79 research outputs found

    The Poverty Alleviation Effect of Public Services and Social Development Opportunities

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    After 2020, the strategic focus of rural poverty reduction will shift from absolute poverty to relative poverty. How to accurately identify the root causes of rural relative poverty and alleviate the problem of rural relative poverty has become the key factor to realize rural revitalization. Using the binary logistic regression model and the comprehensive survey data of Chinese society, it is found that the lack of feasible ability of farmers has an obvious poverty effect. Among them, the lack of basic feasible ability such as physical health and mental health and feasible development ability such as education are important factors leading to farmers’ relative poverty; however, the poverty causing effect of farmers’ willingness to work is not obvious, and the state of relative poverty will stimulate farmers’ willingness to work to a certain extent; increasing the supply of basic public services in rural areas is an important way to alleviate rural relative poverty; increasing rural social development opportunities also has an important effect on poverty alleviation, which can significantly reduce the probability of farmers’ relative poverty

    Protective effect of theaflavins on neuron against 6-hydroxydopamine-induced apoptosis in SH-SY5Y cells

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    Theaflavins, the oxidation products of tea polyphenols are important biologically active components of black tea. 6-hydroxydopamine is a pro-parkinsonian neurotoxin. Theaflavins could inhibit the auto-oxidation of 6-hydroxydopamine in a dose-dependent manner from 0.5 µg/ml to 25 µg/ml. Here we investigated the protective effect of theaflavins on 6-hydroxydopamine induced SH-SY5Y cells against apoptosis (within this concentration range). It was found that pretreating SH-SY5Y cells with 0.5 µg/ml of theaflavins prevented 6-hydroxydopamine-induced loss of cell viability, condensed nuclear morphology, attenuated 6-hydroxydopamine-induced apoptosis, decrease of mitochondrial membrane potential and the increase of intracellular nitric oxide levels. Our results indicated that theaflavins had protective effect against 6-hydroxydopamine induced apoptosis at low concentrations, possibly through inhibition of reactive oxygen species and nitric oxide production

    Identification of Novel Variants of Metadherin in Breast Cancer

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    Metadherin (MTDH, also known as AEG-1, and Lyric) has been demonstrated to play a potential role in several significant aspects of tumor progression. It has been reported that overexpression of MTDH is associated with progression of disease and poorer prognosis in breast cancer. However, there are no studies to date assessing variants of the MTDH gene and their potential relationship with breast cancer susceptibility. Thus, we investigated all variants of the MTDH gene and explored the association of the variants with breast cancer development. Our cohort consisted of full-length gene sequencing of 108 breast cancer cases and 100 healthy controls; variants were detected in 11 breast cancer cases and 13 controls. Among the variants detected, 9 novel variants were discovered and 2 were found to be associated with the susceptibility of breast cancer. However, additional studies need to be conducted in larger sample sizes to validate these findings and to further investigate whether these variants are prognostic in breast cancer patients

    Robust Global Identification and Output Estimation for LPV Dual-Rate Systems Subjected to Random Output Time-Delays

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    Identification of lti time-delay systems with missing output data using GEM algorithm

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    This paper considers the parameter estimation for linear time-invariant (LTI) systems in an input-output setting with output error (OE) time-delay model structure. The problem of missing data is commonly experienced in industry due to irregular sampling, sensor failure, data deletion in data preprocessing, network transmission fault, and so forth; to deal with the identification of LTI systems with time-delay in incomplete-data problem, the generalized expectation-maximization (GEM) algorithm is adopted to estimate the model parameters and the time-delay simultaneously. Numerical examples are provided to demonstrate the effectiveness of the proposed method. © 2014 Xianqiang Yang and Hamid Reza Karimi

    Adaptively robust filtering with classified adaptive factors

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