Rogue waves (RWs) can form on the ocean surface due to the well-known quasi-four-wave resonant interaction or superposition principle. The first is known as the nonlinear focusing mechanism and leads to an increased probability of RWs when unidirectionality and narrowband energy of the wave field are satisfied. This work delves into the dynamics of extreme wave focusing in crossing seas, revealing a distinct type of nonlinear RWs, characterised by a decisive longevity compared with those generated by the dispersive focusing (superposition) mechanism. In fact, through fully nonlinear hydrodynamic numerical simulations, we show that the interactions between two crossing unidirectional wave beams can trigger fully localised and robust development of RWs. These coherent structures, characterised by a typical spectral broadening then spreading in the form of dual bimodality and recurrent wave group focusing, not only defy the weakening expectation of quasi-four-wave resonant interaction in directionally spreading wave fields, but also differ from classical focusing mechanisms already mentioned. This has been determined following a rigorous lifespan-based statistical analysis of extreme wave events in our fully nonlinear simulations. Utilising the coupled nonlinear Schrödinger framework, we also show that such intrinsic focusing dynamics can be captured by weakly nonlinear wave evolution equations. This opens new research avenues for further explorations of these complex and intriguing wave phenomena in hydrodynamics as well as other nonlinear and dispersive multi-wave systems.

The purpose of this study was to explore the electroencephalogram (EEG) features sensitive to situation awareness (SA) and then classify SA levels. Forty-eight participants were recruited to complete an SA standard test based on the multi-attribute task battery (MATB) II, and the corresponding EEG data and situation awareness global assessment technology (SAGAT) scores were recorded. The population with the top 25% of SAGAT scores was selected as the high-SA level (HSL) group, and the bottom 25% was the low-SA level (LSL) group. The results showed that (1) for the relative power of $\beta$1 (16–20Hz), $\beta$2 (20–24Hz) and $\beta$3 (24–30Hz), repeated measures analysis of variance (ANOVA) in three brain regions (Central Central-Parietal, and Parietal) × three brain lateralities (left, midline, and right) × two SA groups (HSL and LSL) showed a significant main effect for SA groups; post hoc comparisons revealed that compared with LSL, the above features of HSL were higher. (2) for most ratio features associated with $\beta$1 ∼ $\beta$3, ANOVA also revealed a main effect for SA groups. (3) EEG features sensitive to SA were selected to classify SA levels with small-sample data based on the general supervised machine learning classifiers. Five-fold cross-validation results showed that among the models with easy interpretability, logistic regression (LR) and decision tree (DT) presented the highest accuracy (both 92%), while among the models with hard interpretability, the accuracy of random forest (RF) was 88.8%, followed by an artificial neural network (ANN) of 84%. The above results suggested that (1) the relative power of $\beta$1 ∼ $\beta$3 and their associated ratios were sensitive to changes in SA levels; (2) the general supervised machine learning models all exhibited good accuracy (greater than 75%); and (3) furthermore, LR and DT are recommended by combining the interpretability and accuracy of the models.

Water fountains (WFs) are thought to represent an early stage in the morphological evolution of circumstellar envelopes surrounding low- and intermediate-mass evolved stars. These objects are considered to transition from spherical to asymmetric shapes. Despite their potential importance in this transformation process of evolved stars, there are only a few known examples. To identify new WF candidates, we used databases of circumstellar OH (1612 MHz) and H2O (22.235 GHz) maser sources, and compared the velocity ranges of the two maser lines. Finally, 41 sources were found to have a velocity range for the H2O maser line that exceeded that of the OH maser line. Excluding known planetary nebulae and after reviewing the maser spectra in the original literature, we found for 11 sources the exceedance as significant, qualifying them as new WF candidates.

Frequent freezing injury greatly influences winter wheat production; thus, effective prevention and a command of agricultural production are vital. The freezing injury monitoring method integrated with ‘3S’ (geographic information systems (GIS), global positioning system (GPS) and remote sensing (RS)) technology has an unparalleled advantage. Using HuanJing (HJ)-1A/1B satellite images of a winter wheat field in Shanxi Province, China plus a field survey, crop types and winter wheat planting area were identified through repeated visual interpretations of image information and spatial analyses conducted in GIS. Six vegetation indices were extracted from processed HJ-1A/1B satellite images to determine whether the winter wheat suffered from freezing injury and its degree of severity and recovery, using change vector analysis (CVA), the freeze injury representative vegetation index and the combination of the two methods, respectively. Accuracy of the freezing damage classification results was verified by determining the impact of freezing damage on yield and quantitative analysis. The CVA and the change of normalized difference vegetation index (ΔNDVI) monitoring results were different so a comprehensive analysis of the combination of CVA and ΔNDVI was performed. The area with serious freezing injury covered 0.9% of the total study area, followed by the area of no freezing injury (3.5%), moderate freezing injury (10.2%) and light freezing injury (85.4%). Of the moderate and serious freezing injury areas, 0.2% did not recover; 1.2% of the no freezing injury and light freezing injury areas showed optimal recovery, 15.6% of the light freezing injury and moderate freezing injury areas showed poor recovery, and the remaining areas exhibited general recovery.

The root-knot nematode, Meloidogyne javanica, is a major problem for the production of Sacha Inchi plants. We examined the effects of strip intercropping of Sacha Inchi/Chinese leek of 3–4 years on the seasonal dynamics of plant and soil traits in tropical China. Results indicated that in the intercropping system, a partially temporal divergence of belowground resource acquisition via niche separation occurred throughout the growing seasons, besides a complete spatially-separated plant height between the two crops. Compared with Sacha Inchi monoculture, the increased seed yield per unit area in the intercropping system was mainly attributed to the higher plant survival rate, rather than the enhanced plant traits of healthy plants. Intercropping greatly suppressed M. javanica populations only in the wet season, compared with monoculture; which may be associated with the combined effects of the direct allelopathy and indigenous microbe induced-suppressiveness. Intercropping did not affect microbial richness and α-diversity in the rhizosphere, except for the decreased fungal richness. Both bacterial and fungal composition and structure were diverged between monoculture v. intercropping system. The relative abundances of the dominant bacterial genera (Bacillus, Gaiellales, Lactococcus, Massilia and Lysobacter, etc.) differed significantly between the two cropping systems. For fungi, intercropping decreased the relative abundances of Fusarium and Gibberella, but increased those of Nectriaceae_unclassified, Chaetomiaceae, Humicola and Mortierella. Overall, Sacha Inchi/Chinese leek intercropping suppressed M. javanica populations and shifted microbial compositions (especially decreased pathogen-containing Fusarium). The increased yield and economic returns in this intercropping system provide valid information for the effective agricultural management.

Ruelle predicted that the maximal amplification of perturbations in homogeneous isotropic turbulence is exponential $\exp ({\sigma \sqrt {Re} \,t})$ (where $\sigma \sqrt {Re}$ is the maximal Lyapunov exponent). In our earlier works, we predicted that the maximal amplification of perturbations in fully developed turbulence is faster than exponential and is given by $\exp ({\sigma \sqrt {Re} \sqrt {t} +\sigma _1 t})$ where $\sigma \sqrt {Re} \sqrt {t}$ is much larger than $\sigma \sqrt {Re} \, t$ for small $t$. That is, we predicted superfast initial amplification of perturbations. Built upon our earlier numerical verification of our prediction, here, we conduct a large numerical verification with resolution up to $2048^3$ and Reynolds number up to $6210$. Our direct numerical simulation here confirms our analytical prediction. Our numerical simulation also demonstrates that such superfast amplification of perturbations leads to superfast nonlinear saturation. We conclude that such superfast amplification and superfast nonlinear saturation of ever existing perturbations suggest a mechanism for the generation, development and persistence of fully developed turbulence.

Electric-powered disposable unmanned aerial vehicles (UAVs) have wide applications due to their advantages in terms of long time flight and load capacity. Thus, improving their endurance has become an important task to enhance the performance of these UAVs. To achieve this, we investigated a battery dumping strategy which splits the battery into several packs that are used and dumped in sequence to reduce the dead weight. The Peukert effect is also considered. In this paper, the sensitivity analysis method was employed to analyse the endurance benefits for different battery weight ratios, Peukert constants and capacities, quantitatively. The results show that the endurance benefits are significantly affected by all three parameters. For ideal batteries, the endurance can be improved by 20% and 28% respectively when employing a double-pack or triple-pack battery strategy (for a battery weight ratio of 0.4), but these benefits will fall rapidly if the Peukert constant exceeds 1.0 or the battery weight declines. Besides, the endurance will be 10% longer if the lift coefficient rather than the velocity remains constant after the battery packs are dumped at a Peukert constant of 1.2.

The modelling of edge carbon transport and emission on EAST tokamak under resonant magnetic perturbation (RMP) fields has been conducted with the three-dimensional edge transport code EMC3-EIRENE. The measured vertical distribution of CVI emission by the extreme ultraviolet spectrometer system for the perturbed case shows a reduction in the CVI emission by 20 % compared to the equilibrium case. The chord-integrated CVI emission can be reconstructed by EMC3-EIRENE modelling, which presents an increase in the CVI emission with RMP fields. The discrepancy between experiments and simulations has been investigated by parameter study to examine the sensitivity of the simulation results on the edge plasma conditions and the impurity perpendicular transport. It is found that the variation of edge plasma conditions for the equilibrium case cannot resolve the discrepancy in the CVI emission between simulations and measurements. The simulations with enhanced impurity perpendicular transport coefficient allows a reasonable agreement with the measured reduction of CVI emission.

We present a long-term seasonal tree ring cellulose oxygen isotope (δ18Oc) time series created by analyzing four segments (S1, S2, S3, and S4) per year during the period of 1951–2009 from southeastern Tibetan Plateau. This intraseasonal δ18Oc reveals the onset and mature phase of the summer monsoon precipitation in this region. Analysis indicates that the δ18Oc of S1 has the strongest correlation with precipitation during the regional monsoon onset (29–33 pentads, May 21–June 10, r = −0.69), and the δ18Oc values for S2, S3, and S4 correlate strongly with June, July, and August precipitation, respectively. Combined δ18Oc of S2, S3, and S4 shows the most robust correlation (r = −0.82) with the mature-phase monsoon precipitation (June-July-August, JJA), passing rigorous statistical tests for calibration and verification in dendroclimatology. These results demonstrate the feasibility in using long-term intraseasonal δ18Oc to reconstruct the Asian summer monsoon's intraseasonal variations.

At present, analysis of diet and bladder cancer (BC) is mostly based on the intake of individual foods. The examination of food combinations provides a scope to deal with the complexity and unpredictability of the diet and aims to overcome the limitations of the study of nutrients and foods in isolation. This article aims to demonstrate the usability of supervised data mining methods to extract the food groups related to BC. In order to derive key food groups associated with BC risk, we applied the data mining technique C5.0 with 10-fold cross-validation in the BLadder cancer Epidemiology and Nutritional Determinants study, including data from eighteen case–control and one nested case–cohort study, compromising 8320 BC cases out of 31 551 participants. Dietary data, on the eleven main food groups of the Eurocode 2 Core classification codebook, and relevant non-diet data (i.e. sex, age and smoking status) were available. Primarily, five key food groups were extracted; in order of importance, beverages (non-milk); grains and grain products; vegetables and vegetable products; fats, oils and their products; meats and meat products were associated with BC risk. Since these food groups are corresponded with previously proposed BC-related dietary factors, data mining seems to be a promising technique in the field of nutritional epidemiology and deserves further examination.

Although numerous studies have investigated the individual effects of salinity, irrigation and fertilization on soil microbial communities, relatively less attention has been paid to their combined influences, especially using molecular techniques. Based on the field of orthogonal designed test and deoxyribonucleic acid sequencing technology, the effects of saline water irrigation amount, salinity level of irrigation water and nitrogen (N) fertilizer rate on soil bacterial community structure were investigated. The results showed that the irrigation amount was the most dominant factor in determining the bacterial richness and diversity, followed by the irrigation water salinity and N fertilizer rate. The values of Chao1 estimator, abundance-based coverage estimator and Shannon indices decreased with an increase in irrigation amount while increased and then decreased with an increase in irrigation water salinity and N fertilizer rate. The highest soil bacterial richness and diversity were obtained under the least irrigation amount (25 mm), medium irrigation water salinity (4.75 dS/m) and medium N fertilizer rate (350 kg/ha). However, different bacterial phyla were found to respond distinctively to these three factors: irrigation amount significantly affected the relative abundances of Proteobacteria and Chloroflexi; irrigation water salinity mostly affected the members of Actinobacteria, Gemmatimonadetes and Acidobacteria; and N fertilizer rate mainly influenced the Bacteroidetes' abundance. The results presented here revealed that the assessment of soil microbial processes under combined irrigation and fertilization treatments needed to be more careful as more variable consequences would be established by comparing with the influences based on an individual factor, such as irrigation amount or N fertilizer rate.

Deep-brain magnetic stimulation (DMS) is an effective therapy for various neuropsychiatric disorders including major depression disorder. The molecular and cellular mechanisms underlying the impacts of DMS on the brain remain unclear. Studies have reported abnormalities in the white matter of depressive brains, suggesting the involvement of myelin and oligodendrocyte pathologies in the development of major depressive disorder. In this study, we use a cuprizone induced demyelination animal model to generate depressive like behaviours and white matter and oligodendrocyte damages. Meanwhile, we treated the animal with DMS 20 minutes daily during the cuprizone challenge or recovery period. Behavioural tests, including nesting, new objective recognition, working memory and depression-like behaviours were tested periodically. Histological staining and western blotting were used to examine the underlying mechanism of DMS. We found that DMS reverse cuprizone induced behavioural deficits in acute demyelination but not during the recovery period. DMS alleviated demyelination and inflammation induced by cuprizone. During the recovery period, DMS had no impacts on overall neural progenitor cell proliferation, but enhanced the maturation of oligodendrocyte. This data suggest that DMS may be a promising treatment option for improving white matter function in psychiatric disorders and neurological diseases in future.

The elastoplastic behavior of a Functionally Graded Material (FGM) simply supported beam consisting of elastic material A and elastoplastic material B under uniformly distributed load is investigated. A power function is used to describe the volume fractions of the constituent materials, and the average stress of the FGM beam is obtained by using the averaging method. This method can avoid the assumption of the varying properties of the whole material, and can consider the different Possion’s ratios of the different constituent materials. What’s more, only the elastoplastic material B in the FGM beam will yield, and the yield function is determined by the stress of material B only, rather than the average stress of the whole material. The method used in this work is more closer to the real material than the method by assuming the variation of the whole properties of FGM. The theoretical results show a good agreement with the finite element results, which indicates that the method provided in this work is valid. With this method, the variation of the elastic and plastic areas, the stress distribution on the cross section, variation of the curvature and neutral layer, and the residual stress distribution of the FGM beam are discussed through numerical results. This work can provide a new way for the design and in-depth investigation of FGM material.

Quantifying reasonable crop yield gaps and determining potential regions for yield improvement can facilitate regional plant structure adjustment and promote crop production. The current study attempted to evaluate the yield gap in a region at multi-scales through model simulation and farmer investigation. Taking the winter wheat yield gap in the Huang-Huai-Hai farming region (HFR) for the case study, 241 farmers’ fields in four typical high-yield demonstration areas were surveyed to determine the yield limitation index and attainable yield. In addition, the theoretical and realizable yield gap of winter wheat in 386 counties of the HFR was assessed. Results showed that the average field yield of the demonstration plots was 8282 kg/ha, accounting for 0.72 of the potential yield, which represented the highest production in the region. The HFR consists of seven sub-regions designated 2.1–2.7: the largest attainable yield gap existed in the 2.6 sub-region, in the southwest of the HFR, while the smallest was in the 2.2 sub-region, in the northwest of the HFR. With a high irrigated area rate, the yield gap in the 2.2 sub-region could hardly be reduced by increasing irrigation, while a lack of irrigation remained an important limiting factor for narrowing the yield gap in 2.3 sub-region, in the middle of the HFR. Therefore, a multi-scale yield gap evaluation framework integrated with typical field survey and crop model analysis could provide valuable information for narrowing the yield gap.

The strong-coupling mode, called the “quasimode”, is excited by stimulated Brillouin scattering (SBS) in high-intensity laser–plasma interactions. Also SBS of the quasimode competes with SBS of the fast mode (or slow mode) in multi-ion species plasmas, thus leading to a low-frequency burst behavior of SBS reflectivity. Competition between the quasimode and the ion-acoustic wave (IAW) is an important saturation mechanism of SBS in high-intensity laser–plasma interactions. These results give a clear explanation of the low-frequency periodic burst behavior of SBS and should be considered as a saturation mechanism of SBS in high-intensity laser–plasma interactions.