Blood flow rate in jejunal ischemia-reperfusion injury

We examined changes in the blood flow rate in the course of jejunal ischemic injury using a laser Doppler flowmeter. For this purpose, we designed a sensor holding system, which involved the fixation of the sensor to the jejunum and allowed their movements to be synthronized. When the jejunum was reperfused after 10 min of ischemia, the blood flow rate markedly increased and then gradually decreased to the initial level. A 30-min period of ischemia produced the slowest recovery of the blood flow rate. This system could be useful for monitoring the blood flow rate in different anatomical regions.     

The importance of interest rates for forecasting the exchange rate

This study compares the forecasting performance of a structural exchange rate model that combines the purchasing power parity condition with the interest rate differential in the long run, with some alternative exchange rate models. The analysis is applied to the Norwegian exchange rate. The long‐run equilibrium relationship is embedded in a parsimonious representation for the exchange rate. The structural exchange rate representation is stable over the sample and outperforms a random walk in an out‐of‐sample forecasting exercise at one to four horizons. Ignoring the interest rate differential in the long run, however, the structural model no longer outperforms a random walk. Copyright © 2006 John Wiley _ Sons, Ltd.     

Random walk hypothesis in exchange rate reconsidered

An econometric model for exchange rate based on the behavior of dynamic international asset allocation is considered. The capital movement intensity index is constructed from the adjustment of a fully hedged international portfolio. Including this index as an additional explanatory variable helps to explain the fluctuation of the exchange rate and predict better than the competing random walk model. Supporting empirical evidence is found in Germany–USA, Japan–USA, Singapore–USA and Taiwan–USA exchange markets. Copyright © 2006 John Wiley & Sons, Ltd.     

Model instability in predictive exchange rate regressions

In this paper we aim to improve existing empirical exchange rate models by accounting for uncertainty with respect to the underlying structural representation. Within a flexible Bayesian framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with transitions across regimes being driven by a Markov process. We assume a time-varying transition probability matrix with transition probabilities depending on a measure of the monetary policy stance of the central bank at home and in the USA. We apply this model to a set of eight exchange rates against the US dollar. In a forecasting exercise, we show that model evidence varies over time, and a model approach that takes this empirical evidence seriously yields more accurate density forecasts for most currency pairs considered.     

Short-term forecasting of the US unemployment rate

This paper aims to assess whether Google search data are useful when predicting the US unemployment rate among other more traditional predictor variables. A weekly Google index is derived from the keyword “unemployment” and is used in diffusion index variants along with the weekly number of initial claims and monthly estimated latent factors. The unemployment rate forecasts are generated using MIDAS regression models that take into account the actual frequencies of the predictor variables. The forecasts are made in real time, and the forecasts of the best forecasting models exceed, for the most part, the root mean squared forecast error of two benchmarks. However, as the forecasting horizon increases, the forecasting performance of the best diffusion index variants decreases over time, which suggests that the forecasting methods proposed in this paper are most useful in the short term.     

Age-related disappearance of Mayer-like heart rate waves

Healthy elderly subjects (greater than or equal to 65 years) did not show the prominent low frequency (0.07-0.09 Hz) heart rate oscillations (Mayer waves) recorded in young adults immediately following passive upright tilt. This difference may be related to altered autonomic function with physiologic aging.     

Transmural pressure as a determinant of basic intrinsic heart rate

Summary It was observed the heart rate was minimum at zero transmural pressure. The mean heart rate at zero transmural pressure was 23±5/min. This mean heart rate increased from 23±5/min to a peak value of 40±6/min (74% acceleratin) when the transmural pressure was raised from 0 to +4 mm Hg and to a similar peak value of 36±8/min (56% acceleration) when the transmural pressure was lowered from 0 to –4 mm Hg. The peak values attained at ±4 mm Hg were higly significant (p<0.001). It is concluded that the heart rate at zero transmural pressure represents the basic intrinsic pacemaker frequency independent of neural, humoral, thermal and haemodynamically induced mechanical influences.     

Kinetic analysis of lactate dehydrogenase using integrated rate equations

The reaction catalyzed by lactate dehydrogenase was analyzed under fully second-order conditions using integrated rate equations. A two-step regression analysis was utilized to fit twenty-one progress curves repeated in sextuplicate to the general mechanism second-order integrated rate equation with additional terms for substrate inhibition. The fitting error was less than one percent. The resulting kinetic constants support a ternary complex mechanism; in no case were constants supporting another mechanism predicted. The inhibition constant for oxamate was also determined.     

Time-series forecasting of the German unemployment rate

The purpose of the paper is to investigate the accuracy of forecasts derived from univariate and multivariate time-series models. An iterative method to adjust for impact assessment in univariate ARIMA models is discussed and illustrated for the German unemployment rate. Finally, we also examine the pros and cons of the impact assessment model in comparison with VAR models.     

Modelling the frequency and severity of extreme exchange rate returns

Risk managers are often concerned about tail probabilities of asset return distributions, in particular the frequency and severity of extreme returns. In this article, we propose a model that integrates extreme value theory and point processes to model the frequency and severity of exchange rate returns. The proposed model is applied to daily spot exchange rate series and the parameters of interest, such as the tail index, the mean size and rate of occurrence of extreme returns, are estimated using maximum likelihood estimation. We study the impact of recent currency crises on the frequency and severity of the series and find that, during 1995–9, the frequency of extreme daily Japanese yen–US dollar spot exchange rate returns increases twofold, and the time duration of high volatility persists longer for the Japanese yen series than for the Swiss franc and Danish krone series. Copyright © 2001 John Wiley & Sons, Ltd.     

Exchange rate forecasting and the performance of currency portfolios

We examine the potential gains of using exchange rate forecast models and forecast combination methods in the management of currency portfolios for three exchange rates: the euro versus the US dollar, the British pound, and the Japanese yen. We use a battery of econometric specifications to evaluate whether optimal currency portfolios implied by trading strategies based on exchange rate forecasts outperform single currencies and the equally weighted portfolio. We assess the differences in profitability of optimal currency portfolios for different types of investor preferences, two trading strategies, mean squared error‐based composite forecasts, and different forecast horizons. Our results indicate that there are clear benefits of integrating exchange rate forecasts from state‐of‐the‐art econometric models in currency portfolios. These benefits vary across investor preferences and prediction horizons but are rather similar across trading strategies.     

Kuhnian theory-choice and virtue convergence: Facing the base rate fallacy

Perhaps the strongest argument for scientific realism, the no-miracles-argument, has been said to commit the so-called base rate fallacy. The apparent elusiveness of the base rate of true theories has even been said to undermine the rationality of the entire realism debate. On the basis of the Kuhnian picture of theory choice, I confront this challenge by arguing that a theory is likely to be true if it possesses multiple theoretical virtues and is embraced by numerous scientists–even when the base rate converges to zero.     

连续冲洗式沉沙池截沙率试验研究

对连续冲洗式沉沙池截沙率进行分析研究，并在一维流超饱和输沙法基础上，得出连续冲洗式沉沙池池段分组截沙率、工作段分组截沙率、大于某粒径级截沙率以及总截沙率的近似计算方法。为验证该方法的实用性，对连续冲洗式沉沙池的截沙率进行模型试验，试验结果表明：采用近似处理的截沙率计算公式，其计算结果与实测结果吻合较好，在符合计算精度的前提下，可以用于实际工程计算。     

A latent variable approach to forecasting the unemployment rate

A forecasting model for unemployment is constructed that exploits the time series properties of unemployment while satisfying the economic relationships specified by Okun's law and the Phillips curve. In deriving the model, we jointly consider the problem of obtaining estimates of the unobserved potential rate of unemployment consistent with Okun's law and the Phillips curve, and associating the potential rate of unemployment with actual unemployment. The empirical example shows that the model clearly outperforms alternative forecasting procedures typically used to forecast unemployment. Copyright © 2011 John Wiley & Sons, Ltd.     

Does the miracle argument embody a base rate fallacy?

One way to reconstruct the miracle argument for scientific realism is to regard it as a statistical inference: since it is exceedingly unlikely that a false theory makes successful predictions, while it is rather likely that an approximately true theory is predictively successful, it is reasonable to infer that a predictively successful theory is at least approximately true. This reconstruction has led to the objection that the argument embodies a base rate fallacy: by focusing on successful theories one ignores the vast number of false theories some of which will be successful by mere chance.In this paper, I shall argue that the cogency of this objection depends on the explanandum of the miracle argument. It is cogent if what is to be explained is the success of a particular theory. If, however, the explanandum of the argument is the distribution of successful predictions among competing theories, the situation is different. Since the distribution of accidentally successful predictions is independent of the base rate, it is possible to assess the base rate by comparing this distribution to the empirically found distribution of successful predictions among competing theories.     

Estimating daily seasonality in foreign exchange rate changes

Combining time- and frequency-domain analysis demonstrates considerable improvement in modelling seasonal patterns in daily exchange rate changes. A high-pass filter in the frequency domain is used, followed by the usual time-domain analysis with GARCH models, to estimate day-of-the-week effects in the spot returns on five exchanges against US dollars and the results are seen to compare favourably with those from a pure time-domain GARCH approach.     

A threshold model for the French franc/deutschmark exchange rate

The behaviour of the French franc/deutschmark exchange rate is examined in this paper. During the time period studied, these currencies were constrained to lie within prescribed bands relative to one another and the usual random walk explanation of the exchange rate may not be appropriate. The data are examined for evidence of non-linear structure and it is shown that a piecewise linear SETAR model provides a better explanation and superior forecasting performance than a random walk.     

Forecasting the 10‐year US Treasury rate

This study compares the performance of two forecasting models of the 10‐year Treasury rate: a random walk (RW) model and an augmented‐autoregressive (A‐A) model which utilizes the information in the expected inflation rate. For 1993–2008, the RW and A‐A forecasts (with different lead times and forecast horizons) are generally unbiased and accurately predict directional change under symmetric loss. However, the A‐A forecasts outperform the RW, suggesting that the expected inflation rate (as a leading indicator) helps improve forecast accuracy. This finding is important since bond market efficiency implies that the RW forecasts are optimal and cannot be improved. Copyright © 2009 John Wiley & Sons, Ltd.     

Infusion at constant rate in vivo

Summary Infusion can be maintained at a constant rate over an extended period of time in vivo by the use of an implanted diffusion chamber. Plasma⁵⁹Fe was maintained at a constant level for 10 days when infused from a s.c. implant. Injected isotope was cleared exponentially with a half-clearance time of about 8 h.This study was supported in part by grants from the U.S. PHS, ROI FD 00800, and the American Cancer Society, P-5134.Acknowledgments. We thank M. Byers and J.A. Mason for expert technical assistance.     

Google Trends and the forecasting performance of exchange rate models

In this paper, we use Google Trends data for exchange rate forecasting in the context of a broad literature review that ties the exchange rate movements with macroeconomic fundamentals. The sample covers 11 OECD countries’ exchange rates for the period from January 2004 to June 2014. In out‐of‐sample forecasting of monthly returns on exchange rates, our findings indicate that the Google Trends search query data do a better job than the structural models in predicting the true direction of changes in nominal exchange rates. We also observed that Google Trends‐based forecasts are better at picking up the direction of the changes in the monthly nominal exchange rates after the Great Recession era (2008–2009). Based on the Clark and West inference procedure of equal predictive accuracy testing, we found that the relative performance of Google Trends‐based exchange rate predictions against the null of a random walk model is no worse than the purchasing power parity model. On the other hand, although the monetary model fundamentals could beat the random walk null only in one out of 11 currency pairs, with Google Trends predictors we found evidence of better performance for five currency pairs. We believe that these findings necessitate further research in this area to investigate the extravalue one can get from Google search query data.