The enhanced electrochemical properties could be attributed to their favorable three-dimensional graphene aerogel network, which accounts for the improved structural stability and electronic conductivity of γ-Fe2O3 during the lithiation/delithiation process. © 2020 IOP Publishing Ltd.Motivated by practical implementation of transition-metal oxide-graphene heterostructures, we use all atom molecular dynamics simulations to study dynamics of water in a nano slit bounded by a transition metal oxide surface, namely, TiO$_2$ termination of SrTiO$_3$, and graphene. The resultant asymmetric, strong confinement produces square ice-like crystallites of water pinned at TiO$_2$ surface and drives enhanced hydrophobicity of graphene via the proximity effect to the hydrophilic TiO$_2$ surface. This importantly brings in dynamic heterogeneity, both in translational and rotational degrees of freedom, due to coupling between the slow relaxing, strongly adsorbed water layer at the hydrophilic oxide surface, and faster relaxation of subsequent water layers. The heterogeneity is signalled in ruggedness of the effective free energy landscapes. We discuss possible implications of our findings in drug delivery. © 2020 IOP Publishing Ltd.Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these lesions are variable, the initial investigations are usually similar. Patients who are suspected to have a brain tumor will be assessed with computed tomography (CT) and magnetic resonance imaging (MRI). The imaging findings are used by neurosurgeons to determine the feasibility of surgical resection and plan such an undertaking. Imaging studies are also an indispensable tool in tracking tumor progression or its response to treatment. As these imaging studies are non-invasive, relatively cheap and accessible to patients, there have been many efforts over the past two decades to increase the amount of clinically-relevant information that can be extracted from brain imaging. https://www.selleckchem.com/products/cx-4945-silmitasertib.html Most recently, artificial intelligence (AI) techniques have been employed to segment and characterize brain tumors, as well as to detect progression or treatment-response. However, the clinical utility of such endeavours remains limited due to challenges in data collection and annotation, model training, and the reliability of AI-generated information. We provide a review of recent advances in addressing the above challenges. First, to overcome the challenge of data paucity, different image imputation and synthesis techniques along with annotation collection efforts are summarized. Next, various training strategies are presented to meet multiple desiderata, such as model performance, generalization ability, data privacy protection, and learning with sparse annotations. Finally, standardized performance evaluation and model interpretability methods have been reviewed. We believe that these technical approaches will facilitate the development of a fully-functional AI tool in the clinical care of patients with gliomas. © 2020 IOP Publishing Ltd.Considering a quantum network, here we propose two kinds of circular charge currents. These are referred as net current in the full system and the current confined within a particular segment of the network. The network is composed of two rings, where one of the rings is subjected to a magnetic flux. Depending on the connectivity among the rings a new kind of states, insensitive to the magnetic flux, is generated along with the current carrying states. Because of this, a pronounced oscillation in net current with filling factor appears which suggests a possible switching action. Appearance of these vanishing current carrying states gradually decreases with increasing the degree of connectivity between the rings. As long as the rings are coupled by using more than a single bond, a circular current of other kind appears in the flux free ring which induces a strong magnetic field. The strength of this induced magnetic field can be regulated selectively by tuning the magnetic flux in the other ring. This phenomenon can be utilized for spin switching and other spintronic applications. Finally, we examine the role of non-uniform disorder on these currents, and find several atypical signatures. Our study can be generalized to any higher loop system for investigating magneto-transport properties. © 2020 IOP Publishing Ltd.The WO3 as an important semiconductor has attracted widespread attention for supercapacitors. However, the applications of WO3 are limited by the poor performance of capacitance and conductivity. In this paper, a novel method is presented for preparing a WO3/reduced graphene oxide (RGO) composite, based on the poly(ionic liquid) (PIL) as linker. The PIL makes the tight contact of WO3 and graphene for well utilizing the excellent electrical conductivity of graphene. The results of the morphology for the as prepared WO3/PIL/RGO composite indicates that the WO3 nanoparticles distribute uniformly on the surface of RGO. In addition, the WO3/PIL/RGO electrode displays much higher specific capacitance of 316 F•g-1 at 1 A•g-1 than that of the pure WO3 electrode. Furthermore, the WO3/PIL/RGO as a promising electrode material, also has good rate and long cycling performance for supercapacitors. © 2020 IOP Publishing Ltd.Positron emission tomography and prompt gamma detection are promising proton therapy monitoring modalities. Fast calculation of the expected distributions is desirable for comparison to measurements and to develop/train algorithms for automatic treatment error detection. A filtering formalism was used for positron-emitter predictions and adapted to allow for its use for the beamline of any proton therapy centre. A novel approach based on a filtering formalism was developed for the prediction of energy-resolved prompt-gamma distributions for arbitrary tissues. The method estimates prompt-gamma yields and their energy spectra in the entire treatment field. Both approaches were implemented in a research version of the RayStation treatment planning system. The method was validated against positron emission tomography monitoring data and Monte Carlo simulations for four patients treated with scanned proton beams. Longitudinal shifts between profiles from analytical and Monte Carlo calculations were within -1.7 and 0.