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The norovirus (NoV) genome is diverse. Therefore, this study explored the epidemiological characteristics and genetic features of NoV in Ningxia Hui Autonomous Region, China, from 2011 to 2022 to clarify the genetic diversity in this region. Stool samples were screened for NoV and then sequenced and genotyped. In total, 1,788 of 13,083 specimens were NoV -positive (13.67%); 204 (1.56%) and 1,584 (12.11%) cases were GI and GII, respectively. Additionally, 559 were NoV infection with other viruses (4.27%), primarily with rotavirus (277/559, 49.55%). The NoV incidence rate was the highest among children aged 0–2 years (18.09%, 1054/5,828) and lowest among adults aged 45–64 years (110/1,495, 7.36%); it was also higher in the winter and spring than in the other seasons. GI.3[P3] was the dominant GI genotype. The dominant GII genotype changed roughly every two years. In the GII group, GII.4 was the most common genotype (46.79%), followed by GII.3 (21.34%), GII.2 (12.34%), and GII.17 (9.77%). There were three variants of GII.4 Den Haag, GII.4 New Orleans and GII.4 Sydney identified in the detected GII.4 strains, with GII.4 Sydney dominating. The GII.4 (87.36%), GII.3 (86.35%), and GII.2 (72.92%) strains were primarily detected in children, whereas it was the GII.17 (52.63%) strain in adults. Overall, the NoV genotypes in the Ningxia Hui Autonomous Region were diverse. Primarily, GII groups were dominant, but this changed over time. [ABSTRACT FROM AUTHOR]

Few-shot relation extraction (FSRE) constitutes a critical task in natural language processing (NLP), involving learning relationship characteristics from limited instances to enable the accurate classification of new relations. The existing research primarily concentrates on using prototype networks for FSRE and enhancing their performance by incorporating external knowledge. However, these methods disregard the potential interactions among different prototype networks, and each prototype network can only learn and infer from its limited instances, which may limit the robustness and reliability of the prototype representations. To tackle the concerns outlined above, this paper introduces a novel prototype network called SACT (multi-head self-attention and contrastive-center loss), aimed at obtaining more comprehensive and precise interaction information from other prototype networks to bolster the reliability of the prototype network. Firstly, SACT employs a multi-head self-attention mechanism for capturing interaction information among different prototypes from traditional prototype networks, reducing the noise introduced by unknown categories with a small sample through information aggregation. Furthermore, SACT introduces a new loss function, the contrastive–center loss function, aimed at tightly clustering samples from a similar relationship category in the center of the feature space while dispersing samples from different relationship categories. Through extensive experiments on FSRE datasets, this paper demonstrates the outstanding performance of SACT, providing strong evidence for the effectiveness and practicality of SACT. [ABSTRACT FROM AUTHOR]

Lane detection, a crucial component of autonomous driving systems, is in charge of precise lane location to ensure that cars navigate lanes appropriately. However, in challenging conditions like shadows and extreme lighting, lanes may become obstructed or blurred, posing a significant challenge to the lane-detection task as the model struggles to extract sufficient visual information from the image. The current anchor-based lane-detection network detects lanes in complex scenes by mapping anchors to images to extract features and calculating the relationship between each anchor and other anchors for feature fusion. However, it is insufficient for anchors to extract subtle features from images, and there is no guarantee that the information carried by each anchor is valid. Therefore, this study proposes the adaptive cross-scale ROI fusion network (ACSNet) to fully extract the features in the image so that the anchor carries more useful information. ACSNet selects important anchors in an adaptive manner and fuses these important anchors with the original anchors across scales. Through this feature extraction method, the features of different field-of-view ranges under complex road surfaces can be learned, and diversified features can be integrated to ensure that lanes can be well detected under complex road surfaces such as shadows and extreme lighting. Furthermore, due to the slender structure of lane lines, there are relatively few useful features in the images. Therefore, this study also proposes a Three-dimensional Coordinate Attention Mechanism (TDCA) to enhance image features. The Three-dimensional Coordinate Attention Mechanism extensively explores relationships among features in the row, column, and spatial dimensions. It calculates feature weights for each of these dimensions and ultimately performs element-wise multiplication with the entire feature map. Experimental results demonstrate that our network achieves excellent performance on the existing public datasets, CULane and Tusimple. [ABSTRACT FROM AUTHOR]

Cancer is known as a heterogeneous disease. Cancer driver genes (CDGs) need to be inferred for understanding tumor heterogeneity in cancer. However, the existing computational methods have identified many common CDGs. A key challenge exploring cancer progression is to infer cancer subtype-specific driver genes (CSDGs), which provides guidane for the diagnosis, treatment and prognosis of cancer. The significant advancements in single-cell RNA-sequencing (scRNA-seq) technologies have opened up new possibilities for studying human cancers at the individual cell level. In this study, we develop a novel unsupervised method, CSDGI (Cancer Subtype-specific Driver Gene Inference), which applies Encoder-Decoder-Framework consisting of low-rank residual neural networks to inferring driver genes corresponding to potential cancer subtypes at the single-cell level. To infer CSDGs, we apply CSDGI to the tumor single-cell transcriptomics data. To filter the redundant genes before driver gene inference, we perform the differential expression genes (DEGs). The experimental results demonstrate CSDGI is effective to infer driver genes that are cancer subtype-specific. Functional and disease enrichment analysis shows these inferred CSDGs indicate the key biological processes and disease pathways. CSDGI is the first method to explore cancer driver genes at the cancer subtype level. We believe that it can be a useful method to understand the mechanisms of cell transformation driving tumours. Author summary: Cancer is recognized as a complex disease with diverse characteristics. In order to comprehend the diversity within tumors, it is essential to infer cancer subtype-specific driver genes (CSDGs), which offer valuable insights for investigating cancer progression and treatment. The remarkable progress made in single-cell RNA-sequencing (scRNA-seq) technologies has ushered in new prospects for studying human cancers at the cellular level. Cancer Subtype-specific Driver Gene Inference (CSDGI) is a novel unsupervised method proposed. In our study, we use Encoder-Decoder-Framework to infer driver genes specific to cancer subtypes in the CSDGI. We apply CSDGI to three tumor single-cell transcriptomics data. The experimental results have shown the effectiveness of CSDGI. Furthermore, functional and disease enrichment analyses illustrate that these inferred CSDGs shed light on crucial biological processes and disease pathways. Our collection of driver genes will serve as a valuable resource in unraveling the mechanisms driving cell transformation in tumors. [ABSTRACT FROM AUTHOR]

This paper is concerned with the dynamic output feedback robust model predictive control (RMPC) problem for a class of discrete‐time asynchronous Markovian jump systems (MJSs) subject to polytopic parameter uncertainties and hard constraints on states and inputs. A hidden Markov model is employed to describe the asynchronous phenomenon between the detected modes and the system modes. For the purpose of improving the network utilization as well as reducing the transmission burden and avoiding data collisions, the try‐once‐discard (TOD) protocol is deployed in the shared communication network between sensor nodes and the controller node. Considering the difficulty of obtaining the system state in the practice, the dynamic output‐feedback control in the framework of RMPC is adopted, and the worst‐case optimization problem over the infinite moving horizon is formulated for the performance analysis and control synthesis. By means of the Lyapunov‐like function approach, free weighting matrices and inequality techniques such as the S$$ S $$‐procedure are introduced to deal with the non‐convexity caused by couplings between decisive variables and the negative influence resulting from the data orchestration is mitigated. Based on the delicate establishments, a certain upper bound of the objective function is employed to construct an auxiliary optimization problem with solvability to find the desired controllers, and sufficient conditions are obtained to guarantee that the MJSs under the proposed RMPC‐based controllers are mean‐square stable. Finally, an illustrative example is used to demonstrate the validity of the proposed methods. [ABSTRACT FROM AUTHOR]

Location information on Twitter plays a critical role in emergency detection, event recommendation, and disaster warning. However, only a limited amount of Twitter data are geotagged. Previous research has presented various models for inferring location based on text, social relations, and contextual data, yielding highly promising results. Nonetheless, these existing methods have certain limitations that need to be addressed. Firstly, most of the existing methods overlook the role of local celebrities (well-known users in the local community) as indicators of location within the social network. Secondly, they fail to consider the associations between words in tweets, resulting in insufficiently rich features extracted from the tweets. We propose a multi-view-based location inference model called MVGeo to overcome these limitations. In the network view, our approach employs the Gaussian Mixture Model (GMM) to identify and retain local celebrities, thereby strengthening user location associations. In the tweet view, we construct a heterogeneous graph based on the co-occurrence relationship between words in tweets and the user's mentioned relationship with the words. This allows us to fully leverage the local correlation between words and the global correlation to extract tweet features more comprehensively. Finally, we employ a modified multi-layer graph convolutional network, called Gate-GCN, to fuse the network and tweet information. This expansion of the feature space enables us to extract sample features from multiple perspectives. To demonstrate the effectiveness of MVGeo, we conduct exhaustive experimental evaluations on a publicly available dataset and compare its performance against several state-of-the-art benchmark models. The results confirm the superior performance of the proposed model. [ABSTRACT FROM AUTHOR]

With the continuous development of knowledge graph completion (KGC) technology, the problem of few-shot knowledge graph completion (FKGC) is becoming increasingly prominent. Traditional methods for KGC are not effective in addressing this problem due to the lack of sufficient data samples. Therefore, completing the task of knowledge graph with few-shot data has become an urgent issue that needs to be addressed and solved. This paper first presents a concise introduction to FKGC, which covers relevant definitions and highlights the advantages of FKGC techniques. We then categorize FKGC methods into meta-learning-based, metric-based, and graph neural network-based methods, and analyze the unique characteristics of each model. We also introduced the research on FKGC in a specific domain - Temporal Knowledge Graph Completion (TKGC). Subsequently, we summarized the commonly used datasets and evaluation metrics in existing methods and evaluated the completion performance of different models in TKGC. Finally, we presented the challenges faced by FKGC and provided directions for future research. [ABSTRACT FROM AUTHOR]

Single-cell RNA-sequencing (scRNA-seq) technologies have enabled the study of human cancers in individual cells, which explores the cellular heterogeneity and the genotypic status of tumors. Gene signature identification plays an important role in the precise classification of cancer subtypes. However, most existing gene selection methods only select the same informative genes for each subtype. In this study, we propose a novel gene selection method, automatic association feature learning (AAFL), which automatically identifies different gene signatures for different cell subpopulations (cancer subtypes) at the same time. The proposed AAFL method combines the residual network with the low-rank network, which selects genes that are most associated with the corresponding cell subpopulations. Moreover, the differential expression genes are acquired before gene selection to filter the redundant genes. We apply the proposed feature learning method to the real cancer scRNA-seq data sets (melanoma) to identify cancer subtypes and detect gene signatures of identified cancer subtypes. The experimental results demonstrate that the proposed method can automatically identify different gene signatures for identified cancer subtypes. Gene ontology enrichment analysis shows that the identified gene signatures of different subtypes reveal the key biological processes and pathways. These gene signatures are expected to bring important implications for understanding cellular heterogeneity and the complex ecosystem of tumors. [ABSTRACT FROM AUTHOR]

Multimodal sentiment analysis aims to understand people's attitudes and opinions from different data forms. Traditional modality fusion methods for multimodal sentiment analysis con-catenate or multiply various modalities without fully utilizing context information and the correlation between modalities. To solve this problem, this article provides a new model based on a multimodal sentiment analysis framework based on a recurrent neural network with a complex attention mechanism. First, after the raw data is preprocessed, the numerical feature representation is obtained using feature extraction. Next, the numerical features are input into the recurrent neural network, and the output results are multimodally fused using a complex attention mechanism layer. The objective of the complex attention mechanism is to leverage enhanced non-linearity to more effectively capture the inter-modal correlations, thereby improving the performance of multimodal sentiment analysis. Finally, the processed results are fed into the classification layer and the sentiment output is obtained using the classification layer. This process can effectively capture the semantic information and contextual relationship of the input sequence and fuse different pieces of modal information. Our model was tested on the CMU-MOSEI datasets, achieving an accuracy of 82.04%. [ABSTRACT FROM AUTHOR]

Fiber loop ring‐down spectroscopy (FLRDS) is a highly sensitive spectroscopic technology. Here, a spectral processing method is proposed for low‐cost fiber loop ring‐down systems. In the proposed method, the amplitude modulation theory is used to establish a new ring‐down spectral model, and the particle swarm optimization algorithm is introduced into FLRDS. The experimental results demonstrate that the proposed method can effectively process the ring‐down spectral signals acquired from the low‐cost fiber loop ring‐down system. Moreover, this method demonstrates higher accuracy and stronger adaptability than the current widely used method. Owing to its excellent performance, the proposed method has considerable potential to be applied in low‐cost fiber loop ring‐down systems. [ABSTRACT FROM AUTHOR]

Since the facts in the knowledge graph (KG) cannot be updated automatically over time, some facts have temporal conflicts. To discover and eliminate the temporal conflicts in the KG, this paper proposes a novel temporal conflict resolution method based on temporal KG embedding (named TeCre). Firstly, the predicate relation and timestamp information of time series are incorporated into the entity–relation embedding representation by leveraging the temporal KG embedding (KGE) method. Then, taking into account the chronological sequence of the evolution of the entity–relation representation over time, TeCre constrains the temporal relation in the KG according to the principles of time disjoint, time precedence, and time mutually exclusive constraints. Besides that, TeCre further considers the sequence vectorization of predicate relation to discover the temporal conflict facts in the KG. Finally, to eliminate the temporal conflict facts, TeCre deletes the tail entities of the temporal conflict facts, and employs the link prediction method to complete the missing tail entities according to the output of the score function based on the entity–relation embedding. Experimental results on four public datasets show that TeCre is significantly better than the state-of-the-art temporal KG conflict resolution model. The mean reciprocal ranking (MRR) and Hits@10 of TeCre are at least 5.46% and 3.2% higher than the baseline methods, respectively. [ABSTRACT FROM AUTHOR]

A 2.5‐year‐old pediatric patient with acute flaccid paralysis was diagnosed with primary immunodeficiency (PID) in Ningxia Province, China, in 2011. Twelve consecutive stool specimens were collected from the patient over a period of 10 months (18 February 2011 to 20 November 2011), and 12 immunodeficiency vaccine‐derived poliovirus (iVDPV) strains (CHN15017‐1 to CHN15017‐12) were subsequently isolated. Nucleotide sequencing analysis of the plaque‐purified iVDPVs revealed 2%–3.5% VP1‐region differences from their parental Sabin 3 strain. Full‐length genome sequencing showed they were all Sabin 3/Sabin 1 recombinants, sharing a common 2C‐region crossover site, and the two key determinants of attenuation (U472C in the 5′ untranslated region and T2493C in the VP1 region) had reverted. Temperature‐sensitive experiments demonstrated that the first two iVDPV strains partially retained the temperature‐sensitive phenotype's nature, while the subsequent ten iVDPV strains distinctly lost it, possibly associated with increased neurovirulence. Nineteen amino‐acid substitutions were detected between 12 iVDPVs and the parental Sabin strain, of which only one (K1419R) was found on the subsequent 10 iVDPV isolates, suggesting this site's potential as a temperature‐sensitive determination site. A Bayesian Monte Carlo Markov Chain phylogenetic analysis based on the P1 coding region yielded a mean iVDPV evolutionary rate of 1.02 × 10−2 total substitutions/site/year, and the initial oral‐polio‐vaccine dose was presumably administered around June 2009. Our findings provide valuable information regarding the genetic structure, high‐temperature growth sensitivity, and antigenic properties of iVDPVs following long‐term evolution in a single PID patient, thus augmenting the currently limited knowledge regarding the dynamic changes and evolutionary pathway of iVDPV populations with PID during long‐term global replication. [ABSTRACT FROM AUTHOR]

Objective: To investigate the preoperative morbidity of deep venous thrombosis (DVT) and predictive risk factors associated with DVT after closed tibial shaft fracture. Methods: Ultrasonography and blood analyses were performed preoperatively in patients who sustained tibial shaft fracture between October 2014 and December 2018. Univariate analyses were used in the data of demographics, comorbidities, mechanism of injury, concomitant fractures and laboratory biomarkers. Multivariate logistic regression analyses were conducted to determine the independent risk factors associated with DVT. Results: In total, 918 patients with an operatively treated tibial shaft fracture were included, among whom 122 patients had preoperative DVTs, indicating a crude morbidity of 13.3%. Ninety-two of 758 (12.1%) patients with isolated tibial shaft fracture developed DVT, while 30 of 160 (18.8%) patients with concurrent fracture presented with DVT. The average interval between fracture and initial diagnosis of DVT was 3.1 days (median, 2 days), ranging from 0 to 33 days. Among DVT-positive patients, 16 (13.1%) patients presented with proximal DVT and 106 (86.9%) patients had distal DVT. Multivariate logistic regression analysis showed four independent risk factors were significantly correlated to the development of DVT, including increased age (OR = 1.17, p = 0.003), diabetes (OR = 1.99, p = 0.009), serum hydroxybutyrate dehydrogenase > 182 U/L (OR = 1.83, p = 0.008), and delay to DUS (in each day) (OR = 1.13, p < 0.001). Conclusion: In the present cohort study, the incidence of DVT was 12.1% in patients with isolated tibial shaft fracture. We suggest individualized risk stratification and early anticoagulation for patients with high risk factors including pre-existing diabetes, HBDH > 182 U/L, delay to DUS and older age. Level of evidence: Level III, a prospective cohort study. [ABSTRACT FROM AUTHOR]

The purpose of knowledge graph entity disambiguation is to match the ambiguous entities to the corresponding entities in the knowledge graph. Current entity ambiguity elimination methods usually use the context information of the entity and its attributes to obtain the mention embedding vector, compare it with the candidate entity embedding vector for similarity, and perform entity matching through the similarity. The disadvantage of this type of method is that it ignores the structural characteristics of the knowledge graph where the entity is located, that is, the connection between the entity and the entity, and therefore cannot obtain the global semantic features of the entity. To improve the Precision and Recall of entity disambiguation problems, we propose the EDEGE (Entity Disambiguation based on Entity and Graph Embedding) method, which utilizes the semantic embedding vector of entity relationship and the embedding vector of subgraph structure feature. EDEGE first trains the semantic vector of the entity relationship, then trains the graph structure vector of the subgraph where the entity is located, and balances the weights of these two vectors through the entity similarity function. Finally, the balanced vector is input into the graph neural network, and the matching between the entities is output to achieve entity disambiguation. Extensive experimental results proved the effectiveness of the proposed method. Among them, on the ACE2004 data set, the Precision, Recall, and F1 values of EDEGE are 9.2%, 7%, and 11.2% higher than baseline methods. [ABSTRACT FROM AUTHOR]

Current studies on cable harness layouts have mainly focused on cable harness route planning. However, the topological structure of a cable harness is also extremely complex, and the branch structure of the cable harness can affect the route of the cable harness layout. The topological structure design of the cable harness is a key to such a layout. In this paper, a novel multi-branch cable harness layout design method is presented, which unites the probabilistic roadmap method (PRM) and the genetic algorithm. First, the engineering constraints of the cable harness layout are presented. An obstacle-based PRM used to construct non-interference and near to the surface roadmap is then described. In addition, a new genetic algorithm is proposed, and the algorithm structure of which is redesigned. In addition, the operation probability formula related to fitness is proposed to promote the efficiency of the branch structure design of the cable harness. A prototype system of a cable harness layout design was developed based on the method described in this study, and the method is applied to two scenarios to verify that a quality cable harness layout can be efficiently obtained using the proposed method. In summary, the cable harness layout design method described in this study can be used to quickly design a reasonable topological structure of a cable harness and to search for the corresponding routes of such a harness. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the presence of preoperative DVT following spinal fracture and the association between the presence of DVT and risk factors. Ultrasonography and blood analyses were performed preoperatively in patients diagnosed with spinal fracture between October 2014 and December 2018. Univariate analyses were performed on the data of demographics, comorbidities, location of injury, spinal cord injury (SCI) grading and laboratory biomarkers. The receiver operating characteristic (ROC) curve analysis was employed to obtain the optimal D-dimer cut-off value for diagnosis. In total, 2432 patients with spinal fractures were included, among whom 108 (4.4%) patients had preoperative DVTs. The average interval between fracture and initial diagnosis of DVT was 4.7 days (median, 2 days), ranging from 0 to 20 days; 78 (72.2%) were diagnosed within 7 days after injury and 67 (62.0%) within 3 days; 19 (17.5%) patients had proximal vein involved and 89 (82.4%) presented in distal veins. Multivariate logistic regression suggested six risk factors independently correlated to DVT, including delay to DUS (in each day) (odds ratio [OR] = 1.11), ASA class III–IV (OR = 2.36), ASIA grade (A/B) (OR = 2.36), ALB < 3.5 g/dL (OR = 2.08), HDL-C < 1.1 mmol/L (OR = 1.68) and d-Dimer > 1.08 µg/ml (OR = 2.49). [ABSTRACT FROM AUTHOR]

Background: α-Tocopherol is one of the most important vitamin E components present in plant. α-Tocopherol is a potent antioxidant, which can deactivate photoproduced reactive oxygen species (ROS) and prevent lipids from oxidation when plants suffer drought stress. γ-Tocopherol methyltransferase (γ-TMT) catalyzes the formation of α-tocopherol in the tocopherol biosynthetic pathway. Our previous studies showed that over-expression of γ-TMT gene can increase the accumulation of α-tocopherol in alfalfa (Medicago sativa). However, whether these transgenic plants confer increased drought tolerance and the underlying mechanism are still unknown. Results: In the present study, we further evaluate transgenic alfalfa lines, and found that over-expression of MsTMT led to an increase in α-tocopherol and total tocopherol level in the transgenic lines compared with the control plant. It was revealed that drought tolerance of the transgenic alfalfa was remarkably increased, with alleviated oxidative damage and accumulation of more osmolytic substances. The stomatal development in transgenic plants was significantly inhibited on both sides of leaves, which may be resulted from the repression of MsSPCHLESS (MsSPCH) gene. The reduced stomatal density of transgenic plants contributes to a lower stomatal conductance and higher water use efficiency (WUE). Moreover, both RNA-seq and qRT-PCR analyses indicate that regulatory mechanism of MsTMT in drought involved in both ABA-dependent and ABA-independent pathways. Conclusion: Our results suggest that MsTMT gene plays a positive role in regulating alfalfa response to PEG-simulated drought stress, which might involve complex mechanisms, including ROS scavenging system, stomatal development and multiple phytohormone signaling pathways. This study will broaden our view on the function of γ-TMT gene and provide new strategy for genetic engineering in alfalfa breeding. [ABSTRACT FROM AUTHOR]

SUMMARY: Deformable linear objects (DLOs) have a wide variety of applications in a range of fields. Their key characteristic is that they extend much further in one of their dimensions than in the other two. Accurate motion planning is particularly important in the case of DLOs used in robotics applications. In this paper, a new strategy for planning the motions of DLOs under multiple constraints is proposed. The DLO was modeled as Cosserat elastic rods so that the deformation is simulated accurately and efficiently. The control of the motion of the DLO was enhanced by supplementing one gripper installed at each end with additional supports. This allows DLOs to undergo complex deformations, and thus avoid collisions during motion. The appropriate number of supports and their positions were determined, and then a rapidly exploring random tree algorithm was used to search for the best path to guide the DLO toward its target destination. The motion of the simulated DLO is described as it is controlled using two grippers and specific numbers of supports. To prove that the proposed DLO motion planning strategy can successfully guide relatively long DLOs through complex environments without colliding with obstacles, a case study of the strategy was conducted when guiding a DLO through a puzzle. [ABSTRACT FROM AUTHOR]

Tocopherols are a group of lipid-soluble compounds and they are essential for human nutrition. Tocopherols are also well known as powerful antioxidants associated with ascorbate and glutathione, which protect plants from oxygen toxicity. However, an increasing amount of research suggests that tocopherols play roles in stress resistance far beyond their antioxidative activity. This work focuses on the tocopherol biosynthetic pathway, the activities of their different forms, and their roles in response to abiotic and biotic stresses. Here, we made an overview of three major tocopherol-related retrograde signaling pathways which were mediated by plant hormones, reactive oxygen species (ROS), and microRNAs (miRNAs), respectively. Furthermore, the available information on the progress of genetic engineering of tocopherol in plants was summarized. Finally, we identified questions that need to be addressed and discussed the prospective methods for tocopherol biofortification in plants. This review highlights the multifaceted role of tocopherols, which will facilitate further elucidating the functions of genes and direction of crop breeding. [ABSTRACT FROM AUTHOR]

Knowledge graph conflict resolution is a method to solve the knowledge conflict problem in constructing knowledge graphs. The existing methods ignore the time attributes of facts and the dynamic changes of the relationships between entities in knowledge graphs, which is liable to cause high error rates in dynamic knowledge graph construction. In this article, we propose a knowledge graph conflict resolution method, knowledge graph evolution algorithm based on deep learning (Kgedl), which can resolve facts confliction with high precision by combing time attributes, semantic embedding representations, and graph structure features. Kgedl first trains the semantic embedding vector through the relationships between entities. Then, the path embedding vector is trained from the graph structures of knowledge graphs, and the time attributes of entities are combined with the semantic and path embedding vectors. Finally, Kgedl uses a recurrent neural network to make the inconsistent facts appear in the dynamic evolution of the knowledge graph consistent. A large number of experiments on real datasets show that Kgedl outperforms the state-of-the-art methods. Especially, Kgedl achieves 23% higher performance than the classical method numerical Probabilistic Soft Logic (nPSL).in the metric HITS@10. Also, extensive experiments verified that our proposal possess better robustness by adding noise data. [ABSTRACT FROM AUTHOR]

Forming a carbonaceous protective layer during combustion has been proven to be an effective way to improving the flame retardancy of polymers and it has been found that some metal compounds could promote dehydrogenation and aromatization of the degradation products. In this research, several divalent or multivalent metal compounds were added in the intumescent flame retardant (IFR) based on ammonium polyphosphate, pentaerythritol and melamine for polyethylene terephthalate (PET) fabrics. The prepared flame retardant dispersions containing 25 wt% IFR and 1 wt% metal compounds were applied on PET fabrics by the common pad-dry-cure method. None of the treated samples generated any dripping during the vertical burning test, with the highest limiting oxygen index being up to 33.4%. Thermogravimetric analysis showed that the catalytic effect of metal compounds may occur in promoting the formation of char residues. The morphology of char residues of two of the IFR/metal compound-treated PET fabrics, IFR/FeCl3 and IFR/ZnCl2, were smooth and compact, as shown by scanning electron microscopy. Laser Raman spectroscopy of the char residues suggested that a higher graphitization degree was obtained by adding the metal compounds. Real-time Fourier transform infrared spectroscopy showed that metal compounds made more phosphorus available for phosphorylation and char formation. The results of the present study indicate the possibility for enhancing char formation via the catalytic effect of metal compounds to improve the flame retardant and anti-dripping properties of the PET fabrics. [ABSTRACT FROM AUTHOR]

Summary: Along with the increasing popularity of online social network (OSN), it is common that the same user holds many accounts among different OSNs (eg, Facebook, Twitter, WeChat, QQ). In this scenario, an interesting and challenging problem arises: how to link accounts among OSNs belonged to a natural person, which is also known as a graph matching problem. The solution helps understand user behaviors and offer better services. To solve the account linking problem, various techniques for OSNs have been proposed. However, most existing methods assume specific OSN features impractical in general OSNs and unscalable to large‐scale OSNs. To address these shortcomings, in this paper, we remodel the account linking problem into maximum matching on weighted bipartite graphs and utilize the Kuhn‐Munkres algorithm to solve it. In our solution, we capture user profile, user online time distribution, and user interest as features to describe user accounts and measure account similarity, which is used as weight of edge in bipartite graphs. Then, the maximum matching on weighted bipartite graphs is solved with the Kuhn‐Munkres algorithm. The experiments conducted on the real datasets show that our solution outperforms the baseline methods with 11%, 17%, and 29% on average in precision, recall, and F1 score, respectively. [ABSTRACT FROM AUTHOR]

Bioluminescence has been harnessed for use in bacterial reporter systems and for in vivo imaging of infection in animal models. Strain Xen35, a bioluminescent derivative of Streptococcus pneumoniae serotype 4 strain TIGR4 was previously constructed for use for in vivo imaging of infections in animal models. We have shown that strain Xen35 is less virulent than its parent TIGR4 and that this is associated with the expression of the genes for bioluminescence. The expression of the luxA-E genes in the pneumococcus reduces virulence and down regulates the expression of the pneumococcal pilus. [ABSTRACT FROM AUTHOR]

A fusant strain T1, which was constructed by protoplast fusion betweenAcinetobactersp. SRL8,Escherichiasp. XBR68 andAcinetobactersp. RC10, could simultaneously decolorize three different dyes, namely reactive brilliant blue XBR, disperse orange SRL, and red base RC. Maximum decolorization of initial 30 mg L−1was achieved at pH 7.0, 35°C and 3% inoculum (v/v) under anaerobic condition during 24 h incubation. The decolorization ratio for XBR, SRL, and RC by the strain T1 could reach 91.5, 87.6, and 65.7%, respectively. Supplementation with appropriate concentration of glucose (0.2%, w/v) in the decolorization reaction system could further enhance decolorization percent. The strain T1 was highly tolerant to three different dyes up to 400 mg L−1. Biological decolorization of the three different dyes by the strain T1 was investigated in a sequential anaerobic/aerobic process. The reaction system was operated at room temperature. The results indicated that over 95% color removal was obtained in anaerobic process and 97.6% COD removal occurred in the aerobic process. [ABSTRACT FROM AUTHOR]

Soil enzyme activity and microbial population play important roles in maintaining soil fertility and ensure crop yield. Paichongding (IPP) is a novel cis-nitromethylene neonicotinoid insecticide, which was recently developed in China. In this study, in order to better understand IPP ecological toxicity, the impact of IPP on soil enzyme activity and microbial population in soils was investigated. The results showed that, urease activity was inhibited by IPP before 75 days incubation, after that this inhibiting effect gradually weakened. IPP had different stimulating effects on the activities of dehydrogenase, protease, and catalase. They were consistently stimulated from the initial time in soils. The results of microbial population indicated that the number of bacteria increased after IPP application compared with the control, fungal number increased before 45 days incubation and then decreased. While actinomycete number decreased during degradation period. DT50 (half-life value), k (degradation rate constant) of IPP in S1 (yellow loam soil), and S2 (Huangshi soil) were found 90 days and 173 days, 0.0077 day, and 0.0040 day, respectively. [ABSTRACT FROM AUTHOR]

Insecticides are widely sprayed in modern agriculture for ensuring the crop yield, which could also lead to contamination and insecticide residue in soils. Paichongding (IPP) is a novel neonicotinoid insecticide and was developed recently in China. Soil bacterial community, diversity, and community composition vary widely depending on environmental factors. As for now, little is known about bacterial species thriving, bacterial community diversity, and structure in IPP-spraying soils. In present study, IPP degradation in yellow loam and Huangshi soils was investigated, and bacterial communities and diversity were examined in soil without IPP spray and with IPP spray through pyrosequencing of 16S ribosomal RNA (rRNA) gene amplicons. The degradation ratio of IPP at 60 days after treatment (DAT) reached 51.22 and 34.01 % in yellow loam and Huangshi soil, respectively. A higher richness of operational taxonomic units (OTUs) was found in yellow loam soil (867 OTUs) and Huangshi soil (762 OTUs) without IPP spray while OUTs were relatively low in IPP-spraying soils. The community composition also differed both in phyla and genus level between these two environmental conditions. Proteobacteria, Firmicutes, Planctomycetes, Chloroflexi, Armatimonadetes, and Chlorobi were stimulated to increase after IPP application, while IPP inhibited the phyla of Bacteroidetes, Actinobacteria, and Acidobacteria. [ABSTRACT FROM AUTHOR]

We focus on information diffusion in microblogging networks. As a classic problem of human dynamics in social networks, many researches have been done on information spreading in social media. In this work, we presented a new information diffusion model considering both network topology and spreading mechanism in microblogging networks. Extensive experiments have been done to estimate the impacts of reciprocity and modulrity on the outbreak size and spreading speed of a story in many artificial networks. By analyzing the experimental results in detail, we show that both reciprocity and modularity will impact the outbreak size and the spreading speed to some extent. Furthermore, modularity will impact the outbreak size much more than reciprocity. In most circumstances, the outbreak size of a story in the network with moderate modularity could be larger than that with low or high modularity. In addition, with the growth of reciprocity, the outbreak size will increase slightly. As a significant application, we have found some efficient strategies to control information spreading in real-world microblogging networks, and a better outcome will be attained to improve or restrain the outbreak size by adding or removing the edges between modules, rather than the edges with large betweenness. These findings introduced in this paper could be useful for decision-making processes in microblogging networks. [ABSTRACT FROM AUTHOR]

A method for an Agrobacterium-mediated transformation with phosphomannose isomerase-based selection system was investigated for cotyledons explants of Lotus corniculatus L. cultivar Leo. The effects of mannose on shoot formation and rooting was evaluated to choose appropriate selection pressure for Lotus corniculatus L. transformation. Complete inhibition in Murashige and Skoog medium supplemented with 20 g/L mannose in the presence of 20 g/L sucrose was observed, indicating that Lotus corniculatus L. is incapable of utilizing mannose as a carbon source. The mannose-resistant shoots from individual transformed lines selected in early developmental stage were identified by PCR analysis, resulting in a transformation frequency of 16.2 %. Six randomly chosen PCR-positive plantlets were further confirmed by Southern-blotting and RT-PCR analysis to demonstrate integration of the phosphomannose isomerase ( PMI) gene. Chlorophenol red assays were performed to determine PMI enzyme activity. These results demonstrate that the PMI-based selection is a highly efficient system for Lotus corniculatus L. transformation without requiring the use of conventional antibiotics or herbicide marker genes. [ABSTRACT FROM AUTHOR]

Enzyme activity and microbial population in soils have important roles in keeping soil fertility. ZJ0273 is a novel pyrimidynyloxybenzoic-based herbicide, which was recently developed in China. The effect of ZJ0273 on soil enzyme activity and microbial population in two different soils was investigated in this study for the first time. The protease activity was significantly inhibited by ZJ0273 and this inhibiting effect gradually weakened after 60-day incubation. The results also showed that ZJ0273 had different stimulating effects on the activities of dehydrogenase, urease, and catalase. Dehydrogenase was consistently stimulated by all the applied concentrations of ZJ0273. The stimulating effect on urease weakened after 60-day incubation. Catalase activity was subject to variations during the period of the experiments. The results of microbial population showed that the number of bacteria and actinomycetes increased in ZJ0273-treated soil compared with the control after 20 days of incubation, while fungal number decreased after only 10 days of incubation in soils. DT50 (half-life value) and k (degradation rate constant) of ZJ0273 in S1 (marine-fluvigenic yellow loamy soil) and S2 (Huangshi soil) were found 69.31 and 49.50 days and 0.010 and 0.014 day, respectively. [ABSTRACT FROM AUTHOR]

Adenoviruses are common pathogens, mostly targeting ocular, gastrointestinal and respiratory cells, but in some cases infection disseminates, presenting in severe clinical outcomes. Upon dissemination and contact with blood, coagulation factor X (FX) interacts directly with the adenovirus type 5 (Ad5) hexon. FX can act as a bridge to bind heparan sulphate proteoglycans, leading to substantial Ad5 hepatocyte uptake. FX “coating” also protects the virus from host IgM and complement-mediated neutralisation. However, the contribution of FX in determining Ad liver transduction whilst simultaneously shielding the virus from immune attack remains unclear. In this study, we demonstrate that the FX protection mechanism is not conserved amongst Ad types, and identify the hexon hypervariable regions (HVR) of Ad5 as the capsid proteins targeted by this host defense pathway. Using genetic and pharmacological approaches, we manipulate Ad5 HVR interactions to interrogate the interplay between viral cell transduction and immune neutralisation. We show that FX and inhibitory serum components can co-compete and virus neutralisation is influenced by both the location and extent of modifications to the Ad5 HVRs. We engineered Ad5-derived HVRs into the rare, native non FX-binding Ad26 to create Ad26.HVR5C. This enabled the virus to interact with FX at high affinity, as quantified by surface plasmon resonance, FX-mediated cell binding and transduction assays. Concomitantly, Ad26.HVR5C was also sensitised to immune attack in the absence of FX, a direct consequence of the engineered HVRs from Ad5. In both immune competent and deficient animals, Ad26.HVR5C hepatic gene transfer was mediated by FX following intravenous delivery. This study gives mechanistic insight into the pivotal role of the Ad5 HVRs in conferring sensitivity to virus neutralisation by IgM and classical complement-mediated attack. Furthermore, through this gain-of-function approach we demonstrate the dual functionality of FX in protecting Ad26.HVR5C against innate immune factors whilst determining liver targeting. [ABSTRACT FROM AUTHOR]

Streptococcus pneumoniae (pneumococcal) meningitis is a common bacterial infection of the brain. The cholesterol-dependent cytolysin pneumolysin represents a key factor, determining the neuropathogenic potential of the pneumococci. Here, we demonstrate selective synaptic loss within the superficial layers of the frontal neocortex of post-mortem brain samples from individuals with pneumococcal meningitis. A similar effect was observed in mice with pneumococcal meningitis only when the bacteria expressed the pore-forming cholesterol-dependent cytolysin pneumolysin. Exposure of acute mouse brain slices to only pore-competent pneumolysin at disease-relevant, non-lytic concentrations caused permanent dendritic swelling, dendritic spine elimination and synaptic loss. The NMDA glutamate receptor antagonists MK801 and D-AP5 reduced this pathology. Pneumolysin increased glutamate levels within the mouse brain slices. In mouse astrocytes, pneumolysin initiated the release of glutamate in a calcium-dependent manner. We propose that pneumolysin plays a significant synapto- and dendritotoxic role in pneumococcal meningitis by initiating glutamate release from astrocytes, leading to subsequent glutamate-dependent synaptic damage. We outline for the first time the occurrence of synaptic pathology in pneumococcal meningitis and demonstrate that a bacterial cytolysin can dysregulate the control of glutamate in the brain, inducing excitotoxic damage. [ABSTRACT FROM AUTHOR]

Background. Streptococcus pneumoniae causes serious diseases such as pneumonia and meningitis. Its major pathogenic factor is the cholesterol-dependent cytolysin pneumolysin, which produces lytic pores at high concentrations. At low concentrations, it has other effects, including induction of apoptosis. Many cellular effects of pneumolysin appear to be calcium dependent. Methods. Live imaging of primary mouse astroglia exposed to sublytic amounts of pneumolysin at various concentrations of extracellular calcium was used to measure changes in cellular permeability (as judged by lactate dehydrogenase release and propidium iodide chromatin staining). Individual pore properties were analyzed by conductance across artificial lipid bilayer. Tissue toxicity was studied in continuously oxygenated acute brain slices. Results. The reduction of extracellular calcium increased the lytic capacity of the toxin due to increased membrane binding. Reduction of calcium did not influence the conductance properties of individual toxin pores. In acute cortical brain slices, the reduction of extracellular calcium from 2 to 1 mM conferred lytic activity to pathophysiologically relevant nonlytic concentrations of pneumolysin. Conclusions. Reduction of extracellular calcium strongly enhanced the lytic capacity of pneumolysin due to increased membrane binding. Thus, extracellular calcium concentration should be considered as a factor of primary importance for the course of pneumococcal meningitis. [ABSTRACT FROM AUTHOR]

Mixed crystals of K(NH)HPO(KADP) were grown from KDP (KHPO) dominated mixed solutions with varying molar proportion of ADP (NHHPO) addition. It was found that, as the increase of ADP molar concentration, the growth rate along z-axis of KADP crystal decreased rapidly. The structure of KADP crystals was investigated by powder XRD and the lattice parameter was calculated. The results showed that the lattice parameter c of KADP crystal increased with the molar concentration of ADP. The optical homogeneity of grown KADP crystals was determined with a differential phase-shifting interferometry. Frequency dependences of the dielectric constant and dielectric loss of KADP crystals were measured at room temperature (290 K). The dielectric constants of KADP crystals were almost invariant with the increase of frequency. In the region of 10∼10Hz, the values of the dielectric loss reduced with the increase of frequency. The piezo-resonance coupling effect still exists in KADP crystals at room temperature, but shifted to low frequency band. (© 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Background: Surgical site infection (SSI) was the most common complication of tibial plateau fracture after open reduction and internal fixation (ORIF). Severe infections even required repeat surgeries, which would cause serious psychological harm to patients and increased the economic burden of treatment. In order to identify the characteristics of the SSI and to avoid the occurrence of SSI, we conducted a prospective study to investigate the incidence and independent risk factors of SSI after ORIF for closed tibial plateau fractures in adults. Methods: This study was performed at a first-level trauma center. From October 2014 to December 2018, the study subjects were adult patients with closed fractures of the tibial plateau, all of whom underwent open reduction and internal fixation (ORIF) treatment. Finally, a total of 1108 patients were followed up. We collected patient demographics information, surgery-related variables, and indexes from preoperative laboratory examinations. Univariate and multivariate logistic analysis models were used to investigate the potential risk factors. Results: Twenty-five patients (2.3%, 25/1108) developed SSI. A total of 15 of 25 infections (60.0%) were due to Staphylococcus aureus and 3 (12.0%) were due to MRSA. Independent risk factors of SSI identified by multivariate logistic analysis model were bone grafting: autograft (OR 6.38; 95% CI 2.155–18.886; p = 0.001) and allograft (OR 3.215; 95% CI 1.009–10.247; p = 0.048), fracture type (Schartzker V–VI) (OR 8.129; 95% CI 2.961–22.319; p < 0.001), aspartate aminotransferase (>40 U/L) (OR 5.500; 95% CI 2.191–13.807; p < 0.001), white blood cell (>10*109/L) (OR 2.498; 95% CI 1.025–6.092; p = 0.044), and anion gap (>16 mmol/L) (OR 8.194; 95% CI 1.101–60.980). Conclusions: We should pay enough attention to patients who carried one or more of these factors at admission and adopt more reasonable treatment strategies to reduce or avoid the occurrence of SSI. [ABSTRACT FROM AUTHOR]

Microorganisms can be used for enhancing flavors or metabolizing functional compounds. The fermented-food-derived bacterial strains comprising Bacillus velezensis, Bacillus licheniformis, and Lactobacillus reuteri mixed with Lactobacillus rhamnosus and Lactobacillus plantarum were used to ferment goji berry (Lycium barbarum L.) juice in this study. The fermentation abilities and antioxidant capacities of different mixtures of multiple strains in goji juice were compared. The results showed that the lactic acid contents increased 9.24–16.69 times from 25.30 ± 0.71 mg/100 mL in goji juice fermented using the SLV (Lactobacillus rhamnosus, Lactobacillus reuteri, and Bacillus velezensis), SZP (Lactobacillus rhamnosus, Lactobacillus plantarum, and Bacillus licheniformis), and SZVP (Lactobacillus rhamnosus, Lactobacillus plantarum, Bacillus velezensis, and Bacillus licheniformis) mixtures, and the protein contents increased 1.31–2.11 times from 39.23 ± 0.67 mg/100 mL. In addition, their contents of volatile compounds increased with positive effects on aroma in the fermented juices. Conversion of the free and bound forms of phenolic acids and flavonoids in juice was influenced by fermentation, and the antioxidant capacity improved significantly. Fermentation enhanced the contents of lactic acid, proteins, volatile compounds, and phenols. The antioxidant capacity was strongly correlated with the phenolic composition. [ABSTRACT FROM AUTHOR]

Sporadic outbreaks caused by coxsackievirus A4 (CV-A4) have been reported worldwide. To further elucidate the detailed genetic characteristics and evolutionary recombination events of CV-A4, virus samples from nationwide hand, foot and mouth disease (HFMD) surveillance, encompassing 27 out of the 31 provinces in China, were investigated. Comprehensive and systematic phylogenetic analyses were performed by using 29 complete genomes, 142 complete CV-A4 VP1 sequences. Four genotypes (A, B, C and D) and five sub-genotypes (C1-C5) were re-identified based on the complete VP1 sequences. C2 is the predominant sub-genotype of CV-A4 associated with HFMD and has evolved into 3 clusters. Cluster 1 is a major cluster that has been persistently and extensively circulating in China since 2006 and has been associated with all severe cases. All the sequences showed high homology with the CV-A4 prototype in the P1 region, while higher identities with CV-A5, CV-14 and CV-16 in the P2 and P3 regions. Recombination analysis revealed that C2 had two specific genetic recombination patterns with other EV-A prototypes in the 5′-UTR and 3D region compared with C5. These recombination patterns might be associated with the increased transmissibility of C2 viruses, which were obtained due to their persistent and extensive circulation in populations. [ABSTRACT FROM AUTHOR]

Lithium- and sodium-rich layered transition-metal oxides have recently been attracting significant interest because of their large capacity achieved by additional oxygen-redox reactions. However, layered transition-metal oxides exhibit structural degradation such as cation migration, layer exfoliation or cracks upon deep charge, which is a major obstacle to achieve higher energy-density batteries. Here we demonstrate a self-repairing phenomenon of stacking faults upon desodiation from an oxygen-redox layered oxide Na2RuO3, realizing much better reversibility of the electrode reaction. The phase transformations upon charging A2MO3 (A: alkali metal) can be dominated by three-dimensional Coulombic attractive interactions driven by the existence of ordered alkali-metal vacancies, leading to counterintuitive self-repairing of stacking faults and progressive ordering upon charging. The cooperatively ordered vacancy in lithium-/sodium-rich layered transition-metal oxides is shown to play an essential role, not only in generating the electro-active nonbonding 2p orbital of neighbouring oxygen but also in stabilizing the phase transformation for highly reversible oxygen-redox reactions. Here the authors report the evolution of stacking faults in Na2RuO3 showing that there is progressive cation ordering upon charging and notably the stacking faults can disappear. This behavior is driven by cooperative Coulombic interactions and can contribute to stabilizing the phase transformations. [ABSTRACT FROM AUTHOR]

Coxsackievirus A10 (CV-A10) associated with Hand, foot, and mouth disease (HFMD) cases emerged increasingly in recent years. In this study, the samples from nation-wide HFMD surveillance, including 27 out of 31 provinces in China were investigated, and the continuous and extensive virological surveillance, covered 13 years, were conducted to provide a comprehensive molecular characterization analysis of CV-A10. 855 CV-A10 viruses (33 severe cases included), were isolated from HFMD children patients during 2009 to 2016 in China. 164 representative sequences from these viruses, together with 117 CV-A10 sequences downloaded from GenBank based on entire VP1 were recruited in this study. Two new genotypes (F and G) and two sub-genotypes (C1 and C2) were identified. Among 264 Chinese sequences, 9 of them were genotype B, 8 of them were C1, and the other (247) were C2, the predominant sub-genotype in China since 2012. Chinese C2 viruses showed obvious temporal characteristics and can be divided into 3 clusters (cluster 1~3). Cluster 3 viruses was circulating extensively during 2014 and 2016 with more severe cases. It is very necessary and important to continuously conduct the extensive virological surveillance for CV-A10, and further evolutionary studies will provide more evidence on its evolution and virulence. [ABSTRACT FROM AUTHOR]