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As the next-generation power system, smart grid presents challenges to enterprises in managing and analyzing massive data, meeting complex operational and decision-making demands, and predicting future power demand for grid optimization. This paper aims to proposed a fusion algorithm for smart grid enterprise decision-making and economic benefit analysis, enhancing the accuracy of decision-making and predictive capability of economic benefits. The proposed method combines techniques such as Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), and edge computing. The LSTM model is employed to model historical data of the smart grid. The GAN model generates diverse scenarios for future power demand and economic benefits. The proposed method is evaluated on four public datasets, including the ENTSO-E Dataset, and outperforms several traditional algorithms in terms of prediction accuracy, efficiency, and stability. Notably, on the ENTSO-E Dataset, the proposed algorithm achieves a reduction of over 46.6% in FLOP, and a decrease in inference time by over 48.3%, and an improvement of 38% in MAPE. The novel fusion algorithm proposed in this paper demonstrates significant advantages in accuracy and predictive capability, providing a scientific basis for smart grid enterprise decision-making and economic benefit analysis while offering practical value for real-world applications.

Abstract Human cerebellum encompasses numerous neurons, exhibiting a distinct developmental paradigm from cerebrum. Here we conducted scRNA-seq, scATAC-seq and spatial transcriptomic analyses of fetal samples from gestational week (GW) 13 to 18 to explore the emergence of cellular diversity and developmental programs in the developing human cerebellum. We identified transitory granule cell progenitors that are conserved across species. Special patterns in both granule cells and Purkinje cells were dissected multidimensionally. Species-specific gene expression patterns of cerebellar lobes were characterized and we found that PARM1 exhibited inconsistent distribution in human and mouse granule cells. A novel cluster of potential neuroepithelium at the rhombic lip was identified. We also resolved various subtypes of Purkinje cells and unipolar brush cells and revealed gene regulatory networks controlling their diversification. Therefore, our study offers a valuable multi-omics landscape of human fetal cerebellum and advances our understanding of development and spatial organization of human cerebellum.

In the realm of artificial intelligence, knowledge graphs (KGs) serve as an essential structured framework, capturing intricate relationships between diverse entities and supporting a broad spectrum of AI applications. Despite their utility, the static characteristic of KGs poses challenges in dynamically evolving information landscapes. This has catalyzed the development of temporal knowledge graphs (TKGs), which introduce a temporal layer to KGs, facilitating the representation of knowledge progression through time. This study zeroes in on the critical task of TKG extrapolation, which is vital for forecasting future occurrences and offering foresight into emerging situations across a variety of fields. Most contemporary approaches to TKG extrapolation are predicated on the symmetrical encoder–decoder paradigm, wherein the processes of representation learning and reasoning are harmoniously intertwined. While the encoder often garners the most attention due to its role in capturing and encoding information, the pivotal role of the decoder, which is often overlooked, is essential for direct inference and the accurate projection of temporal dynamics. To this end, we present the Householder-transformation-based temporal knowledge graph extrapolation (HTKGE) method: a groundbreaking encoder–decoder framework that reimagines the decoder’s contribution to TKG extrapolation. Our approach spotlights an adaptive decoder propelled by Householder transformations, which engage dynamically with the temporal encoding from the encoder. This interaction fosters a nuanced comprehension of the TKG’s temporal trajectory. Our empirical evaluations across four benchmark TKG datasets substantiate HTKGE’s consistent efficacy in TKG extrapolation tasks.

Knowledge graphs (KGs) have become a cornerstone for structuring vast amounts of information, enabling sophisticated AI applications across domains. The progression to temporal knowledge graphs (TKGs) introduces time as an essential dimension, allowing for a dynamic representation of entity relationships. Despite their potential, TKGs often suffer from incompleteness, necessitating the development of temporal knowledge graph completion (TKGC) techniques. These methods, particularly focusing on interpolation within the known timeframe, aim to infer missing temporal facts and enhance the predictive capabilities of TKGs. The prevalent reliance on Euclidean space modeling in TKGC methods presents challenges in capturing the complex, hierarchical, and time-varying nature of TKGs. To overcome these limitations, we introduced the attention-based geometry interaction embedding (ATGIE) method, a novel approach that leverages the strengths of multiple geometric spaces, i.e., Euclidean, hyperbolic, and hypersphere, to model the intricacies of TKGs more effectively. ATGIE employs an attention mechanism to dynamically weigh the contributions of different geometric spaces, allowing it to adaptively form reliable spatial structures based on interactive geometric information. This multi-space modeling not only captures the diverse relationships within TKGs but also facilitates a nuanced understanding of how entities and their relationships evolve over time. Through extensive experiments, we demonstrate ATGIE’s superiority in TKGC tasks, showcasing its improvement over existing methods, robustness to noise, and sensitivity to temporal dynamics. The results highlight ATGIE’s potential to advance the state-of-the-art in TKGC, offering a promising direction for research and application in the field.

Abstract To provide high‐quality imaging by decreasing the sparse view imaging artefact from the computed tomography (CT) images, this study addresses a new artefact suppression technique for sparse data for both single material and multi‐material objects that have diverse materials. It begins with a pre‐reconstructed image and a network of target patches that have been trained beforehand and then uses the forward projection (FP) approach to resolve the structural mutation brought on by sparse‐view projection. As an edge‐preserving operator to commit to the forward operator for sinogram correction, the bilateral filter was used. Both simulated and actual data have been gathered and evaluated in experiments. The suggested forward operator and normalized compensation (FONC) method produce results that have far smaller artefact and errors than those of more traditional techniques. For simulation # blade, the Normalized Mean Square Distance (NMSD) of the proposed method was reduced by 8.94%, Structural Similarity Index (SSIM) and the Universal Quality Index (UQI) were increased by 78.17% and 80.49%, respectively, which also demonstrate better uniformity of the results to practical data # pan, where the root mean squared error was reduced by 13.93%. SSIM and UQI were increased by 25.66% and 37.02%, respectively. The results conclusively show that the planned strategies are successful in eliminating artefact for irregular objects.

Many emerging markets rely on land financing, whereby land grants are used to raise funds for the government. In the short term, land financing eases the government’s fiscal deficit and boosts regional economic development. However, the long-term implications of such behaviour have not been adequately discussed. This study focuses on the relationship between local government land finance dependence (LGLFD) and urban innovation quality (UIQ). We find that LGLFD significantly inhibits the improvement of UIQ, and this inhibition occurs through three main channels: changing government spending preferences, reducing financial efficiency, and deteriorating the institutional environment. Our empirical study analyses 3662 samples from 264 Chinese cities from 2003 to 2016, confirming our research hypothesis. Further research finds that there is significant heterogeneity in the effect of LGLFD on UIQ. Based on these conclusions, some policy implications are proposed.

A two-dimensional numerical model incorporating solid mechanics, electrochemistry, mass diffusion, and ion migration processes is developed to investigate the load effect on the crevice corrosion. The model is a transient model of crevice corrosion occurring in cracks of 304 stainless steel in a dilute NaCl solution, and the interaction between stress and electrochemical corrosion was considered. By solving the multiphysical coupling model in COMSOL, the effect of applied load on electrochemical corrosion in the crack tip region was calculated, and the local corrosion current density in the crack tip region with stress concentration within the crack was also calculated by using the Tafel relationship. The distribution of Fe2+ ion, Na+ ion, CL− ion, and H and O2 substance concentrations within the crack cavity is predicted by the equation analysis of substance transport. The results show that metal oxidation is more clearly affected by plastic deformation, the rate of hydrogen evolution reaction increases with stress enhancement, and the oxygen absorption reaction is not affected by stress strain. The distribution of iron ions, hydrogen, and oxygen within the crack is affected by the electrochemical reaction rate, and the distribution of iron ions, sodium ions, and chloride ions is affected by the electrolyte potential.

The creep behaviour of hot hammer forged Ti-6Al-4V alloy under different forging temperatures has an essential influence on their high-temperature service performance. In this article, the high-temperature mechanical property and creep behaviour of Ti-6Al-4V alloy forging at different forging temperatures were first investigated experimentally. Then, in view of the critical effect of microcracks and other defects on the service life of components in forging, the creep characteristics at the tip of a 2 mm crack were characterized by the finite element method. The results show that when the Ti-6Al-4V alloy was forged at 1000°C, the high-temperature mechanical property was improved, and the steady-state creep rate and creep residual deformation were significantly reduced. In addition, the creep strain and creep rate at the crack tip were decreased apparently during creep, and the creep strain gradient in the crack tip region was also significantly reduced. This indicates that the creep deformation of Ti-6Al-4V alloy can be controlled by an appropriate forging temperature during hot hammer forging process and might delay the crack propagation to improve the service life of components.

The radiative forcing of spatially varying carbon dioxide (CO2) concentrations has modified the climate by altering surface energy, the water budget, and carbon cycling. Over the past several decades, due to anthropogenic emissions, atmospheric CO2 concentrations in the whole terrestrial ecosystem have become greater than the global mean. The relationship between climatic variables and net primary production (NPP) can be regulated by the radiative forcing of this spatial variation. The present results show that owing to the radiative forcing of spatially varying CO2 concentrations, NPP has reduced globally by −0.6 Pg C yr−1. Region 2, with increased CO2 and decreased NPP, shows the greatest reductions, by −0.7 Pg C yr−1. Variations of both NPP and CO2 concentrations are distributed asymmetrically. As human activities are mainly located in the Northern Hemisphere, increased CO2 has mainly manifested in these regions. Especially in region 2, with increased CO2 and decreased NPP, increasing downward longwave radiation has heated the ground surface by 2.2 W m−2 and raised surface temperatures by 0.23°C. At the same time, due to the radiative forcing of spatial variations in CO2 concentrations, local dependence of NPP on soil moisture has increased due to enhanced temperature and evapotranspiration coupling, which may improve negative NPP anomalies locally, especially in region 2. With continued increasing CO2 concentrations, its spatial variation due to radiative forcing is likely to amplify warming and have a negative impact on NPP in the terrestrial ecosystem.

Targeting the challenges in the risk analysis of laboratory fire accidents, particularly considering fire accidents in Chinese universities, an integrated approach is proposed with the combination of association rule learning, a Bayesian network (BN), and fuzzy set theory in this study. The proposed approach has the main advantages of deriving conditional probabilities of BN nodes based on historical accident data and association rules (ARs) and making good use of expert elicitation by using an augmented fuzzy set method. In the proposed approach, prior probabilities of the cause nodes are determined based on expert elicitation with the help of an augmented fuzzy set method. The augmented fuzzy set method enables the effective aggregation of expert opinions and helps to reduce subjective bias in expert elicitations. Additionally, an AR algorithm is applied to determine the probabilistic dependency between the BN nodes based on the historical accident data of Chinese universities and further derive conditional probability tables. Finally, the developed fuzzy Bayesian network (FBN) model was employed to identify critical causal factors with respect to laboratory fire accidents in Chinese universities. The obtained results show that H4 (bad safety awareness), O1 (improper storage of hazardous chemicals), E1 (environment with hazardous materials), and M4 (inadequate safety checks) are the four most critical factors inducing laboratory fire accidents.

A key strategy for meeting China’s 2060 carbon neutrality goal and the global 1.5 °C climate goal is to rapidly shift away from unabated coal use. Here, the authors detail how to structure a high-ambition, plant-by-plant coal phaseout in China while balancing multiple national needs.

Manganese deficiency critically impairs the function and stability of photosystem II (PSII) and negatively impacts crop growth and yield. However, the response mechanisms of carbon and nitrogen metabolism to Mn deficiency in different genotypes of maize and the differences in Mn deficiency tolerance are unclear. Herein, three different genotypes of maize seedlings (sensitive genotype: Mo17, tolerant genotype: B73, and B73 × Mo17) were exposed to Mn deficiency treatment for 16 days using liquid culture with different concentrations of MnSO4 [0.00, 2.23, 11.65, and 22.30 mg/L (control)]. We found that complete Mn deficiency significantly reduced maize seedling biomass; negatively affected the photosynthetic and chlorophyll fluorescence parameters; and depressed nitrate reductase, glutamine synthetase, and glutamate synthase activity. This resulted in reduced leaf and root nitrogen uptake, with Mo17 being most severely inhibited. B73 and B73 × Mo17 maintained higher sucrose phosphate synthase and sucrose synthase activities and lower neutral convertase activity compared to Mo17, which resulted in higher accumulation of soluble sugars and sucrose and maintenance of the osmoregulation capacity of leaves, which helped mitigate damage caused by Mn deficiency. The findings revealed the physiological regulation mechanism of carbon and nitrogen metabolism in different genotypes of maize seedlings that resist Mn deficiency stress, providing a theoretical basis for developing high yield and quality.

Abstract Atmospheric carbon dioxide (CO2) would be increasing much more if it were not for terrestrial carbon (C) uptake, fueling the drawdown of atmospheric CO2 in vegetation and soil on decadal to centennial time scales. Here, we used a global Earth system model (BNU‐ESM) with two different CO2 data sets (i.e., uniform CO2 vs. non‐uniform CO2 data sets) to simulate the responses of the C balance, particularly to the non‐uniform CO2 effect. Under future conditions of 2071–2100, accounting for spatial variations of CO2 concentrations resulted in 0.51 Pg C yr−1 or 19% additional global net ecosystem production (NEP) inductions relative to the uniform conditions. The reduction in NEP in the future was mostly caused by the reduction in the Northern Hemisphere, within which summer was the season that accounted for the largest fraction of this reduction. Changes in NEP under future conditions differed largely to those under present conditions, resulting from changes in the circulation caused by the non‐uniform CO2—for example, reductions in evapotranspiration limit water vapor contributions to the lower atmosphere, and substantially diminish convective precipitation, which led to decreased precipitation. Our findings call for more attention to be paid to the influence of spatial variations in CO2 concentration—particularly in the Northern Hemisphere—to better constrain the projected C uptake under future conditions. Also, it highlights the fundamental importance of non‐uniform CO2 in determining the pattern, response, and magnitude of C uptake through to 2100.

The spatiotemporal features of carbon and nitrogen fluxes over China between 1979 and 2015 were simulated by the Atmosphere–Vegetation Interaction Model (AVIM). The carbon fluxes of gross primary production and net primary production captured the distribution pattern in China better than MODIS and TRENDY data. The results for nitrogen deposition and biological nitrogen fixation show the good performance of the AVIM simulation compared with the CMIP6 and CABLE data, with a deposition rate >4 g N m−2 yr−1 in south China. The variation in the gross primary production and net primary production can be up to 300 and 200 g C m−2 yr−1 in south and southeast China, respectively, and there is a discrepancy between the AVIM and the data from MODIS and TRENDY. This shows the difficulty in simulating the carbon flux in a monsoon climate region and the importance of coupling the nitrogen–carbon fluxes. The standard deviation of nitrogen deposition and biological nitrogen fixation is simulated well by the AVIM and there is a large range in nitrogen deposition of 0.8–1.2 g N m−2 yr−1 in south China. The climatological mean of the fluxes performs better than the variation in the standard deviation and anomaly and this variation in the carbon–nitrogen flux is the key to decreasing bias in future modeling studies.

The material mechanical properties and crack propagation behavior of dissimilar metal welded joint (DMWJ) of pressurized water reactor (PWR) was investigated. In this research, the mechanical parameters of the cladding layer materials (304L-SA508) of the DMWJ in PWRs were obtained by the continuous indentation test. Simultaneously, the user-defined (USDFLD) subroutine in ABAQUS was used to establish the heterogeneous materials model of the welded joint. On this basis, the local crack propagation path of DMWJs has been discussed based on the extended finite element method (XFEM). The result indicated that the strength value at the fusion boundary line (FB line) is the largest, and the yield strength reaches 689 MPa. The yield stress values of the cladding metal (304 L) and base metal (SA508) are 371 MPa and 501 MPa, respectively. Affected by the material constraint effect of the DMWJ, the crack will propagate through the FB line when the initial crack is perpendicular to the FB line. And when the initial crack parallels the FB line, the crack will deviate from it. Meanwhile, the crack propagation length is smaller as the initial crack tip is closer to the FB line when the load condition is constant.

Line scan cameras are widely used to acquire pavement images due to their imaging characteristics and low price, but the acquired pavement line array images often have uneven brightness. To eliminate the impact of image greyscale unevenness on subsequent processing, an automatic dodging method is proposed based on mask dodging algorithm. The main idea of the method is to chuck the images into sub-blocks with the approximate greyscale change degree by introducing the cumulative slope conception. The rules to determine the filter size and the parameters required to adjust the sub-block are self-adaptive. The contrast stretching method is improved to make it more suitable for pavement images. The method is compared with other classical dodging algorithms, and the results show that the proposed automatic dodging method is better than others intuitively and quantitatively. The image length has no significant influence on it. Moreover, the crack segmentation results indicate that the proposed dodging method is effective for line array images, and a more accuracy crack segmentation could be achieved if the images preprocessed by the proposed dodging methods.

Purpose This study aimed to detect the association between nitric oxide synthase 3 (NOS3) gene polymorphisms (rs1799983 and rs3918181) and the susceptibility to osteonecrosis of the femoral head (ONFH).Methods Total 88 ONFH patients (55 non-traumatic ONFH and 33 traumatic ONFH) and 90 healthy controls were recruited in this case–control study. Polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP) was adopted for genotyping NOS3 rs1799983 and rs3918181 polymorphisms. χ2 test was used to calculate differences in genotype and allele frequencies of NOS3 gene polymorphisms between the cases and controls. Relative risk of ONFH was represented using odds ratios (ORs) with corresponding 95% confidence intervals (CIs).Results The T allele of the polymorphism rs1799983 showed significantly different frequencies between ONFH patients and control groups (p = .046) and carrying this allele significantly decreased the disease risk (OR = 0.521, 95%CI = 0.272–0.997), especially for non-traumatic ONFH (OR = 0.408, 95%CI = 0.179–0.929, p = .029). But genotype frequencies of the polymorphism rs1799983 had no obvious difference between the compared two groups (p > .05 for all). There was no remarkable association between NOS3 rs3918181 polymorphism and NOFH risk (p > .05 for all).Conclusions NOS3 rs1799983 polymorphism is obviously associated with ONFH and its T allele may be a protective factor against ONFH occurrence in Chinese Han population.

Nitrogen cycling has profound effects on carbon uptake in the terrestrial ecosystem and the response of the biosphere to climate changes. However, nutrient cycling is not taken into account in most land surface models for climate change. In this study, a nitrogen model, based on nitrogen transformation processes and nitrogen fluxes exchange between the atmosphere and terrestrial ecosystem, was incorporated into the Atmosphere–Vegetation Interaction Model (AVIM) to simulate the carbon cycle under nitrogen limitation. This new model, AVIM-CN, was evaluated against site-scale eddy covariance–based measurements of an alpine meadow located at Damxung station from the FLUXNET 2015 dataset. Results showed that the annual mean gross primary production simulated by AVIM-CN (0.7073 gC m−2 d−1) was in better agreement with the corresponding flux data (0.5407 gC m−2 d−1) than the original AVIM (1.1403 gC m−2 d−1) at Damxung station. Similarly, ecosystem respiration was also down-regulated, from 1.7695 gC m−2 d−1 to 1.0572 gC m−2 d−1, after the nitrogen processes were introduced, and the latter was closer to the observed vales (0.8034 gC m−2 d−1). Overall, the new results were more consistent with the daily time series of carbon and energy fluxes of observations compared to the former version without nitrogen dynamics. A model that does not incorporate the limitation effects of nitrogen nutrient availability will probably overestimate carbon fluxes by about 40%.

China’s contribution to global greening is regulated by increasing atmospheric CO2 concentrations, climate change, and land use. Based on TRENDY project data, this study identified that the shifts in China’s contribution to the global leaf area index (LAI) trend strongly reduced during the warming hiatus, translating from 13.42 ± 26.45% during 1982–1998 into 7.91 ± 25.45% during 1999–2012. First, significant negative sensitivities of LAI to enhanced vapor pressure deficit (VPD), when only considering the climate effect derived from TRENDY models in China, were found to have shifted substantially after the late 1990s. However, globally, LAI had positive rather than negative responses to enhanced VPD. These opposing shifts in the response of LAI to enhanced VPD reduced the national contribution to global vegetation greening. Second, shifts in land-use change and their effects on the LAI trends in the two periods in China were accompanied by major changes in land cover and land management intensity, including forestry. Consequently, the contribution of land use in China reduced by −47.68% during the warming hiatus period, as compared with the warming period. Such a shift in the impact of land-use change on LAI simulated by ecosystem models might result from the models’ lack of consideration of conserving and expanding forests with the goal of mitigating climate change for China. Our results highlight the need for ecosystem models to reproduce the enhanced negative impact on global LAI and consider the shifts in man-made adaptation policies (e.g., forest management) to improve terrestrial ecosystem models in the future.

To understand the effect of cold working of welding heat-affected zone on the driving force of the crack growth and crack growth rate of stress corrosion cracking (SCC) near the welding fusion line, the finite element simulation method was used to analyze the effect of cold working on the tensile stress of the crack tip at different locations near the fusion line. On this basis, the strain rate of the crack tip in the Ford-Andresen model is replaced by the creep rate of the crack tip, and the creep rate of the crack tip is used as driving force for the crack growth of SCC. The effect of the cold working level at the heat-affected zone on the driving force of the crack growth and crack growth rate of SCC are analyzed, and driving force of the crack growth and crack growth rate of SCC after one overload was compared.

Abstract Long‐term trend of total cloud cover (TCC) had been studied based on 51 meteorological stations across South China during the period 1960–2012. TCC reduction mainly happened over the past 53 years, and the value of climatic trend rate (CTR) averaged in all stations was − 0.625%·10a−1. The primary cause of the significant reduction of TCC was the temperature (LT) and relative humidity (LRH) in the low troposphere in the context of global warming. Correlation coefficients between TCC and LRH in annual and seasonal mean had all passed 99% significance test, and strong positive correlations indicate that LRH plays a much more important role in the change of TCC in South China.

The slow strain rate tensile test (SSRT) is a common means to investigate stress corrosion cracking (SCC) in key engineering structural materials of light-water reactors, and it is an important task to real-time monitor the crack growing length and rate of the specimen during the test. Because the specimen is placed in an autoclave with high-pressure and high-temperature water environment-simulated light-water reactor, the current potential drop method, which includes current potential drop (DCPD) and alternating current potential drop (ACPD), is the main means to real-time monitor crack growth rate in the SCC test. As a supplementary means to obtain the crack growth rate during the test, the SSRT process of nickel-based Alloy 600 CT specimens is investigated by using the elastic-plastic finite element method (EPFEM) in this paper. Based on the consideration that both the elastic-plastic deformation and crack length of the specimen would affect the relationship between the load and the displacement of the loading point during the SSRT test, the relationship between the loading point displacement caused by crack propagation ΔLc and plastic deformation ΔLp is separated by EPFEM. Then, the SCC crack growth rate and the real-time crack length are obtained. This proposed approach could be used to improve the test results in the SSRT test.

Dynamic plastic deformation (DPD) achieved by multipass hammer forging is one of the most important metal forming operations to create the excellent materials properties. By using the integrated approaches of optical microscope and scanning electron microscope, the forging temperature effects on the multipass hammer forging process and the forged properties of Ti-6Al-4V alloy were evaluated and the forging samples were controlled with a total height reduction of 50% by multipass strikes from 925°C to 1025°C. The results indicate that the forging temperature has a significant effect on morphology and the volume fraction of primary α phase, and the microstructural homogeneity is enhanced after multipass hammer forging. The alloy slip possibility and strain rates could be improved by multipass strikes, but the marginal efficiency decreases with the increased forging temperature. Besides, a forging process with an initial forging temperature a bit above β transformation and finishing the forging a little below the β transformation is suggested to balance the forging deformation resistance and forged mechanical properties.

Hepatocellular carcinoma (HCC) is a typical inflammation-associated cancer. IL-21 regulates both innate and adaptive immune responses and has key roles in antitumor and antiviral responses. However, the role of IL-21 in HCC development is poorly defined. In the current study, we explored the role of IL-21R signaling in HCC growth by using IL-21R knockout mice and HCC mouse models. We discovered that IL-21R signaling deficiency promoted HCC growth in tumor-bearing mice. We showed that IL-21R deletion reduced T cells infiltration and activation as well as their function but increased the accumulation of myeloid-derived suppressor cells in tumor tissues to enhance HCC growth. Furthermore, loss of IL-21R signaling in tumor-bearing mice resulted in an imbalance of the systemic immune system characterized by decreased antitumor immune cells and increased immunosuppressive cells in the spleen and lymph nodes. In addition, we revealed that IL-21R signaling is critical for the expansion of antitumor immune cells in the memory immune response to tumor rechallenge. Finally, we showed that the transcriptional levels of IL-21 in the peritumoral region and IL-21R within the tumor are associated with survival and recurrence of HCC patients. In conclusion, our study demonstrates that IL-21R signaling is essential for controlling the development of HCC and immunological memory response to tumor challenge.

A disaster emergency consists of many unfavorable factors, such as different disaster areas, the limited capacity of the rescue centers, and complex rescue conditions. After taking into account the resources of the rescue centers, the ability of rescue teams, and the distance between the rescue centers and the disaster areas, this paper has established a complex model for multiple centers with limited capacity to dispatch teams for emergencies in different disaster areas. The model is solved by the genetic algorithm. Firstly, the paper takes the rescue task as the subunit to perform integer programming. Secondly, a rule is designed according to the symmetry of parents’ crossing. According to the rule, single parent crossover only allows two situations, (1) different rescue mission for the same rescue center and (2) different rescue centers under the same rescue mission. Finally, the performance of parent crossing and symmetric single parent crossing is compared. The results show that the two algorithms can converge to the optimal solution, but each of them has unique advantages in terms of convergence speed and stability. It is suggested that the strategy of the single-parent crossover should be used to deal with local emergency responses and that the two-parent crossover strategy is be used for more complicated global emergency responses.

Estimating balanced nutrient requirements for soybean (Glycine max [L.] Merr) in China is essential for identifying optimal fertilizer application regimes to increase soybean yield and nutrient use efficiency. We collected datasets from field experiments in major soybean planting regions of China between 2001 and 2015 to assess the relationship between soybean seed yield and nutrient uptake, and to estimate nitrogen (N), phosphorus (P), and potassium (K) requirements for a target yield of soybean using the quantitative evaluation of the fertility of tropical soils (QUEFTS) model. The QUEFTS model predicted a linear-parabolic-plateau curve for the balanced nutrient uptake with a target yield increased from 3.0 to 6.0 t ha-1 and the linear part was continuing until the yield reached about 60-70% of the potential yield. To produce 1000 kg seed of soybean in China, 55.4 kg N, 7.9 kg P, and 20.1 kg K (N:P:K = 7:1:2.5) were required in the above-ground parts, and the corresponding internal efficiencies (IE, kg seed yield per kg nutrient uptake) were 18.1, 126.6, and 49.8 kg seed per kg N, P, and K, respectively. The QUEFTS model also simulated that a balanced N, P, and K removal by seed which were 48.3, 5.9, and 12.2 kg per 1000 kg seed, respectively, accounting for 87.1%, 74.1%, and 60.8% of the total above-ground parts, respectively. These results were conducive to make fertilizer recommendations that improve the seed yield of soybean and avoid excessive or deficient nutrient supplies. Field validation indicated that the QUEFTS model could be used to estimate nutrient requirements which help develop fertilizer recommendations for soybean.

There have been incidents recently where stress corrosion cracking (SCC) observed in the dissimilar metal weld (DMW) joints connecting the reactor pressure vessel (RPV) nozzle with the hot leg pipe. Due to the complex microstructure and mechanical heterogeneity in the weld region, dissimilar metal weld joints are more susceptible to SCC than the bulk steels in the simulated high temperature water environment of pressurized water reactor (PWR). Tensile residual stress (RS), in addition to operating loads, has a great contribution to SCC crack growth. Limited experimental conditions, varied influence factors and diverging experimental data make it difficult to accurately predict the SCC behavior of DMW joints with complex geometry, material configuration, operating loads and crack shape. Based on the film slip/dissolution oxidation model and elastic-plastic finite element method (EPFEM), an approach is developed to quantitatively predict the SCC growth rate of a RPV outlet nozzle DMW joint. Moreover, this approach is expected to be a pre-analytical tool for SCC experiment of DMW joints in PWR primary water environment.

Mechanical harvesting has become inevitable for cotton production in China due to the rising labor cost in the country. It usually requires a moderate plant height and compact plant architecture. Correlation and stepwise regression were employed to analyze databases of our 24 field experiments between 2010 and 2017 in Hebei Province. The purpose is to identify the relationships between plant architecture traits and seed cotton yield within natural plant height range (58.6−163.2 cm) or preferred plant height range (80−120 cm) for mechanical harvesting in the Yellow River Valley of China, and define some important factors affecting seed cotton yield. Under natural plant height range across all experiments, there was a significantly negative correlation (r = −0.452) between plant height and yield. On limited plant height range desired for mechanical harvesting, the degree of this negative correlation decreased to r = −0.366. The correlation of plant height with seed cotton yield varied greatly with year, cultivar, plant density and mepiquat chloride (MC) application. Moreover, stepwise regression analysis picked internode length of the 1st (generally including 1st−7th mainstem node from bottom), 2nd (8th−12th node) and 4th (above 17th node) mainstem section and the length of lower fruiting branch (LFB) as significant factors influencing seed cotton yield under plant height range of 80−120 cm. The results have implications for precise control of cotton plant architecture preferred for mechanized harvesting in China.

Based on the thermohydraulic calculation model verified in this study and Non-dominated Sorted Genetic Algorithm-II (NSGA-II), a multi-objective configuration optimization method is proposed, and the performances of shell-and-tube heat exchanger with disc-and-doughnut baffles (STHX-DDB) and shell-and-tube heat exchanger with segmental baffles (STHX-SB) are compared after optimization. The results show that, except in the high range of heat transfer capacity of 16.5–17 kW, the thermohydraulic performance of STHX-DDB is better. Tube bundle diameter, inside tube bundle diameter, number of baffles of STHX-DDB and tube bundle diameter, baffle cut, number of baffles of STHX-SB are chosen as design parameters, and heat transfer capacity maximization and shell-side pressure drop minimization are considered as common optimization objectives. Three optimal configurations are obtained for STHX-DDB and another three are obtained for STHX-SB. The optimal results show that all the six selected optimal configurations are better than the original configurations. For STHX-DDB and STHX-SB, compared with the original configurations, the heat transfer capacity of optimal configurations increases by 6.26% on average and 5.16%, respectively, while the shell-side pressure drop decreases by 44.33% and 19.16% on average, respectively. It indicates that the optimization method is valid and feasible and can provide a significant reference for shell-and-tube heat exchanger design.

Background: On 23 May 2012, a university in Jiangxi, China reported a gastroenteritis outbreak. We investigated the outbreak to identify the agent, source and mode of transmission and to recommend control measures.Methods: A case was defined as any person from the university with onset of diarrhoea (≥3 times/24h) from 1 to 31 May 2012. Active case finding was conducted by reviewing university hospital and drug-store records and interviewing students, workers and teachers. We then conducted a case-control study in which we compared food, water and environmental exposure history. Water samples were collected and tested.Results: We identified 417 cases – an attack rate (AR) of 4.7% (417/8781) for the university. There were 416 student cases (AR = 5.7%) distributed across all 11 colleges, five of which were more heavily affected (AR range = 5.9%–14%). In the case-control study, cases had higher odds of having drunk bottled water (odds ratio [OR] = 4.1; 95% confidence interval [CI] = 1.7–9.9), and there was a dose–response relationship (X 2 trend = 4.6, P < 0.05). Drinking boiled bottled water was inversely associated with being a case (OR = "0.22," 95% CI = "0.07–0.71)." Eating in any of the three university canteens or drinking water from the city water supply was not associated with being a case. Pathogenic Escherichia coli was isolated from two unopened bottled water specimens and from four student cases.Conclusion: This gastroenteritis outbreak was most likely caused by contaminated bottled water. The company in question has been shut down and no further cases have been reported. Increased regulation of bottled water plants and better coordination between different investigators for future outbreaks is recommended.

As the resistance of structures against the crack-tip plastic deformation, constraints has attracted much attention in the research of material fracture behaviour. In order to increase the accuracy of structural integrity assessment, many characterization parameters of in-plane and out-of-plane constraints have been considered and proposed in the last few decades. Three-dimensional finite element analyses have been conducted for five C(T)50 specimens with different out-of-plane constraint. The distributions of four constraint parameters (σ22/σ0, Tz, h and Dp) along crack fronts were calculated. To characterize the out-of-plane constraint, the capability of constraint parameters such as σ22/σ0, Tz, h and Dp were analyzed and compared. Results show that, compared with the three constraint parameters (σ22/σ0, Tz and h) based on crack-tip stress fields, the parameter Dp based on crack-tip equivalent plastic strain is more sensitive to out-of-plane constraint, and may effectively characterize the out-of-plane constraint.

A series of aluminum hypophosphite (AHPi)/graphite-like carbon nitride (g-C3N4) (designated as CAHPi) hybrids were prepared, followed by incorporation into thermoplastic polyurethane (TPU). The introduction of CAHPi hybrids into TPU led to a marked reduction in the peak of the heat release rate (pHRR), total heat release, weight loss rate, smoke production rate and total smoke production (TSP). For instance, pHRR and TSP decreased by 40% and 50% for TPU/CAHPi20. Furthermore, the increasing fire growth index and decreasing fire performance index were obtained for TPU/CAHPi systems, suggesting reduced fire hazards. It was found that improved fire safety of TPU nanocomposites was contributed by condensed phase and gas phase mechanisms. On one hand, g-C3N4 accelerated the thermal decomposition of AHPi for the formation of more char layers. On the other hand, g-C3N4 induced AHPi to generate more free radical capture agents when exposed to flame, besides protecting AHPi against thermal oxidation.