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Many researchers favor repeated measures designs because they allow the detection of within-person change over time and typically have higher statistical power than cross-sectional designs. However, the plethora of inputs needed for repeated measures designs can make sample size selection, a critical step in designing a successful study, difficult. Using a dental pain study as a driving example, we provide guidance for selecting an appropriate sample size for testing a time by treatment interaction for studies with repeated measures. We describe how to (1) gather the required inputs for the sample size calculation, (2) choose appropriate software to perform the calculation, and (3) address practical considerations such as missing data, multiple aims, and continuous covariates.

Modern dune fields are valuable sources of information for the large-scale analysis of terrestrial and planetary environments and atmospheres, but their study relies on understanding the small-scale dynamics that constantly generate new dunes and reshape older ones. Here, we designed a landscape-scale experiment at the edge of the Gobi desert, China, to quantify the development of incipient dunes under the natural action of winds. High-resolution topographic data documenting 42 mo of bedform dynamics are examined to provide a spectral analysis of dune pattern formation. We identified two successive phases in the process of dune growth, from the initial flat sand bed to a meterhigh periodic pattern. We focus on the initial phase, when the linear regime of dune instability applies, and measure the growth rate of dunes of different wavelengths. We identify the existence of a maximum growth rate, which readily explains the mechanism by which dunes select their size, leading to the prevalence of a 15-m wavelength pattern. We quantitatively compare our experimental results with the prediction of the dune instability theory using transport and flow parameters independently measured in the field. The remarkable agreement between theory and observations demonstrates that the linear regime of dune growth is permanently expressed on low-amplitude bed topography, before larger regular patterns and slip faces eventually emerge. Our experiment underpins existing theoretical models for the early development of eolian dunes, which can now be used to provide reliable insights into atmospheric and surface processes on Earth and other planetary bodies.

A prerequisite to effectively managing fish populations is to understand what factors and processes, including predation and changing environments, affect the survival of individuals. In anadromous fishes, the transition from freshwater to marine habitats is considered a critical period regulating population abundance due to high and variable mortality rates. During this period, conditions experienced in freshwater may influence size- and growth-selective mortality in the ocean. To determine if size- or growth-selective mortality occurred in juvenile Interior Columbia River spring Chinook salmon Oncorhynchus tshawytscha as they migrated through the Lower Columbia River and Estuary (LCRE) and during early marine residence, we examined 2 cohorts in years with differing survival (2016 and 2017). We reconstructed the size and growth of individual Chinook salmon from otoliths and compared these attributes in fish caught at 4 sites in the LCRE to those caught in the ocean off Oregon and Washington. We observed evidence of growth-selective mortality in 2017 but not 2016. Specifically, in 2017, when overall survival was lower, individuals caught in the ocean grew significantly faster in freshwater than individuals caught in the estuary. Given that the fish had resided in the ocean for an average of 30 d, these results indicate growth-selective mortality in 2017 occurred soon after ocean entry. The finding that growth in freshwater may impact marine survival adds to the growing body of evidence that processes occurring both prior to and after ocean entry impact the marine survival of this species.

Background Implantable Collamer Lens (ICL) surgery has been proven to be a safe, effective, and predictable method for correcting myopia and myopic astigmatism. However, predicting the vault and ideal ICL size remains technically challenging. Despite the growing use of artificial intelligence (AI) in ophthalmology, no AI studies have provided available choices of different instruments and combinations for further vault and size predictions. This study aimed to fill this gap and predict post-operative vault and appropriate ICL size utilizing the comparison of numerous AI algorithms, stacking ensemble learning, and data from various ophthalmic devices and combinations. Results This retrospective and cross-sectional study included 1941 eyes of 1941 patients from Zhongshan Ophthalmic Center. For both vault prediction and ICL size selection, the combination containing Pentacam, Sirius, and UBM demonstrated the best results in test sets [ R 2  = 0.499 (95% CI 0.470–0.528), mean absolute error = 130.655 (95% CI 128.949–132.111), accuracy = 0.895 (95% CI 0.883–0.907), AUC = 0.928 (95% CI 0.916–0.941)]. Sulcus-to-sulcus (STS), a parameter from UBM, ranked among the top five significant contributors to both post-operative vault and optimal ICL size prediction, consistently outperforming white-to-white (WTW). Moreover, dual-device combinations or single-device parameters could also effectively predict vault and ideal ICL size, and excellent ICL selection prediction was achievable using only UBM parameters. Conclusions Strategies based on multiple machine learning algorithms for different ophthalmic devices and combinations are applicable for vault predicting and ICL sizing, potentially improving the safety of the ICL implantation. Moreover, our findings emphasize the crucial role of UBM in the perioperative period of ICL surgery, as it provides key STS measurements that outperformed WTW measurements in predicting post-operative vault and optimal ICL size, highlighting its potential to enhance ICL implantation safety and accuracy.

Rodent preference for scatter-hoarding large seeds has been widely considered to favor the evolution of large seeds. Previous studies supporting this conclusion were primarily based on observations at earlier stages of seed dispersal, or on a limited sample of successfully established seedlings. Because seed dispersal comprises multiple dispersal stages, we hypothesized that differential foraging preference on seed size by animal dispersers at different dispersal stages would ultimately result in medium-sized seeds having the highest dispersal success rates. In this study, by tracking a large number of seeds for 5 yr, we investigated the effects of seed size on seed fates from seed removal to seedling establishment of a dominant plant Pittosporopsis kerrii (Icacinaceae) dispersed by scatter-hoarding rodents in tropical forest in southwest China. We found that small seeds had a lower survival rate at the early dispersal stage where more small seeds were predated at seed stations and after removal; large seeds had a lower survival rate at the late dispersal stage, more large seeds were recovered, predated after being cached, or larder-hoarded. Medium-sized seeds experienced the highest dispersal success. Our study suggests that differential foraging preferences by scatter-hoarding rodents at different stages of seed dispersal could result in conflicting selective pressures on seed size and higher dispersal success of medium-sized seeds.

Many collapsed fish populations have failed to recover after a decade or more with little fishing. This may reflect evolutionary change in response to the highly selective mortality imposed by fisheries. Recent experimental work has demonstrated a rapid genetic change in growth rate in response to size-selective harvesting of laboratory fish populations. Here, we use a 30-year time-series of back-calculated lengths-at-age to test for a genetic response to size-selective mortality in the wild in a heavily exploited population of Atlantic cod (Gadus morhua). Controlling for the effects of density- and temperature-dependent growth, the change in mean length of 4-year-old cod between offspring and their parental cohorts was positively correlated with the estimated selection differential experienced by the parental cohorts between this age and spawning. This result supports the hypothesis that there have been genetic changes in growth in this population in response to size-selective fishing. Such changes may account for the continued small size-at-age in this population despite good conditions for growth and little fishing for over a decade. This study highlights the need for management regimes that take into account the evolutionary consequences of fishing.

Overfishing drives population decline, which in turn drives loss of genetic diversity. Many studies provide evidence of declines in genetic diversity; however, controversy exists within the literature, as some studies show evidence of no change in genetic diversity despite decades of overharvesting. The apparent discrepancy in the literature should therefore be examined to understand what biological and ecological processes are driving the differences in results. Here, we assess how different factors contribute to fisheries-induced susceptibility to declines in genetic diversity by first focusing on the different roles of genetic markers. Second, we assess how habitat type and conditions contribute to loss of genetic diversity. Third, we assess how life history and physiology affects catchability and loss of genetic diversity. Finally, we discuss how coinciding abiotic and biotic factors influence the intensity of genetic loss. We find a multitude of these factors could be interacting to influence how results are perceived and how intense the loss of genetic diversity can be. Future studies should carefully consider the methodology of genetic analysis used, as well as considerations of life history and ecology of the target species.

Background/Aim: Circulating tumor cells (CTCs) have garnered attention as biomarkers for therapeutic response and prognosis in malignant neoplasms. Nonetheless, existing literature predominantly relies on surrogate markers of tumor cells or focuses on single-cell CTC, failing to adequately address the challenge of detecting cluster-forming CTCs, which bear considerable prognostic implications. This prospective study aims to validate the efficacy of a novel filtration membrane, namely Soft Micro Pore Filter (S-MPF®), for rare cell recovery in detecting CTCs through the analysis of clinical samples. Patients and Methods: Patients with confirmed lung cancer or highly suspected lung cancer based on specific criteria (solid tumor size >2.0 cm, serum carcinoembryonic level >7.5 ng/ml, maximum standard uptake value derived from fluorodeoxyglucose-position emission tomography >2.9) were included in the study. CTCs were extracted from preoperative peripheral arterial blood samples using S-MPF®, and the validity of the filtration system was positively verified. Results: Out of the 25 enrolled patients, 23 had lung cancer. CTC positivity was observed in 17 cases (73.9%), whereas cluster CTC positivity was observed in 16 cases (69.6%), with a median count of two clusters. Single CTC positivity was observed in 11 cases (52.1%), with a median count of one cell. Conclusion: The utilization of the newly developed S-MPF® filtration membrane exhibited a high rate of CTC identification, demonstrating its suitability for clinical applications.

Overharvesting is a serious threat to many fish populations. High mortality and directional selection on body size can cause evolutionary change in exploited populations via selection for a specific phenotype and a potential reduction in phenotypic diversity. Whether the loss of phenotypic diversity that accompanies directional selection impairs response to environmental stress is not known. To address this question, we exposed three zebrafish selection lines to thermal stress. Two lines had experienced directional selection for (1) large and (2) small body size, and one was (3) subject to random removal of individuals with respect to body size (i.e. line with no directional selection). Selection lines were exposed to three temperatures (elevated, 34°C; ambient, 28°C; low, 22°C) to determine the response to an environmental stressor (thermal stress). We assessed differences among selection lines in their life history (growth and reproduction), physiological traits (metabolic rate and critical thermal max) and behaviour (activity and feeding behaviour) when reared at different temperatures. Lines experiencing directional selection (i.e. size selected) showed reduced growth rate and a shift in average phenotype in response to lower or elevated thermal stress compared with fish from the random‐selected line. Our data indicate that populations exposed to directional selection can have a more limited capacity to respond to thermal stress compared with fish that experience a comparable reduction in population size (but without directional selection). Future studies should aim to understand the impacts of environmental stressors on natural fish stocks. Size selection can act in tandem with diversity loss to reduce adaptive potential. Here, we show directional selection magnifies the effect of diversity loss alone to increase a population's susceptibility to thermal stress.

In autonomous manufacturing systems, the performance of time-series-based anomaly detection and fault diagnosis is highly sensitive to window size selection. Conventional approaches rely on empirical rules or fixed window settings, which often fail to capture the diverse temporal characteristics of anomalies and lead to performance degradation. This study systematically addresses the window size selection problem by categorizing anomaly patterns into three representative types: variability, cycle, and local spike. Each pattern is associated with a distinct temporal scale and underlying physical mechanism. Based on this insight, an Anomaly Deviation-Based Window Size Selection (ADW) method is proposed, which quantitatively evaluates anomaly deviation as a function of window size. Unlike traditional preprocessing-oriented approaches, the proposed method redefines window size as a core design variable that directly governs anomaly representation and diagnostic sensitivity. The effectiveness of the ADW method is validated using tension data from a roll-to-roll continuous manufacturing process and vibration data from a rotating bearing fault dataset. Experimental results demonstrate that the proposed approach consistently identifies optimized window sizes tailored to different anomaly types, leading to improved fault classification accuracy and diagnostic robustness. The proposed framework provides a physically interpretable and data-driven guideline for adaptive window size selection in long-term autonomous manufacturing systems.