Improving the ORR Performance by Enhancing the Pt Oxidation Resistance

Proton exchange membrane fuel cells require oxygen reduction catalysts with high activity and stability. Pt based alloy materials are most widely applied ORR catalyst due to its high intrinsic activity, but usually suffer from rapid deactivation as a result of particle agglomeration, detachment, Ostwald ripening and/or Pt dissolution. Here we investigate the degradation of the PdPt alloys via in situ X-ray absorption fine structure, Δμ analysis, identical location-electron microscopy and DFT calculations. We conclude that the origin of high activity and stability of the PdPt catalyst stems from the oxidation resistance of metallic Pt, forming mainly surface adsorbed O species at high potentials. Two stage degradation process are observed, showing an evolution of dynamic surface dependent ORR performance along with the deactivation process. The careful design of Pt alloy structure leads to controlled surface oxygen behaviours. This opens a new way to increase the lifespan of fuel cells and improve the Pt utilization efficiency

Postnatal dexamethasone, respiratory and neurodevelopmental outcomes at two years in babies born extremely preterm.

IMPORTANCE: Postnatal dexamethasone is associated with reduction in bronchopulmonary dysplasia. There remains, however, concern that its short-term benefits are accompanied by long-term adverse effects e.g. poorer neurodevelopmental outcomes. OBJECTIVE: Our aim was to determine the effects of administration of postnatal dexamethasone on respiratory and neurodevelopmental outcome at two years of age after adjusting for neonatal and infant risk factors. MATERIALS AND METHODS: The study included 412 infants born at 23-28 weeks of gestation, 29% had received postnatal dexamethasone. Two outcomes were examined, respiratory hospital admissions in the past 12 months and neurodevelopmental impairment. Logistic regression, adjusted for sex, birthweight z-score, gestation, maternal smoking, oxygen dependency at 36 weeks, airleak, patent ductus arteriosus, pulmonary haemorrhage, major ultrasound abnormality, mode of ventilation and age at assessment, was undertaken. RESULTS: After adjustment, postnatal dexamethasone was associated with significantly increased proportions of both respiratory hospital readmission: (0.35 vs 0.15, difference = 0.20; 95% CI: 0.08, 0.31) and neurodevelopmental impairment (0.59 vs 0.45, difference = 0.14; 95% CI: 0.02, 0.26). CONCLUSIONS: Postnatal dexamethasone use in extremely preterm infants is associated with increased risks of respiratory hospital admissions and neurodevelopmental impairment. These associations were not explained by excess neonatal morbidities

Effect of dexamethasone exposure on the neonatal unit on the school age lung function of children born very prematurely

The objective of this study was to determine the impact of postnatal dexamethasone treatment on the neonatal unit on the school age lung function of very prematurely born children. Children born prior to 29 weeks of gestational age had been entered into a randomised trial of two methods of neonatal ventilation (United Kingdom Oscillation Study). They had comprehensive lung function measurements at 11 to 14 years of age. One hundred and seventy-nine children born at a mean gestational age of 26.9 (range 23–28) weeks were assessed at 11 to 14 years; 50 had received postnatal dexamethasone. Forced expiratory flow at 75% (FEF75), 50%, 25% and 25–75% of the expired vital capacity, forced expiratory volume in one second, peak expiratory flow and forced vital capacity and lung volumes including total lung capacity and residual volume were assessed. Lung function outcomes were compared between children who had and had not been exposed to dexamethasone after adjustment for neonatal factors using linear mixed effects regression. After adjustment for confounders all the mean spirometry results were between 0.38 and 0.87 standard deviations lower in those exposed to dexamethasone compared to the unexposed. For example, the mean FEF75z-score was 0.53 lower (95% CI 0.21 to 0.85). The mean lung function was lower as the number of courses of dexamethasone increased. In conclusion, postnatal dexamethasone exposure was associated with lower mean lung function at school age in children born extremely prematurely. Our results suggest the larger the cumulative dose the greater the adverse effect on lung function at follow-up

Proximity curves for potential-based clustering

YesThe concept of proximity curve and a new algorithm are proposed for obtaining clusters in a finite set of data points in the finite dimensional Euclidean space. Each point is endowed with a potential constructed by means of a multi-dimensional Cauchy density, contributing to an overall anisotropic potential function. Guided by the steepest descent algorithm, the data points are successively visited and removed one by one, and at each stage the overall potential is updated and the magnitude of its local gradient is calculated. The result is a finite sequence of tuples, the proximity curve, whose pattern is analysed to give rise to a deterministic clustering. The finite set of all such proximity curves in conjunction with a simulation study of their distribution results in a probabilistic clustering represented by a distribution on the set of dendrograms. A two-dimensional synthetic data set is used to illustrate the proposed potential-based clustering idea. It is shown that the results achieved are plausible since both the ‘geographic distribution’ of data points as well as the ‘topographic features’ imposed by the potential function are well reflected in the suggested clustering. Experiments using the Iris data set are conducted for validation purposes on classification and clustering benchmark data. The results are consistent with the proposed theoretical framework and data properties, and open new approaches and applications to consider data processing from different perspectives and interpret data attributes contribution to patterns

Psychiatric disorders in individuals born very preterm / very low-birth weight: An individual participant data (IPD) meta-analysis

Background: Data on psychiatric disorders in survivors born very preterm (VP; <32 weeks) or very low birthweight (VLBW; <1500 g) are sparse. We compared rates of psychiatric diagnoses between VP/VLBW and term-born, normal birthweight (term/NBW) control participants. / Methods: This individual participant data (IPD) meta-analysis pooled data from eligible groups in the Adults born Preterm International Collaboration (APIC). Inclusion criteria included: 1) VP/VLBW group (birth weight 2499 g and/or gestational age ≥37 weeks), and 3) structured measure of psychiatric diagnoses using DSM or ICD criteria. Diagnoses of interest were Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Anxiety Disorder, Mood Disorder, Disruptive Behaviour Disorder (DBD), Eating Disorder, and Psychotic Disorder. A systematic search for eligible studies was conducted (PROSPERO Registration Number 47555). / Findings: Data were obtained from 10 studies (1385 VP/VLBW participants, 1780 controls), using a range of instruments and approaches to assigning diagnoses. Those born VP/VLBW had ten times higher odds of meeting criteria for ASD (odds ratio [OR] 10·6, 95% confidence interval [CI] 2·50, 44·7), five times higher odds of meeting criteria for ADHD (OR 5·42, 95% CI 3·10, 9·46), twice the odds of meeting criteria for Anxiety Disorder (OR 1·91, 95% CI 1·36, 2·69), and 1·5 times the odds of meeting criteria for Mood Disorder (OR 1·51, 95% CI 1·08, 2·12) than controls. This pattern of findings was consistent within age (<18 years vs. ≥18 years) and sex subgroups. / Interpretation: Our data suggests that individuals born VP/VLBW might have higher odds of meeting criteria for certain psychiatric disorders through childhood and into adulthood than term/NBW controls. Further research is needed to corroborate our results and identify factors associated with psychiatric disorders in individuals born VP/VLBW. / Funding: Australia's National Health & Medical Research Council; CAPES (Coordenação de Aperfeiçoamento de Pessoal deNível Superior) - International Cooperation General Program; Canadian Institutes of Health Research Team Grant; National Council for Scientific and Technological Development (CNPq); Academy of Finland; Sigrid Juselius Foundation; Signe and Ane Gyllenberg Foundation; European Union's Horizon 2020 research and innovation programme: Project RECAP-Preterm; European Commission Dynamics of Inequality Across the Life-course: structures and processes (DIAL); Neurologic Foundation of New Zealand; MRC programme grant; Health Research Council of New Zealand; National Institutes of Health, USA; The Research Council of Norway; Joint Research Committee between St. Olavs Hospital and Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU); Liaison Committee between Central Norway Regional Health Authority and NTNU

Neuropsychiatric Disease Classification Using Functional Connectomics - Results of the Connectomics in NeuroImaging Transfer Learning Challenge

Large, open-source datasets, such as the Human Connectome Project and the Autism Brain Imaging Data Exchange, have spurred the development of new and increasingly powerful machine learning approaches for brain connectomics. However, one key question remains: are we capturing biologically relevant and generalizable information about the brain, or are we simply overfitting to the data? To answer this, we organized a scientific challenge, the Connectomics in NeuroImaging Transfer Learning Challenge (CNI-TLC), held in conjunction with MICCAI 2019. CNI-TLC included two classification tasks: (1) diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) within a pre-adolescent cohort; and (2) transference of the ADHD model to a related cohort of Autism Spectrum Disorder (ASD) patients with an ADHD comorbidity. In total, 240 resting-state fMRI (rsfMRI) time series averaged according to three standard parcellation atlases, along with clinical diagnosis, were released for training and validation (120 neurotypical controls and 120 ADHD). We also provided Challenge participants with demographic information of age, sex, IQ, and handedness. The second set of 100 subjects (50 neurotypical controls, 25 ADHD, and 25 ASD with ADHD comorbidity) was used for testing. Classification methodologies were submitted in a standardized format as containerized Docker images through ChRIS, an open-source image analysis platform. Utilizing an inclusive approach, we ranked the methods based on 16 metrics: accuracy, area under the curve, F1-score, false discovery rate, false negative rate, false omission rate, false positive rate, geometric mean, informedness, markedness, Matthew’s correlation coefficient, negative predictive value, optimized precision, precision, sensitivity, and specificity. The final rank was calculated using the rank product for each participant across all measures. Furthermore, we assessed the calibration curves of each methodology. Five participants submitted their method for evaluation, with one outperforming all other methods in both ADHD and ASD classification. However, further improvements are still needed to reach the clinical translation of functional connectomics. We have kept the CNI-TLC open as a publicly available resource for developing and validating new classification methodologies in the field of connectomics

Studies of the Decay B+- -> D_CP K+-

We report studies of the decay B+- -> D_CP K+-, where D_CP denotes neutral D mesons that decay to CP eigenstates. The analysis is based on a 29.1/fb data sample of collected at the \Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric e+ e- storage ring. Ratios of branching fractions of Cabibbo-suppressed to Cabibbo-favored processes involving D_CP are determined to be B(B- -> D_1 K-)/B(B- -> D_1 pi-)=0.125 +- 0.036 +- 0.010 and B(B- -> D_2 K-)/B(B- -> D_2 pi-)=0.119 +- 0.028 +- 0.006, where indices 1 and 2 represent the CP=+1 and CP=-1 eigenstates of the D0 - anti D0 system, respectively. We also extract the partial rate asymmetries for B+- -> D_CP K+-, finding A_1 = 0.29 +- 0.26 +- 0.05 and A_2 = -0.22 +- 0.24 +- 0.04.Comment: 10 pages, 2 figures, submitted to Physical Review Letter

Development of a measurement tool to assess public awareness of cancer

&lt;p&gt;Objective: We aimed to develop and validate a measurement tool to assess cancer awareness in the general population: the cancer awareness measure (CAM).&lt;/p&gt; &lt;p&gt;Methods: Items assessing awareness of cancer warning signs, risk factors, incidence, screening programmes and attitudes towards help seeking were extracted from the literature or generated by expert groups. To determine reliability, the CAM was administered to a university participant panel (n=148), with a sub-sample (n=94) completing it again 2 weeks later. To establish construct validity, CAM scores of cancer experts (n=12) were compared with those of non-medical academics (n=21). Finally, university students (n=49) were randomly assigned to read either a cancer information leaflet or a leaflet with control information before completing the measure, to ensure the CAM was sensitive to change.&lt;/p&gt; &lt;p&gt;Results: Cognitive interviewing indicated that the CAM was being interpreted as intended. Internal reliability (Cronbach's α=0.77) and test–retest reliability (r=0.81) were high. Scores for cancer experts were significantly higher than those for non-medical academics (t(31)=6.8, P&#60;0.001). CAM scores were higher among students who received an intervention leaflet than the control leaflet (t(47)=4.8, P&#60;0.001).&lt;/p&gt; &lt;p&gt;Conclusions: These studies show the psychometric properties of the CAM and support its validity as a measure of cancer awareness in the general population.&lt;/p&gt

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO