With the rapid development of electronic devices and wireless communication tools, it is urgent to design and fabricate low-cost, lightweight and effective electromagnetic absorption materials to solve interference of electromagnetic waves. https://www.selleckchem.com/products/ipa-3.html Herein, a new strategy toward porous carbon/graphite nanosheet/ferromagnetic nanoparticle (PC/GNS/Fe) composites was designed to investigate the influence of crystalline carbon on electromagnetic wave absorption. To begin with, graphite nanosheets (GNSs) were incorporated into the porous polyimide by in situ polymerization, and Fe were added as a magnetic particle source and an agent to regulate the pore size. A series of PC/GNS/Fe composite absorbents were obtained. The direct carbonization of porous polymer precursors was beneficial to the design of the pore structure of materials. A hierarchically porous structure derived from the phase separation process was well maintained in the polyimide pyrolysis process. The results demonstrated that the presence of crystalline carbon could influence the reflection loss value and the frequency range. Hence, the absorbing performance can be optimized by adjusting the pore structure and the content of crystalline carbon in materials, which is conducive to obtaining electromagnetic wave absorption materials with excellent comprehensive performance.Convolutional neural networks (CNNs) have recently emerged as a powerful approach for automatic segmentation of brain tumor subregions on 3D multi-parametric MRI scans. Learning rate is a crucial hyperparameter in the training of CNNs, impacting the performance of the learned model. Different learning rate policies trace unique trajectories in the optimization landscape that converge to local minima with varying generalization properties. In this work, we empirically evaluated nine learning rate policy-optimizer pairs with two state-of-the-art architectures, namely 2D slice-based U-Net and 3D DeepMedicRes, on an augmented brain tumor dataset of 534 subjects. Segmentation performance was quantified in terms of Dice similarity coefficient and Hausdorff distance metrics. The policies were ranked based on the final ranking score (FRS) employed by the BraTS challenge, with the statistical significance of the rankings evaluated by random permutation test. For 2D slice-based U-Net architecture, an overall ranking of learning rate policies showed that the polynomial decay policy with Adam optimizer significantly outperformed other policies for the task of individual and hierarchical segmentation of tumor subregions (p 0.3). These findings were also validated on the BraTS 2019 Validation dataset which comprised of an additional 125 subjects. Adaptation to the extra-uterine environment presents many challenges for infants born less than 28 weeks of gestation. Quantitative analysis of readily-available physiological signals at the cotside could provide valuable information during this critical time. We aim to assess the time-varying coupling between heart rate (HR) and perfusion index (PI) over the first 24 hours after birth and relate this coupling to gestational age, inotropic therapy, and short-term clinical outcome. We develop new nonstationary measures of coupling to summarise both frequency- and direction-dependent coupling. These measures employ a coherence measure capable of measuring time-varying Granger casuality using a short-time information partial directed coherence function. Measures are correlated with gestational age, inotropic therapy (yes/no), and outcome (adverse/normal). In a cohort of 99 extremely preterm infants (<28 weeks of gestation), we find weak but significant coupling in both the HR-to-PI and PI-to-HR directions (P<0.05). HR-to-PI coupling increases with maturation (correlation r=0.26; P=0.011); PI-to-HR coupling increases with inotrope administration (r=0.27; P=0.007). And nonstationary features of PI-to-HR coupling are associated with (r=0.27; P=0.009). Nonstationary features are necessary to distinguish different coupling types for complex biomedical systems. Time-varying directional coupling between PI and HR provides objective and independent biomarkers of adverse outcome in extremely preterm infants. Nonstationary features are necessary to distinguish different coupling types for complex biomedical systems. Time-varying directional coupling between PI and HR provides objective and independent biomarkers of adverse outcome in extremely preterm infants.Particle therapy treatment planning requires accurate volumetric maps of the relative stopping power, which can directly be acquired using proton computed tomography (pCT). With fluence-modulated pCT (FMpCT) imaging fluence is concentrated in a region-of-interest (ROI), which can be the vicinity of the treatment beam path, and imaging dose is reduced elsewhere. In this work we present a novel optimization algorithm for FMpCT which, for the first time, calculates modulated imaging fluences for joint imaging dose and image variance objectives. Thereby, image quality is maintained in the ROI to ensure accurate calculations of the treatment dose, and imaging dose is minimized outside the ROI with stronger minimization penalties given to imaging organs-at-risk. The optimization requires an initial scan at uniform fluence or a previous x-ray CT scan. We simulated and optimized FMpCT images for three pediatric patients with tumors in the head region. We verified that the target image variance inside the ROI was achi avoiding excess dose from imaging.The antitumor efficacy of various paclitaxel (PTX) and docetaxel (DTX) formulations in clinical applications is seriously affected by drug resistance. Cabazitaxel, a second-generation taxane, exhibits greater anticancer activity than paclitaxel and docetaxel and has low affinity for the P-glycoprotein (P-gp) efflux pump because of its structure. Therefore, cabazitaxel has the potential to overcome taxane resistance. However, owing to the high systemic toxicity and hydrophobicity of cabazitaxel and the instability of its commercial preparation, Jevtana®, the clinical use of cabazitaxel is restricted to patients with metastatic castration-resistant prostate cancer (mCRPC) who show progression after docetaxel-based chemotherapy. Nanomedicine is expected to overcome the limitations associated with cabazitaxel application and surmount taxane resistance. This review outlines the drug delivery systems of cabazitaxel published in recent years, summarizes the challenges faced in the development of cabazitaxel nanoformulations, and proposes strategies to overcome these challenges.