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The fine nanopillars on the natural cicada wing, which exhibits outstanding superhydrophobicity and anti-reflectivity, are carefully observed and analyzed. Here, a promising strategy by combining anodic aluminum oxide template and hot embossing is proposed for rapidly and efficiently mimicking the orderly and densely arranged nanopillars on the cicada wing surface to polypropylene (PP) surfaces. By adjusting the compression pressure, the nanostructures on the PP replica surface gradually evolve from nanoprotrusion-like features to nanopillar-like features so that a gradient wetting behavior from hydrophilicity to hydrophobicity and further to superhydrophobicity appears on the PP replica surfaces. Specifically, the biomimetic PP replica surface exhibits a contact angle of 159 ± 3° and a rolling angle of 8 ± 3° at a compression pressure of 15 MPa. Moreover, the biomimetic PP replica surface can stabilize its superhydrophobic state under a 1.96 kPa external pressure during the dynamic droplet impact. Besides robust dynamic superhydrophobicity, the biomimetic PP replica surface also demonstrated excellent anti-reflectivity because of the gradually changed effective refractive index. Therefore, the biomimetic PP replica inherits both the superhydrophobicity and anti-reflectivity of the natural cicada wing, which makes the products can effectively reduce the external damage when applied to agricultural films, dustproof films, and packaging materials.The structural design of three-dimensional (3D) flexible wearable sensors using conductive polymer composites is a hot spot in current research. In this paper, honeycomb-shaped flexible resistive pressure sensors with three different support structures were manufactured by using thermoplastic polyurethane and graphene nanoplatelets composites based on fused deposition 3D printing technology. Based on the various 3D conductive network of the sensors, the flexible sensor exhibit excellent piezoresistive performance, such as adjustable gauge factor (GF) (13.70-54.58), exceptional durability and stability. A combination of representative volume element and finite element simulations was used to simulate the stress distribution of sensors with different structures to predict the structure's effect on the sensor GF. In addition, the sensor can be attached to human body to monitor the body's swallowing and walking behaviors. The sensor has prospective process applications for intelligent wearable devices.Deformable image registration (DIR) of 4D-CT is very important in many radiotherapeutic applications including tumor target definition, image fusion, dose accumulation and response evaluation. It is a challenging task to performing accurate and fast DIR of lung 4D-CT images due to its large and complicated deformations. In this study, we propose an unsupervised multi-scale DIR framework with attention-based network (MANet). Three cascaded models used for aligning CT images in different resolution levels were involved and trained by minimizing the loss functions, which were defined as the combination of dissimilarity between the fixed image and the deformed image and DVF regularization term. In addition, attention gates were incorporated into the three models to distinguish the moving structures from non-moving or minimal-moving structures during registration. The three models were trained sequentially and separately to minimize the loss function in each scale to initialize the MANet, and then trained jointly to minimize the total loss function which incorporated an additional dissimilarity between fixed image and deformed image. Besides, an adversarial network was integrated into MANet to enforce the DVF regularization by penalizing the unrealistic deformed images. The proposed MANet was evaluated on the public dir-lab dataset, and the target registration errors (TREs) of the model were compared with convention iterative optimization-based methods and three recently published deep learning-based methods. The initial results showed that the MANet with an average of TRE of 1.53 ± 1.02 mm outperformed other registration methods, and its execution time took about 1 s for DVF estimation with no requirement of manual-tuning for parameters, which demonstrating that our proposed method had the ability of performing superior registration for 4D-CT.The introduction of non-invasive imaging techniques such as MRI imaging for treatment planning and optical eye tracking for in-room eye localization would obviate the requirement of clips implantation for many patients undergoing ocular proton therapy. CB-839 This study specifically addresses the issue of torsional eye movement detection during patient positioning. Non-invasive detection of eye torsion is performed by measuring the iris pattern rotations using a beams eye view optical camera. When handling images of patients to be treated using proton therapy, a number of additional challenges are encountered, such as changing eye position, pupil dilatation and illumination. A method is proposed to address these extra challenges while also compensating for the effect of cornea distortion in eye torsion computation. The accuracy of the proposed algorithm was evaluated against corresponding measurement of eye torsion using the clips configuration measured on x-ray images. This study involves twenty patients who received ocular proton therapy at Paul Scherrer Institute and it is covered by ethical approval (EKNZ 2019-01987).This perspective aims to identify the relationships between the structural and dynamic properties of chromosomes and the fundamental properties of soft-matter systems. Chromatin is condensed into metaphase chromosomes during mitosis. The resulting structures are elongated cylinders having micrometer-scale dimensions. Our previous studies, using transmission electron microscopy, atomic force microscopy, and cryo-electron tomography, suggested that metaphase chromosomes have a multilayered structure, in which each individual layer has the width corresponding to a mononucleosome sheet. The self-assembly of multilayer chromatin plates from small chromatin fragments suggests that metaphase chromosomes are self-organized hydrogels (in which a single DNA molecule crosslinks the whole structure) with an internal liquid-crystal order produced by the stacking of chromatin layers along the chromosome axis. This organization of chromatin was unexpected, but the spontaneous assembly of large structures has been studied in different soft-matter systems and, according to these studies, the self-organization of chromosomes could be justified by the interplay between weak interactions of repetitive nucleosome building blocks and thermal fluctuations.
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