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Organic–inorganic‐halide‐perovskite (OIHP) based light‐emitting diodes (LEDs) are becoming more and more well‐described as having multiple potential uses in lighting and display technology, owing to their broad color gamut and high color purity. Recent research reveals that hole‐transport layers (HTLs) perform crucial roles in realizing high‐performance and highly stable perovskite light‐emitting diodes (PeLEDs). However, the exploration of organic HTLs for obtaining efficient PeLEDs has lagged behind compared to electron‐transport layers. In the past few years, some innovative HTLs have been developed for PeLEDs, which have demonstrated excellent performances in the devices. It has been established that HTL/OIHP interface has a significant impact on the crystallization behaviors and electrical properties of OIHP film. Herein, different types of organic HTLs (polymer/small molecule) used for PeLEDs are discussed. Also, the mechanism of action of those HTLs in perovskite devices is also presented. Moreover, the recent progress of organic HTLs in blue, green, and red PeLED devices is highlighted. Furthermore, the strategies to improve the performance of existing standard HTLs are also reviewed. Additionally, the challenges present in the PeLED technology are briefly summarized. Lastly, viewpoints regarding the ongoing obstacles and forthcoming prospects are emphasized. [ABSTRACT FROM AUTHOR]

Brain segmentation from neonatal MRI images is a very challenging task due to large changes in the shape of cerebral structures and variations in signal intensities reflecting the gestational process. In this context, there is a clear need for segmentation techniques that are robust to variations in image contrast and to the spatial configuration of anatomical structures. In this work, we evaluate the potential of synthetic learning, a contrast‐independent model trained using synthetic images generated from the ground truth labels of very few subjects. We base our experiments on the dataset released by the developmental Human Connectome Project, for which high‐quality images are available for more than 700 babies aged between 26 and 45 weeks postconception. First, we confirm the impressive performance of a standard UNet trained on a few volumes, but also confirm that such models learn intensity‐related features specific to the training domain. We then confirm the robustness of the synthetic learning approach to variations in image contrast. However, we observe a clear influence of the age of the baby on the predictions. We improve the performance of this model by enriching the synthetic training set with realistic motion artifacts and over‐segmentation of the white matter. Based on extensive visual assessment, we argue that the better performance of the model trained on real T2w data may be due to systematic errors in the ground truth. We propose an original experiment allowing us to show that learning from real data will reproduce any systematic bias affecting the training set, while synthetic models can avoid this limitation. Overall, our experiments confirm that synthetic learning is an effective solution for segmenting neonatal brain MRI. Our adapted synthetic learning approach combines key features that will be instrumental for large multisite studies and clinical applications. [ABSTRACT FROM AUTHOR]

There appears to be a mismatch between apparent incompetence in the world and the amount of sociological research it attracts. The aim of this article is to outline a sociology of incompetence and justify its value. I begin by defining incompetence as unsatisfactory performance relative to standards. Incompetence is thus intrinsically sociological in being negotiated and socially (re)constituted. The next section foregrounds how widespread and serious incompetence is. This renders effective sociological understanding crucial to welfare. The article then systematically analyses uses of the term in the British Journal of Sociology (a good quality general journal) to assess the current state of research. This analysis fully confirms the neglect of incompetence as a research topic. The next section proposes suitable methods for preliminary incompetence research addressing distinctive challenges like the stigma of being incompetent. These sections then allow incompetence to be better contextualised by other contributing concepts like power, bureaucracy and meritocracy. The final section justifies suggestions about directions for future research. [ABSTRACT FROM AUTHOR]

Although mouse‐tracking has been taken as a real‐time window on different aspects of human decision‐making processes, whether purely semantic information affects response conflict at the level of motor output as measured through mouse movements is still unknown. Here, across two experiments, we investigated the effects of semantic knowledge by predicting participants' performance in a standard keyboard task and in a mouse‐tracking task through distributional semantics, a usage‐based modeling approach to meaning. In Experiment 1, participants were shown word pairs and were required to perform a two‐alternative forced choice task selecting either the more abstract or the more concrete word, using standard keyboard presses. In Experiment 2, participants performed the same task, yet this time response selection was achieved by moving the computer mouse. Results showed that the involvement of semantic components in the task at hand is observable using both standard reaction times (Experiment 1) as well as using indexes extracted from mouse trajectories (Experiment 2). In particular, mouse trajectories reflected the response conflict and its temporal evolution, with a larger deviation for increasing word semantic relatedness. These findings support the validity of mouse‐tracking as a method to detect deep and implicit decision‐making features. Additionally, by demonstrating that a usage‐based model of meaning can account for the different degrees of cognitive conflict associated with task achievement, these findings testify the impact of the human semantic memory on decision‐making processes. [ABSTRACT FROM AUTHOR]

The use of brief dyslexia rating scales is increasing given current dyslexia legislation efforts across the United States. The purpose of this article is to provide an overview of the historical context of the use of brief dyslexia rating scales, strengths, and limitations of using these measures, criteria for selecting these measures, and a review of three commonly used brief dyslexia rating scales in the United States. A discussion of how brief dyslexia rating scales can be used in conjunction with other forms of assessment is also provided. Implications for practice on using brief dyslexia rating scales are addressed in the context of both assessment and intervention. Practitioner points: Dyslexia screeners are intended to identify students who are at risk of not meeting reading performance standards and consist of both performance‐based measures and brief dyslexia rating scales.Caution should be taken when using brief dyslexia rating scale screeners due to low sample sizes for certain populations, limited numbers of students with dyslexia in the standardization sample of some measures, and variable specificity and sensitivity levels.Practitioners are encouraged to utilize performance‐based screeners if scores on a brief dyslexia rating scale screener fall below a cut score. [ABSTRACT FROM AUTHOR]

Background: Accurate segmentation of brain glioma is a critical prerequisite for clinical diagnosis, surgical planning and treatment evaluation. In current clinical workflow, physicians typically perform delineation of brain tumor subregions slice‐by‐slice, which is more susceptible to variabilities in raters and also time‐consuming. Besides, even though convolutional neural networks (CNNs) are driving progress, the performance of standard models still have some room for further improvement. Purpose: To deal with these issues, this paper proposes an attention‐guided multi‐scale context aggregation network (AMCA‐Net) for the accurate segmentation of brain glioma in the magnetic resonance imaging (MRI) images with multi‐modalities. Methods: AMCA‐Net extracts the multi‐scale features from the MRI images and fuses the extracted discriminative features via a self‐attention mechanism for brain glioma segmentation. The extraction is performed via a series of down‐sampling, convolution layers, and the global context information guidance (GCIG) modules are developed to fuse the features extracted for contextual features. At the end of the down‐sampling, a multi‐scale fusion (MSF) module is designed to exploit and combine all the extracted multi‐scale features. Each of the GCIG and MSF modules contain a channel attention (CA) module that can adaptively calibrate feature responses and emphasize the most relevant features. Finally, multiple predictions with different resolutions are fused through different weightings given by a multi‐resolution adaptation (MRA) module instead of the use of averaging or max‐pooling to improve the final segmentation results. Results: Datasets used in this paper are publicly accessible, that is, the Multimodal Brain Tumor Segmentation Challenges 2018 (BraTS2018) and 2019 (BraTS2019). BraTS2018 contains 285 patient cases and BraTS2019 contains 335 cases. Simulations show that the AMCA‐Net has better or comparable performance against that of the other state‐of‐the‐art models. In terms of the Dice score and Hausdorff 95 for the BraTS2018 dataset, 90.4% and 10.2 mm for the whole tumor region (WT), 83.9% and 7.4 mm for the tumor core region (TC), 80.2% and 4.3 mm for the enhancing tumor region (ET), whereas the Dice score and Hausdorff 95 for the BraTS2019 dataset, 91.0% and 10.7 mm for the WT, 84.2% and 8.4 mm for the TC, 80.1% and 4.8 mm for the ET. Conclusions: The proposed AMCA‐Net performs comparably well in comparison to several state‐of‐the‐art neural net models in identifying the areas involving the peritumoral edema, enhancing tumor, and necrotic and non‐enhancing tumor core of brain glioma, which has great potential for clinical practice. In future research, we will further explore the feasibility of applying AMCA‐Net to other similar segmentation tasks. [ABSTRACT FROM AUTHOR]

Using item‐response theory to model rater effects provides an alternative solution for rater monitoring and diagnosis, compared to using standard performance metrics. In order to fit such models, the ratings data must be sufficiently connected in order to estimate rater effects. Due to popular rating designs used in large‐scale testing scenarios, there tends to be a large proportion of missing data, yielding sparse matrices and estimation issues. In this article, we explore the impact of different types of connectedness, or linkage, brought about by using a linkage set—a collection of responses scored by most or all raters. We also explore the impact of the properties and composition of the linkage set, the different connectedness yielded from different rating designs, and the role of scores from automated scoring engines. In designing monitoring systems using the rater response version of the generalized partial credit model, the study results suggest use of a linkage set, especially a large one that is comprised of responses representing the full score scale. Results also show that a double‐human‐scoring design provides more connectedness than a design with one human and an automated scoring engine. Furthermore, scores from automated scoring engines do not provide adequate connectedness. We discuss considerations for operational implementation and further study. [ABSTRACT FROM AUTHOR]

The subjective aspect of standard‐setting is often criticized, yet data‐driven standard‐setting methods are rarely applied. Therefore, we applied a mixture Rasch model approach to setting performance standards across several testing programs of various sizes and compared the results to existing passing standards derived from traditional standard‐setting methods. We found that heterogeneity of the sample is clearly necessary for the mixture Rasch model approach to standard setting to be useful. While possibly not sufficient to determine passing standards on their own, there may be value in these data‐driven models for providing additional validity evidence to support decision‐making bodies entrusted with establishing cut scores. They may also provide a useful tool for evaluating existing cut scores and determining if they continue to be supported or if a new study is warranted. [ABSTRACT FROM AUTHOR]

The vision for fib MC2020 is to go beyond the point reached by fib MC2010, recent ISO codes, such as ISO 16311, and the current Eurocode activities to extend the application of Eurocodes to existing structures. The contents of fib MC2020 suit these forward‐looking objectives, dealing both with the design of new structures and all the activities associated with the life‐cycle management of existing concrete structures including matters, such as in‐service assessment and interventions upon them, including situations where new structural members are incorporated as parts of existing structures. With the fib MC2020 adaptations taking sustainability as a fundamental requirement, defining implications for subsidiary performance requirements critical to structural design and assessment procedures, it is logical that Model Code 2020 explicitly introduces and consequently seeks to make use of performance‐based concepts. A focus on performance provides a potential way to better align the interests of owners, users, technical consultants (such as structural engineers, material engineers, etc.), contractors, as well as material suppliers and manufacturers. It is envisaged that implementing the concept of the performance‐based approach in design and assessment will encourage rational design and technological progress which will facilitate the creation of superior structures for future generations, by removing constraints to the use of novel types of concrete and reinforcing materials and offering possibilities for optimization of solutions that better fit the needs of stakeholders. This paper addresses the principles of the performance‐based approach to design and assessment and discusses the manner in which it has been introduced in fib MC2020. The benefits and burdens associated with the performance‐based approach and the traditional prescriptive approach to engineering specification are discussed, both from a technical and process/commercial/contractual point of view, to describe the overall benefits of the performance‐based approach. Finally, the future outlook for a coherent integration of the performance‐based approach in design and assessment is addressed, paving the way for further work on standardization for sustainable concrete structures. [ABSTRACT FROM AUTHOR]

Temporal event localisation (TEL) has recently attracted increasing attention due to the rapid development of video platforms. Existing methods are based on either fully/weakly supervised or unsupervised learning, and thus they rely on expensive data annotation and time‐consuming training. Moreover, these models, which are trained on specific domain data, limit the model generalisation to data distribution shifts. To cope with these difficulties, the authors propose a zero‐shot TEL method that can operate without training data or annotations. Leveraging large‐scale vision and language pre‐trained models, for example, CLIP, we solve the two key problems: (1) how to find the relevant region where the event is likely to occur; (2) how to determine event duration after we find the relevant region. Query guided optimisation for local frame relevance relying on the query‐to‐frame relationship is proposed to find the most relevant frame region where the event is most likely to occur. Proposal generation method relying on the frame‐to‐frame relationship is proposed to determine the event duration. The authors also propose a greedy event sampling strategy to predict multiple durations with high reliability for the given event. The authors' methodology is unique, offering a label‐free, training‐free, and domain‐free approach. It enables the application of TEL purely at the testing stage. The practical results show it achieves competitive performance on the standard Charades‐STA and ActivityCaptions datasets. [ABSTRACT FROM AUTHOR]

Content‐based image retrieval (CBIR) is the problem of searching for items in an image database that are similar to the query image. Most of the existing image retrieval methods are trained based on metric learning loss functions (e.g. contrastive loss or triplet loss), however, which require the use of hard sample mining strategies (HMS) to better train the model. The HMS implies that picking out hard positive or negative samples increases the complexity of model training and requires a large amount of additional training time. To address this issue, lessons from recent work are leveraged on representation learning and a model called GS is proposed that combines the state‐of‐the‐art Generalized‐Mean (GeM) pooling and the smoothed average precision (AP). The entire network can be learned end‐to‐end by approximating the non‐differentiable AP function to a differentiable one‐without mining hard samples, only image‐level annotations. A model named GSA is also presented which achieves excellent retrieval performance jointly trained by two various loss functions. Experimental results validate the effectiveness of the proposed approach and demonstrate the competitive performance on a common standard image retrieval dataset (Revisited Oxford and Paris). [ABSTRACT FROM AUTHOR]

Bamboo scrimber and carbonized bamboo scrimber are new green and sustainable materials that have recently gained widespread attention and application in construction and other fields. However, their production is accompanied by the generation of a large number of residues, such as bamboo particles (BPs) and carbonized bamboo particles (CBPs). In this study, we used BPs and CBPs as reinforcing phases and phenol‐formaldehyde (PF) resin, which is mainly used to manufacture bamboo scrimber, as the matrix to prepare bamboo particle composites (BPCs). The physical, flexural, and thermal properties of the composites were characterized, and the activation energies were analyzed and compared using Kissinger and Flynn–Wall–Ozawa (FWO) methods. The results showed that the blending system composed of two types of bamboo processing residues demonstrated significant composite performance enhancement. The BPC performance met the standard requirements for furniture particleboard, and the potential exists to further improve its thermal properties. This study fills the current gap in the kinetic analysis of BPCs and contributes to the further understanding and application of this material, thus facilitating the industrial use of bamboo processing residues and bamboo scrimber for sustainable development and economic benefits. [ABSTRACT FROM AUTHOR]

A stratified analysis of the differences in proportions has been widely employed in epidemiological research, social sciences, and drug development. It provides a useful framework for combining data across strata to produce a common effect. However, for rare events with incidence rates close to zero, popular confidence intervals for risk differences in a stratified analysis may not have appropriate coverage probabilities that approach the nominal confidence levels and the algorithms may fail to produce a valid confidence interval because of zero events in both the arms of a stratum. The main objective of this study is to evaluate the performance of certain methods commonly employed to construct confidence intervals for stratified risk differences when the response probabilities are close to a boundary value of zero or one. Additionally, we propose an improved stratified Miettinen–Nurminen confidence interval that exhibits a superior performance over standard methods while avoiding computational difficulties involving rare events. The proposed method can also be employed when the response probabilities are close to one. [ABSTRACT FROM AUTHOR]

Power‐Flow (PF) solution in isolated microgrids has attracted notable attention recently, because these systems present various particularities compared with the traditional PF solution in large meshed transmission networks. In this sense, this paper develops a novel Newton‐like PF solver for isolated microgrids. The new proposal is based on the Modified Midpoint method and shows high convergence order with relatively low computational burden. These characteristics bring superior theoretical performance compared with the standard Newton–Raphson (NR) method and other high order techniques, which has been conventionally used. Extensive simulations are performed on various small‐, and large‐scale benchmark Microgrids under different loading conditions and R/X ratios. Results provided serve to confirm the theoretical features of the developed solver, outperforming the NR technique as well as other recently developed solvers in all the studied systems with acceptable reliability even under high stressed conditions. [ABSTRACT FROM AUTHOR]

The wild bootstrap is a nonparametric tool that can be used to estimate a sampling distribution in the presence of heteroscedastic errors. In particular, the wild bootstrap enables us to compute confidence regions for regression parameters under non‐i.i.d. models. While the wild bootstrap may perform well in these settings, its obvious drawback is a lack of computational efficiency. The wild bootstrap requires a large number of bootstrap replications, making the use of this tool impractical when dealing with big data. We introduce the analytic wild bootstrap (ANWB), which provides a nonparametric alternative way of constructing confidence regions for regression parameters. The ANWB is superior to the wild bootstrap from a computational standpoint while exhibiting similar finite‐sample performance. We report simulation results for both least squares and ridge regression. Additionally, we test the ANWB on a real dataset and compare its performance with that of other standard approaches. [ABSTRACT FROM AUTHOR]

Frontal alpha asymmetry (FAA) is considered to be a reliable marker of affective processing and psychopathology. Traditionally, the magnitude of alpha is calculated by taking the average over a nomothetic fixed frequency window (e.g., 8 to 13 Hz). Alternatively, methods have been proposed to extract individualized alpha frequency (IAF) peaks and windows in hopes of improving the reliability and validity of signal detection. However, no study has compared the nomothetic to IAF approaches to examine the reliability and validity of resting FAA in a large well‐characterized data set. In this study, we assessed the psychometric performance of the standard fixed window approach, a PZ‐alpha based IAF approach and a global‐alpha based IAF windows detection approach on a previously collected EEG data set (8 recordings per subject collected on four occasions across two weeks). Our results revealed that resting FAA calculated with these three different methods are highly correlated at all frontal regions (mean r =.98). The stability across the 8 recordings over the two weeks also showed no substantial difference between approaches as indicated by intraclass correlations. Moreover, internal‐consistency reliability, validity with respect to measures of emotion and emotion‐related psychopathology and state–trait Structure equation model (SEM) fitting were evaluated and yielded no significant differences across methods. Our results supported the overall reliability and validity of two different IAF approaches to assessing resting FAA but fail to find any incremental advantage over nomothetic approaches to defining alpha bands. Guidelines for methods selection for future research are provided. Frontal EEG asymmetry has been proposed as a marker of risk for psychopathology, especially depression. In the spirit of precision medicine, individualized alpha frequency (IAF) measures for frontal EEG asymmetry might have value for better identifying those at risk for MDD and understanding mechanisms by individually adjusting the alpha band to each individual's peak alpha frequency. This is the first paper to directly compare frontal EEG asymmetry as a marker of risk for MDD using the nomothetic approach versus two IAF approaches. In a large (N = 306) sample of depressed, formerly depressed, and never depressed individuals, we found that IAF is reliable, and as good as, but not better than, the standard method in differentiating individuals on the basis of a history of MDD. [ABSTRACT FROM AUTHOR]

Validity of performance standards is a key element for the defensibility of standard setting results, and validating performance standards requires collecting multiple pieces of evidence at every step during the standard setting process. This study employs a statistical procedure, latent class analysis, to set performance standards and compares latent class analysis results with previously established performance standards via the modified‐Angoff method for cross‐validation. The context of the study is an operational large‐scale science assessment administered in one of the southern states in the United States. Results show that the number of classes that emerged in the latent class analysis concurs with the number of existing performance levels. In addition, there is a substantial level of agreement between latent class analysis results and modified‐Angoff method in terms of classifying students into the same performance levels. Overall, the findings establish evidence for the validity of the performance standards identified via the modified‐Angoff method. Practical implications of the study findings are discussed. [ABSTRACT FROM AUTHOR]

We address two persistent challenges in large‐scale assessments of the Next Generation Science Standards: (a) the validity of score interpretations that target the standards broadly and (b) how to structure claims for assessments of this complex domain. The NGSS pose a particular challenge for specifying claims about students that evidence from summative assessments can support. As a solution, we propose tiered claims, which explicitly distinguish between claims about what students have done or can do on test items—which are typically easier to support under current test designs—and claims about what students could do in the broader domain of performances described by the standards, for which novel evidence is likely required. We discuss the positive implications of tiered claims for test construction, validation, and reporting of results. [ABSTRACT FROM AUTHOR]

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short‐term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real‐time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate‐and‐State (CRS) and statistical Epidemic‐Type Aftershock Sequence (ETAS) models to forecast the space‐time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood‐based metrics and compare their skill against the best‐performing CRS and ETAS models among those developed with the real‐time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real‐time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments (≥ $\ge $2 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next‐generation seismic catalogs. Plain Language Summary: Modern enhanced seismicity catalogs provide an unprecedented picture of how earthquake sequences evolve. These next‐generation catalogs will be released and updated in real time conditions soon. Therefore, we ask whether the extra information they provide can be exploited to boost the performance of current popular models of short‐term earthquake forecasting, namely, physical models of fault‐to‐fault stress interactions and purely statistical models. We use three enhanced catalogs for the 2016–2017 Central Italy earthquake sequence to develop physical and statistical forecasts for the first 6 months of M3+ seismicity. By means of well‐established tests, we quantify the predictive skill of the models and benchmark them against forecasts developed using real‐time data sets only. We find that both physical and statistical forecasts benefit from gradually incorporating the triggering contributions from the many small, newly revealed events reported in the enhanced catalogs, but their overall performance does not convincingly improve compared to their respective real‐time realizations. Sensitivity tests show how future experimental setups should consider that (a) even small variations in the basic components of different catalogs can affect the performance of the resulting forecasts and (b) the typically adopted model spatial resolutions are too coarse to capture small‐scale triggering patterns described by enhanced catalogs. Key Points: We compare retrospective forecast models informed by enhanced versus real‐time earthquake catalogs for the 2016–2017 Central Italy sequenceTo realize the benefits of high‐resolution catalogs, models should integrate advanced experimental setups, like finer spatial gridsResults stimulate further testing on the optimal design of next‐generation forecast models based on enhanced seismic catalogs [ABSTRACT FROM AUTHOR]

Animals regulate their nutrient consumption to maximize the expression of fitness traits with competing nutritional needs ("nutritional trade‐offs"). Nutritional trade‐offs have been studied using a response surface modeling approach known as the Geometric Framework for nutrition (GF). Current experimental design in GF studies does not explore the entire area of the nutritional space resulting in performance landscapes that may be incomplete. This hampers our ability to understand the properties of the performance landscape (e.g., peak shape) from which meaningful biological insights can be obtained. Here, I tested alternative experimental designs to explore the full range of the performance landscape in GF studies. I compared the performance of the standard GF design strategy with three alternatives: hexagonal, square, and random points grid strategies with respect to their accuracy in reconstructing baseline performance landscapes from a landmark GF dataset. I showed that standard GF design did not reconstruct the properties of baseline performance landscape appropriately particularly for traits that respond strongly to the interaction between nutrients. Moreover, the peak estimates in the reconstructed performance landscape using standard GF design were accurate in terms of the nutrient ratio but incomplete in terms of peak shape. All other grid designs provided more accurate reconstructions of the baseline performance landscape while also providing accurate estimates of nutrient ratio and peak shape. Thus, alternative experimental designs can maximize information from performance landscapes in GF studies, enabling reliable biological insights into nutritional trade‐offs and physiological limits within and across species. [ABSTRACT FROM AUTHOR]

During periods of drought, the irrigation needs of current warm‐season turfgrass cultivars and frequent municipal water use restrictions present a major challenge to the turfgrass industry. Turfgrass breeding programs have responded by placing more emphasis on improved drought response. During 2012–2013, 560 genotypes of four warm‐season turfgrass species developed by five southern breeding programs were evaluated for drought response in replicated field trials at seven locations. Breeders selected 35 genotypes as drought‐tolerant selections (DTS) for further evaluation. The objectives of this study were to verify superior drought response among DTS under short‐term drought conditions and to assess the effectiveness of this approach as a viable breeding strategy to improve drought response in warm‐season turfgrasses. Forty‐seven genotypes including standard commercial cultivars of zoysiagrass (Zoysia spp. Willd.), bermudagrass [Cynodon spp. (L.) Pers.], St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze], and seashore paspalum (Paspalum vaginatum Swartz) were exposed to dry‐downs in three consecutive years by withholding irrigation and excluding rainfall. Significant differences in drought performance were seen across genotypes over the multiyear study. Statistical contrasts found that DTS of zoysiagrass, St. Augustinegrass, and seashore paspalum generally performed better than the standard cultivars. Top‐performing DTS zoysiagrass and St. Augustinegrass genotypes maintained >50% green cover longer than the average of the standard cultivars. Based on this research, multilocational screening for drought tolerance was effective in selection of new genotypes with superior performance to standard cultivars and continued screening of turfgrass germplasm to identify new drought‐tolerant genotypes is warranted. [ABSTRACT FROM AUTHOR]

The United Nations Decade of Ecosystem Restoration is an opportunity for States to advance the development of substantive and qualitative international law obligations for conducting restoration activities. This will help countries move beyond the more quantitative target‐driven approach that currently focuses international commitments on the percentage of degraded areas that have to be restored. In this paper, we argue for two pathways for States to accelerate and pursue international obligations to undertake ecological restoration. Firstly, we advocate for the development of a new international legal principle on ecological restoration, adding to existing international environmental law principles such as the prevention principle, and aiming at achieving the highest level of recovery possible. Secondly, we advocate to utilize available mechanisms through the 1992 Convention on Biological Diversity and create a new protocol that will spell out a high ambition level for ecological restoration and a legal basis for adopting generally accepted rules and standards for restoration. The voluntary SER Principles and Standards can play an important role in the development of the legal principle on ecological restoration and standards of best practice. [ABSTRACT FROM AUTHOR]

In order to understand deposit formation during urea selective catalytic reduction (SCR) resulting from isocyanic acid (HNCO) formation, the present study investigates the potential of HNCO hydrolysis by spatially resolved gas phase concentration profiles along a single catalyst channel of commercial Cu‐zeolite and V‐based SCR catalysts. The spatially resolved profiles, obtained in a special hot gas test rig via capillary technique, provide information on reaction rates of HNCO hydrolysis, NH3 adsorption and NO conversion, hereby revealing a better performance of the standard V‐based catalyst regarding the HNCO hydrolysis, which is attributed to the TiO2 support. [ABSTRACT FROM AUTHOR]

The interactive HOMER is automated by the use of a set of parameters. This approach retains the skill and flexibility of an interactive method, but adds the speed and reproducibility of an automatic method. The automation of the interactive HOMER also enables systematic testing. Its performance is evaluated by the homogenization of the Indecis homogenization benchmark datasets. The overall performance of the interactive HOMER compares well with the methods using the homogenization tools Climatol and ACMANT and surpass the performance of the standard automatic HOMER. All the homogenization methods reduce the initial error. The average residual error and all error percentiles below and including the 99th error percentile do not differ more than 0.3°C between interactive HOMER and the other methods. Interactive HOMER and Climatol report fewer homogeneity breaks than the true number, while standard automatic HOMER and ACMANT report more homogeneity breaks. Across the methods, a higher number of reported homogeneity breaks renders a higher share of the true homogeneity breaks to be detected, but also a higher share of the reported breaks to be false positives. On average the differences in the corrected times series are small between the methods implying that the choice of homogenization method is a matter of preference. [ABSTRACT FROM AUTHOR]

The United Nations Decade of Ecosystem Restoration is an opportunity for States to advance the development of substantive and qualitative international law obligations for conducting restoration activities. This will help countries move beyond the more quantitative target‐driven approach that currently focuses international commitments on the percentage of degraded areas that have to be restored. In this paper, we argue for two pathways for States to accelerate and pursue international obligations to undertake ecological restoration. Firstly, we advocate for the development of a new international legal principle on ecological restoration, adding to existing international environmental law principles such as the prevention principle, and aiming at achieving the highest level of recovery possible. Secondly, we advocate to utilize available mechanisms through the 1992 Convention on Biological Diversity and create a new protocol that will spell out a high ambition level for ecological restoration and a legal basis for adopting generally accepted rules and standards for restoration. The voluntary SER Principles and Standards can play an important role in the development of the legal principle on ecological restoration and standards of best practice. [ABSTRACT FROM AUTHOR]

This essay argues for the importance of error as an organizing concept in the management of hazardous technical systems to high levels of reliability and safety. The concept of "error" has been essential to the development of high reliability organizations (HROs). As practiced in HROs, error management has also been an important strategy for the management of uncertainty. "Uncertainty" has been conceived by some analysts as a condition that can convey little or no reliable information about its own boundary conditions or its specific threat to the operation of complex systems. The argument here is that uncertainty is differentiated and specified in HROs and provides important information in relation to error. Uncertainty does not, in the special context of HROs, end the possibility and practice of reliable management. In fact, error in HROs can be a starting point for the further analysis of ways in which uncertainty itself can be managed reliably. But the argument offered here does not mean that uncertainty does not challenge reliability in other settings. The COVID‐19 pandemic is offered as an example of how uncertainties may invalidate even the application of "reliability" as a performance standard in certain domains of management and policy. [ABSTRACT FROM AUTHOR]

Causal models are notoriously difficult to validate because they make untestable assumptions regarding confounding. New scientific experiments offer the possibility of evaluating causal models using prediction performance. Prediction performance measures are typically robust to violations in causal assumptions. However, prediction performance does depend on the selection of training and test sets. Biased training sets can lead to optimistic assessments of model performance. In this work, we revisit the prediction performance of several recently proposed causal models tested on a genetic perturbation data set of Kemmeren. We find that sample selection bias is likely a key driver of model performance. We propose using a less‐biased evaluation set for assessing prediction performance and compare models on this new set. In this setting, the causal models have similar or worse performance compared to standard association‐based estimators such as Lasso. Finally, we compare the performance of causal estimators in simulation studies that reproduce the Kemmeren structure of genetic knockout experiments but without any sample selection bias. These results provide an improved understanding of the performance of several causal models and offer guidance on how future studies should use Kemmeren. [ABSTRACT FROM AUTHOR]

Humans have the ability to learn surprisingly complicated statistical information in a variety of modalities and situations, often based on relatively little input. These statistical learning (SL) skills appear to underlie many kinds of learning, but despite their ubiquity, we still do not fully understand precisely what SL is and what individual differences on SL tasks reflect. Here, we present experimental work suggesting that at least some individual differences arise from stimulus‐specific variation in perceptual fluency: the ability to rapidly or efficiently code and remember the stimuli that SL occurs over. Experiment 1 demonstrates that participants show improved SL when the stimuli are simple and familiar; Experiment 2 shows that this improvement is not evident for simple but unfamiliar stimuli; and Experiment 3 shows that for the same stimuli (Chinese characters), SL is higher for people who are familiar with them (Chinese speakers) than those who are not (English speakers matched on age and education level). Overall, our findings indicate that performance on a standard SL task varies substantially within the same (visual) modality as a function of whether the stimuli involved are familiar or not, independent of stimulus complexity. Moreover, test–retest correlations of performance in an SL task using stimuli of the same level of familiarity (but distinct items) are stronger than correlations across the same task with stimuli of different levels of familiarity. Finally, we demonstrate that SL performance is predicted by an independent measure of stimulus‐specific perceptual fluency that contains no SL component at all. Our results suggest that a key component of SL performance may be related to stimulus‐specific processing and familiarity. [ABSTRACT FROM AUTHOR]

Covalent organic frameworks (COFs) are a novel class of crystalline porous polymers, which possess high porosity, excellent stability, and regular nanochannels. 2D COFs provide a 1D nanochannel to form the proton transport channels. The abovementioned features afford a powerful potential platform for designing materials as proton transportation carriers. Herein, the authors incorporate sulfonic acid groups on the pore walls as proton sources for enhancing proton transport conductivity in the 1D channel. Interestingly, the sulfonic acid COFs (S‐COFs) electrolytes being binder free exhibit excellent proton conductivity of ≈1.5 × 10−2 S cm−1 at 25 ℃ and 95% relative humidity (RH), which rank the excellent performance in standard proton‐conducting electrolytes. The S‐COFs electrolytes keep the high proton conduction over the 24 h. The activation energy is estimated to be as low as 0.17 eV, which is much lower than most reported COFs. This research opens a new window to evolve great potential of structural design for COFs as the high proton‐conducting electrolytes. [ABSTRACT FROM AUTHOR]

Spatial transcriptomics is considered as an important part of spatiotemporal molecular images to bridge molecular information with clinical images. Of those potentials and opportunities, the excellent quality of human sample preparation and handling will ensure the precise and reliable information generated from clinical spatial transcriptome. The present study aims at defining potential factors that might influence the quality of spatial transcriptomics in lung cancer, para‐cancer, or normal tissues, pathological images of sections and the RNA integrity before spatial transcriptome sequencing. We categorised potential influencing factors from clinical aspects, including patient selection, pathological definition, surgical types, sample harvest, temporary preservation conditions and solutions, frozen approaches, transport and storage conditions and duration. We emphasis on the relationship between the combination of histological scores with RNA integrity number (RIN) and the unique molecular identifier (UMI), which is determines the quality of of spatial transcriptomics; however, we did not find significantly relevance between them. Our results showed that isolated times and dry conditions of sample are critical for the UMI and the quality of spatial transcriptomic samples. Thus, clinical procedures of sample preparation should be furthermore optimised and standardised as new standards of operation performance for clinical spatial transcriptome. Our data suggested that the temporary preservation time and condition of samples at operation room should be within 30 min and in 'dry' status. The direct cryo‐preservation within OCT media for human lung sample is recommended. Thus, we believe that clinical spatial transcriptome will be a decisive approach and bridge in the development of spatiotemporal molecular images and provide new insights for understanding molecular mechanisms of diseases at multi‐orientations. [ABSTRACT FROM AUTHOR]

Purpose: To assess catheter reconstruction and error detection performance of an afterloader (Elekta Brachytherapy, Veenendaal, The Netherlands) equipped with electromagnetic (EM) tracking capabilities. Materials/Methods: The Flexitron research unit used was equipped with a special check cable integrating an EM sensor (NDI Aurora V3) that enables tracking and reconstruction capability. The reconstructions of a 24‐cm long catheter were performed using two methods: continuous fixed‐speed check cable backward stepping (at 1, 2.5, 5, 10, 25 and 50 cm/s) and stepping through each dwell position every 1 mm. The ability of the system to differentiate between two closely located (parallel) catheters was investigated by connecting catheters to the afterloader and moving it from its axis with an increment of 1 mm. A robotic arm (Meca500, Mecademic, Montreal) with an accuracy of 0.01 mm was used to move the catheter between each reconstruction. Reconstructions were obtained with a locally weighted scatterplot smoothing algorithm. To quantify the reconstruction accuracy, distances between two catheters were computed along the reconstruction track with a 5 mm step. The reconstructions of curve catheter paths were assessed through parallel and perpendicular phantom configuration to the EM field generator. Indexer length and lateral errors were simulated and a ROC analysis was made. Results: Using a 50 cm/s check cable speed does not allow for accurate reconstructions. A slower check cable speed results in better reconstruction performance and smaller standard deviations. At 1 cm/s, a catheter can be shifted laterally down to 1 mm and all paths can be uniquely identified. The optimum operating distance from the field generator (50 to 300 mm) resulted in a lower absolute mean deviation from the expected value (0.2 ± 0.1 mm) versus being positioned on the edge of the electromagnetic sensitive detection volume (0.6 ±0.3 mm). The reconstructions of curved catheters with a check cable speed under 5 cm/s gave a 0.8 mm ±0.3 mm error, or better. All indexer and lateral shifts of 1 mm were detected with a check cable speed of 2.5 cm/s or lower. Conclusions: The EM‐equipped Flexitron afterloader is able to track and reconstruct catheters with high accuracy. A speed under 5 cm/s is recommended for straight and curved catheter reconstructions. It allows catheter identification down to 1 mm inter‐catheter distance shift. The check cable can also be used to detect common shift errors. [ABSTRACT FROM AUTHOR]

Introduction: Kidney transplant (KT) directors are general surgeons or urologists. All KT centers must meet established performance standards. However, it has not been established if general surgery and urology led programs have disparate outcomes. Methods: Transplant outcomes and donor‐recipient characteristics by director training were investigated. Organ Procurement and Transplantation Network (OPTN) directory, program websites were analyzed for surgical director demographics. Scientific Registry of Transplant Recipients (SRTR) 1‐year kidney survival and deceased donor (DD) wait‐time rankings were evaluated. A retrospective analysis of 142 157 KT recipients from 2010 to 2019 was performed using the United Network for Organ Sharing (UNOS) database. Results: One hunderd and seventy three (90.6%) KT programs were led by general surgeons. There were no significant differences in gender, ethnicity, region, credentials, or fellowship completion. Recipients undergoing KT with urology led programs were older (P =.002) and had longer wait‐times (P <.001). These centers used higher KDPI (.47 vs..45, P <.001) and higher HLA mismatch (3.92 vs. 3.89, P =.02) kidneys. Urology led centers utilized living donors less frequently (32.1% vs. 35.8%, P <.001) and had longer CIT (15.44 vs. 12.21, P <.001). Both had similar SRTR ranking of 1‐year survival and DD wait‐time. Conclusion: Most directors were general surgeon. Patient outcomes did not differ by transplant director training. Urologists represent a viable option for KT leadership and recruitment should be encouraged. [ABSTRACT FROM AUTHOR]

Objective: Characterized by setting high standards for performance, perfectionism is a transdiagnostic process implicated in the development and maintenance of psychopathology. In contrast, cognitive flexibility is associated with enhanced mental health. Yet, the relationship between perfectionism and cognitive flexibility is understudied. We examined the relationship between perfectionism and cognitive flexibility, and whether emotion regulation strategies moderated the association between them. Method: Adult participants (N = 486) were recruited online and completed questionnaires on perfectionism, emotion regulation and cognitive flexibility. Results: Perfectionism negatively correlated with one of the two aspects of cognitive flexibility assessed. Reappraisal, but not suppression, moderated the relationship between perfectionism and flexibility. Conclusions: Results indicate that perfectionism is associated with inflexible appraisal of everyday challenges. Additionally, cognitive reappraisal attenuates the negative relationship between perfectionism and cognitive flexibility; except in individuals with high narcissistic perfectionism for whom the debilitating relationship between the two variables is enhanced by reappraisal. [ABSTRACT FROM AUTHOR]