Some Observations of the Influence Factors on the Response of Pile Groups

Qian-qing Zhang,Shi-min Zhang,Fayun Liang,Qian Zhang,Fei Xu 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.6

A simplified approach for nonlinear analysis of the load-displacement response of pile groups embedded in multilayered soils is presented in this work. A hyperbolic model is used to capture the relationship between unit skin friction and pile-soil relative displacement developed along the pile-soil interface and the stress-displacement relationship developed at the pile end. Considering interactive effect among piles, the parameters related to the hyperbolic model of an individual pile in a group can be computed. As to the analysis of the response of pile groups, a highly effective iterative computer program is developed using the hyperbolic model of an individual pile in a group. The efficiency and accuracy of the present method is verified using a well-documented field test. Furthermore, a parametric study is conducted to capture the influence of pile spacing and number of piles on the load-settlement response of the pile groups connected to a rigid cap. The pile-group settlement ratio and the pile-group resistance ratio are analyzed to assess the interaction effect among individual piles.

How the International Cooperation in “Sci-tech +Industry” Model Working in Developing Mango as “One Village and One Product”: Citing the Industrial Upgrading Experience in Baihua Village as An Example

Yanxiu Zuo(Yanxiu Zuo),Junxiang Qian(Junxiang Qian),Lichi Li(Lichi Li),Zhangguan Ni(Zhangguan Ni),Jun Wu(Jun Wu),Huiyun Zhang(Huiyun Zhang),Yufu Chen(Yufu Chen),Huiyun Zhang(Huiyun Zhang),Li Yao(Yao L 아시아사회과학학회 2022 Jornal of Asia Social Science Vol.9 No.1

Baihua Village is a typical mountainous village in the southwest part of Lujiang county, Longyang District, Baoshan City, Yunnan Province. Residents there made a living on the land, including growing sugarcane and planting maize, whose annual income was no more than 2000 yuan before 2006. Since then when a research institute has set it as one of the pilot villages for mango growing impetus with sci-tech. For the sake of “One village and One Product”, mango breeding and relevant techniques have been applied to daily work. Within years, the developed model of has been explored: simply “villages are the main carriers facilitated by the specialized cooperative for mango growing, back-up by science and technology. Technical trainings serve as the driving force for the leading growers, meanwhile, sellers work as the bridge link the producing-end and the markets”.

Hybrid Model for Renewable Energy and Load Forecasting Based on Data Mining and EWT

Zhang Jinjin,Zhang Qian,Li Guoli,Wu Junjie,Wang Can,Li Zhi 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.3

Accurate renewable resource (RES) and load prediction play key roles in the power grid planning schemes, eff ective dispatch, and stable operation of power systems. The proportions of wind and solar energy continue to increase, leading to wind and light abandonment. Thus, the absorption of wind and photovoltaic power is particularly important. On the basis of accurately predicting load, wind power and photovoltaic output, the accommodation capacity of wind and photovoltaic power is analyzed. The work contains fi ve parts, as follows: (1) empirical wavelet transform (EWT) is used to decompose wind power and load. At the same time, isolated forest (iForest) and fuzzy C-means clustering (FCM) are used to process photovoltaic data. (2) Low frequency and intermediate frequency components of load are predicted by improved random forest (IRF). High frequency component of load is clustered by improved density-based spatial clustering of applications with noise (IDBSCAN). The processing model is selected on the basis of the characteristics of each class sample. Each component of wind power are predicted by IRF. (3) Photovoltaic power of each category is predicted by IRF. (4) Diff erent components of load and wind power data are added. The photovoltaic power forecast data are synthesized according to the time point. (5) The forecast value of load, wind power, and photovoltaic output of a city are comprehensively evaluated by the summarized prediction level indicators. Three accommodation indicators are used for analyzing the accommodation capacity of wind power and photovoltaic. Results show that the forecasting methods of load, wind power, and photovoltaic power can generate better forecasting results than conventional methods. The analysis results of supplementary prediction level and accommodation indices provide reference for eff ective grid dispatching, sustainable, and healthy energy development.

Short‑Term Load Forecasting Method Based on EWT and IDBSCAN

Qian Zhang,Jinjin Zhang 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.2

Accurate load forecasting is of great signifcance to the safety and stability of power grid operation. This paper proposes a combined prediction method based on empirical wavelet transform (EWT) and improved density-based spatial clustering of applications with noise (IDBSCAN). The EWT is used to decompose the load to obtain various intrinsic mode functions (IMFs). Then, each IMF is predicted with a rational method. The low frequency and intermediate frequency components are predicted by long short-term memory (LSTM). High frequency components have uncertain characteristics. Therefore, they are clustered by IDBSCAN, according to meteorological factors. The processing model is selected based on the characteristics of each class sample. Finally, the prediction results of each component are superimposed to obtain the total prediction result. Experiments are conducted based on the measured load data of a Chinese city. A comparison between the proposed method, EWT–LSTM, EWT-Elman, and empirical mode decomposition (EMD)-LSTM is made. The results indicate that the proposed method has higher prediction accuracy and refects the randomness of the actual load.

18. Effects of sulfur starvation on nitrogen assimilation in Bassica napus

Qian Zhang,Sang-Hyun Park,Sowbiya Muneer,Bok-Rye Lee,Tae Hwan Kim 한국초지조사료학회 2012 한국초지조사료학회 학술대회논문집 Vol.2012 No.09

The catalytic core of DEMETER guides active DNA demethylation in <i>Arabidopsis</i>

Zhang, Changqing,Hung, Yu-Hung,Rim, Hyun Jung,Zhang, Dapeng,Frost, Jennifer M.,Shin, Hosub,Jang, Hosung,Liu, Fang,Xiao, Wenyan,Iyer, Lakshminarayan M.,Aravind, L.,Zhang, Xiang-Qian,Fischer, Robert L. National Academy of Sciences 2019 PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF Vol.116 No.35

<P><B>Significance</B></P><P>Flowering plants reproduce via a unique double-fertilization event, producing the zygote and the nutritive endosperm. The genome of the central cell, the precursor of the endosperm, undergoes extensive demethylation prior to fertilization. This epigenetic reconfiguration, directed by the DEMETER (DME) glycosylase at thousands of loci in <I>Arabidopsis</I>, differentiates the epigenetic landscapes of parental genomes and establishes parent of origin-specific expression of many imprinted genes in endosperm essential for seed development. However, how DME is targeted to various locations remains unknown. Here we show that the multidomain DME is organized into 2 functional regions: the C-terminal region, which guides localization and catalysis, and the N-terminal region, which likely recruits chromatin remodelers to facilitate demethylation within heterochromatin.</P><P>The <I>Arabidopsis</I> DEMETER (DME) DNA glycosylase demethylates the maternal genome in the central cell prior to fertilization and is essential for seed viability. DME preferentially targets small transposons that flank coding genes, influencing their expression and initiating plant gene imprinting. DME also targets intergenic and heterochromatic regions, but how it is recruited to these differing chromatin landscapes is unknown. The C-terminal half of DME consists of 3 conserved regions required for catalysis in vitro. We show that this catalytic core guides active demethylation at endogenous targets, rescuing <I>dme</I> developmental and genomic hypermethylation phenotypes. However, without the N terminus, heterochromatin demethylation is significantly impeded, and abundant CG-methylated genic sequences are ectopically demethylated. Comparative analysis revealed that the conserved DME N-terminal domains are present only in flowering plants, whereas the domain architecture of DME-like proteins in nonvascular plants mainly resembles the catalytic core, suggesting that it might represent the ancestral form of the 5mC DNA glycosylase found in plant lineages. We propose a bipartite model for DME protein action and suggest that the DME N terminus was acquired late during land plant evolution to improve specificity and facilitate demethylation at heterochromatin targets.</P>

Brain atlas fusion from high-thickness diagnostic magnetic resonance images by learning-based super-resolution

Zhang, Jinpeng,Zhang, Lichi,Xiang, Lei,Shao, Yeqin,Wu, Guorong,Zhou, Xiaodong,Shen, Dinggang,Wang, Qian Elsevier 2017 Pattern recognition Vol.63 No.-

<P><B>Abstract</B></P> <P>It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We fuse the brain atlas from real diagnostic MR images with high inter-slice thickness. </LI> <LI> All images are processed through the two-stage learning-based super-resolution. </LI> <LI> Groupwise registration is applied for unbiased atlas fusion. </LI> </UL> </P>

ROCK1 induces dopaminergic nerve cell apoptosis via the activation of Drp1-mediated aberrant mitochondrial fission in Parkinson’s disease

Qian Zhang,Changpeng Hu,Jingbin Huang,Wuyi Liu,Wenjing Lai,Faning Leng,Qin Tang,Yali Liu,Qing Wang,Min Zhou,Fangfang Sheng,Guobing Li,Rong Zhang 생화학분자생물학회 2019 Experimental and molecular medicine Vol.51 No.-

Dopamine deficiency is mainly caused by apoptosis of dopaminergic nerve cells in the substantia nigra of themidbrain and the striatum and is an important pathologic basis of Parkinson’s disease (PD). Recent research has shownthat dynamin-related protein 1 (Drp1)-mediated aberrant mitochondrial fission plays a crucial role in dopaminergicnerve cell apoptosis. However, the upstream regulatory mechanism remains unclear. Our study showed that Drp1knockdown inhibited aberrant mitochondrial fission and apoptosis. Importantly, we found that ROCK1 was activated inan MPP+-induced PD cell model and that ROCK1 knockdown and the specific ROCK1 activation inhibitor Y-27632blocked Drp1-mediated aberrant mitochondrial fission and apoptosis of dopaminergic nerve cells by suppressing Drp1dephosphorylation/activation. Our in vivo study confirmed that Y-27632 significantly improved symptoms in a PDmouse model by inhibiting Drp1-mediated aberrant mitochondrial fission and apoptosis. Collectively, our findingssuggest an important molecular mechanism of PD pathogenesis involving ROCK1-regulated dopaminergic nerve cellapoptosis via the activation of Drp1-induced aberrant mitochondrial fission.

12. Sulfur Deprivation Affects Sulfate and Nitrate Assimilation in Brassica napus L.

Qian Zhang,Bok-Rye Lee,Sang-Hyun Park,Tae Hwan Kim 한국초지조사료학회 2013 한국초지조사료학회 학술대회논문집 Vol.2013 No.09

The four models for forecasting the peak period of Dendrolimus punctatus (Lepidoptera: Lasiocampiade) for the second generation egg

Zhang Nan,Qian Guangjing,Zhang Lin,Song Xueyu,Zou Yunding,Bi Shoudong 한국곤충학회 2021 Entomological Research Vol.51 No.7

To improve the accuracy of forecasting the peak period of Dendrolimus punctatus, stationary time series, periodic distance method, stepwise regression model and the Bayes discriminant analysis were used. RSME value, kappa coefficient and accuracy were used as evaluation criteria to predict the peak period for the second generation egg of D. punctatus with over 33 years from 1983 to 2016 in Qianshan County, Anhui Province. The predictions of these models were verified in 2017 and 2018. The prediction of the stationary time model and Bayes discriminant analysis for 2017 was one level lower than the actual result and for 2018 was one level higher than the actual result, while the prediction of the periodic distance method was identical to the actual result for 2017 and greatly different from the actual result for 2018. The accuracy for stationary time series (RMSE = 0.92 kappa = 0.76) and periodic distance method (RMSE = 2.96, kappa = 0.81) from 1983 to 2018 were 87.88% and 85.71%, respectively. When taking into consideration the standard error was based on differential, the accuracy for the prediction of stepwise regression model (RMSE = 0.25, kappa = 1.00) from 1983 to 2018 was 100%. The accuracy of Bayes discriminant method (RMSE = 0.71, kappa = 0.96) was 97.14%. Comparatively speaking, the stepwise regression model and Bayes discriminant analysis method were better than the stationary time series and periodic distance method in RMSE value, kappa coefficient and accuracy. So they were relatively ideal forecast methods.