Cloud radiative kernels (CRK) built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere (TOA) fluxes, and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes, which determines the regional surface temperature change and variability. In this study, CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model (RRTM). Longwave cloud radiative effect (CRE) at the surface is primarily driven by cloud base properties, while TOA CRE is primarily decided by cloud top properties. For this reason, the standard version of surface CRK is a function of latitude, longitude, month, cloud optical thickness (τ) and cloud base pressure (CBP), and the TOA CRK is a function of latitude, longitude, month, τ and cloud top pressure (CTP). Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present, the surface CRKs on CBP-τ histograms were converted to CTP-τ fields using the statistical relationship between CTP, CBP and τ obtained from collocated CloudSat and MODIS observations. For both climate model outputs and satellites observations, the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes. The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth’s Radiant Energy System (CERES) surface irradiances products.
Characterizing electrical breakdown limits of materials is a crucial step in device development. However, methods for repeatable measurements are scarce in two-dimensional materials, where breakdown studies have been limited to destructive methods. This restricts our ability to fully account for variability in local electronic properties induced by surface contaminants and the fabrication process. To tackle this, we implement a two-step deep-learning model to predict the breakdown mechanism and breakdown voltage of monolayer MoS2 devices with varying channel lengths and resistances using current measured in the low-voltage regime as inputs. A deep neural network (DNN) first classifies between Joule and avalanche breakdown mechanisms using partial current traces from 0 to 20 V. Following this, a convolutional long short-term memory network (CLSTM) predicts breakdown voltages of these classified devices based on partial current traces. We test our model with electrical measurements collected using feedback-control of the applied voltage to prevent device destruction, and show that the DNN classifier achieves an accuracy of 79% while the CLSTM model has a 12% error when requiring only 80% of the current trace as inputs. Our results indicate that information encoded in the current behavior far from the breakdown point can be used for breakdown predictions, which will enable non-destructive and rapid material characterization for 2D material device development.
Recent interest in developing fast spintronic devices and laser-controllable magnetic solids has sparked tremendous experimental and theoretical efforts to understand and manipulate ultrafast dynamics in materials. Studies of spin dynamics in the terahertz (THz) frequency range are particularly important for elucidating microscopic pathways toward novel device functionalities. Here, we review THz phenomena related to spin dynamics in rare-earth orthoferrites, a class of materials promising for antiferromagnetic spintronics. We expand this topic into a description of four key elements. (1) We start by describing THz spectroscopy of spin excitations for probing magnetic phase transitions in thermal equilibrium. While acoustic magnons are useful indicators of spin reorientation transitions, electromagnons that arise from dynamic magnetoelectric couplings serve as a signature of inversion-symmetry-breaking phases at low temperatures. (2) We then review the strong laser driving scenario, where the system is excited far from equilibrium and thereby subject to modifications to the free-energy landscape. Microscopic pathways for ultrafast laser manipulation of magnetic order are discussed. (3) Furthermore, we review a variety of protocols to manipulate coherent THz magnons in time and space, which are useful capabilities for antiferromagnetic spintronic applications. (4) Finally, new insights into the connection between dynamic magnetic coupling in condensed matter and the Dicke superradiant phase transition in quantum optics are provided. By presenting a review on an array of THz spin phenomena occurring in a single class of materials, we hope to trigger interdisciplinary efforts that actively seek connections between subfields of spintronics, which will facilitate the invention of new protocols of active spin control and quantum phase engineering.
Background:We performed this meta-analysis to provide a comprehensive evaluation of the role of MicroRNA-210 (miR-210) expression on the overall survival (OS) rate of cancers.Methods:We searched for relevant available literatures on miR-210 and cancer until November 1st, 2016 on the databases PubMed, EMBASE, Cochrane Library, and Science Direct database. We calculated the pooled hazard ratio (HR) with 95% confidence intervals (CIs) for OS, which compared the high and low expression levels of miR-210 in patients of the available studies. Subgroup analysis was performed to evaluate the specific role of miR-210 in ethnicity and the type of cancers. Publication bias was evaluated using Begg funnel plots and Egger regression test.Results:Overall, 19 studies were involved in this meta-analysis. The result indicated that upregulated miR-210 might be associated with poor OS outcome in various carcinomas, with the pooled HR of 1.80 (95% CI: 1.29–2.51). When stratified by disease, significant results were detected in breast cancer (HR = 2.67, 95% CI: 1.24–5.76) and glioma (HR = 2.42, 95% CI: 1.32–4.43). Besides, in the subgroup analysis by ethnicity, significant results were detected only in Asian populations (HR = 2.14, 95% CI: 1.37–3.34).Conclusion:The present meta-analysis suggests that high expressed miR-210 is significantly associated with OS in cancer patients, which has the potential to be a prognostic marker in cancers.
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