38% after 1600 cycles). The prepared ZIBs presented a high power density of 366.6 W kg-1at an energy density of 286 W h kg-1. These extraordinary results indicate the great application potential of AVO as a cathode material for AZIBs.Deep learning (DL) has become widely used for medical image segmentation in recent years. However, despite these advances, there are still problems for which DL-based segmentation fails. Recently, some DL approaches had a breakthrough by using anatomical information which is the crucial cue for manual segmentation. In this paper, we provide a review of anatomy-aided DL for medical image segmentation which covers systematically summarized anatomical information categories and corresponding representation methods. We address known and potentially solvable challenges in anatomy-aided DL and present a categorized methodology overview on using anatomical information with DL from over 70 papers. Finally, we discuss the strengths and limitations of the current anatomy-aided DL approaches and suggest potential future work.Spectral computed tomography has great potential for multi-energy imaging and anti-artifacts. The complete absorption-based energy resolving scheme of x-rays has been used for the integrity of detected information. However, this scheme is limited by the fact that the detector pixel thickness is high and fixed. Here, an energy resolving scheme is proposed using the crosstalk correction method for the incomplete absorption detection of x-rays. A fully connected neural network (FCNN)-based method was used to correct the difference caused by internal x-ray crosstalk of the edge-on detector. The energy and spatial features of the data which is collected in layers were combined to establish the mapping between the ideal data and the data with crosstalk at the pre-processing stage. Thereafter, to reconstruct the stable and highly accurate energy-resolving equations, the layers with low relative energy difference were selected and grouped together to reduce the accumulation difference. The experiment results demonstrate the feasibility of this energy resolving scheme. The differences caused by crosstalk can be suppressed through the proposed FCNN-based method. The resolving accuracy can be further improved by grouping more layers at forward positions in the pixel. Moreover, this improvement can be observed in the reconstructed images with reduced artifacts and improved quality.In this paper structure, magnetic and magneto-thermal properties magnetic entropy change (ΔSm) and refrigeration capacity (q) of Er1-xYx(Co0.84Fe0.16)2alloys (x= 0, 0.2, 0.4, 0.6, 0.8, 1) in magnetic fields up to 90 kOe in a temperature range of 5-360 K are investigated. An analysis of temperature dependences of magnetization (σ) and high-field susceptibility (χhf) showed that in these compounds, three different ferri- and a one ferromagnetic structures are consequently realized. Concentration dependences of magnetic moment at 5 K (μf.u.), Curie temperature (TC), residual magnetization (σr) and coercivity (Hc) have been shown to have an extreme at intermediate Y concentration. The character of temperature dependence of magnetic entropy change (ΔSm(T)) depends on the composition and originates from the type of magnetic structure of the compound and the mutual orientation of R- and 3d- element sublattices magnetization with respect to the resulting one. In compounds withx= 0.6 andx= 0.8 temperature regions with different signs of ΔSmare observed, reflecting the change of dominating R- or 3d- sublattice in the resulting magnetization.Electrical synaptic devices are the basic components for the hardware based neuromorphic computational systems, which are expected to break the bottleneck of current von Neumann architecture. So far, synaptic devices based on three-terminal transistors are considered to provide the most stable performances, which usually use gate pulses to modulate the channel conductance through a floating gate and/or charge trapping layer. Herein, we report a three-terminal synaptic device based on a two-dimensional molybdenum ditelluride (MoTe2)/hexagonal boron nitride (hBN) heterostructure. This structure enables stable and prominent conductance modulation of the MoTe2channel by the photo-doping method through electron migration between the MoTe2channel and ultraviolet (UV) light excited mid-gap defect states in hBN. Therefore, it is free of the floating gate and charge trapping layer to reduce the thickness and simplify the fabrication/design of the device.. Moreover, since UV illumination is indispensable for stable doping in MoTe2channel, the device can realize both short- (without UV illumination) and long- (with UV illumination) term plasticity. Meanwhile, the introduction of UV light allows additional tunability on the MoTe2channel conductance through incident UV wavelength and power intensity, which may be important to mimic advanced synaptic functions. In addition, the photo-doping method can bidirectionally dope MoTe2 channel, which not only leads to large high/low resistance ratio for potential multi-level storage, but also implement both potentiation (n-doping) and depression (p-doping) of synaptic weight.  https://www.selleckchem.com/products/ox04528.html  This work explores alternative three-terminal synaptic configuration without floating gate and charge trapping layer, which may inspire researches on novel electrical synapse mechanisms.Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s).