Context Excess calories from free sugars are implicated in the epidemics of obesity and type 2 diabetes. Honey is a free sugar but is generally regarded as healthy. Objective The effect of honey on cardiometabolic risk factors was assessed via a systematic review and meta-analysis of controlled trials using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach. Data Sources MEDLINE, Embase, and the Cochrane Library databases were searched up to January 4, 2021, for controlled trials ≥1 week in duration that assessed the effect of oral honey intake on adiposity, glycemic control, lipids, blood pressure, uric acid, inflammatory markers, and markers of nonalcoholic fatty liver disease. Data Extraction Independent reviewers extracted data and assessed risk of bias. Data were pooled using the inverse variance method and expressed as mean differences (MDs) with 95%CIs. Certainty of evidence was assessed using GRADE. Data Analysis A total of 18 controlled trials (33 trial comparisons, N = 1105 participants) were included. Overall, honey reduced fasting glucose (MD = −0.20 mmol/L, 95%CI, −0.37 to −0.04 mmol/L; low certainty of evidence), total cholesterol (MD = −0.18 mmol/L, 95%CI, −0.33 to −0.04 mmol/L; low certainty), low-density lipoprotein cholesterol (MD = −0.16 mmol/L, 95%CI, −0.30 to −0.02 mmol/L; low certainty), fasting triglycerides (MD = −0.13 mmol/L, 95%CI, −0.20 to −0.07 mmol/L; low certainty), and alanine aminotransferase (MD = −9.75 U/L, 95%CI, −18.29 to −1.21 U/L; low certainty) and increased high-density lipoprotein cholesterol (MD = 0.07 mmol/L, 95%CI, 0.04–0.10 mmol/L; high certainty). There were significant subgroup differences by floral source and by honey processing, with robinia honey, clover honey, and raw honey showing beneficial effects on fasting glucose and total cholesterol. Conclusion Honey, especially robinia, clover, and unprocessed raw honey, may improve glycemic control and lipid levels when consumed within a healthy dietary pattern. More studies focusing on the floral source and the processing of honey are required to increase certainty of the evidence. Systematic Review Registration PROSPERO registration number CRD42015023580.
Simulation models for large complex reservoirs with a long production history are traditionally used in the framework of deterministic forecasts. The estimation of prediction uncertainties based on reservoir models with long run times is often impractical due to limited statistical data generated from direct full field reservoir simulation runs. Here, we use surrogate models to capture key performance indicators as a function of reservoir uncertainties. Monte Carlo sampling processes are applied for generating key parameter distributions and to identify representative simulation models for field development planning. Transparent workflow steps and a thorough validation exercise of the predictability of surrogate models is a prerequisite for obtaining prediction uncertainties based on proxy modeling results. In this work we present a case study for estimating prediction uncertainties including history data of a large mature offshore oil field. A workflow is designed for a limited number of simulation runs which is expected to affect the stability of statistical reservoir performance indicators. Proxy models are introduced in that framework for analyzing sensitivities and to prepare a basis for extensive data sampling. Alternative proxy modeling techniques are used to cross validate results. To assure an acceptable quality of the history match simulated field oil production rate and gas oil ratio as well as water cut and shut-in pressures in several wells are compared to their historical data. A quantitative measure for the simulation error is calculated for each case. Filtering techniques are applied for discriminating cases with a poor match quality. Sensitivities and correlation effects between field wide uncertainties and reservoir performance indicators are calculated. Representative full field simulation models representing P10, P50 and P90 for oil reserves are identified. The uncertainty quantification workflow was validated for a mature field case study and serves as a basis for field development planning scenarios.
Ethylbisindenyl zirconium dichloride (Et(Ind) 2 ZrCl 2 ) and the MAO methylalumoxane (MAO) co-catalyst were heterogenized on Davision silica 955 partially dehydroxylated at 275°C, following the concept of equilibrium adsorption. The influence of MAO on the electronic environment resulting from the heterogenization was investigated using XPS. Heterogenization of Et(Ind) 2 ZrCl 2 and MAO on the above silica generated two types of zirconocenium cations (Cation 1 and Cation 2), independent of the heterogenization methods. Based on the postulated surface chemistry, Cation 1 is presumed to be in the form of an ion-pair [SiO] − [Et(Ind) 2 ZrCl] Y , whereas Cation 2 is presumed to be a trapped multi-coordinated crown complex of MAO. In the absence of MAO, only Cation 1 is formed. The present study provides some support for the postulated surface chemistry regarding heterogenization of Et(Ind) 2 ZrCl 2 and MAO on silica.
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