A hybrid representation based simile component extraction

Simile, a special type of metaphor, can help people to express their ideas more clearly. Simile component extraction is to extract tenors and vehicles from sentences. This task has a realistic significance since it is useful for building cognitive knowledge base. With the development of deep neural networks, researchers begin to apply neural models to component extraction. Simile components should be in cross-domain. According to our observations, words in cross-domain always have different concepts. Thus, concept is important when identifying whether two words are simile components or not. However, existing models do not integrate concept into their models. It is difficult for these models to identify the concept of a word. What’s more, corpus about simile component extraction is limited. There are a number of rare words or unseen words, and the representations of these words are always not proper enough. Exiting models can hardly extract simile components accurately when there are low-frequency words in sentences. To solve these problems, we propose a hybrid representation-based component extraction (HRCE) model. Each word in HRCE is represented in three different levels: word level, concept level and character level. Concept representations (representations in concept level) can help HRCE to identify the words in cross-domain more accurately. Moreover, with the help of character representations (representations in character levels), HRCE can represent the meaning of a word more properly since words are consisted of characters and these characters can partly represent the meaning of words. We conduct experiments to compare the performance between HRCE and existing models. The experiment results show that HRCE significantly outperforms current models

Social health assistance schemes: the case of Medical Financial Assistance for the rural poor in four counties of China

<p>Abstract</p> <p>Background</p> <p>Economic transition which took place in China over the last three decades, has led to a rapid marketization of the health care sector. Today inequity in health and poverty resulting from major illness has become a serious problem in rural areas of China. Medical Financial Assistance (MFA) is a health assistance scheme that helps rural poor people cope with major illness and alleviate their financial burden from major illness, which will definitely play a significant role in the process of rebuilding Chinese new rural health system. It mainly provides assistance to cover medical expenditure for inpatient services or the treatment of major illnesses, with joint funding from the central and local government. The purpose of this paper is to review the design, funding, implementation and to explore the preliminary effects of four counties' MFA in Hubei and Sichuan province of China.</p> <p>Methods</p> <p>We used an analytical framework built around the main objective of any social assistance scheme. The framework contains six 'targeting' procedural 'steps' which may explain why a specific group does not receive the assistance it ought to receive. More specifically, we explored to what extent the targeting, a key component of social assistance programs, is successful, based on the qualitative and quantitative data collected from four representative counties in central and western China.</p> <p>Results</p> <p>In the study sites, the budget of MFA ranged from 0.8 million Yuan to 1.646 million Yuan in each county and the budget per eligible person ranged from 32.67 Yuan to 149.09 Yuan. The preliminary effects of MFA were quite modest because of the scarcity of funds dedicated to the scheme. The coverage rate of MFA ranged from 17.8% to 24.1% among the four counties. MFA in the four counties used several ways to ration a restricted budget and provided only limited assistance. Substantial problems remained in terms of eligibility and identification of the beneficiaries, utilization and management of funds.</p> <p>Conclusions</p> <p>MFA needs to be improved further although it evidences the concern of the government for the poor rural people with major illness. Some ideas on how to improve MFA are put forward for future policy making.</p

Hypothermia treatment ameliorated cyclin-dependent kinase 5-mediated inflammation in ischemic stroke and improved outcomes in ischemic stroke patients

OBJECTIVES: The inflammatory response is a key mechanism of neuronal damage and loss during acute ischemic stroke. Hypothermia has shown promise as a treatment for ischemic stroke. In this study, we investigated the molecular signaling pathways in ischemic stroke after hypothermia treatment. METHODS: Cyclin-dependent kinase 5 (CDK5) was overexpressed or silenced in cultured cells. Nuclear transcription factor-kB (NF-kB) activity was assessed by measurement of the luciferase reporter gene. An ischemic stroke model was established in Sprague–Dawley (SD) rats using the suture-occluded method. Animals were assigned to three groups: sham operation control, ischemic stroke, and ischemic stroke + hypothermia treatment groups. Interleukin 1b (IL-1b) levels in the culture supernatant and blood samples were assessed by ELISA. Protein expression was measured by Western blotting. RESULTS: In HEK293 cells and primary cortical neuronal cultures exposed to hypothermia, CDK5 overexpression was associated with increased IL-1b, caspase 1, and NF-kB levels. In both a murine model of stroke and in patients, increased IL-1b levels were observed after stroke, and hypothermia treatment was associated with lower IL-1b levels. Furthermore, hypothermia-treated patients showed significant improvement in neurophysiological functional outcome. CONCLUSIONS: Overall, hypothermia offers clinical benefit, most likely through its effects on the inflammatory response

Chiral metallo-supramolecular complexes selectively recognize human telomeric G-quadruplex DNA

Here, we report the first example that one enantiomer of a supramolecular cylinder can selectively stabilize human telomeric G-quadruplex DNA. The P-enantiomer of this cylinder has a strong preference for G-quadruplex over duplex DNA and, in the presence of sodium, can convert G-quadruplexes from an antiparallel to a hybrid structure. The compound's chiral selectivity and its ability to discriminate quadruplex DNA have been studied by DNA melting, circular dichroism, gel electrophoresis, fluorescence spectroscopy and S1 nuclease cleavage. The chiral supramolecular complex has both small molecular chemical features and the large size of a zinc-finger-like DNA-binding motif. The complex is also convenient to synthesize and separate enantiomers. These results provide new insights into the development of chiral anticancer agents for targeting G-quadruplex DNA

The Characteristics of Mechanical Grinding on Kaolinite Structure and Thermal Behavior

AbstractThe relationship between kaolinite structure and the temperature of thermal transformation of phase was discussed in this paper through grinding and heating treatment. The results show that the structure of kaolinite is destroyed rapidly with increasing mechanical grinding time, and the kaolinite structure collapses completely after 1h grinding. The temperature of thermal transformation of phase decreases with the destruction of kaolinite structure. This result has a great significance for the utilization of kaolinite associated with coal measures in China

Mychonastes afer HSO-3-1 as a potential new source of biodiesel

<p>Abstract</p> <p>Background</p> <p>Biodiesel is considered to be a promising future substitute for fossil fuels, and microalgae are one source of biodiesel. The ratios of lipid, carbohydrates and proteins are different in different microalgal species, and finding a good strain for oil production remains a difficult prospect. Strains producing valuable co-products would improve the viability of biofuel production.</p> <p>Results</p> <p>In this study, we performed sequence analysis of the 18S rRNA gene and internal transcribed spacer (ITS) of an algal strain designated HSO-3-1, and found that it was closely related to the <it>Mychonastes afer </it>strain CCAP 260/6. Morphology and cellular structure observation also supported the identification of strain HSO-3-1 as <it>M. afer</it>. We also investigated the effects of nitrogen on the growth and lipid accumulation of the naturally occurring <it>M. afer </it>HSO-3-1, and its potential for biodiesel production. In total, 17 fatty acid methyl esters (FAMEs) were identified in <it>M. afer </it>HSO-3-1, using gas chromatography/mass spectrometry. The total lipid content of <it>M. afer </it>HSO-3-1 was 53.9% of the dry cell weight, and we also detected nervonic acid (C24:1), which has biomedical applications, making up 3.8% of total fatty acids. The highest biomass and lipid yields achieved were 3.29 g/l and 1.62 g/l, respectively, under optimized conditions.</p> <p>Conclusion</p> <p>The presence of octadecenoic and hexadecanoic acids as major components, with the presence of a high-value component, nervonic acid, renders <it>M. afer </it>HSO-3-1 biomass an economic feedstock for biodiesel production.</p

Will the Relaxation of COVID-19 Control Measures Have an Impact on the Chinese Internet-Using Public? Social Media-Based Topic and Sentiment Analysis

Objective: In December 2022, the Chinese government announced the further optimization of the implementation of the prevention and control measures of COVID-19. We aimed to assess internet-using public expression and sentiment toward COVID-19 in the relaxation of control measures in China.Methods: We used a user-simulation-like web crawler to collect raw data from Sina-Weibo and then processed the raw data, including the removal of punctuation, stop words, and text segmentation. After performing the above processes, we analyzed the data in two aspects. Firstly, we used the Latent Dirichlet Allocation (LDA) model to analyze the text data and extract the theme. After that, we used sentiment analysis to reveal the sentiment trend and the geographical spatial sentiment distribution.Results: A total of five topics were extracted according to the LDA model, namely, Complete liberalization, Resource supply, Symptom, Knowledge, and Emotional Outlet. Furthermore, sentiment analysis indicates that while the percentages of positive and negative microblogs fluctuate over time, the overall quantity of positive microblogs exceeds that of negative ones. Meanwhile, the geographical dispersion of public sentiment on internet usage exhibits significant regional variations and is subject to multifarious factors such as economic conditions and demographic characteristics.Conclusion: In the face of the relaxation of COVID-19 control measures, although concerns arise among people, they continue to encourage and support each other