idmTPreg to estimate regression coefficients in datasets that can be described by the progressive illness-death model. The motivation for the development of the package is a recent contribution that enables the estimation of possibly time-varying covariate effects on the transition probabilities for a progressive illness-death data. The main feature of the package is that it befits both non-Markov and Markov progressive illness-death data. The package implements the introduced estimators obtained using a direct binomial regression approach. Also, variance estimates and confidence bands are implemented in the package. This article presents guidelines for the use of the package.BERC 2014-2017 SEV-2013-0323 MTM2016-76969-P FP7/2011: Marie Curie Initial Training Network MEDIASRE

An open-source framework for synthetic post-dive Doppler ultrasound audio generation

Doppler ultrasound (DU) measurements are used to detect and evaluate venous gas emboli (VGE) formed after decompression. Automated methodologies for assessing VGE presence using signal processing have been developed on varying real-world datasets of limited size and without ground truth values preventing objective evaluation. We develop and report a method to generate synthetic post-dive data using DU signals collected in both precordium and subclavian vein with varying degrees of bubbling matching field-standard grading metrics. This method is adaptable, modifiable, and reproducible, allowing for researchers to tune the produced dataset for their desired purpose. We provide the baseline Doppler recordings and code required to generate synthetic data for researchers to reproduce our work and improve upon it. We also provide a set of pre-made synthetic post-dive DU data spanning six scenarios representing the Spencer and Kisman-Masurel (KM) grading scales as well as precordial and subclavian DU recordings. By providing a method for synthetic post-dive DU data generation, we aim to improve and accelerate the development of signal processing techniques for VGE analysis in Doppler ultrasound

Enhanced visible-light photocatalytic activity of strontium-doped zinc oxide nanoparticles

Strontium-doped zinc oxide nanoparticles (Zn1-xSrxO NPs; x=0, 0.02, 0.04, and 0.06) were synthesized by a sol-gel method. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images showed NPs with nearly spherical shapes, with sizes from 27 to 41 nm for high Sr concentration and undoped ZnO NPs, respectively. X-ray diffraction (XRD) patterns, selected area electron diffraction (SAED) patterns, and Raman spectra indicated that the undoped and Sr-doped ZnO NPs were crystallized in a hexagonal wurtzite structure. However, the Raman results revealed a decrease in the crystalline quality with an increase in the Sr concentration in the ZnO structure. Evidence of dopant incorporation is demonstrated by X-ray photoelectron spectroscopy (XPS) of the Sr-doped ZnO NPs. From the results of optical characterizations, the band-gap values of the Zn0.98Sr0.02O and Zn0.96Sr0.04O NPs decreased, while the band-gap value of the Zn0.94Sr0.06O NPs increased in comparison to the band-gap value of the undoped ZnO NPs. Finally, the obtained NPs were used as a photocatalyst to remove methylene blue (MB). Observations showed that the efficiency of the photocatalyst activity of the ZnO NPs was significantly increased by increasing the Sr, but until an optimum concentration

Significantly improved photocurrent response of ZnS-reduced graphene oxide composites

ZnS-nanoparticles (NPs) reduced graphene oxide (rGO) composites with a high degree of crystallinity and high dispersity were successfully synthesized via a facile solvothermal method in the gelatin medium, during which the formation of ZnS NPs, reduction of graphene oxide and loading of ZnS NPs into the rGO surface occur simultaneously. Gelatin, as a natural capping agent, plays a significant role in controlling the degree of dispersion and coverage of ZnS NPs. The effect of rGO on the crystalline structure and optical properties of ZnS NPs were determined via X-ray diffraction, UV-visible diffused reflectance spectroscopy and photoluminescence spectroscopy. The ZnS-rGO composites exhibit excellent potential for photocurrent generation compared with pure ZnS NPs under visible light irradiation, provided that efficient photoinduced charge separation and transportation can be achieved at the interface. The maximum photocurrent response was obtained for ZnS-rGO composite with a 3% mass fraction of rGO, which is 2 times that achieved on pure ZnS NPs. (C) 2015 Elsevier B.V. All rights reserved

Electrodeposition of flower-like platinum on electrophoretically grown nitrogen-doped graphene as a highly sensitive electrochemical non-enzymatic biosensor for hydrogen peroxide detection

An efficient non-enzymatic biosensor electrode consisting of nitrogen-doped graphene (N-graphene) and platinum nanoflower (Pt NF) with different N-graphene loadings were fabricated on indium tin oxide (ITO) glass using a simple layer-by-layer electrophoretic and electrochemical sequential deposition approach. N-graphene was synthesized by annealing graphene oxide with urea at 900 degree C. The structure and morphology of the as-fabricated non-enzymatic biosensor electrodes were determined using X-ray diffraction, field emission electron microscopy, transmission electron microscopy, Raman and X-ray photoelectron spectra. The as-fabricated Pt NF-N-graphene-modified ITO electrodes with different N-graphene loadings were utilized as a non-enzymatic biosensor electrode for the detection of hydrogen peroxide (H2O2). The behaviors of the hybrid electrodes towards H2O2 reduction were assessed using chronoamperometry, cyclic voltammetry and electrochemical impedance spectroscopy analysis. The Pt NF-N-graphene-modified ITO electrode with a 0.05 mg ml-1 N-graphene loading exhibited the lowest detection limit, fastest amperometric sensing, a wide linear response range, excellent stability and reproducibility for the non-enzymatic H2O2 detection, due to the synergistic effect between the electrocatalytic activity of the Pt NF and the high conductivity and large surface area of N-graphene.High Impact Research MoE Grant UM.C/625/1/HIR/MoE/SC/04 from the Ministry of Education Malaysia, UMRG Program RP012A-14SUS, RP038C-15HTM, Grand Challenge GC001C-14SBS and University Malaya Centre for Ionic Liquids (UMCiL). Global Frontier R&D Program on Center for Wave Energy Control based on Metamaterials funded by the National Research Foundation under the Ministry of Science, ICT & Future Planning, Korea (No. 2014063711).Scopu