Abstract Perovskite oxide junctions of p-type colossal magneto-resistance material La 0.67 Sr 0.33 MnO 3 (LSMO), strontium titanate insulator SrTiO 3 (STO) and n-type high- T c superconductor La 1.89 Ce 0.11 CuO 4 (LCCO) were deposited on STO (001) substrates by the pulsed laser deposition method. The current–voltage ( I – V ) characteristics were measured at room temperature and pronounced rectifying characteristics were observed. The trilayer junctions with different thicknesses of the middle STO insulator were investigated and the measurement exhibits a remarkable insulator thickness dependence in their I – V characteristics. We attribute the rectification of the trilayer junctions to the interfaces between different materials by energy band analysis.
As a leading mode of sea surface temperature (SST) variability over the North Atlantic in both observations and model simulations, the Atlantic Multidecadal Oscillation (AMO) can have a substantial influence on regional and global climate. By using Low-Frequency Component Analysis, we explore the uncertainties of the resulting AMO indices and the corresponding spatial patterns derived from three observational SST datasets. We found that the known coherent spatial pattern of the AMO at the basin scale over the North Atlantic appears in two out of the three datasets. Further analysis indicates that both the warming trend and the different techniques used to construct these observed gridded SSTs contribute to the AMO’s spatial coherence over the North Atlantic, especially during periods of sparse data sampling. The SST in the Extended Reconstructed SST dataset version 5 (ERSSTv5), changes from being systematically below the other datasets during the dense sampling periods on either side of the Second World War (WWII), to systematically above the other datasets during WWII, thereby introducing an artificial 10–20-year variability that affects the AMO’s spatial coherence. This coherence in the AMO’s spatial pattern is also affected by bias adjustment in ERSSTv5 at relative cool (i.e., non-summer) seasons, and by the heterogeneous North Atlantic warming pattern. The different AMO patterns can induce the different effects of wind, surface heat fluxes, and then drive ocean circulation and its heat transport convergence, especially for some seasons. For AMO indices, both the different detrending methods and different observational data result in uncertainty for the period 1935–1950. Such SST uncertainty is important to detect the relative role of the atmosphere and ocean in shaping the AMO.
We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at 3.67±0.05±0.15 PeV. Below the knee, the spectral index is found to be -2.7413±0.0004±0.0050, while above the knee, it is -3.128±0.005±0.027, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -0.1200±0.0003±0.0341. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components.
Abstract The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) is an endorsed Model Intercomparison Project in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The goal of FAFMIP is to investigate the spread in the atmosphere-ocean general circulation model projections of ocean climate change forced by increased CO 2 , including the uncertainties in the simulations of ocean heat uptake, global mean sea level rise due to ocean thermal expansion and dynamic sea level change due to ocean circulation and density changes. The FAFMIP experiments have already been conducted with the Flexible Global Ocean-Atmosphere-Land System Model, gridpoint version 3.0 (FGOALS-g3). The model datasets have been submitted to the Earth System Grid Federation (ESGF) node. Here, the details of the experiments, the output variables and some baseline results are presented. Compared with the preliminary results of other models, the evolutions of global mean variables can be reproduced well by FGOALS-g3. The simulations of spatial patterns are also consistent with those of other models in most regions except the North Atlantic and the Southern Ocean, indicating large uncertainties in the regional sea level projections of these two regions.
Abstract Due to the rapid advancement of modern transportation, tunnels have emerged as an important component of transportation infrastructure. A large number of pipelines and tunnels makes the urban underground environment extremely complex. Detecting underground tunnels and pipelines can provide guidance for urban construction. Ground penetrating radar (GPR) possesses attributes such as swift detection speed, no loss, convenient and flexible operation, thereby playing a crucial role in numerous domains. The aim of this research is to verify the feasibility of detecting tunnels with depths on the order of 10 meters, by evaluating tunnel dimensions and depth parameters through a combined approach of simulation and experimental measurements. In this investigation, gprMax was utilized to model and simulate the underground tunnel to establish the correlation between echo data and target position. Additionally, this research employed an 80MHz GPR system to detecting a undergound tunnel and acquiring data which facilitated successful determination of the depth of the underground tunnel based on empirical evidence
Objectives: Out-of-hour admission (on weekends, holidays, and weekday nights) has been associated with higher mortality in patients with acute myocardial infarction (AMI). We conducted a meta-analysis to verify the association between out-of-hour admission and mortality (both short- and long-term) in AMI patients. Design: This Systematic review and meta-analysis of cohort studies. Data Sources: PubMed and EMBASE were searched from inception to 27 May 2021. Eligibility Criteria for Selected Studies: Studies of any design examined the potential association between out-of-hour admission and mortality in AMI. Data Extraction and Synthesis: In total, 2 investigators extracted the data and evaluated the risk of bias. Analysis was conducted using a random-effects model. The results are shown as odds ratios [ORs] with 95% confidence intervals (CIs). I 2 value was used to estimate heterogeneity. Grading of Recommendations Assessment, Development, and Evaluation was used to assess the certainty of the evidence. Results: The final analysis included 45 articles and 15,346,544 patients. Short-term mortality (defined as either in-hospital or 30-day mortality) was reported in 42 articles (15,340,220 patients). Out-of-hour admission was associated with higher short-term mortality (OR 1.04; 95%CI 1.02–1.05; I 2 = 69.2%) but there was a significant statistical indication for publication bias (modified Macaskill's test P < 0.001). One-year mortality was reported in 10 articles (1,386,837 patients). Out-of-hour admission was also associated with significantly increased long-term mortality (OR 1.03; 95%CI 1.01–1.04; I 2 = 66.6%), with no statistical indication of publication bias ( p = 0.207). In the exploratory subgroup analysis, the intervention effect for short-term mortality was pronounced among patients in different regions ( p = 0.04 for interaction) and socio-economic levels ( p = 0.007 for interaction) and long-term mortality was pronounced among patients with different type of AMI ( p = 0.0008 for interaction) or on different types of out-to-hour admission ( p = 0.006 for interaction). Conclusion: Out-of-hour admission may be associated with an increased risk of both short- and long-term mortality in AMI patients. Trial Registration: PROSPERO (CRD42020182364).
Abstract The datasets of two Ocean Model Intercomparison Project (OMIP) simulation experiments from the LASG/IAP Climate Ocean Model, version 3 (LICOM3), forced by two different sets of atmospheric surface data, are described in this paper. The experiment forced by CORE-II (Co-ordinated Ocean–Ice Reference Experiments, Phase II) data (1948–2009) is called OMIP1, and that forced by JRA55-do (surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis) data (1958–2018) is called OMIP2. First, the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described. Second, the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation. We find that the mean states, interannual variabilities, and long-term linear trends can be reproduced well by the two experiments. The differences between the two datasets are also discussed. Finally, the usage of these data is described. These datasets are helpful toward understanding the origin system bias of the fully coupled model.
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