Study on a new green phosphor Ca12Al14O32Cl2: Tb3þ derived from Tb-doped Ca-Al layered double hydroxide

Yufeng Chen,Xiaoqing Wang,Yao Bao 한국물리학회 2017 Current Applied Physics Vol.17 No.1

A new green phosphor Ca12Al14O32Cl2: Tb3þ derived from Tb-doped Ca-Al layered double hydroxide (Tbdoped CaAl-LDH) was prepared through phase transition route. The X-ray diffraction measurement results revealed that the Tb-doped CaAl-LDH transformed into Ca12Al14O32Cl2:Tb3þ phase at 600 『C. With temperature varying from 600, 800e1000 『C, the crystallinity of the Ca12Al14O32Cl2:Tb3þ phase gradually improved. Compositional analyses suggested the chemical formula of the Ca12Al14O32Cl2:Tb3þ phase estimated to be Ca12Al13.52Tb0.48O32Cl2. The Ca12Al13.52Tb0.48O32Cl2 phase can be efficiently excited by near ultraviolet light and show strong green emissions attributed to 5D4/7FJ (J ¼ 5, 6) transition of Tb3þ. The present Ca12Al13.52Tb0.48O32Cl2 may be a promising candidate for green phosphor applied in LED.

Load Allocation Strategy for Command and Control Networks based on Interdependence Strength

Bo Chen,Guimei Pang,Zhengtao Xiang,Hang Tao,Yufeng Chen 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9

Command and control networks(C2N) exhibit evident multi-network interdependencies owing to their complex hierarchical associations, interleaved communication links, and dynamic network changes. However, the existing command and control networks do not consider the effects of dependent nodes on the load distribution. Thus, we proposed a command and control networks load allocation strategy based on interdependence strength. First, a new measure of interdependence strength was proposed based on the edge betweenness, which was followed by proposing the inter-layer load allocation strategy based on the interdependence strength. Eventually, the simulation experiments of the aforementioned strategy were designed to analyze the network invulnerability with different initial load capacity parameters, allocation model parameters, and allocation strategies. The simulation indicates that the strategy proposed in this study improved the node survival rate of the interdependent command and control networks model and successfully prevented cascade failures.

Optimization of coagulation–flocculation process for papermaking-reconstituted tobacco slice wastewater treatment using response surface methodology

Yufeng Wang,Lihuan Mo,Kefu Chen,Jun Li,Jun Xu 한국공업화학회 2014 Journal of Industrial and Engineering Chemistry Vol.20 No.2

A coagulation–flocculation process was used to treat papermaking-reconstituted tobacco slicewastewater with polyaluminium chloride (PAC) as coagulant and a cationic polyacrylamide (CPAM)as flocculant. To maximize the reduction of chemical oxygen demand (COD) and color, the jar tests werecarried out in the experiments and response surface methodology (RSM) was applied to optimize theprocess. A central composite design, i.e., a standard approach in RSM, was used to evaluate the effectsand interactions of three factors, i.e. PAC dosage, CPAM dosage and pH on the treatment efficiency. Results revealed that the maximum reduction of COD and color could be achieved at an optimalconditions, i.e., PAC = 715 mg/L, CPAM = 4.8 mg/L and pH = 6.6, from which the reduction of COD andcolor were 67.8% and 77.7%, respectively. The study also showed that the regression equations could beused as the theoretical basis for coagulation–flocculation process of papermaking-reconstituted tobaccoslice wastewater. They will be very helpful to flexibly select the appropriate process parameters in theengineering applications

Composite large margin classifiers with latent subclasses for heterogeneous biomedical data

Chen, Guanhua,Liu, Yufeng,Shen, Dinggang,Kosorok, Michael R. Wiley Subscription Services, Inc., A Wiley Company 2016 Statistical analysis and data mining Vol.9 No.2

<P>High‐dimensional classification problems are prevalent in a wide range of modern scientific applications. Despite a large number of candidate classification techniques available to use, practitioners often face a dilemma of choosing between linear and general nonlinear classifiers. Specifically, simple linear classifiers have good interpretability, but may have limitations in handling data with complex structures. In contrast, general nonlinear classifiers are more flexible, but may lose interpretability and have higher tendency for overfitting. In this paper, we consider data with potential latent subgroups in the classes of interest. We propose a new method, namely the composite large margin (CLM) classifier, to address the issue of classification with latent subclasses. The CLM aims to find three linear functions simultaneously: one linear function to split the data into two parts, with each part being classified by a different linear classifier. Our method has comparable prediction accuracy to a general nonlinear classifier, and it maintains the interpretability of traditional linear classifiers. We demonstrate the competitive performance of the CLM through comparisons with several existing linear and nonlinear classifiers by Monte Carlo experiments. Analysis of the Alzheimer's disease classification problem using CLM not only provides a lower classification error in discriminating cases and controls, but also identifies subclasses in controls that are more likely to develop the disease in the future.</P>

Mercury speciation and its emissions from a 220MW pulverized coal-fired boiler power plant in flue gas

Yufeng Duan,Liguo Yang,Yiman Jiang,Xianghua Yang,Yuqun Zhuo,Lei Chen,Liang Zhang,Xuchang Xu 한국화학공학회 2007 Korean Journal of Chemical Engineering Vol.24 No.4

Performance evaluation and prediction of activated carbon for VOCs via experiments and LFER methods

Yufeng Zhao,Mengxi Zhang,Chen Yang,Ruyi Xiang,Xudong Yang,Longzhe Cui 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.116 No.-

Due to the diversity and fluidity of volatile organic compounds (VOCs), it is difficult to conduct experimentalstudies on activated carbon (AC) used to capture VOCs in industry. Therefore, predicting theadsorption capacity of AC for VOCs is of great significance for evaluating the adsorption performanceof AC and developing its promising applications. Herein, based on the experimental data of dynamicadsorption, the poly parameter linear free energy relationship (pp-LFER) model was developed to quantifythe interactions between VOCs and AC. Through the dynamic adsorption curves of 25 VOCs on a fixedbed packed with the AC, the partition coefficient (PC) and adsorption capacity (q) of AC for VOCs werecalculated, and the pp-LFER equations used to predict them were established. For the PC values, thepp-LFER model consists of the excess molar refractive index (E), molar polarizability (S), hydrogenbondacidity (A), and logarithmic hexadecane-air partition coefficient (L), and the R2 of it was 0.86. Forthe ln q values, the developed model can predict it in R2 of 0.83, and the increased adsorption capacitywas predominantly attributed to the dispersive interaction (lL). Finally, the internal and external validationresults confirmed that the developed models have reliability, robustness, and predictability.

CFD simulation of coal-water slurry flowing in horizontal pipelines

Liangyong Chen,Wenhao Pu,Changsui Zhao,Yufeng Duan 한국화학공학회 2009 Korean Journal of Chemical Engineering Vol.26 No.4

An Eulerian multiphase approach based on kinetic theory of granular flow was used to simulate flow of coal-water slurries (CWS) in horizontal pipelines. The RNG k-ε turbulent model was incorporated in the governing equation to model turbulent two-phase flow with strong particle-particle interactions. In this model, the coal particles with bimodal distribution were considered as two solid-phase components, and the moment exchange between solid and liquid as well as that between solid and solid were accounted for. The model was firstly validated with pressure gradient and concentration profile data from the open literature, and then validated with pressure gradient data of the authors’ experiments. The effects of influx velocity, total influx concentration and grain composition were numerically investigated, and the results have displayed some important slurry flow characteristics, such as constituent particle concentration distribution and velocity distribution as well as pressure gradients, which are very difficult to display in the experiments. The results suggest that both gravity difference between large and small particles and strong particleparticle interaction had significant effects on concentration distribution as well as velocity distribution.

Forensic biogeographical ancestry inference: recent insights and current trends

Wen Yufeng,Liu Jing,Su Yonglin,Chen Xiacan,Hou Yiping,Liao Linchuan,Wang Zheng 한국유전학회 2023 Genes & Genomics Vol.45 No.10

Background As a powerful complement to the paradigmatic DNA profiling strategy, biogeographical ancestry inference (BGAI) plays a significant part in human forensic investigation especially when a database hit or eyewitness testimony are not available. It indicates one’s biogeographical profile based on known population-specific genetic variations, and thus is crucial for guiding authority investigations to find unknown individuals. Forensic biogeographical ancestry testing exploits much of the recent advances in the understanding of human genomic variation and improving of molecular biology. Objective In this review, recent development of prospective ancestry informative markers (AIMs) and the statistical approaches of inferring biogeographic ancestry from AIMs are elucidated and discussed. Methods We highlight the research progress of three potential AIMs (i.e., single nucleotide polymorphisms, microhaplotypes, and Y or mtDNA uniparental markers) and discuss the prospects and challenges of two methods that are commonly used in BGAI. Conclusion While BGAI for forensic purposes has been thriving in recent years, important challenges, such as ethics and responsibilities, data completeness, and ununified standards for evaluation, remain for the use of biogeographical ancestry information in human forensic investigations. To address these issues and fully realize the value of BGAI in forensic investigation, efforts should be made not only by labs/institutions around the world independently, but also by inter-lab/institution collaborations.

FLOW MECHANISM AND EXPRIMENTAL STUDY OF COMMUTATING MEASUREMENTS IN BRANCHED-CHANNEL IN PUMPING STATION

BAOHUA CHEN,YUFENG CHANG,CHUNTIAN ZHOU 한국수자원학회 2005 한국수자원학회 학술대회 Vol.2005 No.1

Differential effects of type 1 diabetes mellitus and subsequent osteoblastic βcatenin activation on trabecular and cortical bone in a mouse model

Sixu Chen,Daocheng Liu,Sihao He,Lei Yang,Quanwei Bao,Hao Qin,Huayu Liu,Yufeng Zhao,Zhaowen Zong 생화학분자생물학회 2018 Experimental and molecular medicine Vol.50 No.-

Type 1 diabetes mellitus (T1DM) is a pathological condition associated with osteopenia. WNT/β-catenin signaling is implicated in this process. Trabecular and cortical bone respond differently to WNT/β-catenin signaling in healthy mice. We investigated whether this signaling has different effects on trabecular and cortical bone in T1DM. We first established a streptozotocin-induced T1DM mouse model and then constitutively activated β-catenin in osteoblasts in the setting of T1DM (T1-CA). The extent of bone loss was greater in trabecular bone than that in cortical bone in T1DM mice, and this difference was consistent with the reduction in the expression of β-catenin signaling in the two bone compartments. Further experiments demonstrated that in T1DM mice, trabecular bone showed lower levels of insulin-like growth factor-1 receptor (IGF-1R) than the levels in cortical bone, leading to lower WNT/β-catenin signaling activity through the inhibition of the IGF-1R/Akt/glycogen synthase kinase 3β (GSK3β) pathway. After β-catenin was activated in T1-CA mice, the bone mass and bone strength increased to substantially greater extents in trabecular bone than those in cortical bone. In addition, the cortical bone of the T1-CA mice displayed an unexpected increase in bone porosity, with increased bone resorption. The downregulated expression of WNT16 might be responsible for these cortical bone changes. In conclusion, we found that although the activation of WNT/ β-catenin signaling increased the trabecular bone mass and bone strength in T1DM mice, it also increased the cortical bone porosity, impairing the bone strength. These findings should be considered in the future treatment of T1DM-related osteopenia.