Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Reciprocal relationship between left ventricular filling pressure and the recruitable human coronary collateral circulation

AIMS The aim of our study in patients with coronary artery disease (CAD) and present, or absent, myocardial ischaemia during coronary occlusion was to test whether (i) left ventricular (LV) filling pressure is influenced by the collateral circulation and, on the other hand, that (ii) its resistance to flow is directly associated with LV filling pressure. METHODS AND RESULTS In 50 patients with CAD, the following parameters were obtained before and during a 60 s balloon occlusion: LV, aortic (Pao) and coronary pressure (Poccl), flow velocity (Voccl), central venous pressure (CVP), and coronary flow velocity after coronary angioplasty (V(Ø-occl)). The following variables were determined and analysed at 10 s intervals during occlusion, and at 60 s of occlusion: LV end-diastolic pressure (LVEDP), velocity-derived (CFIv) and pressure-derived collateral flow index (CFIp), coronary collateral (Rcoll), and peripheral resistance index to flow (Rperiph). Patients with ECG signs of ischaemia during coronary occlusion (insufficient collaterals, n = 33) had higher values of LVEDP over the entire course of occlusion than those without ECG signs of ischaemia during occlusion (sufficient collaterals, n = 17). Despite no ischaemia in the latter, there was an increase in LVEDP from 20 to 60 s of occlusion. In patients with insufficient collaterals, CFIv decreased and CFIp increased during occlusion. Beyond an occlusive LVEDP > 27 mmHg, Rcoll and Rperiph increased as a function of LVEDP. CONCLUSION Recruitable collaterals are reciprocally tied to LV filling pressure during occlusion. If poorly developed, they affect it via myocardial ischaemia; if well grown, LV filling pressure still increases gradually during occlusion despite the absence of ischaemia indicating transmission of collateral perfusion pressure to the LV. With low, but not high, collateral flow, resistance to collateral as well as coronary peripheral flow is related to LV filling pressure in the high range.

Low rank subspace clustering (LRSC)

We consider the problem of fitting a union of subspaces to a collection of data points drawn from one or more subspaces and corrupted by noise and/or gross errors. We pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and/or gross errors. By self-expressive we mean a dictionary whose atoms can be expressed as linear combinations of themselves with low-rank coefficients. In the case of noisy data, our key contribution is to show that this non-convex matrix decomposition problem can be solved in closed form from the SVD of the noisy data matrix. The solution involves a novel polynomial thresholding operator on the singular values of the data matrix, which requires minimal shrinkage. For one subspace, a particular case of our framework leads to classical PCA, which requires no shrinkage. For multiple subspaces, the low-rank coefficients obtained by our framework can be used to construct a data affinity matrix from which the clustering of the data according to the subspaces can be obtained by spectral clustering. In the case of data corrupted by gross errors, we solve the problem using an alternating minimization approach, which combines our polynomial thresholding operator with the more traditional shrinkage-thresholding operator. Experiments on motion segmentation and face clustering show that our framework performs on par with state-of-the-art techniques at a reduced computational cost.

Differential Stability of Reciprocal Friendships and Unilateral Relationships Among Preschool Children

It was expected that reciprocal relationships would be maintained more frequently across a six-month interval than would unilateral ones. Of secondary concern was the question of whether the dimensions children offered to justify their friendships would remain more stable for reciprocal than unilateral relationships.

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Diminishing reciprocal fairness by disrupting the right prefrontal cortex.

Humans restrain self-interest with moral and social values. They are the only species known to exhibit reciprocal fairness, which implies the punishment of other individuals' unfair behaviors, even if it hurts the punisher's economic self-interest. Reciprocal fairness has been demonstrated in the Ultimatum Game, where players often reject their bargaining partner's unfair offers. Despite progress in recent years, however, little is known about how the human brain limits the impact of selfish motives and implements fair behavior. Here we show that disruption of the right, but not the left, dorsolateral prefrontal cortex (DLPFC) by low-frequency repetitive transcranial magnetic stimulation substantially reduces subjects' willingness to reject their partners' intentionally unfair offers, which suggests that subjects are less able to resist the economic temptation to accept these offers. Importantly, however, subjects still judge such offers as very unfair, which indicates that the right DLPFC plays a key role in the implementation of fairness-related behaviors.

Reciprocal Relationships between Leader–Member Exchange (LMX) and Job Satisfaction: A Cross‐Lagged Analysis

While previous research has mainly emphasised the importance of leader–member exchange (LMX) to job satisfaction, there is a lack of research on reciprocal relationships between job satisfaction and LMX. In this study, we not only suggest that good LMX increases job satisfaction, but that job satisfaction can also enhance high-quality supervisor–employee relationships. A full cross-lagged panel analysis was used to test reciprocal relationships between LMX and job satisfaction. Employees (N= 279) of a large information technology company filled out questionnaires at two times, with a time lag of 3 months. In line with our predictions, findings revealed a positive relationship between LMX and job satisfaction both at Time 1 and Time 2. Moreover, LMX at Time 1 predicted the increase of job satisfaction at Time 2, and job satisfaction at Time 1 predicted the increase of LMX at Time 2. The results demonstrate the need to consider reciprocal relationships between job satisfaction and LMX when explaining employees' workplace outcomes. Our findings are discussed in terms of positive psychology theory.

Increasingly Rank: The Use and Misuse of Rankings in Economic Development

Debates over the merits of competing schemes for ranking metropolitan areas as hightech centers shed little light on the important policy questions that should be the core of economic development policy. There are no strong theoretical reasons for preferring one ranking system to others. Rankings often conflate different industries and ignore history, obscuring the varied and often idiosyncratic processes that drive growth in different regions. Although an occupational perspective is a useful one for examining economic activity, it is a supplement to, not a replacement for, a careful understanding of metropolitan industrial specialization. Practitioners should not put too much weight on any ranking system but instead should work to develop detailed knowledge of their region’s special economic niche and to develop relationships and strategies that build on established strengths.

Application of Local Rank Tests for Nonparametric Regression

Let Y_i = f(x_i) + E_i\ (1\le i\le n) with given covariates x_1\lt x_2\lt \cdots\lt x_n , an unknown regression function f and independent random errors E_i with median zero. It is shown how to apply several linear rank test statistics simultaneously in order to test monotonicity of f in various regions and to identify its local extrema.

Environmental correlates of species rank − abundance distributions in global drylands

Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: (i) assess the influence of climatic and soil characteristics on the observed SADs, (ii) infer how environmental variability influences relative abundances, and (iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.

New aspects of estrogen action in the endometrium: Reciprocal interplay with retinoic acid pathway and a novel estrogen-regulated gene

The uterine endometrium is a major target for the estrogen. However, the molecular basis of estrogen action in the endometrium is largely unknown. I have used two approaches to study the effects of estrogen on the endometrium. One approach involved the study of the interaction between estrogen and retinoic acid (RA) pathways in the endometrium. I have demonstrated that estrogen administration to rodents and estrogen replacement therapy (ERT) in postmenopausal women selectively induced the endometrial expression of retinaldehyde dehydrogenase II (RALDH2), a critical enzyme of RA biosynthesis. RALDH2 was expressed exclusively in the stromal cells, especially in the stroma adjacent to the luminal and glandular epithelia. The induction of RALDH2 by estrogen required estrogen receptor and occurred via a direct increase in RALDH2 transcription. Among the three RA receptors, estrogen selectively induced the expression of RARα. In parallel, estrogen also increased the utilization of all-trans retinol (the substrate for RA biosynthesis) and the expression of two RA-regulated marker genes, cellular retinoic acid binding protein II (CRABP2) and tissue transglutaminase (tTG) in the endometrium. Thus estrogen coordinately upregulated both the production and signaling of RA in both the rodent and human endometrium. This coordinate upregulation of RA system appeared to play a role in counterbalancing the stimulatory effects of estrogen on the endometrium, since the depletion of endogenous RA in mice led to an increase in estrogen-stimulated stromal proliferation and endometrial Akt phosphorylation. In addition, I have also used a systematic approach (DNA microarray) to categorize genes and pathways affected by the ERT in the endometrium of postmenopausal women and identified a novel estrogen-regulated gene EIG121. EIG121 was exclusively expressed in the glandular epithelial cells of the endometrium and induced by estrogen in vivo and in cultured cell lines. Compared with the normal endometrium, EIG121 was highly overexpressed in type 1 endometrial cancer, but profoundly suppressed in type 2 endometrial tumors. Taken together, these studies suggested that estrogen regulates the expression of many genes of both the pro-proliferative and anti-proliferative pathways and the abnormality of these pathways may increase the risks for estrogen-dependent endometrial hyperplasia and endometrial cancer. ^

Extension of k-ratio methods to rank-based analyses

An extension of k-ratio multiple comparison methods to rank-based analyses is described. The new method is analogous to the Duncan-Godbold approximate k-ratio procedure for unequal sample sizes or correlated means. The close parallel of the new methods to the Duncan-Godbold approach is shown by demonstrating that they are based upon different parameterizations as starting points.^ A semi-parametric basis for the new methods is shown by starting from the Cox proportional hazards model, using Wald statistics. From there the log-rank and Gehan-Breslow-Wilcoxon methods may be seen as score statistic based methods.^ Simulations and analysis of a published data set are used to show the performance of the new methods. ^

A SIMULATION STUDY OF THE SIZE AND POWER OF SOME TWO-SAMPLE TESTS FOR UNEQUALLY CENSORED SURVIVAL DATA (RANK TESTS, LOGRANK, PROPORTIONAL HAZARDS, WILCOXON TESTS, EXPONENTIAL DISTRIBUTION)

Sizes and power of selected two-sample tests of the equality of survival distributions are compared by simulation for small samples from unequally, randomly-censored exponential distributions. The tests investigated include parametric tests (F, Score, Likelihood, Asymptotic), logrank tests (Mantel, Peto-Peto), and Wilcoxon-Type tests (Gehan, Prentice). Equal sized samples, n = 18, 16, 32 with 1000 (size) and 500 (power) simulation trials, are compared for 16 combinations of the censoring proportions 0%, 20%, 40%, and 60%. For n = 8 and 16, the Asymptotic, Peto-Peto, and Wilcoxon tests perform at nominal 5% size expectations, but the F, Score and Mantel tests exceeded 5% size confidence limits for 1/3 of the censoring combinations. For n = 32, all tests showed proper size, with the Peto-Peto test most conservative in the presence of unequal censoring. Powers of all tests are compared for exponential hazard ratios of 1.4 and 2.0. There is little difference in power characteristics of the tests within the classes of tests considered. The Mantel test showed 90% to 95% power efficiency relative to parametric tests. Wilcoxon-type tests have the lowest relative power but are robust to differential censoring patterns. A modified Peto-Peto test shows power comparable to the Mantel test. For n = 32, a specific Weibull-exponential comparison of crossing survival curves suggests that the relative powers of logrank and Wilcoxon-type tests are dependent on the scale parameter of the Weibull distribution. Wilcoxon-type tests appear more powerful than logrank tests in the case of late-crossing and less powerful for early-crossing survival curves. Guidelines for the appropriate selection of two-sample tests are given. ^