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With the improvement of aircraft flight speed, bird impact is easy to cause serious accidents such as windshield breakdown, aircraft destruction and human death. In order to improve the bird impact resistance of aircraft windshield glass, the dynamic response of windshield glass (YB-3 plexiglass) after bird impact of small general-purpose aircraft flying at cruise speed was studied. By establishing the bird impact windshield glass model and adopting the fixed restraint mode around, the windshield glass is impacted at the speeds of 200km/h, 220km/h and 250km/h and the angles of 30°, 60° and 90°, respectively. The changes of stress-strain, displacement and energy absorption of the windshield glass under the impact of bird body, as well as the effects of different impact speeds and impact angles on the dynamic response of the glass are analyzed. It is found that during the whole impact process, the stress and strain of YB-3 plexiglass will reach the peak in a short time, then oscillate back and forth in a period of time, and the final residual deformation is small. With the increase of impact velocity, the stress, strain and displacement of glass will increase accordingly; With the increase of the impact angle, the energy absorbed by the windshield glass decreases accordingly, and the damage and deformation around the impact point are reduced. By studying the bird impact of the windshield of small general-purpose aircraft, it provides a theoretical basis for the airworthiness certification of general-purpose aircraft and the design optimization of windshield glass.

As a new generative model, the generative adversarial network (GAN) has great potential in the accuracy and efficiency of generating pseudoreal data. Nowadays, bearing fault diagnosis based on machine learning usually needs sufficient data. If enough near-real data can be generated in the case of insufficient samples in the actual operating condition, the effect of fault diagnosis will be greatly improved. In this study, a new rolling bearing data generation method based on the generative adversarial network (GAN) is proposed, which can be trained adversarially and jointly via a learned embedding, and applied to solve fault diagnosis problems with insufficient data. By analyzing the time-domain characteristics of rolling bearing life cycle monitoring data in actual working conditions, the operation data are divided into three periods, and the construction and training of the generative adversarial network model are carried out. Data generated by adversarial are compared with the real data in the time domain and frequency domain, respectively, and the similarity between the generated data and the real data is verified.

Although researchers have previously examined whether graphene modified by sulfur can improve the electrochemical performance of LiFePO4/C composites, they have rarely examined whether it can do so during the synchronous synthesis of LiFePO4/C and sulfur-modified reduced graphene oxide (SG) via a one-step hydrothermal method. To answer this question, a series of olivine structure LiFePO4/C composites wrapped with SG were investigated. Subsequently, we found that SG can form a three-dimensional conductive network on the surface of the LiFePO4/C sample. In the process, XRD and HRTEM tests were undertaken as well. From the XRD test, the results show that SG does not affect the olivine structure of LiFePO4/C. In the HRTEM experiment, clear lattice fringes and a uniformly coated carbon layer on the sample surface were observed. Alongside these results, there were 4 others. First, the charge–discharge data showed that the electrochemical performance of the samples could be increased by SG modification. Second, sample S2 with a mass ratio of Na2S to rGO of 1:10 shows the best specific discharge capacity and stability. Third, the specific capacity of S2 is 163 mAhg−1 at 0.2 C, and the capacity retention is 108.23% even after 200 cycles at a magnification of 10 C. Fourth, according to EIS, the charge migrating resistance of S2 is 226.4 Ω, and the lithium-ion diffusion coefficient is 2.41 × 10−14 cm2·S−1. The significance of these results is that they indicate that wrapping LiFePO4/C with SG significantly contributed to the improvement of its electrochemical performance.

The gene family protein phosphatase 2C (PP2C) is related to developmental processes and stress responses in plants. Barley (Hordeum vulgare L.) is a popular cereal crop that is primarily utilized for human consumption and nutrition. However, there is little knowledge regarding the PP2C gene family in barley. In this study, a total of 1635 PP2C genes were identified in 20 barley pan-genome accessions. Then, chromosome localization, physical and chemical feature predictions and subcellular localization were systematically analyzed. One wild barley accession (B1K-04-12) and one cultivated barley (Morex) were chosen as representatives to further analyze and compare the differences in HvPP2Cs between wild and cultivated barley. Phylogenetic analysis showed that these HvPP2Cs were divided into 12 subgroups. Additionally, gene structure, conserved domain and motif, gene duplication event detection, interaction networks and gene expression profiles were analyzed in accessions Morex and B1K-04-12. In addition, qRT-PCR experiments in Morex indicated that seven HvMorexPP2C genes were involved in the response to aluminum and low pH stresses. Finally, a series of positively selected homologous genes were identified between wild accession B1K-04-12 and another 14 cultivated materials, indicating that these genes are important during barley domestication. This work provides a global overview of the putative physiological and biological functions of PP2C genes in barley. We provide a broad framework for understanding the domestication- and evolutionary-induced changes in PP2C genes between wild and cultivated barley.

LiFePO4 modified by N-doped graphene (NG) with a three-dimensional conductive network structure was synthesized via a one-step in situ hydrothermal method. The effects of N amount of NG on the phase structure, morphology, and electrochemical properties of LiFePO4 are investigated in this study. X-ray diffraction (XRD) results show that doping suitable N amounts in NG do not alter the crystal structure of LiFePO4, and scanning electron microscopy (SEM) images show that NG can slightly reduce the particle size of LiFePO4. The high-resolution transmission electron microscopy (HRTEM) results show that the LiFePO4 particles are well covered and connected by NG. The electrochemical performance confirms that LiFePO4 modified by 20% N-doped graphene (named LFP/NG-4) displays a perfect specific capacity of 166.6 mAh·g−1 at a rate of 0.2C and can reach 125 mAh·g−1 at a rate of 5 C. Electrochemical impedance spectroscopy (EIS) results illustrate that the charge transfer resistance value of the LFP/NG-4 composite is only 58.6 Ω, which is very low compared with LiFePO4. Cyclic voltammetry (CV) tests indicate that the addition of 20% N-doped graphene can effectively reduce electrode polarization and improve reversibility. The LFP/NG-4 composite with a three-dimensional conductive network structure can be regarded as a promising cathode material for Li-ion batteries.

Purpose Pulmonary fibrosis (PF) is a common clinical disease, which results in serious respiratory impairment. Xin Jia Xuan Bai Cheng Qi Decoction (XJXBCQ) is a traditional prescription commonly used in treating lung diseases. We investigate the effect of XJXBCQ against PF and its mechanism via the regulation of TGF-β1/Smad in vitro and in vivo.

Automatically generating an accurate and meaningful description of an image is very challenging. However, the recent scheme of generating an image caption by maximizing the likelihood of target sentences lacks the capacity of recognizing the human-object interaction (HOI) and semantic relationship between HOIs and scenes, which are the essential parts of an image caption. This article proposes a novel two-phase framework to generate an image caption by addressing the above challenges: 1) a hybrid deep learning and 2) an image description generation. In the hybrid deep-learning phase, a novel factored three-way interaction machine was proposed to learn the relational features of the human-object pairs hierarchically. In this way, the image recognition problem is transformed into a latent structured labeling task. In the image description generation phase, a lexicalized probabilistic context-free tree growing scheme is innovatively integrated with a description generator to transform the descriptions generation task into a syntactic-tree generation process. Extensively comparing state-of-the-art image captioning methods on benchmark datasets, we demonstrated that our proposed framework outperformed the existing captioning methods in different ways, such as significantly improving the performance of the HOI and relationships between HOIs and scenes (RHIS) predictions, and quality of generated image captions in a semantically and structurally coherent manner.\enlargethispage-8pt.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. The type-1 ordered weighted averaging (T1OWA) operator has demonstrated the capacity for directly aggregating multiple sources of linguistic information modeled by fuzzy sets rather than crisp values. Yager's ordered weighted averaging (OWA) operators possess the properties of idempotence, monotonicity, compensativeness, and commutativity . This article aims to address whether or not T1OWA operators possess these properties when the inputs and associated weights are fuzzy sets instead of crisp numbers. To this end, a partially ordered relation of fuzzy sets is defined based on the fuzzy maximum ( join ) and fuzzy minimum ( meet ) operators of fuzzy sets, and an alpha-equivalently-ordered relation of groups of fuzzy sets is proposed. Moreover, as the extension of orness and andness of an Yager's OWA operator, joinness and meetness of a T1OWA operator are formalized, respectively. Then, based on these concepts and the representation theorem of T1OWA operators , we prove that T1OWA operators hold the same properties as Yager's OWA operators possess, i.e., idempotence, monotonicity, compensativeness, and commutativity . Various numerical examples and a case study of diabetes diagnosis are provided to validate the theoretical analyses of these properties in aggregating multiple sources of uncertain information and improving integrated diagnosis, respectively.

Objective To investigate the efficacy of poly (lactic acid co castor oil) microspheres containing ropivacaine for sciatic nerve block of mice. Methods A total of 150 Kunming male mice were randomly assigned into 3 groups, namely placebo microspheres (lactic acid co castor oil) group (group A, n=50), ropivacaine injection group (group B, n=50) and ropivacaine microspheres group (group C, n=50). After sevoflurane anesthesia, the mouse was fixed on the operating table and the bilateral sciatic nerve was exposed. The corresponding preparations were implanted or injected near the sciatic nerve. Five mice were randomly selected from each group for the next experiments. Paw withdrawal thermal latency, the ability to splay and flex of the hind paw and plasma ropivacaine concentration were measured 10min, 30min, 1h, 3h, 5h, 7h, 10h, 15h, 30h and 48h after drug administration. Results The anesthetic effect of group C began to work at 3h. Compared with group B, the duration of sciatic nerve sensory block of group C was significantly longer and the effect of motor block was weaker. No anesthetic effect was observed in group A. The sensory and motor block of group B reached the peak at 1h, and the pharmacodynamics subsided at 7h. Compared with group B, the concentration of ropivacaine in group C increased slowly, and the peak value at 10h after administration was gradually decreased. Conclusions Ropivacaine loading poly (lactic acid co castor oil) microspheres can significantly extend the effect of ropivacaine on sciatic nerve sensory block. Compared with ropivacaine injection, motor block effect of ropivacaine loading poly (lactic acid co castor oil) microspheres is reduced and its plasma ropivacaine concentration fluctuation range is small. DOI: 10.11855/j.issn.0577-7402.2018.04.06

(1) Background: We aimed to develop a transparent machine-learning (ML) framework to automatically identify patients with a condition from electronic health records (EHRs) via a parsimonious set of features. (2) Methods: We linked multiple sources of EHRs, including 917,496,869 primary care records and 40,656,805 secondary care records and 694,954 records from specialist surgeries between 2002 and 2012, to generate a unique dataset. Then, we treated patient identification as a problem of text classification and proposed a transparent disease-phenotyping framework. This framework comprises a generation of patient representation, feature selection, and optimal phenotyping algorithm development to tackle the imbalanced nature of the data. This framework was extensively evaluated by identifying rheumatoid arthritis (RA) and ankylosing spondylitis (AS). (3) Results: Being applied to the linked dataset of 9657 patients with 1484 cases of rheumatoid arthritis (RA) and 204 cases of ankylosing spondylitis (AS), this framework achieved accuracy and positive predictive values of 86.19% and 88.46%, respectively, for RA and 99.23% and 97.75% for AS, comparable with expert knowledge-driven methods. (4) Conclusions: This framework could potentially be used as an efficient tool for identifying patients with a condition of interest from EHRs, helping clinicians in clinical decision-support process.

Firstly, a numerical computation model of submarine radiation noise was established to obtain the radiation noise of the submarine, which was compared with the experimental results, thus verifying the validity of the model. As indicated by the computational result, the submarine fairwater played a significant impact on radiation noise at the front section, whose structure was therefore necessary to be studied. In the paper, there were several different type submarine fairwaters. Large eddy simulation (LES) and boundary element method (BEM) were applied to conduct the numerical computation for the vortex flow field and acoustic characteristics of the original fairwater, the fairwater with fillet and the streamline fairwater. Furthermore, the impact and suppression effect of the fairwater’s type on wall pressure fluctuations and flow-induced noise were analyzed. As shown from the research, the vertical fairwater with fillet or the streamline fairwater can significantly improve the flow quality, thus considerably reducing the pressure fluctuations and flow-induced noise. The paper is conductive to the academic research of flow noise of submarine as well as the new submarine design in the future.

Plant specific NAC (NAM, ATAF1/2 and CUC2) transcription factors (TFs) play important roles in response to abiotic stress. In this study, we identified and characterized a NAC protein, ThNAC7, from Tamarix hispida. ThNAC7 is a nuclear localized protein and has transcriptional activation activity. ThNAC7 expression was markedly induced by salt and osmotic stresses. Transiently transformed T. hispida seedlings overexpressing ThNAC7 (OE) or with RNA interference (RNAi) silenced ThNAC7 were generated to investigate abiotic stress tolerance via the gain- and loss- of function. Overexpressing ThNAC7 showed an increased reactive oxygen species (ROS) scavenging capabilities and proline content, which was accomplished by enhancing the activities of superoxide dismutase (SOD) and peroxidase (POD) in transiently transformed T. hispida and stably transformed Arabidopsis plants. Additionally, ThNAC7 activated these physiological changes by regulating the transcription level of P5CS, SOD and POD genes. RNA-sequencing (RNA-seq) comparison between wild-type and ThNAC7-transformed Arabidopsis showed that more than 40 known salt tolerance genes might regulated by ThNAC7, including stress tolerance-related genes and TF genes. The results indicated that ThNAC7 induces the transcription level of genes associated with stress tolerance to enhance salt and osmotic stress tolerance via an increase in osmotic potential and enhanced ROS scavenging.

In kinesin-3, the coiled-coil 1 (CC1) can sequester the preceding neck coil (NC) for autoinhibition, but the underlying mechanism is poorly understood. Here, we determined the structures of the uninhibited motor domain (MD)-NC dimer and inhibited MD-NC-CC1 monomer of kinesin-3 KIF13B. In the MD-NC-CC1 monomer, CC1 is broken into two short helices that unexpectedly interact with both the NC and the MD. Compared with the MD-NC dimer, the CC1-mediated integration of NC and MD not only blocks the NC dimer formation, but also prevents the neck linker (NL) undocking and the ADP release from the MD. Mutations of the essential residues in the interdomain interaction interface in the MD-NC-CC1 monomer restored the MD activity. Thus, CC1 fastens the neck domain and MD and inhibits both NC and NL. This CC1-mediated lockdown of the entire neck domain may represent a paradigm for kinesin autoinhibition that could be applicable to other kinesin-3 motors.

Data integrity validation is considered to be an important tool to solve the problem that cloud subscribers cannot accurately know whether there are non-subjective changes in the data they upload to cloud servers. In this paper, a data integrity verification model based on dynamic successor tree index structure, Bloom filter and Merkle tree is proposed. The block labels generated according to the features of the dynamic successor tree index structure can sense whether changes have been made to the user's data, while the Merkle tree can track the cha*nged data blocks, enabling the user to effectively verify the integrity of the data stored in the cloud server and provide more effective protection for data.

Summary SUN proteins are the core components of LINC complexes that span across the nuclear envelope for nuclear positioning and migration. SUN proteins contain at least one predicted coiled-coil domain preceding the SUN domain. Here, we found that the two coiled-coil domains (CC1 and CC2) of SUN2 exhibit distinct oligomeric states. CC2 is a monomer in solution. The structure of the CC2-SUN monomer revealed that CC2 unexpectedly folds as a three-helix bundle that interacts with the SUN domain and locks it in an inactive conformation. In contrast, CC1 is a trimer. The structure of the CC1 trimer demonstrated that CC1 is an imperfect coiled coil for the trimerization and activation of the SUN domain. Modulations of CC1 and CC2 dictate different oligomeric states of CC1-CC2-SUN, which is essential for LINC complex formation. Thus, the two coiled-coil domains of SUN2 act as the intrinsic dynamic regulators for controlling the SUN domain activity.

With the continuous development of society, maintenance work has been paid more and more attention in the production field. As one of the indispensable components of many production equipment, the gear reducer can effectively guarantee the safe operation state and maximize the efficiency of the production process through preventive maintenance. This paper constructs a preventive maintenance strategy for gear reduction gearboxes through the analysis of preventive maintenance decisions. Compare the two methods of regular maintenance and sequential maintenance to determine a more practical method. Then the method is verified by an example and the conclusion is drawn.

The recycling of quadrotor drones is a very important process in the execution of the mission. Traditional navigation devices such as GPS and inertial navigation are limited in many casesComplete the safety landing assessment of the four-rotor UAV. The main work is as follows: First Find relevant information to understand the development history of the four-rotor UAV and the risk of the safe landing of the four-rotor UAV and the factors affecting the landing of the four-rotor UAV, and Analyze the structure, flight principle and operation mode of the quadrotor UAV, establish the ground coordinate system and the fuselage coordinate system.Then Propose he conditions that the four-rotor UAV can land safely and the safety landing assessment method of the quadrotor UAV, and obtain the probability formula for the safe landing of the quadrotor UAV. Designing the ground environment of the landing surface of the quadrotor UAV, simulation experiments, and the probability that the four-rotor UAV will land safely in this environment.

Purpose Pulmonary fibrosis (PF) is a common clinical disease, which results in serious respiratory impairment. Xin Jia Xuan Bai Cheng Qi Decoction (XJXBCQ) is a traditional prescription commonly used in treating lung diseases. We investigate the effect of XJXBCQ against PF and its mechanism via the regulation of TGF-β1/Smad in vitro and in vivo. Materials and methods XJXBCQ was first extracted and probed for chemical characterization. An PF model in vitro and in vivo was established in rats and in MRC-5 cells. In bleomycin (BLM)-induced rats model, lung function such as peak expiratory flow (PEF), minute ventilation (MV) and hydroxyproline (HYP) were measured; histopathological changes of lung tissue and TGF-β1 in peripheral blood of rats were detected. TGF-β receptor, Smad2 and its phosphorylation expression were tested by Western blot assay in rats model. Then the effects of XJXBCQ on TGF-β1/Smad signal pathway were assessed by Western blot analysis in vitro, and IL-17A and IL-25 levels were evaluated by ELISA in vivo. Results Our results showed that XJXBCQ significantly enhanced the lung functions, such as PEF, MV and HYP, by reducing the expression level of lung inflammatory cytokine and the content and fibrosis of lung collagen. Moreover, XJXBCQ effectively inhibited TGF-β1, Smad2 and its phosphorylation expression, and the activation of Smad7 in vitro and in vivo. Furthermore, XJXBCQ had an inhibitory effect on the α-smooth muscle actin (α-SMA) and fibronectin (Fn) in vitro and downregulated IL-17A and IL-25 by inhibiting the activation of TGF-β1/Smad signaling pathway in vitro and in vivo. Further, XJXBCQ effectively inhibitied ventilation volume and peak expiratory content remodeling and hydroxyproline content through inhibition of TGF-βRⅡ, Smad2 and its phosphorylation expression, and activation of Smad7 in vivo. Conclusion XJXBCQ extract had an anti-PF effect in vitro and in vivo, which could be attributed to the inhibition of the expression of p-Smad2 and increase in the expression of Smad7 by regulating the TGF-β1/Smad activity.

Background Polypharmacy presents a serious and significant public health challenge as average lifespans increase. The objective of this study was to identify patterns of polypharmacy before dementia diagnosis, their prevalence, and possible complications. Methods We used electronic health records in the Welsh general practitioners’ database from 1990 to 2015, via the Secure Anonymised Information Linkage Databank. Cohort selection, based on a previously validated phenotype, was done with the use of Read Codes to identify any dementia diagnosis within the dataset. No age restriction was applied, but complete data for each patient was required. Analysis was stratified by sex and age, but not dementia type. Medications were identified by Read Codes, and split into four 5-year sub-periods. Factor analysis was used for patients taking at least three medicines in each period. Findings We identified 33 451 patients with a dementia diagnosis from more than 42 million rows of health records. 22 011 (65·8%) patients in the cohort were female, with mean age at dementia diagnosis of 72·75 years (SD 13·59). In sub-period 1 (0–5 years pre-diagnosis), 22 157 (82·2%) of 26 968 patients were taking three or more medications, and three clusters were identified: medicines for urinary or respiratory infections, arthritis or rheumatism, and heart disease (17 947 [66·5%] patients); medicines for urinary or respiratory infections, arthritis or rheumatism, heart disease, and depression (5938 [22·0%]); and medicines for osteoarthritis (701 [2·6%]). By contrast, in sub-period 4 (15–20 years pre-diagnosis), 421 (5·5%) of 7660 patients were taking three or more medications, and five patterns emerged: medicines for infections, arthropathy, and cardiovascular disease (421 [5·5%] patients); medicines for anxiety and acute respiratory infection (184 [2·4%]); medicines for acute respiratory infection and cardiovascular disease (161 [2·1%]); medicines for dermatological disease (23 [0·3%]); and medicines for asthma and other acute respiratory infections (four [0·1%]). 23 891 (71·4%) patients in all periods took medications for arthritis, heart disease, and infections, with or without medications for mental health. Interpretation The earlier before dementia diagnosis, the greater the number of medicine clusters are observed, with lower prevalence of each cluster. Understanding how dementia medicines interact and cause complications with other groups of medicines is fundamental. These patterns can inform safe prescribing practices before diagnosis in selecting medicines with a low anticholinergic burden to minimise their effect on cognitive impairments. Further analysis of these types of polypharmacy among people without dementia will be done in the future. Funding Health Data Research UK (NIWA1).

Interaction between wage and economic growth is a very complex process. Scholars have different understandings about the relationship between the two. Some studies find a positive correlation between wage and economic growth, while others find negative correlations. Based on a multi-agent simulation model of the economic growth, we design a wage distribution mechanism to simulate the impact of wage distribution on economic cycles. It is found that there is an inherent relationship between economic growth cycles and the ratio of minimum wage to average wage. Through the empirical analysis using data from the United States between 1982 and 2013, existence of this relationship is confirmed. Understanding such inherent relationship may provide some insights for government to adjust minimum wage according to the pattern of economic cycles, optimize labor and social security policies, and to promote economic growth.

Data exchange (load transfer) between boundaries is a key technique in multi-physics coupling numerical simulation. Based on the relationships of point and triangle in unstructured grids, an improved data exchange algorithm, namely Unstructured Panel Inside Projective Constant-Volume Tetrahedron (UPIPCVT), is proposed for higher precision. Furthermore, the achieved data of target point is calculated by tri-linear interpolation function in the projective panel, so that it makes the computation more simple. Examples show that UPIPCVT shows a good precision and computation efficiency in data exchange.

Disposition effect, which refers to investors’ being reluctant to realize losses, is very common in financial markets, especially in mainland China. This paper introduces the disposition effect into a multi-agent model, to research investor behavior and its impact on financial markets. As the result of computer simulation, disposition effect reveals asymmetric volatility which reflects the actual situation in mainland China market, i.e. the impact of bad news on volatility is greater than the impact of good news of the same magnitude. Sensitivity analysis shows that investors’ disposition behaviour slows the release rate of news, makes market more stable around the fundamental price. Meanwhile, proper level of disposition effect can avoid some loss in investment, and make chartist get relative higher return than usual. These conclusions could hopefully offer insights and effective support for investment decision-making and policy regulation.

The robust designs of broadband extreme ultraviolet multilayers based on the multiobjective genetic algorithm are validated experimentally. In order to reduce the influence of random layer thickness fluctuations on the great deformation of the experimental reflection of extreme ultraviolet multilayer with a wide angular band, the multiobjective genetic algorithm has been improved to optimize the multilayer system composed by the layer thicknesses which can be controlled precisely. The robust designs of broadband Mo/Si multilayers were fabricated, and the experimental results were presented and analyzed, and then the advantage of robust multilayer designs was demonstrated.The robust designs of broadband extreme ultraviolet multilayers based on the multiobjective genetic algorithm are validated experimentally. In order to reduce the influence of random layer thickness fluctuations on the great deformation of the experimental reflection of extreme ultraviolet multilayer with a wide angular band, the multiobjective genetic algorithm has been improved to optimize the multilayer system composed by the layer thicknesses which can be controlled precisely. The robust designs of broadband Mo/Si multilayers were fabricated, and the experimental results were presented and analyzed, and then the advantage of robust multilayer designs was demonstrated.

Background Early prediction of the outcomes of dementia is important and challenging. This study aimed to identify influential predictors from primary care electronic health records that can robustly predict whether patients with dementia will be admitted to hospital or remain under GP care. Methods Health records of patients with dementia were collected from general practice (GP) and hospital data in Wales between 1980 and 2015. These records were linked at individual patient level via the Secure Anonymised Information Linkage databank. The GP records of each patient were selected 1 year before diagnosis up to hospital admission. An artificial intelligence technique, neural network with entropy regularisation (a multilayer feedforward neural network whose weights between input layer and the first hidden layer were regularised by an entropy metric into the fitness function during training process) was used to automatically identify the most influential predictors from initial GP read codes, sex, and age. 10-fold cross validation was used to assess the predictive performance of the identified signals. Findings 52·5 million individual records of 59 298 patients (20 674 men, 38 624 women) with dementia were used. 30 178 were admitted to hospital and 29 120 remained with GP care. More men were admitted to hospital than stayed with GP care (11 233 vs 9441), whereas more women stayed with GP care than were admitted (19 679 vs 18 945). From the 54 649 initial event codes, the ten most important signals identified for admission for dementia were two diagnostic events (nightmares, essential hypertension), five medication events (betahistine dihydrochloride, ibuprofen gel, simvastatin, influenza vaccine, calcium carbonate and colecalciferol chewable tablets), and three procedural events (third party encounter, social group 3—skilled, blood glucose raised). They performed significantly above chance to predict admission to hospital with sensitivity of 0·758 (95% CI 0·731–0·785), specificity 0·759 (0·71–0·808), precision 0·766 (0·735–0·797), and negative predictive value 0·751 (0·741–0·761). Linear regression with all raw features yielded values of 0·286 (0·26–0·313), 0·804 (0·792–0·816), 0·487 (0·463–0·511), and 0·633 (0·615–0·651), respectively, and with ten identified features yielded values of 0·684 (0·679–0·691), 0·712 (0·705–0·718), 0·747 (0·738–0·754), and 0·644 (0·64–0·651). Interpretation Outperforming traditional methods, the artificial intelligence technique provides an effective means of identifying influential clinical signals to predict hospital admission of patients with dementia significantly above chance. Funding Health Data Research UK Wales and Northern Ireland Site, National Centre for Population Health and Wellbeing Research (CA02), Major Project of National Social Science Foundation of China (16ZDA0092), Guangxi University Digital ASEAN Cloud Big Data Security and Mining Technology Innovation Team.

Transgenic plant-derived vaccines comprise a new type of bioreactor that combines plant genetic engineering technology with an organism's immunological response. This combination can be considered as a bioreactor that is produced by introducing foreign genes into plants that elicit special immunogenicity when introduced into animals or human beings. In comparison with traditional vaccines, plant vaccines have some significant advantages, such as low cost, greater safety, and greater effectiveness. In a number of recent studies, antigen-specific proteins have been successfully expressed in various plant tissues and have even been tested in animals and human beings. Therefore, edible vaccines of transgenic plants have a bright future. This review begins with a discussion of the immune mechanism and expression systems for transgenic plant vaccines. Then, current advances in different transgenic plant vaccines will be analyzed, including vaccines against pathogenic viruses, bacteria, and eukaryotic parasites. In view of the low expression levels for antigens in plants, high-level expression strategies of foreign protein in transgenic plants are recommended. Finally, the existing safety problems in transgenic plant vaccines were put forward will be discussed along with a number of appropriate solutions that will hopefully lead to future clinical application of edible plant vaccines.

Several replication-initiation proteins are assembled stepwise onto replicators to form pre-replicative complexes (pre-RCs) to license eukaryotic DNA replication. We performed a yeast functional proteomic screen and identified the Rix1 complex members (Ipi1p-Ipi2p/Rix1-Ipi3p) as pre-RC components and critical determinants of replication licensing and replication-initiation frequency. Ipi3p interacts with pre-RC proteins, binds chromatin predominantly at ARS sequences in a cell cycle-regulated and ORC- and Noc3p-dependent manner and is required for loading Cdc6p, Cdt1p and MCM onto chromatin to form pre-RC during the M-to-G₁ transition and for pre-RC maintenance in G₁ phase-independent of its role in ribosome biogenesis. Moreover, Ipi1p and Ipi2p, but not other ribosome biogenesis proteins Rea1p and Utp1p, are also required for pre-RC formation and maintenance, and Ipi1p, -2p and -3p are interdependent for their chromatin association and function in pre-RC formation. These results establish a new framework for the hierarchy of pre-RC proteins, where the Ipi1p-2p-3p complex provides a critical link between ORC-Noc3p and Cdc6p-Cdt1p-MCM in replication licensing.

Zonula occludens (ZO)-1 is a multi-domain scaffold protein known to have critical roles in the establishment of cell–cell adhesions and the maintenance of stable tissue structures through the targeting, anchoring, and clustering of transmembrane adhesion molecules and cytoskeletal proteins. Here, we report that ZO-1 directly binds to MRCKβ, a Cdc42 effector kinase that modulates cell protrusion and migration, at the leading edge of migrating cells. Structural studies reveal that the binding of a β hairpin from GRINL1A converts ZO-1 ZU5 into a complete ZU5-fold. A similar interaction mode is likely to occur between ZO-1 ZU5 and MRCKβ. The interaction between ZO-1 and MRCKβ requires the kinase to be primed by Cdc42 due to the closed conformation of the kinase. Formation of the ZO-1/MRCKβ complex enriches the kinase at the lamellae of migrating cells. Disruption of the ZO-1/MRCKβ complex inhibits MRCKβ-mediated cell migration. These results demonstrate that ZO-1, a classical scaffold protein with accepted roles in maintaining cell–cell adhesions in stable tissues, also has an active role in cell migration during processes such as tissue development and remodelling.

In eukaryotes, replication licensing is achieved through sequential loading of several replication-initiation proteins onto replication origins to form pre-replicative complexes (pre-RCs), and unscheduled replication licensing is prevented by cyclin-dependent kinases (CDKs) through inhibitory phosphorylations of multiple initiation proteins. It is known that CDK inactivation during mitotic exit promotes pre-RC formation for the next cell cycle. However, whether the removal of the inhibitory phosphorylations on the initiation proteins is essential and the identity of the acting phosphatase(s) remain unknown. Here, we show that cell division cycle protein 14 (Cdc14p) dephosphorylates replication-initiation proteins Orc2p, Orc6p, Cdc6p and Mcm3p to restore their competence for pre-RC assembly in the budding yeast Saccharomyces cerevisiae. Cells without functional Cdc14p fail to dephosphorylate initiation proteins and to form pre-RCs – even when CDK activities are suppressed – and cannot replicate DNA in mitotic rereplication systems, whereas pulsed ectopic expression of Cdc14p in mitotic cells results in efficient pre-RC assembly and DNA rereplication. Furthermore, Cdc14p becomes dispensable for DNA rereplication in mitotic cells with combined non-phosphorylatable and/or phosphorylation-insensitive alleles of the initiation proteins. These data unravel the essential role of Cdc14p in replication licensing, beyond its established functions in mitotic exit, providing new insight into the intricate regulation of DNA replication through the interplay of CDKs and the Cdc14p phosphatase.

In order to improve the performance of Cloud Security Immune System(CSIS), the representation and storage of the feature data of self-set is studied. Firstly, it proposes a Bloom Filter Self-Set storage model (BFSS), which can reduce the storage space of self-set effectively and save query time. Secondly, in order to support the delete operation of the feature data, it put forwards a Counting Bloom Filter Self-set storage model (CTBFSS). Finally, to reduce the storage space of self-set and reduce querying time further, it raises Compressed Bloom Filter Self-Set storage model (CPBFSS).Experiments demonstrate that BFSS, CTBFSS and CPBFSS can reduce the time cost between customer and service effectively on the premise of higher recognition rate, speed up the search procedure and improve the overall performance of the system. Keywords—Cloud Security; Human Immune; Bloom Filter

Plant basic helix-loop-helix (bHLH) transcription factors play essential roles in abiotic stress tolerance. However, most bHLHs have not been functionally characterized. Here, we characterized the functional role of a bHLH transcription factor from Arabidopsis, AtbHLH112, in response to abiotic stress. AtbHLH112 is a nuclear-localized protein, and its nuclear localization is induced by salt, drought and abscisic acid (ABA). In addition, AtbHLH112 serves as a transcriptional activator, with the activation domain located at its N-terminus. In addition to binding to the E-box motifs of stress-responsive genes, AtbHLH112 binds to a novel motif with the sequence 'GG[GT]CC[GT][GA][TA]C' (GCG-box). Gain- and loss-of-function analyses showed that the transcript level of AtbHLH112 is positively correlated with salt and drought tolerance. AtbHLH112 mediates stress tolerance by increasing the expression of P5CS genes and reducing the expression of P5CDH and ProDH genes to increase proline levels. AtbHLH112 also increases the expression of POD and SOD genes to improve reactive oxygen species (ROS) scavenging ability. We present a model suggesting that AtbHLH112 is a transcriptional activator that regulates the expression of genes via binding to their GCG- or E-boxes to mediate physiological responses, including proline biosynthesis and ROS scavenging pathways, to enhance stress tolerance.