Electron energy-loss spectroscopy and ab initio electronic structure of the LaOFeP superconductor

The electronic band structures of the LaOFeP superconductor have been calculated theoretically by the first principles method and measured experimentally by electron energy loss spectroscopy. The calculations indicate that the Fe atom in LaOFeP crystal shows a weak magnetic moment and does not form a long-range magnetic ordering. Band structure, Fermi surfaces and fluorine-doping effects are also analyzed based on the data of the density functional theory. The fine structures of the EELS data have been carefully examined in both the low loss energy region and the core losses region (O K, Fe L2,3, and La M4,5). A slight bump edge at 44 eV shows notable orientation-dependence: it can be observed in the low loss EELS spectra with q parallel to c, but becomes almost invisible in the q vertical to c spectra. Annealing experiments indicate that low oxygen pressure favors the appearance of superconductivity in LaOFeP, this fact is also confirmed by the changes of Fe L2,3 and O K excitation edges in the experimental EELS data

Performance Analysis and Enhancement of Deep Convolutional Neural Network - Application to Gearbox Condition Monitoring

Convolutional neural network has been widely investigated for machinery condition monitoring, but its performance is highly affected by the learning of input signal representation and model structure. To address these issues, this paper presents a comprehensive deep convolutional neural network (DCNN) based condition monitoring framework to improve model performance. First, various signal representation techniques are investigated for better feature learning of the DCNN model by transforming the time series signal into different domains, such as the frequency domain, the time–frequency domain, and the reconstructed phase space. Next, the DCNN model is customized by taking into account the dimension of model, the depth of layers, and the convolutional kernel functions. The model parameters are then optimized by a mini-batch stochastic gradient descendent algorithm. Experimental studies on a gearbox test rig are utilized to evaluate the effectiveness of presented DCNN models, and the results show that the one-dimensional DCNN model with a frequency domain input outperforms the others in terms of fault classification accuracy and computational efficiency. Finally, the guidelines for choosing appropriate signal representation techniques and DCNN model structures are comprehensively discussed for machinery condition monitoring

Spatial and temporal heterogeneity of tropical cyclone precipitation over China from 1959 to 2018

Tropical cyclone precipitation (TCP) can cause serious floods and urban waterlogs as well as cause various secondary disasters, such as landslides and debris flows, which negatively affect human lives and the sustainable development of the economy. This study applied the prewhitening Mann-Kendall test, empirical orthogonal function, and continuous wavelet transform to investigate the long-term trend, spatiotemporal pattern, and periodicity of TCP at monthly, interannual, and interdecadal timescales over China. The recurrence risks of extreme TCP were analyzed using the return period estimation model. The results showed that 1) TCP displayed a significant increasing trend, especially in eastern China, inland areas, and Guangxi Province. The TCP periodicities were 2.5 and 4.9 years across all of China. However, TCP cycles had large discrepancies in the time and frequency domains in different subregions. 2) Monthly TCP demonstrated a decreasing trend in May and an increasing trend from June to October in all of China. The TCP in northeastern China and southern China tended to decrease in July and August, respectively. 3) TCP demonstrated a decreasing tendency from the 1960s–1980s followed by a rebounding trend in the 1990s–2010s. In addition, TCP showed a dipole mode in the 1970s and 2000s. 4) There was an increasing recurrence risk of extreme TCP in the Yangtze River Delta, Hainan Province, southeastern Guangxi Province, and southwestern Guangdong Province. It is therefore necessary to improve forecasting of extreme TCP events to improve risk management and prevention capacity of natural disasters, especially in regions with high population and economy exposure

Projection of future climate change in the Poyang Lake Basin of China under the global warming of 1.5–3°C

This study projected the future climate changes in the Poyang Lake Basin (PLB) of China under various global warming targets (1.5–3°C), based on the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) and 4 statistical downscaling methods, including Quantile Mapping (QM), Daily Translation (DT), Delta, and Local Intensity Scaling (LOCI). The RMSE, R$^{2}$ and KGE indicators were used to evaluate the competency of the aforementioned methods applied to daily precipitation (Pre), daily mean temperature (Tas), daily maximum temperature (Tasmax), and daily minimum temperature (Tasmin). The global warming of 1.5, 2 and 3°C will occur around 2040, from 2045 to 2080 and around 2075, respectively, for the emission scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. The results demonstrated that under the 1.5, 2 and 3°C global warming targets, the projected annual precipitation declined by 14.82, 11.92 and 8.91% relative to the reference period (1986–2005), respectively. The Tas increased significantly by 0.43, 0.94 and 1.92°C and the Tasmax increased by 0.58, 1.11 and 2.09°C. The Tasmin decreased by 0.29°C under the 1.5°C warming target, while it increased by 0.19 and 1.18°C under the 2 and 3°C warming targets. The spatial distributions of future annual precipitation in the PLB were relative consistent. However, the regional variability was significant, which the southern and eastern regions experienced more precipitation than the northern and western regions. The south-central part of the Ganjiang basin was the high-value area while the northeastern part was the low-value area. The Tas, Tasmax and Tasmin had a consistent spatial variation characteristic that the high latitude areas were warmer than the low latitude areas, and the western regions were warmer than the central and eastern regions while the northeastern regions were cooler than the remaining regions

How Well Does the ERA5 Reanalysis Capture the Extreme Climate Events Over China? Part II: Extreme Temperature

The fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts (ERA5) is the latest reanalysis product. However, the reliability of ERA5 to capture extreme temperatures is still unclear over China. Hence, based on conventional meteorological station data, a new criterion (DISO) was used to validate the ERA5 capturing extreme temperature indices derived from the Expert Team on Climate Change Detection and Indices (ETCCDI) across the six subregions of China on different timescales. The conclusions are as follows: the original daily temperatures (mean temperature, maximum temperature, and minimum temperature) can be well reproduced by ERA5 reanalysis over China. ERA5 tends to exhibit more misdetection for the duration of extreme temperature events than extreme temperature intensity and frequency. In addition, ERA5 performed best in the summer and worst in the winter, respectively. The trend of absolute indices (e.g., TXx and TNx), percentile-based indices (e.g., TX90p, TX10p, TN90p, and TN10p), and duration indices (e.g., WSDI, CSDI, and GSL) can be captured by ERA5, but ERA5 failed to capture the tendency of the diurnal temperature range (DTR) over China. Spatially, ERA5 performs well in southeastern China. However, it remains challenging to accurately recreate the extreme temperature events in the Tibetan Plateau. The elevation difference between the station and ERA5 grid point contributes to the main bias of reanalysis temperatures. The accuracy of ERA5 decreases with the increase in elevation discrepancy

How Well Does the ERA5 Reanalysis Capture the Extreme Climate Events Over China? Part I: Extreme Precipitation

ERA5 is the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts, with high spatiotemporal resolution and global coverage. However, the reliability of ERA5 for simulating extreme precipitation events is still unclear over China. In this study, 12 extreme precipitation indices and a comprehensive quantitative distance between indices of simulation and observation were used to evaluate ERA5 precipitation from three fundamental aspects: intensity, frequency, and duration. The geomorphological regionalization method was used to divide the subregions of China. The results showed that the ability of ERA5 to simulate annual total precipitation was better than that of daily precipitation. For the intensity indices, ERA5 performs well for simulating the PRCPTOT (annual total wet days precipitation) over China. ERA5 performs better on RX5day (max 5-days precipitation amount) and R95p (very wet days), especially in eastern China, than on RX1day (max 1-day precipitation amount) and R99p (extremely wet days). For the frequency indices, the ability of the ERA5 simulation increased as the amount of precipitation increased, except for northwestern China. However, the ability of ERA5 to simulate R50 mm (number of extreme heavy precipitation days) decreased. For the duration indices, ERA5 was better at simulating drought events than wet events in eastern China. Our results highlight the need for ERA5 to enhance the simulation of trend changes in extreme precipitation events

Upregulation of AT1 Receptor Mediates a Pressor Effect Through ROS-SAPK/JNK Signaling in Glutamatergic Neurons of Rostral Ventrolateral Medulla in Rats With Stress-Induced Hypertension

The present study examined whether angiotensin II (Ang II) mediates the pressor effect through nicotinamide adenine dinucleotide phosphate (NADPH) oxidase-derived reactive oxygen species (ROS)-mitogen-activated protein kinase (MAPK) signaling in the glutamatergic neurons of the rostral ventrolateral medulla (RVLM) in stress-induced hypertensive rats (SIHR). The SIHR model was established using electric foot-shocks combined with noises for 15 days. We observed that Ang II type 1 receptor (AT1R) and the glutamatergic neurons co-localized in the RVLM of SIHR. Furthermore, glutamate levels in the intermediolateral column of the spinal cord were higher in SIHR than in controls. Microinjection of Ang II into the RVLM of SIHR activated stress-activated protein kinase/Jun N-terminal kinase (SAPK/JNK), extracellular signal-regulated protein kinase (ERK) 1/2, and p38MAPK. Compared with controls, the activation of SAPK/JNK, ERK1/2, p38MAPK, and ROS in the RVLM were higher in SIHR, an effect that was blocked by an NADPH oxidase inhibitor (apocynin) and an AT1R antagonist (candesartan). RVLM microinjection of apocynin or a SAPK/JNK inhibitor (SP600125), but not an ERK1/2 inhibitor (U0126) or a p38MAPK inhibitor (SB203580), decreased AT1R mRNA and mean arterial blood pressure (MABP) in SIHR. The increase of AT1R protein expression and MABP was inhibited by intracerebroventricular infusion (ICV), for 14 days, of SP600125, but not U0126 or SB203580 in SIHR. We conclude that Ang II modulates the pressor effect through AT1R-dependent ROS-SAPK/JNK signaling in glutamatergic neurons in the RVLM of SIHR

Integrative analysis of the metabolome and transcriptome reveals the molecular mechanism of chlorogenic acid synthesis in peach fruit

As the most abundant phenolic acid in peach fruit, chlorogenic acid (CGA) is an important entry point for the development of natural dietary supplements and functional foods. However, the metabolic and regulation mechanisms underlying its accumulation in peach fruits remain unclear. In this study, we evaluated the composition and content of CGAs in mature fruits of 205 peach cultivars. In peach fruits, three forms of CGA (52.57%), neochlorogenic acid (NCGA, 47.13%), and cryptochlorogenic acid (CCGA, 0.30%) were identified. During the growth and development of peach fruits, the content of CGAs generally showed a trend of rising first and then decreasing. Notably, the contents of quinic acid, shikimic acid, p-coumaroyl quinic acid, and caffeoyl shikimic acid all showed similar dynamic patterns to that of CGA, which might provide the precursor material basis for the accumulation of CGA in the later stage. Moreover, CGA, lignin, and anthocyanins might have a certain correlation and these compounds work together to maintain a dynamic balance. By the comparative transcriptome analysis, 8 structural genes (Pp4CL, PpCYP98A, and PpHCT) and 15 regulatory genes (PpMYB, PpWRKY, PpERF, PpbHLH, and PpWD40) were initially screened as candidate genes of CGA biosynthesis. Our findings preliminarily analyzed the metabolic and molecular regulation mechanisms of CGA biosynthesis in peach fruit, which provided a theoretical basis for developing high-CGA content peaches in future breeding programs