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Much research effort is invested in attempting to determine causal influences on disease onset and progression to inform prevention and treatment efforts. However, this is often dependent on observational data that are prone to well-known limitations, particularly residual confounding and reverse causality. Several statistical methods have been developed to support stronger causal inference. However, a complementary approach is to use design-based methods for causal inference, which acknowledge sources of bias and attempt to mitigate these through the design of the study rather than solely through statistical adjustment. Genetically informed methods provide a novel and potentially powerful extension to this approach, accounting by design for unobserved genetic and environmental confounding. No single approach will be absent from bias. Instead, we should seek and combine evidence from multiple methodologies that each bring different (and ideally uncorrelated) sources of bias. If the results of these different methodologies align-or triangulate-then we can be more confident in our causal inference. To be truly effective, this should ideally be done prospectively, with the sources of evidence specified in advance, to protect against one final source of bias-our own cognitions, expectations, and fondly held beliefs.

Parents are key protective systems in the lives of children experiencing homelessness. Evidence suggests that parent emotional reactivity, expression, and regulation play a critical role in promoting adaptive parenting behaviors. Studies of emotional reactivity in parents utilize different methods, including self-report, observations, and physiological measures. However, these methods are rarely evaluated together, particularly among disadvantaged families. The present study examined how subjective (i.e., self-report), observed, and physiological measures of parent emotional reactivity relate to each other and to observed parenting behaviors in problem-solving and teaching parent-child interaction tasks. Participants included fifty 4- to 7-year-old children and their caregivers staying in an emergency homeless shelter. Observed and subjective emotional reactivity were largely uncorrelated, except for positive emotions during problem-solving tasks. Adaptive parenting behavior was related to lower scores on measures of subjective and observed negative emotions and higher observed scores for positive emotions during problem-solving tasks, as well as higher observed scores of positive emotions during teaching tasks. Physiological reactivity was not related to parenting behaviors. Results suggest that associations of emotional reactivity with parenting behavior depend on the context of the parent-child interaction and how emotional reactivity is measured. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Traditional single-ended fault location method is influenced by the fault resistance and the remote in feed, which reflects as the two equations built by fault phase have four unknowns. And in the grid-connected converter system, the weak feedback characteristic further reduces the performance of the method. To solve it, a single-ended fault location method based on control and protection coordination is proposed in this paper. First, using the high controlled-ability of the converter, the control strategy for fault ride-through (FRT) operation is divided into two stages by switching control modes. Then, according to the electrical quantities under two stages, four uncorrelated equations can be established, and the equations still have four unknown parameters. The fault distance can be calculated by solving them. The simulation results show that the proposed method has high accuracy and is immune to fault resistance and fault location, it solves the problem of insufficient equations in principle.

Objectives This study aimed to determine the acoustic characteristics of the external auditory canal (EAC) and predict the real-ear aided response (REAR) using an EAC model that includes the standing wave effect. Methods The EAC transfer function equations were derived by summing the incoming and outgoing waves. First, we investigated the real-ear unaided gain (REUG). Second, seven patients (eight ears) wearing hearing aids (HAs) were enrolled as subjects to examine the REAR. We conducted wideband tympanometry (WBT) to measure the absorbance, the frequency response at 65 dB (65dB-FR) of the HAs, and the measured REAR for an international speech test signal (ISTS) at 65 dB. Results The EAC model that includes the standing-wave effect is considered to be valid from examination of the REUG. A significant correlation was found between the measured and calculated REARs at 900 Hz, 1000 Hz, 2000 Hz, and 3000 Hz in an uncorrelated test. A two-way analysis of variance (ANOVA) found significant differences in the 65dB-FR and the measured REARs at 800, 900, 1000, and 2000 Hz, but this difference disappeared after correction of the calculated acoustic characteristics of the EAC. Conclusions By measuring the WBT characteristics and correcting them with an EAC model, the in-situ REAR can be determined from the HA characteristics in the mid-frequency range. There is a risk of insufficient HA amplification in the mid-frequency range when no real-ear measurements are performed.

Our primary objective in this article is to compare the spectral densities of some cyclostationary time series. By using the limiting distributions of the discrete Fourier transform, a novel approach is introduced to determine whether the spectral densities of some uncorrelated cyclostationary time series are the same or not. Also, the ability of the proposed technique is examined by employing simulated and real datasets.

What explains variation in the degree of regulation across US states and industries? We examine cross- sectional variation in state government regulation facing 81 3-digit North American Industry Classification System industries by matching novel data on regulatory restrictions at the state-industry level with data on state-industry characteristics. For most states, an increase in industry size is positively correlated with the extent of regulation. Additionally, for most industries, there is also a positive correlation between industry size and the degree to which state governments regulate that industry. When we control for unobserved heterogeneity at the state and industry levels, we find the extent of industry-level regulation is robustly correlated with the size of the industry. However, other industry factors, like average wages, average establishment sizes, or the distribution of establishment sizes, are uncorrelated with the extent of regulation. Taken as a whole, our findings are consistent with hypotheses for regulation that emphasize the fixed costs of establishing regulation or the salience of large industries and are inconsistent with hypotheses that suggest that regulation is influenced by firm size or industry-level concentration of establishment sizes.

In reality, symmetric relations cannot informatively explain the causal complexity due to non-100% linear observable relationships. However, asymmetric relations are seldom discussed in crowdfunding fundraising. Based on the signaling theory and start-up quality, this article uses symmetric (logistics regression and negative binomial regression) and asymmetric analyses (fuzzy-set qualitative comparative) to explain the causal complexity of intellectual, human, and social capital signals in technology project fundraising. This article tests data collected from 516 technology projects in reward-based crowdfunding in China. As a result, symmetric analysis partly supports hypotheses from symmetric relations. However, asymmetric analysis indicates that uncorrelated capital signals in the symmetric analysis are active conditions in configurations to funding success and performance. Furthermore, asymmetric analysis supports that social capital signals are more important than intellectual capital signals and human capital signals. Non-third-party authorized signals are more important than third-party authorized signals in fundraising. Social connection between investors and start-ups is also the necessary social capital signal for funding success. These findings highlight the importance of joint effects of capital signals on crowdfunding fundraising, thus enriching the understanding of start-up quality and signals, third-party endorsement, unprofessional investors, and the high-noise environment of crowdfunding.

A natural approach to enhance portfolio diversification is to rely on factor-risk parity, which yields the portfolio whose risk is equally spread among a set of uncorrelated factors. The standard choice is to take the variance as risk measure, and the principal components (PCs) of asset returns as factors. Although PCs are unique and useful for dimension reduction, they are an arbitrary choice: any rotation of the PCs results in uncorrelated factors. This is problematic because we demonstrate that any portfolio is a factor-variance-parity portfolio for some rotation of the PCs. More importantly, choosing the PCs does not account for the higher moments of asset returns. To overcome these issues, we propose using the independent components (ICs) as factors, which are the rotation of the PCs that are maximally independent, and care about higher moments of asset returns. We demonstrate that using the IC-variance-parity portfolio helps to reduce the return kurtosis. We also show how to exploit the near independence of the ICs to parsimoniously estimate the factor-risk-parity portfolio based on value at risk. Finally, we empirically demonstrate that portfolios based on ICs outperform those based on PCs, and several state-of-the-art benchmarks.

We shall prove a weak law of large numbers for the uncorrelated (see Definition 3.1) fuzzy random variable sequence with respect to the uniform Hausdorff metric $d_H^{\infty}$, which is an extension of weak law of large numbers for independent fuzzy random variables., 9 pages

The present paper contributes to the controversy regarding gender differences in risk taking by investigating the impact of social comparison. Drawing on previous results from evolutionary biology, we argue that the social ranking is more important for men than for women, i.e. men (women) should focus more on relative (absolute) income. We develop a corresponding model of decision making under risk which predicts that risk taking is higher (lower) for positively (negatively) correlated risks than for uncorrelated risks and that this effect is stronger for men than for women. These predictions are confirmed by our first experiment. Building upon the first experiment, we show in a second experiment that we can make gender differences to appear or disappear by changing the social context in a systematic way. We conclude that social comparison and the correlation of risks may play an important role for the occurrence of gender differences in risk taking.

While digital multi-user (MU) maximal ratio combining (MRC) is well understood, relatively few analytical results exist for analog MU-MRC. For example, it has recently been shown that MU system performance is highly dependent on the correlation model used, but the scope is limited to digital processing. Thus, in this paper we compare the performance of analog and digital MRC, focusing on the effects of correlation. We begin by deriving the expected signal and interference powers, demonstrating that the signal-to-interference ratio decreases with correlation when users have the same correlation matrices, while it increases when their correlation matrices are different. These finite system results are then extended by deriving asymptotic signal-to-interference-and-noise ratio expressions for both analog and digital MRC for the benchmark scenarios of uncorrelated and perfectly correlated Rayleigh channels. Here, we once again demonstrate that the performance is critically dependent on the correlation scenario.

It is well-known that there are instances of the binary paint shop problem for which the recursive greedy heuristic is better than the greedy heuristic. In this note, we give an example of a family of instances where the greedy heuristic is better than the recursive greedy heuristic, thus showing that these heuristics are uncorrelated.

This paper estimates that pollution damages avoidable by solar capacity vary considerably across zip codes in the United States and that they are uncorrelated with solar subsidy levels in e...

This paper studies Structural Vector Autoregressions in which a structural shock of interest (e.g., an oil supply shock) is identified using an external instrument. The external instrument is taken to be correlated with the target shock (the instrument is relevant) and to be uncorrelated with other shocks of the model (the instrument is exogenous). The potential weak correlation between the external instrument and the target structural shock compromises the large-sample validity of standard inference. We suggest a confidence set for impulse response coefficients that is not affected by the instrument strength (i.e., is weak-instrument robust) and asymptotically coincides with the standard confidence set when the instrument is strong.

Digital games are one of the potential pedagogical approaches within STEM teaching and learning. The main idea behind using digital games in STEM contexts is to enhance the children’s conceptual understanding and to increase their interest in STEM. The interest in STEM is still an unsolved global issue. Most studies looking into digital games show there to be positive implications when it comes to STEM learning. This gap and the uncorrelated scenario from both the theoretical and practical perspectives need to both be solved. Here we conceptualise the usefulness of STEM digital games for stimulating an interest in STEM, particularly among children from a design perspective. The previous studies are the main qualitative sources for the interpretation of the main argument in this paper. As result, digital games have a strong empirically supportive foundational basis that acts as a medium to stimulate interest. To achieve this, STEM digital games should be designed to be of better quality. Good STEM digital games will contribute to better STEM learning outcomes and meaningful gaming experiences that can contribute to the interest in STEM. This study proposes a comprehensive framework to understand the purpose of the design and development of STEM digital games. https://doi.org/10.26803/ijlter.20.10.13

Effective suppression of inadvertent or deliberate jamming signals is crucial to ensure reliable wireless communication. However, as demonstrated in this paper, when the transmitted jamming signals are highly correlated, and especially when the correlation coefficient varies, nullifying the jamming signals can be challenging. Unlike existing techniques that often assume uncorrelated jamming signals or non-zero but constant correlation, we analyze the impact of the non-zero and varying correlations between transmitted jamming signals on the suppression of the jamming signals. Specifically, we observe that by varying the correlation coefficients between transmitted jamming signals, jammers can “virtually change” the jamming channels hence their nullspace, even when these channels do not physically change. This makes most jamming suppression techniques that rely on steering receiving beams towards the nullspace of jamming channels no longer applicable. To tackle the problem, we develop techniques to effectively track the jamming nullspace and correspondingly update receiving beams. Monte Carlo simulations show that our proposed techniques can suppress/nullify jamming signals for all considered scenarios with non-zero and varying correlation coefficients amongst transmitted jamming signals.

We introduce the concept of risk entanglement in a preference-free setting to jointly explain the exchange rate volatility, cyclicality, and currency risk premia in the data. Risk entanglement specifies a subset of incomplete market models, in which nondiffusive or nonlog-normal shocks to exchange rates are not fully spanned by asset returns. When risks are entangled, there exist multiple pricing-consistent exchange rates, but none of them are equal to the ratio of the stochastic discount factors (SDFs) or their projections. Decoupling the exchange rate from the SDFs allows us to address key FX market patterns that are puzzling in international finance.

Although resilience has been identified to be moderately heritable, little is known about the genetic variants involved. While there has not yet been a robust genome-wide association study (GWAS) of resilience, existing GWAS of related phenotypes may provide a starting point for developing our understanding of the heritability of resilience. In a sample of older, US adults (N = 9480), we examined the extent to which proxy polygenic scores (PGS) explained the variance in resilience. Four of the 32 PGS assessed (subjective wellbeing, neuroticism, depressive symptoms and educational attainment) reached significance among participants with European ancestries, but with relatively small effects (|β|= 0.002-0.09). Notably, PGSs derived from GWAS of PTSD among participants with either European or African ancestries were uncorrelated with resilience. Even aggregated across all available proxy PGSs, existing PGSs are not sufficient to inform our understanding of the genetics underlying the heritability of resilience. A large-scale GWAS of resilience is needed as it would provide greater insight into the genetic mechanisms underlying the heritability of resilience.

Rotating machines are commonly used in industrial applications. Mechanical faults such as rotor unbalance, shaft misalignment, pulley misalignment, structural looseness, and bearing faults leading to unplanned shutdown based on the severity of these faults. The condition monitoring technique based on vibration analysis has the potential to detect and diagnose a great number of early stage faults. However, some mechanical faults have correlated vibration features leading to ambiguous diagnosis to identify and distinguish these faults. In this paper, a proposed method based on the Principal Component Analysis (PCA) is presented to produce uncorrelated Principal Components (PCs) to identify the healthy and different faulty cases. A test rig was prepared to simulate a group of mechanical faults such as rotor unbalance, pulley misalignment, belt damage, combined unbalance with pulley misalignment, and combined unbalance with belt damage. The conventional vibration measurements were collected for each case and their features were extracted and used to produce the equivalent PCs. It was found that the produced uncorrelated PCs have the superior to distinguish the majority of simulated faults which have correlated vibration features as presented in the rest of paper.

This paper is mainly concerned with sets which do not contain four-term arithmetic progressions, but are still very rich in three term arithmetic progressions, in the sense that all sufficiently large subsets contain at least one such progression. We prove that there exists a positive constant c and a set A ⊂ F^n_q which does not contain a four-term arithmetic progression, with the property that for every subset A′ ⊂ A with |A′| ≥ |A|^(1−c), A′ contains a nontrivial three term arithmetic progression. We derive this from a more general quantitative Roth-type theorem in random subsets of F^n_q, which improves a result of Kohayakawa-Luczak-Rodl/Tao-Vu. We also discuss a similar phenomenon over the integers, where we show that for all ϵ > 0, and all sufficiently large N ∈ N, there exists a four-term progression-free set A of size N with the property that for every subset A′ ⊂ A with |A′| ≫ 1/(logN)^(1−ϵ)⋅ N contains a nontrivial three term arithmetic progression. Finally, we include another application of our methods, showing that for sets in F^n_q or Z the property of "having nontrivial three-term progressions in all large subsets" is almost entirely uncorrelated with the property of "having large additive energy".

In multiple linear regression models, the explanatory variables should be uncorrelated within each other but this assumption is violated in most of the cases. Generally, ordinary least square (OLS)...

We study the inter-reader variability in manual delineation of cystic renal masses (CRMs) presented in computerized tomography (CT) images and its effect on the classification performance of a machine learning algorithm in distinguishing benign from potentially malignant CRMs. In addition, we assessed whether the inclusion of higher-order robust radiomic features improves the classification performance over the use of first-order features. 230 CRMs were independently delineated by two radiologists. Through a combination of random fluctuations, dilation, and erosion operations over the original region of interests (ROIs), we generated four additional sets of synthetic ROIs to capture the inter-reader variability realistically, as confirmed by dice coefficient measurements and visual assessment. We then identified the robust features based on the intra-class coefficient (ICC > 0.85) across these datasets. We applied a tenfold stratified cross-validation (CV) to train and test the performance of the random forest model for the classification of CRMs into benign and potentially malignant. The mean area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value were 0.87, 0.82, 0.90, 0.85, and 0.93, respectively. With the usage of first-order features alone, the corresponding values were nearly identical. AUC ranged for the robust and uncorrelated features from 0.83 ± 0.09 to 0.93 ± 0.04 and for the first-order features from 0.84 ± 0.09 to 0.91 ± 0.04. Our study indicates that the first-order features alone are sufficient for the classification of CRMs, and that inclusion of higher-order features does not necessarily improve performance.

The COVID-19 pandemic is a global crisis that has forced governments around the world to implement large-scale interventions such as school closures and national lockdowns. Previous research has shown that partisanship plays a major role in explaining public attitudes towards these policies and beliefs about the intensity of the crisis. However, it remains unclear whether and how partisan differences in policy support relate to partisan gaps in beliefs about the number of deaths that the pandemic will cause. Do individuals who forecast fewer COVID-19 deaths show less agreement with preventive measures? How does partisanship correlate with people’s beliefs about the intensity of the crisis and their support for COVID-19 policies? Here, we sought to answer these questions by performing a behavioral experiment in Argentina (Experiment 1, N = 640) and three quasi-replication studies in Uruguay (Experiment 2, N = 372), Brazil (Experiment 3, N = 353) and the United States (Experiment 4, N = 630). In all settings, participants forecasted the number of COVID-19 deaths in their country after considering either a high or low number, and then rated their agreement with a series of interventions. This anchoring procedure, which experimentally induced a large variability in the forecasted number of deaths, did not modify policy preferences. Instead, each experiment provided evidence that partisanship was a key indicator of the optimism of forecasts and the degree of support for COVID-19 policies. Remarkably, we found that the number of forecasted deaths was robustly uncorrelated with participants’ agreement with preventive measures designed to prevent those deaths. We discuss these empirical observations in the light of recently proposed theories of tribal partisan behavior. Moreover, we argue that these results may inform policy making as they suggest that even the most effective communication strategy focused on alerting the public about the severity of the pandemic would probably not translate into greater support for COVID-19 preventive measures.

American industries have grown more concentrated over the last 40 years. In the absence of productivity innovation, this should lead to price hikes and output reductions, decreasing consumer welfare. With US census data from 1972 to 2012, I use price data to disentangle revenue from output. Industry-level estimates show that concentration increases are positively correlated to productivity and real output growth, uncorrelated with price changes and overall payroll, and negatively correlated with labor’s revenue share. I rationalize these results in a simple model of competition. Productive industries (with growing oligopolists) expand real output and hold down prices, raising consumer welfare, while maintaining or reducing their workforces, lowering labor’s share of output. (JEL D43, L13, D24, D33, D21, D42)

While cognitive control enables the selection of goal-relevant responses, metacontrol enables the selection of context-appropriate control operations. In task switching, metacontrol modulates task-switching efficiency by retrieving the associations between a contextual cue and a particular cognitive control demand. While the automatic retrieval of cognitive control is appealing due to its time and energy efficiency, the effects of different contextual cues have been shown in separate studies and appear to have different characteristics. Here, we devised a single task-switching paradigm to test whether we can observe both list-wide and item-specific metacontrol within subjects. In two experiments, we demonstrated reduced switch costs in lists associated with a high probability of switching as compared with lists with a low probability of switching (i.e., a list-wide switch probability [LWSP] effect). Similarly, we observed an analogous item-specific switch probability (ISSP) effect such that items associated with a high probability of switching incurred smaller switch costs as compared with items associated with a low probability of switching. We also confirmed that both list-wide and item-specific switch probability effects were not dependent on lower-level stimulus-response associations. However, the LWSP and the ISSP effects were uncorrelated, suggesting a lack of dependence. Together, these findings suggest that there are two distinct modes of metacontrol that are deployed in a context-sensitive manner in order to adapt to specific cognitive demands.

Few studies have examined the post-discharge benefits associated with recover-oriented programs delivered in inpatient and sub-acute mental health settings. The aim of this study was to evaluate the medium-term outcomes of a 6-week sub-acute inpatient intervention program for 27 service users with a diagnosis of serious mental illness (mean age = 33.22 years, 70.4% with a psychosis diagnosis). Recovery data were collected on admission, at discharge, and at 3- and 6-months post-discharge using self-report, collaborative and clinical measures. The three clinician-rated measures (assessing therapeutic engagement, functioning, and life skills) revealed linear improvements from admission to 6-month follow-up (with mean z-change ranging from 0.72 to 1.35), as did the self-reported social connection measure (Mental Health Recovery Star, MHRS; mean z-change: 1.05). There were also curvilinear improvements in self-determination and self-reported MHRS symptom management and functioning scores; however, only modest changes were detected in hope (Herth Hope Index) and MHRS self-belief scores. Change scores based on self-reported and clinician-rated measures tended to be uncorrelated. An exploration of client-level outcomes revealed three recovery trajectory subgroups: transient (21.7%), gradual (34.8%), or sustained (43.5%) improvement; with members of the latter group tending to have longer illness durations. The study’s findings are encouraging, to the extent that they demonstrate recovery-focused sub-acute inpatient programs can promote clinical recovery and aspects of personal recovery. However, they also suggest that recovery perspectives differ between clients and clinicians, and that far more work is required to understand the psychological factors that generate and sustain the hope that recovery is possible.

In this paper, we focused on the new stochastic frontier model with the nonlinear autoregressive structure in panel data. In classic finance models, uncorrelated errors are considered, which are fr...

Data assimilation systems usually assume that the observation errors of wind components, i.e., u (the longitudinal component) and v (the latitudinal component), are uncorrelated. However, since wind components are derived from observations in the form of wind speed and direction (spd and dir), the observation errors of u and v are correlated. In this paper, an explicit expression of the observation errors and correlation for each pair of wind components are derived based on the law of error propagation. The new data assimilation scheme considering the correlated error of wind components is implemented in the Weather Research and Forecasting Data Assimilation (WRFDA) system. Besides, adaptive quality control (QC) is introduced to retain the information of high wind-speed observations. Results from real data experiments assimilating the Advanced Scatterometer (ASCAT) sea surface winds suggest that analyses from the new data assimilation scheme are more reasonable compared to those from the conventional one, and could improve the forecasting of Typhoon Noru.

We develop a novel methodology for studying the causal impact of announcement timing. Our methodology uses firms’ earnings announcements and leverages quasi-exogenous variation attributable to the specific day-of-week on which a calendar month begins. We refer to the resulting variation in announcement timing as “calendar rotations,” which are uncorrelated with proxies for announcement content. In applying our methodology, we show announcements moved forward by calendar rotations receive heightened media and investor attention, and experience greater earnings announcement premia. Taken together, our study details a method for studying how the timing of information flows impacts outcomes of interest to financial economists.

This article is concerned with a novel data-driven bias-eliminated subspace identification approach for closed-loop systems. Compared with the existing methods, the proposed method first proposes to utilize the coprime factorization of the controller to construct an instrumental variable uncorrelated with noise under closed-loop conditions. Furthermore, it can reliably eliminate the pole estimation bias due to the correlation between inputs and noise under feedback control. More importantly, the proposed method establishes a general framework for both open-loop and closed-loop system identification. Performance comparisons with two other closed-loop methods are made from many different aspects. Finally, the performance of the identified system is again demonstrated in the vehicle lateral dynamic system.

Research that has compared the predictive validities of word frequency (WF) and contextual diversity (CD) in lexical processing tasks has generally found that CD accounts for more unique variance than does WF. After CD's variance has been accounted for, WF accounts for little or none of the remaining variance in lexical processing times. This has led some researchers to conclude that the concept CD is thought to measure -- variety in contexts of appearance -- is more relevant to learning than is WF, which is instead an index of total exposure to a stimulus (see Adelman, Brown, & Quesada, 2006; Jones, Johns, & Recchia, 2012). We provide evidence that CD is a poor operationalization of variety in contexts of appearance. As a consequence, prior comparisons between WF and CD and the conclusions drawn from those comparisons should be re-examined. We discuss how the concept of linguistic context has been poorly treated in the CD literature and that, if we allow for linguistic contexts to be variable in size and nested, the apparent dichotomy presented by CD and WF disappears. This article also introduces a new measure of context variability that is simple to calculate and relatively uncorrelated with WF. We demonstrate that in most cases, the described measure accounts for more unique variance in lexical processing times than does CD. These results are used to motivate consideration of what an appropriate definition of context is for studying lexical processing, and ways alternative to CD that might be used to operationalize context variability.

For species primarily regulated by a common predator, the P* rule of Holt and Lawton [1993] predicts that the prey species that supports the highest mean predator density (P*) excludes the other prey species. This prediction is re-examined in the presence of temporal fluctuations in the vital rates of the interacting species including predator attack rates. When the fluctuations in predator attack rates are temporally uncorrelated, the P* rule still holds even when the other vital rates are temporally auto-correlated. However, when temporal auto-correlations in attack rates are positive but not too strong, the prey species can coexist due to the emergence of a positive covariance between predator density and prey vulnerability. This coexistence mechanism is similar to the storage effect for species regulated by a common resource. Negative or strongly positive auto-correlations in attack rates generate a negative covariance between predator density and prey vulnerability and a stochastic priority effect can emerge: with non-zero probability either prey species is excluded. These results highlight how temporally auto-correlated species’ interaction rates impact the structure and dynamics of ecological communities.

Intersex has been reported regularly in wild populations of gonochoristic fish. The authors investigated the possible feminization of seahorses in a population of Hippocampus reidi in Brazil, as well as report a case of a brood pouch reduction after reproductive stimuli. The female seahorses of this population showed two kinds of morphological anomalies. The proportion of the animals affected in the study population was consistent and was uncorrelated with the sex ratio. The study indicates the changes in the sexual profile of the individual.

We identify a component of monetary policy news that is extracted from high-frequency changes in risky asset prices. These surprises, which we call “risk shifts”, are uncorrelated, and therefore complementary, to risk-free rate surprises. We show that (i) risk shifts capture the lion’s share of stock price movements around FOMC announcements; (ii) that they are accompanied by significant investor fund flows, suggesting that investors react heterogeneously to monetary policy news; and (iii) that price pressure amplifies the stock market response to monetary policy news. Our results imply that central bank information effects are overshadowed by short-term dynamics stemming from investor rebalancing activities and are likely to be more difficult to identify than previously thought.

This paper extends the principal component analysis (PCA) to moderately non-stationary vector time series. We propose a method that searches for a linear transformation of the original series such that the transformed series is segmented into uncorrelated subseries with lower dimensions. A columns’ rearrangement method is proposed to regroup transformed series based on their relationships. We discuss the theoretical properties of the proposed method for fixed and large dimensional cases. Many simulation studies show our approach is suitable for moderately non-stationary data. Illustrations on real data are provided.

PURPOSE To compare the double-Maddox rod test with other methods of measuring cyclodeviation DESIGN: Retrospective cohort study. METHODS We retrospectively identified 153 adults in a clinical practice with cyclodeviation assessed using double-Maddox rods, of whom 105 were also assessed using fusible synoptophore targets, 73 using nonfusible synoptophore targets, 118 using single-Maddox rod, and 43 using fundus photography. Relationships between double-Maddox rod and other tests were evaluated by calculating mean differences with 95% confidence intervals (CI), intraclass correlation coefficients (ICC), and Bland-Altman plots with linear regression. RESULTS Synoptophore cross-in-circle targets and the largest (of right or left) single-Maddox rod values were similar to double-Maddox values (mean differences: -1.2° and 0.1°, respectively; ICC: 0.79 and 0.82, respectively). Synoptophore house targets measured less excyclodeviation (mean difference: -2.7°; ICC: 0.71). Mean summed single-Maddox rod values were somewhat similar to double-Maddox values (mean difference: 1.5°; ICC: 0.85), but differences increased with greater cyclodeviation (r2 = 0.2678; P < .001). Fundus photographs showed large, uncorrelated differences compared with double-Maddox rod test, when summing right and left eyes and when using the largest of right or left (mean differences: 12.2° and 6.2°; ICC: -0.02 and 0.21, respectively), and differences increased with greater cyclodeviation (r2 = 0.4094; P < .001 and r2 = .1143; P= .03, respectively). CONCLUSIONS There was good agreement between double-Maddox and the largest single- Maddox test values and synoptophore cross-in-circle targets but poorer agreement with other tests. Further study is needed to understand which measurements best reflect true cyclodeviation and relationships with symptoms.

Gulisashvili et al. [Quant. Finance, 2018, 18(10), 1753-1765] provide a small-time asymptotics for the mass at zero under the uncorrelated stochastic-alpha-beta-rho (SABR) model by approximating the integrated variance with a moment-matched lognormal distribution. We improve the accuracy of the numerical integration by using the Gauss--Hermite quadrature. We further obtain the option price by integrating the constant elasticity of variance (CEV) option prices in the same manner without resorting to the small-strike volatility smile asymptotics of De Marco et al. [SIAM J. Financ. Math., 2017, 8(1), 709-737]. For the uncorrelated SABR model, the new option pricing method is accurate and arbitrage-free across all strike prices.

Evolutionary rescue occurs when genetic change allows a population to persist in response to an environmental change that would otherwise have led to extinction. Most studies of evolutionary rescue assume that species have either fully clonal or fully sexual reproduction; however, many species have partially clonal reproductive strategies in which they reproduce both clonally and sexually. Furthermore, the few evolutionary rescue studies that have evaluated partially clonal reproduction did not consider fluctuations in the environment, which are nearly ubiquitous in nature. Here, we use individual-based simulations to investigate how environmental fluctuations (either uncorrelated or positively autocorrelated) influence the effect of clonality on evolutionary rescue. We show that, for moderate magnitudes of environmental fluctuations, as was found in the absence of fluctuations, increasing the degree of clonality increases the probability of population persistence in response to an abrupt environmental change, but decreases persistence in response to a continuous, directional environmental change. However, with large magnitudes of fluctuations, both the benefits of clonality following a step change and the detrimental effects of clonality following a continuous, directional change are generally reduced; in fact, in the latter scenario, increasing clonality can even become beneficial if environmental fluctuations are autocorrelated. We also show that increased generational overlap dampens the effects of environmental fluctuations. Overall, we demonstrate that understanding the evolutionary rescue of partially clonal organisms requires not only knowledge of the species life history and the type of environmental change, but also an understanding of the magnitude and autocorrelation of environmental fluctuations.

Glacier mass-balance observations at seasonal resolution have been performed since 1914 at two sites on Claridenfirn, Switzerland. The measurements are the longest uninterrupted records of glacier mass balance worldwide. Here, we provide a complete re-analysis of the 106-year series (1914–2020), focusing on both point and glacier-wide mass balance. The approaches to evaluate and homogenize the direct observations are described in detail. Based on conservative assumptions, average uncertainties of$\pm$0.25 m w.e. are estimated for glacier-wide mass balances at the annual scale. It is demonstrated that long-term variations in mass balance are clearly driven by melting, whereas decadal changes in accumulation are uncorrelated with mass balance and can only be relevant in short periods. Mass change of Claridenfirn is impacted by dry calving at a frontal ice cliff. Considerations of ice volume flux at a cross-profile reveal long-term variations in frontal ice loss accounting for$\sim$9% of total annual ablation on average. The effect of changes in frontal ablation mostly explains$\lt$10% of the mass-balance difference relative to the period 1960–1990, but accounts for$\sim$20% in 2010–2020. Glacier mass changes are discussed in the context of observations throughout the European Alps indicating that Claridenfirn is regionally representative.