Representing grounding line migration in synchronous coupling between a marine ice sheet model and a z-coordinate ocean model

Synchronous coupling is developed between an ice sheet model and a z-coordinate ocean model (the MITgcm). A previously-developed scheme to allow continuous vertical movement of the ice-ocean interface of a floating ice shelf (“vertical coupling”) is built upon to allow continuous movement of the grounding line, or point of floatation of the ice sheet (“horizontal coupling”). Horizontal coupling is implemented through the maintenance of a thin layer of ocean ( ∼ 1 m) under grounded ice, which is inflated into the real ocean as the ice ungrounds. This is accomplished through a modification of the ocean model’s nonlinear free surface evolution in a manner akin to a hydrological model in the presence of steep bathymetry. The coupled model is applied to a number of idealized geometries and shown to successfully represent ocean-forced marine ice sheet retreat while maintaining a continuous ocean circulation

Safety assessment of probiotics for human use

The safety of probiotics is tied to their intended use, which includes consideration of potential vulnerability of the consumer or patient, dose and duration of consumption, and both the manner and frequency of administration. Unique to probiotics is that they are alive when administered, and unlike other food or drug ingredients, possess the potential for infectivity or in situ toxin production. Since numerous types of microbes are used as probiotics, safety is also intricately tied to the nature of the specific microbe being used. The presence of transferable antibiotic resistance genes, which comprises a theoretical risk of transfer to a less innocuous member of the gut microbial community, must also be considered. Genetic stability of the probiotic over time, deleterious metabolic activities, and the potential for pathogenicity or toxicogenicity must be assessed depending on the characteristics of the genus and species of the microbe being used. Immunological effects must be considered, especially in certain vulnerable populations, including infants with undeveloped immune function. A few reports about negative probiotic effects have surfaced, the significance of which would be better understood with more complete understanding of the mechanisms of probiotic interaction with the host and colonizing microbes. Use of readily available and low cost genomic sequencing technologies to assure the absence of genes of concern is advisable for candidate probiotic strains. The field of probiotic safety is characterized by the scarcity of studies specifically designed to assess safety contrasted with the long history of safe use of many of these microbes in foods

APACHE III outcome prediction in patients admitted to the intensive care unit after liver transplantation: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>The Acute Physiology and Chronic Health Evaluation (APACHE) III prognostic system has not been previously validated in patients admitted to the intensive care unit (ICU) after orthotopic liver transplantation (OLT). We hypothesized that APACHE III would perform satisfactorily in patients after OLT</p> <p>Methods</p> <p>A retrospective cohort study was performed. Patients admitted to the ICU after OLT between July 1996 and May 2008 were identified. Data were abstracted from the institutional APACHE III and liver transplantation databases and individual patient medical records. Standardized mortality ratios (with 95% confidence intervals) were calculated by dividing the observed mortality rates by the rates predicted by APACHE III. The area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow C statistic were used to assess, respectively, discrimination and calibration of APACHE III.</p> <p>Results</p> <p>APACHE III data were available for 918 admissions after OLT. Mean (standard deviation [SD]) APACHE III (APIII) and Acute Physiology (APS) scores on the day of transplant were 60.5 (25.8) and 50.8 (23.6), respectively. Mean (SD) predicted ICU and hospital mortality rates were 7.3% (15.4) and 10.6% (18.9), respectively. The observed ICU and hospital mortality rates were 1.1% and 3.4%, respectively. The standardized ICU and hospital mortality ratios with their 95% C.I. were 0.15 (0.07 to 0.27) and 0.32 (0.22 to 0.45), respectively.</p> <p>There were statistically significant differences in APS, APIII, predicted ICU and predicted hospital mortality between survivors and non-survivors. In predicting mortality, the AUC of APACHE III prediction of hospital death was 0.65 (95% CI, 0.62 to 0.68). The Hosmer-Lemeshow C statistic was 5.288 with a p value of 0.871 (10 degrees of freedom).</p> <p>Conclusion</p> <p>APACHE III discriminates poorly between survivors and non-survivors of patients admitted to the ICU after OLT. Though APACHE III has been shown to be valid in heterogenous populations and in certain groups of patients with specific diagnoses, it should be used with caution – if used at all – in recipients of liver transplantation.</p

Observational needs for improving ocean and coupled reanalysis, S2S prediction, and decadal prediction

Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate as well as the initialization of operational long-range prediction models. There are many remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean-observing system throughout its history, the presence of biases and drifts in models, and the simplifying assumptions made in DA solution methods. From a governance point of view, more support is needed to bring the ocean-observing and DA communities together. For prediction applications, there is wide agreement that protocols are needed for rapid communication of ocean-observing data on numerical weather prediction (NWP) timescales. There is potential for new observation types to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of NWP, covering hours to weeks, out to multiple decades. Better communication between DA and observation communities is encouraged in order to allow operational prediction centers the ability to provide guidance for the design of a sustained and adaptive observing network

OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs. OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations

Review and Unification of Methods for Computing Derivatives of Multidisciplinary Systems

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97061/1/AIAA2012-1589.pd