Characterisation of MEAs for Electrochemical Energy Conversion Using an Easy Test Technique

The paper describes an EasyTest cell developed for simple, safe and inexpensive to run testing and optimisation of the active materials (catalysts, catalytic supports, polymer membrane electrolytes) and electrode structures utilized in PEM Fuel cells and Electrolysers. The main advantages of the new EasyTest technique are demonstrated by a comparative study on the performance of two types of membrane electrode assemblies for electrochemical energy conversion. Nafion and PBI-based polymer electrolyte membranes covered with catalytic layers containing 20 % Pt dispersed on carbon black (E-TEK, De Nora) are tested as hydrogen electrodes working in a fuel cell and an electrolyser mode at two characteristic temperatures, varying the total partial pressure in the cell. The PBI-based membrane electrode assembly (MEA) gives lower current densities compared to that containing Nafion, while its performance remains stable in a much broader potential range. At overpotentials of about = 300–350 mV the Nafion MEA reaches a limiting current density, while in the case of PBI-based MEA such an effect is not registered in the whole potential range tested

Investigation of octupole vibrational states in 150Nd via inelastic proton scattering (p,p'g)

Octupole vibrational states were studied in the nucleus $^{150}\mathrm{Nd}$ via inelastic proton scattering with \unit[10.9]{MeV} protons which are an excellent probe to excite natural parity states. For the first time in $^{150}\mathrm{Nd}$, both the scattered protons and the $\gamma$ rays were detected in coincidence giving the possibility to measure branching ratios in detail. Using the coincidence technique, the $B(E1)$ ratios of the decaying transitions for 10 octupole vibrational states and other negative-parity states to the yrast band were determined and compared to the Alaga rule. The positive and negative-parity states revealed by this experiment are compared with Interacting Boson Approximation (IBA) calculations performed in the (spdf) boson space. The calculations are found to be in good agreement with the experimental data, both for positive and negative-parity states

Precise γ-ray intensity measurements in 10B

Precise electromagnetic transition matrix elements in 10Be and 10C have provided surprisingly stringent tests of modern ab initio calculations using realistic nuclear forces. The analog transition in 10B can further constrain these new calculations and probe the symmetry of the wave functions across the A=10 multiplet. We report on a careful measurement of the γ-ray intensities from states populated in the 10B(p,p) reaction at 10 MeV, including a determination of the key E2 branch from the J=2 T=1 state at 5164keV to the J=0 T=1 state at 1740keV of 0.16(4)%. \ua9 2012 American Physical Society

Novel automated approach to the quantitative analysis of dopaminergic functional images in a large cohort of Parkinson's patients

PET and SPECT are nuclear medicine imaging techniques that allow for the study of physiological processes in vivo. These techniques allow to assess the dopaminergic system in subjects with Parkinson's disease (PD), which is the system most severely affected by the disease. Parkinson’s Progression Markers Initiative is a multicenter, longitudinal study aimed at identifying novel biomarkers of PD progression. This study utilizes brain SPECT/PET imaging to investigate the dopaminergic system, by examining the distribution of the dopamine transporter (DaT) or the vesicular monoamine transporter 2 (VMAT) in the striatum. Several imaging metrics can be used to quantify the dopaminergic tracer binding in the striatum. These metrics are typically calculated on regions of interest (ROIs) that require either manual placement or coregistration with MR structural images. In the first part of this work, an automated approach to quantifying dopaminergic tracer binding is presented; the method consists of a new metric, SI, evaluated over a bounding box that is automatically placed on the SPECT/PET images. In order to validate this metric, the correlation is computed between the SI values and the motor scores of PD subjects from the PPMI database. We find that sum intensity achieves correlations as strong as the ones obtained using conventional approaches such as the putamen binding ratio, evaluated on manually-placed ROIs, but using a simplified and operator-independent approach. The second part of this work focuses on predicting the rate of PD progression over the four years during which the PD subjects were enrolled in the PPMI study. Two methods of quantifying disease progression are considered. The first approach uses imaging features collected at year-0 of the study to predict the decline in the putamen binding ratios over the next four years. The model achieves a prediction error of 13% for the better side of the putamen, which is comparable to the test-retest reproducibility of this metric. The second approach uses imaging and clinical features at year-0 to predict the clinical outcome (quantified by year-4 motor and cognitive scores). Novel combinations of clinical and imaging features that are predictors of disease severity are identified.Science, Faculty ofPhysics and Astronomy, Department ofGraduat

The system for symbol –analytic transformations SANTRA–2. Preparation of a program and debugging means

Abstract: The source language of the system for symbol –analytic transformations SANTRA–2 is based on general symbolic manipulation means. These means provide transformations of algebraic expressions particularly. The language provides such facilities as pass–by–name call, dynamic macrogeneration, the use of abstract data types and another as well. The pointed out properties provide solving tasks of analytic computations that are hardly solved by systems having analogous orientation, whith less expenditure. The description of the source language and main facilities is given in the papers included in the reference. In this preprint some aspects of practical using of the system including debugging means are described.Note: Research direction:Programming, parallel computing, multimedi

Synthesis of octa(1,1,3,3-tetramethylbutyl)octakis (dimethylphosphinoylmethyleneoxy)calix[8]arene and its application in the synergistic solvent extraction and separation of lanthanoids

A new lower rim substituted calix[8]arene bearing eight phosphine oxide moieties has been synthesized. The structure of 5,11,17,23,29,35,41,47-octa(1,1,3,3-tetramethylbutyl)-49,50,51,52,53,54,55,56-octakis(dimethylphosphinoylmethyleneoxy)calix[8]arene (S) was identified and confirmed by elemental analysis, IR-, H-1, C-13 and P-31-{H-1} NMR spectroscopy as well as by ES-mass spectrometry

Synthesis and characterization of partially substituted at lower rim phosphorus containing calix(4)arenes

The synthesis and characterization of several new phosphorus-containing partially lower rim substituted derivatives of 5,11,17,23-tetra(t-butyl) calix(4)arene (1) and 5,11,17,23-tetra(t-octyl)calix(4)arene (II), namely 5,11,17,23-tetra(t-butyl)-25,27-dihydroxy-26,28-bis(diphenylphosphinoyl-oxy) calix(4)arene (IV); 5,11,17,23-tetra(t-butyl)-25-hydroxy-26,27,28-tris(tetramethyldiamido- phosphinoyl-oxy) calix(4)arene (Vb); 5,11,17,23-tetra(t-butyl)-25,27-dihydroxy-26,28-bis(dimethyl-phosphinoyl- methoxy) calix(4)arene (VI); 5,11,17,23-tetra (t-octyl)25,27-dihydroxy-26,28-bis(dimethyl-phosphinoyl-methoxy) calix(4)arene (VII) are reported. The structure of the synthesized calix(4)arene derivatives are identified and confirmed by elemental analysis, IR, H-1, C-13, P-31(H-1) NMR spectroscopy and mass spectrometry as and X-ray crystallographic analysis of 5,11,17,23-tetra(t-butyl)25,27-dihydroxy-26,28-bis(dimethyl-phosphinoyl-methoxy) calix(4)arene VI. According to the NMR spectra, all calix(4)arenes are in cone conformation

Aggregation behavior and in vitro biocompatibility study of octopus-shaped macromolecules based on tert-butylcalix[4]arenes

A series of products based on tert-butylcalix[4]arene have been synthesized by anionic polymerization of ethylene oxide. The resulting products are amphiphilic octopus-shaped macromolecules, consisting of a hydrophobic calix[4]arene core and four arms of hydrophilic poly(ethylene oxide) chains. In aqueous solutions the polyoxyethylated tert-butylcalix[4]arenes were found to self-associate above certain CMC determined by dye solubilization technique. The light scattering study reveals that the polyoxyethylated tert-butylcalix[4]arenes form aggregates of narrow size distribution and hydrodynamic diameters ranging from about 155 to 245 nm and aggregation numbers from tens to hundreds macromolecules per particle depending on the degree of polymerization of the PEO chains. An in vitro biocompatibility study showed that the tested compounds are practically devoid of intrinsic cytotoxic and hemolytic effects and moreover they failed to modulate the mitogen-induced interleukin-2 release from the human T-lymphocyte cell line Jurkat E6-1. Taken together the excellent in vitro biocompatibility profile and the favorable physicochemical characteristics of the tested polyoxyethylated calix[4]arenes give us reason to consider them as promising for further evaluation as drug delivery platforms

Improved prediction of outcome in Parkinson's disease using radiomics analysis of longitudinal DAT SPECT images

No disease modifying therapies for Parkinson's disease (PD) have been found effective to date. To properly power clinical trials for discovery of such therapies, the ability to predict outcome in PD is critical, and there is a significant need for discovery of prognostic biomarkers of PD. Dopamine transporter (DAT) SPECT imaging is widely used for diagnostic purposes in PD. In the present work, we aimed to evaluate whether longitudinal DAT SPECT imaging can significantly improve prediction of outcome in PD patients. In particular, we investigated whether radiomics analysis of DAT SPECT images, in addition to use of conventional non-imaging and imaging measures, could be used to predict motor severity at year 4 in PD subjects. We selected 64 PD subjects (38 male, 26 female; age at baseline (year 0): 61.9±7.3, range [46,78]) from the Parkinson's Progressive Marker Initiative (PPMI) database. Inclusion criteria included (i) having had at least 2 SPECT scans at years 0 and 1 acquired on a similar scanner, (ii) having undergone a high-resolution 3T MRI scan, and (iii) having motor assessment (MDS-UPDRS-III) available in year 4 used as outcome measure. Image analysis included automatic region-of-interest (ROI) extraction on MRI images, registration of SPECT images onto the corresponding MRI images, and extraction of radiomic features. Non-imaging predictors included demographics, disease duration as well as motor and non-motor clinical measures in years 0 and 1. The image predictors included 92 radiomic features extracted from the caudate, putamen, and ventral striatum of DAT SPECT images at years 0 and 1 to quantify heterogeneity and texture in uptake. Random forest (RF) analysis with 5000 trees was used to combine both non-imaging and imaging variables to predict motor outcome (UPDRS-III: 27.3±14.7, range [3,77]). The RF prediction was evaluated using leave-one-out cross-validation. Our results demonstrated that addition of radiomic features to conventional measures significantly improved (p<0.001) prediction of outcome, reducing the absolute error of predicting MDS-UPDRS-III from 9.00±0.88 to 4.12±0.43. This shows that radiomics analysis of DAT SPECT images has a significant potential towards development of effective prognostic biomarkers in PD. Keywords: DAT SPECT, Longitudinal, Radiomics, Textural features, Outcome prediction, Parkinson's diseas

Artificial Neural Network-Based Prediction of Outcome in Parkinson\u27s Disease Patients Using DaTscan SPECT Imaging Features

PURPOSE: Quantitative analysis of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) images can enhance diagnostic confidence and improve their potential as a biomarker to monitor the progression of Parkinson\u27s disease (PD). In the present work, we aim to predict motor outcome from baseline DAT SPECT imaging radiomic features and clinical measures using machine learning techniques. PROCEDURES: We designed and trained artificial neural networks (ANNs) to analyze the data from 69 patients within the Parkinson\u27s Progressive Marker Initiative (PPMI) database. The task was to predict the unified PD rating scale (UPDRS) part III motor score in year 4 from 92 imaging features extracted on 12 different regions as well as 6 non-imaging measures at baseline (year 0). We first performed univariate screening (including the adjustment for false discovery) to select 4 regions each having 10 features with significant performance in classifying year 4 motor outcome into two classes of patients (divided by the UPDRS III threshold of 30). The leave-one-out strategy was then applied to train and test the ANNs for individual and combinations of features. The prediction statistics were calculated from 100 rounds of experiments, and the accuracy in appropriate prediction (classification of year 4 outcome) was quantified. RESULTS: Out of the baseline non-imaging features, only the UPDRS III (at year 0) was predictive, while multiple imaging features depicted significance. The different selected features reached a predictive accuracy of 70 % if used individually. Combining the top imaging features from the selected regions significantly improved the prediction accuracy to 75 % (p \u3c 0.01). The combination of imaging features with the year 0 UPDRS III score also improved the prediction accuracy to 75%. CONCLUSION: This study demonstrated the added predictive value of radiomic features extracted from DAT SPECT images in serving as a biomarker for PD progression tracking