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In view of the unsatisfactory effect and major limitations of the style transfer of art works, this paper takes Chinese ink painting for the research subject. The obvious texture characteristics of Chinese ink painting are selected as the input of the Cycle Generative Adversarial Network (CycleGAN) model builder, and the relativistic evaluator is employed to improve the model loss function and the adversarial loss function. An improved art style transfer method of the CycleGAN model is proposed. The experiment shows that the improved CycleGAN model is efficient and feasible for style transfer. Compared with the traditional CycleGAN model, the proposed model performs better in GAN train and GAN test, with a higher average pass rate, which is an increase of nearly 10%. At the same time, with the increase of the number of iterations, the training time of the improved model is close to that of the original model, but the image of the improved model training is larger, which shows that it has more advantages.

A major disturbance in nature, drought, has a significant impact on the vulnerability and resilience of semi-arid ecosystems by shifting phenology and productivity. However, due to the various disturbance mechanisms, phenology and primary productivity have remained largely ambiguous until now. This paper evaluated the spatio-temporal changes of phenology and productivity based on GIMMS NDVI3g time series data, and demonstrated the responses of vegetation phenology and productivity to drought disturbances with the standardized precipitation evapotranspiration index (SPEI) in semi-arid ecosystems of northern China. The results showed that (1): vegetation phenology exhibited dramatic spatial heterogeneity with different rates, mostly presented in the regions with high chances of land cover type variation. The delayed onset of growing season (SOS) and advanced end of growing season (EOS) occurred in Horqin Sandy Land and the eastern Ordos Plateau with a one to three days/decade (p < 0.05) rate and in the middle and east of Inner Mongolia with a two days/decade rate, respectively. Vegetation productivity presented a clear pattern: south increased and north decreased. (2) Spring drought delayed SOS in grassland, barren/sparsely vegetated land, and cropland, while autumn drought significantly advanced EOS in grassland and barren/sparsely vegetated lands. Annual drought reduced vegetation productivity and the sensitivity of productivity regarding drought disturbance was higher than that of phenology.

5-Methylfurfural (MF) is a very useful chemical. Selective hydrogenation of biomass platform molecule 5-(hydroxymethyl)furfural (HMF) to MF using H 2 as the reducing agent is very attractive, but challenging because hydrogenation of C=O bond in HMF is more favourable than C–OH both kinetically and thermodynamically, and this route has not been realized. In this work, we prepare isolated single atomic catalysts (SACs) Pt 1 /Nb 2 O 5 -Ov, Pd 1 /Nb 2 O 5 -Ov, and Au 1 /Nb 2 O 5 -Ov, in which single metal atoms are supported on oxygen defective Nb 2 O 5 (Nb 2 O 5 -Ov). It is discovered that the SACs can efficiently catalyze the hydrogenation of HMF to MF using H 2 as the reducing agent with MF selectivity of >99% at complete conversion, while the selectivities of the metal nanocatalysts supported on Nb 2 O 5 are very poor. A combination of experimental and density function theory (DFT) studies show that the unique features of the SACs for the reaction result from the cooperation of the Nb and Pt sites near the interface in the Pt 1 /Nb 2 O 5 -Ov. The Pt atoms are responsible for the activation of H 2 and the Nb sites activate C-OH in the reaction. This work opens the way for producing MF by direct hydrogenation of biomass-derived HMF using H 2 as the reductant. Selective hydrogenation of 5-(hydroxymethyl)furfural (HMF) to 5-Methylfurfural using H2 as reductant is very attractive, but remains challenging. Here, the authors report that isolated single atomic catalysts can catalyze the reaction efficiently with selectivity >99% at complete conversion of HMF.

Alpine meadow and alpine steppe are the two most widely distributed nonzonal vegetation types in the Qinghai-Tibet Plateau. In the context of global climate change, the differences in spatial-temporal variation trends and their responses to climate change are discussed. It is of great significance to reveal the response of the Qinghai-Tibet Plateau to global climate change and the construction of ecological security barriers. This study takes alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau as the research objects. The normalized difference vegetation index (NDVI) data and meteorological data were used as the data sources between 2000 and 2018. By using the mean value method, threshold method, trend analysis method and correlation analysis method, the spatial and temporal variation trends in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau were compared and analyzed, and their differences in the responses to climate change were discussed. The results showed the following: (1) The growing season length of alpine meadow was 145~289 d, while that of alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau was 161~273 d, and their growing season lengths were significantly shorter than that of alpine meadow. (2) The annual variation trends of the growing season NDVI for the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau increased obviously, but their fluctuation range and change rate were significantly different. (3) The overall vegetation improvement in the Qinghai-Tibet Plateau was primarily dominated by alpine steppe and alpine meadow, while the degradation was primarily dominated by alpine meadow. (4) The responses between the growing season NDVI and climatic factors in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau had great spatial heterogeneity in the Qinghai-Tibet Plateau. These findings provide evidence towards understanding the characteristics of the different vegetation types in the Qinghai-Tibet Plateau and their spatial differences in response to climate change.

Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Currently, lung cancer diagnosis mainly relies on manual pathology section analysis, but the low efficiency and subjective nature of manual film reading can lead to certain misdiagnoses and omissions. With the continuous development of science and technology, artificial intelligence (AI) has been gradually applied to imaging diagnosis. Although there are reports on AI-assisted lung cancer diagnosis, there are still problems such as small sample size and untimely data updates. Therefore, in this study, a large amount of recent data was included, and meta-analysis was used to evaluate the value of AI for lung cancer diagnosis. With the help of STATA16.0, the value of AI-assisted lung cancer diagnosis was assessed by specificity, sensitivity, negative likelihood ratio, positive likelihood ratio, diagnostic ratio, and plotting the working characteristic curves of subjects. Meta-regression and subgroup analysis were used to investigate the value of AI-assisted lung cancer diagnosis. The results of the meta-analysis showed that the combined sensitivity of the AI-aided diagnosis system for lung cancer diagnosis was 0.87 [95% CI (0.82, 0.90)], specificity was 0.87 [95% CI (0.82, 0.91)] (CI stands for confidence interval.), the missed diagnosis rate was 13%, the misdiagnosis rate was 13%, the positive likelihood ratio was 6.5 [95% CI (4.6, 9.3)], the negative likelihood ratio was 0.15 [95% CI (0.11, 0.21)], a diagnostic ratio of 43 [95% CI (24, 76)] and a sum of area under the combined subject operating characteristic (SROC) curve of 0.93 [95% CI (0.91, 0.95)]. Based on the results, the AI-assisted diagnostic system for CT (Computerized Tomography), imaging has considerable diagnostic accuracy for lung cancer diagnosis, which is of significant value for lung cancer diagnosis and has greater feasibility of realizing the extension application in the field of clinical diagnosis.

Summary Soybean is one of the most important oilseed and fodder crops. Benefiting from the efforts of soybean breeders and the development of breeding technology, large number of germplasm has been generated over the last 100 years. Nevertheless, soybean breeding needs to be accelerated to meet the needs of a growing world population, to promote sustainable agriculture and to address future environmental changes. The acceleration is highly reliant on the discoveries in gene functional studies. The release of the reference soybean genome in 2010 has significantly facilitated the advance in soybean functional genomics. Here, we review the research progress in soybean omics (genomics, transcriptomics, epigenomics and proteomics), germplasm development (germplasm resources and databases), gene discovery (genes that are responsible for important soybean traits including yield, flowering and maturity, seed quality, stress resistance, nodulation and domestication) and transformation technology during the past decade. At the end, we also briefly discuss current challenges and future directions.

Adaptive changes in plant phenology are often considered to be a feature of the so-called ‘domestication syndrome’ that distinguishes modern crops from their wild progenitors, but little detailed evidence supports this idea. In soybean, a major legume crop, flowering time variation is well characterized within domesticated germplasm and is critical for modern production, but its importance during domestication is unclear. Here, we identify sequential contributions of two homeologous pseudo-response-regulator genes, Tof12 and Tof11 , to ancient flowering time adaptation, and demonstrate that they act via LHY homologs to promote expression of the legume-specific E1 gene and delay flowering under long photoperiods. We show that Tof12 -dependent acceleration of maturity accompanied a reduction in dormancy and seed dispersal during soybean domestication, possibly predisposing the incipient crop to latitudinal expansion. Better understanding of this early phase of crop evolution will help to identify functional variation lost during domestication and exploit its potential for future crop improvement. Whole-genome resequencing and association analyses in 424 soybean accessions identify two homeologous genes that contributed to flowering time adaptation during soybean domestication.

Designing heterogeneous solid surface frustrated Lewis pair (ssFLP) catalyst for hydrogenation is a new challenge in catalysis and no research has been reported on the construction of ssFLP on boehmite (AlOOH) surfaces up to now as far as we know. Herein, AlOOH with a layer structure is prepared and it is found that the Lewis basic O Hv site (one H removed from OH) and an adjacent Lewis acidic unsaturated Al site (Al 3+ unsatur .) proximal to a surface OH v (OH vacancy) on AlOOH layers could form the ssFLP. The layered structure of AlOOH and its abundant OH defects over the surface result in a high concentration of O Hv /Al 3+ unsatur . FLPs, which are conducive to highly efficient hydrogen activation for hydrogenation of olefins and alkynes with low H-H bond dissociates activation energy of 0.16 eV under mild conditions (T = 80°C and P(H 2 ) = 2.0 MPa). This work develops a new kind of hydrogenation catalyst and provides a new perspective for creating solid surface FLP. Designing heterogeneous solid surface frustrated Lewis pair (ssFLP) catalyst for hydrogenation is a new challenge in catalysis. Here, the authors show the ssFLP can be constructed on layered AlOOH for hydrogenation reactions under mild conditions.

Mobile robots moving fast or in scenes with poor lighting conditions often cause the loss of visual feature tracking. In coal mine tunnels, the ground is often bumpy and the lighting is uneven. During the movement of the mobile robot in this scene, there will be violent bumps. The localization technology through visual features is greatly affected by the illumination and the speed of the camera movement. To solve the localization and mapping problem in an environment similar to underground coal mine tunnels, we improve a localization and mapping algorithm based on a monocular camera and an Inertial Measurement Unit (IMU). A feature-matching method that combines point and line features is designed to improve the robustness of the algorithm in the presence of degraded scene structure and insufficient illumination. The tightly coupled method is used to establish visual feature constraints and IMU pre-integration constraints. A keyframe nonlinear optimization algorithm based on sliding windows is used to accomplish state estimation. Extensive simulations and practical environment verification show that the improved simultaneous localization and mapping (SLAM) system with a monocular camera and IMU fusion can achieve accurate autonomous localization and map construction in scenes with insufficient light such as coal mine tunnels.

To minimize leakage and maintain the efficiency of turbomachinery, brush seal can be installed with zero clearance or interference as the flexibility. This leads to contact between the rotor and bristle pack, and may cause self-excited vibration, even instability. In this study, to establishment a mathematical model of the rotor system, a seal force model with bristle interference is proposed and the nonlinear oil-film force is applied in view of short bearing assumption. The influences of main factors containing rotor rotational speed, installing interval, disc mass, and disk eccentricity on the nonlinear characteristics of the rotor-bearing-brush seal system are conducted by adopting bifurcation diagram, spectrum cascade, axis orbit, and Poincaré map. The results indicate that the vibration amplitude of the system with bristle interference is a bit larger than that without interference. The system stability is enhanced with smaller disk mass at a higher rotational speed. The proposed model could provide valuable reference for the design of a rotor-bearing-seal system.