Quantifying quantitative literacy: Age heaping and the history of human capital

Age data frequently display excess frequencies at round or attractive ages, such as even numbers and multiples of five. This phenomenon of age heaping has been viewed as a problem in previous research, especially in demography and epidemiology. We see it as an opportunity and propose its use as a measure of human capital that can yield comparable estimates across a wide range of historical contexts. A simulation study yields methodological guidelines for measuring and interpreting differences in ageheaping, while analysis of contemporary and historical datasets demonstrates the existence of a robust correlation between age heaping and literacy at both the individual and aggregate level. To illustrate the method, we generate estimates of human capital in Europe over the very long run, which support the hypothesis of a major increase in human capital preceding the industrial revolution.

Subsampling inference in threshold autoregressive models

This paper discusses inference in self exciting threshold autoregressive (SETAR)models. Of main interest is inference for the threshold parameter. It iswell-known that the asymptotics of the corresponding estimator depend uponwhether the SETAR model is continuous or not. In the continuous case, thelimiting distribution is normal and standard inference is possible. Inthe discontinuous case, the limiting distribution is non-normal and cannotbe estimated consistently. We show valid inference can be drawn by theuse of the subsampling method. Moreover, the method can even be extendedto situations where the (dis)continuity of the model is unknown. In thiscase, also the inference for the regression parameters of the modelbecomes difficult and subsampling can be used advantageously there aswell. In addition, we consider an hypothesis test for the continuity ofthe SETAR model. A simulation study examines small sample performance.

Automated quantitative pupillometry for the prognostication of coma after cardiac arrest.

BACKGROUND: Sedation and therapeutic hypothermia (TH) delay neurological responses and might reduce the accuracy of clinical examination to predict outcome after cardiac arrest (CA). We examined the accuracy of quantitative pupillary light reactivity (PLR), using an automated infrared pupillometry, to predict outcome of post-CA coma in comparison to standard PLR, EEG, and somato-sensory evoked potentials (SSEP). METHODS: We prospectively studied over a 1-year period (June 2012-June 2013) 50 consecutive comatose CA patients treated with TH (33 °C, 24 h). Quantitative PLR (expressed as the % of pupillary response to a calibrated light stimulus) and standard PLR were measured at day 1 (TH and sedation; on average 16 h after CA) and day 2 (normothermia, off sedation: on average 46 h after CA). Neurological outcome was assessed at 90 days with Cerebral Performance Categories (CPC), dichotomized as good (CPC 1-2) versus poor (CPC 3-5). Predictive performance was analyzed using area under the ROC curves (AUC). RESULTS: Patients with good outcome [n = 23 (46 %)] had higher quantitative PLR than those with poor outcome [n = 27; 16 (range 9-23) vs. 10 (1-30) % at day 1, and 20 (13-39) vs. 11 (1-55) % at day 2, both p < 0.001]. Best cut-off for outcome prediction of quantitative PLR was <13 %. The AUC to predict poor outcome was higher for quantitative than for standard PLR at both time points (day 1, 0.79 vs. 0.56, p = 0.005; day 2, 0.81 vs. 0.64, p = 0.006). Prognostic accuracy of quantitative PLR was comparable to that of EEG and SSEP (0.81 vs. 0.80 and 0.73, respectively, both p > 0.20). CONCLUSIONS: Quantitative PLR is more accurate than standard PLR in predicting outcome of post-anoxic coma, irrespective of temperature and sedation, and has comparable prognostic accuracy than EEG and SSEP.

Comment to "Weak instruments robust tests in GMM and the New Keynesian Phillips curve" by Frank Kleibergen and Sophocles Mavroeidis

I discuss the identifiability of a structural New Keynesian Phillips curve when it is embedded in a small scale dynamic stochastic general equilibrium model. Identification problems emerge because not all the structural parameters are recoverable from the semi-structural ones and because the objective functions I consider are poorly behaved. The solution and the moment mappings are responsible for the problems.

GPS analysis of human locomotion: further evidence for long-range correlations in stride-to-stride fluctuations of gait parameters.

During free walking, gait is automatically adjusted to provide optimal mechanical output and minimal energy expenditure; gait parameters, such as cadence, fluctuate from one stride to the next around average values. It was described that this fluctuation exhibited long-range correlations and fractal-like patterns. In addition, it was suggested that these long-range correlations disappeared if the participant followed the beep of metronome to regulate his or her pace. Until now, these fractal fluctuations were only observed for stride interval, because no technique existed to adequately analyze an extended time of free walking. The aim of the present study was to measure walking speed (WS), step frequency (SF) and step length (SL) with high accuracy (<1 cm) satellite positioning method (global positioning system or GPS) in order to detect long-range correlations in the stride-to-stride fluctuations. Eight participants walked 30 min under free and constrained (metronome) conditions. Under free walking conditions, DFA (detrended fluctuation analysis) and surrogate data tests showed that the fluctuation of WS, SL and SF exhibited a fractal pattern (i.e., scaling exponent alpha: 0.5 < alpha < 1) in a large majority of participants (7/8). Under constrained conditions (metronome), SF fluctuations became significantly anti-correlated (alpha < 0.5) in all participants. However, the scaling exponent of SL and WS was not modified. We conclude that, when the walking pace is controlled by an auditory signal, the feedback loop between the planned movement (at supraspinal level) and the sensory inputs induces a continual shifting of SF around the mean (persistent anti-correlation), but with no effect on the fluctuation dynamics of the other parameters (SL, WS).

A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.

Inequalities for a new data-based method for selecting nonparametric density estimates

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

Quantitative Assessment of T1 Relaxation and Diffusion as a Prognostic Tool for Brain Development: A Longitudinal Preliminary Study on Preterm Babies

BACKGROUND: Despite major advances in care of premature infants, survivors exhibit mild cognitive deficits in around 40%. Beside severe intraventricular haemorrhages (IVH) and cystic periventricular leucomalacia (PVL), more subtle patterns such as grade I and II IVH, punctuate WM lesions and diffuse PVL might be linked to the cognitive deficits. Grey matter disease is also recognized to contribute to long-term cognitive impairment.¦OBJECTIVE: We intend to use novel MR techniques to study more precisely the different injury patterns. In particular MP2RAGE (magnetization prepared dual rapid echo gradient) produces high-resolution quantitative T1 relaxation maps. This contrast is known to reflect tissue anomalies such as white matter injury in general and dysmyelination in particular. We also used diffusion tensor imaging, a quantitative technique known to reflect white matter maturation and disease.¦DESIGN/METHODS: All preterm infants born under 30 weeks of GA were included. Serial 3T MR-imaging using a neonatal head-coil at DOL 3, 10 and at term equivalent age (TEA), using DTI and MP2RAGE sequences was performed. MP2RAGE generates a T1 map and allows calculating the relaxation time T1. Multiple measurements were performed for each exam in 12 defined white and grey matter ROIs.¦RESULTS: 16 patients were recruited: mean GA 27 2/7 w (191,2d SD±10,8), mean BW 999g (SD±265). 39 MRIs were realized (12 early: mean 4,83d±1,75, 13 late: mean 18,77d±8,05 and 14 at TEA: 88,91d±8,96). Measures of relaxation time T1 show a gradual and significant decrease over time (for ROI PLIC mean±SD in ms: 2100.53±102,75, 2116,5±41,55 and 1726,42±51,31 and for ROI central WM: 2302,25±79,02, 2315,02±115,02 and 1992,7±96,37 for early, late and TEA MR respectively). These trends are also observed in grey matter area, especially in thalamus. Measurements of ADC values show similar monotonous decrease over time.¦CONCLUSIONS: From these preliminary results, we conclude that quantitative MR imaging in very preterm infants is feasible. On the successive MP2RAGE and DTI sequences, we observe a gradual decrease over time in the described ROIs, representing the progressive maturation of the WM micro-structure and interestingly the same evolution is observed in the grey matter. We speculate that our study will provide normative values for T1map and ADC and might be a predictive factor for favourable or less favourable outcome.

Carbon and oxygen isotope study of hydrothermal carbonates in the zinc-lead deposits of the San Vicente district, central Peru: A quantitative modeling on mixing processes and CO2 degassing

Carbon and oxygen isotope studies of the host and gangue carbonates of Mississippi Valley-type zinc-lead deposits in the San Vicente District hosted in the Upper Triassic to Lower Jurassic dolostones of the Pucara basin (central Peru) were used to constrain models of the ore formation. A mixing model between an incoming hot saline slightly acidic radiogenic (Pb, Sr) fluid and the native formation water explains the overall isotopic variation (delta(13)C = - 11.5 to + 2.5 parts per thousand relative to PDB and delta(18)O = + 18.0 to + 24.3 parts per thousand relative to SMOW) of the carbonate generations. The dolomites formed during the main ore stage show a narrower range (delta(13)C = - 0.1 to + 1.7 parts per thousand and delta(18)O = + 18.7 to + 23.4 parts per thousand) which is explained by exchange between the mineralizing fluids and the host carbonates combined with changes in temperature and pressure. This model of fluid-rock interaction explains the pervasive alteration of the host dolomite I and precipitation of sphalerite I. The open-space filling hydrothermal white sparry dolomite and the coexisting sphalerite II formed by prolonged fluid-host dolomite interaction and limited CO2 degassing. Late void-filling dolomite III (or calcite) and the associated sphalerite III formed as the consequence of CO2 degassing and concomitant pH increase of a slightly acidic ore fluid. Widespread brecciation is associated to CO2 outgassing. Consequently, pressure variability plays a major role in the ore precipitation during the late hydrothermal events in San Vicente. The presence of native sulfur associated with extremely carbon-light calcites replacing evaporitic sulfates (e.g., delta(13)C = - 11.5 parts per thousand), altered native organic matter and heavier hydrothermal bitumen (from - 27.0 to - 23.0 parts per thousand delta(13)C) points to thermochemical reduction of sulfate and/or thiosulfate. The delta(13)C- and delta(18)O-values of the altered host dolostone and hydrothermal carbonates, and the carbon isotope composition of the associated organic matter show a strong regional homogeneity. These results coupled with the strong mineralogical and petrographic similarities of the different MVT occurrences perhaps reflects the fact that the mineralizing processes were similar in the whole San Vicente belt, suggesting the existence of a common regional mineralizing hydrothermal system with interconnected plumbing.

Biotic potential and reproductive parameters of Spodoptera eridania (Stoll) (Lepidoptera, Noctuidae) in the laboratory

Biotic potential and reprodutcive parameters of Spodoptera eridania (Stoll) (Lepidoptera, Noctuidae) in the laboratory: This study aimed to evaluate the biotic potential and reproductive parameters of Spodoptera eridania (Stoll, 1782) under controlled conditions (25 ± 1ºC, 70 ± 10% RH and 14 hour photophase). The longevity, pre-, post- and oviposition periods, fecundity and fertility of 15 couples was evaluated. The longevity of females (10.80 days) was not significantly higher than those of males (9.27 days). The mean durations of the pre, post and oviposition periods were 2.067, 0.600 and 8.133 days, respectively. The mean fecundity per female was 1,398 eggs and the mean fertility was 1,367.50 larvae. On average, females copulated 1.133 times. A strong positive correlation was observed between the number of mating and fecundity (r = 0.881, P <0.001). However a strong negative correlation was observed between the number of copulations and the duration of the pre-oviposition period (r = -0.826, P = 0.002) and longevity (r = -0.823, P = 0.001). The biotic potential of S. eridania was estimated at 1.894 x 10(25) individuals/female/year. The net reproductive rate (Ro) was 560.531 times per generation and the mean generation time (T) was 35.807 days. The intrinsic rate of increase (rm) was 0.177, with a finite rate of increase (l) of 1.193, per week

Weighted Euclidean biplots

We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.

Quality assessment of cardiovascular magnetic resonance in the setting of the European CMR registry: description and validation of standardized criteria.

BACKGROUND: Cardiovascular magnetic resonance (CMR) has become an important diagnostic imaging modality in cardiovascular medicine. However, insufficient image quality may compromise its diagnostic accuracy. We aimed to describe and validate standardized criteria to evaluate a) cine steady-state free precession (SSFP), b) late gadolinium enhancement (LGE), and c) stress first-pass perfusion images. These criteria will serve for quality assessment in the setting of the Euro-CMR registry. METHODS: Thirty-five qualitative criteria were defined (scores 0-3) with lower scores indicating better image quality. In addition, quantitative parameters were measured yielding 2 additional quality criteria, i.e. signal-to-noise ratio (SNR) of non-infarcted myocardium (as a measure of correct signal nulling of healthy myocardium) for LGE and % signal increase during contrast medium first-pass for perfusion images. These qualitative and quantitative criteria were assessed in a total of 90 patients (60 patients scanned at our own institution at 1.5T (n=30) and 3T (n=30) and in 30 patients randomly chosen from the Euro-CMR registry examined at 1.5T). Analyses were performed by 2 SCMR level-3 experts, 1 trained study nurse, and 1 trained medical student. RESULTS: The global quality score was 6.7±4.6 (n=90, mean of 4 observers, maximum possible score 64), range 6.4-6.9 (p=0.76 between observers). It ranged from 4.0-4.3 for 1.5T (p=0.96 between observers), from 5.9-6.9 for 3T (p=0.33 between observers), and from 8.6-10.3 for the Euro-CMR cases (p=0.40 between observers). The inter- (n=4) and intra-observer (n=2) agreement for the global quality score, i.e. the percentage of assignments to the same quality tertile ranged from 80% to 88% and from 90% to 98%, respectively. The agreement for the quantitative assessment for LGE images (scores 0-2 for SNR <2, 2-5, >5, respectively) ranged from 78-84% for the entire population, and 70-93% at 1.5T, 64-88% at 3T, and 72-90% for the Euro-CMR cases. The agreement for perfusion images (scores 0-2 for %SI increase >200%, 100%-200%,<100%, respectively) ranged from 81-91% for the entire population, and 76-100% at 1.5T, 67-96% at 3T, and 62-90% for the Euro-CMR registry cases. The intra-class correlation coefficient for the global quality score was 0.83. CONCLUSIONS: The described criteria for the assessment of CMR image quality are robust with a good inter- and intra-observer agreement. Further research is needed to define the impact of image quality on the diagnostic and prognostic yield of CMR studies.

Quantitative comparison of simulations of seismic wave propagation in heterogeneous poro-elastic media involving fluid-solid interfaces and in equivalent visco-elastic solids

There is increasing evidence to suggest that the presence of mesoscopic heterogeneities constitutes the predominant attenuation mechanism at seismic frequencies. As a consequence, centimeter-scale perturbations of the subsurface physical properties should be taken into account for seismic modeling whenever detailed and accurate responses of the target structures are desired. This is, however, computationally prohibitive since extremely small grid spacings would be necessary. A convenient way to circumvent this problem is to use an upscaling procedure to replace the heterogeneous porous media by equivalent visco-elastic solids. In this work, we solve Biot's equations of motion to perform numerical simulations of seismic wave propagation through porous media containing mesoscopic heterogeneities. We then use an upscaling procedure to replace the heterogeneous poro-elastic regions by homogeneous equivalent visco-elastic solids and repeat the simulations using visco-elastic equations of motion. We find that, despite the equivalent attenuation behavior of the heterogeneous poro-elastic medium and the equivalent visco-elastic solid, the seismograms may differ due to diverging boundary conditions at fluid-solid interfaces, where there exist additional options for the poro-elastic case. In particular, we observe that the seismograms agree for closed-pore boundary conditions, but differ significantly for open-pore boundary conditions. This is an interesting result, which has potentially important implications for wave-equation-based algorithms in exploration geophysics involving fluid-solid interfaces, such as, for example, wave field decomposition.

Extraction of soil water by plants: development and validation of a model

A quantitative model of water movement within the immediate vicinity of an individual root is developed and results of an experiment to validate the model are presented. The model is based on the assumption that the amount of water transpired by a plant in a certain period is replaced by an equal volume entering its root system during the same time. The model is based on the Darcy-Buckingham equation to calculate the soil water matric potential at any distance from a plant root as a function of parameters related to crop, soil and atmospheric conditions. The model output is compared against measurements of soil water depletion by rice roots monitored using γ-beam attenuation in a greenhouse of the Escola Superior de Agricultura "Luiz de Queiroz"/Universidade de São Paulo(ESALQ/USP) in Piracicaba, State of São Paulo, Brazil, in 1993. The experimental results are in agreement with the output from the model. Model simulations show that a single plant root is able to withdraw water from more than 0.1 m away within a few days. We therefore can assume that root distribution is a less important factor for soil water extraction efficiency.