Sources of selection bias in evaluating social programs: An interpretation of conventional measures and evidence on the effectiveness of matching as a program evaluation method

This paper decomposes the conventional measure of selection bias in observational studies into three components. The first two components are due to differences in the distributions of characteristics between participant and nonparticipant (comparison) group members: the first arises from differences in the supports, and the second from differences in densities over the region of common support. The third component arises from selection bias precisely defined. Using data from a recent social experiment, we find that the component due to selection bias, precisely defined, is smaller than the first two components. However, selection bias still represents a substantial fraction of the experimental impact estimate. The empirical performance of matching methods of program evaluation is also examined. We find that matching based on the propensity score eliminates some but not all of the measured selection bias, with the remaining bias still a substantial fraction of the estimated impact. We find that the support of the distribution of propensity scores for the comparison group is typically only a small portion of the support for the participant group. For values outside the common support, it is impossible to reliably estimate the effect of program participation using matching methods. If the impact of participation depends on the propensity score, as we find in our data, the failure of the common support condition severely limits matching compared with random assignment as an evaluation estimator.

Chemical phenotype matching between a plant and its insect herbivore

Two potential outcomes of a coevolutionary interaction are an escalating arms race and stable cycling. The general expectation has been that arms races predominate in cases of polygenic inheritance of resistance traits and permanent cycling predominates in cases in which resistance is controlled by major genes. In the interaction between Depressaria pastinacella, the parsnip webworm, and Pastinaca sativa, the wild parsnip, traits for plant resistance to insect herbivory (production of defensive furanocoumarins) as well as traits for herbivore “virulence” (ability to metabolize furanocoumarins) are characterized by continuous heritable variation. Furanocoumarin production in plants and rates of metabolism in insects were compared among four midwestern populations; these traits then were classified into four clusters describing multitrait phenotypes occurring in all or most of the populations. When the frequency of plant phenotypes belonging to each of the clusters is compared with the frequency of the insect phenotypes in each of the clusters across populations, a remarkable degree of frequency matching is revealed in three of the populations. That frequencies of phenotypes vary among populations is consistent with the fact that spatial variation occurs in the temporal cycling of phenotypes; such processes contribute in generating a geographic mosaic in this coevolutionary interaction on the landscape scale. Comparisons of contemporary plant phenotype distributions with phenotypes of herbarium specimens collected 9–125 years ago from across a similar latitudinal gradient, however, suggest that for at least one resistance trait—sphondin concentration—interactions with webworms have led to escalatory change.

Random circular permutation of genes and expressed polypeptide chains: application of the method to the catalytic chains of aspartate transcarbamoylase.

Recent studies on proteins whose N and C termini are in close proximity have demonstrated that folding of polypeptide chains and assembly of oligomers can be accomplished with circularly permuted chains. As yet no methodical study has been conducted to determine how extensively new termini can be introduced and where such termini cannot be tolerated. We have devised a procedure to generate random circular permutations of the catalytic chains of Escherichia coli aspartate transcarbamoylase (ATCase; EC 2.1.3.2) and to select clones that produce active or stable holoenzyme containing permuted chains. A tandem gene construct was made, based on the desired linkage between amino acid residues in the C- and N-terminal regions of the polypeptide chain, and this DNA was treated with a suitable restriction enzyme to yield a fragment containing the rearranged coding sequence for the chain. Circularization achieved with DNA ligase, followed by linearization at random with DNase I, and incorporation of the linearized, repaired, blunt-ended, rearranged genes into a suitable plasmid permitted the expression of randomly permuted polypeptide chains. The plasmid with appropriate stop codons also contained pyrI, the gene encoding the regulatory chain of ATCase. Colonies expressing detectable amounts of ATCase-like molecules containing permuted catalytic chains were identified by an immunoblot technique or by their ability to grow in the absence of pyrimidines in the growth medium. Sequencing of positive clones revealed a variety of novel circular permutations. Some had N and C termini within helices of the wild-type enzyme as well as deletions and insertions. Permutations were concentrated in the C-terminal domain and only few were detected in the N-terminal domain. The technique, which is adaptable generally to proteins whose N and C termini are near each other, can be of value in relating in vivo folding of nascent, growing polypeptide chains to in vitro renaturation of complete chains and determining the role of protein sequence in folding kinetics.

Matching research and innovation policies in EU countries. Bruegel Working Paper 2015/16, December 2015

The European Union has prioritised the pursuit of innovation based growth and targeting of resources to promote research and development, but performance on innovation remains weak.With the lack of results comes fatigue, waning interest and mounting criticism about policy. Should the EU abandon its ambition to become the most innovative region in the world?We examine EU member state research and innovation policies. We assess whether the deployment of innovation policy instruments in EU countries matches their innovation capacity performance relative to other EU countries.We find a relative homogeneity of policy mixes in EU countries, despite the fairly wide and stable differences in their innovation capacities.Our analysis therefore provides a rationale for a more comprehensive review of innovation policy mixes to assess their adequacy in addressing country specific innovation challenges.

MOREMATA: Stata module (Mata) to provide various functions

This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().

Assortative matching of exporters and importers

This paper uses the opening of the US textile/apparel market for China at the end of the Multifibre Arrangement in 2005 as a natural experiment to provide evidence for positive assortative matching of Mexican exporting firms and US importing firms by their capability. We identify three findings for liberalized products by comparing them to other textile/apparel products: (1) US importers switched their Mexican partners to those making greater preshock exports, whereas Mexican exporters switched their US partners to those making fewer preshock imports; (2) for firms who switched partners, trade volume of the old partners and the new partners are positively correlated; (3) small Mexican exporters stop exporting. We develop a model combining Becker-type matching of final producers and suppliers with the standard Melitz-type model to show that these findings are consistent with positive assortative matching but not with negative assortative matching or purely random matching. The model indicates that the findings are evidence for a new mechanism of gain from trade.

Stable carbon isotopes of Planulina wuellerstorfi of sediment core MD01-2444

The observation that Greenland and Antarctic temperatures have followed a specific 'asymmetrical' pattern on millennial time-scales sets rigid constraints on any viable theory of abrupt climate change. The further observation that the very same asymmetry is also reflected in planktonic and benthic d18O measurements from the Northeast Atlantic has extended this constraint to include a specific response in the ocean. Here we present records of deep-water temperature, d18O and d13C variability from the Northeast Atlantic that help to shed light on the links between overturning circulation perturbations, sea-level variability and inter-hemispheric climate change on millennial time-scales. Results indicate that while deep-water temperatures in the Northeast Atlantic have tracked Greenland climate, the d18O signature of local deepwater (d18Odw) has varied in a manner more reminiscent of Antarctic temperature variability. The previously identified correspondence of Antarctic warm events with benthic d18O minima in the Northeast Atlantic is thus found to apply specifically to d18Odw minima, and to extend beyond Marine Isotope Stage 3 to the entirety of the last 50 ka. It is impossible to reconcile completely the Iberian Margin d18Odw record with existing reconstructions of millennial sea-level variability, leading to the conclusion that a significant portion of the d18Odw record must represent local hydrographic change. This is supported by benthic d13C measurements, which suggest the incursion during Greenland stadials of a colder, low-d18O and low-d13C water-mass, of presumed Antarctic origin. These observations confirm a one-to-one coupling of inter-hemispheric climate events with changes in the Atlantic overturning circulation, but fail to rule in or out a unique mechanism by which they were triggered.

Stable oxygen isotope record of foraminifera from the Ontong Java Plateau

We provide a reconstruction of atmospheric CO2 from deep-sea sediments, for the past 625000 years (Milankovitch chron). Our database consists of a Milankovitch template of sea-level variation in combination with a unique data set for the deep-sea record for Ontong Java plateau in the western equatorial Pacific. We redate the Vostok ice-core data of Barnola et al. (1987, doi:10.1038/329408a0). To make the reconstructions we employ multiple regression between deep-sea data, on one hand, and ice-core CO2 data in Antarctica, on the other. The patterns of correlation suggest that the main factors controlling atmospheric CO2 can be described as a combination of sea-level state and sea-level change. For best results squared values of state and change are used. The square-of-sea-level rule agrees with the concept that shelf processes are important modulators of atmospheric CO2 (e.g., budgets of shelf organic carbon and shelf carbonate, nitrate reduction). The square-of-change rule implies that, on short timescales, any major disturbance of the system results in a temporary rise in atmospheric CO2.

Accuracy of SRM and power tap power monitoring systems for bicycling

Purpose: Although manufacturers of bicycle power monitoring devices SRM and Power Tap (PT) claim accuracy to within 2.5%, there are limited scientific data available in support. The purpose of this investigation was to assess the accuracy of SRM and PT under different conditions. Methods: First, 19 SRM were calibrated, raced for 11 months, and retested using a dynamic CALRIG (50-1000 W at 100 rpm). Second, using the same procedure, five PT were repeat tested on alternate days. Third, the most accurate SRM and PT were tested for the influence of cadence (60, 80, 100, 120 rpm), temperature (8 and 21degreesC) and time (1 h at similar to300 W) on accuracy. Finally, the same SRM and PT were downloaded and compared after random cadence and gear surges using the CALRIG and on a training ride. Results: The mean error scores for SRM and PT factory calibration over a range of 50-1000 W were 2.3 +/- 4.9% and -2.5 +/- 0.5%, respectively. A second set of trials provided stable results for 15 calibrated SRM after 11 months (-0.8 +/- 1.7%), and follow-up testing of all PT units confirmed these findings (-2.7 +/- 0.1%). Accuracy for SRM and PT was not largely influenced by time and cadence; however. power output readings were noticeably influenced by temperature (5.2% for SRM and 8.4% for PT). During field trials, SRM average and max power were 4.8% and 7.3% lower, respectively, compared with PT. Conclusions: When operated according to manufacturers instructions, both SRM and PT offer the coach, athlete, and sport scientist the ability to accurately monitor power output in the lab and the field. Calibration procedures matching performance tests (duration, power, cadence, and temperature) are, however, advised as the error associated with each unit may vary.

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

Random distributed feedback fibre lasers

The concept of random lasers exploiting multiple scattering of photons in an amplifying disordered medium in order to generate coherent light without a traditional laser resonator has attracted a great deal of attention in recent years. This research area lies at the interface of the fundamental theory of disordered systems and laser science. The idea was originally proposed in the context of astrophysics in the 1960s by V.S. Letokhov, who studied scattering with "negative absorption" of the interstellar molecular clouds. Research on random lasers has since developed into a mature experimental and theoretical field. A simple design of such lasers would be promising for potential applications. However, in traditional random lasers the properties of the output radiation are typically characterized by complex features in the spatial, spectral and time domains, making them less attractive than standard laser systems in terms of practical applications. Recently, an interesting and novel type of one-dimensional random laser that operates in a conventional telecommunication fibre without any pre-designed resonator mirrors-random distributed feedback fibre laser-was demonstrated. The positive feedback required for laser generation in random fibre lasers is provided by the Rayleigh scattering from the inhomogeneities of the refractive index that are naturally present in silica glass. In the proposed laser concept, the randomly backscattered light is amplified through the Raman effect, providing distributed gain over distances up to 100km. Although an effective reflection due to the Rayleigh scattering is extremely small (~0.1%), the lasing threshold may be exceeded when a sufficiently large distributed Raman gain is provided. Such a random distributed feedback fibre laser has a number of interesting and attractive features. The fibre waveguide geometry provides transverse confinement, and effectively one-dimensional random distributed feedback leads to the generation of a stationary near-Gaussian beam with a narrow spectrum. A random distributed feedback fibre laser has efficiency and performance that are comparable to and even exceed those of similar conventional fibre lasers. The key features of the generated radiation of random distributed feedback fibre lasers include: a stationary narrow-band continuous modeless spectrum that is free of mode competition, nonlinear power broadening, and an output beam with a Gaussian profile in the fundamental transverse mode (generated both in single mode and multi-mode fibres).This review presents the current status of research in the field of random fibre lasers and shows their potential and perspectives. We start with an introductory overview of conventional distributed feedback lasers and traditional random lasers to set the stage for discussion of random fibre lasers. We then present a theoretical analysis and experimental studies of various random fibre laser configurations, including widely tunable, multi-wavelength, narrow-band generation, and random fibre lasers operating in different spectral bands in the 1-1.6μm range. Then we discuss existing and future applications of random fibre lasers, including telecommunication and distributed long reach sensor systems. A theoretical description of random lasers is very challenging and is strongly linked with the theory of disordered systems and kinetic theory. We outline two key models governing the generation of random fibre lasers: the average power balance model and the nonlinear Schrödinger equation based model. Recently invented random distributed feedback fibre lasers represent a new and exciting field of research that brings together such diverse areas of science as laser physics, the theory of disordered systems, fibre optics and nonlinear science. Stable random generation in optical fibre opens up new possibilities for research on wave transport and localization in disordered media. We hope that this review will provide background information for research in various fields and will stimulate cross-disciplinary collaborations on random fibre lasers. © 2014 Elsevier B.V.

Multiwavelength generation in a random distributed feedback fiber laser using an all fiber Lyot filter

Multiwavelength lasing in the random distributed feedback fiber laser is demonstrated by employing an all fiber Lyot filter. Stable multiwavelength generation is obtained, with each line exhibiting subnanometer line-widths. A flat power distribution over multiple lines is obtained, which indicates that the power between lines is redistributed in nonlinear mixing processes. The multiwavelength generation is observed both in first and second Stokes waves. © 2014 Optical Society of America.

Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet

Rotation invariance is important for an iris recognition system since changes of head orientation and binocular vergence may cause eye rotation. The conventional methods of iris recognition cannot achieve true rotation invariance. They only achieve approximate rotation invariance by rotating the feature vector before matching or unwrapping the iris ring at different initial angles. In these methods, the complexity of the method is increased, and when the rotation scale is beyond the certain scope, the error rates of these methods may substantially increase. In order to solve this problem, a new rotation invariant approach for iris feature extraction based on the non-separable wavelet is proposed in this paper. Firstly, a bank of non-separable orthogonal wavelet filters is used to capture characteristics of the iris. Secondly, a method of Markov random fields is used to capture rotation invariant iris feature. Finally, two-class kernel Fisher classifiers are adopted for classification. Experimental results on public iris databases show that the proposed approach has a low error rate and achieves true rotation invariance. © 2010.

Lyot-filter based multiwavelength random distributed feedback fiber laser

Multiwavelength lasing in the random distributed feedback fiber laser is demonstrated by employing an all fiber Lyot filter. Stable multiwavelength generation is obtained, with each line exhibiting sub-nanometer line-widths. A flat power distribution over multiple lines is also obtained, which indicates the contribution of nonlinear wave mixing towards power redistribution and equalization in the system. The multiwavelength generation is observed simultaneously in first and second Stokes waves. © 2014 SPIE.

Geometric Stable Laws Through Series Representations

Let (Xi ) be a sequence of i.i.d. random variables, and let N be a geometric random variable independent of (Xi ). Geometric stable distributions are weak limits of (normalized) geometric compounds, SN = X1 + · · · + XN , when the mean of N converges to infinity. By an appropriate representation of the individual summands in SN we obtain series representation of the limiting geometric stable distribution. In addition, we study the asymptotic behavior of the partial sum process SN (t) = ⅀( i=1 ... [N t] ) Xi , and derive series representations of the limiting geometric stable process and the corresponding stochastic integral. We also obtain strong invariance principles for stable and geometric stable laws.