Search

We present and discuss the advancements made in PyRETIS 3, the third instalment of our Python library for an efficient and user‐friendly rare event simulation, focused to execute molecular simulations with replica exchange transition interface sampling (RETIS) and its variations. Apart from a general rewiring of the internal code towards a more modular structure, several recently developed sampling strategies have been implemented. These include recently developed Monte Carlo moves to increase path decorrelation and convergence rate, and new ensemble definitions to handle the challenges of long‐lived metastable states and transitions with unbounded reactant and product states. Additionally, the post‐analysis software PyVisa is now embedded in the main code, allowing fast use of machine‐learning algorithms for clustering and visualising collective variables in the simulation data. [ABSTRACT FROM AUTHOR]

The paper uses structured machine learning regressions for nowcasting with panel data consisting of series sampled at different frequencies. Motivated by the problem of predicting corporate earnings for a large cross‐section of firms with macroeconomic, financial, and news time series sampled at different frequencies, we focus on the sparse‐group LASSO regularization which can take advantage of the mixed‐frequency time series panel data structures. Our empirical results show the superior performance of our machine learning panel data regression models over analysts' predictions, forecast combinations, firm‐specific time series regression models, and standard machine learning methods. [ABSTRACT FROM AUTHOR]

α‐1 acid glycoprotein (AGP) is one of the most abundant plasma proteins. It fulfills two important functions: immunomodulation, and binding to various drugs and receptors. These different functions are closely associated and modulated via changes in glycosylation and cancer missense mutations. From a structural point of view, glycans alter the local biophysical properties of the protein leading to a diverse ligand‐binding spectrum. However, glycans can typically not be observed in the resolved X‐ray crystallography structure of AGP due to their high flexibility and microheterogeneity, so limiting our understanding of AGP's conformational dynamics 70 years after its discovery. We here investigate how mutations and glycosylation interfere with AGP's conformational dynamics changing its biophysical behavior, by using molecular dynamics (MD) simulations and sequence‐based dynamics predictions. The MD trajectories show that glycosylation decreases the local backbone flexibility of AGP and increases the flexibility of distant regions through allosteric effects. We observe that mutations near the glycosylation site affect glycan's conformational preferences. Thus, we conclude that mutations control glycan dynamics which modulates the protein's backbone flexibility directly affecting its accessibility. These findings may assist in the drug design targeting AGP's glycosylation and mutations in cancer. [ABSTRACT FROM AUTHOR]

Aims: Identifying early right ventricular (RV) dysfunction and impaired vasodilator reserve is challenging in heart failure with preserved ejection fraction (HFpEF). We hypothesized that cardiac magnetic resonance (CMR)‐based exercise imaging and serial cyclic guanosine monophosphate (cGMP) measurements can identify dynamic RV‐arterial uncoupling and responsiveness to pulmonary vasodilators at early stages of the HFpEF syndrome. Methods and results: Patients with HFpEF (n = 16), impaired left ventricular relaxation due to concentric remodelling (LVCR, n = 7), and healthy controls (n = 8) underwent CMR at rest and during supine bicycle exercise with simultaneous measurements of central haemodynamics and circulating cGMP levels, before and after oral administration of 50 mg sildenafil. At rest, mean pulmonary artery pressures (mPAP) were higher in HFpEF, compared with LVCR and controls (27 ± 2, 18 ± 1, and 11 ± 1, respectively; P = 0.01), whereas biventricular volumes, heart rate, and stroke volume were similar. During exercise, LVCR and HFpEF had a greater increase in the ratio of mPAP over cardiac output than controls (5.50 ± 0.77 and 6.34 ± 0.86 vs. 2.24 ± 0.55 in controls, P = 0.005). The ratio of peak exercise to rest RV end‐systolic pressure‐volume, a surrogate of RV contractility, was significantly reduced in LVCR and HFpEF (2.32 ± 0.17 and 1.56 ± 0.08 vs. 3.49 ± 0.35 in controls, P < 0.001) and correlated with peak exercise VO2 (R2 = 0.648, P < 0.001). cGMP levels increased with exercise across the HFpEF spectrum (P < 0.05 vs. baseline), except when postcapillary pulmonary hypertension was present at rest (P = 0.73 vs. baseline). A single sildenafil administration failed to increase circulating cGMP levels and did not improve RV performance. Conclusion: Exercise CMR identifies impaired RV‐arterial coupling at an early stage of HFpEF. Circulating cGMP levels phenocopy the haemodynamic spectrum in HFpEF but fail to increase after phosphodiesterase type 5 inhibition, endorsing the need for alternative interventions to increase cGMP signalling in HFpEF. [ABSTRACT FROM AUTHOR]

Background: An isovolumetric intragastric balloon to continuously measure gastric phasic contractility was recently developed by us. We aimed to investigate the readout of this technique in relation to gastric content and gastric emptying. Methods: In this crossover investigation, the VIPUNTM Gastric Monitoring System, which comprises a double lumen nasogastric feeding tube with integrated intragastric balloon, was used to assess phasic gastric contractility by interpretation of the pressure in an isovolumetric balloon in 10 healthy subjects. Balloon pressure was recorded in fasted state, during a 2‐hour intragastric nutrient infusion (1 kcal/ml at 25, 75, or 250 ml/h) and 4 hours post‐infusion, and quantified as Gastric Balloon Motility Index (GBMI), ranging from 0 (no contractility) to 1 (maximal contractility). Gastric accumulation was quantified with magnetic resonance imaging and gastric emptying with a13C‐breath test. Results are expressed as mean(SD). Key Results: GBMI was significantly lower during infusion at 250 ml/h compared to baseline (0.13(0.05) versus 0.46(0.12)) and compared to infusion at 25 (0.54(0.21)) and 75 ml/h (0.43(0.20)), all P < 0.005. Gastric content volume was larger after infusion at 250 versus 75 ml/h (P < 0.001). Half‐emptying time and accumulation were both negatively correlated with postprandial contractility. Postprandial GBMI was significantly lower when GCV>0 ml compared to when the stomach was empty. Conclusions and Inferences: Enteral nutrition dose‐dependently decreased the contractility readout. This decrease was linked to gastric accumulation of enteral nutrition. [ABSTRACT FROM AUTHOR]

This paper studies Nasdaq market makers' activities during the one and one-half hour preopening period. Price discovery during the preopening is conducted via price signaling as opposed to the auction used to open the NYSE or the continuous market used during trading. In the absence of trades, Nasdaq dealers use crossed and locked inside quotes to signal to other market makers which direction the price should move. Furthermore, we find evidence of price leadership among market makers that bears little resemblance to their IPO/SEO lead underwriter participation. [ABSTRACT FROM AUTHOR]

We derive asymptotic properties of estimators and test statistics to determine—in a grouped data setting—common versus group‐specific factors. Despite the fact that our test statistic for the number of common factors, under the null, involves a parameter at the boundary (related to unit canonical correlations), we derive a parameter‐free asymptotic Gaussian distribution. We show how the group factor setting applies to mixed‐frequency data. As an empirical illustration, we address the question whether Industrial Production (IP) is still the dominant factor driving the U.S. economy using a mixed‐frequency data panel of IP and non‐IP sectors. We find that a single common factor explains 89% of IP output growth and 61% of total GDP growth despite the diminishing role of manufacturing. [ABSTRACT FROM AUTHOR]

The ability to precisely model methane absorption in the R(6) manifold of the 2ν3 band at atmospheric pressure and temperature conditions is a key technical requirement of the German‐French, Methane Remote Sensing Lidar (MERLIN) space mission. To this end, 27 high‐resolution and high‐signal‐to‐noise‐ratio absorption spectra of air‐broadened 12CH4 were recorded using a variable‐temperature frequency‐stabilized cavity ring‐down spectroscopy apparatus. The measurement conditions corresponded to sample temperature, pressure, and methane molar fraction values spanning 220–290 K, 4–110 kPa, and 4–7 μmol/mol, respectively. The measured spectra were fit using the sum of isolated Hartmann‐Tran profiles with the addition of line mixing. For each line within the manifold, all spectroscopic parameters at room temperature were fixed to our previously obtained values (Delahaye et al., 2016, https://doi.org/10.1002/2015JD024524) and only the temperature dependences of the model parameters were adjusted. The results show that the fitted model agrees with the measured methane absorption to better than 0.3% for the entire R(6) manifold spectral region and to within 0.1% at the online position of the MERLIN for all considered pressure and temperature conditions. A first comparison with ground‐based atmospheric measurement was also made showing significant improvement with respect to existing spectroscopic modeling of methane absorption. Key Points: Absorption cross sections of methane in the MERLIN spectral region is accurately measured and modeled for various P and T conditionsOur model is capable to represent measured absorption to within 0.1% at the MERLIN online positionComparison with atmospheric measurement shows significant improvement with respect to existing spectroscopic modeling of CH4 absorption [ABSTRACT FROM AUTHOR]

There is now considerable evidence suggesting that estimated betas of unconditional capital asset pricing models (CAPMs) exhibit statistically significant time variation. Therefore, many have advocated the use of conditional CAPMs. If we succeed in capturing the dynamics of beta risk, we are sure to outperform constant beta models. However, if the beta risk is inherently misspecified, there is a real possibility that we commit serious pricing errors, potentially larger than with a constant traditional beta model. In this paper we show that this is indeed the case, namely that pricing errors with constant traditional beta models are smaller than with conditional CAPMs. [ABSTRACT FROM AUTHOR]

We present a general and flexible Bayesian approach using uncertainty multipliers to simultaneously analyze the input and parameter uncertainty of a groundwater flow model with consideration of the heteroscedasticity of the groundwater level error. Groundwater recharge and groundwater abstraction multipliers are introduced to quantify the uncertainty of the spatially distributed input data of the groundwater model in addition to parameter uncertainty. The heteroscedasticity of the groundwater level error is also considered in our Bayesian approach by incorporating a new heteroscedastic error model. The proposed methodology is applied in an overexploited aquifer in Bangladesh where groundwater abstraction and recharge data are highly uncertain. The results of the study confirm that consideration of recharge and abstraction uncertainty through the use of recharge and abstraction multipliers is feasible even in a fully distributed physically based groundwater flow model. Heteroscedasticity is present in the groundwater level error and has an effect on the model predictions and parameter distributions. The input uncertainty affects the model predictions and parameter distributions and it is the dominant source of uncertainty in the groundwater flow prediction. Additionally, the approach described also provides a new way to optimize the spatially distributed recharge and abstraction data along with the parameter values under uncertain input conditions. We conclude that considering model input uncertainty along with parameter uncertainty and heteroscedasticity of the groundwater level error is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds. Key Points: Full Bayesian approach to simultaneously quantify input and parameter uncertainty of a groundwater flow modelNew heteroscedastic error model for groundwater level is includedUse of groundwater recharge and abstraction multipliers leads to physically more realistic results [ABSTRACT FROM AUTHOR]

Abstract: This paper provides new evidence on the effect of computerized individualized practice and instruction on language skills, more specifically on spelling. An individually randomized experiment among 7th grade students in the Netherlands is developed to study the effect of an adaptive digital homework tool on spelling performance. Using an instrumental variable approach to control for actual use of the digital tool, we show that there are small positive effects of practicing with an adaptive digital tool for spelling for 7th grade students. Effects are largest for low‐performing students. [ABSTRACT FROM AUTHOR]

Abstract: In order to better understand the water vapor (WV) intrusion into the tropical stratosphere, a mesoscale simulation of the tropical tropopause layer using the BRAMS (Brazilian version of Regional Atmospheric Modeling System (RAMS)) model is evaluated for a wet season. This simulation with a horizontal grid point resolution of 20 km × 20 km cannot resolve the stratospheric overshooting convection (SOC). Its ability to reproduce other key parameters playing a role in the stratospheric WV abundance is investigated using the balloon‐borne TRO‐Pico campaign measurements, the upper‐air soundings over Brazil, and the satellite observations by Aura Microwave Limb Sounder, Microwave Humidity Sounder, and Geostationary Operational Environmental Satellite 12. The BRAMS exhibits a good ability in simulating temperature, cold‐point, WV variability around the tropopause. However, the simulation is typically observed to be warmer by ∼2.0°C and wetter by ∼0.4 ppmv at the hygropause, which can be partly affiliated with the grid boundary nudging of the model by European Centre for Medium‐Range Weather Forecasts operational analyses. The modeled cloud tops show a good correlation (maximum cross‐correlation of ∼0.7) with Geostationary Operational Environmental Satellite 12. Furthermore, the overshooting cells detected by Microwave Humidity Sounder are observed at the locations, where 75% of the modeled cloud tops are higher than 11 km. Finally, the modeled inertia‐gravity wave periodicity and wavelength are comparable with those deduced from the radio sounding measurements during TRO‐Pico campaign. The good behavior of BRAMS confirms the SOC contribution in the WV abundance, and variability is of lesser importance than the large‐scale processes. This simulation can be used as a reference run for upscaling the impact of SOC at a continental scale for future studies. [ABSTRACT FROM AUTHOR]

This paper explores the effect of digital differentiation on student performance using a randomized experiment. The experiment is conducted in a second year biology class among 115 prevocational students in the Netherlands. Differentiation allowed students in the treatment group to work at three different levels. The results show that there is a significant effect of digital differentiation on the posttest score. This effect is robust to adding covariates such as students' ability, grade repetition, age, gender, class and average neighborhood income. There are no differential effects when dividing students in three groups, by ability. The results imply that differentiation in large classrooms is possible and beneficial for all students, once done digitally. [ABSTRACT FROM AUTHOR]

We examine the effects of mixed sampling frequencies and temporal aggregation on the size of commonly used tests for cointegration, and we find that these effects may be severe. Matching sampling schemes of all series generally reduces size distortion, and the nominal size is obtained asymptotically only when all series are skip sampled in the same way - for example, end-of-period sampling. We propose and analyse mixed-frequency versions of the cointegration tests in order to control the size when some high-frequency data are available. Otherwise, when no high-frequency data are available, we discuss controlling size using bootstrapped critical values. We test stock prices and dividends for cointegration as an empirical demonstration. [ABSTRACT FROM AUTHOR]

This paper describes a dataset with data from three individually randomized educational technology experiments on differentiation, formative testing and feedback during one school year for a group of 8th grade students in the Netherlands, using administrative data and the online motivation questionnaire of Boekaerts. The dataset consists of pre- and posttest scores for each experiment, as well as background information on the students, such as gender, age, ability, grade repetition and neighborhood characteristics. It also includes motivation of students. The dataset, or parts of it, could be interesting to use in future studies, focusing on effects of the use of educational technology, for comparison with similar and/or slightly different experiments, and for studies such as meta-analyses or replication studies, especially given the individual experimental setup. [ABSTRACT FROM AUTHOR]

Single mothers are vulnerable to living in poverty. The question of how to safeguard the economic status of single mothers in a context of increasing dual earnership is a crucial one. In the present study we addressed this issue by investigating the impact of child benefits on the poverty risk of single mothers in 15 European countries. We focused in particular on the design of child benefits and investigated whether targeting towards single mothers was associated with better poverty reduction. In doing so, we combined information on statutory child benefit entitlement with an empirical analysis of poverty reduction using survey data. We found that: (i) both spending effort and targeting are important to explain the effectiveness of child benefits in reducing single mother poverty; (ii) targeting is related to higher levels of poverty reduction independent of spending effort; yet (iii) it matters how targeting is done. [ABSTRACT FROM AUTHOR]

The methanol-to-olefin process is a showcase example of complex zeolite-catalyzed chemistry. At real operating conditions, many factors affect the reactivity, such as framework flexibility, adsorption of various guest molecules, and competitive reaction pathways. In this study, the strength of first principle molecular dynamics techniques to capture this complexity is shown by means of two case studies. Firstly, the adsorption behavior of methanol and water in H-SAPO-34 at 350 °C is investigated. Hereby an important degree of framework flexibility and proton mobility was observed. Secondly, the methylation of benzene by methanol through a competitive direct and stepwise pathway in the AFI topology was studied. Both case studies clearly show that a first-principle molecular dynamics approach enables unprecedented insights into zeolite-catalyzed reactions at the nanometer scale to be obtained. [ABSTRACT FROM AUTHOR]

Dimension reduction is often necessary when attempting to reach longer length and time scales in molecular simulations. It is realized by constraining degrees of freedom or by coarse-graining the system. When evaluating the accuracy of a dimensional reduction, there is a practical challenge: the models yield vectors with different lengths, making a comparison by calculating their dot product impossible. This article investigates mapping procedures for normal mode analysis. We first review a horizontal mapping procedure for the reduced Hessian techniques, which projects out degrees of freedom. We then design a vertical mapping procedure for the 'implosion' of the all-atom (AA) Hessian to a coarse-grained scale that is based upon vibrational subsystem analysis. This latter method derives both effective force constants and an effective kinetic tensor. Next, a series of metrics is presented for comparison across different scales, where special attention is given to proper mass-weighting. The dimension-dependent metrics, which require prior mapping for proper evaluation, are frequencies, overlap of normal mode vectors, probability similarity, Hessian similarity, collectivity of modes, and thermal fluctuations. The dimension-independent metrics are shape derivatives, elastic modulus, vibrational free energy differences, heat capacity, and projection on a predefined basis set. The power of these metrics to distinguish between reasonable and unreasonable models is tested on a toy alpha helix system and a globular protein; both are represented at several scales: the AA scale, a Gō-like model, a canonical elastic network model, and a network model with intentionally unphysical force constants. Published 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

SUMMARY The basic building blocks of a classic multigrid algorithm, which are essentially stencil computations, all have a low ratio of executed floating point operations per byte fetched from memory. This important ratio can be identified as the arithmetic intensity. Applications with a low arithmetic intensity are typically bounded by memory traffic and achieve only a small percentage of the theoretical peak performance of the underlying hardware. We propose a polynomial Chebyshev smoother, which we implement using cache-aware tiling, to increase the arithmetic intensity of a multigrid V-cycle. This tiling approach involves a trade-off between redundant computations and cache misses. Unlike common conception, we observe optimal performance for higher degrees of the smoother. The higher-degree polynomial Chebyshev smoother can be used to smooth more than just the upper half of the error frequencies, leading to better V-cycle convergence rates. Smoothing more than the upper half of the error spectrum allows a more aggressive coarsening approach where some levels in the multigrid hierarchy are skipped. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Images of the morphology of a polygonal network of ice-wedge casts are a valuable aid to paleoclimatological reconstructions. Usually such images are obtained by aerial photography showing polygonal crop marks reflecting textural differences between wedge filling and host material. Our objective was to investigate an alternative method by measuring the soil apparent electrical conductivity, (ECa) with an electromagnetic induction (EMI) sensor. Based on an aerial photograph showing polygonal crop marks in an agricultural field in Belgium. a test area of 0.63 ha was selected. A small part of the test area (6 by 6 m) was excavated revealing a clear pattern of ice-wedge casts. The wedges penetrated clay-rich Tertiary marine sediments, covered by a 0.6-m layer of eolian sandy sediments, and were associated with the permafrost during the last glacial period. We took 94 subsoil (0.6-0.8 m) samples distributed over the test area and analyzed their texture. The results showed a clear difference between the Eocene host material (on average 21% clay) and the Quaternary wedge filling (on average 6% clay). The test area was surveyed with an EMI sensor (we used an EM38DD) which resulted in an accurate image of the polygonal network. We concluded that an EMI survey is an appropriate technique to image the morphology of a polygonal network of subsoil ice-wedge casts. A final perspective comprises the strong heterogeneity of the subsoil, since nearly half of the subsoil consists of ice-wedge material. This might open perspectives for precision agriculture in such landscapes. [ABSTRACT FROM AUTHOR]

Using a unique data set of detailed balance sheet information on mutual funds, we find that most mutual funds using derivatives do so to a very limited extent that has little discernable impact on returns. However, there exist two types of funds that make more extensive use of derivatives, global funds and specialized domestic equity funds. The risk and return characteristics of these two groups of funds are significantly different from funds employing derivatives sparingly or not at all. Fund managers time their use of derivatives in response to past returns. Evidence during the financial crisis of August 1998 supports the hypothesis that the effects of derivative use are most pronounced during the periods of extreme movement. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:629-658, 2011 [ABSTRACT FROM AUTHOR]

Standard normal mode analysis becomes problematic for complex molecular systems, as a result of both the high computational cost and the excessive amount of information when the full Hessian matrix is used. Several partial Hessian methods have been proposed in the literature, yielding approximate normal modes. These methods aim at reducing the computational load and/or calculating only the relevant normal modes of interest in a specific application. Each method has its own (dis)advantages and application field but guidelines for the most suitable choice are lacking. We have investigated several partial Hessian methods, including the Partial Hessian Vibrational Analysis (PHVA), the Mobile Block Hessian (MBH), and the Vibrational Subsystem Analysis (VSA). In this article, we focus on the benefits and drawbacks of these methods, in terms of the reproduction of localized modes, collective modes, and the performance in partially optimized structures. We find that the PHVA is suitable for describing localized modes, that the MBH not only reproduces localized and global modes but also serves as an analysis tool of the spectrum, and that the VSA is mostly useful for the reproduction of the low frequency spectrum. These guidelines are illustrated with the reproduction of the localized amine-stretch, the spectrum of quinine and a bis-cinchona derivative, and the low frequency modes of the LAO binding protein. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa is a ubiquitous Gram-negative bacterium, which is also able to cause severe opportunistic infections in humans. The colonization of the host is importantly affected by the production of the high-affinity iron (III) scavenging peptidic siderophore pyoverdine. The species P. aeruginosa can be divided into three subgroups (‘siderovars’), each characterized by the production of a specific pyoverdine and receptor (FpvA). We used a multiplex PCR to determine the FpvA siderovar on 345 P. aeruginosa strains from environmental or clinical origin. We found about the same proportion of each type in clinical strains, while FpvA type I was slightly over-represented (49%) in environmental strains. Our multiplex PCR also detected the presence or absence of an additional receptor for type I pyoverdine (FpvB). The fpvB gene was in fact present in the vast majority of P. aeruginosa strains (93%), regardless of their siderovar or their origin. Finally, molecular analyses of fpvA and fpvB genes highlighted a complex evolutionary history, probably linked to the central role of iron acquisition in the ecology and virulence of P. aeruginosa. [ABSTRACT FROM AUTHOR]

We report on quartz Optically Stimulated Luminescence (OSL) dating of the infill of 14 relict sand wedges and composite-wedge pseudomorphs at 5 different sites in Flanders, Belgium. A laboratory dose recovery test indicates that the single-aliquot regenerative-dose (SAR) procedure is suitable for our samples (measured to a given dose ratio 0.980 ± 0.005; n=139). Completeness of resetting of the wedge infill of two samples was confirmed by single-grain analyses. The suite of optical ages indicates that repeated thermal contraction cracking, degradation and infilling with wind-blown sediment appear to have been commonplace in Flanders during the Late Pleniglacial (Oxygen Isotope Stage 2; OIS2); more specifically, around the Last Glacial Maximum (LGM, ∼21 kyr ago) and the transition period between the LGM and the start of the Lateglacial (∼15 kyr ago). Optical dating at one site has revealed two significantly older wedge levels, the younger inset into the older; the younger wedge has an age of 36 ± 4 kyr (Middle Pleniglacial; OIS3), the older wedge 129 ± 11 kyr, which points to formation during the Late Saalian (OIS6). Our OSL ages of the wedges and host sediments bracket formation of the BGB (Beuningen Gravel Bed: a widespread deflation horizon in northwestern Europe) at between ∼15 and 18 kyr; this is in good agreement with previous OSL dating studies. We conclude that optical dating using quartz SAR OSL establishes an absolute chronology for these periglacial phenomena and allows secure palaeoenvironmental reconstructions to be made. [ABSTRACT FROM AUTHOR]

We consider a log-linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different methodologies: time series regressions of 21 US metropolitan areas and mixed data sampling (MIDAS) regressions with aggregate REIT returns. Both approaches confirm that the cap rate is related to fluctuations in future returns. We also investigate the provenance of the predictability. Based on the model, we decompose fluctuations in the cap rate into three parts: (i) local state variables (demographic and local economic variables); (ii) growth in rents; and (iii) an orthogonal part. About 30% of the fluctuation in the cap rate is explained by the local state variables and the growth in rents. We use the cap rate decomposition into our predictive regression and find a positive relation between fluctuations in economic conditions and future returns. However, a larger and significant part of the cap rate predictability is due to the orthogonal part, which is unrelated to fundamentals. This implies that economic conditions, which are also used in hedonic pricing of real estate, cannot fully account for future movements in returns. We conclude that commercial real estate prices are better modelled as financial assets and that the discounted rent model might be more suitable than traditional hedonic models, at least at an aggregate level. [ABSTRACT FROM AUTHOR]

In this paper, an overview is given of the composition of 30 commercially available parrot seed mixtures. As parrots dehull the seeds, the analysis of the total seed mixture tends to differ from that of the ingested feed. Statistical evaluation and comparison of the dehulled seeds vs. the whole seeds indicates that most parrot species are fed a diet rich in fat (31.7 ± 13.1% crude fat) and energy (22.4 ± 2.9 MJ ME/kg). As the analysis of the total seed mixtures underestimates fat and energy content of the ingested feed, it is suggested that researchers, bird nutritionists and bird food producers should calculate diets based on the analysis of the dehulled seeds. Finally, the calculated data were compared with the composition of formulated pelleted/extruded diets on the market. These data indicate that the energy density of most diets (15.6 ± 1.4 MJ ME/kg) is far below the energy density of common seed mixtures. [ABSTRACT FROM AUTHOR]

Summary Bacteria can have population structures ranging from the fully sexual to the highly clonal. Despite numerous studies, the population structure of Pseudomonas aeruginosa is still somewhat contentious. We used a polyphasic approach in order to shed new light on this issue. A data set consisting of three outer membrane (lipo)protein gene sequences (oprI , oprL and oprD ), a DNA-based fingerprint (amplified fragment length polymorphism), serotype and pyoverdine type of 73 P. aeruginosa clinical and environmental isolates, collected across the world, was analysed using biological data analysis software. We observed a clear mosaicism in the results, non-congruence between results of different typing methods and a microscale mosaic structure in the oprD gene. Hence, in this network, we also observed some clonal complexes characterized by an almost identical data set. The most recent clones exhibited serotypes O1, 6, 11 and 12. No obvious correlation was observed between these dominant clones and habitat or, with the exception of some recent clones, geographical origin. Our results are consistent with, and even clarify, some seemingly contradictory results in earlier epidemiological studies. Therefore, we suggest an epidemic population structure for P. aeruginosa , comparable with that of Neisseria meningitidis , a superficially clonal structure with frequent recombinations, in which occasionally highly successful epidemic clones arise. [ABSTRACT FROM AUTHOR]

In this paper we examine the prevalence of data, specification, and parameter uncertainty in the formation of simple rules that mimic monetary policymaking decisions. Our approach is to build real-time data sets and simulate a real-time policy-setting environment in which we assume that policy is captured by movements in the actual federal funds rate, and then to assess what sorts of policy rule models and what sorts of data best explain what the Federal Reserve actually did. This approach allows us not only to track the performance of alternative rules over time (hence facilitating a type of model selection among competing rules), but also to more generally assess the importance of the data revision process in the formation of macroeconomic time series models. From the perspective of real-time data, our results suggest that the use of data that are erroneous, in the sense that they were not available at the time decisions could have been made based on forecasts from the rules, can lead to the selection of quantitatively different models. From the perspective of finding a rule that best approximates what the Federal Reserve Board (Fed) has actually done (and hence from the perspective of finding a rule that best approximates what the Fed will do in the future), we find that (i) our version of "calibration" is better than naïve estimation, although both are dominated by an approach to rule formation based on the use of adaptive least-squares learning; (ii) rules based on data that are not seasonally adjusted are more reliable than those based on seasonally adjusted data; and (iii) rules based solely on preliminary data do not minimize mean square forecast error risk. In particular, early releases of data can be noisy, and for this reason it is useful to also use data that have been revised when making decisions using policy rules. [ABSTRACT FROM AUTHOR]

Time series are demeaned when sample autocorrelation functions are computed. By the same logic it would seem appealing to remove seasonal means from seasonal time series before computing sample autocorrelation functions. Yet, standard practice is only to remove the overall mean and ignore the possibility of seasonal mean shifts in the data. Whether or not time series are seasonally demeaned has very important consequences on the asymptotic behavior of autocorrelation functions. The effect on the asymptotic distribution of seasonal mean shifts and their removal is investigated and the practical consequences of these theoretical developments are discussed. We also examine the small sample behavior of autocorrelation function estimates through Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Evaluates the performance of proposed tests for structural breaks in the conditional variance dynamics of asset returns. Use of high-frequency data; Identification of the number and location of multiple breaks; Size and power of the tests for detecting breaks in the conditional variance.

To forecast the turnaround of an economy we do not usually take seasonal effects into account. Recently, the author showed that business cycle turning points as well as durations do not appear to be uniformly distributed throughout the year (see Ghysels, 1991a). In this paper we suggest improving the forecasting performance of turning-point predictions by adopting periodic hazard models. Following Diebold and Rudebusch (1989), we construct several formal probability models and score their prediction performance. The results indicate that for sequential forecasting rules significant gains can be made by exploiting periodicities in turning-point probabilities. [ABSTRACT FROM AUTHOR]

Presents a generalized predictive testing procedure for structural stability in nonlinear dynamic simultaneous equations model. Attractive features of the test; Two alternative ways of dealing with nonnormal disturbances; Applications of the techniques suggested to a VAR model and to consumption-based asset pricing models.

A predictive test for parameter stability of GMM estimates is studied. The test is based on examining whether parameter estimates of one subsample can be used to predict over the other subsample. It applies to a wide variety of dynamic, nonlinear simultaneous equation models for the wide class of inference methods covered by GMM. The asymptotic properties and local power are derived. It is shown that the test has equal asymptotic power against local alternatives in both subsamples regardless of which subsample is conditioned on. The test is also compared with tests proposed by Andrews and Fair (1988). [ABSTRACT FROM AUTHOR]

Provides a statistical analysis of the Canadian budget process with information provided by the Department of Finance. Description of methodology used in analysis; Types of illustrations used in analysis, and why they were used; Observations made with applications of tests to fiscal forecasts; Detailed information on analysis.

Presents information on a study on modelling seasonality in non-linear analysis in the context of econometry. Description of non-linear time series models and seasonality; Periodic regime-switching models; Methodology; Conclusions of the study.

The article focuses on identification and prediction of economic recessions using time-frequency functional models. It argues that the model being used by several researchers including Holan, Yang, and Matheson provides a better forecast than models that excludes daily frequency variable. It adds that their framework can be represented into a Monitoring, Intrusion, Detection, Administration System (MIDAS) extension of a probit model.

The free energy surface of zeolite ‐ catalyzed reactions at real operating conditions is typically complex. As such, techniques that allow sampling of larger portions of the potential and free energy landscape are required to mimic experimental conditions as closely as possible. Various points on the free energy surface can be connected by a multitude of reaction paths. Mapping the free energy surface by advanced molecular dynamics simulations of a zeolite ‐ catalyzed reaction can hence be compared with studying a map in an atlas to discover the possible means of transport to travel between two cities. For the complete story see the Full Paper on page 9385 by B. Ensing, V. Van Speybroeck et al. [ABSTRACT FROM AUTHOR]