Adverse effect of DEHP exposure on the serum insulin level of Balb/c mice

Jing Wang,Jinquan Li,Kashif Rafiq Zahid,Kun Wang,Yan Qian,Ping Ma,Shumao Ding,Xu Yang,Xianliang Wang,Xianliang Wang,Xu Yang 대한독성 유전단백체 학회 2016 Molecular & cellular toxicology Vol.12 No.1

Di(2-ethylhexyl) phthalate (DEHP) is a common indoor pollutant in the world, which may cause lots of harmful effects in human including diabetes according to epidemiological studies. To explore the underlying role of DEHP in diabetes-like symptoms, Balb/c mice were chose to be the experimental animals in this paper. They were separated as eight groups as follows: (1) saline+normal diet (vehicle control), (2) 10 mg/kg.day DEHP+normal diet, (3) 50 mg/kg.day DEHP+normal diet, (4) 250 mg/kg.day DEHP+normal diet, (5) streptozotocin (STZ)+high fat diet (diabetes model), (6) 10 mg/kg.day DEHP+ STZ+high fat diet, (7) 50 mg/kg.day DEHP+STZ +high fat diet, (8) 250 mg/kg.day DEHP+STZ+high fat diet. The biomarkers of this experiment include four groups: (1) general indicates: body weight and drinking water, (2) blood biomarkers: serum insulin and fasting glucose, (3) pathological examination: pancreas section and kidney section, and (4) biomarkers of oxidative stress: reactive oxygen species (ROS) and malondialdehyde (MDA) in liver cells. Our study results demonstrate that: (1) at our treatment levels DEHP cannot directly induce diabetes, but reduce serum insulin level in DEHP-exposed non-STZ-treated animals, (2) pathological examination finds that these is a dose-dependent damage in the pancreas in DEHP- exposed STZ-treated groups, and (3) the oxidative mechanism may be involved in this pathological process.

A Model Stacking Algorithm for Indoor Positioning System using WiFi Fingerprinting

JinQuan Wang,YiJun Wang,GuangWen Liu,GuiFen Chen 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.4

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

Nanostructured gold films for SERS by block copolymer-templated galvanic displacement reactions.

Wang, Yong,Becker, Michael,Wang, Li,Liu, Jinquan,Scholz, Roland,Peng, Juan,Gö,sele, Ulrich,Christiansen, Silke,Kim, Dong Ha,Steinhart, Martin American Chemical Society 2009 Nano letters Vol.9 No.6

<P>Up to now, little effort has been made to exploit large-area high-throughput patterning by block copolymer (BCP) lithography to generate nanostructured substrates with periods well below 100 nm for surface-enhanced Raman scattering (SERS). We show that simple BCP-templated galvanic displacement reactions yield dense arrays of mushroom-shaped gold nanopillars with a period of 50 nm. The nanoporous BCP films used as templates were obtained by swelling-induced reconstruction of reverse micelle monolayers deposited on silicon wafers. Coupling of adjacent mushroom caps almost impinging on each other combined with their strong local curvature results in a high spatial density of hot spots in the narrow gaps between them. Thus, substrates characterized by high SERS efficiencies are obtained.</P>

SNP Discovery from Transcriptome of Cashmere Goat Skin

Wang, Lele,Zhang, Yanjun,Zhao, Meng,Wang, Ruijun,Su, Rui,Li, Jinquan Asian Australasian Association of Animal Productio 2015 Animal Bioscience Vol.28 No.9

The goat Capra hircus is one of several economically important livestock in China. Advances in molecular genetics have led to the identification of several single nucleotide variation markers associated with genes affecting economic traits. Validation of single nucleotide variations in a whole-transcriptome sequencing is critical for understanding the information of molecular genetics. In this paper, we aim to develop a large amount of convinced single nucleotide polymorphisms (SNPs) for Cashmere goat through transcriptome sequencing. In this study, the transcriptomes of Cashmere goat skin at four stages were measured using RNA-sequencing and 90% to 92% unique-mapped-reads were obtained from total-mapped-reads. A total of 56,231 putative SNPs distributed among 10,057 genes were identified. The average minor allele frequency of total SNPs was 18%. GO and KEGG pathway analysis were conducted to analyze the genes containing SNPs. Our follow up biological validation revealed that 64% of SNPs were true SNPs. Our results show that RNA-sequencing is a fast and efficient method for identification of a large number of SNPs. This work provides significant genetic resources for further research on Cashmere goats, especially for the high density linkage map construction and genome-wide association studies.

SNP Discovery from Transcriptome of Cashmere Goat Skin

Lele Wang,Yanjun Zhang,Meng Zhao,Ruijun Wang,Rui Su,Jinquan Li 아세아·태평양축산학회 2015 Animal Bioscience Vol.28 No.9

The goat Capra hircus is one of several economically important livestock in China. Advances in molecular genetics have led to the identification of several single nucleotide variation markers associated with genes affecting economic traits. Validation of single nucleotide variations in a whole-transcriptome sequencing is critical for understanding the information of molecular genetics. In this paper, we aim to develop a large amount of convinced single nucleotide polymorphisms (SNPs) for Cashmere goat through transcriptome sequencing. In this study, the transcriptomes of Cashmere goat skin at four stages were measured using RNA-sequencing and 90% to 92% unique-mapped-reads were obtained from total-mapped-reads. A total of 56,231 putative SNPs distributed among 10,057 genes were identified. The average minor allele frequency of total SNPs was 18%. GO and KEGG pathway analysis were conducted to analyze the genes containing SNPs. Our follow up biological validation revealed that 64% of SNPs were true SNPs. Our results show that RNA-sequencing is a fast and efficient method for identification of a large number of SNPs. This work provides significant genetic resources for further research on Cashmere goats, especially for the high density linkage map construction and genome-wide association studies.

Expression of fox-related genes in the skin follicles of Inner Mongolia cashmere goat

Wenjing Han,Xiaoyan Li,Lele Wang,Honghao Wang,Kun Yang,Zhixin Wang,Ruijun Wang,Rui Su,Zhihong Liu,Yanhong Zhao,Yanjun Zhang,Jinquan Li 아세아·태평양축산학회 2018 Animal Bioscience Vol.31 No.3

Objective: This study investigated the expression of genes in cashmere goats at different periods of their fetal development. Methods: Bioinformatics analysis was used to evaluate data obtained by transcriptome sequencing of fetus skin samples collected from Inner Mongolia cashmere goats on days 45, 55, and 65 of fetal age. Results: We found that FoxN1, FoxE1, and FoxI3 genes of the Fox gene family were probably involved in the growth and development of the follicle and the formation of hair, which is consistent with previous findings. Real-time quantitative polymerase chain reaction detecting system and Western blot analysis were employed to study the relative differentially expressed genes FoxN1, FoxE1, and FoxI3 in the body skin of cashmere goat fetuses and adult individuals. Conclusion: This study provided new fundamental information for further investigation of the genes related to follicle development and exploration of their roles in hair follicle initiation, growth, and development.

Design and Experiment of an Automatic Temperature Control Device of Composite Shape-Stabilized Phase Change Material for Concrete Box Bridges

Zhen Wang,Jianting Zhou,Leng Liao,Jinquan Zhang,Huabin Zhang 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.2

To solve the problem of bridge surface cracking caused by an uneven temperature field inside and outside the web of a concrete box structure, an automatic temperature control device applied to the beam surface of a concrete box bridge in the daytime is developed. The device, hanging on the surface of the box girder webs, consists of a radiation cooling coating and a composite shape-stabilized phase change material. With reference to a bridge in Guizhou Province, finite element analysis, short-term temperature monitoring and temperature-drop monitoring are carried out using the device. The result shows that the automatic temperature control device works well continuously. For a box girder without an automatic temperature control device, the inside and outside of the web demonstrate different sensitivities to the temperature of the external environment, with a high temperature fluctuation and a relatively high temperature stress. For a box girder with an automatic temperature control device, as the cooling coating reflects part of the solar radiation and the phase transformation of the composite shape-stabilized phase change material releases or absorbs part of the latent heat to or from the external environment, the temperature fluctuation and temperature stress of the inside and outside of the web are relatively small. When the temperature suddenly drops, the automatic temperature control device works better than under conventional weather conditions because it can reduce the external temperature by approximately 50% on the outer surface of the box girder webs.

Analysis of Operation Characteristics of a Diesel Generator Set with Constant‑Power Pulsed Load

Meng Shi,Puyu Wang,Jinquan Wang,Haichao Li,Ye Xu,Kefeng Huang,Jianke Li 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.6

To improve the power quality of a diesel generator set with a pulsed load in a microgrid, this paper studied the operation characteristics of the system and proposed pulsed load conditions for an actual project based on test data. For a low average pulse power and a high peak power, a new mathematical model of the pulsed load in diferent operation modes was proposed. Then, a simulation model of the microgrid was established in MATLAB/Simulink, and the operation of the system was studied considering changes in various pulsed load parameters (the peak power Pk, output duty cycle D and switching period Ts). It was verifed by tests that the simulation model is efective and can refect the operation of the system. Based on the simulation model, the operation characteristics of the system with a bivariate pulsed load were studied, and qualifcation conditions for the diesel generator set in an actual project were proposed.

A GA-Based Neural Fuzzy System for Modeling a Paper Mill Wastewater Treatment Process

Huang, Mingzhi,Wan, Jinquan,Ma, Yongwen,Zhang, Huiping,Wang, Yan,Wei, Chaohai,Liu, Hongbin,Yoo, ChangKyoo American Chemical Society 2011 INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH - Vol.50 No.23

<P>A genetic algorithm-based neural fuzzy system (GA-NFS) was presented for studying the coagulation process of wastewater treatment in a paper mill. In order to adapt the system to a variety of operating conditions and acquire a more flexible learning ability, the GA-NFS was employed to model the nonlinear relationships between the effluent concentration of pollutants and the chemical dosages, and a hybrid learning algorithm divided into two stages was proposed for parameters learning. During the first learning stage, a genetic algorithm was used to optimize the structure of GA-NFS and the membership function of each fuzzy term due to its capability of parallel and global search. On the basis of an optimized training stage, the back-propagation algorithm (BP algorithm) was chosen to update the parameters of GA-NFS to improve the system precision. The GA-NFS proves to be very effective in modeling coagulation perform and performs better than adaptive-network-based fuzzy inference system (ANFIS). RMSE, MAPE, and <I>R</I> between the predicted and observed values for GA-NFS were only 0.01099, 2.3337, and 0.9375, respectively.</P>

Modeling of a paper-making wastewater treatment process using a fuzzy neural network

Mingzhi Huang,유창규,Jinquan Wan,Yan Wang,Yongwen Ma,Huiping Zhang,류홍빈,Zhanzhan Hu 한국화학공학회 2012 Korean Journal of Chemical Engineering Vol.29 No.5

An intelligent system that includes a predictive model and a control was developed to predict and control the performance of a wastewater treatment plant. The predictive model was based on fuzzy C-means clustering, fuzzy inference and neural networks. Fuzzy C-means clustering was used to identify model’s architecture, extract and optimize fuzzy rule. When predicting, MAPE was 4.7582% and R was 0.8535. The simulative results indicate that the learning ability and generalization of the model was good, and it can achieve a good predication of effluent COD. The control model was based on a fuzzy neural network model, taking into account the difference between the predicted value of COD and the setpoint. When simulating, R was 0.9164, MAPE was 5.273%, and RMSE was 0.0808, which showed that the FNN control model can effectively change the additive dosages. The control of a paper-making wastewater treatment process in the laboratory using the developed predictive control model and MCGS (monitor and control generated system) software shows the dosage was computed accurately to make the effluent COD remained at the setpoint,when the influent COD value or inflow flowrate was changed. The results indicate that reasonable forecasting and control performances were achieved through the developed system; the maximum error was only 3.67%, and the average relative error was 2%.