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In order to utilize a wider range of low-grade syngas, the syngas biomethanation was studied in this work with respect to the gas–liquid mass transfer and the reactor start-up strategy. Two reactors, a continuous stirred tank (CSTR) and a bubble column with gas recirculation (BCR-C), were used in the experiment by feeding an artificial syngas of 20% H2, 50% CO, and 30% CO2 into the reactors at 55 °C. The results showed that the CH4 productivity was slightly increased by reducing the gas retention time (GRT), but was significantly improved by increasing the stirring speed in the CSTR and the gas circulation rate in the BCR-C. The best syngas biomethanation performance of the CSTR with a CH4 productivity of 22.20 mmol·Lr−1·day−1 and a yield of 49.01% was achieved at a GRT of 0.833 h and a stirring speed of 300 rpm, while for the BCR-C, the best performance with a CH4 productivity of 61.96 mmol·Lr−1·day−1 and a yield of 87.57% was achieved at a GRT of 0.625 h and a gas circulation rate of 40 L·Lr−1·h−1. The gas–liquid mass transfer capability provided by gas circulation is far superior to mechanical stirring, leading to a much better performance of low-grade syngas biomethanation in the BCR-C. Feeding H2/CO2 during the startup stage of the reactor can effectively stimulate the growth and metabolism of microorganisms, and create a better metabolic environment for subsequent low-grade syngas biomethanation. In addition, during the thermophilic biomethanation of syngas, Methanothermobacter is the dominant genus.

ABSTRACT Purpose To develop a semi-mechanistic model linking in vitro to in vivo drug release. Methods A nonlinear mixed-effects model describing the in vitro drug release for 6 hydrophilic matrix based modified release formulations across different experimental conditions (pH, rotation speed and ionic strength) was developed. It was applied to in vivo observations of drug release and tablet gastro intestinal (GI) position assessed with magnetic marker monitoring (MMM). By combining the MMM observations with literature information on pH and ionic strength along the GI tract, the mechanical stress in different parts of the GI tract could be estimated in units equivalent to rotation speed in the in vitro USP 2 apparatus. Results The mechanical stress in the upper and lower stomach was estimated to 94 and 134 rpm, respectively. For the small intestine and colon the estimates of mechanical stress was 93 and 38 rpm. Predictions of in vivo drug release including between subject/tablet variability was made for other newly developed formulations based on the drug release model and a model describing tablet GI transit. Conclusion The paper outlines a modeling approach for predicting in vivo behavior from standard in vitro experiments and support formulation development and quality control.

ABSTRACT Purpose To outline and test a new modeling approach for prospective predictions of absorption from newly developed modified release formulations based on in vivo studies of gastro intestinal (GI) transit, drug release and regional absorption for the investigational drug AZD0837. Methods This work was a natural extension to the companion article “A semi-mechanistic model to link in vitro and in vivo drug release for modified release formulations” . The drug release model governed the amount of substance released in distinct GI regions over time. GI distribution of released drug substance, region specific rate and extent of absorption and the influence of food intake were estimated. The model was informed by magnetic marker monitoring data and data from an intubation study with local administration in colon. Results Distinctly different absorption properties were characterized for different GI regions. Bioavailability over the gut-wall was estimated to be high in duodenum (70%) compared to the small intestine (25%). Colon was primarily characterized by a very slow rate of absorption. Conclusions The established model was largely successful in predicting plasma concentration following administration of three newly developed formulations for which no clinical data had been applied during model building.

Using an empirical New-Keynesian model with optimal discretionary monetary policy, we estimate key parameters-the central bank's preference parameters; the degree of forward-looking behavior in the determination of inflation and output; and the variances of inflation and output shocks-to match some broad characteristics of U.S. data. The parameterization we obtain implies a small concern for output stability but a large preference for interest rate smoothing, and a small degree of forward-looking behavior in price-setting but a large degree of forward-looking in the determination of output. Our methodology also allows us to carefully examine the consequences of alternative parameterizations and to provide intuition for our results.

Recent research shows that when commonly estimated dynamic Taylor rules, which are augmented with a lagged interest, are embedded in a variety of macroeconomic models, they imply a greater amount of predictable information about future movements in interest rates than is actually evident in the yield curve. We extend the analysis to consider more generally the predictability of the arguments of the Taylor rule—inflation and the output gap—in addition to the interest rate. Specifically, we compare the predictability of these three variables in a macroeconomic model with a dynamic Taylor rule to their predictability in real-time surveys of macroeconomic forecasters or a VAR model. We find that the strongest evidence against the dynamic Taylor rule is that while it is easy to predict the variables that enter the rule, it is very hard to predict actual interest rate changes. This disparity suggests that dynamic Taylor rules neglect important aspects of monetary policy behavior.

A study of self-assessed hearing problems was performed comprising 48,680 Swedish inhabitants aged 16-84 years. The participants of the survey responded to personal interviews during the period 1986-1993. One of the questions in the interview concerned difficulties of hearing in background noise. The total prevalence of the reported hearing problems was 10.7 per cent, varying from 2.4 per cent in the youngest age group to 30 per cent in the oldest. Men reported difficulties in hearing more often than women, except in the youngest age group. Hearing problems were more often reported by manual workers, unemployed and by those who had taken early retirement, than by non-manual employees and the self-employed. Regional differences regarding hearing problems were observed. The prevalence of self-reported problems was lowest in metropolitan Stockholm (7.9 per cent) and increased in the following order: other major cities (9.4 per cent), other cities (10.5 per cent), small population centres (12.5 per cent), agricultural areas (13.5 per cent) and sparsely populated forest areas (15 per cent). In summary, a number of factors related to ageing, socioeconomic status and domicile were related to self-assessed difficulties hearing a conversation. These factors obviously include determinants such as genetics, health status, gender-related differences, exposure to noise and possible conditioning effects of low-level noise exposure.

Recent research suggests that commonly estimated dynamic Taylor rules augmented with a lagged interest rate imply too much predictability of interest rate changes compared with yield curve evidence. We show that this is not sufficient proof against the Taylor rule: the result could be driven by other equations of the model that the Taylor rule is embedded in. To disentangle the effects, we study the predictability of all variables in a simple model of monetary policy: inflation, the output gap, and the interest rate, and we compare with evidence from survey data and a VAR model. We find that the strongest evidence against the Taylor rule is that while it is easy to predict the variables that enter the rule, it is very hard to predict actual interest rate changes. This is consistent with usual Taylor-type rules if policy shocks are very large, but it is more likely that there are other aspects of monetary policy behaviour that are neglected by the Taylor rule.

Recent research suggests that commonly estimated dynamic Taylor rules augmented with a lagged interest rate imply too much predictability of interest rate changes compared with yield curve evidence. We show that this is not sufficient proof against the Taylor rule: the result could be driven by other equations of the model that the Taylor rule is embedded in. To disentangle the effects, we study the predictability of all variables in a simple model of monetary policy: inflation, the output gap, and the interest rate, and we compare with evidence from survey data and a VAR model. We find that the strongest evidence against the Taylor rule is that while it is easy to predict the variables that enter the rule, it is very hard to predict actual interest rate changes. This is consistent with usual Taylor-type rules if policy shocks are very large, but it is more likely that there are other aspects of monetary policy behaviour that are neglected by the Taylor rule.

Using an empirical New-Keynesian model with optimal discretionary monetary policy, we calibrate key parameters--the central bank's preference parameters; the degree of forward-looking behavior in the determination of inflation and output; and the variances of inflation and output shocks--to match some broad characteristics of U.S. data. Our preferred parameterizations all imply a small concern for output stability but a large preference for interest rate smoothing, and a small degree of forward-looking behavior in price-setting but a large degree of forward-looking in the determination of output. We provide some intuition for these results and discuss their consequences for practical monetary policy analysis.