In situ growth of cobalt on ultrathin Ti_(3)C_(2)T_(x)as an efficient cocatalyst of g-C_(3)N_(4)for enhanced photocatalytic CO_(2)reduction

Photocatalytic CO_(2)reduction to valuable product exhibit promising prospect for solving the energy crisis and the greenhouse effect.Herein,Co-Ti_(3)C_(2)T_(x)/g-C_(3)N_(4)(Co-TC/CN)composite with enhanced photocatalytic performance for converting CO_(2)to CO and CH_(4)was constructed by electrostatic self-assembly method.The close contact interface between Co-Ti_(3)C_(2)T_(x)and g-C_(3)N_(4)nanosheets can be used as fast transport channels of photogenerated electrons and effectively promote the separation of photogenerated electrons and holes,and the interface between the Co and Ti_(3)C_(2)T_(x)might be the active sites for CO_(2)adsorption and activation.The optimized Co-Ti_(3)C_(2)T_(x)/g-C_(3)N_(4)composite exhibited the highest photocatalytic performance with the CO and CH_(4)production of 55.04 μmol·g^(-1)and 2.29 μmol·g^(-1),respectively,which were 7.5 times and 5.8 times than those of g-C_(3)N_(4).Furthermore,the stability of g-C_(3)N_(4)was improved after coupling with Co-Ti_(3)C_(2)T_(x).

Dilemma and Solution of Green Transportation Construction under the Background of Urban Development

With the development of the city and the increase of the population, the demand for transportation is increasing. The increases in transportation ways and demand have also brought certain energy and environmental problems to transportation construction. A good transportation environment and green travel experience have an important role in promoting the happiness of urban life and the sustainable development of society. Based on this, the following solutions are proposed for the construction and development of urban green transportation. First, as a guiding role, the government should formulate active transportation and green transportation policies to promote the reform of multiple public transportation methods. Second, as a leading role, the market can support a variety of the construction of green travel modes, which could encourage the development of shared bicycles and new energy vehicles. Third, as the main role of city, the citizens would like to choose green travel tools with the guidance in the conscious level. If we built green behavior into a fashionable business card of the city, green behavior will lead the city’s transportation construction and development.

Detection and quantification of entanglement with measurement-device-independent and universal entanglement witness

Entanglement is the key resource in quantum information processing,and an entanglement witness(EW)is designed to detect whether a quantum system has any entanglement.However,prior knowledge of the target states should be known first to design a suitable EW,which weakens this method.Nevertheless,a recent theory shows that it is possible to design a universal entanglement witness(UEW)to detect negative-partial-transpose(NPT)entanglement in unknown bipartite states with measurement-device-independent(MDI)characteristic.The outcome of a UEW can also be upgraded to be an entanglement measure.In this study,we experimentally design and realize an MDI UEW for two-qubit entangled states.All of the tested states are well-detected without any prior knowledge.We also show that it is able to quantify entanglement by comparing it with concurrence estimated through state tomography.The relation between them is also revealed.The entire experimental framework ensures that the UEW is MDI.

Entanglement quantification via weak measurements assisted by deep learning

Entanglement has been recognized as being crucial when implementing various quantum information tasks.Nevertheless, quantifying entanglement for an unknown quantum state requires nonphysical operations or post-processing measurement data. For example, evaluation methods via quantum state tomography require vast amounts of measurement data and likely estimation.

Neutralization of interleukin-17A alleviates burn-induced intestinal barrier disruption via reducing pro-inflammatory cytokines in a mouse model

Background:The intestinal barrier integrity can be disrupted due to burn injury,which is responsible for local and systemic inflammatory responses.Anti-inflammation strategy is one of the proposed therapeutic approaches to control inflammatory cascade at an early stage.Interleukin-17A(IL-17A)plays a critical role in inflammatory diseases.However,the role of IL-17A in the progression of burn-induced intestinal inflammation is poorly understood.In this study,we aimed to investigate the effect of IL-17A and associated pro-inflammatory cytokines that were deeply involved in the pathogenesis of burn-induced intestinal inflammatory injury,and furthermore,we sought to determine the early source of IL-17A in the intestine.Methods:Mouse burn model was successfully established with infliction of 30%total body surface area scald burn.The histopathological manifestation,intestinal permeability,zonula occludens-1 expression,pro-inflammatory cytokines were determined with or without IL-17A-neutralization.Flow cytometry was used to detect the major source of IL-17A^(+)cells in the intestine.Results:Burn caused intestinal barrier damage,increase of intestinal permeability,alteration of zonula occludens-1 expressions,elevation of IL-17A,IL-6,IL-1βand tumor necrosis factor-α(TNF-α),whereas IL-17A neutralization dramatically alleviated burn-induced intestinal barrier disruption,maintained zonula occludens-1 expression,and noticeably,inhibited pro-inflammatory cytokines elevation.In addition,we observed that the proportion of intestinal IL-17A^(+)Vγ4^(+)T subtype cells(but not IL-17A^(+)Vγ1^(+)T subtype cells)were increased in burn group,and neutralization of IL-17A suppressed this increase.Conclusions:The main original findings of this study are intestinal mucosa barrier is disrupted after burn through affecting the expression of pro-inflammatory cytokines,and a protective role of IL-17A neutralization for intestinal mucosa barrier is determined.Furthermore,Vγ4^(+)T cells are identified as the major early producers of IL-17A that orchestrate an inflammatory response in the burn model.These data suggest that IL-17A blockage may provide a unique target for therapeutic intervention to treat intestinal insult after burn.

Prediction of sepsis in trauma patients

Trauma is one of the leading causes of death worldwide. Approximately 39.5% of deaths occur in the hospital, and the mortality rate of delayed death caused by septic complications is still high. Early prediction of the development of sepsis can help promote early intervention and treatment for patients and contribute to improving patient outcomes. Thus so far, biomarkers, patient demo-graphics and injury characteristics are the main methods used for predicting sepsis in trauma patients. However, studies that verify their predictive value are limited, and the results are still controversial. More work should be conducted to explore more efcient and accurate ways to predict post-traumatic sepsis.

Discovery method for distributed denial-of-service attack behavior in SDNs using a feature-pattern graph model

The security threats to software-defined networks(SDNs)have become a significant problem,generally because of the open framework of SDNs.Among all the threats,distributed denial-of-service(DDoS)attacks can have a devastating impact on the network.We propose a method to discover DDoS attack behaviors in SDNs using a feature-pattern graph model.The feature-pattern graph model presented employs network patterns as nodes and similarity as weighted links;it can demonstrate not only the traffc header information but also the relationships among all the network patterns.The similarity between nodes is modeled by metric learning and the Mahalanobis distance.The proposed method can discover DDoS attacks using a graph-based neighborhood classification method;it is capable of automatically finding unknown attacks and is scalable by inserting new nodes to the graph model via local or global updates.Experiments on two datasets prove the feasibility of the proposed method for attack behavior discovery and graph update tasks,and demonstrate that the graph-based method to discover DDoS attack behaviors substantially outperforms the methods compared herein.

Genome Assembly and Population Resequencing Reveal the Geographical Divergence of Shanmei(Rubus corchorifolius)

Rubus corchorifolius(Shanmei or mountain berry,2n=14)is widely distributed in China,and its fruits possess high nutritional and medicinal values.Here,we reported a highquality chromosome-scale genome assembly of Shanmei,with contig size of 215.69 Mb and 26,696 genes.Genome comparison among Rosaceae species showed that Shanmei and Fupenzi(Rubus chingii Hu)were most closely related,followed by blackberry(Rubus occidentalis),and that environmental adaptation-related genes were expanded in the Shanmei genome.Further resequencing of 101 samples of Shanmei collected from four regions in the provinces of Yunnan,Hunan,Jiangxi,and Sichuan in China revealed that among these samples,the Hunan population of Shanmei possessed the highest diversity and represented the more ancestral population.Moreover,the Yunnan population underwent strong selection based on the nucleotide diversity,linkage disequilibrium,and historical effective population size analyses.Furthermore,genes from candidate genomic regions that showed strong divergence were significantly enriched in the flavonoid biosynthesis and plant hormone signal transduction pathways,indicating the genetic basis of adaptation of Shanmei to the local environment.The high-quality assembled genome and the variome dataset of Shanmei provide valuable resources for breeding applications and for elucidating the genome evolution and ecological adaptation of Rubus species.