This paper studied the use of eye movement data to form criteria for judging whether pilots perceive emergency information such as cockpit warnings. In the experiment, 12 subjects randomly encountered different warning information while flying a simulated helicopter, and their eye movement data were collected synchronously. Firstly, the importance of the eye movement features was calculated by ANOVA (analysis of variance). According to the sorting of the importance and the Euclidean distance of each eye movement feature, the warning information samples with different eye movement features were obtained. Secondly, the residual shrinkage network modules were added to CNN (convolutional neural network) to construct a DRSN (deep residual shrinkage networks) model. Finally, the processed warning information samples were used to train and test the DRSN model. In order to verify the superiority of this method, the DRSN model was compared with three machine learning models, namely SVM (support vector machine), RF (radom forest) and BPNN (backpropagation neural network). Among the four models, the DRSN model performed the best. When all eye movement features were selected, this model detected pilot perception of warning information with an average accuracy of 90.4%, of which the highest detection accuracy reached 96.4%. Experiments showed that the DRSN model had advantages in detecting pilot perception of warning information.

We report the experimental results of the commissioning phase in the 10 PW laser beamline of the Shanghai Superintense Ultrafast Laser Facility (SULF). The peak power reaches 2.4 PW on target without the last amplifying during the experiment. The laser energy of 72 ± 9 J is directed to a focal spot of approximately 6 μm diameter (full width at half maximum) in 30 fs pulse duration, yielding a focused peak intensity around 2.0 × 1021 W/cm2. The first laser-proton acceleration experiment is performed using plain copper and plastic targets. High-energy proton beams with maximum cut-off energy up to 62.5 MeV are achieved using copper foils at the optimum target thickness of 4 μm via target normal sheath acceleration. For plastic targets of tens of nanometers thick, the proton cut-off energy is approximately 20 MeV, showing ring-like or filamented density distributions. These experimental results reflect the capabilities of the SULF-10 PW beamline, for example, both ultrahigh intensity and relatively good beam contrast. Further optimization for these key parameters is underway, where peak laser intensities of 1022–1023 W/cm2 are anticipated to support various experiments on extreme field physics.

Root-lesion nematodes (Pratylenchus spp.) are a group of economically important pathogens that have caused serious economic losses in many crops. In 2019, root-lesion nematodes were recovered from tomato (Solanum lycopersicum) root samples collected from Sichuan Province, People's Republic of China (PRC). Extracted nematodes were disinfected, and one individual female was cultured on a carrot disc for propagation at 25 °C by parthenogenesis and designated the SC isolate. Afterwards, the isolate was identified on the basis of morphometric and molecular markers. Both morphometric characters and molecular analysis of the internal transcribed spacer region gene (ITS) of ribosomal DNA, the D2-D3 expansion region of the 28S rDNA gene and the mitochondrial cytochrome oxidase I (mtDNA-COI) gene revealed that the species of root-lesion nematode was Pratylenchus scribneri. The Bayesian tree inferred from the ITS rDNA, 28S rDNA and mtDNA-COI gene sequences also showed that this isolate formed a highly supported clade with other P. scribneri isolates. The pathogenicity of the root-lesion nematode SC isolate on tomato was assessed, showing that tomato was a suitable host for P. scribneri. To the best of our knowledge, this is the first report of P. scribneri on tomato in Sichuan Province, PRC. These are also the first molecular data obtained from P. scribneri on tomato in the PRC, and the pathogenicity of P. scribneri to tomato was studied for the first time. This study provides scientific data for the detection, identification and control of tomato root-lesion nematode disease.

The commercial Computational Fluid Dynamics (CFD) software STAR-CCM+ was used to simulate the flow and breakup characteristics of a Liquid Jet Injected into the gaseous Crossflow (LJIC) under real engine operating conditions. The reasonable calculation domain geometry and flow boundary conditions were obtained based on a civil aviation engine performance model similar to the Leap-1B engine which was developed using the GasTurb software and the preliminary design results of its low-emission combustor. The Volume of Fluid (VOF) model was applied to simulate the breakup feature of the near field of LJIC. The numerical method was validated and calibrated through comparison with the public test data at atmospheric conditions. The results showed that the numerical method can capture most of the jet breakup structure and predict the jet trajectory with an error not exceeding ±5%. The verified numerical method was applied to simulate the breakup of LJIC at the real engine operating condition. The breakup mode of LJIC was shown to be surface shear breakup at elevated condition. The trajectory of the liquid jet showed good agreement with Ragucci’s empirical correlation.

Considering the shortcomings of current methods for real-time resolution of two-aircraft flight conflicts, a geometric optimal conflict resolution and recovery method based on the velocity obstacle method for two aircraft and a cooperative conflict resolution method for multiple aircraft are proposed. The conflict type was determined according to the relative position and velocity of the aircraft, and a corresponding conflict mitigation strategy was selected. A resolution manoeuvre and a recovery manoeuvre were performed. On the basis of a two-aircraft conflict resolution model, a multi-aircraft cooperative conflict resolution game was constructed to identify an optimal solution for maximising group welfare. The solution and recovery method is simple and effective, and no new flight conflicts are introduced during track recovery. For multi-aircraft conflict resolution, an equilibrium point that maximises the welfare function of the group was identified, and thus, an optimal strategy for multi-aircraft conflict resolution was obtained.

Manure is a primary source of methane (CH4) emissions into the atmosphere. A large proportion of CH4 from manure is emitted during storage, but this varies with storage methods. In this research, we tested whether covering a manure heap with plastic reduces CH4 emission during a short-term composting process. A static chamber method was used to detect the CH4 emission rate and the change of the physicochemical properties of cattle manure which was stored either uncovered (treatment UNCOVERED) or covered with plastic (treatment COVERED) for 30-day periods during the four seasons? The dry matter content of the COVERED treatment was significantly less than the UNCOVERED treatment (P < 0.01), and the C/N ratio of the COVERED treatment significantly greater than the UNCOVERED treatment (P > 0.05) under high temperature. In the UNCOVERED treatment, average daily methane (CH4) emissions were in the order summer > spring > autumn > winter. CH4 emissions were positively correlated with the temperature (R2 = 0.52, P < 0.01). Compared to the UNCOVERED treatment, the daily average CH4 emission rates from COVERED treatment manure were less in the first 19 days of spring, 13 days of summer, 10 days of autumn and 30 days of winter. In summary, covering the manure pile with plastic reduces the evaporation of water during storage; and in winter, long-term covering with plastic film reduces the CH4 emissions during the storage of manure.

The aim of this study was to explore the frequency and distribution of gene mutations that are related to isoniazid (INH) and rifampin (RIF)-resistance in the strains of the multidrug-resistant tuberculosis (MDR-TB) Mycobacterium tuberculosis (M.tb) in Beijing, China. In this retrospective study, the genotypes of 173 MDR-TB strains were analysed by spoligotyping. The katG, inhA genes and the promoter region of inhA, in which genetic mutations confer INH resistance; and the rpoB gene, in which genetic mutations confer RIF resistance, were sequenced. The percentage of resistance-associated nucleotide alterations among the strains of different genotypes was also analysed. In total, 90.8% (157/173) of the MDR strains belonged to the Beijing genotype. Population characteristics were not significantly different among the strains of different genotypes. In total, 50.3% (87/173) strains had mutations at codon S315T of katG; 16.8% (29/173) of strains had mutations in the inhA promoter region; of them, 5.5% (15/173) had point mutations at −15 base (C→T) of the inhA promoter region. In total, 86.7% (150/173) strains had mutations at rpoB gene; of them, 40% (69/173) strains had mutations at codon S531L of rpoB. The frequency of mutations was not significantly higher in Beijing genotypic MDR strains than in non-Beijing genotypes. Beijing genotypic MDR-TB strains were spreading in Beijing and present a major challenge to TB control in this region. A high prevalence of katG Ser315Thr, inhA promoter region (−15C→T) and rpoB (S531L) mutations was observed. Molecular diagnostics based on gene mutations was a useful method for rapid detection of MDR-TB in Beijing, China.

Longan is an economically important sub-tropical fruit tree native to southern China and southeast Asia. Its production has been affected significantly by climate change, but the underlying reasons remain unclear. Herein, the potential growing areas of longan were simulated by the Maxent model under current and future conditions. The results showed excellent prediction performance, with an area under curve of >0.9 for model training and validation. The key environmental variables identified were mean temperature of the coldest quarter, minimum temperature of the coldest month, annual mean temperature and mean temperature of the driest quarter. The optimum suitable areas of longan were found to be concentrated mainly in south-western, southern and eastern China, with a slight increase in optimum suitable areas under two different emission scenarios of three global climatic models. However, its future potential growing areas were predicted to differ among provinces or cities. Suitable growing areas in Sichuan, Jiangxi, Guangxi and Chongqing will first increase and then remain approximately unchanged between the 2050s and 2070s; those in Yunnan, Guangdong and Hainan will remain approximately unchanged from the present to the 2070s; those in Fujian and Guizhou will fluctuate slightly from the present to the 2050s and then increase to the 2070s; those in Taiwan will first decrease and then increase. In summary, the major future production areas of longan will be Guangdong, Hainan and Guangxi provinces, followed by Chongqing, Yunnan, Fujian and Taiwan. Thus, this study serves as a useful guide for the management of longan.

Gravitational waves from coalescing neutron stars encode information about nuclear matter at extreme densities, inaccessible by laboratory experiments. The late inspiral is influenced by the presence of tides, which depend on the neutron star equation of state. Neutron star mergers are expected to often produce rapidly rotating remnant neutron stars that emit gravitational waves. These will provide clues to the extremely hot post-merger environment. This signature of nuclear matter in gravitational waves contains most information in the 2–4 kHz frequency band, which is outside of the most sensitive band of current detectors. We present the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimised to study nuclear physics with merging neutron stars. The concept uses high-circulating laser power, quantum squeezing, and a detector topology specifically designed to achieve the high-frequency sensitivity necessary to probe nuclear matter using gravitational waves. Above 1 kHz, the proposed strain sensitivity is comparable to full third-generation detectors at a fraction of the cost. Such sensitivity changes expected event rates for detection of post-merger remnants from approximately one per few decades with two A+ detectors to a few per year and potentially allow for the first gravitational-wave observations of supernovae, isolated neutron stars, and other exotica.

Bordetella bronchiseptica is a potential zoonotic pathogen, which mainly causes respiratory diseases in humans and a variety of animal species. B. bronchiseptica is one of the important pathogens isolated from rabbits in Fujian Province. However, the knowledge of the epidemiology and characteristics of the B. bronchiseptica in rabbits in Fujian Province is largely unknown. In this study, 219 B. bronchiseptica isolates recovered from lung samples of dead rabbits with respiratory diseases in Fujian Province were characterised by multi-locus sequencing typing, screening virulence genes and testing antimicrobial susceptibility. The results showed that the 219 isolates were typed into 11 sequence types (STs) including five known STs (ST6, ST10, ST12, ST14 and ST33) and six new STs (ST88, ST89, ST90, ST91, ST92 and ST93) and the ST33 (30.14%, 66/219), ST14 (26.94%, 59/219) and ST12 (16.44%, 36/219) were the three most prevalent STs. Surprisingly, all the 219 isolates carried the five virulence genes (fhaB, prn, cyaA, dnt and bteA) in the polymerase chain reaction screening. Moreover, the isolates were resistant to cefixime, ceftizoxime, cefatriaxone and ampicillin at rates of 33.33%, 31.05%, 11.87% and 3.20%, respectively. This study showed the genetic diversity of B. bronchiseptica in rabbits in Fujian Province, and the colonisation of the human-associated ST12 strain in rabbits in Fujian Province. The results might be useful for monitoring the epidemic strains, developing preventive methods and preventing the transmission of epidemic strains from rabbits to humans.

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.