Paradigm shift in determining Neoproterozoic atmospheric oxygen

ACKNOWLEDGMENTS We thank the Geological Survey of Australia for permission to sample the Empress 1A and Lancer 1 cores, the Natural Sciences and Engineering Research Council of Canada for financial support (grant #7961–15) of U. Brand, and the National Natural Science Foundation of China for support of F. Meng and P. Ni (grants 41473039 and 4151101015). We thank M. Lozon (Brock University) for drafting and constructing the figures. We thank the editor, Brendan Murphy, as well as three reviewers (Steve Kesler, Erik Sperling, and an anonymous reviewer), for improving the manuscript into its final form.Peer reviewedPublisher PD

Modeling of CH4-assisted SOEC for H2O/CO2 co-electrolysis

This research was supported by a grant of SFC/RGC Joint Research Scheme (X-PolyU/501/14) from Research Grant Council, University Grants Committee, Hong Kong SAR.Co-electrolysis of H2O and CO2 in a solid oxide electrolysis cell (SOEC) is promising for simultaneous energy storage and CO2 utilization. Fuel-assisted H2O electrolysis by SOEC (SOFEC) has been demonstrated to be effective in reducing power consumption. In this paper, the effects of fuel (i.e. CH4) assisting on CO2/H2O co-electrolysis are numerically studied using a 2D model. The model is validated with the experimental data for CO2/H2O co-electrolysis. One important finding is that the CH4 assisting is effective in lowering the equilibrium potential of SOEC thus greatly reduces the electrical power consumption for H2O/CO2 co-electrolysis. The performance of CH4-assisted SOFEC increases substantially with increasing temperature, due to increased reaction kinetics of electrochemical reactions and CH4 reforming reaction. The CH4-assisted SOFEC can generate electrical power and syngas simultaneously at a low current density of less than 600 Am−2 and at 1123 K. In addition, different from conventional SOEC whose performance weakly depends on the anode gas flow rate, the CH4-assisted SOFEC performance is sensitive to the anode gas flow rate (i.g. peak current density is achieved at an anode flow rate of 70 SCCM at 1073 K). The model can be used for subsequent design optimization of SOFEC to achieve high performance energy storage.PostprintPeer reviewe

Bis[N-(8-quinol­yl)pyridine-2-carbox­amidato-κ3 N,N′,N′′]manganese(III) perchlorate monohydrate

The MnIII ion in the title complex, [Mn(C15H10N3O)2]ClO4·H2O, is coordinated meridionally by six N atoms from two tridentate N-(8-quinol­yl)pyridine-2-carboxamidate ligands, yielding a distorted octa­hedral coordination geometry. The two ligands are nearly planar and their mean planes are almost perpendicular, with a dihedral angle of 86.7 (2)°

Modeling of proton-conducting solid oxide fuel cells fueled with syngas

Solid oxide fuel cells (SOFCs) with proton conducting electrolyte (H-SOFCs) are promising power sources for stationary applications. Compared with other types of fuel cells, one distinct feature of SOFC is their fuel flexibility. In this study, a 2D model is developed to investigate the transport and reaction in an H-SOFC fueled with syngas, which can be produced from conventional natural gas or renewable biomass. The model fully considers the fluid flow, mass transfer, heat transfer and reactions in the H-SOFC. Parametric studies are conducted to examine the physical and chemical processes in H-SOFC with a focus on how the operating parameters affect the H-SOFC performance. It is found that the presence of CO dilutes the concentration of H2, thus decreasing the H-SOFC performance. With typical syngas fuel, adding H2O cannot enhance the performance of the H-SOFC, although water gas shift reaction can facilitate H2 production

Assessment of Patient-Reported Outcome and Sedation-Agitation Score in Critically Ill Patients

When evaluating patients’ outcomes, the US health care system has shifted from a “disease control” model to a “patient-centered” model, which takes patients’ feedback into consideration to monitor the interventions and quality of care. Therefore, comparing patients’ feedback and clinicians’ assessments is an important indicator in evaluating interventions, especially of critically ill patients in the intensive care unit (ICU). In the intensive care unit, more than 70% of critically ill patients experience agitation and 40-60% of them are under mismanagement with either inadequate relief of anxiety or over-sedation. In this project, the main goal was to assess the association between patient-reported outcome (PRO, reported by patients according to pain, sedation, discomfort questions) and patient the Sedation-Agitation Score (SAS, reported by clinicians), to take patients’ feedback into consideration to monitor interventions. The other goal is to establish the best model in predicting SAS score using PRO along with other demographic variables. Our results show that overall there is not a strong correlation between PRO and median SAS scores. However, patients experienced variations in treatment duration and different numbers of nursing shifts during hospitalization. Treatment plan may vary; thus, SAS scores may vary within each nursing shift. Each patient has his/her own trajectory of SAS scores by shifts; therefore, considering number of shifts is one important factor to build associations between SAS score and PRO score. In our mixed model analysis, if the model only includes number of shifts during hospitalization and PRO survey score (median level of pain score, median level of discomfort score, median level of sedation score), variables including shift, median pain and median discomfort generate a better association with median SAS score per shift. If demographic variables (age, gender, severity of illness) are included in the model, adding the age variable in the above model generates a better model fit and produces better association with median SAS score per shift compared to other demographic models. In conclusion, the best model to predict patients’ SAS scores will be using number of shifts during hospitalization, pain and discomfort scores from the PRO survey as well as the age variables