Chemically mediated behavior of recruiting corals and fishes: A tipping point that may limit reef recovery

Coral reefs are in global decline, converting from dominance by coral to dominance by seaweed. Once seaweeds become abundant, coral recovery is suppressed unless herbivores return to remove seaweeds, and corals then recruit. Variance in the recovery of fishes and corals is not well understood.We show that juveniles of both corals and fishes are repelled by chemical cues from fished, seaweed-dominated reefs but attracted to cues from coral-dominated areas where fishing is prohibited. Chemical cues of specific seaweeds from degraded reefs repulsed recruits, and cues from specific corals that are typical of healthy reefs attracted recruits. Juveniles were present at but behaviorally avoided recruiting to degraded reefs dominated by seaweeds. For recovery, degraded reefs may need to be managed to produce cues that attract, rather than repel, recruiting corals and fishes

Blade Displacement Measurements of the Full-Scale UH-60A Airloads Rotor

Blade displacement measurements were acquired during a wind tunnel test of the full-scale UH-60A Airloads rotor. The test was conducted in the 40- by 80-Foot Wind Tunnel of the National Full-Scale Aerodynamics Complex at NASA Ames Research Center. Multi-camera photogrammetry was used to measure the blade displacements of the four-bladed rotor. These measurements encompass a range of test conditions that include advance ratios from 0.15 to unique slowed-rotor simulations as high as 1.0, thrust coefficient to rotor solidity ratios from 0.01 to 0.13, and rotor shaft angles from -10.0 to 8.0 degrees. The objective of these measurements is to provide a benchmark blade displacement database to be utilized in the development and validation of rotorcraft computational tools. The methodology, system development, measurement techniques, and preliminary sample blade displacement measurements are presented

Tail autotomy effects on the escape behavior of the lizard Gonatodes albogularis (Squamata: Sphaerodactylidae), from Córdoba, Colombia

Background: Caudal autotomy appears to be an adaptation strategy to reduce the risk of being preyed upon. In an encounter with a predator, the prey must reduce the risk of being preyed upon, and one of the strategies that has exerted a strong pressure on selection has been tail loss. In lizards, it has been demonstrated that tail loss reduces the probability of survival in the event of a second attack; therefore, they must resort to new escape strategies to reduce the risk of falling prey. In order to evaluate the effect of tail loss on the escape behavior of Gonatodes albogularis in natural conditions, we took samples from a forest interior population. We expected that individuals that had not lost their tails would allow the predator to get closer than those that had lost it. For each sample, we recorded the following: (1) escape behavior, measured through three distances (e.g., approach distance, escape distance, and final distance); (2) distance to shelter; and (3) length of tail. We included only males in the study since we did not record any females without a tail and far fewer with a regenerated tail. Results: We found that tail loss does have an effect on the escape behavior of G. albogularis. Males that have their tails intact allow the predator to come closer, and we found a negative correlation between the approach distance and the length of the tail. Conclusion: Our results support the escape behavior theory, in which G. albogularis males drop their tails when the risk of predation is much higher than the cost of fleeing.Facultad de Ciencias Naturales y Muse

Blade Displacement Measurement Technique Applied to a Full-Scale Rotor Test

Blade displacement measurements using multi-camera photogrammetry were acquired during the full-scale wind tunnel test of the UH-60A Airloads rotor, conducted in the National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel. The objectives were to measure the blade displacement and deformation of the four rotor blades as they rotated through the entire rotor azimuth. These measurements are expected to provide a unique dataset to aid in the development and validation of rotorcraft prediction techniques. They are used to resolve the blade shape and position, including pitch, flap, lag and elastic deformation. Photogrammetric data encompass advance ratios from 0.15 to slowed rotor simulations of 1.0, thrust coefficient to rotor solidity ratios from 0.01 to 0.13, and rotor shaft angles from -10.0 to 8.0 degrees. An overview of the blade displacement measurement methodology and system development, descriptions of image processing, uncertainty considerations, preliminary results covering static and moderate advance ratio test conditions and future considerations are presented. Comparisons of experimental and computational results for a moderate advance ratio forward flight condition show good trend agreements, but also indicate significant mean discrepancies in lag and elastic twist. Blade displacement pitch measurements agree well with both the wind tunnel commanded and measured values

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance

Abstract: Serial MRI is an essential assessment tool in prostate cancer (PCa) patients enrolled on active surveillance (AS). However, it has only moderate sensitivity for predicting histopathological tumour progression at follow-up, which is in part due to the subjective nature of its clinical reporting and variation among centres and readers. In this study, we used a long short-term memory (LSTM) recurrent neural network (RNN) to develop a time series radiomics (TSR) predictive model that analysed longitudinal changes in tumour-derived radiomic features across 297 scans from 76 AS patients, 28 with histopathological PCa progression and 48 with stable disease. Using leave-one-out cross-validation (LOOCV), we found that an LSTM-based model combining TSR and serial PSA density (AUC 0.86 [95% CI: 0.78–0.94]) significantly outperformed a model combining conventional delta-radiomics and delta-PSA density (0.75 [0.64–0.87]; p = 0.048) and achieved comparable performance to expert-performed serial MRI analysis using the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) scoring system (0.84 [0.76–0.93]; p = 0.710). The proposed TSR framework, therefore, offers a feasible quantitative tool for standardising serial MRI assessment in PCa AS. It also presents a novel methodological approach to serial image analysis that can be used to support clinical decision-making in multiple scenarios, from continuous disease monitoring to treatment response evaluation. Key Points: •LSTM RNN can be used to predict the outcome of PCa AS using time series changes in tumour-derived radiomic features and PSA density. •Using all available TSR features and serial PSA density yields a significantly better predictive performance compared to using just two time points within the delta-radiomics framework. •The concept of TSR can be applied to other clinical scenarios involving serial imaging, setting out a new field in AI-driven radiology research

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance

Serial MRI is an essential assessment tool in prostate cancer (PCa) patients enrolled on active surveillance (AS). However, it has only moderate sensitivity for predicting histopathological tumour progression at follow-up, which is in part due to the subjective nature of its clinical reporting and variation among centres and readers. In this study, we used a long short-term memory (LSTM) recurrent neural network (RNN) to develop a time series radiomics (TSR) predictive model that analysed longitudinal changes in tumour-derived radiomic features across 297 scans from 76 AS patients, 28 with histopathological PCa progression and 48 with stable disease. Using leave-one-out cross-validation (LOOCV), we found that an LSTM-based model combining TSR and serial PSA density (AUC 0.86 [95% CI: 0.78-0.94]) significantly outperformed a model combining conventional delta-radiomics and delta-PSA density (0.75 [0.64-0.87]; p = 0.048) and achieved comparable performance to expert-performed serial MRI analysis using the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) scoring system (0.84 [0.76-0.93]; p = 0.710). The proposed TSR framework, therefore, offers a feasible quantitative tool for standardising serial MRI assessment in PCa AS. It also presents a novel methodological approach to serial image analysis that can be used to support clinical decision-making in multiple scenarios, from continuous disease monitoring to treatment response evaluation