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Underwater images, as a crucial medium for storing ocean information in underwater sensors, play a vital role in various underwater tasks. However, they are prone to distortion due to the imaging environment, which leads to a decline in visual quality, which is an urgent issue for various marine vision systems to address. Therefore, it is necessary to develop underwater image enhancement (UIE) and corresponding quality assessment methods. At present, most underwater image quality assessment (UIQA) methods primarily rely on extracting handcrafted features that characterize degradation attributes, which struggle to measure complex mixed distortions and often exhibit discrepancies with human visual perception in practical applications. Furthermore, current UIQA methods lack the consideration of the perception perspective of enhanced effects. To this end, this paper employs luminance and saliency priors as critical visual information for the first time to measure the enhancement effect of global and local quality achieved by the UIE algorithms, named JLSAU. The proposed JLSAU is built upon an overall pyramid-structured backbone, supplemented by the Luminance Feature Extraction Module (LFEM) and Saliency Weight Learning Module (SWLM), which aim at obtaining perception features with luminance and saliency priors at multiple scales. The supplement of luminance priors aims to perceive visually sensitive global distortion of luminance, including histogram statistical features and grayscale features with positional information. The supplement of saliency priors aims to perceive visual information that reflects local quality variation both in spatial and channel domains. Finally, to effectively model the relationship among different levels of visual information contained in the multi-scale features, the Attention Feature Fusion Module (AFFM) is proposed. Experimental results on the public UIQE and UWIQA datasets demonstrate that the proposed JLSAU outperforms existing state-of-the-art UIQA methods. [ABSTRACT FROM AUTHOR]

From birth to adulthood, the mammalian heart grows primarily through increasing cardiomyocyte (CM) size, which is known as maturational hypertrophic growth. The Hippo-YAP signaling pathway is well known for regulating heart development and regeneration, but its roles in CM maturational hypertrophy have not been clearly addressed. Vestigial-like 4 (VGLL4) is a crucial component of the Hippo-YAP pathway, and it functions as a suppressor of YAP/TAZ, the terminal transcriptional effectors of this signaling pathway. To develop an in vitro model for studying CM maturational hypertrophy, we compared the biological effects of T3 (triiodothyronine), Dex (dexamethasone), and T3/Dex in cultured neonatal rat ventricular myocytes (NRVMs). The T3/Dex combination treatment stimulated greater maturational hypertrophy than either the T3 or Dex single treatment. Using T3/Dex treatment of NRVMs as an in vitro model, we found that activation of VGLL4 suppressed CM maturational hypertrophy. In the postnatal heart, activation of VGLL4 suppressed heart growth, impaired heart function, and decreased CM size. On the molecular level, activation of VGLL4 inhibited the PI3K-AKT pathway, and disrupting VGLL4 and TEAD interaction abolished this inhibition. In conclusion, our data suggest that VGLL4 suppresses CM maturational hypertrophy by inhibiting the YAP/TAZ-TEAD complex and its downstream activation of the PI3K-AKT pathway. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study based on multiphase-seepage and wellbore multiphase-flow theories. It establishes a model for calculating the rate of gas intrusion that considers various factors, including formation pore permeability, bottomhole pressure difference, rheology of the drilling fluid, and surface tension. Experiments were conducted to investigate the mechanism of gas intrusion under shut-in conditions, and the experimental results were employed to validate the reliability of the proposed method for calculating the gas intrusion rate. Furthermore, this research explores the transportation rates of single bubbles and bubble clusters in drilling fluid under shut-in conditions. Additionally, empirical expressions were derived for the drag coefficient for single bubbles and bubble clusters in the wellbore. These expressions can be used to calculate gas transportation rates for various equivalent radii of single bubbles and bubble clusters. The initial bubble size of intrusive gas, the transportation speed of intrusive gas in the wellbore, the rate of gas intrusion, and variations in the wellbore pressure after gas intrusion were analyzed. Additionally, a method was developed to calculate the rising velocity of bubble clusters in water based on experimental results. The study reveals that the average bubble size in the bubble cluster is significantly smaller than the size of single bubbles generated from the orifice. When the viscosity of the drilling fluid is low, the transportation velocity of the bubble cluster exhibits a positive correlation with the average bubble diameter. When the average bubble diameter exceeds 1 mm, the bubble velocity no longer varies with changes in the bubble-cluster diameter. The research results provide theoretical support for wellbore pressure prediction and pressure control under shutdown conditions. [ABSTRACT FROM AUTHOR]

FLake has been one of the most extensively used lake models in many studies for lake thermal structure simulations. However, due to the scarcity of lake temperature observations, its applicability and performance on lakes over the Tibetan Plateau are still poorly investigated, especially in small- to medium-sized lakes. In this study, based on water profile observations in Dagze Co, a medium-sized lake on the central Tibetan Plateau, the sensitivity of lake thermal features to three key parameters in FLake was investigated. The performance of FLake in reproducing the lake thermal features was evaluated and improved by optimizing these key parameters. The results showed that the FLake model with default parameter settings can generally reproduce the thermal features of Dagze Co, but there are still significant deviations compared to observation. The sensitive experiments demonstrated that the thermal structure of the lake obviously responds to the change in the water extinction coefficient (Kd), friction velocity (u*), and ice albedo ( α i c e ). Based on previous studies and sensitive experiments, the three key parameters were set to the optimized value, which substantially improved the performance of FLake. The values of bias and RMSE of simulated lake surface water temperature decreased from 3.08 °C and 3.62 °C to 2.0 °C and 2.48 °C after parameter optimization. The integration of a simple salinity scheme further improved the ability of FLake to reproduce the observed thermal features of Dagze Co. These results will improve our understanding of thermal processes in lakes on the Tibetan Plateau, as well as the applicability of lake models. [ABSTRACT FROM AUTHOR]

Active suspension control and direct yaw-moment control (DYC) are widely used in the vehicle control field. To solve the coupling between those two controllers, a coordinated control of active suspension and DYC is proposed to further improve the vehicle roll and yaw stability. To enhance the adaptive ability of the active suspension, a proportional integral control optimized by the genetic fuzzy algorithm is introduced. DYC is proposed based on the sliding mode control. To restrain the chattering, the parameters of the sliding mode control is optimized by a genetic algorithm. Finally, a coordinated controller is presented based on the adaptive distribution of the anti-roll torque in the front and rear suspension. The simulation results show that the proposed active suspension and DYC can greatly improve the roll and yaw stability, respectively. The expected vehicle status can be well tracked. In addition, the coordinated control is compared by simply using two independent controllers under a different tire–road friction coefficient and different steering maneuver. The results show that the coordinated control has an even better performance under each working condition. [ABSTRACT FROM AUTHOR]

The distribution of load has high uncertainty, which is the main cause of a rack structure's instabilities. The objective of this study was to identify the most unfavorable and favorable load distributions on steel storage racks with and without bracings under seismic loading through a stochastic optimization—a genetic algorithm (GA). This paper begins with optimizing the most unfavorable and favorable load distributions on the steel storage racks with and without bracings using GA. Based on the optimization results, the failure position and seismic performance influencing factors, such as the load distributions on the racks and at hazardous positions, are then identified. In addition, it is demonstrated that the maximum stress ratio of the uprights under the most unfavorable load distribution is higher than that under the full-load normal design, and it is not the case that the higher the center of gravity the more dangerous the steel storage rack is, demonstrating that the load distribution pattern has a significant impact on the structural safety of steel storage racks. The statistics of the distributions of the load generated during the optimization of the GA and the contours of the probability distributions of the load are generated. Combining the probability distribution contours and the GA's optimization findings, the "convex" distribution hazard model and the "concave" distribution safety model for a steel storage rack with bracings are identified. In addition, the features of the distribution hazard model and the load distribution safety model are also identified for steel storage racks without bracings. [ABSTRACT FROM AUTHOR]

Congenital heart disease is one of the leading causes of pediatric morbidity and mortality, thus highlighting the importance of deciphering the molecular mechanisms that control heart development. As the terminal transcriptional effectors of the Hippo–YAP pathway, YAP and TEAD1 form a transcriptional complex that regulates the target gene expression and depletes either of these two genes in cardiomyocytes, thus resulting in cardiac hypoplasia. Vestigial-like 4 (VGLL4) is a transcriptional co-factor that interacts with TEAD and suppresses the YAP/TEAD complex by competing against YAP for TEAD binding. To understand the VGLL4 function in the heart, we generated two VGLL4 loss-of-function mouse lines: a germline Vgll4 depletion allele and a cardiomyocyte-specific Vgll4 depletion allele. The whole-body deletion of Vgll4 caused defective embryo development and perinatal lethality. The analysis of the embryos at day 16.5 revealed that Vgll4 knockout embryos had reduced body size, malformed tricuspid valves, and normal myocardium. Few whole-body Vgll4 knockout pups could survive up to 10 days, and none of them showed body weight gain. In contrast to the whole-body Vgll4 knockout mutants, cardiomyocyte-specific Vgll4 knockout mice had no noticeable heart growth defects and had normal heart function. In summary, our data suggest that VGLL4 is required for embryo development but dispensable for myocardial growth. [ABSTRACT FROM AUTHOR]

Toll-like receptors (TLRs) are a family of pattern recognition receptors (PRRs) that modulate innate immune responses and play essential roles in the pathogenesis of heart diseases. Although important, the molecular mechanisms controlling cardiac TLR genes expression have not been clearly addressed. This study examined the expression pattern of Tlr1, Tlr2, Tlr3, Tlr4, Tlr5, Tlr6, Tlr7, Tlr8, and Tlr9 in normal and disease-stressed mouse hearts. Our results demonstrated that the expression levels of cardiac Tlr3, Tlr7, Tlr8, and Tlr9 increased with age between neonatal and adult developmental stages, whereas the expression of Tlr5 decreased with age. Furthermore, pathological stress increased the expression levels of Tlr2, Tlr4, Tlr5, Tlr7, Tlr8, and Tlr9. Hippo-YAP signaling is essential for heart development and homeostasis maintenance, and YAP/TEAD1 complex is the terminal effector of this pathway. Here we found that TEAD1 directly bound genomic regions adjacent to Tlr1, Tlr2, Tlr3, Tlr4, Tlr5, Tlr6, Tlr7, and Tlr9. In vitro, luciferase reporter data suggest that YAP/TEAD1 repression of Tlr4 depends on a conserved TEAD1 binding motif near Tlr4 transcription start site. In vivo, cardiomyocyte-specific YAP depletion increased the expression of most examined TLR genes, activated the synthesis of pro-inflammatory cytokines, and predisposed the heart to lipopolysaccharide stress. In conclusion, our data indicate that the expression of cardiac TLR genes is associated with age and activated by pathological stress and suggest that YAP/TEAD1 complex is a default repressor of cardiac TLR genes. [ABSTRACT FROM AUTHOR]

Functional brain network (FBN) is an intuitive expression of the dynamic neural activity interaction between different neurons, neuron clusters, or cerebral cortex regions. It can characterize the brain network topology and dynamic properties. The method of building an FBN to characterize the features of the brain network accurately and effectively is a challenging subject. Entropy can effectively describe the complexity, non-linearity, and uncertainty of electroencephalogram (EEG) signals. As a relatively new research direction, the research of the FBN construction method based on EEG data of fatigue driving has broad prospects. Therefore, it is of great significance to study the entropy-based FBN construction. We focus on selecting appropriate entropy features to characterize EEG signals and construct an FBN. On the real data set of fatigue driving, FBN models based on different entropies are constructed to identify the state of fatigue driving. Through analyzing network measurement indicators, the experiment shows that the FBN model based on fuzzy entropy can achieve excellent classification recognition rate and good classification stability. In addition, when compared with the other model based on the same data set, our model could obtain a higher accuracy and more stable classification results even if the length of the intercepted EEG signal is different. [ABSTRACT FROM AUTHOR]