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The role of joint entity and relation extraction is to identify entities and their corresponding relations from specific texts, and it is also the basis for constructing and updating knowledge graph. Currently, joint extraction methods ignore information redundancy in the extraction process while pursuing performance. To address this issue, a model based on latent relations for joint entity and relation extraction is proposed. This paper designs a new decoding method to reduce the redundant information of relationships, entities and triples in the prediction process, and it is divided into two steps: extracting potential entity pairs and decoding relationships to complete the extraction of triples. Firstly, the potential entity pair extractor is used to predict whether there is potential relationship between entities, and at the same time, the entity pairs with high confidence are selected as the final potential entity pairs. Secondly, the relational decoding is regarded as a multi-label binary classification task, and the confidence of all relationships between each potential entity pair is predicted by the relational decoder. Finally, the number and type of relationships are determined by confidence to complete the task of extracting triples. Experimental results on two general datasets show that the proposed model is better than the baseline models in terms of accuracy and F1 indicators, which verifies the effectiveness of the proposed model. The ablation experiment also proves the effectiveness of the internal parts of the model.

This research aimed to figure out the relationships between depression, loneliness and pathological Internet use by testing 677 middle school students (M.sub.age = 12.12, SD = 0.79) and making a three-wave cross-lagged analysis. The total measuring time was two years, with a time interval of one year. The results showed the following: (1) There were significantly positive relationships between depression, loneliness and pathological Internet use at three time points; (2) Depression at T1 and T2 could significantly and positively predict pathological Internet use at T2 and T3, while loneliness could not. Pathological Internet use at T1 could significantly and positively predict the feelings of depression and loneliness at T2, while pathological Internet use at T2 could not significantly and positively predict the feelings of depression and loneliness at T3. Thus, results were inconclusive regarding whether PIU led to later psychiatric symptoms. This complex interactions varied with time and did not vary with gender. The findings show important significance for promotion of adolescents' psychology development and the prevention of pathological Internet use., Author(s): Xin Fang [sup.1] [sup.2] , Mei Tian [sup.3] , Ruihua Wang [sup.3] , Peng Wang [sup.1] Author Affiliations: (1) grid.410585.d, 0000 0001 0495 1805, Department of Psychology, Shandong Normal [...]

Clinical research reports serve as the presentation of scientific research findings and directly reflect the quality of the research. This article describes the writing of different types of clinical research reports， such as observational studies and randomized controlled trial studies， with a particular focus on randomized controlled trials. Each scientific research design has its reporting focus， and the writing of scientific research papers has uniform requirements and a specific writing format. Mastering the proper format of drafting research reports is of practical value and significant importance for conduction high-quality clinical research.

Statistics plays an important role in medical research， and the selection of appropriate statistical methods is crucial for drawing reliable and valuable conclusions. This paper provides a brief introduction to commonly used statistical analysis methods for medical data， covering descriptive analysis， parametric test， nonparametric test， correlation analysis， regression analysis， and analysis of survival data. It focuses on discussing the assumptions of multiple linear regression， logistic regression and Cox proportional risk regression， as well as how to choose the appropriate statistical methods for analyzing and interpreting medical data based on different research objectives and data types.

The entity and relation extraction task, which is the technical source of constructing and updating large-scale knowledge graph, aims to identify the relationship between entities from unstructured text. Among the existing joint extraction methods of entity and relation, parallel decoding of tuples efficiently generates tuples by set prediction. However, this method ignores the interaction between entity and relationship, and entity subject and object, resulting in the generation of invalid tuples. To address this problem, this paper proposes a joint extraction model of entity and relation based on dual set prediction networks. To enhance the interaction between relationships and entities, a dual set prediction network is used to decode the tuples in parallel, and the entity information and relationship types in the tuples are generated sequentially. The first set prediction network models the set of tuples and decodes the subject-object information in the tuple. The second set prediction network models the set of tuples embedded with subject-object information and decodes the relationship type between subject and object. This paper designs an entity filter for entity subject-object, which predicts the subject-object correlation among entities in a sentence and filters out the tuples with lower subject-object correlation according to the result. Experiments on the NYT (New York Times) and WebNLG public datasets show that the proposed model performs better than the baseline model in terms of accuracy and F1 metrics when the encoder is BERT, which verifies the validity of the model.

Few-shot knowledge graph completion (FKGC) is a new research hotspot in the field of knowledge graph completion, which aims to complete knowledge graph with a few samples of data. This task is of great importance in practical application and the fields of knowledge graph. In order to further promote the development of the field of FKGC, this paper summarizes and analyzes the current methods. Firstly, this paper describes the concept of FKGC and related content. Secondly, three types of FKGC methods are summarized based on technical methods, including scale learning-based methods, meta learning-based methods, and other model-based methods. In addition, this paper analyzes and summarizes each method from the perspectives of model core, model ideas, advantages and disadvantages, etc. Then, the datasets and evaluation indexes of FKGC method are summarized, and the FKGC method is analyzed from two aspects of model characteristics and experimental results. Finally, starting from the practical problems, this paper summarizes the difficult problems of the current FKGC task, analyses the difficulties behind the problems, gives the corresponding solutions, and prospects several development directions that deserve attention in this field in the future.

Hepatocellular carcinoma (HCC) is a kind of primary liver cancer with a high mortality rate. In China, the incidence ratio in males to females with HCC is 2:1–5:1. The difference in sex hormone pathways between males and females and the interaction between androgen/androgen receptors and HBV can lead to an incidence difference between males and females with HCC. Hence, the androgen/androgen receptor oncogenic pathway in hepatocellular carcinoma has received considerable attention. This review mainly summarizes the recent research progress on the androgen/androgen receptor oncogenic pathway in hepatocellular carcinoma.

ObjectiveTo investigate the related factors of hypertension and comorbid hypertension-diabetes mellitus （HT-DM） among rural residents in Shanghai， China.MethodsA total of 2 159 residents over 35 years old were randomly selected from a rural community in the suburbs of Shanghai through cluster random sampling. Their basic sociological characteristics and blood lipid levels were investigated. Chi-square test was used to analyze the relationship between hypertension （or HT-DM） and gender， age， education levels， marital status， original household registration and current household registration. The relationship between hypertension （or HT-DM） and blood lipid level was analyzed by a conditional logistic regression model.ResultsThe prevalence of hypertension was 26.35% and that of HT-DM was 4.68% in the study population. Chi-square test analysis showed that hypertension was significantly associated with age， marital status， educational level， and rural household registration， while HT-DM was significantly associated with age， educational level， and rural household registration. Chi-square trend analysis indicated that the prevalence of hypertension and HT-DM increased with age in both male and female populations （χ2=129.82， 193.04，both P

Corona virus disease 2019 （COVID-19） has led to more than 500 million cases， including 6.19 million deaths. Mutated strains of SARS-CoV-2 （alpha， beta， gamma， delta and omicron） have successively emerged. Currently the omicron variant is gradually replacing the delta variant， driving a surge of cases in most countries including China， posing a great challenge to the prevention and treatment of COVID-19. In the face of the severe pandemic situation， a large number of non-medical volunteers are fighting on the front lines of the war against the pandemic and are vulnerable to exposure due to lack of professional knowledge. This paper introduces the routine skills training of volunteers and emergency response， aiming to provide behavioral guidance for non-medical volunteers in designated isolation facilities.

Objective To evaluate the surgical effect and complication of laser in situ fenestration with thoracic endovascular aortic repair (TEVAR) in the patients with aortic dissection involving arch branches. Methods From December 2018 to December 2020, 181 patients with aortic dissection involving arch branches admitted to our hospital were analyzed retrospectively among whom 172 patients had laser in situ fenestration with TEVAR. The inclusion criteria were dissection involved aortic arch and the process of TEVAR required reconstruction of the branched vessels in arch. Patients both with aortic dissection lesions less than 15 mm from the coronary ostium and the diameter of ascending aorta more than 45 mm were excluded. Results All cases underwent laser in situ fenestration with TEVAR including 37 cases (21.51%) in acute stage and 135 cases (78.49%) in subacute stage and 165 cases (95.93%) with success of reconstruction of branch vessels. In-hospital death occurred in 6 cases (3.49%), stroke in 2 cases (1.16%), paraplegia in 4 cases (2.33%), proximal stent-graft induced new entry (SINE) in 2 cases (1.16%), and without distal SINE. A total of 168 cases (97.67%) were followed-up. There were 311 branch vessels reconstructed. Follow-up CT angiography was done(10.6±5.4) months which showed that 295 branch vessels were patency with patency rate 94.86%. The partial or complete false lumen thrombosis of thoracic aorta was found in 152 cases (88.37%). Conclusions Laser in situ fenestration with TEVAR was performed with high success rate and low complication rate for the patients with aortic dissection involving arch branches. Long-term follow-up and large sample studies are needed for long-term clinical effects.

High-k oxide dielectric films are indispensable for low-power-consumption oxide thin-film transistors (TFTs) applied in advanced and portable electronics. However, high-quality oxide dielectric films prepared by solution process typically require sophisticated processes and long thermal annealing time, severely limiting both the throughput manufacturing and cost-effectiveness. In this study, the influence of different heating-up methods on the surface morphology and dielectric properties was systematically investigated. Gradient heating-up method could not only substantially improve the surface morphology and quality of high-k ZrO2 films but also efficiently shorten the annealing time. The gradient heating-up process was further designed on the basis of thermal behavior of the xerogel-like precursor, which successfully realize the preparation of high-quality ZrO2 films with an annealing time of 5 min (i.e. the efficiency of thermal treatment increased by about 89%). The ZrO2 film presented excellent dielectric properties, including a low leakage current density of ∼10−8 A cm−2 (at 2 MV cm−1), a large areal capacitance of 169 nF cm−2 and a high dielectric constant of 20.41 (1 MHz). Furthermore, InSnZnO TFT based on the ZrO2 gate dielectrics shows an acceptable device performances, such as a high carrier mobility of 2.82 cm2 V−1 s, a high on/off current ratio of ∼105 and a low subthreshold swing of 0.19 V decade −1 at a low operation voltage of 5 V. This work provide a highly promising approach to fabricate high-quality solution-processed high-k oxide dielectric films employed for large-scale and low-power-consumption electronics. [ABSTRACT FROM AUTHOR]